A Linguistic Approach to the Study of Dyslexia 9781800415973

Table of contents :
Contents
Contributors
Introduction
Part 1: Psychological and Neurobiological Foundations of Language Skills in People with Dyslexia
1 The Neurobiological Basis of Language Skills and Dyslexia
2 Late Effects of Early Language Delay on Complex Language and Literacy Abilities: A Clinical Approach to Dyslexia in Subjects with a Previous Language Impairment
3 Foreign Language Learning Difficulties in Developmental Dyslexia: A Narrative Review of the Existing Evidence
Part 2: Theoretical and Experimental Linguistic Research on Dyslexia
4 Phonological and Lexical Effects on Reading in Dyslexia
5 Morphemes as Reading and Spelling Units in Developmental Dyslexia
6 Morphological Knowledge in Frenchspeaking Children with Dyslexia
7 Developmental Dyslexia and Morphosyntactic Competence in Italian Young Adults
8 Dyslexia and Syntactic Deficits: Overview and a Case Study of Language Training
9 The Impact of Dyslexia on Lexico-Semantic Abilities: An Overview
10 Dyslexia and Pragmatic Skills
Part 3: Applied Linguistic Research and Dyslexia
11 Visual and Auditory Stimuli for Teaching EFL Vocabulary to Learners with Dyslexia
12 Reading as a Multi- Layer Activity: Training Strategies at Text Level
13 Teaching Latin to Dyslexic Learners: A Methodological Proposal
14 Foreign Language Teacher Preparedness to Teach Learners with Dyslexia
Index

Citation preview

A Linguistic Approach to the Study of Dyslexia

COMMUNICATION DISORDERS ACROSS LANGUAGES Series Editors: Dr Nicole Müller, at University College Cork, Ireland and Dr Martin Ball, Bangor University, Wales. The discipline of communication disorders has made great strides over the last fifty years and more. We now know much more about the nature and causes of breakdowns in speech and language, both in adults and children. We know more about how to classify these breakdowns, how to describe and analyse pathological speech and language, and how to treat communication disorders. Unfortunately, a large proportion of this work is restricted to a small number of European languages; indeed, much of it is on and in English alone. Research in communication disorders in languages other than English has seen a marked increase in recent years, as has the investigation of such disorders in speakers of more than one language, and communities where bi- and multilingualism is the norm. This series serves to spotlight new and ongoing research in communication disorders across languages. We aim to do this by including studies of communication disorders (including assessment methods and guidelines for intervention) in particular multilingual communities, studies of the manifestations of specific types of disorder in a range of languages (particularly lesser researched languages), and of communication breakdown in bi- and multilingual speakers. Books in the series are used by practitioners, researchers and students, and they address a range of topics, including speech and language disorders in children, literacy, acquired speech and language disorders in adults, fluency, and voice. All books in this series are externally peer-reviewed. Full details of all the books in this series and of all our other publications can be found on http://www.multilingual-matters.com, or by writing to Multilingual Matters, St Nicholas House, 31-34 High Street, Bristol, BS1 2AW, UK.

COMMUNICATION DISORDERS ACROSS LANGUAGES: 20

A Linguistic Approach to the Study of Dyslexia Edited by Gloria Cappelli and Sabrina Noccetti

MULTILINGUAL MATTERS Bristol • Jackson

DOI https://doi.org/10.21832/CAPPEL5966 Library of Congress Cataloging in Publication Data A catalog record for this book is available from the Library of Congress. Names: Cappelli, Gloria, editor. | Noccetti, Sabrina, editor. Title: A Linguistic Approach to the Study of Dyslexia/Edited by Gloria Cappelli and Sabrina Noccetti. Description: Bristol, UK; Jackson, TN: Multilingual Matters, 2022. | Series: Communication Disorders Across Languages: 20 | Includes bibliographical references and index. | Summary: ‘This volume contributes to the growing body of research on developmental dyslexia, focusing on the behavioural manifestations of the disorder at different levels of the language system. It presents data from experimental and applied research and their applications in language teaching, rehabilitation of reading dysfunctions and teacher training’ – Provided by publisher. Identifiers: LCCN 2022017220 (print) | LCCN 2022017221 (ebook) | ISBN 9781800415966 (hardback) | ISBN 9781800415973 (pdf) | ISBN 9781800415980 (epub) Subjects: LCSH: Dyslexic children – Education. | Reading – Remedial teaching. | Contrastive linguistics. Classification: LCC LC4708 .L56 2022 (print) | LCC LC4708 (ebook) | DDC 371.91/44–dc23/eng/20220609 LC record available at https://lccn.loc.gov/2022017220 LC ebook record available at https://lccn.loc.gov/2022017221 British Library Cataloguing in Publication Data A catalogue entry for this book is available from the British Library. ISBN-13: 978-1-80041-596-6 (hbk) Multilingual Matters UK: St Nicholas House, 31-34 High Street, Bristol, BS1 2AW, UK. USA: Ingram, Jackson, TN, USA. Website: www.multilingual-matters.com Twitter: Multi_Ling_Mat Facebook: https://www.facebook.com/multilingualmatters Blog: www.channelviewpublications.wordpress.com Copyright © 2022 Gloria Cappelli, Sabrina Noccetti and the authors of individual chapters. All rights reserved. No part of this work may be reproduced in any form or by any means without permission in writing from the publisher. The policy of Multilingual Matters/Channel View Publications is to use papers that are natural, renewable and recyclable products, made from wood grown in sustainable forests. In the manufacturing process of our books, and to further support our policy, preference is given to printers that have FSC and PEFC Chain of Custody certification. The FSC and/or PEFC logos will appear on those books where full certification has been granted to the printer concerned. Typeset by Riverside Publishing Solutions. Printed and bound in the UK by the CPI Books Group Ltd.

Contents

Contributors

vii

Introduction Gloria Cappelli and Sabrina Noccetti

1

Part 1: Psychological and Neurobiological Foundations of Language Skills in People with Dyslexia 1 The Neurobiological Basis of Language Skills and Dyslexia Enrico Ghidoni

21

2 Late Effects of Early Language Delay on Complex Language and Literacy Abilities: A Clinical Approach to Dyslexia in Subjects with a Previous Language Impairment Claudia Casalini, Daniela Brizzolara, Anna Maria Chilosi, Filippo Gasperini and Chiara Pecini

66

3 Foreign Language Learning Difficulties in Developmental Dyslexia: A Narrative Review of the Existing Evidence Filippo Gasperini

87

Part 2: Theoretical and Experimental Linguistic Research on Dyslexia 4 Phonological and Lexical Effects on Reading in Dyslexia Marijan Palmović, Ana Matić Škorić, Mirta Zelenika Zeba and Melita Kovačević

109

5 Morphemes as Reading and Spelling Units in Developmental Dyslexia128 Cristina Burani 6 Morphological Knowledge in French-speaking Children with Dyslexia  Rachel Berthiaume, Amélie Bourcier and Daniel Daigle v

150

vi Contents

7 Developmental Dyslexia and Morphosyntactic Competence in Italian Young Adults Giovanna Marotta

165

8 Dyslexia and Syntactic Deficits: Overview and a Case Study of Language Training Anna Cardinaletti, Elisa Piccoli and Francesca Volpato

188

9 The Impact of Dyslexia on Lexico-Semantic Abilities: An Overview Gloria Cappelli

211

10 Dyslexia and Pragmatic Skills Gloria Cappelli, Sabrina Noccetti, Nicoletta Simi, Giorgio Arcara and Valentina Bambini

240

Part 3: Applied Linguistic Research and Dyslexia

11 Visual and Auditory Stimuli for Teaching EFL Vocabulary to Learners with Dyslexia Sabrina Noccetti

265

12 Reading as a Multi-Layer Activity: Training Strategies at Text Level  Francesca Santulli and Melissa Scagnelli

286

13 Teaching Latin to Dyslexic Learners: A Methodological Proposal305 Rossella Iovino 14 Foreign Language Teacher Preparedness to Teach Learners with Dyslexia  Joanna Nijakowska

321



338

Index

Contributors

Giorgio Arcara has a degree in psychology and a PhD in psychobiology. He is head of the Neurophysiology Laboratory at the San Camillo Hospital, Venice. His research focuses on language, communication, and their neural correlates, with the final aim of improving the assessment and rehabilitation of neurological patients. Valentina Bambini is Associate Professor of Linguistics at the University School for Advanced Studies IUSS Pavia, Italy. Her research interests are in the field of neurolinguistics, experimental pragmatics, clinical pragmatics and neuropragmatics and are organized in two main areas. The first revolves around the comprehension of metaphors and other implicit meanings in the brain. The second is pragmatic language disorder in adults with psychiatric or neurological diseases. In this field she has contributed novel tools for the assessment and training of pragmatic skills. She is co-founder of the Experimental Pragmatics in Italy (XPRAG.it) research network. Rachel Berthiaume holds a PhD in applied linguistics from the Université du Québec in Montréal (Canada). She has been a professor at the Faculty of Education of the Université de Montréal since 2009. Her research activities are mainly devoted to investigating the role of morphological processing in the acquisition of reading among students with and without learning disabilities. Her funded research projects have enabled her to study the development of morphological knowledge as well as educational environments that stimulate and structure such development. More recently, she has, with Daniel Daigle, co-edited a monograph, Morphological Processing and Literacy Development: Current Issues and Research (Routledge, 2018), in which findings from studies conducted on vocabulary, spelling, word recognition and reading comprehension from a morphological perspective are synthesized with the assistance of collaborators who have contributed greatly to this field of research. Amélie Bourcier holds a PhD in education from the Unversité de Montréal (Canada), where she is a lecturer. She is also a special education teacher vii

viii Contributors

who works with children, teenagers and adults with learning disabilities, mostly dyslexia. Her research interests are related to dyslexic students, on how they learn to read and on how teachers can effectively help them to succeed throughout their academic path. She is also interested in morphological awareness and how it can improve the reading abilities of dyslexic and non-dyslexic students. Daniela Brizzolara was a clinical psychologist for more than 40 years at the National Research Hospital of Developmental Neuroscience ‘IRCCS Stella Maris’ of Pisa, where she was head of the Developmental Neuropsychology Laboratory. Her research interests are in the field of neurodevelopmental disorders, in particular developmental language disorders and specific learning disabilities. The focus of her research is on the relationship between these two neurodevelopmental disorders and on the role of phonological working memory as the link between the two. She has coordinated many research projects of national interest and contributed to creating tests to measure working memory in clinical and experimental settings. She has authored numerous research papers in peer reviewed journals. She is co-editor (with Chiara Pecini) of Disturbi e traiettorie atipiche del neurosviluppo. Diagnosi e intervento (McGraw-Hill Education, 2020), a book covering many neurodevelopmental disorders, both from a clinical and a neurofunctional perspective.   Cristina Burani has been Director of Research at the Institute for Cognitive Sciences and Technologies (ISTC), CNR, Rome, Italy. She has conducted research in experimental psycholinguistics and the neuropsychology of language, with main reference to lexical processing, reading aloud, and developmental and acquired dyslexia. She is the author of several publications in international refereed journals. She has taught psycholinguistics at the University of Trieste and had appointments in PhD programs in neuropsychology, cognitive neurosciences, developmental and clinical psychology, and experimental psychology, at the universities of Rome-La Sapienza and Trieste, in the framework of national and European community grants. Gloria Cappelli, PhD, is Associate Professor of English Language and Linguistics at the University of Pisa. Her research focuses on semantics and pragmatics, English for Specific Purposes and multimodal discourse, and second and foreign language acquisition in learners with and without dyslexia. She has published in national and international journals and in edited volumes and has authored and edited books on English verbs of cognitive attitude, lexical semantics and tourism communication (‘I reckon I know how Leonardo da Vinci must have felt’: Epistemicity, Evidentiality and English Verbs of Cognitive

Contributors ix

Attitude, Pari Publishing, 2007). She is a member of the Italian Association of English Studies and of the European Society for the Study of English. Anna Cardinaletti is a Professor of Linguistics at Ca’ Foscari University of Venice, where she teaches applied linguistics, clinical linguistics and Italian linguistics. She received her PhD in 1990 at the University of Padua and has published extensively on theoretical and experimental linguistics. Her research interests include theoretical comparative syntax and typical and atypical language acquisition, in particular in cases of deafness and learning difficulties. She has coordinated national and international projects on sign languages, deafness, and inclusive education, and is one of the founders of the University spin-off VEASYT and the Director of the Venice Accessibility Lab. Claudia Casalini is a clinical psychologist at the National Research Hospital of Developmental Neuroscience, IRCCS Stella Maris Foundation of Pisa. Her research interests are in the field of typical and atypical development, neurofunctional correlates and neuropsychological underpinnings of cognitive functioning in children with developmental language disorders, specific learning disorders and other special educational needs. She has participated in numerous research projects and authored and co-authored numerous research papers in peer reviewed journals. She is an adjunct professor at the University of Pisa. Anna Maria Chilosi is a medical doctor and a PhD neurologist and psychiatrist at the Scientific Institute for Research Hospitalization and Health Care Stella Maris of Calambrone, Pisa. She has extensive expertise in the assessment, diagnosis and treatment of children with speech and oral and written language pathology. She has been a principal investigator of research projects supported by national and international institutions and author or co-author of more than 150 scientific papers, including 52 peer-reviewed papers, 23 books chapters and four books, with national and international publishers, including Disprassia verbale in età evolutiva. Inquadramento clinico, basi neurobiologiche e principi di trattamento (Erickson, 2020).   Daniel Daigle is a professor at the Faculty of Education of the Université de Montréal (Canada). He obtained a PhD in education from the Université de Montréal and has done postdoctoral studies in psycholinguistics at the Université de Strasbourg (France). His funded research focuses on the acquisition of reading and writing abilities in normally developing children and in children with reading and writing difficulties. This work has allowed him to develop training programs for teaching spelling and vocabulary and to describe and highlight teacher

x Contributors

best practices that have a real impact on student learning. He has authored and co-authored more than 60 publications, including books (most recently L’apprentissage de la lecture et de l’écriture: Décomposer les objets d’enseignement en microtâches pour les rendre accessibles à tous les élèves, Chenelière Education, 2021), book chapters, articles in peer-reviewed scientific journals, and articles published in professional journals. Filippo Gasperini, PhD, is a clinical psychologist at the National Research Hospital of Developmental Neuroscience IRCCS Stella Maris of Pisa, where he works in a multi-professional team specifically devoted to the diagnosis and intervention in children and adolescents with dyslexia and other specific learning disabilities. His research interests are in the field of typical and atypical development of reading, writing and mathematical skills, neurofunctional correlates and cognitive underpinnings of learning in children with dyslexia and other neurodevelopmental disorders. He has authored and co-authored numerous research papers in peer-reviewed journals. Enrico Ghidoni is a neurologist and expert in clinical neuropsychology and was head of the Clinical Neuropsychology, Cognitive Disorders and Adult Dyslexia Unit at Santa Maria Nuova Hospital in Reggio Emilia (Italy). He was one of the founding members of the Italian Dyslexia Association and coordinated several training projects on specific learning disorders for the Ministry of Education. He is a member of the SLDwork committee. He has published studies on adult dyslexia, and on other neuropsychological topics. He currently works at the Anemos Neuroscience Centre (Reggio Emilia), at the SOS-dyslexia diagnostic centres (Milan, Bologna) and at the San Sebastiano Foundation (Florence). He is also involved in a European project on dyslexia and work. He is a member of the Ministry of Education Technical Scientific Committee for SLD. Rossella Iovino teaches Latin and Italian Literature and Language in high school. In 2012 she obtained a PhD at the University Ca’ Foscari of Venice with a thesis on the syntax of Latin nominal expressions from both a synchronic and diachronic perspective. She has published numerous articles and book chapters devoted to the application of advances in theoretical linguistics to language teaching, as well as to the simplification of institutional language in medical and forensic settings. Melita Kovačević is a tenured professor at the Department of Speech and Language Pathology, Faculty of Education and Rehabilitation Sciences at the University of Zagreb. She teaches courses on language development,

Contributors xi

psycholinguistics, bilingualism and cognitive psychology at Bachelor, Masters and Doctoral level. Her scientific interests are psycholinguistic and neurolinguistic research, as well as some aspects of language pathology. She has held the position of Director of the Doctoral Programme in Language and Cognitive Neuroscience since 2003. Giovanna Marotta is Professor of General Linguistics and Phonetics and Phonology at the University of Pisa. Although her primary scientific interests concern the phonology of Italian and Latin, as well as the prosody of Romance varieties, she has also published many papers on semantics and the relation between language and cognition, with special regard to the categories that express spatial relations in natural languages. In more recent years, she has developed a strong interest in the pathologies of linguistic development, with particular regard to dyslexia. Ana Matić Škorić is a postdoctoral researcher at the Department of Speech and Language Pathology, Faculty of Education and Rehabilitation Sciences, University of Zagreb. She obtained a Master’s degree in speech and language pathology and a PhD in linguistics. Her main research interest is language processing in typical populations, and populations with developmental and acquired language disorders. In her experimental work she uses offline and online behavioural methods. She has published 17 scientific papers and five book chapters and has been involved in the development of screening and diagnostic tools for language disorders. Joanna Nijakowska is a university professor in the Centre for Foreign Language Teacher Training and European Education, University of Warsaw, Poland. A teacher trainer, a specialist in second/foreign language acquisition and didactics, psycholinguistics and learning difficulties, she runs teacher training courses and workshops for ELT students and practitioners. She has coordinated international projects and co-authored award-winning FL teacher training materials on inclusive instructional practices with learners with dyslexia. She has authored books (including Dyslexia in the Foreign Language Classroom, Multilingual Matters, 2010) and research papers on dyslexia, inclusive classroom practices, effectiveness of foreign language teacher training, and teachers’ needs, concerns, attitudes and self-efficacy beliefs about inclusive language teaching. Sabrina Noccetti is an Assistant Professor of English Language and Linguistics at the University of Pisa. She holds a PhD in morphology and psycholinguistics from the University of Vienna (Austria). She received her degree from Pisa University, where she has been

xii Contributors

teaching since 2000. She is the representative for her department in the disability and learning difficulties office of the University of Pisa. Her research focuses primarily on first language development, with particular reference to morphological acquisition in children and adult learners, and on second language learning, with special focus on pragmatic competence and lexical development, in adults with and without learning disorders. She is the author and co-author of books and papers published with international and national publishing houses, including Pre- and Protomorphology in Language Acquisition: An Italian Case Study (Plus, 2002) and E. Tribushinina, M.D. Voeikova and S. Noccetti (eds) Semantics and Morphology of Early Adjectives in First Language Acquisition (Cambridge Scholars Publishing, 2015). Marijan Palmović, PhD, is a professor at the Department of Speech and Language Pathology, Faculty of Education and Rehabilitation Sciences at the University of Zagreb, where he lectures in neurolinguistics, general linguistics and methodology. He has published two books, including Metodologija istraživanja dječjeg jezika (Naklada Slap, 2007) and more than 50 scientific papers in peer-reviewed journals and conference proceedings. He is mainly involved in experimental work in psycholinguistics and neurolinguistics, primarily tackling topics in phonology and morphology with an array of methods, including EEG/ ERP and eye-tracking.  Chiara Pecini is an Associate Professor of Developmental and Educational Psychology at the University of Florence. She was Clinical Psychologist Manager at the National Research Hospital of Developmental Neuroscience IRCCS Stella Maris from 2007 to 2018. Her main interests focus on a comparative approach to typical and atypical development, the neurofunctional correlates and cognitive underpinnings of learning and cognitive functioning in children with specific learning disorders and other special educational needs. Her research has also explored tele-rehabilitation procedures and educational robotics for cognitive empowerment in both typical and special needs children. She has given talks as an invited speaker at national and international conferences and has published extensively in peer-reviewed journals. Elisa Piccoli is a PhD student at Ca’ Foscari University of Venice. She is interested in syntax and language training. In her Master’s thesis, she analysed the syntactic competence of high school students with learning difficulties. She is currently investigating the comprehension and production of Italian oblique relative clauses by monolingual children, bilingual adults and individuals with learning difficulties.

Contributors xiii

Francesca Santulli is full Professor of Linguistics at Ca’ Foscari University of Venice. Her research has focused on various aspects of language and linguistics, ranging from the history of linguistics to philology, from phonetics to language contact. She has applied linguistic and rhetorical models of analysis to corpora of texts belonging to different genres, combining qualitative and quantitative methodologies. She has also investigated reading disabilities from the linguistic perspective, focusing on the fundamentals of reading, and she is developing a large interdisciplinary research project hinging on the improvement of reading strategies in both typical and dyslexic adults. Melissa Scagnelli is a psychologist, psychotherapist and research fellow at IULM University, Milan and a lecturer of Cognitive and Developmental Psychology at Ca’ Foscari University of Venice. Her research interests focus on autism and specific learning disorders in children and young adults. She has investigated reading disabilities and methods for the improvement of reading strategies in both neurotypical and dyslexic adults. She is also a trainer in educational organizations.  Nicoletta Simi is a postdoctoral research fellow in the Department of Psychology of the Univerity of Tuebingen in Germany. She holds a PhD in English linguistics from the University of Pisa. Her PhD research was centred on the study of reading comprehension processes in typically developed young adults and in young adults with dyslexia speaking English either as a first or a foreign language. This also included underlying general processes such as cognitive processing speed, working memory and the motivational/anxiety aspects of language use. Her most recent research tackles the ways in which conflicts of a linguistic nature get detected, monitored and adapted in L1 speakers of English and German, with special focus on lexical ambiguity, negation and world knowledge violations. Francesca Volpato is a Researcher in Linguistics at Ca’ Foscari University of Venice, where she received her PhD in 2010. She has investigated the linguistic competence of monolingual and bilingual children, adolescents, and adults with typical and atypical language development, focusing on the comprehension and production of syntactically complex sentences. She has contributed to the development of syntactic intervention approaches based on formal linguistics for individuals with hearing impairment or learning difficulties. She is the author of one book, Relative Clauses, Phi Features, and Memory Skills (Edizioni Ca’ Foscari, 2019) and many journal articles and has contributed to edited volumes. She coordinates the Laboratory of Linguistics for Deafness and Language Disorders at Ca’ Foscari.

xiv Contributors

Mirta Zelenika Zeba is a clinical psychologist at the Clinic for Rehabilitation of Hearing and Speech SUVAG and a research associate at the Faculty of Electrical Engineering and Computing, University of Zagreb. She has a Master’s degree in psychology and a PhD in cognitive sciences. She has published a number of scientific papers. She is involved in interdisciplinary research and development activities focused on research methodologies in psychological and electrophysiological measurements and the analysis of biomedical signals regarding mental fatigue, attention and learning.

Introduction Gloria Cappelli and Sabrina Noccetti

1 A Linguistic Approach to Dyslexia

The intention of this volume is to contribute to the growing body of research on developmental dyslexia, with particular attention given to its impact on the various components of the language system and on its development and functioning. With respect to existing books, it offers an attempt to delineate the linguistic and communicative profile of people with this specific learning disorder and observes it primarily from a behavioural perspective, assuming the vantage point of linguistics and linguistic research. The vast interdisciplinary research on dyslexia has greatly advanced our knowledge as to its cognitive and neural underpinnings. Over the past decade, however, a growing number of studies have appeared which have tried to correlate dyslexia with difficulties observed at various levels of the linguistic system (Adolf & Hogan, 2018). However, not many investigations have tackled how the differences and the deficits detected ultimately emerge in the linguistic behaviour of people with dyslexia and contribute to characterising their communicative profile. Moreover, problems with morphology, syntax, lexico-semantic and text-level processing have not traditionally been considered typical markers of dyslexia but only secondary characteristics stemming from the primary deficit. Maybe it is for this reason that research on the impairments associated with these aspects of language is relatively recent and scant. Yet, dyslexia manifests first and foremost in difficulties in manipulating language, and although it is usually detected at school-age, since the most severe issues are found in the acquisition of literacy, the first signs of atypical linguistic behaviour can sometimes be identified long before school-age and the start of oral language (Kuhl et al., 2020; Nicolson & Fawcett, 2019; Sanfilippo et al., 2020). Such signs can often go unnoticed, because, unless children present serious and evident linguistic disorders, when difficulties with the written language become noticeable, they will have already attained a good command of their native language and, therefore, it might be too late to trace the first signs of atypical language development. Identifying children at risk at a very young age is certainly challenging. For this reason, since we know that developmental 1

2  A Linguistic Approach to the Study of Dyslexia

dyslexia is a heritable condition, studies have been carried out in the last twenty years that have focused on children at genetic risk and have tried to verify whether markers of the disorder could be identified in the very early stages of language development (van Alphen et al., 2004). Unfortunately, they are seldom retrospective longitudinal studies (such as Torppa et al., 2010) and fail to control factors that may be relevant for language acquisition, such as child-directed speech (Ramírez-Esparza et al., 2014) and the role of reduced exposition to reading experience at a very young age. Nowadays, there is nonetheless large agreement that dyslexia is associated with a wider range of differences in linguistic abilities than just reading and phonological deficits, although such differences vary in their severity and distribution. Most practitioners dealing with this condition on a daily basis – be they teachers or clinicians – find themselves having to understand the difficulties experienced by their patients and learners and to intervene and manage deficits in their linguistic performance. For this reason, the contribution of linguistics to the scientific debate on these topics is crucial and this volume represents an attempt to bring together neuroscientific, psycholinguistic, experimental and linguistic research, both theoretical and applied. A word of caution is in order. In recent years, our knowledge of dyslexia, of the distinctive features of the individual learning disorders and of developmental language disorder, has greatly advanced. However, the same research has shown that defining the ‘boundaries’ of dyslexia and identifying its distinctive features is far from easy (Casalini et al., Chapter 2, this volume; Snowling, Hulme et al., 2020; Snowling, Hayiou-Thomas et al., 2020). Because the disorder rarely occurs in isolation and relies on a complex interplay of neurobiological, cognitive and environmental factors, it can assume many different manifestations besides the most obvious: reading difficulties. For this reason, some prefer talking of ‘dyslexias’ and the chapters included in the volume offer critical overviews of the possible effects of this condition at the various levels of the linguistic system without proposing simplistic generalisations. And, although research should aspire to reaching an increasingly deeper and more precise understanding of the features of dyslexia, including through finer profiling of the participants and their diagnoses in experimental studies, we believe that the results of recent linguistic research on dyslexia can greatly advance our ability to recognise and address the issues associated with it. 2 Developmental Dyslexia

Dyslexia is a developmental disorder, generally described as a deficit in the phonological component of the language, whose primary symptom is poor reading. It is deemed to be independent of intelligence, education and of the socio-economic status of the people affected by it.

Introduction 3

Since the majority of people with dyslexia present a phonological disorder, this is considered the most reliable marker of this condition (but see Ramus and Szenkovits (2008) for a different hypothesis on the matter). The phonological deficit is reported as a typifying feature in the definitions of dyslexia provided by the American and British dyslexia associations. For example, in the (2002) definition of the IDA (American International Dyslexia Association Board of Directors), the deficit is described as a ‘specific learning disability, neurological in origin, characterised by difficulties with accurate and/or fluent word recognition and by poor spelling and decoding abilities’. Likewise, Rose’s (2009: 30) definition, adopted by the British Dyslexia Association (BDA) mentions difficulties that ‘… primarily affect the skills involved in accurate and fluent word reading and spelling’ and states that ‘characteristic features of dyslexia are difficulties in phonological awareness, verbal memory and verbal processing speed’. The ‘phonological core deficit’ (Stanovich, 1986) is still generally referred to as the prominent cognitive impairment in dyslexia, even though very often in comorbidity with verbal working memory and verbal processing speed deficits. Whether phonological processing is impaired or simply inefficient, in most individuals with the disorder, dyslexia leads to the difficulties listed in the definitions (see Palmović et al., Chapter 4, this volume). As a consequence, they struggle to learn to read and write and remain slower and less accurate than age-matched controls (Reid, 2016). People with dyslexia may also display difficulties in counting the syllables of a word, tapping them, making rhymes, working with syllable onsets and rhymes, and repeating non-words. Nonetheless, dyslexia seldom manifests itself as a pure phono­ logical disorder. Indeed, it is often in comorbidity with other neurodevelopmental disorders, such as dyscalculia, dysgraphia, dysor­ thography, attention deficits and hyperactivity disorders (ADHD), and developmental coordination disorders (DCD). Sometimes it also co-occurs with emotional problems, such as anxiety and depression (Huang et al., 2020). As the comorbidities are more frequent than one could expect by chance, developmental dyslexia is better described as multidimensional (see Kormos & Smith, 2012; Moll et al., 2020; Morton & Frith, 1995; Nicolson & Fawcett, 2008) and requiring a multipledeficit approach (Pennington, 2006), which could help identify risk factors, interactions among co-occurring disorders, as well as the most common behavioural aspects (Moll et al., 2020). Wolf and Bowers (1999) proposed a ‘double deficit hypothesis’. The authors claim that, in people with dyslexia, a speed processing deficit may co-occur with the phonological deficit, which would result in greater difficulties in reading tasks. People with a double deficit are slower than controls to access and retrieve verbal labels, and the speed processing deficit manifests in slowed speed of naming. This in turn contributes

4  A Linguistic Approach to the Study of Dyslexia

to the reading problems. Moreover, when the speed processing deficit is present, it does not seem to be limited to the phonological component and naming speed, but there is evidence of diffuse difficulties (Nicolson & Fawcett, 2008). Other causes have been hypothesised for dyslexia. Goswami (2002, 2019) has proposed that a ‘speech rhythm deficit’ leads to difficulties in perceiving syllables boundaries. Consequently, the deficit may represent a big obstacle to language learning, because the ends of words carry important grammatical information. It is therefore also relevant for morphological and syntactic learning (Goswami, 2019), especially, but not exclusively, of inflectional languages. Recent studies on the benefits of rhythmic stimulation to increase dyslexic people’s sensitivity towards grammatical errors have provided support for this idea (Canette et al., 2020). Some accounts of dyslexia identify the main cause of the condition as sensorial processing impairments. For the ‘visuo-spatial attention deficit’ hypothesis (Facoetti et al., 2003), the reading problems experienced by people with the disorder depend on the difficulty in shifting the focus of attention from one location to another. The ‘magnocellular deficit’ hypothesis, however, posits that differences in the magnocellular pathways of people with dyslexia cause visual and auditory deficits and an abnormal eye movement while reading (Stein, 2001, 2019). Others have proposed that a complex interplay of sensory and cognitive deficits (e.g. inefficient executive functions; cf. Smith-Spark et al., 2016; Spencer et al., 2020) may play a crucial role in dyslexia, emerging in impaired visual attention (Facoetti et al., 2010) and result in reading comprehension difficulties in children with dyslexia (Taran et al., 2022). Others have proposed that the manifestations of dyslexia derive from an ‘automatization deficit’, which affects other components of the language system, besides the phonological level. Denckla and Rudel (1976) found correlations between reading and naming deficits. Their Rapid Automatized Naming test (RAN) has since been used to foster and automatise the disrupted verbal access and retrieval of children with dyslexia and specific learning impairment (see Cappelli, Chapter 9, this volume; Casalini et al., Chapter 2, this volume; Noccetti, Chapter 11, this volume; Pecini et al., 2018). Indeed, an automatisation, or procedural memory, disorder has been observed in some people with the condition, which can lead to a general learning problem affecting not only language but also motor skills and balance (Nicolson & Fawcett, 2008, 2019). Automatisation deficits severely impair language learning and force learners with the disorder to rely more on declarative than procedural memory. More recently, Nicolson & Fawcett (2019) have proposed a developmental account of dyslexia, showing that, during pre-reading years, dyslexic children exhibit a delay in building the neuronal networks underpinning reading activities.

Introduction 5

Research has detected important differences between the brains of people with and without developmental dyslexia. Such differences have been correlated to the symptoms manifested during reading, spelling and learning tasks (Ghidoni, Chapter 1, this volume; Habib, 2000; Ramus, 2004). Recently, genetic studies have also identified a group of genes that can be related to dyslexia, and which are involved in dysgenetic processes during gestation (Erbeli et al., 2022; Galaburda et al., 1989; Ghidoni, Chapter 1, this volume). The study of the interplay between genetics and environmental factors in reading, spelling and memory phenotypes has shown that environmental disadvantage can modulate the effects of genetic variants upon reading skills (Mascheretti et al., 2013). Among the environmental factors influencing the gene’s expression in the phenotype, Mascheretti et al. (2013) mention maternal smoking during pregnancy, birth weight, and familiar socioeconomic status (SES). They suggest that the great variability in the manifestations of dyslexia could be related to the interplay of genetic and environmental factors. The different outcomes in reading skills can be, therefore, variously connected to prenatal care, the quality and quantity of the interactions in familiar environments, and the availability of reading materials. For instance, children from high SES families are deemed as being exposed to qualitatively and quantitatively richer language, where they hear more words and syntactically complex sentences, more conversation-eliciting questions and more explicit information during mother–child interactions (Hart & Risley, 1995; Huttenlocher et al., 2010). Mascheretti et al. (2013) suggest that the great variability in the manifestations of dyslexia could be placed in relation to the interplay of genetic and environmental factors. Indeed, a shared view on dyslexia is yet to come, and the many studies that have appeared over the past few decades have reached contrasting conclusions on most of the issues tackled. Given the complex image of the condition arrived at by much interdisciplinary research, it seems in fact fair to assume that the differences evidenced in the studies on dyslexia reflect the expression of different phenotypes, which are the result of a complex interaction of genetic and biological conditions and environmental factors (Casalini et al., Chapter 2, this volume; Snowling & Melby-Lervåg, 2016). The great diversity observed in the communicative profile of people with dyslexia seems to reflect this intricate and complex interplay of many different aspects and suggests that the phonological core deficit and the ‘secondary markers’ should be rather interpreted as different manifestations of the disorder. In the next section, we attempt to offer an overview of the linguistic abilities of people with dyslexia as it emerges from the contributions included in the volume. 3 Linguistic Abilities and Dyslexia

A growing body of research has revealed that dyslexia appears to impact on various aspects of language development and linguistic

6  A Linguistic Approach to the Study of Dyslexia

competence. It is therefore our opinion that dyslexia also needs to be investigated from the point of view of linguistics, so as to contribute to a better delineation of the communicative profile of people impacted by this disorder. The linguistic perspective can also offer insights into the specific aspects of language that may be affected by developmental dyslexia, identify possible reasons for such difficulties and make predictions as to the path of linguistic development in this population. As already mentioned, great variability among people with dyslexia, including their linguistic behaviour, is to be expected. As a consequence, we are aware that no description of specific language difficulties, including those discussed in this volume, can be used to draw definite conclusions as to a distinctive communicative profile that would be applicable to all people with dyslexia. Indeed, language development and knowledge depend on variables such as the quantity and quality of social contacts and the input to which a person is exposed from infancy to adulthood, as well as reading experience and education. However, since linguistic competence plays a crucial role in the development of learning skills (Tallal et al., 1997), we believe that, in this population, the identification of difficulties at the various levels of the linguistic system is fundamental for educators, carers and clinicians alike. Educators can take advantage of research findings to plan teaching activities that may enhance learning and overcome the problems faced by their students with dyslexia. Research on linguistic competence has tackled various aspects of language (morphological, syntactic, lexical and pragmatic competence) and has involved people with dyslexia of different ages and native languages (Landerl et al., 2013; Moll et al., 2014; Perfetti & Harris, 2013). This implies that results would be better interpreted as dependent on the neurological maturity of the subjects investigated and on the specific features of the language involved. Some studies (Koster et al., 2005; McArthur et al., 2000; Rispens et al., 2004; Scarborough, 1990, 1991; van Alphen et al., 2004), for example, have highlighted a delayed development of (morpho)syntactic skills and vocabulary in pre-school children at genetic risk of dyslexia. Children with dyslexia have also been found to display difficulties in segmenting morphologically complex words and in detecting the base of plurimorphemic words (Casalis et al., 2004), with consequent difficulties in understanding their compositional meaning. This difficulty may prevent the understanding of novel complex words and, as a consequence, the comprehension of texts. Indeed, the most recent studies have started to take into account the role of morphotactic (and morphosemantic) transparency as facilitating factors in developing morphological awareness and reading comprehension (see Berthiaume et al., Chapter 6 and Burani, Chapter 5, this volume, for a review and discussion on this topic). These features, which are also proven to be a facilitating factor in the acquisition of native languages and in the presence of atypical language development (Diependaele et al., 2011;

Introduction 7

Dressler, 2003), are connected to universal preferences for morphological regularities and parallelism. They allow us to predict that, in the case of opacity and irregularities, more processing effort and difficulty will be experienced. Most studies about linguistic skills and dyslexia point to slower linguistic processing more than to actual deficits. Therefore, it can be expected that linguistic complexity (intended as morphological irregularities, opaque morphological word formation and inflectional processes) will be costly for people with dyslexia. Moreover, crosslinguistically and across age groups, the latter have been found to display problems with syntax and morphosyntactic agreement (Cardinaletti et al., Chapter 8, this volume), to be slower than controls in reacting to spoken sentence production task, and to produce less fluent, grammatical and complete sentences (Wiseheart & Altmann, 2018). These difficulties are evidenced also by electrophysiological studies. In an event-related potential (ERP) study by Rispens et al. (2006), Dutch adults with dyslexia were shown to react more slowly than controls in subject-verb agreement violations in spoken language (see also Cantiani et al., 2013). The ERP data also showed that subjects in the focus group did not have brain activation in the case of violation with NP plural, although they had recognised the syntactic violation in a previously submitted behavioural judgement test. The authors suggest that the lack of brain activation may depend on an extra processing load for plural NPs. Moreover, the study highlighted a delayed syntactic processing with respect to unimpaired controls. Similar experimental results were obtained by studies on word processing in subject, object and predicate position (Leikin, 2002) and in semantic tasks (Rasamimanana et al., 2020; Schulz et al., 2008). Weaknesses have also been reported in different areas of syntax. Issues have been observed in processing relative clauses (Cardinaletti & Volpato, 2015; Chan, 2014; Guasti et al., 2015; Marotta, Chapter 7, this volume), passive clauses (Cardinaletti & Volpato, 2015), clitic pronouns (Arosio et al., 2014, 2016; Avram et al., 2013; Casani, 2020; Chondrogianni et al., 2015; Vender et al., 2018), wh-questions (Guasti, 2013; Guasti et al., 2015) and negation (Vender & Delfitto, 2010). Most studies agree that children with dyslexia experience a delay in vocabulary learning when compared with their typically developing peers (Cappelli, Chapter 9, this volume; van Viersen et al., 2017, 2018) and have poor vocabulary skills when compared with age-matched controls (Cappelli, 2019; Łockiewicz et al., 2019; Swanson, 2012). The dyslexic population may therefore be characterized by a smaller vocabulary size than neurotypical peers. The difficulties experienced by people with dyslexia are interrelated and influence each other. Problems in word learning and retrieval have an impact on reading skills, which in turn benefit from rich and robust vocabulary. And, needless to say, vocabulary learning needs

8  A Linguistic Approach to the Study of Dyslexia

exposure to massive input gained through reading, social contacts and education. Indeed, vocabulary acquisition is supported by an efficient cognitive system allowing rapid phonological decoding, word retrieval and integration of lexico-semantic information. Therefore, deficits at one level hamper the normal process of linguistic development, with a cascading effect in several other domains. Thus, issues with the lexical and semantic domains can impact on reading comprehension, and communicative as well as narrative skills, especially when the latter is measured in terms of lexical diversity, productivity and grammaticality (Gagarina et al., 2012). People with dyslexia may also face difficulties in making inferences, in developing reading strategies (Cain & Oakhill, 2006), and in acquiring pragmatic skills to interpret non-literal meaning and humour (Cappelli et al., 2018; Cappelli et al., Chapter 10, this volume; Griffiths, 2007). These findings seem to indicate that the linguistic competence of people with dyslexia may be dependent on the cognitive load imposed by the processing of specific linguistic structures. If the processing requires the control of various components and the integration of information from multiple sources, then the processing becomes more costly, and an inefficient working memory system and automatisation processes cannot support it (Spencer et al., 2020). The effects of dyslexia emerge both in the written and in the oral language, as well as in non-native language acquisition (see Gasperini, Chapter 3, this volume; Noccetti, Chapter 11, this volume). Some accommodations and strategies may be necessary in the classroom to meet the needs of learners with this condition (see Iovino, Chapter 13, this volume; Noccetti, Chapter 11, this volume; Nijakowska, Chapter 14, this volume; Santulli & Scagnelli, Chapter 12, this volume) and facilitate learning. We believe that, besides advancing our understanding of the multifarious manifestations of this learning disorder, linguistic research on dyslexia can have a significant positive impact on the lives of people with this condition. Including linguistic assessment in the diagnostic process would be greatly beneficial for clinicians, educators and carers alike. Identifying issues with specific linguistic areas in individuals with dyslexia and making research-informed hypotheses as to the potential behavioural outcomes of such differences and deficits would favour the design of more effective rehabilitation activities and teaching methodologies and would ultimately lead to a more exact identification of subtypes of dyslexia and to more effective and possibly timely interventions. 4 Overview of the Volume

The volume is divided into three parts. The first part is focused on the cognitive substrata of the linguistic features of people with dyslexia

Introduction 9

and on their possible effects in terms of the difficulties in second language learning. The second part presents theoretical and experimental linguistic research on dyslexia at various levels of the language system, and the third part reports on some applications of the results of such theoretical and experimental research in educative contexts. The chapters of the volume reflect a variety of methodological approaches that also depend on the language of the investigated groups, all contributing to better sketching of the profile of the person with dyslexia and offering food for thought for teachers of foreign languages and teacher trainers. The three chapters included in Part 1, ‘Psychological and Neuro­ biological Foundations of Language Skills in People with Dyslexia’, offer an overview of the most important studies and results of the neurological research on dyslexia and the cognitive underpinnings of foreign language learning. Chapter 1, ‘The Neurobiological Basis of Language Skills and Dyslexia’, by Enrico Ghidoni, reviews the scientific literature on functional neuroimaging studies, which show the involvement of a complex system of multiple networks variously implicated in different linguistic tasks. The chapter aims at outlining a causal model of the disorder, from the genetic predisposition to the clinical–behavioural manifestations. It presents a critical analysis of the procedural/implicit deficit hypothesis for language and reading disorders, highlighting the strengths and weaknesses of the model, and the persistence of a gap between different levels of description. It also deals with the similarities and differences between processes involved in reading and language learning, analysing the relation between learning type and phonological, syntactic and lexical sub-processes. Chapter 2, ‘Late Effects of Early Language Delay on Complex Language and Literacy Abilities’, by Claudia Casalini, Daniela Brizzolara, Anna Maria Chilosi, Filippo Gasperini and Chiara Pecini, presents a review of studies that have investigated how an early delay in the main milestones of oral language acquisition can have significant ‘cascade effects’ on the later acquisition of complex oral and written linguistic abilities. Indeed, a high percentage of children with specific learning disorders have a history of oral language delay. Previous language delay, together with cognitive, environmental and neurobiological modulating factors, may affect the behavioural manifestations of dyslexia, suggesting the existence of different subtypes. They recommend, therefore, that a history of linguistic problems and an assessment of language and phonological working memory skills should be integrated in dyslexia diagnostic processes. The complex interplay among several risk and protective factors, varying largely from case to case, is also discussed in Chapter 3 in relation to foreign language (FL) learning.

10  A Linguistic Approach to the Study of Dyslexia

Chapter 3, ‘Foreign Language Learning Difficulties in Developmental Dyslexia: A Narrative Review of the Existing Evidence’, by Filippo Gasperini, presents an overview of several empirical studies on FL learning and the difficulties experienced by learners with dyslexia. Gasperini’s discussion stresses once more the considerable variability among learners. Indeed, FL learning is a process that can be influenced by several factors, both internal and external to the individuals. The internal factors are of a linguistic, cognitive and emotional nature, and the external factors include the characteristics of the languages involved (both the native and the FL), the sociocultural factors and the instructional choices. The author suggests that future research should focus on the role of those variables as well as the presence or absence of difficulties in the native language of the subjects. This may better help understand the factors that modulate the ease of FL learning and provide evidence-based grounds for the policies used to design school curricula for this population. The seven chapters of Part 2 of the volume, ‘Theoretical and Experimental Linguistic Research on Dyslexia’, explore issues related to the linguistic competence of people with dyslexia. The second part opens with Chapter 4, ‘Phonological and Lexical Effects on Reading in Dyslexia’, by Marijan Palmović, Ana Matić Škorić, Mirta Zelenika Zeba and Melita Kovačević. Using eye-tracking techniques, the authors present an experimental study with Croatian children with the learning disorder, who were asked to read short texts. The texts were controlled by word frequency and phonotactic probabilities. In addition, the position of the words in the text was also controlled (at the beginning or at the end of the text) to verify whether contextual information could facilitate word recognition. The results of the experiment show that, in the absence of contextual cues, phonotactic constraint guides lexical activation. Conversely, when the word is at the end of the paragraph, word recognition is facilitated by contextual information. The study highlights that phonotactic probabilities and contextual cues guide word recognition in reading and support the claim that the impaired mechanism of implicit or statistical learning can explain differences between individuals with dyslexia and unimpaired controls in detecting word boundaries and word recognition. In Chapter 5, ‘Morphemes as Reading and Spelling Units in Developmental Dyslexia’, Cristina Burani discusses how young readers with dyslexia benefit from morpheme-based reading. The author presents several studies showing that the presence of morphemes in the word (root and affixes) favours decoding, as readers rely on lexical access rather than sublexical correspondences, thus improving reading speed. Moreover, the author reports on recent studies where morpheme-based processing also increases reading accuracy and spelling, besides reading speed. In particular, visual word recognition is speeded by the properties

Introduction 11

of the roots, while reading accuracy seems to be affected more by the properties of the suffixes. Indeed, morphemes are used as both reading and spelling units and, when they are familiar, they facilitate the reading fluency and accuracy of new or low-frequency words, both in people with dyslexia and in typically developing readers. Chapter 6, ‘Morphological Knowledge in French-speaking Children with Dyslexia’, by Rachel Berthiaume, Amélie Bourcier and Daniel Daigle, also focuses on the morphological awareness of people with dyslexia. They review several studies, conducted on people with this condition and of different native languages, which focus on the differences in morphological processing between dyslexic and non-­dyslexic readers. Although people with dyslexia have some morphological knowledge, they generally perform worse than age-matched controls but similarly to younger neurotypical control groups at the same reading level. The authors hypothesise that the morphological disadvantage shown by people with dyslexia may depend on reduced exposure to the morphological structure of words, which is accessed through reading experience. The authors then present studies which demonstrate that morphological analysis has a facilitating role for the lexical processing of both words and pseudo-words. Therefore, they endorse the explicit teaching of derivational morphology to help children with dyslexia develop morphological awareness and increase their reading comprehension skills and vocabulary, suggesting several activities for teaching practice. In Chapter 7, ‘Developmental Dyslexia and Morphosyntactic Competence in Italian Young Adults’, by Giovanna Marotta, the morphosyntactic competence of a group of Italian university students with developmental dyslexia is discussed, through the analysis of their written and spoken production. The quantitative and qualitative analysis of their mistakes is aimed at identifying general trends typical of this linguistic impairment. The students’ language skills were also assessed using a standardised test that measures the reception of grammar. Participants were found to face several difficulties, especially in the identification of the syntactic subject in null-subject sentences, in the reconstruction of the syntactic sequence in which subject and verb are distant, due to an embedded element, and in the comprehension of subject relative clauses and relative sentences embedded in the main clause. The study emphasises that morphosyntactic deficits persist into adulthood and may affect the subjects’ competence in reading and writing processes. In the following chapter, Chapter 8, ‘Dyslexia and Syntactic Deficits: Overview and a Case Study of Language Training’, Anna Cardinaletti, Elisa Piccoli and Francesca Volpato discuss syntactic deficits that manifest when Italian-speaking children and adults with dyslexia are administered oral tasks. In particular, the chapter focuses on those

12  A Linguistic Approach to the Study of Dyslexia

complex language structures that are typical of the formal register used at school and university, such as subordinate clauses, relative clauses, passives and long-distance pronominal dependencies. The authors point to the necessity of assessing the syntactic competence of people with dyslexia to better define their profile and to focus on specific remedial training. Several constructions, in fact, belong to the formal register and are acquired late through language experience and via reading, and therefore are often not detected by standardised tests usually administered in pre-school years or during primary school. Reviewing the literature on this topic, the authors report on experimental studies where students with dyslexia, trained on syntactic tasks, improved on both the trained and untrained structures. The authors suggest that there is a generalisation effect of the syntactic training of the most complex structures which extends to less complex structures of the same syntactic type. They therefore discuss the necessity of language training using specific techniques of explicit teaching of those properties that have not developed implicitly. In Chapter 9, ‘The Impact of Dyslexia on Lexico-Semantic Abilities’, Gloria Cappelli presents an overview of the research on the impact of dyslexia on the lexico-semantic level of the linguistic system. Research has reached inconsistent conclusions. Most studies seem to converge on reduced vocabulary knowledge, with a gap between dyslexic and typically developing children emerging or becoming more evident at school-entry age, and progressively widening over the years. On the other hand, a few others have refuted disparities in vocabulary in wellcompensated adult dyslexics (e.g. university students). Overall, most studies agree that, at a behavioural level, people with dyslexia have intact semantic abilities, which they rely on to compensate for their deficient phonology, although different conclusions have been reached by recent studies on non-alphabetical languages. Neuroimaging and electrophysiological explorations have also found differences in brain functioning during semantic processing, which points to a mismatch between the neural and behavioural manifestations of dyslexia in semantic tasks. Possible causes for and implications of differences in the lexico-semantic profile of people with dyslexia are discussed. Chapter 10, ‘Dyslexia and Pragmatic Skills’, by Gloria Cappelli, Sabrina Noccetti, Nicoletta Simi, Giorgio Arcara and Valentina Bambini, presents a review of studies on pragmatic difficulties in people with dyslexia. The review highlights that the latter are less efficient in processing pragmatic meanings than their typically developing peers, very likely because of slower language processing speed and working memory deficits. Indeed, such issues hamper understanding of the inferential components of communication – including figurative language and humour – and impact on text comprehension at large. The authors discuss examples and conclude that the findings of this recent

Introduction 13

research strand point towards pragmatic deficit as a possibly relevant dimension of dyslexia. The authors open the path for further research in this direction. The four chapters of Part 3, ‘Applied Linguistic Research and Dyslexia’, focus on teacher training and teaching methodologies that may facilitate learning in different areas. Chapter 11, ‘Visual and Auditory Stimuli for Teaching EFL Vocabulary to Learners with Dyslexia’, by Sabrina Noccetti, presents an experiment in which two groups of dyslexic Italian university students and age-matched controls were first trained in the rapid naming of English non-words presented with visual vs. written stimuli, and then tested on their acquisition in two different test sessions, immediately after training and two weeks later. The data showed that words presented together with matched visual stimuli were better retained by the two groups in both tests. However, the DD group enjoyed major benefits from learning words by means of images, as emerged from the results of the second test administered after two weeks. The author suggests that when congruent aural and visual stimuli are associated, they function as cues for their reciprocal recall. It is suggested that this felicitous associative recognition condition may elicit the semantic component of memory, which is strategically used by the DD group of students but not by the controls. In Chapter 12, ‘Reading as a Multi-Layer Activity: Training Strategies at Text Level’, Francesca Santulli and Melissa Scagnelli present a training course, named SuperReading, which promotes a strategic reading behaviour working on different psychological and linguistic components. The authors illustrate the main aspects of the course, attended by a population of 130 Italian participants, both typical and dyslexic readers. Data obtained after the administration of reading texts pre- and post-course show significant improvements in both groups, with dyslexic readers outperforming, at the end of the course, the control group at the beginning. Furthermore, the performance of participants in SuperReading in standardised reading texts before and after attendance indicates that the training modifies their reading behaviour. A sub-group of subjects participated in an eye-tracked study. The data obtained in laboratory tests confirm paper and pencil results, highlighting statistically significant changes in the mean reading pattern of the subjects. The following chapter, Chapter 13, ‘Teaching Latin to Dyslexic Learners: A Methodological Proposal’, by Rossella Iovino, is intended as a reflection on Latin teaching to learners with dyslexia and provides suggestions for activities for the Latin classroom. The author proposes an inductive and inclusive teaching approach to this classical language, in which activities are designed to help learners with the disorder focus on the similarities and differences between Latin and their native language within a comparative framework. Although originally developed for Italian learners, the methodology can be easily adapted to other native

14  A Linguistic Approach to the Study of Dyslexia

languages. Using information and communication technologies, which allow animated visualisation of Latin grammatical structures, the activities proposed aim at promoting reflection on grammar starting from a Latin text, and at improving learning by reducing the mnemonic effort. Finally, Chapter 14, ‘Foreign Language Teacher Preparedness to Teach Learners with Dyslexia’, by Joanna Nijakowska, focuses on the importance of appropriate foreign language teacher training to promote inclusive education and differentiated instruction tailored to the needs of dyslexic students. The author discusses research findings concerning the perceived preparedness of foreign language teachers to actualise inclusive classroom practices with dyslexic students: namely, to differentiate appropriately the instruction and accommodate their diversified educational needs. She refers to the impact of different demographic variables on the teacher’s perceptions and the impact of foreign language teachers’ attitudes, selfefficacy beliefs, and concerns regarding teaching foreign languages to students with specific learning difficulties on the teaching practice. Nijakowska reviews research findings concerning the effectiveness of different types of training (massive open online course (MOOC) and face-to-face course) in reducing concerns and boosting foreign language teachers’ self-efficacy beliefs relating to teaching dyslexic students. References Adlof, S.M. and Hogan, T.P. (2018) Understanding dyslexia in the context of developmental language disorders. Language, Speech, and Hearing Services in Schools 49 (4), 762–773. Arosio, E., Branchini, C., Barbieri, L. and Guasti, M.T. (2014) Failure to produce direct object clitic pronouns as a clinical marker of SLI in school-aged Italian speaking children. J. Clin. Linguist. Phonet. 28, 1–25. Arosio, F., Pagliarini, E., Perugini, M., Barbieri, L. and Guasti, M.T. (2016) Morphosyntax and logical abilities in Italian poor readers: The problem of SLI under-identification. First Language 36, 295–315. Avram, L., Sevcenco, A. and Stoicescu, I. (2013) Clinical markers of specific language impairment and developmental dyslexia in Romanian: The case of accusative clitics (pp. 129–159). In L. Avram and A. Sevcenco (eds) Topics in Language Acquisition and Language Learning in a Romanian Context. Selected Papers from Bucharest Colloquium of Language Acquisition (BUCLA). Bucharest: Bucharest University Press. Cain, K. and Oakhill, J. (2006) Profiles of children with specific reading comprehension difficulties. British Journal of Educational Psychology 76 (4), 683–696. Canette, L.H., Fiveash, A., Krzonowski, J., Corneyllie, A., Lalitte, P., Thompson, D. and Tillmann, B. (2020) Regular rhythmic primes boost P600 in grammatical error processing in dyslexic adults and matched controls. Neuropsychologia 138, 107324. Cantiani, C., Lorusso, M., Perego, P., Molteni, M. and Guasti, M. (2013) Event-related potentials reveal anomalous morphosyntactic processing in developmental dyslexia. Applied Psycholinguistics 34 (6), 1135–1162. Cappelli, G. (2019) Pragmatic and lexical skills of learners with dyslexia and EFL learning. In M.M. Coppola, F. Di Blasio and S. Francesconi (eds) Contact Zones: Cultural, Linguistic and Literary Connections in English (pp. 55–74). Trento: Trento University Press.

Introduction 15

Cappelli, G., Noccetti, S., Arcara, G. and Bambini, V. (2018) Pragmatic competence and its relationship with the linguistic and cognitive profile of young adults with dyslexia. Dyslexia 24 (3), 294–306. Cardinaletti, A. and Volpato, F. (2015) On the comprehension and production of passive sentences and relative clauses by Italian university students with dyslexia. In E. Di Domenico, C. Hamann and S. Matteini (eds) Structures, Strategies and Beyond: Studies in Honour of Adriana Belletti (pp. 223–279). Amsterdam and Philadelphia: John Benjamins. Casalis, S., Colé, P. and Sopo, D. (2004) Morphological awareness in developmental dyslexia. Annals of Dyslexia 54 (1), 114–138. Casani, E. (2020) Distinguishing DD from SLI. Language profiles of Italian dyslexic children with and without specific language impairment. Pragmalingüística 2, 45–69. Chan, C.Y.H. (2014) The role of working memory in the comprehension of relative clauses by Chinese dyslexic children. Asian Journal of Education and e-Learning 2 (3), 165–172. Chondrogianni, V., Marinis, T., Edwards, S. and Blom, E. (2015) Production and on-line comprehension of definite articles and clitic pronouns by Greek sequential bilingual children and monolingual children with specific language impairment. Applied Psycholinguistics 36, 1155–1191. Denckla, M.B. and Rudel, R.G. (1976) Rapid ‘automatized’ naming (RAN): Dyslexia differentiated from other learning disabilities. Neuropsychologia 14 (4), 471–479. Diependaele, K., Duñabeitia, J.A., Morris, J. and Keuleers, E. (2011) Fast morphological effects in first and second language word recognition. Journal of Memory and Language 64 (4), 344–358. Dressler, W. (2003) Morphological typology and first language acquisition: Some mutual challenges. In G. Booij, E. Guevara, A. Ralli, S. Sgroi and S. Scalise (eds) Morphology and Linguistic Typology. Online Proceedings of the Fourth Mediterranean Morphology Meetings. http://morbo.lingue.unibo.it/mmm. Erbeli, F., Rice, M. and Paracchini, S. (2022) Insights into dyslexia genetics research from the last two decades. Brain Sciences 12, 27–40. Facoetti, A., Corradi, N., Ruffino, M., Gori, S. and Zorzi, M. (2010) Visual spatial attention and speech segmentation are both impaired in preschoolers at familial risk for developmental dyslexia. Dyslexia 16 (3), 226–239. Facoetti, A., Lorusso, M.L., Paganoni, P., Cattaneo, C., Galli, R., Umilta, C. and Mascetti, G.G. (2003) Auditory and visual automatic attention deficits in developmental dyslexia. Cognitive Brain Research 16 (2), 185–191. Gagarina, N.V., Klop, D., Kunnari, S., Tantele, K., Välimaa, T., Balčiūnienė, I. and Walters, J. (2012) MAIN: Multilingual assessment instrument for narratives. ZAS Papers in Linguistics 56, 1–155. Galaburda, A.M., Rosen, G.D. and Sherman, G.F. (1989) Connectional anomaly in association with cerebral microgyria in the rat. Society for Neuroscience Abstracts 13, 1601. Goswami, U. (2002) Phonology, reading development, and dyslexia: A cross–linguistic perspective. Annals of Dyslexia 52, 139–163. Goswami, U. (2019) Speech rhythm and language acquisition: An amplitude modulation phase hierarchy perspective. Annals of the New York Academy of Science 1453, 67–78. Griffiths, C.C.B. (2007) Pragmatic abilities in adults with and without dyslexia: A pilot study. Dyslexia 13, 276–296. Guasti, M.T. (2013) Agreement in the production of subject and object wh-questions. In L. Cheng and N. Corver (eds) Diagnostics in Syntax (pp. 295–313). Oxford: Oxford University Press. Guasti, M.T., Branchini, C., Vernice, M., Barbieri, L. and Arosio, F. (2015) Language disorders in children with developmental dyslexia. In S. Stavrakaki (ed.) Specific Language Impairments: Current Trends in Research (pp. 35–54). Amsterdam: John Benjamins.

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Habib, M. (2000) The neurological basis of developmental dyslexia: An overview and working hypothesis. Brain 123 (12), 2373–2399. Hart, B. and Risley, T.R. (1995) Meaningful Differences in the Everyday Experience of Young American Children. Baltimore, MD: Paul H. Brookes Publishing. Huang, Y., He, M., Li, A., Lin, Y., Zhang, X. and Wu, K. (2020) Personality, behavior characteristics, and life quality impact of children with dyslexia. International Journal of Environmental Research and Public Health 17 (4), 1415. Huttenlocher, J., Waterfall, H., Vasilyeva, M., Vevea, J. and Hedges, L.V. (2010) Sources of variability in children’s language growth. Cognitive Psychology 61 (4), 343–365. Kormos, J. and Smith, A.M. (2012) Teaching Languages to Students with Specific Learning Differences. Bristol: Multilingual Matters. Koster, C., Been, P.H., Krikhaar, E.M., Zwarts, F., Diepstra, H.D. and Van Leeuwen, T.H. (2005) Differences at 17 Months: Productive language patterns in infants at familial risk for dyslexia and typically developing infants. Journal of Speech, Language & Hearing Research 48 (2), 426–438. Kuhl, U., Neef, N.E., Kraft, I., Schaadt, G., Dörr, L., Brauer, J., Czepezauer, I., Müller, B., Wilcke, A., Kirsten, H. and Emmrich, F. (2020) The emergence of dyslexia in the developing brain. Neuroimage 211, p. 116633. Landerl, K., Ramus, F., Moll, K., Lyytinen, H., Leppänen, P.H.T., Lohvansuu, K. … Schulte–Körne, G. (2013) Predictors of developmental dyslexia in European orthographies with varying complexity. Journal of Child Psychology and Psychiatry 54 (6), 686–694. Leikin, M. (2002) Processing syntactic functions of words in normal and dyslexic readers. Journal of Psycholinguist Research 31 (2), 145–163. Łockiewicz, M., Jaskulska, M. and Fawcett, A. (2019) The analysis of free writing, vocabulary, and dyslexia in English as a native and foreign language (English vs. Polish students). Health Psychology Report 7 (1), 57–68. McArthur, G., Hogben, J., Edwards, V., Heath, S. and Mengler, E. (2000) On the ‘specifics’ of specific reading disability and specific language impairment. Journal of Child Psychology and Psychiatry 41 (7), 869–874. Mascheretti, S., Bureau, A., Battaglia, M., Simone, D., Quadrelli, E., Croteau, J., Cellino, M.R., Giorda, R., Beri, S., Maziade, M. and Marino, C. (2013) An assessment of geneby-environment interactions in developmental dyslexia-related phenotypes. Genes, Brain and Behavior 12 (1), 47–55. Moll, K., Snowling, M.J. and Hulme, C. (2020) Introduction to the special issue ‘Comorbidities between reading disorders and other developmental disorders’. Scientific Studies of Reading 24 (1), 1–6. Moll, K., Ramus, F., Bartling, J., Bruder, J., Kunze, S. and Neuhoff, N., … Landerl, K. (2014) Cognitive mechanisms underlying reading and spelling development in five European orthographies. Learning and Instruction 29, 65–77. Morton, J. and Frith, U. (1995) Causal modeling: A structural approach to developmental psychopathology. In D. Cicchetti and D.J. Cohen (eds) Developmental Psychopathology. Volume 1: Theory and Methods (pp. 357–390). Malden, MA: John Wiley & Sons. Nicolson, R.I. and Fawcett, A.J. (2008) Dyslexia and the cerebellum. In G. Reid, A. Fawcett, F. Manis and L. Siegel (eds) Learning, Cognition and Dyslexia. The SAGE Handbook of Dyslexia (pp. 77–98). London: Sage Publications. Nicolson, R.I. and Fawcett, A.J. (2019) Development of dyslexia: The delayed neural commitment framework. Frontiers in Behavioral Neuroscience 13, Article 112, 1–16. Pecini, C., Spoglianti, S., Michetti, S., Bonetti, S., Dilieto, M.C., Gasperini, F., Cristofani, P., Bozza, M., Brizzolara, D., Casalini, C., Mazzotti, S., Salvadorini, R., Bargagna, S. and Chilosi, A.M. (2018) Tele–rehabilitation in developmental dyslexia: Methods of implementation and expected results. Minerva Pediatrica 70 (6), 529–538.

Introduction 17

Pennington, B.F. (2006) From single to multiple deficit models of developmental disorders. Cognition 101 (2), 385–413. Perfetti, C.A. and Harris, L.N. (2013) Universal reading processes are modulated by language and writing system. Language Learning and Development 9 (4), 296–316. Ramírez-Esparza, N., García-Sierra, A. and Kuhl, P.K. (2014) Look who’s talking: Speech style and social context in language input to infants are linked to concurrent and future speech development. Developmental Science 17 (6), 880–891. Ramus, F. (2004) Neurobiology of dyslexia: A reinterpretation of the data. TRENDS in Neurosciences 27 (12), 720–726. Ramus, F. and Szenkovits, G. (2008) What phonological deficit? Quarterly Journal of Experimental Psychology 61 (1), 129–141. Rasamimanana, M., Barbaroux, M., Colé, P. and Besson, M. (2020) Semantic compensation and novel word learning in university students with dyslexia. Neuropsychologia 139, 107358. Reid, G. (2016) Dyslexia: A Practitioner’s Handbook. Malden, MA: John Wiley & Sons. Rispens, J., Roeleven, S. and Koster, C. (2004) Sensitivity to subject–verb agreement in spoken language in children with developmental dyslexia. Journal of Neurolinguistics 17 (5), 333–347. Rispens, J.E., Been, P.H. and Zwarts, F. (2006) Brain responses to subject–verb agreement violations in spoken language in developmental dyslexia: An ERP study. Dyslexia 12 (2), 134–149. Rose, S.J. (2009) Identifying and Teaching Children and Young People with Dyslexia and Literacy Difficulties: An Independent Report from Sir Jim Rose to the Secretary of State for Children, Schools and Families. Department for Children, Schools and Families. https://dera.ioe.ac.uk/14790/7/00659–2009DOM–EN_Redacted.pdf (last accessed December 2020). Sanfilippo, J., Ness, M., Petscher, Y., Rappaport, L., Zuckerman, B. and Gaab, N. (2020) Reintroducing dyslexia: Early identification and implications for pediatric practice. Pediatrics 146 (1). Scarborough, H.S. (1990) Very early language deficits in dyslexic children. Child Development 61 (6), 1728–1743. Scarborough, H.S. (1991) Antecedents to reading disability: Preschool language development and literacy experiences of children from dyslexic families. Reading and Writing 3 (3–4), 219–233. Schulz, E., Maurer, U., van der Mark, S., Bucher, K., Brem, S., Martin, E. and Brandeis, D. (2008) Impaired semantic processing during sentence reading in children with dyslexia: Combined fMRI and ERP evidence. Neuroimage 41 (1), 153–168. Smith-Spark, J.H., Henry, L.A., Messer, D.J., Edvardsdottir, E. and Ziecik, A.P. (2016) Executive functions in adults with developmental dyslexia. Research in Developmental Disabilities 53–54, 323–341. Snowling, M.J. and Melby-Lervåg, M. (2016) Oral language deficits in familial dyslexia: A meta-analysis and review. Psychological Bulletin 142 (5), 498–545. Snowling, M.J., Hulme, C. and Nation, K. (2020) Defining and understanding dyslexia: Past, present and future. Oxford Review of Education 46 (4), 501–513. Snowling, M.J., Hayiou-Thomas, M.E., Nash, H.M. and Hulme, C. (2020) Dyslexia and developmental language disorder: Comorbid disorders with distinct effects on reading comprehension. Journal of Child Psychology and Psychiatry 61 (6), 672–680. Spencer, M., Richmond, M.C. and Cutting, L.E. (2020) Considering the role of executive function in reading comprehension: A structural equation modeling approach. Scientific Studies of Reading 24 (3), 179–199. Stanovich, K.E. (1986) Matthew effects in reading: Some consequences of individual differences in the acquisition of literacy. Reading Research Quarterly 26, 360–407. Stein, J. (2001) The magnocellular theory of developmental dyslexia. Dyslexia 7 (1), 12–36.

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Stein, J. (2019) The current status of the magnocellular theory of developmental dyslexia. Neuropsychologia 130, 66–77. Swanson, H.L. (2012) Adults with reading disabilities: Converting a meta-analysis to practice. Journal of Learning Disabilities 45 (1), 17–30. Tallal, P., Miller, S.L., Jenkins, W.M. and Merzenich, M.M. (1997) The role of temporal processing in developmental language-based learning disorders: Research and clinical implications. In B. Blackman (ed.) Foundations of Reading Acquisition and Dyslexia: Implications for Early Intervention (pp. 49–66). Mahwah, NJ: Laurence Erlbaum. Taran, N., Farah, R., DiFrancesco, M., Altaye, M., Vannest, J., Holland, S., Rosch, K., Schlaggar, B.R. and Horowitz–Kraus, T. (2022) The role of visual attention in dyslexia: Behavioral and neurobiological evidence. Human Brain Mapping 43, 1720–1737. Torppa, M., Lyytinen, P., Erskine, J., Eklund, K. and Lyytinen, H. (2010) Language development, literacy skills, and predictive connections to reading in Finnish children with and without familial risk for dyslexia. Journal of Learning Disabilities 43 (4), 308–321. van Alphen, P., De Bree, E., Gerrits, E., De Jong, J., Wilsenach, C. and Wijnen, F. (2004) Early language development in children with a genetic risk of dyslexia. Dyslexia 10 (4), 265–288. van Viersen, S., de Bree, E.H., Zee, M., Maassen, B., van der Leij, A. and de Jong, P.F. (2018) Pathways into literacy: The role of early oral language abilities and family risk for dyslexia. Psychological Science 29 (3), 418–428. van Viersen, S., de Bree, E.H., Verdam, M., Krikhaar, E., Maassen, B., van der Leij, A. and de Jong, P.F. (2017) Delayed early vocabulary development in children at family risk of dyslexia. Journal of Speech, Language, and Hearing Research 60 (4), 937–949. Vender, M. and Delfitto, D. (2010) Towards a pragmatics of negation: The interpretation of negative sentences in developmental dyslexia. GG@ G–Generative Grammar at Geneva 6, 1–28. Vender, M., Hu, S., Mantione, F., Delfitto, D. and Melloni, C. (2018) The production of clitic pronouns: A study on bilingual and monolingual dyslexic children. Frontiers in Psychology 9, Article 2301. Wiseheart, R. and Altmann, L.J.P. ( 2018) Spoken sentence production in college students with dyslexia: Working memory and vocabulary effects. International Journal of Language and Communication Disorders 53 (2), 355–369. Wolf, M. and Bowers, P.G. (1999) The double-deficit hypothesis for the developmental dyslexias. Journal of Educational Psychology 91 (3), 415–438.

Part 1: Psychological and Neurobiological Foundations of Language Skills in People with Dyslexia

1 The Neurobiological Basis of Language Skills and Dyslexia Enrico Ghidoni

1 Introduction

Language is a highly complex functional system that includes many specialized tasks and activities, among which reading constitutes a research area of great interest due to the frequency with which reading can present specific disorders (dyslexia) with relevant personal and social effects. Therefore, the study of the neuro-functional bases of reading is undoubtedly the most developed sector of the research regarding the neural bases of language. The neurobiological basis of reading and its disorder has been extensively investigated by neurophysiological and neuroimaging studies, which show the involvement of a complex system of multiple networks variously implicated in different linguistic tasks. In parallel, the study of neuropsychological learning mechanisms (implicit/ procedural vs. explicit/declarative) has highlighted the similarities and differences between the processes involved in reading and language learning. This review will consider mainly the neuroimaging studies, with particular emphasis on those that highlight the correlations with various components of language in typical and atypical neurologic development. This synthesis of research data is able to support a hypothetical model of the reading disorder causation from genetic susceptibility to behavioural phenomenology. We present a critical analysis of the prevailing interpretative model, highlighting its strengths and weaknesses, and the persistence of a gap between different levels of description. 2 The Multifaceted Phenomenology of Reading Disorder

Reading disorder (or dyslexia) is the most well-known and frequent clinical description of specific learning disabilities (SLD). The definition adopted by the International Dyslexia Association (Lyon et al., 2003) 21

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indicates a neurobiological basis for reading disorder as one of its main features, together with correlation to a phonological deficit and to associated difficulties that are unexpected given the cognitive profile of the person who manifests the disorder. Research has focused on the cognitive characterization of the disorder, as well as on the neuroimaging and neurophysiological aspects. Reading disorder is a multifaceted phenomenon that can be approached by examining multiple levels of description, the most immediate being the clinical–behavioural aspect of a person (child, adolescent or adult) who struggles with literacy acquisition or the fluid use of writing, reading and calculation. The phenomenology is extremely variable. Its characterization by accurate testing evaluation can highlight different patterns for many components of the reading process (such as decoding and comprehension) as well as for other aspects of cognitive and linguistic functioning. Specific examination tools for the different components of the cognitive processes involved in reading can unveil underlying mechanisms. This has generated cognitive models of reading such as the classical dual route model (Coltheart, 1978, 1985; Coltheart & Rastle, 1994), in which two procedures are used to compute pronunciations from print: a lexical procedure (word recognition) and a sublexical procedure (grapheme to phoneme conversion). These alternative but complementary routes can be evaluated on the basis of neuropsychological analysis in patients with acquired or developmental reading disorders. In developmental dyslexia there is evidence of a dysfunctional pattern in which both processing routes are variably involved. The relation between orthographic and phonological representations and processes is a key mechanism in the dual route model. Reading disorders are based upon an atypical processing of the information between grapheme and phoneme representations, i.e. between the orthographic input and the phonological output, whether this occurs through the lexical direct pathway or through the sublexical conversion pathway. This is known as the phonological deficit theory. The progression to other levels of description of the mechanisms underlying typical or atypical reading is a more difficult and controversial issue. The relationship between neural networks mechanisms and their cognitive correlates is still not completely understood, though increasing knowledge of the structural and functional neuroimaging of dyslexia has produced hypotheses for such a relationship.

3 Beyond Reading: Neurobiological Bases of Language

Reading is a specialized component of language which uses the ana­tomical substrates and functional mechanisms of language inpeculiar

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and complex patterns (cf. section 4). Therefore, the neurobiological bases of reading largely overlap with the neurobiological bases of language, for which a few words are in order. We will consider only some aspects of the neuro-functional mechanisms of language, in particular those that have greater relevance in relation to the study of dyslexia. The neurobiological bases of language have been intensively studied in recent decades, especially through neuroimaging. The countless research papers produced have highlighted the evolution of anatomical and functional bases during language development and learning. Moreover, they have shown the correlations with other important aspects associated with linguistic abilities, such as implicit and explicit learning mechanisms, both in a first and in other languages, in typical and atypical development. Research on the dynamic involvement of implicit and explicit processes during language learning has resulted in the characterization of the role of the separate mechanisms that correlate with the development and activation of different brain networks (Conway & Pisoni, 2008; Ellis, 2008; Ullman, 2015). In particular, it is now known that implicit learning, which is used above all in the initial learning of the mother tongue (L1), is based on cortico-subcortical circuits implicated in the procedural memory system. Explicit learning processes are instead based on declarative memory systems and mainly involve the hippocampus and temporal and frontal cortical structures. The activation of cortico-striatal networks during language learning has been demonstrated (Krishnan et al., 2016) and there is evidence of procedural learning deficits in people with language or reading disorders. Implicit and explicit learning are separate but interact and compete in complex ways. Both processes may be involved in different ways in the acquisition of the various components of language. Thus, vocabulary and semantics are learnt above all through explicit processes, while grammar is learnt implicitly by immersion, direct exposure and practice. However, even explicit processes are at stake when particular grammatical rules are learned during formal education, and, conversely, incidental vocabulary acquisition can happen through direct exposure to linguistic input. The role of explicit processes is in general much more important in the learning of a second language (L2), which occurs above all through education. If L1 grammar is mainly learnt procedurally, L2 grammar is intentionally learnt, and therefore the declarative memory system plays as crucial a role as it does in explicit vocabulary learning. However, over time and usage, L2 grammar as well can be proceduralized (Hernandez & Li, 2007; Ullman, 2015; Ullman & Pierpont, 2005). Research on language learning and bilingualism has revealed both structural and functional changes in the brain. Functional studies and diffusion tensor imaging (DTI) studies with various parameters (e.g.

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fractional anisotropy, mean diffusivity, radial diffusivity) have shown changes in bilinguals in different white matter structures (Hämäläinen et al., 2017), an increase in grey matter in different brain structures, and a thickening of the corpus callosum (Costa & Sebastián-Gallés, 2014). Studies on white matter and functional connectivity have shown a greater connectivity between the inferior frontal gyrus and posterior regions (Luk et al., 2012). Such changes are sensitive to a number of factors. For example, immersion learning (as opposed to learning in formal educational settings) seems to modify some connection bundles (e.g. the superior longitudinal fasciculus and the inferior fronto-occipital fasciculus; Stein et al., 2014) and occurs using mechanisms more similar to those used for L1 learning (Morgan-Short & Ullman, 2012). The type of language and orthography (alphabetic vs. logographic; transparent vs. opaque) is also relevant in determining the different weight of networks and neural structures involved. Thus, Cao et al. (2017) report a greater importance of the sublexical mechanisms for the reading of Spanish (i.e. a transparent language), and the involvement of the superior temporal gyrus for phonological assembly. Direct lexical mechanisms (e.g. orthography-to-phonology) and the inferior frontal gyrus would be more relevant for reading Chinese, which involves the recognition of the whole word. Therefore, the right fusiform gyrus over the left one would be recruited for the learning of Chinese (Nelson et al., 2009; Tan et al., 2005). The commitment of the spelling decoding component is very different in different languages ​​and orthographies (Hadzibeganovic et al., 2010), and this can account for the different anatomic–functional substratum of reading disorders in different languages. The study of bilingualism has therefore assumed an important role in the research on the neurobiology of language, language learning and reading abilities, because it has highlighted relatively specific and separate anatomical–functional substrates for the L1 and the L2. These substrates have been identified through studies of structure, connectivity and functional activation. The importance of the different brain structures for first and second languages depends on numerous factors such as the age of acquisition, the degree of exposure and the level of proficiency achieved in the L2 (Hämäläinen et al., 2017). Metaanalyses have concluded that there is a substantial overlap in L1 and L2 neuroanatomical correlates (Fabbro, 2001; Indefrey & Levelt, 2004). In general, when a second language is learnt early or simultaneously with the first, the functional substrate for the two is ​​ more similar and overlapping (Hämäläinen et al., 2017; Perani et al., 1998). There are clear differences in cortical activation patterns between early and late bilinguals (Jasinska & Petitto, 2013), although an important activation of the frontal lobes is present in both situations. Increasing proficiency is associated with the engagement of a common network between the L1 and the L2 (Abutalebi et al., 2001), and the L2 proficiency level and the

The Neurobiological Basis of Language Skills and Dyslexia  25

age of acquisition are associated with structural modifications that affect the left inferior parietal lobule (Mechelli et al., 2004), the supramarginal gyrus, the left inferior frontal, the anterior cingulate cortex, the anterior temporal pole, the caudate nucleus and cerebellum (Green & Abutalebi, 2013; Hämäläinen et al., 2017; Li et al., 2014). Correlations between the structural and functional modifications of the bilingual brain, and more specifically the lexical/semantic, phonological and morphosyntactic aspects, can also be identified. Another important aspect in bilingualism is the management of the use of the two languages, which requires control processes and the commitment of the executive functions (Bialystock et al., 2012). Deciding which language to use in a given context depends on the activation of different brain areas. An fMRI study on bilingual French/ German subjects during selection processes between the two languages​​ in a naming task (Abutalebi et al., 2007) showed that the process requires activation of the left caudate and the anterior cingulate cortex, while a more recent work of the same group (Green & Abutalebi, 2016) has emphasized the role of the dorsal anterior cingulate cortex/ pre-supplementary cortex area in the selection and switching processes. The executive functions are involved in the choice and in the passage from one language to another (i.e. the switch), which is used every time a lexical item has to be accessed (Bialystock et al., 2012) through processes of inhibition of the non-pertinent lexical label (Abutalebi & Green, 2008). A quantitative meta-analysis has evaluated the neural bases of the linguistic switch process (Luk et al., 2012) and has highlighted the significant activation of at least seven brain regions involved in the executive functions (left inferior frontal gyrus, left middle temporal gyrus, left middle frontal gyrus, right precentral gyrus, right superior temporal gyrus, midline pre-supplementary motor area and bilateral caudate nuclei). These effects on the executive functions are precocious and subtended by modifications of the neural networks (e.g. left frontal lobe, left striate, cingulum, etc.), especially in early bilinguals. There is the phenomenon of the enlargement of the functional areas but also of reduced recruitment of resources in some tasks. This reinforcement of executive functions (i.e. the bilingual advantage) leads to the greater efficiency of bilinguals in many tests of executive functions and to better cognitive reserve in the bilingual elderly (Abutalebi et al., 2015; Costa & Sebastián-Gallés, 2014; Wong et al., 2016). In some studies, the default mode network also shows stronger intrinsic functional connectivity (Grady et al., 2015). An analytical review of the results of numerous studies on bilingualism is beyond the scope of the present chapter. Bialystock et al. (2012), Stein et al. (2014), Garcia-Penton et al. (2016) and Wong et al. (2016) offer thorough reviews on such matters. L1 and L2 reading abilities are related to the strength of reading network connections even in a resting state condition (Zhang et al., 2014).

26  Part 1: Psychological and Neurobiological Foundations of Language Skills

As is evident, the neurobiological substratum of linguistic functions is extremely complex, and it is further complicated in the presence of disorders. Liégeois et al.’s (2014) meta-analysis of 10 studies showed structural and functional abnormalities in the left supramarginal gyrus in the presence of speech disorders. Language disturbances show anomalies in a more widespread network, with a lack of consistency between the various studies, and greater convergence on the superior temporal gyri. Dyslexia can be considered predominantly (but not only) a disorder of some aspects of linguistic functioning. A language disorder or delay can precede the development of the first signs of dyslexia, and dyslexia and language disorder can remain comorbid. Functional abnormalities of the reading network found in dyslexics are associated with further left inferior and medial frontal gyrus activation deficits in dyslexics with a history of language delay (Pecini et al., 2011). People with dyslexia and with language disorders also differ in the patterns of connectivity between various brain regions (Richards, Nagy et al., 2016). Interestingly, it has been found that differences in brain activation as a function of language (English vs. Chinese) tend to disappear in dyslexics (Hu et al., 2010). The particular status of reading with respect to other linguistic activities also concerns its learning. While the acquisition of spoken language initially occurs mainly through implicit processes, the learning of reading takes place through explicit instruction of the correspondence rules between graphemes and phonemes, and of word pronunciation and spelling. This constitutes a specific feature of reading development with respect to language. However, several studies have pointed out that implicit learning processes can also be compromised in dyslexia, probably either at an early stage of the development of the phonological system or in a late stage of function automatization (Folia et al., 2008; Kahta & Schiff, 2016). The following is a detailed analytical overview of the major studies on the neurobiological basis of dyslexia of the past three decades. 4 The Neurobiological Basis of Dyslexia

The demonstration of the neurobiological bases of reading disorders has important practical implications. Firstly, there is a persistent need to prove the real existence of individual functional diversity, sometimes still denied because of the multidimensional nature of reading ability and, hence, of the arbitrary establishment of its normal thresholds. Secondly, the recognition of its neurobiological nature can influence the choice of diagnostic procedures and the type of intervention and can provide practitioners (e.g. physicians, psychologists, speech therapists, neuropsychologists, educators and teachers) with a common cultural background. The latter is, at present, limited to basic clinical and diagnostic evaluation at best. Research in these areas has contributed

The Neurobiological Basis of Language Skills and Dyslexia  27

to a cultural change towards specific learning disorders and dyslexia by showing that this condition is not psychological or motivational. In what follows, an extended narrative review of neurobiological data is provided. Interestingly, the neurological basis of dyslexia had already been hypothesized in the early studies on this reading disorder. Thus, describing what is perhaps the first case of dyslexia, Morgan (1896) defined it as a ‘congenital blindness for words’ and hypothesized a left angular gyrus developmental deficit. In more recent years, the studies of Galaburda and Kemper (1979) and Galaburda et al. (1985) have revealed the presence of structural abnormalities in areas of the cerebral cortex in some dyslexic people. These anatomical anomalies consisted of neuronal aggregations located outside the typical cortical layers (ectopia), more evident in the language areas of the left hemisphere, but also present in several other structures, such as the medial and lateral geniculate body, the primary auditory and visual cortex, and the cerebellum. Moreover, a relative symmetry of the planum temporale was also observed. This region is usually asymmetric, with greater extension on the left side. Galaburda’s autopsy studies have not been replicated by other researchers despite their great influence and are still waiting to be authenticated by further research. All the latest developments on the neurobiological ontogeny of dyslexia are based on genetic, neurophysiological and neuroimaging evidence. Section 4.1 is dedicated to the contribution of genetic studies, section 4.2 focuses on neurophysiological studies and section 4.3 offers an overview of the findings of neuroimaging studies of different types in typical development and dyslexia. 4.1 Genetic studies

The ability to read involves a complex system of cognitive processes based in multiple brain areas: the ‘reading brain’ (Wolf, 2007). This complex system is the result of a set of genetic mechanisms that can produce dysfunctions in many different ways. Consequently, there is no single path leading to reading disorder (Pernet et al., 2009) but, rather, multiple genetic alterations that can give rise to a dysfunctional system (Grigorenko, 2009). Our knowledge of these processes is still partial. Furthermore, reading ability is influenced by the reading experience, and received reading instruction and its distribution in the population are continuous rather than categorical. Estimation of the relevance of genetic inheritance comes from studies on families in which dyslexia occurs in several members in more or less evident forms, and from studies on people who share all or part of their genetic heritage (e.g. twins). Heritability may be responsible for about 70% for monozygotic and 50% for dizygotic twins (Hensler et al., 2010). In addition to behavioural measurements, it is now possible to

28  Part 1: Psychological and Neurobiological Foundations of Language Skills

make correlations with molecular genetic data obtained from biological materials (blood or saliva), using increasingly sophisticated techniques (genetic typing and sequencing) and statistical elaborations (linkage and association studies). The first study of the molecular genetics of dyslexia (Smith et al., 1983) was performed by analysing the entire genome of many dyslexic members belonging to the same families. Although the entire genome was analysed, only a small number of markers was available at that time. The results led to the hypothesis that a genetic factor was located on chromosome 15 (DYX1). Nowadays, the analysis of the entire genome is possible using a huge number of markers, and, over the past 15 years, numerous studies have focused on at least 20 loci of potential genetic susceptibility in genome regions that usually contain many different genes and are thought to be associated with reading disorder (Kere, 2014; Rubenstein et al., 2011; Schumacher et al., 2007). The nine most studied loci are those coded as DYX1-DYX9 and contain at least 14 genes that seem to be associated with the risk of dyslexia (Carrion-Castillo et al., 2013; Eicher & Gruen, 2013; Mascheretti et al., 2017; Paracchini et al., 2016; Truong et al., 2016). Some genes are now well known (e.g. ROBO1, KIAA0319, DCDC2, DYX1C1, MRPL2, C2orf3, FOXP2) but many others have been proposed. In large studies, the association of these genes with reading disorder is not always clear (Becker et al., 2014), while it may be more evident in certain family groups. These genes are implicated in the processes of neuronal migration, axonal orientation and ciliary biology during brain development, driving the axons and growth processes of the dendrites. Primary cilia are a microtubule-based organelle protruding from the cell surface, implicated in diverse processes such as neurogenesis, neuronal migration, axon pathfinding, and circuit formation in the developing cortex (Hasenpusch-Theil & Theil, 2021). Their alterations may be responsible for structural and connectivity abnormalities. Recent research has also addressed the correlations between each of these genes and structural and functional neuroimaging data such as variations in grey matter volume, white matter volume and structure, and activation during reading and language tasks (for a review see Mascheretti et al., 2017; Thomas et al., 2021). The situation is even more complex because there are many other conditions, as variants of duplicate DNA traits or deletions, which do not include genes but whose presence is related in various ways to language and reading skills and to the appearance of dyslexia (Gialluisi et al., 2014; Swagerman et al., 2017). The relative extent to which the risk of dyslexia can be determined in each gene is not known and is probably quite low, so grouping effects that amplify the risk must occur. Another set of candidate genes for dyslexia is emerging from genome-wide association studies such as S100B, COL4A2, CNTNAP2, LOC388780, VEPH1 (Jimenez-Bravo et al., 2017;

The Neurobiological Basis of Language Skills and Dyslexia  29

Gialluisi et al., 2021). A neurobiological model can be hypothesized which, starting from the genetic anomalies, through alterations of the neural architecture of the left temporal lobe, leads to alterations of the neurophysiological processes of acoustic analysis (‘neural oscillations’) and then to the phonological deficit and the consequent reading disorder (Giraud & Ramus, 2013; Ramus, 2004). A limitation of genetic studies is the fact that the ability to read also depends on a set of environmental factors that modify the risk of developing a disorder. Environmental and genetic factors interact in a complex and unknown way, at multiple levels of description, from molecular to behavioural. Prematurity and low birth weight are reported as environmental factors that play a role in determining the risk. There are no certain data regarding maternal smoking, risk of miscarriage and family history of psychiatric or medical illnesses (Mascheretti et al., 2018). Other complex factors, such as parenting, nutrition, healthcare, peer relations and education, may also play a role. Links are currently being made between these factors (Kere, 2014) but establishing clear connections is still at the rudimentary stages. This has given rise to a complex theory that considers prenatal and childhood stress a fundamental factor in determining the changes in neuroplasticity that can cause the development of dyslexia (Kershner, 2020, 2021). The epigenetic aspects are therefore another field of emerging interest in research (Smith, 2011), since the influences of non-strictly genetic factors may be of great importance in determining the final result at the clinical– behavioural level. The altered regulation of transcription processes in the genome determines effects that do not modify the DNA sequence but have consequences on gene expression and may be inheritable. The profound implications of these findings are not yet easily grasped in their full scope. The practical implications of genetics and epigenetics for enabling preventive interventions at the educational level are still a long way in coming (Elliott & Grigorenko, 2014). 4.2 Neurophysiological studies

Interesting data has come from established instrumental techniques such as electroencephalography (EEG). The spectral distribution of EEG activity on the scalp has shown differences between dyslexics and controls. Dyslexics show an abnormally low amplitude of the resting alpha rhythm in the posterior regions (Babiloni et al., 2012) and changes in the theta bandwidth during reading tasks (Spironelli et al., 2006), or significantly higher activity in delta and theta bands compared to control group in the frontal, central and parietal areas bilaterally (Bosch-Bayard et al., 2018). Other specific aspects were found for the microstructural characteristics of sleep, investigated by EEG, in dyslexic subjects, but with heterogeneous results (for a review see Gorgoni et al., 2020).

30  Part 1: Psychological and Neurobiological Foundations of Language Skills

Several neurophysiological studies have shown complex alterations in dyslexic subjects compared to typically developing readers (Caylak, 2009). As the core of the reading disorder seems to lie in the link between visual and auditory information, research has focused on the study of evoked responses to visual or auditory stimuli (Schulte-Korne & Bruder, 2010). In particular, the early processing of visual motion stimuli, or the timely processing of fast-changing auditory stimuli, were found to be atypical in dyslexic subjects, thus providing the basis for the abnormal structuring of higher-level processes such as the phonological. EventRelated Potential studies (ERP) using different response parameters both for visual and auditory stimuli have highlighted many altered aspects in dyslexics. These data were interpreted as indicative of a magnocellular visual system deficit (cf. Heim & Keil (2004) and Schulte-Korne & Bruder (2010) for a systematic review). In particular, the auditory evoked responses studies employed the mismatch negativity paradigm (MMN), where the presentation of acoustic stimuli at a certain point is varied (e.g. by introducing a higher frequency tone). The unexpected stimulus causes the appearance of a negative wave, which is much less evident in dyslexics. Various modifications of the stimulus parameters have made it possible to define the characteristics of the auditory disorder, which seems to be related to very elementary aspects at the psychoacoustic level (Schulte-Korne & Bruder, 2010). An instability of psychoacoustic responses to sounds (Hornickel & Kraus, 2013) may result in the impossibility of coordinating phonology and spelling during reading. Some authors have not confirmed early alterations to MMN. However, the evaluation of later responses also shows significant differences in dyslexics (Halliday et al., 2014). MMN for speech stimuli can discriminate between infants at risk and infants not at risk of developing dyslexia, as shown in a systematic review of 17 studies (Volkmer & Schulte-Korne, 2018). However, the results for older children (6–7 years) and for non-speech stimuli are very heterogeneous. A recent study has confirmed that MMN responses to speech-sound changes were absent, diminished or atypical in at-risk newborns (Thiede et al., 2019). A meta-analysis was recently performed on 25 studies that used the MMN procedure in children and adults, which confirmed significant differences between dyslexics and controls, with effect sizes ranging from small to medium (Gu & Bi, 2020). The study of early stages of auditory perception has opened up a very active research path that could eventually provide the key to the initial events leading to phonological deficits (Goswami, 2014; Lizarazu et al., 2015). Other studies have addressed the role of cerebral oscillatory responses: atypias have been demonstrated in the distribution of cortical oscillatory rhythms in the various frequency bands, particularly those correlated with speech and reading. The most recent studies have shown anomalies in gamma, theta and delta rhythms, which are involved in

The Neurobiological Basis of Language Skills and Dyslexia  31

synchronization processes related to aspects of language analysis at different levels, from prosody to syllables and phonemes. A detailed analysis of the results of these studies is beyond the scope of this chapter. A thorough review is provided by Jimenez-Bravo et al. (2017). 4.3 Neuroimaging studies

The largest amount of information on the neurobiological bases of specific learning disorders comes from the very prolific field of neuroimaging studies. The development of increasingly sophisticated techniques has allowed researchers to address the issue of reading disorders from many points of view: from the strictly morphological definition of the shape and volume of the different areas and brain structures, to the functional study of the areas of brain activation during certain tasks and with different types of stimuli. The amount of accumulated data is impressive and not always consistent. The following sections attempt to provide a synthetic critical overview. 4.3.1 The typical reading network

Neuroimaging studies have contributed, first of all, to the definition of the neuroanatomical structures involved in normal reading processes. This is a complex network formed by the cortical areas and by the connection bundles already present before the acquisition of reading which undergo specific adaptation processes during literacy development (‘neuronal recycling’; Dehaene, 2007; Dehaene et al., 2015). A vast body of research points to the conclusion that in the normal reading brain, the dorsal temporo-parietal network, the ventral occipito-temporal network, and another distributed network that includes frontal, temporal and parietal areas, correspond respectively to the phonological, orthographic and semantic components of reading. Converging evidence from diffusion tensor imaging (DTI) studies underlines the dichotomy between a dorsal system devoted to phonological processing (Vandermosten, Boets, Poelmans et al., 2012) and a ventral system devoted to lexical processing such as word recognition and exception word reading (Cummine et al., 2015). Cortical regions of the reading network include the left inferior frontal gyrus (including Broca’s area), the left superior temporal gyrus (including Wernicke’s area), the left temporo-occipital cortex (e.g. the left posterior fusiform gyrus, including the so-called ‘visual word form area’), as well as other regions around the left sylvian fissure (Zhang et al., 2014). The cerebellum also contributes to the process of reading by connecting the cortical areas underpinning the phonological and semantic processes (Alvarez & Fiez, 2018; Cui et al., 2016; Fernandez et al., 2016; Travis et al., 2015). Such a role is emphasized by proponents of the cerebellar deficit hypothesis for learning disorders (Nicolson & Fawcett, 1990).

32  Part 1: Psychological and Neurobiological Foundations of Language Skills

Moreover, a wide range of grey matter regions contribute to the skill of reading comprehension, as shown by Cui et al.’s (2018) large voxel-based morphometry (VBM) study encompassing three data sets of subjects, both adults and children. An area that is considered of critical importance for reading is the visual word form area (VWFA) in the ventral occipito-temporal cortex (Brodman area 37). This cortical area is specifically activated by alphabetic stimuli (i.e. words) and to a lesser extent by non-words or other types of stimuli (Cohen et al., 2002). The VWFA is connected to perisylvian language areas, with relatively specific bundles for graphemephoneme conversion processes and for lexical access (Bouhali et al., 2014). Its precise location is determined by its connections with the language areas in particular (Dehaene & Dehaene-Lambertz, 2016). It is also strongly linked to the dorsal structures involved in attention and spatial functions (Vogel et al., 2011), which suggests that this area is not solely used for reading processes but also for important attentive processes. Functional magnetic resonance studies (fMRI) have allowed us to highlight the different activation of brain circuits when different types of stimuli which require different subcomponents of the reading network are introduced, such as orthographic-phonological processing or processing that accesses the semantic system (Graves et al., 2010; Liebig et al., 2017; Paz-Alonso et al., 2018; Welcome & Joanisse, 2014). The selective activation of brain areas and pathways for different stimuli (e.g. letters vs. numbers or symbols) has been confirmed by various studies (Carreiras et al., 2015). The left parietal cortex is involved in letter identity, and critically in letter position coding, thus specifically contributing to the early stages of the reading process. A stimulusspecific mechanism for letter position coding is operating during orthographic processing. Reading networks are identifiable even at rest and have their core in the cortical regions in the left posterior middle temporal cortex and in the left and right posterior inferior frontal cortex (Koyama et al., 2010). To highlight the phases of cortical activation after visual or auditory presentation of a word, Marinkovic et al. (2003) resorted to a functional method using magnetic resonance and magnetoencephalography (MEG). Progressive extension of cortical activation from the occipital area to ever wider portions of the temporal lobe and inferior frontal regions was shown by the consecutive maps in the first 400 ms after exposure to the visual stimulus. More refined studies of correlations between the components of reading processes and neural structures have been developed. Yeatman et al. (2011) reported that measurements of diffusivity in the left arcuate fasciculus correlate with phonological awareness skills, whereas arcuate volume lateralization correlates with phonological memory and reading

The Neurobiological Basis of Language Skills and Dyslexia  33

skills. The role of auditory-phonological, visual magnocellular and motor-cerebellar systems in reading processes has been investigated by Danelli et al. (2013) through functional magnetic resonance (fMRI). The left occipito-temporal cortex was fractionated in functionally different areas that are variously activated depending on the task, and its central portion (corresponding to VWFA) is particularly active in reading tasks. Welcome and Joanisse (2014) carried out a DTI tractography study on the correlations between fibre bundles and specific subcomponents of the reading process in normal readers. Associations were found, for example, between non-word reading and white matter tracts under the auditory cortex, and also with the inferior fronto-occipital fasciculus and the uncinate fasciculus. Pecini et al. (2008) observe that normal readers activate the inferior frontal gyrus and the dorso-lateral prefrontal cortex during phonological tasks (e.g. rhymes), and some subjects also activate the superior temporal sulcus and the temporo-parieto-occipital junction. Hence, the phonological processing in Italian seems to activate predominantly frontal structures. Cattinelli et al. (2013) offer an extensive meta-analysis of functional fMRI studies in normal readers, which includes 35 cortical activation studies during reading tasks. Three networks have been identified: (1) a circuit sensitive to difficult tasks, including the Broca’s area and brain areas related to the attentional processes; (2) a circuit devoted to words, which includes the temporal lobe and anterior fusiform gyrus (words, semantics); and (3) a circuit for non-words, which includes basal occipito-temporal areas and the inferior parietal region. Orthographic, phonological and semantic processes depend on the different engagement of these three networks. Therefore, neuroimaging can identify specific cerebral regions for words decoding, for non-words processing, and for more difficult tasks. The analysis of the correspondence between subcomponent processes of reading and the specific activation of brain regions is now an active topic of research (Liebig et al., 2017) and there is evidence of an engagement of some structures in all component processes (e.g. the ventral occipito-temporal cortex). The links between occipital and temporal cortex have been better defined by Catani et al. (2003) through tractography studies (DTI). They observed that the inferior longitudinal fasciculus mediates the rapid transfer of visual signals from the visual cortex to the fronto-temporal cortex, supporting orthographicsemantic processing Tractography-based research in pre-school children (Vandermosten et al., 2015) has also shown that there are two main neural components: a dorsal pathway, which probably supports phonological processes, and a ventral pathway involved in orthographical recognition processes. The specialization of the dorsal pathway for phonological processes gradually develops during reading acquisition, while the ventral component has a strong predictive impact on reading skills.

34  Part 1: Psychological and Neurobiological Foundations of Language Skills

The effects of shallow and opaque orthography on the reading network has also been investigated. Paulesu et al. (2000) found interesting differences between Italian and English subjects. Positron emission tomography (PET) shows that Italians have greater activation in the upper left temporal region, which is associated with phonological processing. Conversely, the British subjects show greater activation in the left posterior inferior temporal gyrus and anterior inferior frontal gyrus, which are associated with the retrieval of words. These activation differences are clearly related to the spelling characteristics of the two languages. In recent years, many works have been published on the evolution of the reading network from childhood to adulthood. Martin et al. (2015) published a meta-analysis of 40 fMRI studies on this subject, which detected network areas that are activated in both children and adults (i.e. left ventral occipito-temporal, inferior frontal and posterior parietal areas) and other areas that are either only activated in children (i.e. left superior temporal area and bilateral supplementary motor areas) or in adults (i.e. posterior occipito-temporal areas and bilateral cerebellum, left pre-central dorsal area). Thus, there is a developmental change in the patterns of activation of reading circuits, with a rather complex pattern (Cheema & Cummine, 2018) that can be an important reference in the case of an atypical development such as that observed in dyslexia. 4.3.2 Morphological and structural data in dyslexia

Structural differences in the dyslexic brain are generally studied through voxel-based morphometry (VBM), which enables the differences in volume or thickness of the grey matter to be quantified. In 70% of typical readers, the left temporo-parietal region is considerably wider on the left side (Geschwind & Levitsky, 1968). However, Heim and Keil’s (2004) summary of previous studies reports the loss or reversal of the asymmetry of this region in dyslexics, and, more specifically, of the planum temporale (i.e. the region posterior to Heschl gyri). The latter has been found to be either symmetric or to have an asymmetry in favour of the right hemisphere (cf. Galaburda et al., 1985). Recent VBM data have confirmed these findings (Altarelli et al., 2014; Brambati et al., 2004; Sanchez Bloom et al., 2013). In contrast, Leonard et al.’s (2001) MR study reported a surprising left prevalence of the planum temporale in dyslexic subjects, along with a right prevalence at the cerebral hemisphere level, a left prevalence for the anterior lobe of the cerebellum, and the presence of duplications in the left Heschl gyri. As is evident, the inconsistency and heterogeneity observed in the structural data do not allow us to reach clear conclusions (cf. Eckert, 2004). Since there is a large overlap in the data relative to the temporal planum of dyslexics and controls, asymmetry is best viewed as just one among many neural markers that may increase the risk of dyslexia (Ramus et al., 2018).

The Neurobiological Basis of Language Skills and Dyslexia  35

Among the studies that have focused on cortical areas in people with dyslexia, Silani et al. (2005) found a reduction in the volume of the grey and white matter in inferior and middle temporal gyri and in the left arcuate fasciculus. These are the same regions where functional PET studies have shown hypoactivity. Other authors have reported abnormalities, especially in the superior temporal gyrus (Dole et al., 2013). Tamboer et al. (2015) found that he total volume of white matter was lower in dyslexics, but that there were no significant differences between controls and dyslexics for grey matter, while there were some interesting correlations between behavioural measures and some structures (caudate, cerebellum). However, He et al. (2013) have hypothesized a correlation between the volume of grey matter and various neuropsychological parameters that reflect the reading process (e.g. phonological decoding, sound-form association, and naming speed). Płoński et al. (2017) confirmed anomalies in the left hemisphere in the superior and middle temporal gyri, subparietal sulcus and prefrontal areas. They also found an atypical curvature pattern with extra folds in the left hemispheric perisylvian regions. Anomalies of cortical folding and gyrification are frequently reported (Casanova et al., 2010; Caverzasi et al., 2018; Serrallach et al., 2016) and may be concentrated in left occipito-temporal and right superior frontal areas (Williams et al., 2017). The typically decreasing age-related evolution of gyrification is lost in dyslexia (Caverzasi et al., 2018). Im et al. (2016) reported further data relating to atypical sulcal morphology in left parieto-temporal and occipito-temporal regions. These anomalies were correlated with reduced reading performance in dyslexic children and were present also in younger pre-schoolers/kindergarteners with a familial risk. Furthermore, children at risk who will develop dyslexia show a bilateral reduction of the cortical surface of the fusiform gyrus (Beelen et al., 2019). The role of occipito-temporal cortex is further emphasized in an extensive review of neuroimaging studies (Kronbichler & Kronbichler, 2018). A recent whole brain study by Kujala et al. (2020) has found decreased volumes of grey matter in dyslexia, comprising a lefthemispheric network including superior temporal and inferior frontal gyri, insula, the limbic system, basal ganglia and white matter, including the right middle temporal gyrus and hippocampus, thus showing the role of subcortical structures as well. The presence of major alterations in the left thalamus in a very large number of dyslexic subjects has been reported by Jednoróg et al. (2015). Other studies have found an increase in the thickness of the corpus callosum in the splenium, its posterior part (Hasan et al., 2012; Rumsey et al., 1996). This finding would indicate an increased connectivity between the hemispheres, but it is still in need of further confirmation. Eckert et al. (2003) carried out the manual measurement of some brain structures on MR images. This revealed a decrease in volume in the

36  Part 1: Psychological and Neurobiological Foundations of Language Skills

right anterior lobe of the cerebellum, in the frontal lobe pars triangularis (area 45) in both hemispheres, and in the whole brain. In particular, the volume of the right anterior lobe of the cerebellum had a good discriminating power between dyslexic and non-dyslexic participants, both children and adults. Eckert et al. (2005) confirmed these data with VBM measurements. Phinney et al. (2007), however, claimed that phonological ability is related to the total brain volume in normal readers but not in dyslexics. Morphological and structural features of the cerebellum have been extensively investigated. Kibby et al. (2008) found an asymmetry in favour of the right side in the control subjects. Laycock et al. (2008) reported a greater volume of white matter in dyslexics’ cerebellar hemispheres than in controls, associated with peculiar spectroscopic data. This was taken to support the hypothesis of an excess of connections and a lack of myelination in this population. Some authors studying cognitive subtypes of dyslexia (categorized into three clusters based on behavioural data) have found relatively specific associations with grey matter volume in various cerebral areas (Jednoróg et al., 2014). Zadina et al. (2006) observed no differences in quotients of hemispheric asymmetry, except in a group of phonological dyslexics, who had atypical asymmetry patterns and presented the most enlarged prefrontal regions. A greater development of the frontal regions was also reported recently in Chinese dyslexics (Qi et al., 2016), where connectivity hubs are reduced on the left but increased on the right and anterior regions. In comparison with controls, hubs in dyslexics are more distributed in frontal areas. Attempts to correlate neuroimaging with behavioural data of dyslexia cognitive subtypes are currently poor and discordant (Jednoróg et al., 2014; Van Ermingen-Marbach et al., 2013; Zadina et al., 2006). There is no agreement on the clinical definition of subtypes, and results from different studies are too heterogeneous and inconsistent. For this reason, differences of grey matter volume in specific brain areas cannot univocally predict behavioural phenotypes (Jednoróg et al., 2014). As is evident, the current state of the art, even considering only VBM data, is rather complex. To draw some conclusions from such prolific literature, systematic reviews and meta-analyses have been carried out over the last decade. Eden and Vaidya’s (2008) review found evidence of structural alterations associated with dyslexia localized at the inferior frontal, temporal and parietal areas in the left hemisphere and in the cerebellum, without specifying more precisely the nature and size of such alterations. Linkersdörfer et al. (2012) detected both morphological and functional data convergence regarding some structures such as fusiform and superior temporal gyri. Vandermosten et al.’s (Vandermosten, Boets, Wouters et al., 2012) quantitative meta-analysis of VBM studies highlighted a cluster in the left temporo-parietal region, corresponding

The Neurobiological Basis of Language Skills and Dyslexia  37

to the arcuate fasciculus and corona radiata. Richlan et al.’s (2013) metaanalysis of nine VBM studies pointed to a reduction of grey matter in the right superior temporal gyrus and in the left superior temporal sulcus. Bennett and Lagopoulos’s (2015) review found reduced volume in areas that are part of both the dorsal (temporo-parietal junction and inferior parietal lobule) and ventral (fusiform) networks. Here a word of caution is in order: different statistical methods in meta-analytic reviews can produce different results. Thus, Eckert et al. (2016) found evidence of lower grey matter volume in the left posterior superior temporal sulcus/middle temporal gyrus regions and the left orbitofrontal gyrus/ pars orbitalis regions. Finally, it is worth mentioning that other factors contributing to such a complex matter have been considered, such as the correlation with genetic factors (Skeide et al., 2015), the impact of reading practice (Chyl et al., 2021), the role of the writing system (Richlan, 2020; Yan et al., 2021), or the role of gender (Altarelli et al., 2013). Some studies have focused on pre-school children at family risk of developing dyslexia and non-at-risk controls. The aim was to differentiate between the effect of exposure to reading and reading practice and morpho-structural predisposition features (Clark et al., 2014; Hosseini et al., 2013; Raschle et al., 2011). Such studies found structural alterations in pre-reading children in the areas of the reading network, or, in some cases, in lower level auditory and visual areas. Structural studies have posited possible gender-specific differences in dyslexia. Thus, Altarelli et al. (2013) found that the word specific area shows reduced cortical thickness only in female dyslexic subjects. The cause is, however, unclear and research on this topic is scant. One exception is represented by Evans et al. (2014), who have reported a different pattern of reduction of grey matter in females compared to males in the premotor cortex and visual sensory cortex, mainly on the right side. By comparison children and adult males show the classic volume reduction pattern on the left. 4.3.3 Tractography and other connectivity studies

The study of the connection paths of the white matter (tractography, DTI) has also provided important information in defining the network that normally underlies the reading process (Beaulieu et al., 2005). However, the most interesting data have emerged from studies performed on dyslexic subjects. Several authors have dealt with the issue of DTI in children at family risk. Such alterations are already present before reading acquisition. Abnormalities in the left arcuate fasciculus in these pre-school children have been demonstrated in Wang et al. (2016), Kraft et al. (2016) and Langer et al. (2017). Similarly, Vandermosten et al. (2015) observed alterations in the ventral tracts. Hoeft et al. (2011) found that children at risk of dyslexia who grow up to be good readers show a faster

38  Part 1: Psychological and Neurobiological Foundations of Language Skills

development of the right superior longitudinal fasciculus. This is probably a compensatory mechanism. These studies may make early identification and intervention possible for at-risk children, since their findings may have predictive value for reading ability. As in the case of the other types of neuroimaging research discussed in the previous sections, DTI studies are also characterized by a marked heterogeneity in terms of their results. Thus, a review by Vandermosten et al. (2012) concluded that, generally, there is a reduction in fractional anisotropy (FA) in the left temporo-parietal white matter (i.e. in the arcuate fasciculus and in the corona radiata). Conversely, a recent quantitative meta-analysis by Moreau et al. (2018), including five studies on differences in FA data between dyslexic and typical readers, and 10 studies on FA as a function of reading ability, has shown no systematic difference of FA in the two groups, or as a function of reading ability after correction for multiple comparisons. This has led the authors to conclude that reading ability is not associated with reliable differences in white matter integrity. Studies with DTI and other tractographic techniques, such as spherical deconvolution, are still few, featuring considerable methodological differences and reaching heterogeneous results. It is, therefore, premature to draw conclusions through metaanalysis (Ramus et al., 2018). A schematic summary of the findings in relevant DTI studies is provided in Table 1.1. 4.3.4 Functional studies (fMRI and PET)

Neuroimaging research on the neurobiological basis of dyslexia has generated many studies based upon the application of functional magnetic resonance techniques with BOLD signal detection, which is an index of the oxygenation level of brain areas involved in certain cognitive tasks. In fact, the very early studies were performed with the PET method, which is based on the detection of blood flow through marked oxygen. Rumsey et al.’s (1992) activation study is an example. It showed a reduction of blood flow in the left temporo-parietal region. Another PET study by Paulesu et al. (1996) highlighted a reduced activity in different areas of the left hemisphere during phonological and linguistic tasks, in particular in the insular cortex. This was interpreted as indicative of a disconnection between the posterior and frontal areas of the reading network. Functional alterations are not a consequence of defective reading but precede it, as demonstrated by studies on children of pre-school age with a family risk (Raschle et al., 2012, 2014). Ozernov-Palchik and Gaab (2016) take into account behavioural, neurophysiological, functional and structural neuroimaging indicators and offer a comprehensive review of risk factors and predictive factors for reading skills. In a recent study by Luniewska et al. (2019) children at risk who develop reading impairment were found to present a delay in the development of

Year

2008

2008

2009

2009

2010

2011

2011

2012

Study

Richards et al.

Steinbrink et al.

Keller & Just

Odegard et al.

Rimrodt et al.

Hoeft et al.

Van der Mark et al.

Hasan et al.

50 children (10–16 y.o.) ­divided in:11 NC, 24 DD, 15 with ­comprehension deficit

18 DD children, 24 NC (9.7–12.5 y.o.)

25 DD children, 20 NC

14 DD and 17 NC (7–16 y.o.)

10 DD children, 7 NC, (12 y.o.)

47 DD children (8–12 y.o.), 25 NC

8 DD adults, 8 NC

4 DD adults, 7 NC

Subjects

FA, mean diffusivity, radial diffusivity

fMRI ­connectivity maps

FA, fMRI

FA, fibre orientation

FA

FA

FA

FA

Parameters

(Continued on next page)

Mean diffusivity of the posterior middle sector of the corpus callosum significantly correlated with measures of word reading and reading comprehension. Reading group differences in FA, MD, and RD were observed in the posterior corpus callosum.

Disruption of functional c­ onnectivity between the VWFA and left inferior frontal and left inferior parietal language areas in children with dyslexia. F­ unctional disconnection of the left occipito-temporal system is limited to the narrow central portion of the VWFA which is involved in the visual processing of words, and this alteration a ­ ppears early in dyslexic children.

Right superior longitudinal f­ asciculus (including arcuate fasciculus) white-matter ­organization significantly predicted future reading gains in dyslexia.

Reduction in FA in dyslexics in the left inferior frontal gyrus and left temporo-parietal white matter; microstructural alterations of the white matter are related to the atypical orientation of the fibres in the circuits involved in reading, including the linguistic network of the left perisylvian region.

Negative correlations were o ­ bserved in the left posterior corpus callosum between FA values and measures of decoding. Positive correlations between FA values and real word and pseudoword decoding were o ­ bserved in the left superior corona radiata.

Lower FA in a region of the left anterior centrum semiovale.

Decreased FA in dyslexics in bilateral fronto-temporal and left temporo-parietal white matter regions (inferior and superior longitudinal fasciculus). S­ ignificant correlations between white matter anisotropy and speed of pseudoword reading were found.

Higher FA in controls in both temporal regions (fusiform and inferior temporal), as well as in right parietal (inferior), right o ­ ccipital (middle), and many frontal regions.

Main findings

Table 1.1  Summary of DTI and connectivity studies in dyslexia (number and age of subjects and parameters; abbreviations: DD — ­developmental dyslexia, NC – neurotypical controls, DTI – diffusion tensor imaging, FA – fractional anisotropy)

The Neurobiological Basis of Language Skills and Dyslexia  39

Year

2012

2014

2014

2015

2015

2016

2016

Study

Vandermosten, Boets, Poelmans et al.

Fan et al.

Finn et al.

Richards et al.

Vanderauwera et al.

Cui et al.

Fernandez et al.

Table 1.1 (Continued)

29 DD children, 27 NC

28 DD children, 33 NC

71 prereading children, 36 with family risk for DD, 35 no risk

14 children with dysgraphia, 12 with dyslexia, 7 NC

75 children (32 DD, 43 NC) and 104 adults (40 DD, 64 NC)

19 DD, 20 NC (8–17 y.o.)

20 DD adults, 20 NC

Subjects

FA, axial and radial ­diffusivity

DTI, mean, ­axial and ­radial ­diffusivity

DTI with s­ pherical ­deconvolution

FA, axial diffusivity, fMRI connectivity

fMRI, whole brain connectivity

DTI

FA

Parameters

Greater FA for the poor readers in tracts connecting the cerebellum with temporo-parietal and inferior frontal regions relative to typical readers. In the occipito-temporal region, FA was greater for the older poor readers but smaller for the younger ones.

Discriminative features that c­ ontributed to the classification were primarily associated with r­ egions within the putative reading network/system (e.g. the superior longitudinal ­fasciculus, inferior fronto-­occipital f­ asciculus, thalamocortical p ­ rojections, and corpus callosum), the limbic system (e.g. the cingulum and fornix), and the motor system (e.g. the cerebellar peduncle, corona radiata, and corticospinal tract).

Phonological awareness is s­ ustained by left i­ntrahemispheric connections and not ­interhemispheric or projection tracts

The control group exhibited more white matter integrity than either the dysgraphic or dyslexic group; the dysgraphic and dyslexic groups showed more functional connectivity than the control group but differed in ­patterns of functional connectivity. Dysgraphic and dyslexic groups showed different patterns of significant DTI–fMRI connectivity correlations for specific seed points and written language tasks. Thus, d ­ ysgraphia and dyslexia differ in white matter integrity, fMRI functional connectivity, and white matter–grey matter correlations.

Dyslexics showed a d ­ ivergent connectivity within the visual paths and between the visual ­association areas and the prefrontal attention areas; in addition, an increase in right hemisphere connectivity and a decrease in VWFA ­connectivity and abnormally persistent ­connectivity with the anterior language areas around the i­nferior frontal gyrus.

Abnormal thalamic connectivity in the sensorimotor and lateral prefrontal cortices.

Reduced FA in the left arcuate fasciculus of adults with dyslexia, in particular in the segment that directly connects posterior t­ emporal and frontal areas; correlation between ­performance on phoneme awareness and speech perception and the integrity of left arcuate fasciculus (FA), and between ­orthographic processing and FA values in left inferior fronto-occipital fasciculus.

Main findings

40  Part 1: Psychological and Neurobiological Foundations of Language Skills

Year

2016

2017

2017

2017

2018

2019

2021

2021

Study

Zhao et al.

Morken et al.

Yagle et al.

Muller-Axt et al.

Moreau et al.

Tschentscher et al.

Sihvonen et al.

Zuk et al.

Table 1.1 (Continued)

35 children NC, 18 at risk with good outcome, 17 at risk with poor reading

23 adults DD, 21 NC

12 adults DD, 12 NC

11 DD, 11 dyscalculics, 11 comorbids, 11 NC

24 adults: 12 DD, 12 NC

29 children: 10 DD, 10 NC, 9 with dysgraphia

25 children at risk, 24 NC, evaluated at 6, 8, 12 y.o.

32 DD children (9–14 y.o.) and 32 NC

Subjects

DTI

Whole brain connectometry, quantitative anisotropy

DTI

FA, probabilistic tractography

Probabilistic tractography

DTI, fMRI, eye movements

fMRI ­connectivity

DTI, spherical deconvolution

Parameters

The white matter integrity of the right posterior superior longitudinal fasciculus SLF, in conjunction with cognitive–linguistic and socioeconomic factors, may play an important role in facilitating reading development among at-risk children.

Tractography analyses revealed structural white matter anomalies in DD in the left ventral route and bilaterally in the dorsal route. Connectivity deficits also observed in the corpus callosum, forceps major, vertical occipital fasciculus and corticostriatal and thalamic pathways.

Male adults with DD have reduced structural connectivity between the left medial geniculate body (auditory thalamus) and the left planum temporale.

Study of corona radiata and arcuate fasciculus is in favour of no differences between groups for these particular tracts.

Dyslexics show reduced connections in the direct pathway between the left visual thalamus and cortical area V5/MT.

The dyslexic group differed from both control groups in FA in left optic radiation.

Longitudinal study on cortical connectivity of five areas of interest from 6 to 12 years; complex patterns of evolution were observed, where dyslexics generally showed a delay; at 12 years there are no differences in connection between groups (but still there are differences in reading skills).

Dyslexics show increased hindrance-modulated oriented anisotropy (HMOA) in the right superior longitudinal fasciculus. They also show a reduced leftward asymmetry of the inferior fronto-occipital fasciculus and an increased rightward asymmetry of the second branch of the superior longitudinal fasciculus. These data provide evidence for an abnormal lateralization of occipito-frontal and parieto-frontal pathways in dyslexia.

Main findings

The Neurobiological Basis of Language Skills and Dyslexia  41

42  Part 1: Psychological and Neurobiological Foundations of Language Skills

phonological structures such as the bilateral superior temporal gyri, left middle temporal gyrus, right insula and right frontal cortex. Functional studies are performed using different methods for image acquisition and processing, different samples, and different types of tasks and stimuli. Again, this has contributed to the heterogeneity of the results. Drawing unambiguous conclusions from, and making a synthesis of, the complex panorama of fMRI studies published in the last three decades is obviously difficult. Table 1.2 offers an analytical overview of the major contributions to this field. Recently a great deal of work has been done to provide a synthesis by means of the meta-analysis of such a large body of research. Pugh et al. (2001) carried out an early review from which evidence of two dysfunctional posterior systems emerged in dyslexics: the dorsal temporo-parietal and the ventral occipito-temporal system. The dorsal system is necessary for the grapheme-phoneme conversion and is the first to develop. The ventral is mainly dedicated to the rapid recognition of words. A detailed review of all previous studies (including neurophysiological data) has been published by Heim and Keil (2004). They emphasized the intrinsic complexity of linguistic processes and the different methodologies applied in the cognitive tasks proposed for functional activation. Maisog et al.’s (2008) meta-analysis on nine functional studies with PET or fMRI on adult subjects shows that controls have greater activity than dyslexics in different areas of the left hemisphere. By contrast, dyslexics show more intense activation areas than controls in the right hemisphere. No signs of cerebellar dysfunction or hyperactivity in the left frontal area emerged. Richlan et al.’s (2009) meta-analysis includes 17 functional studies with fMRI or PET from infancy to young adult age with the aim of detecting hypo- or hyperactivity in dyslexic subjects during reading tasks. The most hypoactive areas are inferior parietal, superior temporal, middle and inferior temporal, fusiform gyrus. At the frontal level there is inferior frontal hypoactivity and hyperactivity in the motor region and left anterior insula. However, data on insula involvement collected by other authors are somewhat contrasting. Richlan et al. (2011) compiled another meta-analysis considering fMRI studies on children (9) and adults (9) separately, with the hypothesis that children have a prevalence of temporo-parietal phonological dysfunction, and adults a visualorthographic occipito-temporal dysfunction. In fact, the data were in favour of a left ventral occipito-temporal dysfunction in both groups. The hypoactivity of the superior left temporal region was found only in adults. These data emphasize the early role of the left occipital-temporal region for reading, and its dysfunction in dyslexia. Linkersdörfer et al.’s (2012) meta-analysis also focuses on structural data. It includes 24 studies published between 1996 and 2011. The quantitative analysis showed hypoactivation in the fusiform and left

Year

1992

1996

1996

1998

2001

2006

2008

2009

2009

Study

Rumsey et al.

Eden et al.

Paulesu et al.

Shaywitz et al.

Paulesu et al.

Hoeft et al.

Quagllino et al.

Steinbrink et al.

Van der Mark et al.

18 DD children, 24 NC (9–12 y.o.)

7 DD adults, 7 NC, (18–23 y.o.)

6 DD children, 6 agematched, 6 reading-level NC (8–12 y.o.)

10 DD children, 10 agematched, 10 reading-level NC, (8–12 y.o.)

18 DD adults (6 Italians, 6 English, 6 French) and 18 NC

29 DD adults and 32 NC (16–64 y.o.)

5 DD adults

DD and NC

14 DD adults, 14 NC (mean age 27 y.o.)

Subjects

fMRI, visual word stimuli and false-fonts

fMRI, auditory verbal and non-verbal stimuli

fMRI, non-word reading

fMRI, rhyme judgement

PET, phonological tasks

fMRI, phonological tasks

PET, phonological and linguistic tasks

fMRI, activation for moving visual stimuli

PET, rhyme detection task

Methods, parameters

(Continued on next page)

Cortical activation of VWFA occurs in the same areas for dyslexics and controls but a degree of specialization for words is found only in controls.

Controls show a decrease in hemodynamics in the right insula and an increase in left insula – dyslexics show such events only for non-verbal stimuli; the anterior insula is important for temporal analysis of acoustic stimuli, which is deficient in dyslexia.

In dyslexic children there is no causal interaction between area 40 (supramarginal gyrus) and inferior frontal areas 44–45.

Reduced activation relative to both age-matched and reading-matched children in the left parieto-temporal cortex and five other regions, including the right parieto-temporal cortex.

Reduced activity in a region of the left hemisphere in dyslexics from all three countries, with the maximum peak in the middle temporal gyrus and additional peaks in the inferior and superior temporal gyri and middle occipital gyrus.

Hypoactivity of the left posterior regions and a relative hyperactivity in the left inferior frontal region.

Reduced activity in various areas of the left hemisphere, in particular the insular cortex (disconnection between posterior and frontal areas of the reading network).

Lack of activation in V5 area (visual magnocellular system).

Reduction of blood flow in left temporo-parietal region.

Main findings

Table 1.2  Summary of functional studies in dyslexia (number and age of subjects, methods and parameters; abbreviations: DD — ­developmental dyslexia, NC – neurotypical controls)

The Neurobiological Basis of Language Skills and Dyslexia  43

Year

2010

2010

2010

2010

2011

Study

Hu et al.

Landi et al.

Liu et al.

Wolf et al.

Hoeft et al.

Table 1.2 (Continued)

25 DD children (mean age 14 y.o.), 20 NC (mean age 11 y.o.)

12 DD, 13 NC (16–21 y.o.)

12 DD children and 12 NC (8–14 y.o.)

13 DD adolescents, 13 NC (9–19 y.o.)

21 English (11 DD, 10 NC), age 12–16 y.o.; 16 Chinese (8 DD, 8 NC), age 13–15 y.o.

Subjects

fMRI, DTI, rhyme judgement task

fMRI, verbal working memory tasks

fMRI, semantic task, visual or auditory

fMRI, phonological and semantic tasks, visual or auditory

fMRI, visual semantic matching

Methods, parameters

Greater right prefrontal activation during a reading task that demanded phonological awareness and right superior longitudinal fasciculus (including arcuate fasciculus) white-matter organization significantly predicted future reading gains in dyslexia. Right prefrontal brain mechanisms may be critical for reading improvement in dyslexia and that may differ from typical reading development. These parameters may be more accurate than available behavioural measures.

Connectivity abnormalities in dyslexics were detected within a phonological left prefrontal network, increased functional connectivity was found in left prefrontal and inferior parietal regions. Within an executive bilateral fronto-parietal network, dyslexics showed a decreased connectivity pattern in bilateral dorsolateral prefrontal and posterior parietal regions, while increased connectivity was found in left angular gyrus, left hippocampal cortex and right thalamus.

Dyslexics show a modality specific deficit in the bottom-up connection processes from the orthographic (fusiform gyrus) to the semantic regions (middle temporal); there were no differences in connectivity from frontal regions, a finding that suggests that the basic deficit in reading disorder does not concern top-down processes.

Reduced activation for dyslexics in a number of left-hemisphere readingrelated areas regardless of task type (semantic vs. phonological) or modality (auditory vs. visual modality). Hypoactivation was detected in inferior frontal gyrus, superior temporal gyrus, and the occipito-temporal region.

Common hypoactivation pattern (in left angular gyrus and left middle frontal, posterior temporal and occipito-temporal regions) in Chinese and English dyslexics despite different activation in Chinese versus English normal readers. Differences in Chinese and English normal reading were observed as increased activation for Chinese in the left inferior frontal sulcus; and increased activation for English in the left posterior superior temporal sulcus. These cultural differences were not observed in dyslexics, who activated both left inferior frontal sulcus and left posterior superior temporal sulcus, consistent with the use of culturally independent strategies when reading is less efficient.

Main findings

44  Part 1: Psychological and Neurobiological Foundations of Language Skills

Year

2011

2011

2012

2013

2013

2013

2014

Study

Pecini et al.

Tanaka et al.

Monzalvo et al.

Cutting et al.

Langer et al.

Van ErmingenMarbach et al.

Schurz et al.

Table 1.2 (Continued)

15 DD, 14 NC (16–20 y.o.)

31 DD children (17 phonological, 14 nonphonological), 13 NC (8–11 y.o.)

15 DD children, 15 NC (8–12 y.o.)

20 DD, 12 comprehension deficit subjects, 19 NC (10–14 y.o.)

23 DD children, 23 NC, (10 y.o.)

34 DD with normal IQ, 35 DD with low IQ, 62 NC (8–13 y.o.)

13 DD, 13NC, mean age 24

Subjects

fMRI, reading tasks and resting state

fMRI, phonological decision task

fMRI, reading fluency task

fMRI, word recognition

fMRI, visual stimuli (words, faces, buildings, checkers), and auditory (spoken sentences)

fMRI, rhyme judgement task

fMRI, phonological tasks (rhyme generation)

Methods, parameters

(Continued on next page)

Reduced connectivity in dyslexia between the left posterior temporal areas and the left inferior frontal gyrus. This occurs during reading tasks as well as in the rest state. Instead, the connections between the reading-related areas and the default mode network are increased in dyslexics (in particular the precuneus connections).

Phonological dyslexics show greater activation than non-phonological in the inferior frontal area (area 44) probably implicated in phonological segmentation processes, in the left supplementary motor area (area 6), in the left precentral gyrus and in the right insula. Conversely, non-phonological dyslexics show hyperactivity in the left supramarginal gyrus (phonological store) and in the angular gyrus. This study therefore provides evidence for a different neurobiological substrate in different subtypes of dyslexics.

The demand for faster reading in dyslexics results in a very less intense activation of the fusiform gyrus than in typical readers.

Subjects with comprehension deficits show activation of cortical areas different from dyslexics and controls: hypoactivity is observed in the inferior frontal gyrus, indicating a difficulty of lexical-semantic access during the recognition of words.

Visually, dyslexics do not activate the left VWFA for words, and also show minor activation for faces on the right side. Auditorily, dyslexic children exhibited reduced responses to speech in posterior temporal cortex, left insula and supplementary motor area, as well as reduced responses to maternal language in subparts of the planum temporale, left basal language area and VWFA.

Dyslexics with high or low IQ have a reduced activation in the same cerebral temporal and occipito-temporal areas. So the neurobiological basis seems independent from the intellectual level.

Dyslexics show a reduced activation of phonological processing areas (middle frontal gyrus, precuneus, inferior parietal lobule and superior left temporal gyrus); those with language delay also have hypoactivity in the inferior left frontal gyrus (which is implicated in working memory).

Main findings

The Neurobiological Basis of Language Skills and Dyslexia  45

Year

2015

2016

2016

2017

2019

2017

2018

Study

Zhou et al.

Achal et al.

Boros et al

Danelli et al.

Buchweitz et al.

Jaffe-Dax & Ahissar

Twait et al.

Table 1.2 (Continued)

31 DD children, 35 NC, mean age 10

20 DD, 19 NC

16 DD children and 16 NC (7–13 y.o.)

20 DD adults and 23 NC, mean age 20

15 DD children and 18 NC (8–12 y.o.)

48 adult readers (with variable reading skills)

21 DD children, 26 NC, mean age 12

Subjects

fMRI, narrative comprehension task

fMRI, tone perception (implicit memory) task

fMRI, resting state and word reading task

fMRI, pseudoword reading, auditory rhyming, visual motion task, motor sequence learning

fMRI, visual presentation of symbols, letters, digits, pseudowords and false fonts

fMRI at rest

fMRI resting state

Methods, parameters

Children with dyslexia showed significantly decreased functional connectivity values of an independent component related to the salience network (insula, anterior cingulate cortex).

Dyslexics showed fast decay of adaptation across a broad range of cortical areas, although most significant effects found in auditory cortex.

Results show underconnectivity between the occipito-temporal region (VWFA) and the brain’s default-mode network in dyslexic readers and more activation of the anterior cingulate cortex for typical readers relative to dyslexics.

Dyslexics were systematically impaired only in reading and in visuophonological tasks, while deficits for other systems (e.g. motor/cerebellar, visual magnocellular/motion perception) were only very occasional. However, there is a coarser connectivity, leading to disconnection between the multiple domains that normally interact during reading.

In early orthographic processing task (recognition of symbols, letters, and digits) there is inadequate activation of the middle occipital gyrus and VWFA; this finding is interpreted as a deficit of basic visuo-spatial processing, which involves also the dorsal pathway.

Phonological processing areas (ventrolateral prefrontal, temporo-parietal junction) are less active in dyslexics and connections from sub-regions of the temporo-parietal area, show a hyperconnectivity with the caudate nucleus (dorsal striatum) that probably expresses a compensatory mechanism.

Dyslexics children have deficits in the network composed of the prefrontal, dorsal visual and ventral visual regions and may have a lack of modulation from the left medial frontal gyrus to the dorsal (intraparietal sulcus) and ventral visual regions (VWFA). The strengths of the identified functional connections were significantly correlated with the score of fluent reading.

Main findings

46  Part 1: Psychological and Neurobiological Foundations of Language Skills

Year

2018

2019

2020

2020

Study

Francisco et al.

Luniewska et al.

Ashburn et al.

Vandermosten et al.

Table 1.2 (Continued)

30 children at risk, 24 without risk, mean age 8

23 children DD, 23 NC, mean age 9.7

90 children: 55 with family risk, 35 without risk, age 6–8

21 dd, 20 NC, mean age 25

Subjects

fMRI, distinct phoneme response

fMRI, single word processing task

fMRI, rhyme judgement task

fMRI, audiovisual speech processing task

Methods, parameters

Children with a familial risk for dyslexia display less distinctive phonemic representations in bilateral temporal regions but this is not sufficient to result in reading problems.

In DD group there was no cerebellar activity and there were no differences when they were compared to children without dyslexia; the results do not support the theory that the cerebellum is affected functionally during reading.

Longitudinal study with three time points. Children who develop reading impairment present a delay in the development of phonological structures such as the bilateral superior temporal gyri, left middle temporal gyrus, right insula and right frontal cortex.

Dyslexic readers showed reduced activity in the supramarginal gyrus, in the auditory, visual, audiovisual conditions

Main findings The Neurobiological Basis of Language Skills and Dyslexia  47

48  Part 1: Psychological and Neurobiological Foundations of Language Skills

supramarginal gyrus and an overactivation of the left cerebellum. Paulesu et al. (2014) carried out a meta-analysis of the functional studies published up to 2013, encompassing 53 articles. Hypoactive areas cover the left inferior frontal premotor region, the supramarginal cortex and the left inferior-temporal and fusiform regions. There is therefore a specific deficient activation of the left occipito-temporal cortex in dyslexia, especially during reading and visual phonological tasks. Additional deficits of motor and attentive systems that are relevant to reading may be associated with a dysfunction of the left dorsal fronto-parietal cortex. Pollack et al. (2015), examining the activation patterns in a meta-analysis of various alphabetic languages, reported an atypical pattern of activation, involving significant activations in the right hemisphere, including the superior, medial and inferior frontal regions, lingual gyrus and the inferior occipital area. This pattern appears universal across alphabetic languages. Complex meta-analysis techniques are beginning to be used that allow reverse inferences to verify the interpretation of results emerging from multiple studies. Using this approach Hancock et al. (2017) found anatomical convergence between hyperactivation regions and regions supporting articulation, consistent with the proposed compensatory role of these regions, and low convergence with phonological and implicit sequence learning regions. Another object of investigation has been the effect of shallow vs. deep orthography-phonology correspondence. Different models of processing and functional substrates can be hypothesized for shallow vs. deep orthographies (Richlan, 2014). Martin et al. (2016) conducted a meta-analysis of 28 fMRI studies on dyslexic vs. non-dyslexic subjects, 14 focusing on deep orthography languages and ​​ 14 on transparent languages. Both show hypoactivation of the left temporo-occipital cortex. Languages with deep orthography (e.g. English) result in a greater hypoactivity in the inferior parietal regions, in the inferior frontal gyrus, left precuneus, and right superior temporal gyrus. Conversely, hyperactivity characterizes the left anterior insula. Languages with transparent orthographies show areas of partially different hypoactivity. From this we can conclude that, despite the biological unity of dyslexia, there are specific anomalies determined by the type of spelling (and consequent type of compensation). Numerous studies have reported a large network of compensatory activation in right-hemispheric and other bilateral reading-related areas (Turker, 2018). Another interesting issue is the difference in neurofunctional mechanisms of dyslexia depending on the writing system, i.e. alphabetic languages vs. morpho-syllabic languages (such as Chinese). Several recent systematic reviews have appeared (Richlan, 2020; Yan et al. 2021), which report reduced activation of the left superior temporal gyrus in all languages. Moreover, a reduced activation of the left middle temporal

The Neurobiological Basis of Language Skills and Dyslexia  49

gyrus has been observed in the alphabetic languages, and a reduced activation of the left inferior frontal gyrus in Chinese (Yan et al., 2021). A longstanding and stimulating research area on the neurobiological aspects of specific learning disorders involves the use of neuroimaging techniques to evaluate the effects of remediation, rehabilitation or adaptation of educational methodologies. It is an expanding field with promising but not yet definitive results. Generally, studies show that interventions can result in an increase in functional activation in various brain areas (Barquero et al., 2014; Horowitz-Kraus et al., 2014, 2015; Partanen et al., 2019; Simos et al., 2002), intrinsic connectivity improvement (Keller & Just, 2009; Koyama et al., 2013; Richards et al., 2008; Richards, Peverley et al., 2016), and structural modifications (Krafnick et al., 2011). A systematic review and a meta-analysis covering 39 intervention studies (Perdue et al., 2022) has reported evidence of changes in activation, connectivity and structure within the reading network and in the right hemisphere frontal and sub-cortical regions. A recent study by Richards, Peverley et al. (2016) has adopted an interdisciplinary approach in which the use of highly sophisticated neuroimaging techniques goes hand in hand with attention to aspects closely related to educational and teaching interventions. Such research is especially welcome because it may have important repercussions for educational practices. The development of educational practices informed by neuroscience is strongly advocated, but much work still needs be done at this time (Ozernov-Palchik & Gaab, 2016). 4.3.5 Summary of neuroimaging data

The analytical overview of research data on the neurobiological bases of specific learning disorders appears complex and sometimes confusing. It is, however, evident that the results converge to define the presence of a dysfunctional substrate in the mechanisms of connectivity between different brain regions. The latter constitute a network that is modified according to the atypical developmental matrix and involves different components depending on the type of task and detection technique used. Recently a tendency emerged to review these data critically, due to the inconsistent or contrasting results obtained in primary studies as well as in meta-analyses. Large reviews of neuroimaging data such as Ramus et al. (2018) conclude that there is sufficient evidence for a total brain volume reduction in dyslexia, while there are no macroscopic asymmetries between the hemispheres. Morphometric studies also suffer from disparities in methodology and technical aspects, leading to heterogeneous results. A common consideration involves the sample size of VBM studies, where there is evidence that the number of differences in grey matter volume between dyslexics and typical readers is inversely related to the number of subjects included in the studies. The different statistical methods

50  Part 1: Psychological and Neurobiological Foundations of Language Skills

applied to correct multiple comparison effects also play a role. The lack of correction for multiple comparisons can indeed generate false positive results. A word of caution must also be expressed regarding the meaning of the asymmetry of the planum temporale, which is confirmed only by means of particular methodologies for defining the boundaries of this structure (Altarelli et al., 2014; Ramus et al., 2018). White matter study with DTI tractography and other techniques such as spherical deconvolution can generate data about parameters such as fractional anisotropy (FA) and many others. Again, the variability of methods and techniques is accompanied by inconsistent results (Ramus et al., 2018). Some authors have concluded that the differences in grey matter volume between dyslexic and typical readers are mainly an outcome of disordered reading experience, with only a very small number citing this as a primary feature (Krafnick et al., 2014). Some findings may be the result of reduced or suboptimal reading experience and are therefore a consequence of dyslexia rather than its cause (Huettig et al., 2017). Finally, the extensive analysis of many functional studies has shown various patterns of hypoactivation and hyperactivation, but some findings are rarely replicated. The intrinsic variability in the mechanisms involved is also due to the cognitive and behavioural diversity in people with dyslexia, as well as to the underlying structural and functional brain substrate of the disorder (cf. multiple deficit model, Pennington, 2006). The age and level of maturation of the subjects and the type of orthography and spelling system also contribute to the heterogeneity of the results obtained in the experimental studies. Last but not least, the relevance of the treatments and interventions is an emerging issue. 5 Some Conclusions: From the Neurobiological Basis to Cognition and Behaviour

Despite the various unresolved questions and the variability of results of the scientific research, the overall consideration of genetic, neurophysiological and neuroimaging data indicates that it is now timely to outline a hypothetical model of a causal pathway from genetic predisposition to clinical–behavioural manifestations (Galaburda et al., 2006; Ramus, 2004). A simplified model is proposed in Figure 1.1. Dyslexia (and more generally, specific learning disorders) are constitutional conditions that depend primarily on the presence of multiple genetic risk factors, altering the neural migration processes and the structural organization of the cerebral cortex, predominantly in the perisylvian areas of the left hemisphere. In this process, which begins in the foetal life and continues throughout the developmental stage, important environmental factors also come into play, whose identification and role are not yet well defined. Structural differences (e.g. ectopias, gyrification alterations, and the volume of grey matter anomalies) result

The Neurobiological Basis of Language Skills and Dyslexia  51

Genetic risk + Environmental Factors

Neuronal migration abnormalities

Neuronal ectopias and other structural atypias

Acoustic temporal sampling disorder Implicit/Procedural deficit Phonemic categorization deficit

Phonological deficit

Reading and/or Language disorder Figure 1.1  A simplified causal model

in functional differences that are particularly relevant in some low-level visual and auditory sensory areas critical for fast temporal analysis of sensory input, leading to phoneme categorization and their relationship to graphemes, thus resulting in a weaker phonological system. In this context, too, many aspects of learning may be defective: for example, implicit learning. Some believe that this is the fundamental core of the disorder (cf. procedural or implicit deficit theory; Nicolson & Fawcett, 1990, 2007; Ullman & Pierpont, 2005). However, the causal links and the intermediate passages between multiple steps of this hypothetical model are still to be defined. It is difficult to conceive of the relationship between morphological and functional anomalies and the presence of a general or specific deficit in procedural learning, and the reciprocal effects between low-level sensory processing (acoustic and visual) and learning mechanisms. In turn, phonological dysfunction (which may be partially offset by the development of alternative processing pathways) leads to multiple intermediate process dysfunctions (e.g. phonological awareness, access to the lexicon, phonological working memory), which cause disturbances in the acquisition, fluency and accuracy of reading and/or other academic skills. The causal influences between these intermediate processes are complex and are controversial issues. At various levels, it remains difficult to distinguish between causes and consequences, and

52  Part 1: Psychological and Neurobiological Foundations of Language Skills

the relationships between the various levels can be subject to bottom-up dynamics that should also take into account environmental and epigenetic aspects. In this context, the importance of neuroplasticity, an intrinsic feature of neural systems, emerges. Neuroplasticity has been poorly studied so far but the complexity of genetic neurophysiological and neuroimaging data may justify the recently proposed hypothesis about an early inhibition of brain plasticity as a response to environ­ mental and epigenetic stressors (i.e. adaptive retrogression) that may be at the origin of dyslexia (Kershner, 2020, 2021). In this putative model of the causative cascade leading to a learning disorder, every step can be critically discussed (Guidi et al., 2018). The neuronal migration defect related to genetic alterations is still under investigation. The relevance of cortical ectopias reported by Galaburda et al. (1985) is also debated because his dyslexic cases had concomitant disorders such as ADHD, epilepsy, and other conditions that question the specificity of brain alterations. As has been shown above, the structural and functional differences of the atypical reading brain are also very complex, and the studies offer inconsistent results. The link between the morphological and functional differences in the brain and the phonological deficit is not completely revealed and does not make for an exhaustive explanation of the clinical phenomenology observed. Moreover, it remains unclear why it specifically impacts the reading network and does not rather result in a generalized cognitive impairment. Despite these limitations and other questionable results, we believe that the considerable amount of research and the studies of the last 20 years have greatly advanced our knowledge. They have allowed us to define more precise neurobiological and neurocognitive models, and to arrive at a clearer formulation of the questions that still need answering, such as those relative to the links between the many levels of description involved in the individual language-related processes. References Abutalebi, J. and Green, D.W. (2008) Control mechanisms in bilingual language production: Neural evidence from language switching studies. Language and Cognitive Processes 23 (4), 557–582. Abutelabi, J., Cappa, S.F. and Perani, D. (2021) The bilingual brain as revealed by functional neuroimaging. Bilingualism: Language and Cognition 4 (2), 179–190. Abutalebi, J., Guidi, L., Borsa, V., Canini, M., Della Rosa, P.A., Parris, B.A. and Weekes, B.S. (2015) Bilingualism provides a neural reserve for aging populations. Neuropsychologia 69, 201–210. Abutalebi, J., Annoni, J.M., Zimine, I., Pegna, A.J., Seghier, M.L., Lee-Jahnke, H., Lazeyras, F., Cappa, S. and Khateb, A. (2007) Language control and lexical competition in bilinguals: An event-related fMRI study. Cerebral Cortex 18 (7), 1496–1505. Achal, S., Hoeft, F. and Bray, S. (2016) Individual differences in adult reading are associated with left temporo-parietal to dorsal striatal functional connectivity. Cerebral Cortex 26 (10), 4069–4081.

The Neurobiological Basis of Language Skills and Dyslexia  53

Altarelli, I., Monzalvo, K., Iannuzzi, S., Fluss, J., Billard, C., Ramus, F. and DehaeneLambertz, G. (2013) A functionally guided approach to the morphometry of occipitotemporal regions in developmental dyslexia: Evidence for differential effects in boys and girls. The Journal of Neuroscience 33 (27), 11296–11301. Altarelli, I., Leroy, F., Monzalvo, K., Fluss, J., Billard, C., Dehaene-Lambertz, G. … and Ramus, F. (2014) Planum temporale asymmetry in developmental dyslexia: Revisiting an old question. Human Brain Mapping 35 (12), 5717–5735. Alvarez, T.A. and Fiez, J.A. (2018) Current perspectives on the cerebellum and reading development. Neuroscience and Biobehavioral Reviews 92, 55–86. Ashburn, S.M., Flowers, D.L., Napoliello, E.M. and Eden, G.F. (2020) Cerebellar function in children with and without dyslexia during single word processing. Human Brain Mapping 41 (1), 120–138. Babiloni, C., Stella, G., Buffo, P., Vecchio, F., Onorati, P., Muratori, C. ... and Rossini, P.M. (2012) Cortical sources of resting state EEG rhythms are abnormal in dyslexic children. Clinical Neurophysiology 123 (12), 2384–2391. Barquero, L.A., Davis, N. and Cutting, L.E. (2014) Neuroimaging of reading intervention: A systematic review and activation likelihood estimate meta-analysis. PloS ONE 9 (1), e83668. Beaulieu, C., Plewes, C., Paulson, L.A., Roy, D., Snook, L., Concha, L. and Phillips, L. (2005) Imaging brain connectivity in children with diverse reading ability. Neuroimage 25 (4), 1266–1271. Becker, J., Czamara, D., Scerri, T.S., Ramus, F., Csépe, V., Talcott, J.B. ... and Honbolygó, F. (2014) Genetic analysis of dyslexia candidate genes in the European cross-linguistic NeuroDys cohort. European Journal of Human Genetics 22 (5), 675–680. Beelen, C., Vanderauwera, J., Wouters, J., Vandermosten, M. and Ghesquière, P. (2019) Atypical gray matter in children with dyslexia before the onset of reading instruction. Cortex 121, 399–413. Bennett, M.R. and Lagopoulos, J. (2015) Neurodevelopmental sequelae associated with gray and white matter changes and their cellular basis: A comparison between Autism Spectrum Disorder, ADHD and dyslexia. International Journal of Developmental Neuroscience 46, 132–143. Bialystok, E., Craik, F.I. and Luk, G. (2012) Bilingualism: Consequences for mind and brain. Trends in Cognitive Sciences 16 (4), 240–250. Boros, M., Anton, J.L., Pech-Georgel, C., Grainger, J., Szwed, M. and Ziegler, J.C. (2016) Orthographic processing deficits in developmental dyslexia: Beyond the ventral visual stream. NeuroImage 128, 316–327. Bosch-Bayard, J., Peluso, V., Galan, L., Valdes Sosa, P. and Chiarenza, G.A. (2018) Clinical and electrophysiological differences between subjects with dysphonetic dyslexia and non-specific reading delay. Brain Sciences 8 (9), 172–200. Bouhali, F., de Schotten, M.T., Pinel, P., Poupon, C., Mangin, J.F., Dehaene, S. and Cohen, L. (2014) Anatomical connections of the visual word form area. The Journal of Neuroscience 34 (46), 15402–15414. Brambati, S.M., Termine, C., Ruffino, M., Stella, G., Fazio, F., Cappa, S.F. and Perani, D. (2004) Regional reductions of gray matter volume in familial dyslexia. Neurology 63 (4), 742–745. Buchweitz, A., Costa, A.C., Toazza, R., de Moraes, A.B., Cara, V.M., Esper, N.B. ... and Franco, A.R. (2019) Decoupling of the occipitotemporal cortex and the brain’s defaultmode network in dyslexia and a role for the cingulate cortex in good readers: A brain imaging study of Brazilian children. Developmental Neuropsychology 44 (1), 146–157. Cao, F., Sussman, B.L., Rios, V., Yan, X., Wang, Z., Spray, G.J. and Mack, R.M. (2017) Different mechanisms in learning different second languages: Evidence from English speakers learning Chinese and Spanish. NeuroImage 148, 284–295. Carreiras, M., Quiñones, I., Hernández-Cabrera, J.A. and Duñabeitia, J.A. (2015) Orthographic coding: Brain activation for letters, symbols, and digits. Cerebral Cortex 25 (12), 4748–4760.

54  Part 1: Psychological and Neurobiological Foundations of Language Skills

Carrion-Castillo, A., Franke, B. and Fisher, S.E. (2013) Molecular genetics of dyslexia: An overview. Dyslexia 19 (4), 214–240. Casanova, M.F., El-Baz, A.S., Giedd, J., Rumsey, J.M. and Switala, A.E. (2010) Increased white matter gyral depth in dyslexia: Implications for corticocortical connectivity. Journal of Autism and Developmental Disorders 40 (1), 21–29. Catani, M., Jones, D.K. and Donato, R. (2003) Occipito-temporal connections in the human brain. Brain 126 (9), 2093–2107. Cattinelli, I., Borghese, N.A., Gallucci, M. and Paulesu, E. (2013) Reading the reading brain: A new meta-analysis of functional imaging data on reading. Journal of Neurolinguistics 26 (1), 214–238. Caverzasi, E., Mandelli, M.L., Hoeft, F., Watson, C., Meyer, M., Allen, I.E. ... and Mukherjee, P. (2018) Abnormal age–related cortical folding and neurite morphology in children with developmental dyslexia. NeuroImage: Clinical 18, 814–821. Caylak, E. (2009) Neurobiological approaches on brains of children with dyslexia: Review. Academic Radiology 16 (8), 1003–1024. Cheema, K. and Cummine, J. (2018) The relationship between white matter and reading acquisition, refinement and maintenance. Developmental Neuroscience 40 (3), 209– 222. Chyl, K., Fraga-González, G., Brem, S. and Jednoróg, K. (2021) Brain dynamics of (a)typical reading development – a review of longitudinal studies. npj Science of Learning 6 (1), 1–9. Clark, K.A., Helland, T., Specht, K., Narr, K.L., Manis, F.R., Toga, A.W. and Hugdahl, K. (2014) Neuroanatomical precursors of dyslexia identified from pre-reading through to age 11. Brain 137 (12), 3136–3141. Cohen, L., Lehéricy, S., Chochon, F., Lemer, C., Rivaud, S. and Dehaene, S. (2002) Language-specific tuning of visual cortex? Functional properties of the visual word form area. Brain 125 (5), 1054–1069. Coltheart, M. (1978) Lexical access in simple reading tasks. In G. Underwood (ed.) Strategies of Information Processing (pp. 151–216). San Diego, CA: Academic Press. Coltheart, M. (1985) In defence of dual-route models of reading. Behavioral and Brain Sciences 8 (4), 709–710. Coltheart, M. and Rastle, K. (1994) Serial processing in reading aloud: Evidence for dualroute models of reading. Journal of Experimental Psychology: Human Perception and Performance 20 (6), 1197. Conway, C.M. and Pisoni, D.B. (2008) Neurocognitive basis of implicit learning of sequential structure and its relation to language processing. Annals of the New York Academy of Sciences 1145 (1), 113–131. Costa, A. and Sebastián-Gallés, N. (2014) How does the bilingual experience sculpt the brain? Nature Reviews Neuroscience 15, 336–345. Cui, Z., Xia, Z., Su, M., Shu, H. and Gong, G. (2016) Disrupted white matter connectivity underlying developmental dyslexia: A machine learning approach. Human Brain Mapping 37 (4), 1443–1458. Cui, Z., Su, M., Li, L., Shu, H. and Gong, G. (2018) Individualized prediction of reading comprehension ability using gray matter volume. Cerebral Cortex 28 (5), 1656–1672. Cummine, J., Dai, W., Borowsky, R., Gould, L., Rollans, C. and Boliek, C. (2015) Investigating the ventral-lexical, dorsal-sublexical model of basic reading processes using diffusion tensor imaging. Brain Structure and Function 220 (1), 445–455. Cutting, L.E., Clements-Stephens, A., Pugh, K.R., Burns, S., Cao, A., Pekar, J.J. ... and Rimrodt, S.L. (2013) Not all reading disabilities are dyslexia: Distinct neurobiology of specific comprehension deficits. Brain Connectivity 3 (2), 199–211. Danelli, L., Berlingeri, M., Bottini, G., Ferri, F., Vacchi, L., Sberna, M. and Paulesu, E. (2013) Neural intersections of the phonological, visual magnocellular and motor/cerebellar systems in normal readers: Implications for imaging studies on dyslexia. Human Brain Mapping 34 (10), 2669–2687.

The Neurobiological Basis of Language Skills and Dyslexia  55

Danelli, L., Berlingeri, M., Bottini, G., Borghese, N.A., Lucchese, M., Sberna, M. ... and Paulesu, E. (2017) How many deficits in the same dyslexic brains? A behavioural and fMRI assessment of comorbidity in adult dyslexics. Cortex 97, 125–142. Dehaene, S. (2007) Les neurones de la lecture. Paris : Éditions Odile Jacob. Dehaene, S. and Dehaene-Lambertz, G. (2016) Is the brain prewired for letters? Nature Neuroscience 19 (9), 1192–1193. Dehaene, S., Cohen, L., Morais, J. and Kolinsky, R. (2015) Illiterate to literate: Behavioural and cerebral changes induced by reading acquisition. Nature Reviews Neuroscience 16 (4), 234. Dole, M., Meunier, F. and Hoen, M. (2013) Gray and white matter distribution in dyslexia: A VBM study of superior temporal gyrus asymmetry. PloS ONE 8 (10), e76823. Eckert, M. (2004) Neuroanatomical markers for dyslexia: A review of dyslexia structural imaging studies. The Neuroscientist 10 (4), 362–371. Eckert, M.A., Leonard, C.M., Richards, T.L., Aylward, E.H., Thomson, J. and Berninger, V.W. (2003) Anatomical correlates of dyslexia: Frontal and cerebellar findings. Brain 126 (2), 482–494. Eckert, M.A., Berninger, V.W., Vaden, K.I., Gebregziabher, M., Tsu, L. and the Dyslexia Data Consortium (2016) Gray matter features of reading disability: A combined metaanalytic and direct analysis approach. eneuro, ENEURO–0103. January/February 2016, 3(1) e0103–15.2015 1–15. Eckert, M.A., Leonard, C.M., Wilke, M., Eckert, M., Richards, T., Richards, A. and Berninger, V. (2005) Anatomical signatures of dyslexia in children: Unique information from manual and voxel based morphometry brain measures. Cortex 41 (3), 304–315. Eden, G.F. and Vaidya, C.J. (2008) ADHD and developmental dyslexia. Annals of the New York Academy of Sciences 1145 (1), 316–327. Eden, G.F., VanMeter, J.W., Rumsey, J.W., Maisog, J. and Zeffiro, T.A. (1996) Functional MRI reveals differences in visual motion processing in individuals with dyslexia. Nature 382 (6586), 66–69. Eicher, J.D. and Gruen, J.R. (2013) Imaging-genetics in dyslexia: Connecting risk genetic variants to brain neuroimaging and ultimately to reading impairments. Molecular Genetics and Metabolism 110 (3), 201–212. Elliott, J.G. and Grigorenko, E.L. (2014) The Dyslexia Debate (No. 14). Cambridge: Cambridge University Press. Ellis, N.C. (2008) Implicit and explicit knowledge about language. In N.H. Hornberger (ed)  Encyclopedia of Language and Education (pp. 1878–1890). Boston, MA: Springer. Evans, T.M., Flowers, D.L., Napoliello, E.M. and Eden, G.F. (2014) Sex-specific gray matter volume differences in females with developmental dyslexia. Brain Structure and Function 219 (3), 1041–1054. Fabbro, F. (2001) The bilingual brain: Cerebral representation of languages. Brain and Language 79 (2), 211–222. Fan, Q., Davis, N., Anderson, A.W. and Cutting, L.E. (2014) Thalamo-cortical connectivity: What can diffusion tractography tell us about reading difficulties in children? Brain Connectivity 4 (6), 428–439. Fernandez, V.G., Juranek, J., Romanowska-Pawliczek, A., Stuebing, K., Williams, V.J. and Fletcher, J.M. (2016) White matter integrity of cerebellar-cortical tracts in reading impaired children: A probabilistic tractography study. Brain and Language 161, 45–56. Finn, E.S., Shen, X., Holahan, J.M., Scheinost, D., Lacadie, C., Papademetris, X. ... and Constable, R.T. (2014) Disruption of functional networks in dyslexia: A whole-brain, data-driven analysis of connectivity. Biological Psychiatry 76 (5), 397–404. Folia, V., Uddén, J., Forkstam, C., Ingvar, M., Hagoort, P. and Petersson, K.M. (2008) Implicit learning and dyslexia. Annals of the New York Academy of Sciences 1145, 132–150.

56  Part 1: Psychological and Neurobiological Foundations of Language Skills

Francisco, A.A., Takashima, A., McQueen, J.M., Van den Bunt, M., Jesse, A. and Groen, M.A. (2018) Adult dyslexic readers benefit less from visual input during audiovisual speech processing: fMRI evidence. Neuropsychologia 117, 454–471. Galaburda, A.M. and Kemper, T.L. (1979) Cytoarchitectonic abnormalities in developmental dyslexia: A case study. Annals of Neurology 6 (2), 94–100. Galaburda, A.M., Sherman, G.F., Rosen, G.D., Aboitiz, F. and Geschwind, N. (1985) Developmental dyslexia: Four consecutive patients with cortical anomalies. Annals of Neurology 18 (2), 222–233. Galaburda, A.M., LoTurco, J., Ramus, F., Fitch, R.H. and Rosen, G.D. (2006) From genes to behavior in developmental dyslexia. Nature Neuroscience 9 (10), 1213–1217. García-Pentón, L., Fernández García, Y., Costello, B., Duñabeitia, J.A. and Carreiras, M. (2016) The neuroanatomy of bilingualism: How to turn a hazy view into the full picture. Language, Cognition and Neuroscience 31 (3), 303–327. Geschwind, N. and Levitsky, W. (1968) Human brain: Left-right asymmetries in temporal speech region. Science 161, 186–187. Gialluisi, A., Newbury, D.F., Wilcutt, E.G., Olson, R.K., DeFries, J.C., Brandler, W.M. ... and Luciano, M. (2014) Genome-wide screening for DNA variants associated with reading and language traits. Genes, Brain and Behavior 13 (7), 686–701. Gialluisi, A., Andlauer, T.F., Mirza-Schreiber, N., Moll, K., Becker, J., Hoffmann, P. ... and Schulte-Körne, G. (2021) Genome-wide association study reveals new insights into the heritability and genetic correlates of developmental dyslexia. Molecular Psychiatry 26 (7), 3004–3017. Giraud, A.L. and Ramus, F. (2013) Neurogenetics and auditory processing in developmental dyslexia. Current Opinion in Neurobiology 23 (1), 37–42. Gorgoni, M., Scarpelli, S., Reda, F. and De Gennaro, L. (2020) Sleep EEG oscillations in neurodevelopmental disorders without intellectual disabilities. Sleep Medicine Reviews 49, 101224. Goswami, U. (2014) The neural basis of dyslexia may originate in primary auditory cortex. Brain 137 (12), 3100–3102. Grady, C.L., Luk, G., Craik, F.I. and Bialystok, E. (2015) Brain network activity in monolingual and bilingual older adults. Neuropsychologia 66, 170–181. Graves, W.W., Desai, R., Humphries, C., Seidenberg, M.S. and Binder, J.R. (2010) Neural systems for reading aloud: A multiparametric approach. Cerebral Cortex 20 (8), 1799–1815. Green, D.W. and Abutalebi, J. (2013) Language control in bilinguals: The adaptive control hypothesis. Journal of Cognitive Psychology 25 (5), 515–530. Green, D.W. and Abutalebi, J. (2016) Language control and the neuroanatomy of bilingualism: In praise of variety. Language, Cognition and Neuroscience 31 (3), 340–344. Grigorenko, E.L. (2009) At the height of fashion: What genetics can teach us about neurodevelopmental disabilities. Current Opinion in Neurology 22 (2), 126–130. Gu, C. and Bi, H.Y. (2020) Auditory processing deficit in individuals with dyslexia: A metaanalysis of mismatch negativity. Neuroscience & Biobehavioral Reviews 116, 396–405. Guidi, L.G., Velayos-Baeza, A., Martinez-Garay, I., Monaco, A.P., Paracchini, S., Bishop, D.V. and Molnár, Z. (2018) The neuronal migration hypothesis of dyslexia: A critical evaluation 30 years on. European Journal of Neuroscience 48 (10), 3212–3233. Hadzibeganovic, T., van den Noort, M., Bosch, P., Perc, M., van Kralingen, R., Mondt, K. and Coltheart, M. (2010) Cross-linguistic neuroimaging and dyslexia: A critical view. Cortex 46 (10), 1312–1316. Halliday, L.F., Barry, J.G., Hardiman, M.J. and Bishop, D.V. (2014) Late, not early mismatch responses to changes in frequency are reduced or deviant in children with dyslexia: An event-related potential study. Journal of Neurodevelopmental Disorders 6 (1), 21. Hämäläinen, S., Sairanen, V., Leminen, A. and Lehtonen, M. (2017) Bilingualism modulates the white matter structure of language-related pathways. NeuroImage 152, 249–257.

The Neurobiological Basis of Language Skills and Dyslexia  57

Hancock, R., Richlan, F. and Hoeft, F. (2017) Possible roles for fronto-striatal circuits in reading disorder. Neuroscience and Biobehavioral Reviews 72, 243–260. Hasan, K.M., Molfese, D.L., Walimuni, I.S., Stuebing, K.K., Papanicolaou, A.C., Narayana, P.A. and Fletcher, J.M. (2012) Diffusion tensor quantification and cognitive correlates of the macrostructure and microstructure of the corpus callosum in typically developing and dyslexic children. NMR in Biomedicine 25 (11), 1263–1270. Hasenpusch-Theil, K. and Theil, T. (2021) The multifaceted roles of primary cilia in the development of the cerebral cortex. Frontiers in Cell and Developmental Biology 9, 86. He, Q., Xue, G., Chen, C., Chen, C., Lu, Z.L. and Dong, Q. (2013) Decoding the neuroanatomical basis of reading ability: A multivoxel morphometric study. The Journal of Neuroscience 33 (31), 12835–12843. Heim, S. and Keil, A. (2004) Large-scale neural correlates of developmental dyslexia. European Child and Adolescent Psychiatry 13 (3), 125–140. Hensler, B.S., Schatschneider, C., Taylor, J. and Wagner, R.K. (2010) Behavioral genetic approach to the study of dyslexia. Journal of Developmental and Behavioral Pediatrics: JDBP 31 (7), 525–532. Hernandez, A.E. and Li, P. (2007) Age of acquisition: Its neural and computational mechanisms. Psychological Bulletin 133 (4), 638–650. Hoeft, F., Hernandez, A., McMillon, G., Taylor–Hill, H., Martindale, J.L., Meyler, A. ... and Whitfield-Gabrieli, S. (2006) Neural basis of dyslexia: A comparison between dyslexic and nondyslexic children equated for reading ability. The Journal of Neuroscience 26 (42), 10700–10708. Hoeft, F., McCandliss, B.D., Black, J.M., Gantman, A., Zakerani, N., Hulme, C. ... and Gabrieli, J.D. (2011) Neural systems predicting long-term outcome in dyslexia. Proceedings of the National Academy of Sciences 108 (1), 361–366. Hornickel, J. and Kraus, N. (2013) Unstable representation of sound: A biological marker of dyslexia. The Journal of Neuroscience 33 (8), 3500–3504. Horowitz-Kraus, T., DiFrancesco, M., Kay, B., Wang, Y. and Holland, S.K. (2015) Increased resting-state functional connectivity of visual- and cognitive-control brain networks after training in children with reading difficulties. NeuroImage: Clinical 8, 619–630. Horowitz-Kraus, T., Vannest, J.J., Kadis, D., Cicchino, N., Wang, Y.Y. and Holland, S.K. (2014) Reading acceleration training changes brain circuitry in children with reading difficulties. Brain and Behavior 4 (6), 886–902. Hosseini, S.H., Black, J.M., Soriano, T., Bugescu, N., Martinez, R., Raman, M.M. ... and Hoeft, F. (2013) Topological properties of large-scale structural brain networks in children with familial risk for reading difficulties. Neuroimage 71, 260–274. Hu, W., Lee, H.L., Zhang, Q., Liu, T., Geng, L.B., Seghier, M.L. ... and Price, C.J. (2010) Developmental dyslexia in Chinese and English populations: Dissociating the effect of dyslexia from language differences. Brain 133 (6), 1694–1706. Huettig, F., Lachmann, T., Reis, A. and Petersson, K.M. (2017) Distinguishing cause from effect – many deficits associated with developmental dyslexia may be a consequence of reduced and suboptimal reading experience. Language, Cognition and Neuroscience 33 (3), 333–350. Im, K., Raschle, N.M., Smith, S.A., Ellen Grant, P. and Gaab, N. (2016) Atypical sulcal pattern in children with developmental dyslexia and at-risk kindergarteners. Cerebral Cortex 26 (3), 1138–1148. Indefrey, P. and Levelt, W.J. (2004) The spatial and temporal signatures of word production components. Cognition 92 (1–2), 101–144. Jaffe-Dax, S. and Ahissar, M. (2017) In search for the relevant space of implicit memory deficit in dyslexia. In CogSci 2017 (pp. 2267–2272). Austin, TX: Cognitive Science Society Jasinska, K.K. and Petitto, L.A. (2013) How age of bilingual exposure can change the neural systems for language in the developing brain: A functional near infrared

58  Part 1: Psychological and Neurobiological Foundations of Language Skills

spectroscopy investigation of syntactic processing in monolingual and bilingual children. Developmental Cognitive Neuroscience 6, 87–101. Jednoróg, K., Gawron, N., Marchewka, A., Heim, S. and Grabowska, A. (2014) Cognitive subtypes of dyslexia are characterized by distinct patterns of gray matter volume. Brain Structure and Function 219 (5), 1697–1707. Jednoróg, K., Marchewka, A., Altarelli, I., Monzalvo Lopez, A.K., van Ermingen-Marbach, M., Grande, M. ... and Ramus, F. (2015) How reliable are gray matter disruptions in specific reading disability across multiple countries and languages? Insights from a large-scale voxel-based morphometry study. Human Brain Mapping 36 (5), 1741–1754. Jiménez-Bravo, M., Marrero, V. and Benítez-Burraco, A. (2017) An oscillopathic approach to developmental dyslexia: From genes to speech processing. Behavioural Brain Research 329, 84–95. Kahta, S. and Schiff, R. (2016) Implicit learning deficits among adults with developmental dyslexia. Annals of Dyslexia 66 (2), 235–250. Keller, T.-A. and Just, M.-A. (2009). Altering cortical connectivity: Remediation-induced changes in the white matter of poor readers. Neuron 64 (5), 624–631. Kere, J. (2014) The molecular genetics and neurobiology of developmental dyslexia as model of a complex phenotype. Biochemical and Biophysical Research Communications 452 (2), 236–243. Kershner, J.R. (2020) Dyslexia as an adaptation to cortico-limbic stress system reactivity. Neurobiology of Stress 12, 100223. Kershner, J.R. (2021) An evolutionary perspective of dyslexia, stress, and brain network homeostasis. Frontiers in Human Neuroscience 14, 611. Kibby, M.Y., Fancher, J.B., Markanen, R. and Hynd, G.W. (2008) A quantitative magnetic resonance imaging analysis of the cerebellar deficit hypothesis of dyslexia. Journal of Child Neurology 23 (4), 368–380. Koyama, M.S., Kelly, C., Shehzad, Z., Penesetti, D., Castellanos, F.X. and Milham, M.P. (2010) Reading networks at rest. Cerebral Cortex 20 (11), 2549–2559. Koyama, M.S., Di Martino, A., Kelly, C., Jutagir, D.R., Sunshine, J., Schwartz, S.J. ... and Milham, M.P. (2013) Cortical signatures of dyslexia and remediation: An intrinsic functional connectivity approach. PloS ONE 8 (2), e55454. Krafnick, A.J., Flowers, D.L., Napoliello, E.M. and Eden, G.F. (2011) Gray matter volume changes following reading intervention in dyslexic children. Neuroimage 57 (3), 733–741. Krafnick, A.J., Flowers, D.L., Luetje, M.M., Napoliello, E.M. and Eden, G.F. (2014) An investigation into the origin of anatomical differences in dyslexia. The Journal of Neuroscience 34 (3), 901–908. Kraft, I., Schreiber, J., Cafiero, R., Metere, R., Schaadt, G., Brauer, J. ... and Boltze, J. (2016) Predicting early signs of dyslexia at a preliterate age by combining behavioral assessment with structural MRI. NeuroImage 143, 378–386. Krishnan, S., Watkins, K.E. and Bishop, D.V. (2016) Neurobiological basis of language learning difficulties. Trends in Cognitive Sciences 20 (9), 701–714. Kronbichler, L. and Kronbichler, M. (2018) The importance of the left occipitotemporal cortex in developmental dyslexia. Current Developmental Disorders Reports 5 (1), 1–8. Kujala, T., Thiede, A., Palo-oja, P., Virtala, P., Laasonen, M., Numminen, J. and Sihvonen, A.J. (2020) Brain structures associated with reading and their abnormalities in dyslexia: A whole-brain analysis. bioRxiv. Landi, N., Mencl, W.E., Frost, S.J., Sandak, R. and Pugh, K.R. (2010) An fMRI study of multimodal semantic and phonological processing in reading disabled adolescents. Annals of Dyslexia 60 (1), 102–121. Langer, N., Benjamin, C., Minas, J. and Gaab, N. (2013) The neural correlates of reading fluency deficits in children. Cerebral Cortex 25 (6), 1441–1453. Langer, N., Peysakhovich, B., Zuk, J., Drottar, M., Sliva, D.D., Smith, S. ... and Gaab, N. (2017) White matter alterations in infants at risk for developmental dyslexia. Cerebral Cortex 27 (2), 1027–1036.

The Neurobiological Basis of Language Skills and Dyslexia  59

Laycock, S.K., Wilkinson, I.D., Wallis, L.I., Darwent, G., Wonders, S.H., Fawcett, A.J. ... and Nicolson, R.I. (2008) Cerebellar volume and cerebellar metabolic characteristics in adults with dyslexia. Annals of the New York Academy of Sciences 1145 (1), 222–236. Leonard, C.M., Eckert, M.A., Lombardino, L.J., Oakland, T., Kranzler, J., Mohr, C.M. ... and Freeman, A. (2001) Anatomical risk factors for phonological dyslexia. Cerebral Cortex 11 (2), 148–157. Li, P., Legault, J. and Litcofsky, K.A. (2014) Neuroplasticity as a function of second language learning: Anatomical changes in the human brain. Cortex 58, 301–324. Liebig, J., Froehlich, E., Morawetz, C., Braun, M., Jacobs, A.M., Heekeren, H.R. and Ziegler, J.C. (2017) Neurofunctionally dissecting the reading system in children. Developmental Cognitive Neuroscience 27, 45–57. Liégeois, F., Mayes, A. and Morgan, A. (2014) Neural correlates of developmental speech and language disorders: Evidence from neuroimaging. Current Developmental Disorders Reports 1 (3), 215–227. Linkersdörfer, J., Lonnemann, J., Lindberg, S., Hasselhorn, M. and Fiebach, C.J. (2012) Gray matter alterations co-localize with functional abnormalities in developmental dyslexia: An ALE meta-analysis. PloS ONE 7 (8), e43122. Liu, L., Vira, A., Friedman, E., Minas, J., Bolger, D., Bitan, T. and Booth, J. (2010) Children with reading disability show brain differences in effective connectivity for visual, but not auditory word comprehension. PLoS ONE 5 (10), e13492. Lizarazu, M., Lallier, M., Molinaro, N., Bourguignon, M., Paz-Alonso, P.M., LermaUsabiaga, G. and Carreiras, M. (2015) Developmental evaluation of atypical auditory sampling in dyslexia: Functional and structural evidence. Human Brain Mapping 36 (12), 4986–5002. Luk, G., Green, D.W., Abutalebi, J. and Grady, C. (2012) Cognitive control for language switching in bilinguals: A quantitative meta-analysis of functional neuroimaging studies. Language and Cognitive Processes 27 (10), 1479–1488. Łuniewska, M., Chyl, K., Dębska, A., Banaszkiewicz, A., Żelechowska, A., Marchewka, A. ... and Jednoróg, K. (2019) Children with dyslexia and familial risk for dyslexia present atypical development of the neuronal phonological network. Frontiers in Neuroscience 13, 1287. Lyon, G.R., Shaywitz, S.E. and Shaywitz, B.A. (2003) A definition of dyslexia. Annals of Dyslexia 53 (1), 1–14. Maisog, J.M., Einbinder, E.R., Flowers, D.L., Turkeltaub, P.E. and Eden, G.F. (2008) A meta-analysis of functional neuroimaging studies of dyslexia. Annals of the New York Academy of Sciences 1145 (1), 237–259. Marinkovic, K., Dhond, R.P., Dale, A.M., Glessner, M., Carr, V. and Halgren, E. (2003) Spatiotemporal dynamics of modality-specific and supramodal word processing. Neuron 38 (3), 487–497. Martin, A., Kronbichler, M. and Richlan, F. (2016) Dyslexic brain activation abnormalities in deep and shallow orthographies: A meta-analysis of 28 functional neuroimaging studies. Human Brain Mapping 37 (7), 2676–2699. Martin, A., Schurz, M., Kronbichler, M. and Richlan, F. (2015) Reading in the brain of children and adults: A meta-analysis of 40 functional magnetic resonance imaging studies. Human Brain Mapping 36 (5), 1963–1981. Mascheretti, S., Andreola, C., Scaini, S. and Sulpizio, S. (2018) Beyond genes: A systematic review of environmental risk factors in specific reading disorder. Research in Developmental Disabilities 82, 147–152. Mascheretti, S., De Luca, A., Trezzi, V., Peruzzo, D., Nordio, A., Marino, C. and Arrigoni, F. (2017) Neurogenetics of developmental dyslexia: From genes to behavior through brain neuroimaging and cognitive and sensorial mechanisms. Translational Psychiatry 7 (1), e987–e987.

60  Part 1: Psychological and Neurobiological Foundations of Language Skills

Mechelli, A., Crinion, J.T., Noppeney, U., O’Doherty, J., Ashburner, J., Frackowiak, R.S. and Price, C.J. (2004) Neurolinguistics: Structural plasticity in the bilingual brain. Nature 431, 757. Monzalvo, K., Fluss, J., Billard, C., Dehaene, S. and Dehaene-Lambertz, G. (2012) Cortical networks for vision and language in dyslexic and normal children of variable socioeconomic status. Neuroimage 61 (1), 258–274. Moreau, D., Stonyer, J.E., McKay, N.S. and Waldie, K.E. (2018) No evidence for systematic white matter correlates of dyslexia: An activation likelihood estimation metaanalysis. Brain Research 1683, 36–47. Moreau, D., Wilson, A.J., McKay, N.S., Nihill, K. and Waldie, K.E. (2018) No evidence for systematic white matter correlates of dyslexia and dyscalculia. NeuroImage: Clinical 18, 356–366. Morgan, W.P. (1896) A case of congenital word blindness. British Medical Journal 2 (1871), 1378–1379. Morgan-Short, K. and Ullman, M.T. (2012) The neurocognition of second language. In S.M. Gass and A. Mackey (eds) Handbook of Second Language Acquisition (pp. 282– 299). New York, NY: Routledge. Morken, F., Helland, T., Hugdahl, K. and Specht, K. (2017) Reading in dyslexia across literacy development: A longitudinal study of effective connectivity. NeuroImage 144, 92–100. Müller-Axt, C., Anwander, A. and von Kriegstein, K. (2017) Altered structural connectivity of the left visual thalamus in developmental dyslexia. Current Biology 27 (23), 3692– 3698. Nelson, J.R., Liu, Y., Fiez, J. and Perfetti, C.A. (2009) Assimilation and accommodation patterns in ventral occipitotemporal cortex in learning a second writing system. Human Brain Mapping 30 (3), 810–820. Nicolson, R.I. and Fawcett, A.J. (1990) Automaticity: A new framework for dyslexia research? Cognition 35 (2), 159–182. Nicolson, R.I. and Fawcett, A.J. (2007) Procedural learning difficulties: Reuniting the Developmental Disorders? TRENDS in Neurosciences 30 (4), 135–141. Odegard, T.N., Farris, E.A., Ring, J., McColl, R. and Black, J. (2009) Brain connectivity in non-reading impaired children and children diagnosed with developmental dyslexia. Neuropsychologia 47 (8–9), 1972–1977. Ozernov-Palchik, O. and Gaab, N. (2016) Tackling the ‘dyslexia paradox’: Reading brain and behavior for early markers of developmental dyslexia. Wiley Interdisciplinary Reviews: Cognitive Science 7 (2), 156–176. Paracchini, S., Diaz, R. and Stein, J. (2016) Advances in dyslexia genetics – New insights into the role of brain asymmetries. Advances in Genetics 96, 53–97. Partanen, M., Siegel, L.S. and Giaschi, D.E. (2019) Effect of reading intervention and task difficulty on orthographic and phonological reading systems in the brain. Neuropsychologia 130, 11–23. Paulesu, E., Danelli, L. and Berlingeri, M. (2014) Reading the dyslexic brain: Multiple dysfunctional routes revealed by a new meta-analysis of PET and fMRI activation studies. Frontiers in Human Neuroscience 8 (303), 830. Paulesu, E., Frith, U., Snowling, M., Gallagher, A., Morton, J., Frackowiak, R.S. and Frith, C.D. (1996) Is developmental dyslexia a disconnection syndrome? Evidence from PET scanning. Brain 119, 143–157. Paulesu, E., McCrory, E., Fazio, F., Menoncello, L., Brunswick, N., Cappa, S.F. ... and Pesenti, S. (2000) A cultural effect on brain function. Nature Neuroscience 3 (1), 91–96. Paulesu, E., Démonet, J.F., Fazio, F., McCrory, E., Chanoine, V., Brunswick, N. ... and Frith, U. (2001) Dyslexia: Cultural diversity and biological unity. Science 291 (5511), 2165–2167. Paz-Alonso, P.M., Oliver, M., Lerma-Usabiaga, G., Caballero-Gaudes, C., Quiñones, I., Suárez-Coalla, P. ... and Carreiras, M. (2018) Neural correlates of phonological,

The Neurobiological Basis of Language Skills and Dyslexia  61

orthographic and semantic reading processing in dyslexia. NeuroImage: Clinical 20, 433–447. Pecini, C., Biagi, L., Guzzetta, A., Montanaro, D., Brizzolara, D., Cipriani, P. ... and Cioni, G. (2008) Brain representation of phonological processing in Italian: Individual variability and behavioural correlates. Archives italiennes de biologie 146 (3–4), 189–203. Pecini, C., Biagi, L., Brizzolara, D., Cipriani, P., Di Lieto, M.C., Guzzetta, A. ... and Chilosi, A.M. (2011) How many functional brains in developmental dyslexia? When the history of language delay makes the difference. Cognitive and Behavioral Neurology 24 (2), 85–92. Pennington, B.F. (2006) From single to multiple deficit models of developmental disorders. Cognition 101 (2), 385–413. Perani, D., Paulesu, E., Galles, N.S., Dupoux, E., Dehaene, S., Bettinardi, V. ... and Mehler, J. (1998) The bilingual brain. Proficiency and age of acquisition of the second language. Brain: A Journal of Neurology 121 (10), 1841–1852. Perdue, M.V., Mahaffy, K., Vlahcevic, K., Wolfman, E., Erbeli, F., Richlan, F. and Landi, N. (2022) Reading intervention and neuroplasticity: A systematic review and metaanalysis of brain changes associated with reading intervention. Neuroscience & Biobehavioral Reviews 132, 465–494. Pernet, C., Andersson, J., Paulesu, E. and Demonet, J.F. (2009) When all hypotheses are right: A multifocal account of dyslexia. Human Brain Mapping 30 (7), 2278–2292. Phinney, E., Pennington, B.F., Olson, R., Filley, C.M. and Filipek, P.A. (2007) Brain structure correlates of component reading processes: Implications for reading disability. Cortex 43 (6), 777–791. Płoński, P., Gradkowski, W., Altarelli, I., Monzalvo, K., van Ermingen-Marbach, M., Grande, M. ... and Jednoróg, K. (2017) Multi-parameter machine learning approach to the neuroanatomical basis of developmental dyslexia. Human Brain Mapping 38 (2), 900–908. Pollack, C., Luk, G. and Christodoulou, J.A. (2015) A meta-analysis of functional reading systems in typically developing and struggling readers across different alphabetic languages. Frontiers in Psychology 6, 191. Pugh, K.R., Mencl, W.E., Jenner, A.R., Katz, L., Frost, S.J., Lee, J.R. ... and Shaywitz, B.A. (2001) Neurobiological studies of reading and reading disability. Journal of Communication Disorders 34 (6), 479–492. Qi, T., Gu, B., Ding, G., Gong, G., Lu, C., Peng, D. ... and Liu, L. (2016) More bilateral, more anterior: Alterations of brain organization in the large-scale structural network in Chinese dyslexia. Neuroimage 124 (A), 63–74. Quaglino, V., Bourdin, B., Czternasty, G., Vrignaud, P., Fall, S., Meyer, M.E. ... and de Marco, G. (2008) Differences in effective connectivity between dyslexic children and normal readers during a pseudoword reading task: An fMRI study. Neurophysiologie Clinique/Clinical Neurophysiology 38 (2), 73–82. Ramus, F. (2004) The neural basis of reading acquisition. In M.S. Gazzaniga (ed.) The Cognitive Neurosciences (3rd edn) (pp. 815–824). Cambridge, MA: MIT Press. Ramus, F., Altarelli, I., Jednoróg, K., Zhao, J. and di Covella, L.S. (2018) Neuroanatomy of developmental dyslexia: Pitfalls and promise. Neuroscience and Biobehavioral Reviews 84, 434–452. Raschle, N.M., Chang, M. and Gaab, N. (2011) Structural brain alterations associated with dyslexia predate reading onset. Neuroimage 57 (3), 742–749. Raschle, N.M., Zuk, J. and Gaab, N. (2012) Functional characteristics of developmental dyslexia in left-hemispheric posterior brain regions predate reading onset. Proceedings of the National Academy of Sciences 109 (6), 2156–2161. Raschle, N.M., Stering, P.L., Meissner, S.N. and Gaab, N. (2014) Altered neuronal response during rapid auditory processing and its relation to phonological processing in prereading children at familial risk for dyslexia. Cerebral Cortex 24 (9), 2489–2501.

62  Part 1: Psychological and Neurobiological Foundations of Language Skills

Richards, T., Nagy, W., Abbott, R. and Berninger, V. (2016) Brain connectivity associated with cascading levels of language. Journal of Systems and Integrative Neuroscience 2 (3). doi:10.15761/JSIN.1000139. Richards, T., Stevenson, J., Crouch, J., Johnson, L.C., Maravilla, K., Stock, P. ... and Berninger, V. (2008) Tract-based spatial statistics of diffusion tensor imaging in adults with dyslexia. American Journal of Neuroradiology 29 (6), 1134–1139. Richards, T.L., Grabowski, T.J., Boord, P., Yagle, K., Askren, M., Mestre, Z. ... and Berninger, V. (2015) Contrasting brain patterns of writing-related DTI parameters, fMRI connectivity, and DTI–fMRI connectivity correlations in children with and without dysgraphia or dyslexia. NeuroImage: Clinical 8, 408–421. Richards, T., Peverly, S., Wolf, A., Abbott, R., Tanimoto, S., Thompson, R. ... and Berninger, V. (2016) Idea units in notes and summaries for read texts by keyboard and pencil in middle childhood students with specific learning disabilities: Cognitive and brain findings. Trends in Neuroscience and Education 5 (3), 146–155. Richlan, F. (2014) Functional neuroanatomy of developmental dyslexia: The role of orthographic depth. Frontiers in Human Neuroscience 8, 347. Richlan, F. (2020) The functional neuroanatomy of developmental dyslexia across languages and writing systems. Frontiers in Psychology 11, 155. Richlan, F., Kronbichler, M. and Wimmer, H. (2009) Functional abnormalities in the dyslexic brain: A quantitative meta-analysis of neuroimaging studies. Human Brain Mapping 30 (10), 3299–3308. Richlan, F., Kronbichler, M. and Wimmer, H. (2011) Metaaanalyzing brain dysfunctions in dyslexic children and adults. Neuroimage 56 (3), 1735–1742. Richlan, F., Kronbichler, M. and Wimmer, H. (2013) Structural abnormalities in the dyslexic brain: A meta-analysis of voxel-based morphometry studies. Human Brain Mapping 34 (11), 3055–3065. Rimrodt, S.L., Peterson, D.J., Denckla, M.B., Kaufmann, W.E. and Cutting, L.E. (2010) White matter microstructural differences linked to left perisylvian language network in children with dyslexia. Cortex 46 (6), 739–749. Rubenstein, K., Matsushita, M., Berninger, V.W., Raskind, W.H. and Wijsman, E.M. (2011) Genome scan for spelling deficits: Effects of verbal IQ on models of transmission and trait gene localization. Behavior Genetics 41 (1), 31–42. Rumsey, J.M., Casanova, M., Mannheim, G.B., Patronas, N., DeVaughn, N., Hamburger, S.D. and Aquino, T. (1996) Corpus callosum morphology, as measured with MRI, in dyslexic men. Biological Psychiatry 39 (9), 769–775. Rumsey, J.M., Andreason, P., Zametkin, A.J., Aquino, T., King, C., Hamburger, S.D., Pikus, A., Rapoport, J.L. and Cohen, R.M. (1992) Failure to activate the left temporoparietal cortex in dyslexia: An oxygen 15 positron emission tomographic study. Archives of Neurology 49 (5), 527–534. Published erratum appears in 51 (3), 243. Sanchez Bloom, J.S., Garcia-Barrera, M.A., Miller, C.J., Miller, S.R. and Hynd, G.W. (2013) Planum temporale morphology in children with developmental dyslexia. Neuropsychologia 51 (9), 1684–1692. Schulte-Körne, G. and Bruder, J. (2010) Clinical neurophysiology of visual and auditory processing in dyslexia: A review. Clinical Neurophysiology 121 (11), 1794–1809. Schumacher, J., Hoffmann, P., Schmäl, C., Schulte-Körne, G. and Nöthen, M.M. (2007) Genetics of dyslexia: The evolving landscape. Journal of Medical Genetics 44 (5), 289–297. Schurz, M., Wimmer, H., Richlan, F., Ludersdorfer, P., Klackl, J. and Kronbichler, M. (2014) Resting-state and task-based functional brain connectivity in developmental dyslexia. Cerebral Cortex 25 (10), 3502–3514. Serrallach, B., Groß, C., Bernhofs, V., Engelmann, D., Benner, J., Gündert, N. ... and Seither, S. (2016) Neural biomarkers for dyslexia, ADHD, and ADD in the auditory cortex of children. Frontiers in Neuroscience 10, 324. Shaywitz, S.E., Shaywitz, B.A., Pugh, K.R., Fulbright, R.K., Constable, R.T., Mencl, W.E. ... and Katz, L. (1998) Functional disruption in the organization of the brain

The Neurobiological Basis of Language Skills and Dyslexia  63

for reading in dyslexia. Proceedings of the National Academy of Sciences 95 (5), 2636–2641. Sihvonen, A.J., Virtala, P., Thiede, A., Laasonen, M. and Kujala, T. (2021) Structural white matter connectometry of reading and dyslexia. NeuroImage 241 (1), 118411. Silani, G., Frith, U., Demonet, J.F., Fazio, F., Perani, D., Price, C. ... and Paulesu, E. (2005) Brain abnormalities underlying altered activation in dyslexia: A voxel based morphometry study. Brain 128 (10), 2453–2461. Simos, P.G., Fletcher, J.M., Bergman, E., Breier, J.I., Foorman, B.R., Castillo, E.M. ... and Papanicolaou, A.C. (2002) Dyslexia-specific brain activation profile becomes normal following successful remedial training. Neurology 58 (8), 1203–1213. Skeide, M.A., Kirsten, H., Kraft, I., Schaadt, G., Müller, B., Neef, N. ... and Friederici, A.D. (2015) Genetic dyslexia risk variant is related to neural connectivity patterns underlying phonological awareness in children. Neuroimage 118, 414–421. Smith, S.D. (2011) Approach to epigenetic analysis in language disorders. Journal of Neurodevelopmental Disorders 3 (4), 356–364. Smith, S.D., Kimberling, W.J., Pennington, B.F. and Lubs, H.A. (1983) Specific reading disability: Identification of an inherited form through linkage analysis. Science 219 (4590), 1345–1347. Spironelli, C., Penolazzi, B., Vio, C. and Angrilli, A. (2006) Inverted EEG theta lateralization in dyslexic children during phonological processing. Neuropsychologia 44 (14), 2814–2821. Stein, M., Winkler, C., Kaiser, A. and Dierks, T. (2014) Structural brain changes related to bilingualism: Does immersion make a difference? Frontiers in Psychology 5, 1116. Steinbrink, C., Ackermann, H., Lachmann, T. and Riecker, A. (2009) Contribution of the anterior insula to temporal auditory processing deficits in developmental dyslexia. Human Brain Mapping 30 (8), 2401–2411. Steinbrink, C., Vogt, K., Kastrup, A., Müller, H.P., Juengling, F.D., Kassubek, J. and Riecker, A. (2008) The contribution of white and gray matter differences to developmental dyslexia: Insights from DTI and VBM at 3.0 T. Neuropsychologia 46 (13), 3170–3178. Swagerman, S.C., Van Bergen, E., Dolan, C., de Geus, E.J., Koenis, M.M., Pol, H.E.H. and Boomsma, D.I. (2017) Genetic transmission of reading ability. Brain and Language 172, 3–8. Tamboer, P., Scholte, H.S. and Vorst, H.C. (2015) Dyslexia and voxel-based morphometry: Correlations between five behavioural measures of dyslexia and gray and white matter volumes. Annals of Dyslexia 65 (3), 121–141. Tan, L.H., Laird, A.R., Li, K. and Fox, P.T. (2005) Neuroanatomical correlates of phonological processing of Chinese characters and alphabetic words: A metaanalysis. Human Brain Mapping 25 (1), 83–91. Tanaka, H., Black, J.M., Hulme, C., Stanley, L.M., Kesler, S.R., Whitfield–Gabrieli, S. ... and Hoeft, F. (2011) The brain basis of the phonological deficit in dyslexia is independent of IQ. Psychological Science 22 (11), 1442–1451. Thiede, A., Virtala, P., Ala-Kurikka, I., Partanen, E., Huotilainen, M., Mikkola, K. ... and Kujala, T. (2019) An extensive pattern of atypical neural speech-sound discrimination in newborns at risk of dyslexia. Clinical Neurophysiology 130 (5), 634–646. Thomas, T., Khalaf, S. and Grigorenko, E.L. (2021) A systematic review and meta-analysis of imaging genetics studies of specific reading disorder. Cognitive Neuropsychology 38 (3), 179–204. Travis, K.E., Leitner, Y., Feldman, H.M. and Ben-Shachar, M. (2015) Cerebellar white matter pathways are associated with reading skills in children and adolescents. Human Brain Mapping 36 (4), 1536–1553. Truong, D.T., Shriberg, L.D., Smith, S.D., Chapman, K.L., Scheer-Cohen, A.R., DeMille, M.M.C., Adams, A.K., Nato, A.Q., Wijsman, E.M., Eicher, J.D. and Gruen, J.R. (2016) Multipoint genome-wide linkage scan for nonword repetition in a multigenerational

64  Part 1: Psychological and Neurobiological Foundations of Language Skills

family further supports chromosome 13q as a locus for verbal trait disorders. Human Genetics 135 (12), 1329–1341. Tschentscher, N., Ruisinger, A., Blank, H., Díaz, B. and Von Kriegstein, K. (2019) Reduced structural connectivity between left auditory thalamus and the motio-sensitive planum temporale in developmental dyslexia. Journal of Neuroscience 39 (9), 1720–1732. Turker, S. (2018) Exploring the neurofunctional underpinnings of dyslexia: A review focusing on dyslexic children. In E. Leuf and M. Marin (eds) The Talking Species: Perspectives on the Evolutionary, Neuronal, and Cultural Foundations of Language (pp. 337–377). Graz: Unipress.  Twait, E., Farah, R. and Horowitz-Kraus, T. (2018) Decreased functional connectivity of the salience network during narrative comprehension in children with reading difficulties: An fMRI study. NeuroImage: Clinical 20, 987–992. Ullman, M.T. (2015) The declarative/procedural model. A neurobiologically motivated theory of first and second language. In B. VanPatten and J. Williams (eds) Theories in Second Language Acquisition: An Introduction (pp. 135–158). London: Routledge. Ullman, M.T. and Pierpont, E.I. (2005) Specific language impairment is not specific to language: The procedural deficit hypothesis. Cortex 41, 399–433. Van der Mark, S., Bucher, K., Maurer, U., Schulz, E., Brem, S., Buckelmüller, J. ... and Brandeis, D. (2009) Children with dyslexia lack multiple specializations along the visual word-form (VWF) system. Neuroimage 47 (4), 1940–1949. Van der Mark, S., Klaver, P., Bucher, K., Maurer, U., Schulz, E., Brem, S. ... and Brandeis, D. (2011) The left occipitotemporal system in reading: Disruption of focal fMRI connectivity to left inferior frontal and inferior parietal language areas in children with dyslexia. Neuroimage 54 (3), 2426–2436. Van Ermingen-Marbach, M., Grande, M., Pape-Neumann, J., Sass, K. and Heim, S. (2013) Distinct neural signatures of cognitive subtypes of dyslexia with and without phonological deficits. NeuroImage: Clinical 2, 477–490. Vanderauwera, J., Vandermosten, M., Dell’Acqua, F., Wouters, J. and Ghesquière, P. (2015) Disentangling the relation between left temporoparietal white matter and reading: A spherical deconvolution tractography study. Human Brain Mapping 36 (8), 3273–3287. Vandermosten, M., Boets, B., Wouters, J. and Ghesquière, P. (2012) A qualitative and quantitative review of diffusion tensor imaging studies in reading and dyslexia. Neuroscience and Biobehavioral Reviews 36 (6), 1532–1552. Vandermosten, M., Boets, B., Poelmans, H., Sunaert, S., Wouters, J. and Ghesquière, P. (2012) A tractography study in dyslexia: Neuroanatomic correlates of orthographic, phonological and speech processing. Brain 135 (3), 935–948. Vandermosten, M., Correia, J., Vanderauwera, J., Wouters, J., Ghesquière, P. and Bonte, M. (2020) Brain activity patterns of phonemic representations are atypical in beginning readers with family risk for dyslexia. Developmental Science 23 (1), e12857. Vandermosten, M., Vanderauwera, J., Theys, C., De Vos, A., Vanvooren, S., Sunaert, S. ... and Ghesquière, P. (2015) A DTI tractography study in pre–readers at risk for dyslexia. Developmental Cognitive Neuroscience 14, 8–15. Vogel, A.C., Miezin, F.M., Petersen, S.E. and Schlaggar, B.L. (2011) The putative visual word form area is functionally connected to the dorsal attention network. Cerebral Cortex 22 (3), 537–549. Volkmer, S. and Schulte-Körne, G. (2018) Cortical responses to tone and phoneme mismatch as a predictor of dyslexia? A systematic review. Schizophrenia Research 191, 148–160. Wang, Y., Mauer, M.V., Raney, T., Peysakhovich, B., Becker, B.L., Sliva, D.D. and Gaab, N. (2016) Development of tract-specific white matter pathways during early reading development in at-risk children and typical controls. Cerebral Cortex 27 (4), 2469–2485. Welcome, S.E. and Joanisse, M.F. (2014) Individual differences in white matter anatomy predict dissociable components of reading skill in adults. NeuroImage 96, 261–275. Williams, V.J., Juranek, J., Cirino, P. and Fletcher, J.M. (2017) Cortical thickness and local gyrification in children with developmental dyslexia. Cerebral Cortex 28 (3), 963–973.

The Neurobiological Basis of Language Skills and Dyslexia  65

Wolf, M. (2007) Proust and the Squid. The Story and Science of the Reading Brain. Translated from the Italian. Wolf, M. (2009) Proust e il calamaro. Storia e scienza del cervello che legge. Milan: Vita e Pensiero. Wolf, R.C., Sambataro, F., Lohr, C., Steinbrink, C., Martin, C. and Vasic, N. (2010) Functional brain network abnormalities during verbal working memory performance in adolescents and young adults with dyslexia. Neuropsychologia 48 (1), 309–318. Wong, B., Yin, B. and O’Brien, B. (2016) Neurolinguistics: Structure, function, and connectivity in the bilingual brain. BioMed Research International 1–22. http://dx.doi. org/10.1155/2016/7069274. Yagle, K., Richards, T., Askren, K., Mestre, Z., Beers, S., Abbott, R. ... and Berninger, V. (2017) Relationships between eye movements during sentence reading comprehension, word spelling and reading, and DTI and fMRI connectivity in students with and without dysgraphia or dyslexia. Journal of Systems and Integrative Neuroscience 3 (1), 1–11. Yan, X., Jiang, K., Li, H., Wang, Z., Perkins, K. and Cao, F. (2021) Convergent and divergent brain structural and functional abnormalities associated with developmental dyslexia. Elife 10, e69523. Yeatman, J.D., Dougherty, R.F., Rykhlevskaia, E., Sherbondy, A.J., Deutsch, G.K., Wandell, B.A. and Ben-Shachar, M. (2011) Anatomical properties of the arcuate fasciculus predict phonological and reading skills in children. Journal of Cognitive Neuroscience 23 (11), 3304–3317. Zadina, J.N., Corey, D.M., Casbergue, R.M., Lemen, L.C., Rouse, J.C., Knaus, T.A. and Foundas, A.L. (2006) Lobar asymmetries in subtypes of dyslexic and control subjects. Journal of Child Neurology 21 (11), 922–931. Zhang, M., Li, J., Chen, C., Xue, G., Lu, Z., Mei, L. ... and Wei, M. (2014) Resting-state functional connectivity and reading abilities in first and second languages. Neuroimage 84, 546–553. Zhao, J., de Schotten, M.T., Altarelli, I., Dubois, J. and Ramus, F. (2016) Altered hemispheric lateralization of white matter pathways in developmental dyslexia: Evidence from spherical deconvolution tractography. Cortex 76, 51–62. Zhou, W., Xia, Z., Bi, Y. and Shu, H. (2015) Altered connectivity of the dorsal and ventral visual regions in dyslexic children: A resting-state fMRI study. Frontiers in Human Neuroscience 9, 495. Zuk, J., Dunstan, J., Norton, E., Yu, X., Ozernov-Palchik, O., Wang, Y. ... and Gaab, N. (2021) Multifactorial pathways facilitate resilience among kindergarteners at risk for dyslexia: A longitudinal behavioral and neuroimaging study. Developmental Science 24 (1), e12983.

2 Late Effects of Early Language Delay on Complex Language and Literacy Abilities: A Clinical Approach to Dyslexia in Subjects with a Previous Language Impairment Claudia Casalini, Daniela Brizzolara, Anna Maria Chilosi, Filippo Gasperini and Chiara Pecini

1 Introduction

Research has recently started to focus on the co-occurrence of different neurodevelopmental disorders rather than solely on the ‘core deficits’ of each of them. The literature shows that in about 40% of children presenting a neurodevelopmental disorder the diagnostic criteria for another disorder can also be met (Gooch et al., 2014). This suggests that ‘pure’ disorders are rare, while comorbidity (that is, the simultaneous presence in the same individual of several disorders, without any causal link between them) is common (Williams & Lind, 2013). Developmental dyslexia (DD), a selective difficulty in the acquisition of reading decoding in spite of normal intelligence, motivation and schooling, is one of the most common neurodevelopmental problems, with prevalence rates ranging from 5 to 15% in children and about 4% in adults (Siegel, 2006). DD is characterized by a high comorbidity both inside the learning disability category (‘homotypic comorbidity’ or a 66

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combination of learning disability subtypes – dyslexia, dysorthography, dysgraphia and dyscalculia) and with other disorders (‘heterotypical comorbidity’; Brimo et al., 2021; Carroll et al., 2005). The neurodevelopmental disorder most frequently found in comorbidity with developmental dyslexia is developmental language disorder (DLD) (e.g. Price et al., 2021), which occurs in about 3–7% of pre-schoolers. It is diagnosed in children over the age of 3–4 who are having difficulties mastering their native language, severe enough to impair their ability to comply with educational and social demands. Children presenting a delay in the onset of language at an early age (18–35 months) in the absence of any known cause (so-called ‘late talkers’, Rescorla & Dale, 2013) are at risk of presenting a developmental language disorder. About one-third of them, in fact, continue to have long-term language difficulties (Rice et al., 2008), especially if the delay extends to language comprehension (Chilosi et al., 2019) or phonological working memory (Petruccelli et al., 2012) and their parents have language impairments or learning disabilities (Bishop et al., 2012). As language is a complex and multidimensional skill changing with age, developmental language disorder can take many forms, and linguistic profiles can change not only among different children but also within the same child in relation to developmental phases. Difficulties often affect language understanding as well as production, and can involve grammatical structure, phonology, lexicon, semantics and pragmatics with different degrees of severity. In many cases language difficulties occur despite adequate neurological, cognitive, emotional, social developmental and educational opportunities for learning language. These characteristics led clinicians to use the term ‘Specific Language Impairment’ (SLI) to mean that the child has no difficulties except with language (Bishop, 1994). By contrast, the recent approach to language disorders is less focused on exclusion criteria as well as on the discrepancy between language skills and non-verbal IQ. It is recognized that, despite the absence of major central nervous system pathologies, language disorder is often associated with fragility even in non-linguistic domains (Brizzolara et al., 2012; Sansavini et al., 2021) or can co-occur with other neurodevelopmental disorders (Redmond, 2016). Thus the ‘umbrella term’ developmental language disorder came into use to better describe multifactorial difficulties affecting language and other cognitive domains (Bishop, 2017). 2 Continuity between Developmental Language Disorder and Developmental Dyslexia

A high comorbidity between DLD and DD has long been described: about 50% of English-speaking DLD children have problems learning to read and write when they go to school (Stackhouse, 2000). This

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fact led some researchers to think that they are manifestations of the same underlying pathology, a ‘language learning impairment’ manifesting itself in different ways at different stages (Catts et al., 2005). However, they can also be dissociated disorders. In agreement with the ‘Multifactorial Probabilistic Model’ of neurodevelopmental disorders (Pennington, 2006), developmental language disorder and developmental dyslexia, although differing for several cognitive deficits and behavioural manifestations, may be separate consequences of common neurobiological and endophenotypic factors. Analogous genetic and anatomical–functional anomalies, interacting with environmental and educational risk factors, may impact on different areas of development, leading to different combinations of cognitive endophenotypes (e.g. underlying deficits in different cognitive abilities) (Ullman et al., 2020) and behavioural phenotypes affecting language and/or reading acquisition (e.g. linguistic abilities and reading performances) (Bishop & Snowling, 2004; Doust et al., 2020; Snowling, Hayiou-Thomas et al., 2020). One of the first explanations of dyslexia is that it arises from a phonological deficit affecting the processing of speech sounds in words (see Vellutino et al., 2004 for a review). Indeed, developmental dyslexic children, just as adult dyslexics (Birch & Chase, 2004), present difficulties in oral language skills and phonological processing at different levels: phonological access, categorization, representation, storage and retrieval of sounds that make up words, or in more basic processes of acoustic/phonetic discrimination (Bailey & Snowling, 2002). Phonological difficulties may in turn seriously hamper the acquisition of reading and decoding abilities, as the beginning reader needs to learn to associate letters to sounds to access whole-word phonological representations (Grainger & Ziegler, 2011; Snowling et al., 2019). However, phonological dysfunction is only one of the possible causes of developmental dyslexia, as it is often characterized by difficulties in other language domains as well as in other cognitive functions and by a high variability of behavioural manifestations (Menghini et al., 2010). In particular, although dyslexia manifests itself in alphabetical and non-alphabetical languages (Chan et al., 2007), behavioural phenotypes of developmental dyslexia can differ in relation to the degree of transparency of the spelling system. Indeed, the specific orthography has been identified as a factor influencing reading acquisition in both typical development and dyslexia (for a review, see Ziegler & Goswami, 2005; see also Palmović et al., Chapter 4, this volume). Transparent orthographies are more easily acquired than opaque and complex writing systems (Borleffs et al., 2017) and phonological processing is more predictive in learning English than other orthographies (Moll et al., 2014) as well as in learning an L2 (Perfetti et al., 2013). Moreover, while in English-speaking dyslexic subjects the phonological processing

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deficit is considered the ‘marker’ of reading impairment (Ramus, 2003), this does not always hold true in shallow orthographies such as Italian (Zoccolotti et al., 1999) or in non-alphabetical languages (Chan et al., 2007). Children with DLD have been considered an interesting case for studying the role of oral language skills in learning to read and to validate the phonological deficit hypothesis of dyslexia (Bishop et al., 2009), even in languages with a transparent orthography such as Italian, in which the phonological processing deficit hypothesis of developmental dyslexia is less strongly supported. Many follow-up studies of children with DLD produced consistent evidence of the continuity between DLD and learning disability (Snowling, Moll et al., 2020). The first clue concerns the persistence of DLD: children of school age having persistent language problems are more likely to develop learning disabilities than children who have overcome their language difficulties by the time of entering school (Bishop & Clarkson, 2003). The risk of children with DLD developing a learning disability is two to three times greater at 6 years of age than among children who had overcome their language difficulties by the same age (Catts et al., 2002), and children with persisting DLD at 5 years of age have difficulty reading at 8 years (Botting et al., 2006). In a previous study (Brizzolara et al., 1999), we investigated written language acquisition in a sample of Italian first- and secondgraders diagnosed with DLD in pre-school. Learning to read and write proceeded at a regular pace in second grade if the children had overcome the linguistic disorder by the time of entering primary school. Children manifesting a linguistic disorder at the beginning of grade one, on the other hand, presented considerable difficulties in the acquisition of the written code in second grade. The type or the severity of the disorder constitutes a second element of continuity between DLD and developmental dyslexia. As already mentioned, linguistic disorders can present heterogeneous characteristics. The DSM-IV classification system (APA, 1994) described three clinical types of DLD according to the linguistic areas affected: mixed-receptive-expressive (RE), expressive (Ex) and phonological (Ph) disorder, the latter selectively affecting the use of speech sounds and phonotactic rules. The DSM-5 (American Psychiatric Association, 2013) diagnostic criteria include two diagnostic labels: language disorders and speech sound disorders (SSD). The former refers to a disturbance of the form, function and/or use of the conventional system of symbols that governs communication, including more or less widespread difficulties in all aspects of expressive and/or receptive language (DLD). The latter refers to a difficulty in articulation, fluency, and quality of voice, with systematic omission, substitution or distortion of phonemes within words that interferes with speech intelligibility.

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The risk of developing a learning disability is greater if the DLD is more severe, extending to multiple linguistic components (Nathan et al., 2004), while SSD children have a more favourable learning outcome (Lewis et al., 2000a; Pennington & Bishop, 2009). In a pioneering work, Bishop and Adams (1990) found that expressive and receptive morphosyntactic competence at 4–5 years were significant predictors of reading outcome at 8 years in a sample of DLD children, while expressive phonology at 5 years accounted for only a small proportion of variance in reading accuracy in third grade. Catts (1993) obtained similar results: only children with more widespread language impairment in kindergarten developed reading difficulties in first grade. In a previous work (Brizzolara, Casalini et al., 2006) we studied the acquisition of literacy skills in DLD Italian children in the first stages of school. Children with RE and Ex disorders, characterized by morphosyntactic and phonological deficits, presented greater difficulties in literacy acquisition than those with isolated Ph disorder, supporting the idea that, in Italian children, impairment in multiple components of language is a risk factor for literacy compared with an isolated phonological impairment. However, the latter, if severe enough (Bird et al., 1995) and still present during the early phases of reading acquisition, might determine difficulties in mapping graphemes to phonemes (Lewis et al., 2000b). Studying the literacy abilities of children with speech sound disorder aged 7–9, Peterson et al. (2009) showed that a history of SSD predicts literacy difficulties only when it is associated with developmental language disorder. Recently, Hayiou-Thomas et al. (2017) led a follow-up study of 245 children tested at one-year intervals aged from 3.5 to 9 years, classifying them into four groups (family-risk-only, language-­i mpairment-only,  family-risk-and-language-impairment, typical development). The results confirmed that children with SSD are not at high risk of reading difficulties unless they present co-occurring problems, such as a family history of literacy problems and language impairment. However, more recently Burgoyne et al. (2019) examined the relationship between speech difficulties at school entry and problems with learning to read, testing the hypothesis that phonological skills explain the relationship between speech and reading difficulties. These authors assessed speech and oral language (expressive vocabulary, receptive grammar and listening comprehension), reading and readingrelated skills (single-word reading, letter-sound knowledge, phoneme awareness, rapid automatized naming) and non-verbal IQ in a large (N = 569) unselected sample of 5-year-old children without a clinical diagnosis of developmental language disorder, just after school entry and after six months. A mediation model demonstrated that the relationship between speech difficulties and later reading was entirely mediated by phoneme awareness: speech difficulties at school entry can be related to

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problems in acquiring phoneme awareness, which in turn are associated with problems in learning to read. Even children who manifested a transient language delay can face scholastic difficulties: follow-up studies found that a high percentage of Late Talkers (LT) show lower language abilities than their typical developing peers (Rescorla & Turner, 2015) and poorer literacy skills (Caglar-Ryeng et al., 2020; Rescorla & Dale, 2013). Early diagnosis and treatment of language disorder are protective factors for the learning outcome. In an unpublished work we compared children who were admitted for treatment when they were LT with children starting treatment when developmental language disorder was manifest. The evolution of literacy skills in the early years of the primary school was better in the early treated group (Casalini et al., 2013). Further evidence of continuity emerges from the study of developmental dyslexia in the most advanced stages of schooling in subjects who have recovered from DLD or have only a subclinical trace of it (Snowling et al., 2000), supporting the ‘illusory recovery hypothesis’ (Scarborough & Dobrich, 1990). For example, Stothard et al. (1998) documented reading and writing difficulties at 15 years, not only among subjects who still had a DLD at 8 years but also among those who, at 8 years, had apparently resolved both oral and written linguistic difficulties, when the demands imposed by reading decoding and comprehension, spelling and written narratives tasks are of increasing linguistic complexity. Long-lasting literacy difficulties have been documented in adolescents previously diagnosed with DLD. For example, Conti-Ramsden et al. (2001) found that when a large group of children who had attended language units when they were 7 were re-tested at 11 years, the difficulties they experienced in oral and written language at the beginning of primary school persisted past middle childhood. Del Tufo and Earle (2020) noted that college students with a history of DLD and/or developmental dyslexia continue to face similar challenges to those they did during childhood. In a study of Italian adolescents diagnosed as DLD in the pre-school years, we documented long-term difficulties in reading and writing skills. Furthermore, these students also exhibited linguistic and phonological working memory (PhWM) difficulties. The learning performances were compromised to a greater degree in those subjects who, during pre-school years, had a language disorder that extended to several components: expressive morphosyntactic and lexical abilities were the best predictors of literacy outcomes in adolescence (Brizzolara, Gasperini et al., 2011). The results of retrospective studies of dyslexic children also support the continuity between DLD and developmental dyslexia. According to our studies, more than 30% of dyslexic children have a history of

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oral language delay and many of them present concomitant linguistic difficulties similar to those of DLD (Brizzolara, Chilosi et al., 2006; Chilosi et al., 2009). Recently, Price et al. (2021) also found a significant association between DD and early language delay, as well as between DD and current language difficulties, both expressive and receptive. However, in many dyslexic children, linguistic deficits may be subtle and not clinically evident. For example, McArthur et al. (2000) documented that over 50% of a large cohort of dyslexics performed below the norm on language tests used to identify DLD. Some studies have also found poor narrative skills in children with developmental dyslexia. Both Westerveld and Gillon (2010) and Kida et al. (2015) found that dyslexic children differed from children with typical reading skills in high-level narrative skills measured by grammatical and lexical diversity and verbal productivity. These difficulties are similar to those manifested by adolescents with a previous developmental language disorder (Wetherell et al., 2007) or by children with a positive history for language delay (Fey  et al., 2004; Girolametto et al., 2001; Miniscalco et al., 2007; Wellmann et al., 2011). Whether such difficulties are the long-term consequence of the language disorder or are partly due to the reduced literacy experience is an open issue (Adlof & Hogan, 2018). To summarize, the reported results of perspective studies on the evolution of children with developmental language disorder when entering school and of retrospective studies documenting previous language difficulties in children with developmental dyslexia, confirm the relationship between the two disorders. However, not all children with dyslexia show previous or concomitant linguistic difficulties, nor do all children with DLD manifest developmental dyslexia. 3 Discontinuity between Developmental Language Disorder and Developmental Dyslexia

The investigation of the cognitive factors shared by children with developmental language disorder and children with developmental dyslexia has contributed to the issue of the continuity and discontinuity between oral and written language difficulties. In previous studies on Italian dyslexic children, we tested the verbal and non-verbal abilities of dyslexics grouped according to whether they had a history of language delay, retrospectively documented through an anamnestic questionnaire. Interestingly, while deficits in a test of ‘rapid automatized naming’ of sequential stimuli (RAN) were shared by most dyslexics, phonological working memory (PhWM) deficits were specifically found in dyslexic children who had previous language delay (Brizzolara, Chilosi et al., 2006; Chilosi et al., 2009). The RAN deficit is considered a ‘marker’ of dyslexia (Norton & Wolf, 2012), as a strong relationship between RAN speed and reading

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fluency has been documented in languages with both inconsistent (Plaza & Cohen, 2003) and consistent (Di Filippo et al., 2005) alphabetic and non-alphabetic orthographies (Liao et al., 2015). Bishop et al. (2009) found that the reduced RAN speed is one of the main cognitive deficits contributing to the continuity between DLD and developmental dyslexia. The result of this study showed that, although most children with DLD also had reading impairments, there was a subgroup that learned to decode quite accurately. They were similar to the ‘DLD-plus-DD’ group on most language measures, but their RAN ability was within normal limits. In an unpublished study (Casalini et al., 2011), we found a strong correlation between RAN and reading skills in the early stages of literacy in a group of Italian DLD children (Mage 7:3), confirming that poor language need not hinder acquisition of decoding as long as RAN is intact. Phonological working memory (PhWM) is another cognitive factor studied both in DLD and developmental dyslexia. PhWM deficits have been frequently described in dyslexia (Snowling, 2008), in DLD (Brizzolara, Casalini et al., 2011), in subjects who recovered from the language disorder (Bishop et al., 1996) and in the parents of DLD children (Bishop et al., 2012). They have long been considered as the causal factors of dyslexia (Peterson & Pennington, 2012), and of DLD (Gathercole & Baddeley, 1990), their behavioural ‘marker’ (ContiRamsden et  al., 2001) and the most probable heritable cause of DLD (Bortolini et al., 2006). PhWM abilities may impact on persistence, extension and typology of the linguistic disorder in DLD children. The severity of PhWM deficits may contribute to the persistence of DLD itself. In the study by Brizzolara et al. (1999), we found that subjects with DLD with persistent linguistic disorders entering primary school, showed greater difficulties in PhWM skills than those who resolved the linguistic deficit earlier. Moreover, the PhWM abilities of children with DLD in pre-school years predicted reading skills in the early stages of literacy (Casalini et al., 2011) and in adolescence (Brizzolara, Gasperini et al., 2011). PhWM may be differently affected in different types of DLD. In two studies we found that DLD children with RE and Ex disorder performed worse in repetition tasks of words (Pecini et al., 2005) and non-words (Casalini et al., 2007) than did DLD children with an isolated Ph deficit. In agreement with this result, Conti-Ramsden and Durkin (2007) reported that poor PhWM abilities in DLD are associated with expressive–receptive deficits and reading difficulties in adolescence, thus suggesting complex interactions between language, memory and literacy across development. Thus, PhWM abilities in DLD children may contribute to their literacy difficulties, playing a relevant role in the emergence of learning impairments beyond decoding difficulties. If phonological

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representations are prone to rapid decay in PhWM, cascading impairments are expected in orthographic–phonological mapping, crucial for the acquisition of letter-sound decoding skills. PhWM can also contribute to the explanation for poor reading comprehension. PhWM difficulties, in fact, could render subjects unable to set up or sustain a sound-based representation of the written text or to process linguistic information working out the semantic and syntactic structure of the sentences (Cain, 2006). Indeed, beside decoding difficulties, some DLD children may struggle to understand what they read even when decoding is accurate. For example, in the study of Bishop et al. (2009), DLD children, characterized predominantly by semantic and syntactic problems, weak vocabulary and poor sentence comprehension, also showed poor memory skills and their reading comprehension was rather poor despite adequate decoding skills. The presence of a PhWM deficit can therefore be interpreted as an element of discontinuity between DLD and developmental dyslexia, as it only characterizes dyslexic people with a history of language delay. All the above-mentioned findings on the phonological and cognitive underpinnings support the ‘Double Deficit Hypothesis’ of developmental dyslexia (Nelson, 2015; Wolf & Bowers, 1999). RAN deficits were found in all developmental dyslexics, while double deficits, both in RAN and PhWM, were found only in those with a previous language delay. The additional deficit in phonological processing may thus result in a more widespread learning disability. 4 Profiles of Developmental Dyslexia + Developmental Language Disorder vs Developmental Dyslexia

A history of developmental language disorder is expressed by a more complex learning disability both at the behavioural and cognitive levels (Cantiani et al., 2015). Children with developmental dyslexia who had DLD can be poorer in reading decoding than dyslexic children who presented a normal linguistic development. As for the latter, they show a deficit in reading speed, which has been considered the marker of dyslexia in transparent orthographies (Wimmer & Schurz, 2010), but they can be significantly less accurate. Some studies found comparable levels of reading accuracy in dyslexic people with and without previous language impairment (Scuccimarra et al., 2008), while others found more severe impairments in reading accuracy in dyslexics with a previous or concurrent language delay (Alt et al., 2019; Chilosi et al., 2003, 2009). Therefore, inaccuracy might be a behavioural marker for dyslexic children who had language problems in the pre-school years, reflecting their phonological processing defects. Moll et al. (2014) demonstrated different patterns of associations among predictors and reading speed,

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reading accuracy and spelling skills: in a way largely comparable across orthographies, RAN is the best predictor of reading speed while phonological processing accounts for higher amounts of variance in reading accuracy and spelling. Moreover, children with developmental dyslexia who presented with DLD are worse than children with dyslexia and typical linguistic development in text understanding, especially in the late stages of development (Brizzolara, Chilosi et al., 2006; Chilosi et al., 2009). Reading comprehension impairment can occur in the absence of poor decoding, suggesting that it may be a distinct disorder. Indeed, the profile of ‘pure’ reading comprehension impairment contrasts with that of dyslexia: ‘poor comprehenders’ are children who can decode and spell accurately but have problems understanding the meaning of what they read (Yuill & Oakhill, 1991). As we know, reading requires the activation of several cognitive processes, some of which are basic, such as recognizing letters and words, whereas others are complex, such as language processing, working memory, making inferences and metacognitive strategies (Nicolielo-Carrilho et al., 2018). By means of all these abilities, subjects can maintain and process information and tie this together into a coherent whole, for understanding a text. Poor comprehenders may experience a wide range of difficulties in the basic processes of language (e.g. grammar, sentence structure and vocabulary knowledge), in higher order linguistic functions (e.g. problems with figurative language), but also in several cognitive and metacognitive factors (e.g. working memory, making inferences, monitoring the text sense, and using metacognitive strategies such as looking back on the text to resolve ambiguity; Cain & Oakhill, 2006). Longitudinal studies suggest that children who go on to be poor comprehenders may have weaknesses in all basic language skills including vocabulary, grammar, syntax and semantic knowledge from an early age (Nation et al., 2010). These findings are not surprising as children with developmental dyslexia and developmental language disorder present not only a failure in the PhWM but also difficulties in linguistic abilities as well as in the use of metacognitive strategies that interfere with their reading comprehension. Bishop and Adams (1992) showed that in developmental language disorder both poor oral literal understanding and inferential skills can affect written comprehension. Bishop et al. (2009) demonstrated that in comparison to DLD children who had impaired reading comprehension but intact decoding skills, those with DLD in comorbidity with dyslexia did significantly poorer on reading comprehension. These data are consistent with a twofold view: reading comprehension depends on both oral language and decoding ability, while oral language skills are more important for reading comprehension than for decoding. Bishop and Snowling (2004) argue that semantic, syntactic and discourse deficits,

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which are widespread in DLD, affect reading comprehension and impair the attainment of fluent reading in adolescence. It seems likely, therefore, that syntactic as well as semantic deficits are implicated in poor reading in DLD, along with problems in using information from the linguistic context and top-down vocabulary knowledge to infer word identities (Nation & Snowling, 2004). In our study of adolescents diagnosed with DLD in pre-school age, text comprehension skills were related to the DLD type at school-age thresholds: subjects with RE-DLD and lexical/ morphosyntactic weaknesses showed the most severe difficulties in written text comprehension. After all, according to the model of ‘simple view of reading’, reading comprehension is the product both of decoding and listening comprehension abilities (Catts et al., 2006; Gough & Tumner, 1986). Early oral language abilities are believed to form the foundation of two pathways into literacy development both of which lead to the acquisition of reading comprehension (Oakhill & Cain, 2012). In the first pathway, oral language abilities affect the development of pre-literacy meta-phonological, phonological, and morphosyntactic skills that are, in turn, involved in decoding and reading comprehension. In the second pathway, continuous influence of oral language abilities fosters linguistic comprehension, which is also known to be essential for reading comprehension (Georgiou et al., 2021). Recently Chilosi et al. (2018) analysed behavioural phenotypes in a sample of 106 dyslexic subjects (Mage 10:8 years), finding that only 18% of them presented a deficit in text comprehension. When differentiated on the basis of a history of language delay, only 14% of subjects without a language delay showed a deficit of text comprehension, while among those with a language delay, 32% had a significant failure in text comprehension. These results support the view that difficulties in text understanding are more typical of children with previous language delay (Snowling, Hayiou-Thomas et al., 2020). Consistent with other studies, the breadth and depth of vocabulary of our developmental dyslexic subjects were significantly associated with text comprehension. The skills measured by the WISC-IV Vocabulary sub-test contributed significantly to explaining differences between dyslexics who had or had not a language delay in text understanding. To summarize, in children with developmental language disorder, there can be both phonological and non-phonological language impairments that affect learning to read: children who enter school with poor phonology are at risk of decoding difficulties, while children with broader language impairments are also at risk of reading comprehension difficulties (Bishop & Snowling, 2004). That is why children with developmental language disorder generally have pervasive reading disorders with both processes affected. Moreover, children with developmental dyslexia who presented with DLD also have worse spelling skills than children with dyslexia who

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presented typical linguistic development (Brizzolara, Chilosi et al., 2006; Chilosi et al., 2003, 2009). This represents another element of difference between DLD and developmental dyslexia. Writing to dictation requires good phonological analysis of the input, good segmentation abilities, maintenance in PhWM of a string of phonemes and knowledge of grammatical morphology. All these abilities are impaired in children with DLD, interfering with the acquisition of writing skills under dictation. Dyslexics with previous language delay differ from those with typical linguistic development for both number and type of spelling errors (Angelelli et al., 2016). The former, in fact, suffer from defective orthographic lexical acquisition together with long-lasting phonological difficulties and produce a higher rate of phonological errors with respect to both the controls and dyslexic children with typical linguistic development. Children with developmental dyslexia with a previous language delay are more sensitive to acoustic–phonological mapping to geminate or non-continuant consonants and to polysyllabic stimuli. Their linguistic difficulties also interfere with their composition of a written text (Dockrell et al., 2012). Finally, neurofunctional studies have investigated the neural sub­strate of developmental dyslexia in subjects with different cognitive and behavioural profiles, demonstrating another element of difference between developmental language disorder and developmental dyslexia. Beside the well-documented abnormalities in the peri-Sylvian areas of the left hemisphere (Benitez-Burraco, 2010), a different neuroanatomical organization has been found to underlie the different clinical phenotypes of developmental dyslexia, depending on the presence or the absence of a history of language delay. In a previous fMRI study (Pecini et al., 2011) we investigated the correlation between the brain representation of phonological processing and the presence/absence of previous language delay in young adults with developmental dyslexia in comparison to typical readers. A reduced activation of a fronto-temporal circuit in the left hemisphere, and in particular of the superior temporal gyrus, was found in all dyslexic subjects (see Ghidoni, Chapter 1, this volume). In contrast, only subjects with a history of language delay showed, with respect to patients with typical linguistic development, a reduced activation in the left inferior and medial frontal gyrus that was associated with worse reading comprehension, spelling and phonological accuracy (Pecini et al., 2011). Patael et al. (2018) investigated the neural basis underlying ‘reading discrepancy’, i.e. the difference between reading comprehension and decoding skills, and demonstrated that an increased grey matter volume in the left dorsolateral prefrontal cortex was associated with higher reading comprehension relative to decoding ability (or ‘cognitive resilience’) in a group of dyslexic subjects. Thus, a frontoparietal network, considered fundamental for the role of working memory and cognitive control as protective factors beyond those related

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to language skills, could represent the ‘brain reserve’ that in subjects with developmental language disorder is in fact scarce. 5 Conclusions

The literature revised so far supports the existence of complex relationships between oral and written language difficulties which change at different stages of development. Rather than being captured by a single deficit model, they may be best conceptualized as multiple interactions between oral language, literacy, and other cognitive abilities as well as some environmental factors (Bishop & Snowling, 2004). Given the complexity of the clinical frameworks due to the relationships among individual, genetic and environmental variabilities, it is indeed difficult to examine each factor in isolation, while studying them in combination is crucial for understanding their reciprocal influence. There is agreement that typical linguistic development is funda­ mental for learning to read and that a disorder in language development can interfere with literacy learning (Snowling & Hulme, 2020). In the case of developmental dyslexics with a previous language delay, the deficit in phonological processing (and possibly also in other linguistic domains) may result in a more profound impairment of reading and writing abilities. The literacy difficulties of these subjects, in fact, are not confined to reading decoding speed as it typically occurs in developmental dyslexia, but extend to inaccurate decoding, spelling and text comprehension. The presence or the absence of a previous language delay and the influence of modulating factors at the cognitive, environmental and neurobiological level may affect the behavioural manifestations of dyslexia, or ‘dyslexias’ (Zoccolotti & Friedmann, 2010). These findings point indeed to the existence of different subtypes of developmental dyslexia, according to which the ‘phonological core deficit hypothesis’ appears plausible when dyslexia is in continuity to language impairment. Rather than in a strict sense, a phonological processing deficit interacting with other risk and protective factors, within both the linguistic and cognitive domains (Snowling & MelbyLervåg, 2016), is part of the endophenotype of dyslexia and increases the risk of literacy difficulties. Phonological working memory deficits might represent ‘the link’ in the continuity between oral language and reading disorders in school-age children, aggravating its expressiveness (‘complex reading–writing disorder’) and persistence in more advanced stages of development. PhWM must be evaluated when studying the origins of literacy problems in dyslexia and developmental language disorder (Gray et al., 2019). New prospective investigations on larger samples of children with developmental language disorder, with specific experimental paradigms evaluating the contribution of linguistic and extra-linguistic abilities to

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the acquisition of specific reading and writing procedures are necessary, both from a clinical and a neurocognitive modelling perspective. According to the clinical perspective, the expressiveness and the complex consequences of the developmental language disorder–developmental dyslexia comorbidity are often underestimated, while they require early diagnostic and rehabilitative care through detailed evaluation procedures. Not only children with developmental language disorder need early intervention to enhance both their linguistic functioning and related skills and to prevent as much as possible the long-term consequences on academic performance (Conti-Ramsden et al., 2019) and the significant ‘cascade effects’ on later complex oral and written linguistic abilities: any child who has speech or language difficulty at school entry should be assessed and monitored for delays in reading development in order to provide early intervention to ameliorate such difficulties (Adlof, 2020; Burgoyne et al., 2019). Furthermore, to identify children who may be at risk of developing a complex learning disability, the diagnosis of dyslexia needs to be integrated by a detailed anamnestic investigation of the history of linguistic problems and by the assessment of oral language, PhWM and RAN skills. Indeed, although to date no single factor can be considered distinctive for early diagnosis, we must remember that, along with familiarity, developmental language disorder is the most reliable predictor of developmental dyslexia. In addition to the ‘first level’ diagnosis, in which the learning disability is identified, a ‘second level’ diagnosis is needed to better qualify a cognitive and behavioural profile and to identify the difficulties in the underlying cognitive functions. Such procedures will help choose the most suitable treatment (Habib, 2020) and limit the impact of the disorder on scholastic success and mental health (Chacko et al., 2013; Pecini et al., 2018, 2019). It is noteworthy indeed that in developmental dyslexia emotional distress in childhood is associated with increased risk for future psychological hardship and social dysfunctionality (Conti-Ramsden et al., 2019; Mammarella et al., 2016; Maughan et al., 2003; Willcutt & Pennington, 2000).

References Adlof, S.M. (2020) Promoting reading achievement in children with developmental language disorders: What can we learn from research on specific language impairment and dyslexia? Journal of Speech, Language, and Hearing Research 63 (10), 3277–3292. Adlof, S.M. and Hogan, T.P. (2018) Understanding dyslexia in the context of developmental language disorders. Language, Speech, and Hearing Services in Schools 49 (4), 762–773. Alt, M., Gray, S., Hogan, T.P., Schlesinger, N. and Cowane, N. (2019) Spoken word learning differences among children with dyslexia, concomitant dyslexia and developmental language disorder, and typical development. Language, Speech, and Hearing Services in Schools 50 (4), 540–561. American Psychiatric Association (1994) Diagnostic and Statistical Manual of Mental Disorders 4th edn (DSM-lV). Washington, DC: APA.

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American Psychiatric Association (2013) Diagnostic and Statistical Manual of Mental Disorders: DSM-5. Washington, DC: APA. Angelelli, P., Marinelli, C.V., Iaia, M., Putzolu, A., Gasperini, F., Brizzolara, D., Chilosi, A.M. (2016) Spelling impairments in Italian dyslexic children with and without a history of early language delay. Are there any differences? Frontiers in Psychology 7, 527. Bailey, P.J. and Snowling, M.J. (2002) Auditory processing and the development of language and literacy. British Medical Bulletin 63 (1), 135–146. Benitez-Burraco, A. (2010) The neurobiology and neurogenetics of dyslexia. Neurologia 25 (9), 563–581. Birch, S. and Chase, C. (2004) Visual and language processing deficits in compensated and uncompensated college students with dyslexia. Journal of Learning Disabilities 37 (5), 389–410. Bird, J., Bishop, D.V.M. and Freeman, N.H. (1995) Phonological awareness and literacy development in children with expressive phonological impairments. Journal of Speech, Language, and Hearing Research 38 (2), 446–462. Bishop, D.V.M. (1994) Is specific language impairment a valid diagnostic category? Genetic and psycholinguistic evidence. Philosophical Transactions Royal Society Series B, 346, 105–111. Bishop, D.V.M. (2017) Why is it so hard to reach agreement on terminology? The case of developmental language disorder (DLD). International Journal of Language and Communication Disorders 52 (6), 671–680. Bishop, D.V.M. and Adams, C. (1990) A prospective study of the relationship between specific language impairment, phonological disorders, and reading retardation. Journal of Child Psychology and Psychiatry 31 (7), 1027–1050. Bishop, D.V.M. and Adams, C. (1992) Comprehension problems in children with specific language impairment: Literal and inferential meaning. Journal of Speech, Language, and Hearing Research 35 (1), 119–129. Bishop, D.V.M. and Clarkson, B. (2003) Written language as a window into residual language deficits: A study of children with persistent and residual speech and language impairments. Cortex 39 (2), 215–237. Bishop, D.V.M. and Snowling, M.J. (2004) Developmental dyslexia and specific language impairment: Same or different? Psychological Bulletin 130 (6), 858–886. Bishop, D.V.M., North, T. and Donlan, C. (1996) Nonword repetition as a behavioural marker for inherited language impairment: Evidence from a twin study. Journal of Child Psychology and Psychiatry 37 (4), 391–403. Bishop, D.V.M., McDonald, D., Bird, S. and Hayiou-Thomas, M.E. (2009) Children who read words accurately despite language impairment: Who are they and how do they do it? Child Development 80 (2), 593–605. Bishop, D.V.M., Holt, G., Line, E., McDonald, D., McDonald, S. and Watt, H. (2012) Parental phonological memory contributes to prediction of outcome of late talkers from 20 months to 4 years: A longitudinal study of precursors of specific language impairment. Journal of Neurodevelopmental Disorders 4 (1), 3. Borleffs, E., Maassen, B.A.M., Lyytinen, H. and Zwarts, F. (2017) Measuring orthographic transparency and morphological-syllabic complexity in alphabetic orthographies: A narrative review. Reading and Writing 30, 1617–1638. Bortolini, U., Arfé, B., Caselli, C.M., Degasperi, L., Deevy, P. and Leonard, L.B. (2006) Clinical markers for specific language impairment in Italian: The contribution of clitics and non-word repetition. International Journal of Language and Communication Disorders 41 (6), 695–712. Botting, N., Simkin, Z. and Conti-Ramsden, G. (2006) Associated reading skills in children with a history of Specific Language Impairment (SLI). Reading and Writing 19, 77–98. Brimo, K., Dinkler, L., Gillberg, C., Lichtenstein, P., Lundström, S. and Åsberg Johnels, J. (2021) The co-occurrence of neurodevelopmental problems in dyslexia. Dyslexia 27 (3), 277–293.

Late Effects of Early Language Delay on Complex Language and Literacy Abilities  81

Brizzolara, D., Casalini, C., Chilosi, A.M. and Pecini, C. (2011) The role of phonological working memory in specific language impairment. In D. Riva, C. Njiokiktjien and S. Bulgheroni (eds) Brain Lesion Localization (pp. 73–86). London: John Libbey Eurotext Ltd. Brizzolara, D., Casalini, C., Sbrana, B., Chilosi, A.M., Cipriani, P. (1999) Memoria di lavoro fonologica e difficoltà di apprendimento della lingua scritta nei bambini con disturbo specifico di linguaggio. Psicologia Clinica dello Sviluppo 3, 465–488 Brizzolara, D., Casalini, C., Chilosi, A.M., Mazzotti, S. and Ferretti, G. (2012) Working memory and attention in children with Specific Language Impairment. RIPLA XII (3), 75–100. Brizzolara, D., Gasperini, F., Pfanner, L., Cristofani, P., Casalini, C. and Chilosi, A.M. (2011) Long-term reading and spelling outcome in Italian adolescents with a history of specific language impairment. Cortex 47, 955–973. Brizzolara, D., Casalini, C., Gasperini, F., Roncoli, S., Mazzotti, S., Cipriani, P. and Chilosi, A.M. (2006) A follow-up study of reading and writing in Italian children with specific language impairment. In D. Riva, I. Rapin and G. Zardini (eds) Language: Normal and Pathological Development (pp. 239–252). Milan: Mariani Foundation. Brizzolara, D., Chilosi, A., Cipriani, P., Di Filippo, G., Gasperini, F., Mazzotti, S. and Zoccolotti, P. (2006) Do phonologic and rapid automatized naming deficits differentially affect dyslexic children with and without a history of language delay? A study of Italian dyslexic children. Cognitive and Behavioural Neurology 19 (3), 141–149. Burgoyne, K., Lervag, A., Malone, S. and Hulme, C. (2019) Speech difficulties at school entry are a significant risk factor for later reading difficulties. Early Childhood Research Quarterly 49, 40–48. https://doi.org/10.1016/j.ecresq.2019.06.005. Cain, K. (2006) Children’s reading comprehension: The role of working memory in normal and impaired development. In S.J. Pickering (ed.) Working Memory and Education (pp. 61–91). Amsterdam: Academic Press. Cain, K. and Oakhill, J. (2006) Profiles of children with specific reading comprehension difficulties. British Journal of Educational Psychology 76 (4), 683–696. Cantiani, C., Lorusso, M.L., Perego, P., Molteni, M. and Guasti, M.T. (2015) Developmental dyslexia with and without language impairment: ERPs reveal qualitative differences in morphosyntactic processing. Developmental Neuropsychology 40 (5), 291–312. Carroll, J.M., Maughan, B., Goodman, R. and Meltzer, H. (2005) Literacy difficulties and psychiatric disorders: Evidence for co-morbidity. Journal of Child Psychology and Psychiatry 46 (5), 524–532. Casalini, C., Brizzolara, D., Chilosi, A.M., Mazzotti, S. and Gasperini, F. (2011) Dal disturbo specifico del linguaggio al disturbo di apprendimento: Ipotesi sulle variabili neuropsicologiche in grado di orientare l’outcome. Atti XX Congresso Nazionale AIRIPA (pp. 150–151). https://www.airipa.it/materiali/ediz-precedenti-congresso-airipa/#. Casalini, C., Chilosi, A.M., Mazzotti, S., Pfanner, L., Salvadorini, R. and Brizzolara, D. (2013) Dal Late-Talker al DSA: Aspetti di continuità e discontinuità. Atti XXII Congresso Nazionale AIRIPA (p. 53). https://www.airipa.it/materiali/ediz-precedenti-congresso-airipa/#. Casalini, C., Brizzolara, D., Cipriani, P., Chilosi, A., Marcolini, S., Pecini, C., Roncoli, S. and Burani, C. (2007) Non-word repetition in children with specific language impairment: A deficit in phonological working memory or in long-term knowledge? Cortex 43 (6), 769–776. Catts, H. (1993) The relationship between speech-language impairments and reading disabilities. Journal of Speech and Hearing Disorders 36 (5), 948–958. Catts, H.W., Adlof, S.M. and Ellis Weismer, S. (2006) Language deficits in poor comprehenders: A case for the simple view of reading. Journal of Speech, Language, and Hearing Research 49 (2), 278–293. Catts, H., Fey, M., Tomblin, J. and Zhang, X. (2002) A longitudinal investigation of reading outcomes in children with language impairments. Journal of Speech, Language, and Hearing Research 45 (6), 1142–1157.

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Catts, H.W., Adlof, S.M., Hogan, T.P. and Weismer, S.E. (2005) Are specific language impairment and dyslexia distinct disorders? Journal of Speech, Language, and Hearing Research 48 (6), 1378–1396. Chacko, A., Uderman, J., Feirsen, N., Bedard, A.C. and Marks, D. (2013) Learning and cognitive disorders: Multidiscipline treatment approaches. Child and Adolescent Psychiatric Clinics of North America 22 (3), 457–477. Chan, D.W., Ho, C.S., Tsang, S., Lee, S. and Chung, K.K.H. (2007) Prevalence, gender ratio and gender differences in reading-related cognitive abilities among Chinese children with dyslexia in Hong Kong. British Journal of Educational Studies 33 (2), 249–265. Chilosi, A.M., Lami, L., Pizzoli, C., Pignatti, B., D’Alessandro, D., Gruppioni, B. et al. (2003) Profili neuropsicologici nella dislessia evolutiva. Psicologia Clinica dello Sviluppo 2, 269–286. Chilosi, A.M., Brizzolara, D., Lami, L., Pizzoli, C., Gasperini, F., Pecini, C. and Zoccolotti, P. (2009) Reading and spelling disabilities in children with and without a history of early language delay: A neuropsychological and linguistic study. Child Neuropsychology 15 (6), 582–604. Chilosi, A., Gasperini, F., Cristofani, P., Dasso, B., Musetti, C., Brovedani, P. and Casalini, C. (2018) Comprensione del testo scritto nei soggetti dislessici con e senza pregresso ritardo del linguaggio. Atti XXVII Congresso Nazionale AIRIPA (p. 114). https://www. airipa.it/materiali/ediz-precedenti-congresso-airipa/#.

Chilosi, A.M., Pfanner, L., Pecini, C., Salvadorini, R., Casalini, C., Brizzolara, D. and Cipriani, P. (2019) Which linguistic measures distinguish transient from persistent language problems in Late Talkers from 2 to 4 years? A study on Italian-speaking children. Research in Developmental Disabilities 89, 59–68. doi: 10.1016/j.ridd.2019.03.005. Epub 2019 Apr 1. Conti-Ramsden, G. and Durkin, K. (2007) Phonological short-term memory, language and literacy: Developmental relationships in early adolescence in young people with SLI. Journal of Child Psychology and Psychiatry 48 (2), 147–156. Conti-Ramsden, G., Botting, N. and Faragher, B. (2001) Psycholinguistic markers for specific language impairment (SLI). Journal of Child Psychology and Psychiatry 42 (6), 741–748. Conti‑Ramsden, G., Mok, P., Durkin, K., Pickles, A., Toseeb, U. and Botting, N. (2019) Do emotional difficulties and peer problems occur together from childhood to adolescence? The case of children with a history of developmental language disorder (DLD). European Child & Adolescent Psychiatry 28 (7), 993–1004. Del Tufo, S.N. and Earle, F.S. (2020) Skill profiles of college students with a history of developmental language disorder and developmental dyslexia. Journal of Learning Disabilities 53 (3), 228–240. Di Filippo, G., Brizzolara, D., Chilosi, A., De Luca, M., Judica, A., Pecini, C., Spinelli, D. and Zoccolotti, P. (2005) Rapid naming, not cancellation speed or articulation rate, predicts reading in an orthographically regular language (Italian). Child Neuropsychology 11 (4), 349–361. Dockrell, J., Connelly, V., Lindsay, G. and Mackie, C. (2012) The impact of oral language skills on children’s production of written text. In M. Torrance, D. Alamargot, M. Castello, F. Ganier, O. Kruse, A. Mangen, L. Tolchinsky and L. VanWaes (eds) Learning to Write Effectively: Current Trends in European Research (pp. 39–41). Bingley: Emerald. Doust, C., Gordon, S.D., Garden, N., Fisher, S.E., Martin, N.G., Bates, T.C. and Luciano, M. (2020) The association of dyslexia and developmental speech and language disorder candidate genes with reading and language abilities in adults. Twin Research and Human Genetics 23 (1), 23–32. doi: 10.1017/thg.2020.7. Epub 2020 Apr 6. Fey, M.E., Catts, H.W., Proctor-Williams, K., Tomblin, J.B. and Zhang, X. (2004) Oral and written story composition skills of children with language impairment. Journal of Speech, Language, and Hearing Research 47 (6), 1301–1318.

Late Effects of Early Language Delay on Complex Language and Literacy Abilities  83

Gathercole, S.E. and Baddeley, A.D. (1990) Phonological memory deficits in languagedisordered children: Is there a causal connection? Journal of Memory and Language 29 (3), 336–360. Georgiou, G.K, Martinez, D., Alves Vieira, A.P., Antoniuk, A., Romero, S. and Guo, K. (2021) A meta-analytic review of comprehension deficits in students with dyslexia. Annals of Dyslexia 2021 Sep 17. https://doi.org/10.1007/s11881-021-00244-y. Online ahead of print. Girolametto, L., Wiigs, M., Smyth, R., Weitzman, E. and Pearce, P.S. (2001) Children with a history of expressive vocabulary delay: Outcomes at 5 years of age. American Journal of Speech-Language Pathology 10 (4), 358–369. Gooch, D., Hulme, C., Nash, H.M. and Snowling, M.J. (2014) Comorbidities in preschool children at family risk of dyslexia. Journal of Child Psychology and Psychiatry 55 (3), 237–246. Gough, P.B. and Tumner, W. (1986) Decoding, reading, and reading disability. Remedial Special Education 7 (1), 6–10. Grainger, J. and Ziegler, J.C. (2011) A dual-route approach to orthographic processing. Frontiers in Psychology 2, Article 54, 1–13. Gray, S., Fox, A.B., Green, S., Alt, M., Hogan, T.P., Petscher, Y. and Cowane, N. (2019) Working memory profiles of children with dyslexia, developmental language disorder, or both. Journal of Speech, Language, and Hearing Research 62, 1839–1858. Habib, M. (2020) Developmental dyslexia: A new look at clinical features and brain mechanisms. Handbook of Clinical Neurology 174, 47–59. Hayiou-Thomas, M.E., Carroll, J.M., Leavett, R., Hulme, C. and Snowling, M.J. (2017) When does speech sound disorder matter for literacy? The role of disordered speech errors, co-occurring language impairment and family risk of dyslexia. Journal of Child Psychology and Psychiatry 58 (2), 197–205. Kida, A.S.B., Bueno, G.J., Lima, V.L.C.C., Rossi, S.G., Nepomuceno, P.F., Martin, M.M.M. et al. (2015) Influência da modalidade de reconto naavaliação do desempenho de escolares em compreenção leitora. Estudos Psicol. 32, 605–615. Lewis, B.A., Freebairn, L.A. and Taylor, H.G. (2000a) Academic outcomes in children with histories of speech sound disorders. Journal of Communication Disorders 33 (1), 11–30. Lewis, B.A., Freebairn, L.A. and Taylor, H.G. (2000b) Follow-up of children with early expressive phonology disorders. Journal of Learning Disabilities 33 (5), 433–444. Liao, C.H., Deng, C., Hamilton, J., Shuk-Ching Lee, C., Wei, W. and Georgiou, G.K. (2015) The role of rapid naming in reading development and dyslexia in Chinese. Journal of Experimental Child Psychology 130, 106–122. Mammarella, I.C., Ghisi, M., Bomba, M., Bottesi, G., Caviola, S., Broggi, F. and Nacinovich, R. (2016) Anxiety and depression in children with nonverbal learning disabilities, reading disabilities, or typical development. Journal of Learning Disabilities 49 (2), 130–139. Maughan, B., Rowe, R., Loeber, R. and Stouthamer-Loeber, M. (2003) Reading problems and depressed mood. Journal of Abnormal Child Psychology 31 (2), 219–229. McArthur, G., Hogben, J., Edwards, V., Heath, S. and Mengler, E. (2000) On the ‘specifics’ of specific reading disability and specific language impairment. Journal of Child Psychology and Psychiatry 41 (7), 869–874. Menghini, D., Finzi, A., Benassi, M., Bolzani, R., Facoetti, A., Giovagnoli, S., Ruffino, M. and Vicari, S. (2010) Different underlying neurocognitive deficits in developmental dyslexia: A comparative study. Neuropsychologia 48 (4), 863–872. Miniscalco, C., Hagberg, B., Kadesjö, B., Westerlund, M. and Gillberg, C. (2007) Narrative skills, cognitive profiles and neuropsychiatric disorders in 7–8-year-old children with late developing language. International Journal of Language and Communication Disorders 42 (6), 665–681. Moll, K., Ramus, F., Bartling, J., Bruder, J., Kunze, S., Neuhoff, N., et al. (2014) Cognitive mechanisms underlying reading and spelling development in five European orthographies. Learning and Instruction 29, 65–77.

84  Part 1: Psychological and Neurobiological Foundations of Language Skills

Nathan, L., Stackhouse, J., Goulandris, N. and Snowling, M.J. (2004) The development of early literacy skills among children with speech difficulties: A test of the ‘critical age hypothesis’. Journal of Speech, Language, and Hearing Research 47 (2), 377–391. Nation, K. and Snowling, M.J. (2004) Beyond phonological skills: Broader language skills contribute to the development of reading. Journal of Research in Reading 27 (4), 342–356. Nation, K., Cocksey, J., Taylor, J.S. and Bishop, D.V.M. (2010) A longitudinal investigation of early reading and language skills in children with poor reading comprehension. Journal of Child Psychology and Psychiatry 51 (9), 1031–1039. Nelson, J.M. (2015) Examination of the double-deficit hypothesis with adolescents and young adults with dyslexia. Annals of Dyslexia 65 (3), 159–177. Nicolielo-Carrilho, A.P., Crenitte, P.A.P., Lopes-Herrera, S.A. and Hage, S.R.V. (2018) Relationship between phonological working memory, metacognitive skills and reading comprehension in children with learning disabilities. Journal of Applied Oral Science 23; 26:e20170414. Norton, E.S. and Wolf, M. (2012) Rapid automatized naming (RAN) and reading fluency: Implications for understanding and treatment of reading disabilities. Annual Review of Psychology 63, 427–452. Oakhill, J.V. and Cain, K. (2012) The precursors of reading ability in young readers: Evidence from a four-year longitudinal study. Scientific Studies of Reading 16 (2), 91–121. Patael, S.Z., Farris, E.A., Black, J.M., Hancock, R., Gabrieli, J.D.E., Cutting, L.E. and Hoeft, F. (2018) Brain basis of cognitive resilience: Prefrontal cortex predicts better reading comprehension in relation to decoding. PLoS ONE 14 June, 13 (6). Pecini, C., Casalini, C., Brizzolara, D., Cipriani, P., Pfanner, L. and Chilosi, A.M. (2005) Hemispheric specialization for language in children with different types of specific language impairment. Cortex 41 (2), 157–167. Pecini, C., Biagi, L., Brizzolara, D., Cipriani, P., Di Lieto, M.C., Guzzetta, A. and Chilosi, A.M. (2011) How many functional brains in developmental dyslexia? When the history of language delay makes the difference. Cognitive and Behavioural Neurology 24 (2), 85–92. Pecini, C., Spoglianti, S., Michetti, S., Bonetti, S., Di Lieto, M.C., Gasperini, F., Cristofani, P., Bozza, M., Brizzolara, D., Casalini, C., Mazzotti, S., Salvadorini, R., Bargagna, S. and Chilosi, A.M. (2018) Tele-rehabilitation in developmental dyslexia: Methods of implementation and expected results. Minerva Pediatrica 70 (6), 529–538. doi: 10.23736/S0026-4946.16.04426-1. Epub 2015 Dec 2. Pecini, C., Spoglianti, S., Bonetti, S., Di Lieto, M.C., Guaran, F., Martinelli, A., Gasperini, F., Cristofani, P., Casalini, C., Salvadorini, R., Mazzotti, S., Bargagna, S., Palladino, P., Cismondo, D., Verga, A., Zorzi, C., Brizzolara, D., Vio, C. and Chilosi, A.M. (2019) Training RAN or reading? A tele-rehabilitation study on developmental dyslexia. Dyslexia 25 (3), 318–331. doi: 10.1002/dys.1619. Epub 2019 May 23. Pennington, B.F. (2006) From single to multiple deficit models of developmental disorders. Cognition 101 (2), 385–413. Pennington, B.F. and Bishop, D.V.M. (2009) Relations among speech, language, and reading disorders. Annual Review of Psychology 60, 283–306. Perfetti, C.A., Cao, F. and Booth, J. (2013) Specialization and universals in the development of reading skill: How Chinese research informs a universal science of reading. Scientific Studies of Reading 17 (1), 5–21. Peterson, R.L. and Pennington, B.F. (2012) Developmental dyslexia. Lancet 379 (9830), 1997–2007. Peterson, R.L., Pennington, B.F., Shriberg, L.D. and Boada, R. (2009) What influences literacy outcome in children with speech sound disorder? Journal of Speech, Language, and Hearing Research 52 (5), 1175–1188. Petruccelli, N., Bavin, E.L. and Bretherton, L. (2012) Children with specific language impairment and resolved late talkers: Working memory profiles at 5 years. Journal of Speech, Language, and Hearing Research 55 (6), 1690–1703.

Late Effects of Early Language Delay on Complex Language and Literacy Abilities  85

Plaza, M. and Cohen, H. (2003) The interaction between phonological processing, syntactic awareness and naming speed in the reading and spelling performance of first-grade children. Brain and Cognition 53, 287–292. Price, K.M., Wigg, K.G., Misener, V.L., Clarke, A., Yeung, N., Blokland, K., Wilkinson, M., Kerr, E.N., Guger, S.L., Lovett, M.W. and Barr, C.L. (2021) Language difficulties in school-aged children with developmental dyslexia. Journal of Learning Disabilities April 2021. doi:10.1177/00222194211006207. Ramus, F. (2003) Developmental dyslexia: Specific phonological deficit or general sensorimotor dysfunction? Current Opinion in Neurobiology 13 (2), 212–218. Redmond, S.M. (2016) Language impairment in the attention-deficit/hyperactivity disorder context. Journal of Speech, Language, and Hearing Research 59 (1), 133–142. Rescorla, L.A. and Dale, P.S. (eds) (2013) Late Talkers: Language Development, Intervention, and Outcomes. Baltimore, MD: Brookes. Rescorla, L. and Turner, H.L. (2015) Morphology and syntax in late talkers at age 5. Journal of Speech, Language, and Hearing Research 58 (2), 434–444. Rice, M.L., Taylor, C.L. and Zubrick, S.R. (2008) Language outcomes of 7-year-old children with or without a history of late language emergence at 24 months. Journal of Speech, Language, and Hearing Research 51 (2), 394–407. Sansavini, A., Favilla, M.E., Guasti, M.T., Marini, A., Millepiedi, S., Di Martino, M.V., Vecchi, S., Battajon, N., Bertolo, L., Capirci, O., Carretti, B., Colatei, M.P., Frioni, C., Marotta, L., Massa, S., Michelazzo, L., Pecini, C., Piazzalunga, S., Pieretti, M., Rinaldi, P., Salvadorini, R., Termine, C., Zuccarini, M., D’Amico, S., De Cagno, A.G., Levorato, M.C., Rossetto, T. and Lorusso, M.L. (2021) Developmental language disorder: Early predictors, age for the diagnosis, and diagnostic tools. A scoping review. Brain Sciences 11, 654. https://doi.org/10.3390/brainsci11050654. Scarborough, H.S. and Dobrich, W. (1990) Development of children with early language delay. Journal of Speech, Language, and Hearing Research 33 (1), 70–83. Scuccimarra, G., Cutolo, L., Fiorillo, P., Lembo, C., Pirone, T., Cossu, G. (2008) Is there a distinct form of developmental dyslexia in children with specific language impairment? Findings from an orthographically regular language. Cognitive Behavioural Neurology 21 (4), 221–226. Siegel, L.S. (2006) Perspectives on dyslexia. Paediatrics and Child Health 11 (9), 581–587. Snowling, M.J. (2008) Specific disorders and broader phenotypes: The case of dyslexia. The Quarterly Journal of Experimental Psychology 61 (1), 142–156. Snowling, M.J. and Melby-Lervåg, M. (2016) Oral language deficits in familial dyslexia: A meta-analysis and review. Psychological Bulletin 142 (5), 498–545. Snowling, M.J. and Hulme, C. (2020) Annual research review: Reading disorders revisited – the critical importance of oral language. Journal of Child Psychology and Psychiatry 62 (5), 635–653, 21 September 2020. doi: 10.1111/jcpp.13324. Online ahead of print. Snowling, M., Bishop, D.V.M. and Stothard, S.E. (2000) Is preschool language impairment a risk factor for dyslexia in adolescence? Journal of Child Psychology and Psychiatry 41 (5), 587–600. Snowling, M.J., Moll, K. and Hulme, C. (2020) Language difficulties are a shared risk factor for both reading disorder and mathematics disorder. Journal of Experimental Child Psychology 202, 105009. doi: 10.1016/j.jecp.2020.105009. Online ahead of print. Snowling, M.J., Hayiou-Thomas, M.E., Nash, H.M. and Hulme, C. (2020) Dyslexia and developmental language disorder: Comorbid disorders with distinct effects on reading comprehension. Journal of Child Psychology and Psychiatry 61 (6), 672–680. Snowling, M.J., Nash, H.M., Gooch, D.C., Hayiou-Thomas, M.E., Hulme, C., Wellcome Language and Reading Project Team. (2019) Developmental outcomes for children at high risk of dyslexia and children with developmental language disorder. Child Development 90 (5), 548–564.

86  Part 1: Psychological and Neurobiological Foundations of Language Skills

Stackhouse, J. (2000) Barriers to literacy development in children with speech and language difficulties. In D.V.M. Bishop and L.B. Leonard (eds) Speech and Language Impairments in Children. Hove: Psychology Press. Stothard, S.E., Snowling, M.J., Bishop, D.V.M., Chipchase, B.B. and Kaplan, C.A. (1998) Language impaired preschoolers: A follow-up into adolescence. Journal of Speech, Language, and Hearing Research 41 (2), 407–418. Ullman, M.T., Sayako Earle, F.,  Walenski, M. and Janacsek, K. (2020) The neurocognition of developmental disorders of language. Annual Review of Psychology 71 (1), 389–417. Vellutino, F.R., Fletcher, J.M., Snowling, M.J. and Scanlon, D.M. (2004) Specific reading disability (dyslexia): What have we learned in the past four decades? Journal of Child Psychology and Psychiatry 45 (1), 2–40. Wellman, R.L., Lewis, B.A., Freebairn, L.A., Avrich, A.A., Hansen, A.J. and Stein, C.M. (2011) Narrative ability of children with speech sound disorders and the prediction of later literacy skills. Language Speech and Hearing Services in Schools 42 (4), 561–579. Westerveld, M.F. and Gillon, G.T. (2010) Profiling oral narrative ability in young schoolaged children. International Journal of Speech-Language Pathology 12 (3), 178–189. Wetherell, D., Botting, N. and Conti-Ramsden, G. (2007) Narrative in adolescent specific language impairment (SLI): A comparison with peers across two different narrative genres. International Journal of Language and Communication Disorders 42 (5), 583–605. Willcutt, E.G. and Pennington, B.F. (2000) Psychiatric comorbidity in children and adolescents with reading disability. Journal of Child Psychology and Psychiatry 41, 1039–1048. Williams, D.M. and Lind, S.E. (2013) Comorbidity and diagnosis of developmental disorders. In C.R. Marshall (ed.) Current Issues in Developmental Disorders (pp. 19–45). London: Psychology Press. Wimmer, H. and Schurz, M. (2010) Dyslexia in regular orthographies: Manifestation and causation. Dyslexia: An International Journal of Research and Practice 16 (4), 283–299. Wolf, M. and Bowers, P.G. (1999) The double-deficit hypothesis for the developmental dyslexias. Journal of Educational Psychology 91(3), 415–438. Yuill, N. and Oakhill, J. (1991) Children’s Problems in Text Comprehension. Cambridge: Cambridge University Press. Ziegler, J.C. and Goswami, U. (2005) Reading acquisition, developmental dyslexia, and skilled reading across languages: A psycholinguistic grain size theory. Psychology Bulletin 131 (1), 3–29. Zoccolotti, P. and Friedmann, N. (2010) From dyslexia to dyslexias, from dysgraphia to dysgraphias, from a cause to causes: A look at current research on developmental dyslexia and dysgraphia. Cortex 46 (10), 1211–1215. Zoccolotti, P., De Luca, M., Di Pace, E., Judica, A., Orlandi, M. and Spinelli, D. (1999) Markers of developmental surface dyslexia in a language (Italian) with high graphemephoneme correspondence. Applied Psycholinguistics 20 (2), 191–216.

3 Foreign Language Learning Difficulties in Developmental Dyslexia: A Narrative Review of the Existing Evidence Filippo Gasperini

1 Introduction

Individuals with developmental dyslexia (DD) experience severe difficulties with accurate and/or fluent reading, and often with spelling, despite possessing intellectual abilities within normal limits, receiving adequate instruction and having no sensory deficits (Lyon et al., 2003). Besides primary problems in basic literacy skills, a variety of other subsidiary symptoms is frequently described among subjects with DD (Ramus, 2004), with more general difficulties in the verbal domain being the most commonly reported. Indeed, a broad consensus has emerged in the last four decades on DD as a language-based disorder (Vellutino et al., 2004), as in most cases its primary underlying deficit is in phonological processing, that is in the processing of sounds in oral language. This is said to interfere with the acquisition of correspondence between letters and sounds, which is the foundation of decoding in reading, at least in alphabetic writing systems. Moreover, varying degrees of impairment have been described for other aspects of language development, such as vocabulary (Cappelli, Chapter 9, this volume) and syntax (Cardinaletti et al., Chapter 8, this volume), in at least a subgroup of DD subjects. If DD often entails phonological problems and can even be conceptualized as a more general language-based disorder, then it should come as no surprise that school difficulties experienced by subjects with DD also include foreign language (FL) learning difficulties. Indeed, FL learning has often been described as especially challenging

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for individuals with DD (Helland & Kaasa, 2005; Miles, 1993; Myer & Ganschow, 1988). However, until recent years much of the evidence supporting FL learning difficulties among DD subjects has been of an anecdotal and predominantly subjective nature and it is only over the last two decades that an adequately objective investigation of FL learning problems in subjects with DD has been systematically undertaken. The goal of the present chapter is to provide a narrative review of the existing empirical studies on FL learning among individuals with DD and to discuss other results, including studies of both other learningdisabled and typically developing subjects that may prove useful in elucidating factors that are relevant in explaining possible different outcomes in FL learning in DD. In the following section, I will document the results of some of the main empirical studies from the last 20 years that have directly investigated FL learning of DD individuals in a variety of different languages. I will then present data from both typically developing and selective FL learning-disabled individuals showing both individualinternal and individual-external factors affecting FL learning. In an attempt to outline some of the main variables that may contribute to different outcomes in FL learning among DD subjects, I will also discuss the influence of different writing systems on the acquisition of literacy skills. In section 4, I integrate the evidence from previous sections to summarize these variables, with a special emphasis on individualinternal factors pertaining to oral skills in the first language. In the subsequent section, I briefly describe the type of approach to teaching FL to those with DD that scholars have predominantly proposed to date and I briefly discuss both the theoretical grounds and empirical support for this method. Lastly, I provide some suggestions for future research on FL learning among subjects with DD. 2 FL Learning Outcome in Subjects with Dyslexia

Downey et al. (2000) is one of the first empirical works investigating FL learning outcome in subjects with DD. It reports on two studies comparing English-speaking college students with and without DD. The participants with DD were enrolled in modified FL classes (Latin or Spanish) designed to meet their specific needs. Control subjects without DD attended regular Latin or Spanish classes. In the first study, the authors compared the measures of FL aptitude of the two groups of learners and found significant differences between the participants with DD and those without. The DD subjects scored much lower in each of the tasks in a battery designed to measure the chances of success in FL learning (Modern Language Aptitude Test; Carroll & Sapon, 1959). This battery of tests assessed several abilities such as the skill of learning arbitrary sound–symbol and phonology–meaning associations and

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the ability to infer the rules governing a set of language materials. The second study compared learners with and without DD on FL outcome results obtained at the end of their second semester of learning Latin. Despite the differences in FL aptitude observed in the participants in the first study, in the second study Downey and colleagues did not find any significant differences in the results attained by the DD students and the controls. Their grades as well as their proficiency in word sight translation from Latin were comparable. While certainly very encouraging, these results cannot be easily generalized to most DD subjects, when considering for example that the sample of Downey and colleagues included English-speaking college students learning Latin, and that the latter’s orthographic system is much more transparent than the English system. We should also consider that the Latin course that the college students attended had been purposely modified in order to meet DD associated specific needs, leaving open the question: Would the same positive outcome have been achieved in a more ‘traditional’ learning setting? However, the possible facilitating role of both the orthographic and instructional variables in explaining DD students’ good outcome in the study of Downey et al. (2000) seems to be challenged by the results of a contemporary study by Miller-Guron and Lundberg (2000). The authors investigated several literacy and phonological processing abilities among young adult Swedish DD students in both their native language and English as a FL in the final year of their basic education. Noting that teachers frequently reported unexpected English facility among Swedish dyslexic students, these authors identified three groups of students with Swedish as a first language. The first group was composed of DD students aged 17–35 with a stated preference for reading English texts rather than Swedish (DEP). The second group, matched by age, educational attainment and word reading ability, was composed of Swedish dyslexics who declared a preference for reading in their native language (DSP), and the third group was a control group of typical readers. While the two DD groups performed significantly worse than the controls and at a similar level on most tests in Swedish, the DEP subjects often obtained higher scores than DSP subjects in both English literacy and phonological tests, in some cases even approaching the level of the control subjects. Miller-Gouron and Lundberg did not report on whether the students with dyslexia received special instruction in English compared to their peers but they described this unexpected superior literacy performance in English rather than in Swedish as the Dyslexic Preference for English Reading (DPER) phenomenon and attempted to explain it by taking into account both orthographic and socio-cultural and emotional factors. As English orthography is more inconsistent than Swedish, DPER might be related to sight word reading strategy. This is the use of a procedure implying a direct recall from verbal long-term

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memory of the entire phonological form of a word once its written visual form has been recognized as a whole. This strategy turns out to be particularly useful when one must learn to read a deep orthography such as English, with many written words whose correct phonology cannot be obtained simply by applying the standard grapheme–phoneme conversion rules (also known as sub-lexical reading). Since phonological abilities are critically involved in sub-lexical reading but significantly impaired in most DD subjects, it is possible that some of the dyslexic readers of a regular orthography, such as the ones in Miller-Guron and Lundberg’s study, can take advantage of a sight word reading strategy to efficiently decode written words in a FL with a deep orthography like English. Such a possibility should be considered in places such as Sweden, where English permeates the child environment from an early age (e.g. through television and popular music), so that children are exposed to a considerable amount of spoken and, to a lesser extent, written English from pre-school age. Moreover, in Sweden, English lessons in the first grades tend to focus more on oral language than on reading and writing tasks. These sociocultural factors make English as a FL learning a positive experience both for normally developing readers and, quite likely, also for DD children, who might increase their self-confidence and feel equal to their peers in approaching English as a school subject. DD subjects in the above studies were students in higher education or at the final stages of secondary education, who represent an already partially selected population of above-average achieving DD individuals, whose FL learning outcome would not be the standard for more typically achieving DD subjects. Such a bias is absent when the subjects are children or adolescents still attending compulsory schooling. Crombie (1997), for example, compared Scottish classmates with and without DD learning French as a FL in the 5th grade to the fourth year at secondary school. First, DD subjects performed significantly lower than controls in both reading and writing French, not only when their literacy skills were evaluated throughout the year but also when they were administered experimental tests of pseudowords in reading and spelling. Even more noteworthy, Crombie’s study showed that DD subjects also had difficulty with FL spoken and listening skills, scoring significantly lower than controls when the ratings for the entire year were considered. Indeed, oral language skills were slightly less impaired than written abilities in the DD group as a whole, but there were substantial individual differences within the group, on each of the four areas considered: reading, writing, listening and speaking. Among oral language abilities, listening tended to be more difficult than speaking for DD subjects, probably because speaking can be conducted at the subject’s own pace, whereas, according to the author, in listening individuals must cope with the speed of whoever is presenting the material. Crombie also noted that

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the performance of both written and oral FL tasks tended to be related to the degree of difficulty they had in learning their first language, and in particular to their level of phonological ability. A methodological limitation of Crombie’s study was the lack of truly experimentally controlled standards of FL skills in the four different areas. Each of them was in fact merely scored on an ordinal scale on the basis of the teachers’ judgements and tested with materials that were only partially the same. A number of subsequent studies has employed more carefully controlled FL tasks and materials when comparing DD and control young learners, and more rigorous and quantitative techniques to analyze the variables contributing to individual differences in FL learning among individuals with DD. For example, proceeding from Miller-Guron and Lundberg’s description of a DPER phenomenon affecting some but not all subjects with DD, van der Leij and Morfidi (2006) conducted experiments to identify a specific factor that could account for a different literacy outcome in English as a FL in a group of Dutch students with DD in the first stages of secondary education. These authors identified two groups of DD subjects on the basis of their good or poor orthographic competence in English, as assessed by an orthographic choice task. Orthographic competence refers to skills related to the processing of letters and letter patterns into words and word parts, which in turn facilitate the acquisition of exact orthographic representations of words for both their rapid recognition and accurate spelling (at least for irregular words). In their study, van der Leij and Morfidi found that, whereas all participants in the study were equally impaired in general phonological processing and reading decoding abilities in their native language, DD subjects with good orthographic competence in English outperformed the group with poor orthographic competence. They obtained results similar to those of normal readers in word and text reading skills in English and were also virtually indistinguishable from the controls in verbal lexical abilities, including oral receptive vocabulary in English and Rapid Automatized Naming (RAN) of digits in both English and Dutch. Conversely, DD subjects with poor orthographic abilities in English performed significantly worse than typical readers in these areas. The authors interpreted these results as indicating that orthographic processing abilities can be a relevant variable in explaining individual differences among DD subjects learning a FL with a deep orthography such as English. In such languages, the use of a sight word reading strategy is favoured over a sub-lexical reading procedure, contrary to what happens in more transparent orthographies (e.g. Dutch). In turn, orthographic processing abilities seemed to be related to intersubjective variability in more basic semantic and RAN abilities, that is, in the fluency of phonological retrieval at a lexical level from long-term memory. This is consistent with many other results from research on cognitive predictors of reading acquisition (Kirby et al., 2010).

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Similarly, Helland and Kaasa (2005) were able to isolate a specific variable with which individuals with DD can be identified and which could explain their different FL learning outcome. They compared a group of Norwegian 12-year-old DD children to an age-matched group of typically developing readers on both oral and written scales of EFL. Results showed highly significant differences between the two groups on all the assessed skills. DDs scored lower than controls not only in English literacy skills (specifically single word reading, spelling and translation) but also in English oral skills, including grammatical comprehension, expressive syntax, morphology, as well as semantics and verbal fluency in both conversation and narrative. However, when DD subjects were divided into two subgroups based on their performance on an oral language comprehension test in their native language, children with DD showed a clear heterogeneity in FL learning. While DD subjects with poor oral comprehension skills continued to perform worse than typically developing readers in both oral and written English tests, DD children with normal language comprehension abilities were indistinguishable from controls in almost all oral FL areas, while scoring lower than typical readers on all English written language tasks (i.e. reading and translation), but to a significantly lesser extent than DDs with poor comprehension skills. This points to the conclusion that DD people displaying both decoding deficits and language comprehension impairment are at risk of developing more serious difficulties in FL learning, which extend to oral language skills. A number of studies employing a range of carefully constructed tests of FL learning, scored according to rigorous quantitative criteria, has recently been conducted on Italian DD children. English learning is a good testing ground for evaluating the impact of the orthographic distance between two alphabetic writing systems on FL acquisition in learners with dyslexia, since unlike Italian, English has one of the least transparent orthographic systems. In a series of studies (Bonifacci et al., 2017; Palladino et al., 2013; Palladino et al., 2016) the literacy skills in English of Italian-speaking dyslexic children enrolled in grades 4 to 7 (9- to 14-year-old learners) were investigated. The children were administered an English word and pseudoword reading aloud test to assess their reading decoding efficiency in the FL. All the real words included in the test were highly familiar to Italian children in those grades, and the pseudowords were constructed according to the rules of regular English phonology. Results first showed that Italian DD children are slower and less accurate than controls in reading English words. In one of these studies (Palladino et al., 2013), the authors highlighted that the severity of the reading impairment in DD children was comparable in the two languages. Other notable results emerging from these studies are those concerning English pseudoword reading. When Italian 4th and 5th primary school graders where examined, children with DD

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underperformed in both accuracy and speed of pseudoword reading compared with typically developing children. However, a rather different picture emerged for 7th and 8th graders with DD (i.e. children enrolled in the second and third years of Italian junior high school). These students were only marginally slower than the controls, but as accurate in reading English pseudowords. Therefore, it seems that after an initial stage in which Italian DD children encounter difficulties in acquiring the general grapheme–phoneme conversion rules of English, within a few years, with much exposure to English teaching and written material, they become able to learn these rules and to apply them to new words as accurately as typically developing children, although not with the same fluency. Palladino et al. (2016) demonstrated poor performance in Italian DD children in spelling highly familiar English words under dictation. Qualitative analyses of their performance indicated a mainly phono­ logical basis for their spelling difficulties. For example, analyses of error type showed a prevalence of phonologically non-plausible over phonologically plausible spelling errors among DD subjects. Bonifacci et al. (2017) also found a significant difference in English reading comprehension between DD children and controls, with the former underperforming the latter. Such a result was not obvious, as there was no significant difference between the two groups on a test of Italian reading comprehension. A possible explanation for this pattern of results can be found if we look at the Simple View of Reading model (Gough & Tunmer, 1986). According to this model the ability to comprehend a written text results from the product of reading decoding skills and oral comprehension (or more general linguistic) abilities. Italian children with DD could achieve adequate reading comprehension in their native language because their relatively good verbal abilities in Italian could compensate for a reading decoding deficit that in most cases is not severe in absolute terms, given the fairly advanced schooling of these subjects. Instead, when performing reading comprehension tasks in English, an already poor general linguistic competence in English might not be sufficient to compensate for additional very low decoding skills in the FL among Italian dyslexics. Impaired performance on both accuracy and fluency experimental measures of EFL reading aloud has recently been demonstrated in both Polish and Spanish children and adolescents with DD if compared to typically developing readers carefully matched for a set of relevant variables (i.e. age, grade, gender, socioeconomic status and intelligence; Łockiewicz & Jaskulska, 2019; Suárez-Coalla et al., 2020). The study on Spanish-speaking children also examined some oral skills. The authors found subjects with DD and controls performed similarly in a task requiring the discrimination of English phonemes. However, the DD children performed worse than controls in a semantic classification task focusing on orally presented English words.

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The research results so far discussed only concern DD subjects whose native and foreign languages both have an alphabetic writing system, i.e. one in which each graphic unit represents a sound at the phonemic level. However, an even more stringent test of the impact of distance between the native and the foreign orthography on FL learning could be provided by studies of DD subjects with an alphabetic writing system learning a non-alphabetic FL (and vice versa). Although research of this type is still scant, a study by Chung and Ho (2010) investigated the learning of English as a FL by a group of Chinese DD children. In effect, while English has an alphabetic writing system, Chinese orthography is considered logographic, i.e. one in which each graphic unit is associated with a morpheme (meaning unit) and represents a syllable of spoken Chinese. Moreover, Chinese is visually much more complex than English or other alphabetic writing systems: there are only 26 letters in English, but around 620 stroke-patterns that make up different Chinese characters. In Chung and Ho’s study a group of DD children aged from 9 to 11 years underperformed compared with an age-matched control group in reading decoding skills in both Chinese and English. Chinese and English reading abilities were strongly associated, so that the severity of reading difficulties in the FL substantially paralleled that found in the native language. Similar impairments in a set of readingrelated cognitive tests in the two languages, including phonological and morphological awareness, orthographic processing and RAN, were shown among DD subjects, with robust cross-language correlations between the same constructs. Hence, results from the study of Ho and colleagues not only show a high association between reading problems in Chinese and English as a FL in the same sample of Chinese DD children but they also provide evidence of a cross-language transfer of deficits in reading-related cognitive skills between these very different writing systems. However, predictors of reading decoding difficulties within each language proved to be only partially overlapping, as morphological awareness, orthographic skills and RAN speed were each significantly associated with reading abilities within both the Chinese and English languages, while phonological awareness contributed to reading difficulties only in English. This would confirm other findings that the latter construct is crucial for learning alphabetic English (Torgesen et al., 1994), while it would be of secondary importance for non-alphabetic Chinese (Ho et al., 2002). 3 Factors Affecting FL Learning in Different Populations

About 30 years ago Sparks and Ganschow revived the speculations posited by researchers such as Pimsleur and Carroll in the 1960s about the importance of native language skills and of a more general language aptitude in FL learning. They proposed the Linguistic

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Coding Differences Hypothesis (LCDH) (Sparks et al., 1989; Sparks & Ganschow, 1993), which is based on the assumption that FL learning is built upon native language skills. According to LCDH, the individual’s ability in the first language’s phonological, syntactic and semantic components serves as the foundation for successful FL learning. In turn, both native and FL learning would depend on basic language mechanisms, among which the sound system of languages and the phonological processing abilities play a particularly important role. In this view, FL learning problems are conceptualized as language problems, because FL learning is primarily a language task. The LCDH has received much empirical support in the last three decades. Research has shown that students who exhibit a specific problem in FL learning also often experience more or less pronounced difficulties in one or more aspects of their native language skills, as well as in FL aptitude (including, for example, the ability to make sound–symbol associations, and difficulties with rote learning and grammatical sensitivity), when compared to control groups of FL good achievers. Among these skills, phonological processing abilities (i.e. sound discrimination, phonological awareness, learning a sound–symbol code and phonological memory) have usually turned out to be those most frequently or profoundly impaired in FL poor achievers, while semantic skills often tend to be spared. Sparks et al. (1992) have described three different profiles of FL learning disabled students on the basis of their differing native language processing abilities. The most common prototypical profile shows weak phonological processing abilities, but syntactic and semantic skills ranging from average to above average. A second, less frequent, prototype shows the opposite profile, with average to good phonological skills but poor syntactic and/or semantic abilities. Finally, the third, less common, prototype describes an FL learning disabled student with across-the-board native language difficulties. According to these authors, because of the negative consequences of phonological difficulties in both FL speech perception and production, students with selective phonological processing impairments are likely to experience immediate problems in the FL classroom, as well as in the acquisition of reading decoding skills. Moreover, impairment in the representation and maintenance of unfamiliar verbal material in the phonological working memory system would hamper the acquisition of new FL vocabulary items. Hence, a primary difficulty with some aspects of phonology may have subsequent, detrimental chain reactions on other components of the linguistic system: for example, lexical and morphosyntactic FL development. As for the second profile, Sparks and Ganschow (1993) report that the primary weakness in semantic abilities hampers oral and written text comprehension, vocabulary knowledge and the production of synonyms and antonyms. These students tend to experience FL learning difficulties a little later than students whose

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main problems lie in phonological skills, particularly when required to comprehend both FL oral and written texts. The linguistic variables considered so far can be mainly regarded as subject-internal factors affecting FL learning, insofar as they depend on individual general aptitude or the ability that a subject can at least partly transfer to FL learning. In addition, there are other variables, substantially independent of the individual but pertaining to his/her environment, that can impact on FL acquisition and that can therefore be considered as subject-external factors influencing FL learning. These factors certainly include some of the intrinsic properties of the FL to be learned. For example, it is now well established that some alphabetical orthographies are easier to learn than others. Comparing reading development in the first two classes of primary school among children of 13 European alphabetic orthographies, Seymour and colleagues (Seymour et al., 2003) found that the acquisition of fundamental reading decoding skills occurred more slowly in Danish and in particular in English than in the other languages. Reading acquisition tended to be rather slow in French- and Portuguese-speaking children, but to be less difficult for languages such as Finnish, Greek and Italian. Very likely, these results are neither related to differences in teaching methods nor to the age at which formal reading instruction begins. According to the authors, the different pace in the acquisition of early reading decoding skills among children of different European countries is a consequence of the fundamental orthographic and phonological differences between their languages. First, reading development would be harder for languages like Danish and especially English, both with ‘deep’ orthographies, which exhibit inconsistencies and complexities in the grapheme–phoneme mapping system, than for languages with ‘shallow’ orthographies, like Greek, Italian and Finnish, where the grapheme– phoneme correspondences are more consistent. Moreover, the rate of reading acquisition would partly depend on the syllabic complexity of the FL. Romance languages, like Italian and French, where open CV syllables are predominant and initial or final consonant clusters are quite infrequent, show a faster rate of reading acquisition than Germanic languages, where the numerous closed CVC syllables and complex consonant clusters conceivably make the identification of individual phonemes harder. Besides properties of the specific FL per se, the linguistic distance between the FL and the speaker’s native language can influence FL learning. As long ago as the 1950s, in his contrastive hypothesis Lado (1957) predicted that differences between first and second language linguistic structures caused difficulty in second language learning (‘negative transfer’), while similarities transfer positively and make it easier to learn a second language. Although subsequent research has not systematically confirmed this hypothesis, there are several

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instances in which its predictions have proved to be at least partially true. Odlin (2003), for example, cites research from Ringbom (1987, 1992) which demonstrates that while the teaching of English as a FL in Finland is very similar for Finnish and Swedish speakers, the latter usually learn English much more easily than the former. The reason for this can be found in the much smaller typological distance between the English and Swedish languages, which are Indo–European and Germanic, than between English and the non-Indo–European Finnish language. A specific instance of the influence of the different linguistic structures between Finnish and Swedish on English learning concerns the prepositional system of these languages: Odlin (2003) reports that while Finnish-speaking subjects frequently omit prepositions that are obligatory in English written narratives, Swedish-speaking subjects never do; this seems directly related to the fact that while Swedish employs prepositions in much the same way as English does, Finnish uses a much larger set of options to indicate the same relationships, most importantly, inflectional morphemes. 4 Factors Affecting FL Learning in Subjects with Dyslexia

Evidence reported in section 2, although quantitatively limited, seems consistent in indicating FL learning as a quite challenging area for individuals with DD. As a group, they tend to underperform controls not only on FL scales of literacy abilities but also on oral language skills. In some studies, spelling tends to be more impaired than reading decoding, which in turn seems more affected than reading comprehension. Deficits in oral language skills are usually less severe than those observed in written language, except for phonological processing skills which tend to be substantially reduced. Contradictory results have been reported regarding the degree of impairment of expressive vs. receptive oral language skills. Severity of reading decoding deficit in the FL would substantially parallel the ones present in the native language, while reading comprehension difficulties in the FL would be greater than those in the mother tongue. Yet, beyond these general trends, most of the available research literature converges to show wide variations among DD subjects in the ease with which they acquire FL skills and in their specific profile of proficiency in different areas of FL learning. When reviewing the studies on FL learning among individuals with DD, and on putative factors explaining FL acquisition in different populations, I highlighted several different variables that can predict different outcomes in FL learning or can influence the rate of acquisition of specific aspects of different languages. These seem to include, for example, a set of different linguistic, metalinguistic and orthographic abilities of the learner in his/her mother tongue. Other variables are probably those related to the differences and similarities between native

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and FL phonological and grammatical properties. Moreover, certain languages would be intrinsically harder than others to learn, at least for some of their specific aspects (i.e. spelling), due for example to the specific nature of their phonological and/or orthographic system. Certainly, these variables are not sufficient to explain the degree of ease in FL learning; therefore other factors need to be taken into account that may affect FL or second language learning. The age of language onset (although effects in opposite directions have been reported for this variable: see, for example, Johnson & Newport (1989) versus Paradis (2011)), second language input quantity and quality (Unsworth, 2016), a variety of sociocultural factors related to the second language (Miller-Guron & Lundberg, 2000), both verbal (Sparks et al., 2006) and non-verbal (Genesee et al., 2004), general intelligence and statistical learning abilities (Frost et al., 2013) are also mentioned as potentially influencing FL outcomes. In line with the current prevailing position on typical and atypical development of continuously distributed behavioural traits of multifactorial origin (Pennington, 2006), FL learning could be seen as the result of the interaction of multiple risk and protective factors. These can be either internal or external to the individual and vary from case to case. The learner’s native language skills, as one of the internal factors, appear to play a particularly important role in the foundation of FL acquisition, since they could be at least partially transferred from one language to the other and could also be considered as an index of a more general language learning aptitude. Among the components of the linguistic system, phonological processing abilities would play a prominent role, influencing directly both FL speech perception and production and indirectly other linguistic domains. This effect would be significantly mediated by literacy skills. If this is so, FL learning difficulties among subjects with DD are easily predictable, as phonological processing difficulties are probably the most commonly reported cognitive deficits among these individuals (Vellutino et al., 2004). Indeed, problems with FL learning are often present in DD, as seen in this chapter, although variable in severity and extent throughout the linguistic system. If such variability could be explained primarily by individual differences in phonological processing skills, such as phonological awareness and short-term memory deficits (cf. recent empirical evidence on both Italian and Polish children and adolescents with DD; cf. Fazio et al., 2020 and Łockiewicz & Jaskulska, 2019), other primary difficulties in different language subsystems (e.g. semantics and grammar) might also contribute. Results from Helland and Kaasa’s study (2005), discussed in section 2, seem to confirm this view. It is now widely accepted that DD is a heterogeneous neurobiological disorder, associated with multiple possible impairments in different cognitive domains (Peterson & Pennington, 2015). For example, over recent years, studies on Italian DD

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individuals have consistently shown that DD with and without a history of previous language delay represents two partially different behavioural phenotypes and cognitive endophenotypes. DD with language delay shows more widespread verbal difficulties, ranging from more serious phonological processing deficits to subtle difficulties in other oral linguistic domains, like semantics and syntax, which worsen accuracy in reading, spelling and written text comprehension (Angelelli et al., 2016; Brizzolara et al., 2009; also Casalini et al., Chapter 2, this volume). Although testing has not yet been carried out, it seems highly plausible that a subgroup of DD children with delayed language acquisition, especially if an overt language impairment is still present, will manifest more severe and pervasive difficulties in FL learning than DD subjects whose verbal difficulties are mainly limited to weak phonological processing abilities or whose cognitive underpinnings are not in the linguistic domain but in the visual–perceptual domain. As regards external factors, the intrinsic properties of the specific FL to be learned should certainly be taken into consideration. I have already cited the data on the influence of both the orthographic and phonological characteristics of different European languages on the rate of reading decoding acquisition by their learners. Similar influences have been documented for reading decoding difficulties of DD subjects. For example, some authors have claimed that, on average, DD children learning an opaque orthography such as English suffer from a much more severe impairment in reading decoding than DD children learning a more consistent writing system, like German, Greek or Italian (Landerl et al., 1997). Indeed, cross-language studies using stimuli that are similar in meaning, spelling and pronunciation but with a different degree of orthographic consistency, have shown that reading accuracy tends to be significantly impaired only in DD children learning opaque orthographies, while the reading speed deficit characterizes DD independently of the orthographic system. By contrast, if grapheme– phoneme relationships are consistent, even DD children can achieve high levels of accuracy in the decoding of written stimuli (Landerl et al., 1997; Ziegler et al., 2003). Based on such results, it appears very likely that different languages can be more or less easily learned by DD subjects and as FLs, according to their properties. Moreover, as already pointed out, beyond the intrinsic characteristics of the specific FL, its relative ‘distance’ from the individual’s native language is another variable probably affecting FL learning in DD subjects. To the best of my knowledge, only one study has directly compared the learning of different FLs in the same sample of DD subjects (van Viersen et al., 2017). In this study, the literacy level of four groups of Dutch secondary school students with and without DD and/or giftedness (i.e. high general intelligence) were compared in both their native language and English, French and German as FLs. In both the DD and the typically reading

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group, when English was the FL, gifted students showed higher reading and spelling levels than their averagely intelligent peers. However, the same pattern was not found in the DD group when the FL was either French or German: gifted students with DD and averagely intelligent students with DD showed a similar performance in the French and German reading and spelling tasks. Differences in results among FLs are explained by the authors on the basis of variations in both orthographic depth and the amount of exposure to the foreign languages. The highly inconsistent English writing system would make the use of a sight word strategy more effective than a grapheme–phoneme decoding strategy for reading and would allow gifted DD individuals from transparent orthographies to develop the former as a compensatory mechanism to improve English reading performance. In turn, the opportunity to develop such a mechanism would be particularly enhanced by a high degree of exposure to both print and spoken language in the case of English, which is omnipresent in Dutch society. By contrast, with the much more consistent French and German orthographies it would not be necessary to develop an alternative compensatory reading strategy, although these languages would be disadvantaged by the students’ limited exposure to them outside the classroom setting, even among gifted DD students.

5 Impact of Teaching Strategies on FL Learning in Individuals with Dyslexia

Among the individual external factors affecting FL learning, the methods of teaching a FL must be considered. However, it is only quite recently that scholars of the educational sciences have described specific approaches and a set of techniques considered to be the most suitable for teaching a FL to DD students (Nijakowska, Chapter 14, this volume; and Nijakowska, 2010; Schneider & Crombie, 2003; Sparks et al., 1991). For these students, the widely used communicative teaching approaches, where the learner is expected to implicitly infer the rules and patterns of the FL from the linguistic input in an immersion natural-like context, are not recommended. The preferred approach to teaching a FL to DD subjects is one which provides direct and explicit instructions of all the rules and concepts related to the various components of the target FL. Such a methodology is traditionally part of the quite popular multi-sensory structured language (MLS) techniques, which have been used in Englishspeaking countries to teach literacy skills in the native language to DD children (cf. Gillingham & Stillman, 1960; Kelly & Phillips, 2011), and in recent decades have also been recommended for FLs (Sparks & Miller, 2000). An MLS approach to teaching a FL involves the simultaneous

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activation of the learner’s sensory channels (auditory, visual, tactile and kinaesthetic), as when for example the teacher models mouth movements for an unfamiliar sound while uttering it and students are asked to imitate him/her. Or when he/she simultaneously writes the corresponding grapheme on the board and the children must pronounce the sound and write the letter using pens or writing with their fingers on a variety of textured surfaces such as sand. For DD students, who often experience phonological processing problems, input provided through all available channels maximizes the chance of successful learning. Moreover, multi-sensory enrichment of verbal information would allow for a multiple and deeper encoding of the same information, leading to better retention in the long-term memory (see Noccetti, Chapter 11, this volume). In the MLS approach, the FL teacher provides opportunities for the student to practise and review a concept frequently, to promote automaticity. MLS lessons are highly structured; subjects are presented in a logical order and follow an ascending order in terms of complexity. A slower pace of instruction is established in which few items per lesson are taught, to avoid confusing the DD learner and to give them opportunities for extra practice and overlearning. The MLS enhances metacognition, as students are asked to reflect on which of the strategies is better suited to their style of learning and which is more appropriate in a specific context. Indeed, while there is some evidence for the benefits of MLS instruction in developing the literacy skills of DD children in their native language (for a review see National Reading Panel, 2000), highquality research supporting the efficacy of using MLS approaches to teaching a FL to DD students is still very sparse. One of the very few adequately controlled empirical studies on the effects of MSL instruction on FL learning among DD individuals is that of Sparks and colleagues (Sparks et al., 1998). In this study the participants were high-school English-speaking students starting to learn Spanish as a FL who were divided into groups according to whether they were or were not at-risk FL learners (not all the at-risk learners had received a DD diagnosis). Findings showed that, after two years of instruction, the at-risk students who were enrolled in an MSL programme significantly outperformed the at-risk students receiving traditional, textbook-based Spanish instruction on most of the FL proficiency tests (reading decoding and comprehension, listening and speaking). In addition, they did not differ on any of the FL assessments from the not-at-risk learners who were instructed using traditional methodologies. While results like these are encouraging, even if they are yet to be confirmed, it is necessary to understand why MSL teaching approaches are effective. Indeed, the same question has already been raised for their use in DD teaching contexts in general, as MSL instruction includes several different components. For example, Fletcher and colleagues

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(Fletcher et al., 2007) observe that traditional multi-sensory elements do not appear to be crucial and they contend that the strengths of such programmes may lie in the use of an intense systematic approach focused on the specific needs of individual students. Though not designed specifically for DD learners, the benefits of multi-modal input presentation to learning, including that of a range of language-related skills in both the native and the FL, have been greatly stressed in the last 20 years by a number of authors, such as Kress and van Leuween (1996) and Schnotz and Baadte (2008). In effect, laboratory research has long demonstrated that multi-sensory exposure typically results in superior retention of information compared to uni-sensory exposure (for a brief review see Noccetti, Chapter 11, this volume; Shams & Seitz, 2008). More recently, the benefits of multi-sensory enrichment on learning have also been empirically demonstrated for FL learning. For example, it has been shown that the acquisition of new FL words is faster when these are enriched with pictures illustrating their meaning or even when the learner performs a gesture appropriate to the word (Repetto et al., 2017). However, sound experimental evidence of such effects has only been provided for typically developing learners so far. 6 Conclusions

A growing body of empirical research in the last 20 years has substantially confirmed FL learning as a challenging area for most individuals with DD. Indeed, while difficulties with FL literacy skills were hardly unexpected, impaired FL learning at the oral language level was not so obvious and, indeed, does not seem to occur with equal frequency or severity. The research reviewed in the present chapter has clearly shown considerable variation among DD individuals in both the degree of FL learning difficulties and the types of difficulties in different areas. It is suggested that, similar to the approach taken towards many other behavioural traits, FL learning should be considered as the probabilistic result of a complex interplay among several risk and protective factors, both internal and external to the individual, each varying largely from case to case. The present chapter has examined the empirical evidence, which presented some of the variables that are found to significantly affect FL learning among DD subjects. It also described other factors that are likely to influence FL learning based on more general research on FL and second language learning including DD. Future investigations into FL learning in DD should continue to search for putative internal factors (linguistic, cognitive and emotional) and external factors (e.g. distinguishing between the different oral and written language components of the FL to be acquired and its distance from the individual’s native language and the sociocultural and instructional elements). Such investigation should first try to verify, and possibly specify

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in more detail, the role of those variables whose effect on FL learning in the case of DD has already been empirically found, for example in the co-occurrence of oral language difficulties in the native language. Moreover, future research should directly test the contribution of factors whose influence on FL learning in DD is mainly theoretically or indirectly plausible (for example, the linguistic distance between the learner’s native language and different FLs). It should also take into consideration possible interaction among the more likely factors, both on theoretical and/ or empirical grounds (for example, the interplay between the cognitive endophenotype of the DD subject and linguistic properties and/or cognitive underpinnings of FLs that vary considerably in their distance from the learner’s native language). A deeper understanding of factors modulating the ease of FL learning across different linguistic components and modalities among DD individuals would have the advantage of informing scholastic policies on evidence-based grounds. This would help to better meet the specific needs of the students and improve FL learning, limiting as much as possible failings and frustrations. Such a tailored approach to FL learning (including which specific FLs would be most suitable) would necessarily imply a preliminary detailed clinical (and educational) evaluation of the DD student’s cognitive and linguistic skills, relating these to the quantitative and qualitative aspects of FL learning. Finally, it seems important to stress the need for more systematic and methodologically rigorous empirical research on the effects of specific techniques in teaching a FL to DD students, as well as the need to define a more evidence-based approach to teaching methodologies. While the use of multi-sensory structured language approaches has been recommended by many special education scholars and teachers, high-quality research evidence for the efficacy of this approach to FL learning among DD individuals is still very scant. Moreover, as multisensory structured language approaches typically encompass several different components, as well as the simultaneous activation of the student’s different sensorial modalities, it would be useful to elucidate which of these different aspects are the most relevant in fostering FL learning among DD individuals and, eventually, which ones are actually ineffective. This, in turn, would allow FL teachers and students to capitalize on truly effective strategies, thus maximizing the chances of more effective and rapid FL learning for subjects with DD. References Angelelli, P., Marinelli, C.V., Iaia, M., Putzolu, A., Gasperini, F., Brizzolara, D. and Chilosi, A.M. (2016) Spelling impairments in Italian dyslexic children with and without a history of early language delay. Are there any differences? Frontiers in Psychology 7, Article 527. Bonifacci, P., Canducci, E., Gravagna, G. and Palladino, P. (2017) English as a foreign language in bilingual language-minority children, children with dyslexia and monolingual typical readers. Dyslexia 23 (2), 181–206.

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Brizzolara, D., Lami, L., Pizzoli, C., Gasperini, F., Pecini, C., Cipriani, P. and Zoccolotti, P. (2009) Reading and spelling disabilities in children with and without a history of early language delay: A neuropsychological and linguistic study. Child Neuropsychology 15, 582–604. Carroll, J. and Sapon, S.M. (1959) Modern Language Aptitude Test (MLAT). New York, NY: Psychological Corporation. Chung, K.K.H. and Ho, C.S.H. (2010) Second language learning difficulties in Chinese children with dyslexia: What are the reading-related cognitive skills that contribute to English and Chinese word reading? Journal of Learning Disabilities 43, 195–211. Crombie, M.A. (1997) The effects of specific learning difficulties (dyslexia) on the learning of a foreign language in school. Dyslexia 3, 27–47. Downey, D.M., Snyder, L.E. and Hill, B. (2000) College students with dyslexia: Persistent linguistic deficits and foreign language learning. Dyslexia 6, 101–111. Fazio, D., Ferrari, L., Testa, S., Tamburrelli, F., Marra, E., Biancardi, M., Palladino, P. and Marzocchi, G. (2020) Second-language learning difficulties in Italian children with reading difficulties. British Journal of Educational Psychology 91 (1), 63–77; first published 17 April 2020. Fletcher, J.M., Lyon, G.R., Fuchs, L.S. and Barnes, M.A. (2007) Learning Disabilities. New York, NY: Guilford. Frost, R., Siegelman, N., Narkiss, A. and Afek, L. (2013) What predicts successful literacy acquisition in a second language? Psychological Science 24, 1243–1252. Genesee, F., Paradis, J. and Crago, M. (2004) Dual Language Development and Disorders. A Handbook on Bilingualism and Second Language Learning. Baltimore, MD: Paul Brooks. Gillingham, A. and Stillman, B. (1960) Remedial Training for Children with Specific Disabilities in Reading, Writing, and Penmanship. Cambridge, MA: Educators Publishing. Gough, P. and Tunmer, W. (1986) Decoding, reading, and reading disability. Remedial and Special Education 7, 6–10. Helland, T. and Kaasa, R. (2005) Dyslexia in English as a second language. Dyslexia 11, 41–60. Ho, C.S.H., Chan, D.W.O., Tsang, S.M. and Lee, S.H. (2002) The cognitive profile and multiple deficit hypothesis in Chinese developmental dyslexia. Developmental Psychology 38, 543–553. Johnson, J.S. and Newport, E.L. (1989) Critical period effects in second language learning: The influence of maturational state on the acquisition of English as a second language. Cognitive Psychology 21, 60–99. Kelly, K. and Phillips, S. (2011) Teaching Literacy to Learners with Dyslexia: A Multisensory Approach. London: Sage. Kirby, J.R., Georgiou, G.K., Martinussen, R., Parrila, R., Bowers, P. and Landerl, K. (2010) Naming speed and reading: From prediction to instruction. Reading Research Quarterly 45, 341–362. Kress, G.R., and van Leeuwen, T. (1996) Reading Images: The Grammar of Visual Design. London & New York: Routledge. Lado, R. (1957) Linguistics Across Cultures. Ann Arbor, MI: University of Michigan Press. Landerl, K., Wimmer, H. and Frith, U. (1997) The impact of orthographic consistency on dyslexia: A German–English comparison. Cognition 63, 315–334. Łockiewicz, M. and Jaskulska, M. (2019) NL reading skills mediate the relationship between NL phonological processing skills and a foreign language (FL) reading skills in students with and without dyslexia: A case of a NL (Polish) and FL (English) with different degrees of orthographic consistency. Annals of Dyslexia 69 (2), 219–242. Lyon, G.R., Shaywitz, S.E. and Shaywitz, B.A. (2003) A definition of dyslexia. Annals of Dyslexia 53, 1–14. Miles, T.R. (1993) Dyslexia: The Pattern of Difficulties (2nd edn). London: Whurr Publishers.

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Miller-Guron, L. and Lundberg, I. (2000) Dyslexia and second language reading: A second bite at the apple. Reading and Writing: An Interdisciplinary Journal 12, 41–61. Myer, B.J. and Ganschow, L. (1988) Profiles of frustration: Second language learners with specific learning disabilities. In J.F. Lalande (ed.) Shaping the Future of Foreign Language Education: FLES, Articulation, and Proficiency. Lincolnwood, IL: National Textbook Company. National Reading Panel (2000) Teaching Children to Read: An Evidence-based Assessment of the Scientific Literature on Reading and its Implication for Reading Instruction. Bethesda, MD: National Institute of Child Health and Human Development. Nijakowska, J. (2010) Dyslexia in the Foreign Language Classroom. Bristol: Multilingual Matters. Odlin, T. (2003) Cross-linguistic influence. In C.J. Doughty and M.H. Long (eds) The Handbook of Second Language Acquisition (pp. 436–86). Malden, MA: Blackwell. Palladino, P., Bellagamba, I., Ferrari, M. and Cornoldi, C. (2013) Italian children with dyslexia are also poor in reading English words, but accurate in reading English pseudowords. Dyslexia 19, 165–177. Palladino, P., Cismondo, D., Bellagamba, I., Ferrari, M. and Cornoldi, C. (2016) L2 spelling errors in Italian children with dyslexia. Dyslexia 22, 158–172. Paradis, J. (2011) Individual differences in child English second language acquisition: Comparing child-internal and child-external factors. Linguistic Approaches to Bilingualism 1, 213–237. Pennington, B.F. (2006) From single to multiple deficit models of developmental disorders. Cognition 101, 385–413. Peterson, R.L. and Pennington, B.F. (2015) Developmental dyslexia. Annual Review of Clinical Psychology 11, 283–307. Ramus, F. (2004) Neurobiology of dyslexia: A reinterpretation of the data. TRENDS in Neurosciences 27, 720–726. Repetto, C., Pedroli, E. and Macedonia, M. (2017) Enrichment effects of gestures and pictures on abstract words in a second language. Frontiers in Psychology 8, 2136. Ringbom, H. (1987) The Role of the First Language in Foreign Language Learning. Clevedon: Multilingual Matters. Ringbom, H. (1992) On L1 transfer in L2 comprehension and production. Language Learning 42, 85–112. Schneider, E. and Crombie, M. (2003) Dyslexia and Foreign Language Learning. Abingdon: David Fulton Publishers. Schnotz, W. and Baadte, C. (2008) Domain learning versus language learning with multimedia. In M.A. Farias and K. Obilinovicm (eds) Aprendizaje Multimodal/ Multimodal Learning (pp. 21–49). Santiago de Chile: Publifahu USACH. Seymour, P.H.K., Aro, M. and Erskine, J.M. (2003) Foundation literacy acquisition in European orthographies. British Journal of Psychology 94, 143–174. Shams, L. and Seitz, A.R. (2008) Benefits of multisensory learning. Trends in Cognitive Sciences 12, 411–417. Sparks, R. and Ganschow, L. (1993) Searching for the cognitive locus of foreign language learning difficulties: Linking first and second language learning. Modern Language Journal 77, 289–302. Sparks, R.L. and Miller, K.S. (2000) Teaching a foreign language using multisensory structured language techniques to at-risk learners: A review. Dyslexia 6, 124–132. Sparks, R., Ganschow, L. and Pohlman, J. (1989) Linguistic coding deficits in foreign language learners. Annals of Dyslexia 39, 179–95. Sparks, R., Ganschow, L., Kenneweg, S. and Miller, K. (1991) Use of an Orton– Gillingham method to teach a foreign language to dyslexic/learning-disabled students: Explicit teaching of phonology in a second language. Annals of Dyslexia 41, 96–118.

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Sparks, R., Ganschow, L., Javorsky, J., Pohlman, J. and Patton, J. (1992) Identifying native language deficits in high- and low-risk foreign language learners in high school. Foreign Language Annals 25 (5), 403–18. Sparks, R., Patton, J., Ganschow, L., Humbach, N. and Javorsky, J. (2006) Native language predictors of foreign language proficiency and foreign language aptitude. Annals of Dyslexia 56, 129–160. Sparks, R., Artzer, M., Patton, J., Ganschow, L., Miller, K., Hordubay, D. and Walsh, G. (1998) Benefits of multisensory structured language instruction for at-risk foreign language learners: A comparison study of high school Spanish students. Annals of Dyslexia 48, 239–270. Suárez-Coalla, P., Martínez-García, C. and Carnota, A. (2020) Reading in English as a foreign language by Spanish children with dyslexia. Frontiers in Psychology 11, 19. Torgesen, J.K., Wagner, R.K. and Rashotte, C.A. (1994) Longitudinal studies of phonological processing and reading. Journal of Learning Disabilities 27, 276–286. Unsworth, S. (2016) Quantity and quality of language input in bilingual language development. In E. Nicoladis and S. Montanari (eds) Bilingualism across the Lifespan: Factors Moderating Language Proficiency (pp. 103–121). Language and the Human Lifespan Series. Washington, DC: American Psychological Association. van der Leij, A. and Morfidi, E. (2006) Core deficit and variable differences in Dutch poor readers learning English. Journal of Learning Disabilities 39, 74–90. van Viersen, S., de Bree, E.H., Kalee, L., Kroesbergen, E.H. and de Jong, P.F. (2017) Foreign language reading and spelling in gifted students with dyslexia in secondary education. Reading and Writing 30, 1173–1192. Vellutino, F.R., Fletcher, J.M., Snowling, M.J. and Scanlon, D.M. (2004) Specific reading disability (dyslexia): What have we learned in the past four decades? Journal of Child Psychology and Psychiatry 45 (1), 2–40. Ziegler, J.C., Perry, C., Ma-Wyatt, A., Ladner, D. and Schulte-Körne, G. (2003) Developmental dyslexia in different languages: Language-specific or universal? Journal of Experimental Child Psychology 86, 169–193.

Part 2: Theoretical and Experimental Linguistic Research on Dyslexia

4 Phonological and Lexical Effects on Reading in Dyslexia Marijan Palmović, Ana Matić Škorić, Mirta Zelenika Zeba and Melita Kovačević

1 Introduction

Almost every definition of dyslexia classifies it as a learning disorder – this includes those of the International Dyslexia Association, the British Dyslexia Association, DSM-5, and WHO-ICD-10, to mention the most commonly used. A brief overview of the research literature gives the same picture: dyslexia is generally categorised as a learning deficit, regardless of the particular theory of dyslexia one upholds and regardless of one’s specific views on whether reading difficulties are symptoms of general sensory, motor or cognitive deficits (e.g. Bishop & Snowling, 2004; Lehongre et al., 2011; Lyon et al., 2003; Nicolson et al., 2002). However, the phonological theory of dyslexia is certainly one of the most influential accounts of dyslexia today (Ramus & Ahissar, 2012), and phonological deficits are indicated as symptoms even by scholars who advocate other theories that try to explain dyslexia by different causal factors (e.g. Chandrasekaran et al., 2009). Languages differ in the way phonological information is represented in their orthographic systems. In a language with an alphabetic system, a child has to learn how to map speech sounds onto graphemes. At this point, the cross-linguistic perspective on dyslexia becomes informative, since reading in different languages requires different word recognition and decoding processes (Katz & Frost, 1992). Transparent orthography in Croatian, which has nearly 1:1 phoneme–grapheme mapping (with only three exceptions: lj [ʎ], nj [ɲ] and dž [ʤ]) and has no irregularities (that is, has no words that would be analogous to the English words island or yacht in terms of their irregular spelling) indicates that spelling errors might not be the decisive factor in recognising dyslexia. Still, different types of difficulties have been reported in individuals with dyslexia who speak and read Croatian, such as sound substitution and 109

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insertion (most often vowels), difficulty reading words that consist of combinations of palatal sounds or sounds written with the graphemes lj [ʎ], nj [ɲ] and dž [ʤ], as well as č [ʧ], ć [ʨ] and đ [ʥ] (Lenček, 2012). Similar to other languages with orthographies more transparent than English, reading speed or fluency has been reported as a factor that distinguishes persons with dyslexia from typical readers in Croatian, as well (Lenček, 2012; for similar results in German, cf. Ziegler & Goswami, 2005). Slower reading speed is traced back to impaired phonological skills, i.e. the ‘phonemic discrimination’ necessary for decoding (Lakuš & Erdeljac, 2012). Children with dyslexia are typically slower at reading lists of words or pseudo-words, as well as performing tasks such as Rapid Automatised Naming (RAN), which is a well-known measure of the ability to retrieve phonological information. These abilities have proven to be good predictors of reading skills and are valid diagnostic criteria in a number of languages (de Jong & van der Leij, 2003; van Daal & van der Leij, 1999; Wimmer, 1993; Wolf et al., 2015). One of the main claims of phonological theory is that dyslexia cannot be explained by some low-level acoustic processing as reported in King et al. (2003) (for a review, see Hämäläinen et al., 2012). The locus of impairment is higher-level language processing, specifically the level of phonological representation. In other words, the cause of the impairment should be sought in the way the brain encodes phonological information (Snowling, 2001; Snowling & Stackhouse, 2006). According to this view, literacy development is based primarily on phonological awareness, the ability to manipulate the phonological structure of words. In this theoretical framework, dyslexia is perceived as a language disorder, not as a learning disorder, and its similarities to other language impairments have been discussed (Bishop & Snowling, 2004; Catts et al., 2005; Casalini et al., Chapter 2, this volume). The processing deficit itself is characterised as a deficit in top-down control of auditory skills (Ramus et al., 2003; Ramus et al., 2013; Snowling, 2001; White et al., 2006) or, put simply, in making sense of auditory input. This involves recognising patterns or sequences of sounds – phonemes – that form syllables and words (Gow & Nied, 2014). Phonotactic constraints describe this patterning of phonetic segments within morphemes, syllables and words (Rossi et al., 2011; Trask, 1996). Not all phonetic segments are equally probable. In any language, some sequences are more probable than others. Phonotactic probabilities refer to the relative frequency of the occurrence of segments (phonemes), and sequences of those segments (phoneme combinations), in syllables and words within a given language (Rispens et al., 2015; Vitevitch & Luce, 1999). Probabilistic correspondences between letters and phonemes, as well as one’s ability to detect regularities that exist between them, have an impact on reading development and language processing (Gabay et al., 2015; Kahta & Schiff, 2016).

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Since individuals with dyslexia exhibit substantial problems in various linguistic domains (categorising speech sounds, establishing sound–letter mappings and manipulating sound sequences), it has been suggested that the primary deficit lies in the basic process of language learning – i.e. in learning the structure of a language from a rich and varied environment. These deficits in learning the distributional information of a language imply deficits in implicit learning (Krishnan et al., 2016). It follows that dyslexia is not just a generalised learning deficit but, rather, a deficit specific to language learning. Deficits in the accuracy with which participants perceive or encode phonological input may accompany deficits in learning the structure of a language. In this sense, implicit learning deficits are consistent with the core phonological deficit account of developmental dyslexia (Gabay et al., 2015). One of the questions that motivated our study was the possibility of linking the phonological theory of dyslexia to understanding dyslexia as a learning deficit in order to give the phonological theory more explanatory power. To achieve this, we must look into the details of phonological processing and be more specific about the learning mechanisms we claim are impaired in dyslexia. We assume that the causal mechanism of dyslexia includes implicit learning, as pointed out by Folia et al. (2008) and Nicolson and Fawcett (1994, 2007), and that phonotactics is a specific part of phonology that is affected. We intend to show that children with dyslexia are unable to obtain phonotactic probability information easily, and therefore cannot use this information to make generalisations that would facilitate the decoding necessary for successful reading. Phonotactic rules differ between world languages, allowing and prohibiting various combinations of phonemes. Possible combinations within a language also differ in their frequency. This makes them good candidates for experimental testing. Research published in Croatian that tackles more theoretical aspects of dyslexia used to be rather scarce but, in the last decade, the number of studies has started to increase. Lenček (2012) discussed deficits on the lexical level, the role of context, and strategies that persons with dyslexia employ. One eye-tracking study pointed to characteristic patterns observed in the eye movements of children with dyslexia during reading (Kuvač Kraljević & Palmović, 2011). Another study used a visual search paradigm with target words belonging to the same or different cohorts, and the same or different semantic fields, showing that children with dyslexia obtained lower results (longer search times) when ‘fine-grained’ phonological information was needed to complete the task and when no semantic information was available as a cue (Drmić & Palmović, 2012). Two doctoral dissertations have tackled dyslexia and phonology at the level of syllable structure and consonant clusters (Kelić, 2017; Zelenika Zeba, 2018). In recent years, we have been investigating the effects of phonotactic probability in children and adults with dyslexia by monitoring their eye movements and detecting brain activity during unconscious sub-lexical

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and lexical processing. The obtained findings suggest deficits at the neuro­ psychological level of learning and processing distributional frequencies of phoneme combinations in language input (Zelenika Zeba, 2018) and indicate that these readers are not able to exploit lexical and phonological information in certain language tasks (Matić et al., 2018). The next step, taken in this study, was to observe these effects on reading per se. 1.1 The study

Our study explores the role of phonotactics in word recognition processes. Its specific aim is to observe the influence of phonotactic probability and word frequency on reading in children with dyslexia. It is envisaged as a study employing a natural reading environment, as close to the common reading of a text in a book as possible. To achieve this goal, we employed two classes of dependent measures, ‘whole-text’ measures and measures applied to specific words, i.e. ‘Areas of Interest’ (AoIs). This approach takes advantage of eye-tracking as a method that provides multiple dependent variables reflecting various aspects of the reading process but which affects experimental control to some extent. The results on the whole-text measures (sometimes called ‘global variables’, cf. Conklin et al., 2018), such as the total number of regressions, are necessarily influenced by all words in the texts, while the AoIs yield a smaller dataset for the statistical analysis. The approach taken in this study is based on the argumentation that implicit learning plays an important role in language acquisition. Children are generally sensitive to statistical information and use phonotactic probabilities to learn word and morpheme boundaries (Kelić & Dressler, 2019; Stokes, 2014; Takač et al., 2016). If the implicit learning mechanism is impaired in children with dyslexia, then they do not adequately master these rules implicitly during acquisition and are therefore more affected by infrequent phonotactic combinations within words during reading. We thus expect the following: (1) More time and processing cost will be required for children with dyslexia to read a text regardless of its phonological and lexical features than for typically developing children to read the same text. Children with dyslexia will be particularly affected by less probable combinations due to their impaired ability to implicitly learn the phonological rules. (2) These effects will tend to decrease towards the end of the text due to contextual facilitation. (3) Word frequency effect will be present in both groups of children. 2 Methodology 2.1 Participants

Twenty-four children were recruited for participation in the study, comprising a group of children with dyslexia and their age-matching

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Table 4.1  Characteristics (gender and age) of both groups of participants included in the study: the group of Children with Dyslexia (DD) and the control group of Typically Developing Children (TD) Gender

Age

Participants (groups)

N

M

F

Mage

SD

Min

Max

DD

10

7

3

9;09

0.39

9;01

10;11

TD

14

6

8

9;06

0.48

9;01

10;07

controls. All children were fourth-grade pupils attending a public elementary school. The group of children with dyslexia (DD) consisted of 10 children (Mage = 9;08, Nmale = 7; Nfemale = 3), while the control group (TD) involved 14 children (Mage = 9;06, Nmale = 6; Nfemale = 8) (Table 4.1). The choice of age was guided by the fact that, between the ages of 9 and 10, children’s reading skills progress from mere decoding to reading for comprehension, and, in this period, reading becomes automatised (e.g. Nippold, 2007). This is also the age when dyslexia is usually diagnosed. All participants had normal or corrected-to-normal vision and were without any history of neurological or psychiatric disease or intellectual disabilities. Socioeconomic status (parental education level and family income) was not controlled for. The principal of the elementary school approved the method with which the study was conducted, and all subsequent procedures were agreed upon with the school’s speech and language pathologist (SLP). Parents signed consent forms that contained a full description of the procedure. The final decision on the participants’ inclusion in the study was made with the SLP, who provided documentation on the cognitive and language skills of all the children whose parents had signed the consent form. Children with dyslexia underwent the usual diagnostic procedures and had previously been diagnosed with dyslexia or reading difficulty in observation (in obs.) by an SLP working at another institution. Most of the children diagnosed with dyslexia had already received education within an individual programme or were in the process of being assigned to one. 2.2 Materials and procedure

Four texts, matched in length (number of words and number of lines), were developed for the purpose of this study. Each text consisted of 72 words. Syntactic complexity was also controlled for – i.e. each text contained more independent than dependent clauses (the ratio being roughly 2:1 in each text). The texts described everyday situations familiar to children: one text was about a birthday party, the second was about animals, the third was about school, and the fourth was about children

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Table 4.2  Characteristics (PP and F) of the target words used in the study (numbers below the words represent the word frequency) High phonotactic probability Texts 1 and 2

Low phonotactic probability Texts 3 and 4

High frequency Text 1

Low frequency Text 2

High frequency Text 3

Low frequency Text 4

rođendan birthday

vrabac sparrow

zvono bell

vršnjaci peers

(54,998)

(5,394)

(12,094)

(2,693)

sreća joy

jastreb hawk

rješenje solution

junakinja hero (f)

(219,941)

(2,817)

(295,062)

(6,360)

Note: The boundary between high- and low-frequency words was 10,000 and was chosen arbitrarily. An English gloss is provided below each Croatian target word.

on a playground. Each text contained two target words controlled for frequency (F) and phonotactic probability (PP). Both F and PP were manipulated on two levels: high and low (see Table 4.2). Word frequency data were taken from the Croatian web corpus hrWac (Ljubešić & Klubička, 2016), while phonotactic probabilities for the Croatian corpus were calculated using Phonology Corpus Tools (PCT; Hall et al., 2016). Context was also taken into consideration by placing one of the target words at the beginning of the text and the other near its end, where there was a greater probability of it being predicted and associated with the previous parts of the story. This makes four experimental conditions in the reading paradigm task, for both the initial and the final word: (1) (2) (3) (4)

High phonotactic probability and high frequency (PP + F +) High phonotactic probability and low frequency (PP + F –) Low phonotactic probability and high frequency (PP – F +) Low phonotactic probability and low frequency (PP – F –)

Accounting for word frequencies, phonotactic probabilities, and context in the two groups of participants resulted in a 2 × 2 × 2 mixed design with a group as a two-level between-group factor, and frequency and phonotactic probability as two-level within-group factors. This analysis was performed separately in both positions (at the beginning and near the end of the text) on dependent variables provided by the eye-tracker (described below), in order to reveal between-group differences in reliance on different phonological, lexical or contextual cues during reading. Experimental procedures were performed at the Laboratory for Psycholinguistic Research, Department of Speech and Language Pathology, University of Zagreb, using an eye-tracker with a chin rest (SMI Hi-Speed iView 500). Each participant was tested individually.

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Figure 4.1  Brief outline of the experimental procedure

After the calibration and a short familiarisation phase, the participants were presented with the randomised text stimuli in succession. After each text, the participants were required to answer a forced-choice comprehension question (by clicking on the correct answer with a mouse). Response accuracy on the four questions was not further analysed. The purpose of asking questions was to keep the readers’ focus and attention, as well as to ensure that all participants were reading for understanding and not just for decoding. The children were previously instructed to read the texts silently for understanding and to press a space bar after they had finished reading. After each text and the related question, a fixation cross appeared on the screen with the purpose of stabilising the participant’s gaze. Each trial lasted around 20 minutes, after which all the children were given refreshments. They also received Thank you notes as certificates of participation. A brief description of the entire procedure is schematically shown in Figure 4.1. 2.3 Data collection and analysis

As an online experimental method, eye-tracking is appropriate for reading studies as it connects visual attention and gaze orientation with incremental sentence processing (Clifton et al., 2007; Van Gompel & Pickering, 2007). Since there is substantial evidence that, from early childhood, eye movements are mediated by language (Sekerina, 2014) and word recognition processes seem to be reflected straightforwardly in eye-movement records (Clifton et al., 2007; Rayner, 1998), the reading paradigm is considered one of the best choices among online methods in developmental and general psycholinguistic studies (Marinis, 2010). The dependent measures that were analysed can be grouped as whole-text based and area-of-interest (AoI) based. The former applies to measures that are based on the whole text and reflect overall reading processes (regressions), while the latter applies to specific words that were controlled for the tested properties – i.e. phonotactic probability and frequency (first fixation duration and dwell time). Additionally, these measures reflect different processes in reading. First fixation duration

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covers the earliest processes, while dwell time reflects later or integrative processes in reading (Reichle et al., 1998; Sedivy, 2010). Dwell time was measured as the gaze duration or the total duration of fixations on the target AoIs (in ms). First fixation duration was measured as the duration of the first fixation in the target AoIs (in ms). Regressions were measured as the total number of regressive eye movements within the whole text. All measures were processed in SMI BeGaze software and further analysed using repeated measures ANOVA. 3 Results and Discussion

The results confirm a clear distinction between the two groups of children: the children with dyslexia (DD) and the control group of participants, i.e. typically developing children (TD). The dispersion of results indicates the presence of a few extreme outliers on some levels of dependent variables. After removing the outliers, the results of the ANOVA did not change considerably. The reported effects were noted after the removal of the extreme outliers. Probability distribution indicates a violation of the assumption of normality for some levels of the examined variables. Furthermore, we examined the residuals by analysing a normal probability plot and a normal quantile plot to test the normality of distributions (Casson & Farmer, 2014). Since the deviations from the straight line were minimal, we concluded that the residuals are normally distributed for all dependent variables. Significant differences between the groups have been obtained on all dependent variables except for the number of regressions (REG) (F[1, 15] = 4.26, p = 0.057, η2p = 0.22) (Table 4.3). This is comparable to a similar eye-tracking study (Hyönä & Olson, 1995), in which word frequency and length were manipulated with the conclusion that the differences in the number of regressions per se could not be used to discriminate between good and poor readers. The main effect of word frequency was obtained on dwell times and regressions but not on first fixation times (Table 4.4). As expected, participants spent less time dwelling on the frequent words than on the infrequent ones, which is indicative of lower processing costs when exposed to familiar lexical items. Contrary to our Table 4.3  Statistically significant differences between the two groups on eye-tracking measures (variables of the study) Df

F

P

η2p

Dwell time on the target word at the beginning of the text (DT1)

1, 12

16.52

0.002

0.58

Dwell time on the target word at the end of the text (DT2)

1, 16

15.18

0.001

0.49

First fixation duration at the beginning of the text (FFD1)

1, 11

4.99

0.047

0.31

First fixation duration at the end of the text (FFD2)

1, 14

10.66

0.006

0.43

Variable

Phonological and Lexical Effects on Reading in Dyslexia  117

Table 4.4  Main effects of word frequency on eye-tracking measures (variables of the study) Df

F

P

η2p

DT1

1, 12

24.30

.05). In order to investigate class performance, Table 8.2 provides the number and percentage of correct answers in the different constructions Table 8.2  Repetition task – general results per class 2nd class

4th class

5th class

Students with DD

TD students

Student with DD

TD Students

Student with DD

TD students

Cleft sentences

5/18 27.7%

59/90 65.5%

6/6 100%

20/78 25.6%

0/6 0%

63/90 70%

Wh-questions

34/36 94.4%

174/180 96.6%

12/12 100%

141/156 90.3%

12/12 100%

177/180 98.3%

Left dislocations

18/18 100%

86/90 95.5%

6/6 100%

74/78 94.8%

6/6 100%

82/90 91.1%

Relative clauses

10/27 37%

68/135 50.3%

5/9 55.5%

75/117 64.1%

2/9 22.2%

79/135 58.5%

Subtotal: experimental sentences

67/99 67.6%

387/495 78.1%

29/33 87.8%

310/429 72.2%

20/33 60.6%

401/495 81%

Control sentences

42/48 87.5%

236/240 98.3%

16/16 100%

203/208 97.6%

16/16 100%

234/240 97.5%

109/147 74.2%

623/735 84.7%

45/49 91.8%

513/637 80.5%

36/49 73.5%

635/735 86.4%

Total

196  Part 2: Theoretical and Experimental Linguistic Research on Dyslexia

distinguishing the different school classes attended by the students (also keeping the distinction between students with DD and TD students). Overall, the comparison between the three classes showed that a significant difference was found only between the TD students in the fourth and fifth classes (Wald Z = 2.552, p = .01). The total scores in the fifth class are significantly higher than those in the fourth class.5 In addition to group analyses, we examined the individual performance of the participants with DD. We compared individual DD scores with the mean score of the TD students and considered DD students who scored more than 1.5 SD below the mean of the controls as having some difficulties with movement-derived structures. We found that in the second class, two participants out of three were 2.6 and 1.9 SD below the mean of the TD students attending the same class, and in the fifth class the student with DD was 2.2 SD below the mean of her classmates. The structures that proved to be most demanding for all students, and especially for those with DD attending the second and fifth classes, were cleft sentences and relative clauses. The student with DD in the fifth class was 2.1 SD below the mean of her classmates in the repetition of relative clauses. Since relative clauses were among the most problematic structures, we now focus on the repetition of these structures. Table 8.3 provides the number and percentage of correctly repeated sentences for each type of relative clause investigated. In the elicited production task, which is focused on relative clauses, results confirm difficulties with this sentence type for students with dyslexia. Table 8.4 shows the number and percentage of target sentences correctly produced by the group of students with DD and the group of TD students for each relative clause type. Overall, the percentages of target relative clauses produced by the DD group are lower than those of the TD group. However, the Table 8.3  Repetition task – results on relative clauses 2nd class

4th class

5th class

Students with DD

TD students

Student with DD

TD students

Student with DD

TD students

3/6 50%

24/30 80%

2/2 100%

18/26 69.2%

2/2 100%

29/30 96.6%

Preposition + genitive relatives

2/6 33.3%

12/30 40%

0/2 0%

19/26 73%

0/2 0%

13/30 43.3%

Preposition + cui

1/3 33.3%

7/15 46.6%

1/1 100%

8/13 61.5%

0/1 0%

7/15 46.6%

Preposition + il quale

4/12 33.3%

25/60 41.6%

2/4 50%

30/52 57.6%

0/4 0%

30/60 50%

Total

10/27 37%

68/135 50.3%

5/9 55.5%

75/117 64.1%

2/9 22.2%

79/135 58.5%

Genitive relatives

Dyslexia and Syntactic Deficits: Overview and a Case Study of Language Training  197

Table 8.4  Elicited production task – general results DD

TD

No.

%

No.

%

Subject relatives

20/20

100%

149/156

96%

Object relatives

1/20

5%

7/156

4%

Indirect object relatives

3/20

15%

39/156

25%

Locative relatives

6/20

30%

87/156

56%

Genitive relatives

1/20

5%

48/156

31%

31/100

31%

330/780

42%

Total

difference between the two groups is only marginally significant (Wald Z = 1.931, p = .054). Subject relatives were the structures with the highest percentage of accuracy for both groups, and a clear asymmetry emerges between subject and object relatives. Pied-piping structures, namely indirect object and locative relatives, which are built with a preposition, and genitive relatives, are particularly problematic, especially for the DD group. However, no significant differences were observed between the two groups in any of the different relative clause types. In order to investigate class performance, Table 8.5 provides the number and percentage of correct target answers in the different relative clause types distinguishing the different school classes to which the students belonged (also keeping the distinction between DD and TD students). Overall, the comparison between the three classes showed that a significant difference was found only between the fourth and fifth classes when considering TD students exclusively (Wald Z = 2.745, p = .006). The scores in the fifth class are significantly higher than those Table 8.5  Elicited production task – general results per class 2nd class

4th class

5th class

Students with DD

TD students

Student with DD

TD students

Student with DD

TD students

Subject relatives

12/12 100%

52/56 92.8%

4/4 100%

50/52 96.1%

4/4 100%

47/48 97.9%

Object relatives

1/12 8.3%

2/56 3.5%

0/4 0%

2/52 3.8%

0/4 0%

3/48 6.2%

Indirect object relatives

2/12 16.6%

15/56 26.7%

1/4 25%

9/52 17.3%

0/4 0%

15/48 31.2%

Locative relatives

2/12 16.6%

30/56 53.5%

2/4 50%

21/52 40.3%

2/4 50%

36/48 75%

Genitive relatives

1/12 8.3%

20/56 35.7%

0/4 0%

11/52 21.1%

0/4 0%

17/48 35.4%

Total

18/60 30%

119/280 42.5%

7/20 35%

93/260 35.7%

6/20 30%

118/240 49.1%

198  Part 2: Theoretical and Experimental Linguistic Research on Dyslexia

in the fourth class.6 We also examined the individual performance of the participants with DD and we found that in the second class, one participant was 2 SD below the mean of the TD students attending the same class in the production of locative relatives. Instead of target relative clauses, which belong to the formal register of Italian, both groups produced non-target correct sentences as in example (7) (TD group 42%; DD group 50%) and ungrammatical sentences as in example (8) (TD group 6.7%; DD group 9%). In examples (7a) and (7d), relative clauses are avoided altogether; subject relatives are produced instead of object (7b), indirect object (7c), or genitive (7e) relatives: (7) a. Tocca il leone con le fauci spalancate. Touch the lion with the jaw wide open Target: Tocca il leone che sta ruggendo. Touch the lion that is roaring b. Tocca il gattino spaventato dal topo. Touch the kitten scared by the mouse Target: Tocca il gattino che il topo spaventa. Touch the kitten that the mouse scares c. Tocca il maiale che riceve una calza rossa piena di dolci. Touch the pig that receives a red sock full of sweets Target: Tocca il maiale a cui il gallo regala una calza rossa piena di dolci. Touch the pig to whom the rooster gives a red sock full of sweets d. Tocca lo scatolone con il lupo all’interno. Touch the carton with the wolf inside Target: Tocca lo scatolone in cui entra un lupo. Touch the carton in which enters the wolf e. Tocca il gemello che ha il coniglio che dorme. Touch the twin that has the rabbit that sleeps Target: Tocca il gemello il cui coniglio dorme. Touch the twin whose rabbit sleeps

In example (8), the relative pronoun is replaced by dove (8a), and the wrong preposition (8b) or the wrong type of relative (8c) is chosen: (8) a. *Tocca il cucciolo dove il suo papà pesca un pesce. Touch the puppy where its dad is fishing a fish Target: Tocca il cucciolo il cui papà pesca un pesce. Touch the puppy whose dad is fishing a fish

Dyslexia and Syntactic Deficits: Overview and a Case Study of Language Training  199

b. *Tocca il tetto nel quale scende lo spazzacamino. Touch the roof in which descends the chimney sweep c. *Tocca il tetto il cui spazzacamino scende. Touch the roof whose chimney sweep descends Target: Tocca il tetto da cui/dal quale scende ... Touch the roof from which descends …

Only students with dyslexia produced relative clauses typical of sloppy or informal registers, with just che (9a), or containing che and dative clitic pronouns (9b, 9c): (9) a. Tocca il papà che il figlio gioca a calcio. Touch the dad that the child plays soccer Target: Tocca il papà il cui figlio gioca a calcio. Touch the dad whose child plays soccer b.  Tocca il maiale che il gallo gli regala una calza rossa piena di dolci. Touch the pig that the rooster dat gives a red sock full of sweets Target: see (7c) c. Tocca il gattino che il cane gli dà un bacio. Touch the kitten that the dog dat gives a kiss Target: Tocca il gattino che il cane lecca. Touch the kitten that the dog licks 3.4 Discussion

In this pilot study, we have focused on the competence of Italian high school students with a diagnosis of dyslexia in the use of complex syntactic structures. Two oral tasks were administered: a sentence repetition task including different types of syntactically complex sentences, and an elicited production task focused on relative clauses. In the repetition task, the percentage of correct sentences repeated by the DD group is significantly lower than that of the TD group. Focusing on sentence types, a significant difference between the two groups was found in the repetition of relative clauses, although relative clauses were also repeated in relatively low percentages by the TD group (see Table 8.1). (A higher percentage of correctly repeated relative clauses, namely 88%, was reached by TD university students aged 23–36, Del Puppo & Volpato, 2016.) The test contains the most complex relatives, namely genitive and prepositional, which belong to the formal register of Italian. Our results are in line with those of Del Puppo et al. (2018), whose group of eleven students with dyslexia aged 16;3–18;9 (Mage = 17;7) only

200  Part 2: Theoretical and Experimental Linguistic Research on Dyslexia

significantly differed from age-peers in the repetition of relative clauses (see section 2). Our results are higher than those of the younger, middle school students with dyslexia analyzed by Del Puppo et al. (2018) (seven students aged 12;2–14;0, Mage = 13;1). Although the number of tested DD students is admittedly low, results from both Del Puppo et al. (2018) and our study suggest that the language competence of individuals with dyslexia improves with increasing age. This should be verified with larger samples. Also, note that the experimental sentences were repeated with lower percentages than the control sentences of the same length (see Tables 8.1 and 8.2). Our results also replicate those of Del Puppo et al. (2018). This suggests that the difficulties observed are not due to limited memory resources but should be attributed to the syntactic properties of experimental sentences. In the elicited production task, object relatives are avoided by all students, replicating previous results on TD adolescents (Volpato, 2010, 2019). The students with dyslexia not only produced fewer relative clauses than their TD age-peers (31% vs. 42%, see Table 8.4), but also produced more ungrammatical sentences and sentences typical of sloppy or informal registers. Note that the student with dyslexia attending the fourth class (twelfth grade), who performed better than the other students with dyslexia and repeated the complex sentences correctly most of the time (87.8%, see Table 8.2), failed, however, in the two most complex structures, namely the prepositional genitive relatives, which he did not repeat at all, and the indirect object relatives with agreeing il quale, which he repeated 50% of the time (see Table 8.3). In the elicited production task, he produced subject relatives instead of object relatives, on a par with his age-peers. However, he did not produce any genitive relative (see Table 8.5), which were always replaced by two subject relatives, as in (7e). Furthermore, he never produced the agreeing relative pronoun il quale, but always the non-agreeing form cui, different from the younger and older TD students. The analysis of the individual performance showed that some participants (3 in the repetition task and 1 in the production task) scored more than 1.5 SD below the mean of the controls. This suggests that these students have difficulties with syntactically complex sentences in oral tasks. Relative clauses, in particular prepositional and genitive, are especially demanding for these students. Syntactic difficulties may be due to an unrecognized DLD which manifests itself in the most complex sentences, and/or to the fact that these constructions are typical of the formal register, mainly learnt through reading, which is particularly demanding for students with DD. More data are needed to answer the question of the source of syntactic difficulties in individuals with dyslexia. What is clear is that difficulties with structures typical of the

Dyslexia and Syntactic Deficits: Overview and a Case Study of Language Training  201

formal register may make it challenging for these individuals to read and comprehend academic texts. 4 Language Training on Relative Clauses: A Case Study

One of the students with dyslexia in the second class (age 15;2) was administered a specific syntactic training on relative clauses. This student showed poor performance in both tasks. In particular, his performance in the repetition task was lower than the group of students with dyslexia in his class in wh-questions and relative clauses; it was also lower in control sentences (see Table 8.6 below). Syntactic training was modelled on Levy and Friedmann’s (2009) syntactic intervention administered to a 12;2 year-old Hebrewspeaking adolescent with a diagnosis of learning difficulty (‘significant reading comprehension impairment’), who turned out also to have a syntactic-DLD after assessment with oral comprehension, repetition, and production of constructions derived by syntactic movement. While he had normal performance in lexical, phonological, and verb argument structure tasks, he was poorer than the age-matched control group in relative clauses, focalizations, wh-questions, and sentences with verb movement.7 Levy and Friedmann’s (2009) syntactic intervention lasted six months. In our case, the syntactic training was administered during the months of April and May 2017, after the elicited production task, and was composed of eleven 90-minute sessions. The first session was devoted to the discussion of verb argument structure and the different verb classes depending on the number and type of arguments. In the second session, thematic theory was introduced, namely the property that all and only the arguments selected by the verb appear in the sentence. Sentences may not lack an obligatory argument of the verb (*Maria ama ‘Maria loves’), nor can they contain more arguments than they should (*Maria ama Gianni Table 8.6  Repetition task – general results 2nd class: Student with DD

2nd class Students with DD

TD Students

Before Training

After Training

Cleft sentences

5/18 27.7%

59/90 65.5%

2/6 33%

3/6 50%

Wh-questions

34/36 94.4%

174/180 96.6%

9/12 75%

12/12 100%

Left dislocations

18/18 100%

86/90 95.5%

6/6 100%

6/6 100%

Relative clauses

10/27 37%

68/135 50.3%

2/9 22%

7/9 78%

67/99 67.6%

387/495 78.1%

19/33 58%

28/33 85%

42/48 87.5%

236/240 98.3%

13/16 81%

16/16 100%

109/147 74.1%

623/735 84.7%

32/49 65%

44/49 90%

Subtotal: experimental sentences Control sentences Total

202  Part 2: Theoretical and Experimental Linguistic Research on Dyslexia

la musica ‘Maria loves Gianni the music; *Maria ride zucchero ‘Maria laughs sugar’). The crucial role of the verb was illustrated via a theatre backstage video: the stage director selects the actors and coordinates each actor’s work. Similarly, the lexical properties of the verb specify how many arguments should appear in the sentence and which syntactic category they have (noun phrase, prepositional phrase, clause, etc.). In the next seven sessions, the syntactic derivation of relative clauses was illustrated through card games. Movement of constituents was shown from one position to another position in the sentence. The seven sessions were organized as follows: relative clauses on the subject and the object (two sessions), the indirect object (one session), the locative argument (two sessions), and genitive relative clauses (two sessions). One session was devoted to re-cap activities. In the last session, the sentence repetition and elicited production tasks were administered again. 4.1 Results

In this section, results before and after training are reported for the student with dyslexia attending the second class of high school (tenth grade) who participated in the syntactic training program. His results are compared with those of both the whole group of students with dyslexia attending the second class and the group of TD students attending the same class. Table 8.6 provides the number and percentage of correctly repeated sentences, while Table 8.7 focuses on relative clauses. As Tables 8.6 and 8.7 show, before language training, the student was able to repeat only 65% of the sentences verbatim. Cleft sentences and oblique relative clauses were particularly demanding for him. Overall, his accuracy scores were more than 1.5 SD below the mean of the TD students. After training, his performance improved, reaching 90% of correctly repeated target sentences. Note that cleft sentences and wh-questions improved even if they were not treated directly. As stated above, syntactic training was focused on relative clauses only. As for relative clauses, his performance rose from 22% to 78% of Table 8.7  Repetition task – results on relative clauses 2nd class: Student with DD

2nd class Students with DD

TD Students

Before Training

After Training

Genitive relatives

3/6 50%

24/30 80%

1/2 50%

1/2 50%

Preposition + genitive relatives

2/6 33.3%

12/30 40%

0/2 0%

2/2 100%

Preposition + cui

1/3 33.3%

7/15 46.6%

0/1 0%

1/1 100%

Preposition + il quale

4/12 33.3%

25/60 41.6%

1/4 25%

3/4 75%

Total

10/27 37%

68/135 50.3%

2/9 22%

7/9 78%

Dyslexia and Syntactic Deficits: Overview and a Case Study of Language Training  203

Table 8.8  Elicited production task – general results 2nd class: Student with DD

2nd class Students with DD

TD Students

Before Training

After Training

Subject relatives

12/12 100%

52/56 92.8%

4/4 100%

4/4 100%

Object relatives

1/12 8.3%

2/56 3.5%

1/4 25%

4/4 100%

Indirect object relatives

2/12 16.6%

15/56 26.7%

1/4 25%

2/4 50%

Locative relatives

2/12 16.6%

30/56 53.5%

0/4 0%

2/4 50%

Genitive relatives

1/12 8.3%

20/56 35.7%

0/4 0%

2/4 50%

Total

18/60 30%

119/280 42.5%

6/20 30%

14/20 70%

sentences repeated verbatim. After training, he was also able to repeat prepositional genitive relatives and indirect object relatives with agreeing il quale, which are the most complex sentences in Italian. In Table 8.8, the number and percentage of target sentences produced in the elicited production task are reported. The results of the student who was administered the syntactic training are compared with those of both the whole group of students with dyslexia attending the second class and the group of TD students. Table 8.8 shows that the elicited production of relative clauses also improved, from 30% of produced target relative clauses before training to 70% after training. He was also able to produce locative and genitive relatives, which he did not produce at all before training. Before training, he scored below the mean of the TD students in locative relatives; after training, he performed similarly to controls. 4.2 Discussion

One of the students with dyslexia attending the second class of high school (tenth grade) was administered a syntactic training on relative clauses which lasted less than two months. After training, his performance improved in both tasks. In the repetition task, he was able to correctly repeat 90% of the sentences verbatim. He improved not only on relative clauses, which were the focus of syntactic training, but also on untrained sentences, namely cleft sentences and wh-questions. These generalization effects are expected since (i) cleft sentences and wh-questions are derived by the same type of syntactic movement as relative clauses, (ii) relative clauses are more complex than cleft sentences and wh-questions, and (iii) training of most complex sentences generalizes to less complex sentences. Our pilot study on an adolescent with DD found the same generalization effects observed in previous experiments on syntactic training administered to different populations:

204  Part 2: Theoretical and Experimental Linguistic Research on Dyslexia

aphasic patients (Thompson & Shapiro, 2007; Thompson et al., 1996, 1997, 2003), a Hebrew-speaking adolescent with LD and DLD (Levy & Friedmann, 2009) and Italian children with cochlear implants (D’Ortenzio, 2018; D’Ortenzio et al., 2020). Although the student did not reach 100% of target sentences repeated verbatim, after training he was able to produce fewer errors than before training, in both experimental and control sentences. Some examples are provided in examples (10)–(12). While the sentences repeated before training were ungrammatical (10a, 12a) or belonging to the informal register (complementizer che + dative clitic pronoun gli) (11a), the sentences repeated after training (10b)–(12b) were all target-like: (10) a.  La mamma bacia la bambina a cui il fratello piacciono le tigri. The mum kisses the child to whom the brother ‘please’ the tigers b. La mamma bacia la bambina al cui fratello piacciono le tigri. The mum kisses the child to whose brother ‘please’ the tigers ‘The mum is kissing the child whose brother likes tigers.’ (11) a. La bambina lava il cane che il padrone gli dà i biscotti. The child washes the dog that the owner dat gives the biscuits b. La bambina lava il cane a cui il padrone dà i biscotti. The child washes the dog to whom the owner gives the biscuits (12) a. Il lupo guarda la bambina che la nonna dona un fiore. The wolf looks at the child that the grandmother gives a flower b. Il lupo guarda la bambina alla quale la nonna dona un fiore.  The wolf looks at the child to.the.FEM.SG whom.SG the grandmother gives a flower

As stated above, interrogative sentences also improved. While before training, he turned object questions into subject questions, as in example (13a), after training he was able to produce target object questions correctly agreeing the embedded verb with the plural postverbal subject (13b): (13) a. Quale pulcino hai detto che ferma le giraffe? Which chick [you] have said that stops the giraffes? b. Quale pulcino hai detto che fermano le giraffe? Which chick [you] have said that stop the giraffes?

Dyslexia and Syntactic Deficits: Overview and a Case Study of Language Training  205

In the elicited production task, after training he was able to produce all types of relative clauses and reached 70% of produced complex sentences containing relative clauses. He not only produced object relatives, showing that he had fully acquired this sentence type, but also prepositional and genitive relative clauses, which were not produced before training. Note that if we only consider oblique (i.e. indirect object, locative, genitive) relatives to make the comparison with the sentence repetition task possible, the percentage of correctly produced oblique relative clauses rises from 8% before training (1/12) to 50% (6/12) after training. In examples (14)–(16), his productions before (a. sentences) and after training (b. sentences) are provided. In (14a), a subject relative replaced an indirect object relative by changing the verb; in (15a), the complementizer che and the dative clitic pronoun gli were produced instead of a pied-piped locative PP containing a relative pronoun (attorno a cui); in (16a), an ungrammatical sentence was produced. The sentences in (14b)–(16b) contain target relative clauses: (14) a. Tocca lo studente che sta parlando con il professore. Touch the student that is talking with the professor

b.  Tocca lo studente a cui il prof spiega un argomento di storia Touch the student to whom the professor explains a topic of history

(15) a. Tocca il gatto che il topo gli sta girando intorno. Touch the cat that the mouse dat is turning around

b.  Tocca il gatto attorno a cui gira il topo. Touch the cat around which turns the mouse

(16) a. Tocca il papà quello che gioca a calcio. Touch the dad that that plays soccer

b.  Tocca il papà il cui bambino gioca a calcio. Touch the dad whose child plays soccer

5 Conclusions

In this chapter, we have studied the competence of complex syntactic structures in a small group of Italian high school students with a diagnosis of dyslexia, comparing their performance with that of age-peers attending the same school and the same classes. Two oral tasks were administered: a sentence repetition task including different types of syntactically complex sentences and an elicited production task focused on relative clauses. Our results confirm a clear difficulty with

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complex sentences in both tasks, for all participants with dyslexia. As for the repetition task, we replicated the results of Del Puppo et al.’s (2018) study of a group of eleven age-peers with dyslexia. The results on the elicited production task go in the same direction. Difficulties with complex syntax are often under-estimated in individuals with dyslexia and raise the issue of the need for more focused language assessment to detect syntactic deficits in the most vulnerable areas of grammar. A sentence repetition task like the one used in our study might contribute to the assessment of syntactic competence and to the distinction between different language profiles of individuals with dyslexia, with and without syntactic difficulties. One of the students attending the second class of high school (tenth grade) was administered a syntactic training focused on relative clauses, which turned out to be the most impaired structures for all the students with dyslexia who participated in the study. After training, he was able to correctly repeat 90% of the sentences and to produce 70% of target relatives. His performance improved not only in the repetition and production of relative clauses, but also in the repetition of cleft sentences and wh-questions, which were not part of the teaching program. These generalization effects were found in similar syntactic treatment approaches administered to other populations and show that the training of the most complex structures generalizes over less complex structures of the same syntactic type. The pilot case study presented in this chapter was replicated with a larger sample of high school students with dyslexia, with similar results (Piccoli & Volpato, 2021). More data are needed from individuals with dyslexia to confirm the efficacy of syntactic training in this population, in particular in younger students with DD. Acknowledgements

We thank the students who took part in our study, their families and their schoolteachers. We also thank the school director for allowing the second author to administer the tests and the syntactic training during her internship in the high school. Notes (1) https://dyslexiaida.org/definition-of-dyslexia/ (2) For more recent studies on family risk of dyslexia, see Snowling and Melby-Lervag (2016) and van Viersen et al. (2018). (3) The presence of language deficits in individuals with a diagnosis of dyslexia has been acknowledged in two lines of the Linee guida per il diritto allo studio degli studenti con disturbi specifici di apprendimento, issued by the Italian Ministry of Education, University and Research (MIUR) on July 12, 2011: ‘La comorbilità può essere presente anche tra i DSA e altri disturbi di sviluppo (disturbi di linguaggio, …)’ (Comorbidity can be present between LD and other developmental disorders (specific language impairments, …)).

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(4) Three bilingual students and five L2 Italian speakers also participated in the experiment. Their data are not included in this chapter. (5) This comparison was not possible for LD students given the low number of participants in each class. (6) This comparison was not possible for LD students given the low number of participants in each class. (7) Levy and Friedmann’s (2009) syntactic intervention was modeled on Thompson and Shapiro’s (2005, 2007) and Thompson et al.’s (1993, 1996, 1997, 2003) language intervention with aphasic patients.

References Archibald, L.M.D. and Joanisse, M.F. (2009) On the sensitivity and specificity of nonword repetition and sentence recall to language and memory impairments in children. Journal of Speech, Language, and Hearing Research 52, 899–914. Arosio, F. and Guasti M.T. (2019) The production of wh-questions by Italian-speaking children with SLI. Clinical Linguistics and Phonetics 33, 349–375. Arosio, F., Branchini, C., Barbieri, L. and Guasti, M.T. (2014) Failure to produce direct object clitic pronouns as a clinical marker of SLI in school-aged Italian speaking children. Clinical Linguistics & Phonetics 28, 639–663. Arosio, F., Pagliarini, E., Perugini, M., Barbieri, L. and Guasti, M.T. (2016) Morphosyntax and logical abilities in Italian poor readers: The problem of SLI under-identification. First Language 36 (3), 295–315. Arosio, F., Panzeri, F., Molteni, B., Magazù, S. and Guasti, M.T. (2017) The comprehension of Italian relative clauses in poor readers and in children with Specific Language Impairment. Glossa 2 (1), 1–25. Bar-Shalom, E.G., Crain, S. and Shankweiler, D. (1993) A comparison of comprehension and production abilities of good and poor readers. Applied Psycholinguistics 14 (2), 197–227. Bishop, D. and Snowling, M. (2004) Developmental dyslexia and specific language impairment: Same or different? Psychological Bulletin 130 (6), 858–886. Bishop, D.V., McDonald, D., Bird, S., Hayiou-Thomas, M.E. (2009) Children who read words accurately despite language impairment: Who are they and how do they do it? Child Development 80, 593–605. Brady, S., Shankweiler, D. and Mann, V. (1983) Speech perception and memory coding in relation to reading ability. Journal of Experimental Child Psychology 35 (2), 345–367. Cardinaletti, A. (2014) La linguistica per la comprensione della dislessia: Alcuni test di produzione orale. In A. Cardinaletti, E. Ghidoni, E. Genovese, G. Guaraldi and F. Santulli (eds) Dislessia e apprendimento delle lingue: aspetti linguistici, clinici e normativi (pp. 51–68). Trento: Edizioni Centro Studi Erickson. Cardinaletti, A. and Volpato, F. (2011) L’analisi linguistica per la comprensione dei DSA. Quaderni di Scienze del linguaggio, IULM, 65–87. Cardinaletti, A. and Volpato, F. (2015) On the comprehension and production of passive sentences and relative clauses by Italian university students with dyslexia. In E. Di Domenico, C. Hamann and S. Matteini (eds) Structures, Strategies and Beyond: Studies in Honour of Adriana Belletti (pp. 223–279). Amsterdam: John Benjamins. Catts, H.W., Adlof, S.M., Hogan, T. and Weismer, S.E. (2005) Are specific language impairment and dyslexia distinct disorders? Journal of Speech, Language, and Hearing Research 48 (6), 1378–1396. Conti-Ramsden, G., Botting, N. and Faragher, B. (2001) Psycholinguistic markers for specific language impairment (SLI). Journal of Child Psychology and Psychiatry 42, 741–748. Delage, H. and Durrleman, S. (2018) Developmental dyslexia and specific language impairment: Distinct syntactic profiles? Clinical Linguistics and Phonetics 32 (8), 758–785.

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Del Puppo, G. and Volpato, F. (2016) Ripetizione e comprensione di frasi relative nella dislessia e nella sordità. Paper presented at the PRIN Workshop (Firenze, 26–27 May). Del Puppo, G., Grasso, S. and Volpato, F. (2018) Exploring some morphosyntactic abilities in children and adolescents with dyslexia: Evidence from a repetition task. Paper presented at the Conference on Developmental Language Disorders – DevO (Madrid, 26–28 September). Del Puppo, G., Volpato, F., Padovani, R., Zavattiero, P. and Lusuardi, A. (2016) Valutare la competenza sintattica di bambini con Disturbo Specifico del Linguaggio. Poster presented at the conference CLASTA VII (Communication & Language Acquisition Studies in Typical & Atypical Populations) (Calambrone, Pisa, 29–30 April). D’Ortenzio, S. (2018) Analysis and treatment of movement-derived structures in Italianspeaking cochlear implanted children. Unpublished PhD thesis, Università Ca’ Foscari Venezia. D’Ortenzio, S., Montino, S., Martini, A., Trevisi, P. and Volpato, F. (2020) A syntactically based treatment of relative clauses: Three case studies of Italian children with cochlear implant. In V. Torrens (ed.) Typical and Impaired Processing in Morphosyntax (pp. 177–207). Amsterdam: John Benjamins. Elbro, C. (1997) Early linguistic abilities and reading development: A review and a hypothesis about underlying differences in distinctiveness of phonological representations of lexical items. Reading and Writing 8, 453–485. Friedmann, N. and Novogrodsky, R. (2007) Is the movement deficit in syntactic SLI related to traces or to thematic role transfer? Brain and Language 101, 50–63. Friedmann, N. and Szterman, R. (2011) The comprehension and production of Whquestions in deaf and hard-of-hearing children. Journal of Deaf Studies and Deaf Education 16 (2), 212–235. Gallagher, A., Frith, U. and Snowling, M.J. (2000) Precursors of literacy delay among children at genetic risk of dyslexia. Journal of Child Psychology and Psychiatry 41 (2), 202–213. Guasti, M.T. (2013) Oral skills deficit in children with developmental dyslexia. In S. Stavrakaki, M. Lalioti and P. Konstantinopoulou (eds) Advances in Language Acquisition (pp. 416–424). Newcastle upon Tyne: Cambridge Scholars Publishing. Guasti, M.T. and Cardinaletti, A. (2003) Relative clause formation in Romance child’s production. Probus 15 (1), 47–89. Guasti, M.T., Branchini, C., Vernice, M., Barbieri, L. and Arosio, F. (2015) Language disorders in children with developmental dyslexia. In S. Stavrakaki (ed.) Specific Language Impairment. Current Trends in Research (pp. 35–55). Amsterdam: John Benjamins. Kamhi, A.G. and Catts, H.W. (1986) Toward an understanding of developmental language and reading disorders. Journal of Speech and Hearing Disorders 51, 337–347. Levy, H. and Friedmann, N. (2009) Treatment of syntactic movement in syntactic SLI: A case study. First Language 29, 15–50. Lust B., Flynn S. and Foley, C. (1996) What children know about what they say: Elicited imitation as a research method for assessing children’s syntax. In D. McDaniel, C. McKee and H.S. Cairns (eds) Methods for Assessing Children’s Syntax (pp. 55–76). Cambridge, MA: MIT Press. Manis, F.R., Doi, L.M. and Bhadha, B. (2000) Naming speed, phonological awareness, and orthographic knowledge in second graders. Journal of Learning Disabilities 33 (4), 325–333. Mann V.A., Shankweiler, D.P. and Smith, S.T. (1984) The association between comprehension of spoken sentences and early reading ability: The role of phonetic representation. Journal of Child Language 11 (3), 627–643. Marinis, T. and Armon-Lotem, S. (2015) Sentence repetition. In S. Armon-Lotem, J. de Jong and N. Meir (eds) Assessing Multilingual Children: Disentangling Bilingualism from Language Impairment (pp. 95–121). Bristol: Multilingual Matters.

Dyslexia and Syntactic Deficits: Overview and a Case Study of Language Training  209

McArthur, G.M., Hogben, J.H., Edwards, V.T., Heath, S.M. and Mengler, E.D. (2000) On the ‘specifics’ of specific reading disability and specific language impairment. Journal of Child Psychology and Psychiatry 41 (7), 869–874. Mulas, M. (2000) The acquisition of relative clauses. An experimental investigation. Unpublished MA thesis, Università Ca’ Foscari Venezia. Pennington, B.F. and Bishop, D.V.M. (2009) Relations among speech, language, and reading disorders. Annual Review of Psychology 60, 283–306. Piccoli, E. and Volpato, F. (2021) Syntactic training of oblique relative clauses in Italian students with developmental dyslexia. Paper submitted to the Proceedings of the Olinco Conference, Olomouc, Czech Republic, June 12, 2021. Pivi, M. (2014) On the acquisition of Italian restrictive relative clauses in typical and atypical development. Unpublished PhD thesis, Università Ca’ Foscari Venezia. Pivi, M. and Del Puppo, G. (2015) L’acquisizione delle frasi relative restrittive in bambini italiani con sviluppo tipico e con dislessia evolutiva. In M.E. Favilla and E. Nuzzo (eds) Grammatica applicata: Apprendimento, patologie, insegnamento, Studi AItLA 2 (pp. 59–73). Milano: Società italiana di linguistica applicata. Pivi, M., Del Puppo, G. and Cardinaletti, A. (2016) The elicited oral production of Italian restrictive relative clauses and cleft sentences in typically developing children and children with developmental dyslexia. In P. Guijarro-Fuentes, M. Juan-Garau and P. Larrañaga (eds) Acquisition of Romance Languages (pp. 231–261). Berlin: De Gruyter Mouton. Polišenská, K., Chiat, S. and Roy, P. (2015) Sentence repetition: What does the task measure? International Journal of Language & Communication Disorders 50, 106–118. R Core Team (2018) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/. Ramus, F., Rosen, S., Dakin, S.C., Day, B.L., Castellote, J.M. and White, S. (2003) Theories of developmental dyslexia: Insights from a multiple case study of dyslexic adults. Brain 126 (4), 841–865. Rispens, J., Roeleven, S. and Koster, C. (2004) Sensitivity to subject–verb agreement in spoken language in children with developmental dyslexia. Journal of Neurolinguistics 17 (5), 333–347. Robertson, E.K. and Joanisse, M.F. (2010) Spoken sentence comprehension in children with dyslexia and language impairment: The roles of syntax and working memory. Applied Psycholinguistics 31 (1), 141–165. Scarborough, H.S. and Dobrich, W. (1990) Development of children with early language delay. Journal of Speech and Hearing Research 33 (1), 70–83. Snowling, M.J. and Melby-Lervag, M. (2016) Oral language deficits in familial dyslexia: A meta-analysis and review. Psychological Bulletin 142 (5), 498–545. Snowling, M.J., Gallagher, A. and Frith, U. (2003) Family risk of dyslexia is continuous: Individual differences in the precursors of reading skill. Child Development 74, 358–373. Stein, C., Cairns, H.S. and Zurif, E. (1984) Sentence comprehension limitations related to syntactic deficits in reading disabled children. Applied Psycholinguistics 5, 305–321. Szterman, R. and Friedmann, N. (2015) Insights into the syntactic deficit of children with hearing impairment from a sentence repetition task. In C. Hamann and E. Ruigendijk (eds) Language Acquisition and Development: Generative Approaches to Language Acquisition 2013 (pp. 492–505). Newcastle upon Tyne: Cambridge Scholars Publishing. Tallal, P., Allard, L., Miller, S. and Curtiss, S. (1997) Academic outcomes of language impaired children. In C. Hulme and M. J. Snowling (eds) Dyslexia: Biology, Cognition, and Intervention (pp. 67–181). London: Whurr. Talli, I., Sprenger-Charolles, L. and Stavrakaki, S. (2016) Specific language impairment and developmental dyslexia: What are the boundaries? Data from Greek children. Research in Developmental Disabilities 49–50, 339–353.

210  Part 2: Theoretical and Experimental Linguistic Research on Dyslexia

Theodorou, E., Kambanaros, M. and Grohmann K. (2017) Sentence repetition as a tool for screening morphosyntactic abilities of bilectal children with SLI. Frontiers in Psychology 8, Article 2104. Thompson, C.K. and Shapiro, L.P. (2005) Treating agrammatic aphasia within a linguistic framework: Treatment of underlying forms. Aphasiology 19, 1021–1036. Thompson, C.K. and Shapiro, L.P. (2007) Complexity in treatment of syntactic deficits. American Journal of Speech-Language Pathology 16 (1), 30–42. Thompson, C.K., Shapiro, L.P. and Roberts, M. (1993) Treatment of sentence production deficits in aphasia: A linguistic-specific approach to wh-interrogative training and generalization. Aphasiology 7, 111–133. Thompson, C.K., Shapiro, L.P., Kiran, S. and Sobecks, J. (2003) The role of syntactic complexity in treatment of sentence deficits in agrammatic aphasia: The complexity account of treatment efficacy (CATE). Journal of Speech, Language, and Hearing Research 46, 591–607. Thompson, C.K., Shapiro, L.P., Tait, M., Jacobs, B.J. and Schneider, S.L. (1996) Training wh-question productions in agrammatic aphasia: Analysis of argument and adjunct movement. Brain and Language 52, 175–228. Thompson, C.K., Shapiro, L.P., Ballard, K.J., Jacobs, B.J., Schneider, S.L. and Tait, M. (1997) Training and generalized production of wh- and NP-movement structures in agrammatic aphasia. Journal of Speech, Language, and Hearing Research 40, 228–244. Van der Lely, H. and Battell, J. (2003) Wh-movement in children with grammatical SLI: A test of the RDDR hypothesis. Language 79, 153+-181. van Viersen, S., de Bree, E.H., Zee, M., Maassen, B., van der Leij, A. and de Jong, P.F. (2018) Pathways into literacy: The role of early oral language abilities and family risk for dyslexia. Psychological Science 29 (3), 418–428. Vender, M. and Delfitto, D. (2010) Towards a pragmatics of negation: The interpretation of negative sentences in developmental dyslexia. GG@G – Generative Grammar at Geneva 6, 1–28. Vender, M., Hu, S., Mantione, F., Delfitto, D. and Melloni, C. (2018) The production of clitic pronouns: A study on bilingual and monolingual dyslexic children. Frontiers in Psychology 9, Article 2301. https://doi.org/10.3389/fpsyg.2018.02301. Volpato, F. (2010) The acquisition of relative clauses and phi-features in hearing and hearingimpaired populations. Unpublished PhD thesis. Università Ca’ Foscari Venezia. Volpato, F. (2019) Relative Clauses, Phi Features, and Memory Skills. Venice, Edizioni Ca’ Foscari. Wiseheart, R., Altmann, L.J.P., Park, H. and Lombardino, L.J. (2009) Sentence comprehension in young adults with developmental dyslexia. Annals of Dyslexia 59, 151–167. Zachou, A., Partesana, E., Tenca, E. and Guasti, M.T. (2013) Production and comprehension of direct object clitics and definite articles by Italian children with developmental dyslexia. In S. Stavrakaki, M. Lalioti and P. Konstantinopoulou (eds) Advances in Language Acquisition (pp. 464–471). Newcastle upon Tyne: Cambridge Scholars Publishing.

9 The Impact of Dyslexia on Lexico-Semantic Abilities: An Overview Gloria Cappelli

1 Introduction

Literacy and lexico-semantic skills are strictly interconnected (Cain, 2006, 2009; Cain & Oakhill, 2011; Duff et al., 2015; Perfetti & Hart, 2002; Protopapas et al., 2013; Stafura & Perfetti, 2017; Taylor & Perfetti, 2016). However, although measures of vocabulary knowledge have been used in numerous studies on people with dyslexia, specific interest in the impact of the condition on these specific areas of language is still relatively new. Most studies have focused on children and have investigated the development of vocabulary knowledge and the difficulties with rapid naming, word learning abilities, and foreign language vocabulary acquisition (Cappelli & Noccetti, 2016; Kormos, 2020; Łockiewicz et al., 2019; Noccetti, Chapter 11, this volume; Sarkadi, 2008). More recent studies have started to look into the lexico-semantic skills of adolescents and young adults with dyslexia (mostly high school and university students) (Cappelli et al., 2018; Cavalli et al., 2016; Rasamimanana et al., 2020; Wiseheart & Altmann, 2018). Given that dyslexia manifests itself as primarily a reading disorder, and that vocabulary occupies a central position in most recent models of reading (Stafura & Perfetti, 2017), the lexico-semantic profile of dyslexic people has largely been investigated to gain a better understanding of the mechanisms underlying their difficulties. The connection between vocabulary and reading is also recognized by the most widely accepted definitions of this specific learning disorder (SLD). The International Dyslexia Association describes its behavioural manifestations and lists one of its ‘secondary consequences’ as ‘reduced reading experience’ due to problems with ‘word recognition and poor spelling and decoding abilities’ along with its impact on ‘the growth of vocabulary and background knowledge’ and, therefore, on reading comprehension.1 Interestingly, in so doing, this definition implicitly establishes a causal 211

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connection between possible deficits in vocabulary acquisition and reading experience. This causal connection is, however, not uncontroversial since delays in vocabulary development have been observed in both dyslexic children and in children at family risk from a very early age (van Viersen et al., 2017). Song et al. (2015) observe that the initial size and growth rate of vocabulary may in fact be predictors for later reading development. This change in perspective points to the existence of possible difficulties and differences in the development and organization of the lexical system in people with dyslexia, both in their L1 and in foreign languages (Adolf et al., 2021; Cappelli & Noccetti, 2016). The phonological deficit is believed to be the most relevant factor in this regard (Alt et al., 2017; Gupta & Tisdale, 2009; Litt & Nation, 2014; Sweins, 2015). Other studies have focused on the role of cognitive mechanisms such as working memory, short-term memory, attention and executive functions in the word learning and retrieval difficulties observed in dyslexic people (Laasonen et al., 2012; Smith-Spark et al., 2017; Staels & van den Broek, 2017). Moreover, there is growing evidence of the role played by individual differences in vocabulary knowledge in both word learning and reading fluency (Rose & Rouhani, 2012) and of the advantages offered by rich semantic representations for word recognition and text comprehension at large (Rodd et al., 2002). In spite of these advances in our understanding of dyslexia and its underpinnings, research on these issues has reached contrasting conclusions, thus failing to return a clear, consistent picture of the lexico-semantic profile of people with this SLD. Having outlined the current research scenario, section 2 expands on the reasons why research on dyslexia should not neglect vocabulary and semantic abilities. An overview of the findings on the former is provided in section 3, while section 4 tackles findings on the latter. Section 5 focuses on considerations of underlying working memory and rapid naming issues. Finally, section 6 summarizes the discussion and points out the limitations and implications for future research. 2 Why Study the Lexico-semantic Profile of People with Dyslexia?

Dyslexia is a neurodevelopmental disorder whose main behavioural markers are reading and spelling difficulties. It is the result of multiple risk factors, including genetic and environmental influences (Galaburda et al., 2006; Ghidoni, Chapter 1, this volume; Snowling & MelbyLervåg, 2016). Deficits in the phonological domain (e.g. issues with phonological awareness, phonological short-term memory, and rapid retrieval of phonological forms) are recognized as the major underlying cause of poor word recognition and decoding (Caglar-Ryeng et al., 2020; Snowling, 2019; Vellutino et al., 2004). Other domain-general

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deficits have been indicated as possible sources of dyslexia, including automatization, working memory and statistical learning deficits (Nicolson & Fawcett, 1990; Rasamimanana et al., 2020; Smith-Spark & Fisk, 2007; Vandermosten et al., 2019). Reading difficulties are not limited to decoding: many (although not all) people with dyslexia also have poor comprehension (Georgiou et al., 2021; Simmons & Singleton, 2000; Snowling & Hulme, 2012). Understanding a text, however, is a complex operation, involving more than just phonological skills. It requires access to word meanings, command of grammar, and efficient higher-level processing skills, such as the ability to successfully integrate information and to draw inferences (Cain, 2009; Snowling & Hulme, 2012). Vocabulary and semantics play a central role in most operations connected with reading and reading comprehension (Perfetti & Stafura, 2014; Protopapas et al., 2013; Verhoeven & van Leeuwe, 2008). Integrated models of reading such as the Reading Systems Framework (Perfetti, 1999) and the Lexical Quality Hypothesis (Perfetti & Hart, 2002) view the processes that lead to comprehension as the ideal locus in which weaknesses resulting in reading comprehension issues can be identified (Perfetti & Stafura, 2014), and the lexicon is defined as one of the possible ‘pressure points in the system’ (Perfetti & Stafura, 2014: 26). Indeed, successful reading comprehension depends on effective rapid word identification and decoding to build meaning units and integrate them into a mental model of a text (Perfetti et al., 2008). At the same time, the mapping between word forms and meanings happens through meaningful word-learning encounters with the written text (Perfetti et al., 2005). Accordingly, the dual route view of reading posits that, initially, new words are assigned a phonological form applying the alphabetical principle. This way, children progressively store orthographic, phonological and semantic information in their mental lexicon. Little by little, they become capable of retrieving this stored information more efficiently and rapidly for words they encounter frequently, until word recognition eventually happens through a direct, faster visual route (Coltheart, 2006; Coltheart et al., 2001). Semantic knowledge is expected to have an increasingly important role in word recognition at this stage, because it may foster both lexical retrieval and direct word recognition and decoding (van Rijthoven et al., 2018). Thus, people with better lexical representations may be better at identifying words as well as at phonological tasks (van Goch et al., 2014; Walley et al., 2003). Children with dyslexia struggle with word decoding and therefore with learning to read. Their reading is less fluent and accurate than that of typically developing age-matched peers, and, even if reading becomes accurate in some compensated dyslexic adults, slowness persists alongside issues with phonological processing, rapid naming and verbal working memory tasks (Georgiou et al., 2012; Swanson et al., 1996).

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Within the models mentioned above, comprehension difficulties are attributed to the depletion of memory resources due to the demands imposed by poor phonological skills: slow and inaccurate reading would result in failure to remember previously encountered information (Álvarez-Cañizo et al., 2015; Perfetti, 1985). However, recent studies have found that some dyslexic people have impaired pragmatic skills (Cappelli, 2019; Cappelli et al., 2018; Cardillo et al., 2018; Griffiths, 2007), reduced capacity to interpret humour (Boksa, 2018; Griffiths, 2007; Simi, 2018) and difficulties with pronominal and lexical anaphora resolution when the referent nouns are abstract (Simi, 2021). These findings seem to point towards a more complex linguistic profile than previously hypothesized, and one in which lexico-semantic skills are important in terms of individual differences. In addition to these considerations, the centrality assigned to vocabulary and semantics in integrated models of reading explains why the effects of dyslexia on these domains should receive growing attention, both in terms of behavioural outcomes and causal relations. Over the past 20 years, therefore, studies have been published that have attempted to verify whether the phonological deficits associated with the disorder have a negative effect on the encoding and storage of novel lexical items and on rapid naming and word retrieval. Others have looked at the effects of dyslexia on vocabulary development and semantic skills at large and at the correlation between the latter and the development of literacy. Some have hypothesised that the mental lexicon in dyslexic people may be organized differently or that the phonological and memory issues may result in less precise lexical representations. The next sections offer an overview of the answers provided by linguistic and psycholinguistic research to these questions. 3 Vocabulary and Dyslexia

Vocabulary measures have been included in many studies to account for individual differences (Cavalli et al., 2016; Ouellette & Shaw, 2014). Assessing vocabulary knowledge is no easy task; neither is defining what ‘knowing a word’ might mean. Evaluating somebody’s vocabulary knowledge may thus entail measuring its breadth (how many words they know) and depth (how ‘well’ they know them), both receptively and expressively (Nation, 2001; Schmitt, 2014). A number of tests exist which try to determine receptive vocabulary breadth, such as the Eurocentres Vocabulary Size Test (Meara & Jones, 1990), the Vocabulary Size Test (Nation & Beglar, 2007) and the Peabody Picture Vocabulary Test (PPVT; Dunn & Dunn, 2007). The latter and fluency tasks are frequently used to gather vocabulary measures in experimental studies on language disorders, as well as for diagnostic purposes. Vocabulary depth measures are usually obtained through the ‘Vocabulary’ component of larger

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batteries such as the Wechsler Adult Intelligence Scale (WAIS) and the Wechsler Intelligence Scale for Children (WISC), or through tests such as the Vocabulary Knowledge Scale (VKS; Wesche & Paribakht, 1996) and the Word Associates Test (WAT; Read, 1998). However, any reliable measure of vocabulary depth should be able to determine the degree of precision with which a word is known, the comprehensiveness of such word knowledge, and the extent of the lexical network in which the lexical item is placed (see Read, 2004 and Webb, 2013, for a thorough discussion of these matters). Developmental dyslexia is not traditionally associated with lexical deficits (Snowling & Hulme, 2012), and research has reached mixed conclusions in this regard. Most studies on dyslexic children agree that, at school-entry age, their vocabulary is comparable to that of age-matched peers (Snowling & Melby-Lervåg, 2016; van Viersen et al., 2015). However, meta-analyses focusing on young adults have reported that they have impaired vocabulary skills compared to typicallydeveloped controls (Swanson, 2012; Swanson & Hsieh, 2009). Poor performance in vocabulary tasks has been confirmed by a number of studies, including (but not limited to) Snowling et al. (1997), Hatcher et al. (2002), Ransby and Swanson (2003), Corkett and Parrila (2008), Wiseheart et al. (2009), Cappelli (2019) and Łockiewicz et al. (2019), while others have found comparable or better lexical skills in dyslexic adults (Cavalli et al., 2016; Parrila et al., 2007; van Viersen et al., 2015). Cavalli et al. (2016) have pointed out that a reason for these diverging conclusions could be that most studies supporting differences in lexical skills have merged data relative to vocabulary size and depth, and stress that statistically significant difficulties might be limited to the former. They found that the 20 French university students who participated in their study were in fact better than the controls at tasks testing vocabulary depth. However, the study involved a limited number of informants, most of whom had received remedial interventions that might have mitigated the effects of dyslexia on their lexical abilities. Moreover, university students could be considered very well compensated dyslexics (Livingston & Happé, 2017; Nicolson & Fawcett, 1990), because they have managed to overcome the obstacles posed by the disorder and have successfully advanced along their education path. Overall, the picture that emerges is that of a population with a smaller vocabulary size than typically-developed peers but comparable vocabulary depth. The difference between dyslexic and non-dyslexic people’s vocabulary size appears to increase over time, but only if data obtained from age-matched participants are compared. If informants are matched by reading age, differences seem to be significantly reduced (Wolf & Segal, 1999). Consistent with the IDA (2002) definition of dyslexia mentioned above, reduced reading experience is therefore generally considered to be the reason for this disparity. This is far from

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uncontroversial and leaves many questions open as to the mechanisms responsible for the widening of the gap in vocabulary knowledge, the reasons why it is apparently limited to vocabulary breadth, and as to which and how lexical skills are tested in order to reach such a conclusion. 3.1 Dyslexia and vocabulary development

To verify the causal link between reading and vocabulary development in people with dyslexia, research has investigated whether some effects of the disorder can be identified in the pre-literacy skills of very young children. Since dyslexia is manifested primarily in reading difficulties, it cannot be diagnosed before the beginning of school age. However, it is a heritable disorder, and a number of longitudinal studies have gathered and compared data obtained from children at family risk (AFR) and non-at-family-risk typically developing peers (NAFR), thus gaining interesting insights into the trajectory of their vocabulary development (Caglar-Ryeng et al., 2020; Chen et al., 2017; Kalashnikova et al., 2020; Lyytinen & Lyytinen, 2004; Nash et al., 2013; Snowling et al., 2003, 2007; van Viersen et al., 2017). It is estimated that up to 60% of AFR children will receive a diagnosis of developmental dyslexia at some point (Snowling & MelbyLervåg, 2016). For this reason, besides offering interesting insights into the general cognitive and linguistic profile of this population, identifying early signs of the disorder could help design remedial interventions and give these children the best opportunities for effective learning, since early oral skills have a direct influence on later reading and reading comprehension skills (Hulme et al., 2015). Poor phonological processing is the major risk factor in people with dyslexia (Snowling, 2019), and AFR children have been found to have issues with phonological awareness, phonological short-term memory, and rapid retrieval of phonological forms at a very early age (Noordenbos & Serniclaes, 2015; Snowling & Melby-Lervåg, 2016), including infancy (Kalashnikova et al., 2020). It is therefore plausible that differences in phonological skills may have a negative impact on the (oral) encoding and storage of novel lexical items already in the pre-school years. Differences in vocabulary at an early age are quite difficult to detect and rely for the most part on parental reports, but differences in size have nevertheless been found in AFR children at different developmental ages (Caglar-Ryeng et al., 2020; Kalashnikova et al., 2020; Snowling & MelbyLervåg, 2016; Torppa et al., 2010; van Viersen et al., 2018;). There is no agreement on the age at which the first differences can be observed. Some studies have found disparities at 17 and 19 months of age (Chen et al., 2017; Koster et al., 2005), whereas others have identified between-group

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differences only after 30 months of age (Lyytinen et al., 2004), or even at 6 years of age (Caglar-Ryeng et al., 2019). The meta-analysis by Snowling & Melby-Lervåg (2016) indicates that vocabulary issues in early childhood are quite limited but become more serious after school entry in children with a confirmed diagnosis of dyslexia. Children who turn out not to be dyslexic, on the other hand, tend to catch up by school age (e.g. late talkers). Langedijk (2019) found that dyslexic children lagged two months behind the vocabulary age of peers. These data seem to point towards a specific effect of dyslexia on the development of vocabulary, regardless of reading experience. The latter would, however, be the cause of the widening of the gap in dyslexic and non-dyslexic adults’ vocabulary knowledge. Not all studies agree on vocabulary issues as an early marker of dyslexia, however. In a longitudinal study, Lyytinen et al. (2001) found that AFR children’s receptive vocabulary was comparable to that of NAFR children’s: differences could only be found in expressive language. Likewise, Wolf and Segal (1999) state that many young readingimpaired children do not begin with vocabulary problems, but that some difficulties with retrieval of expressive vocabulary can be found. Snowling et al. (2019) also found that oral language deficits in AFR children later diagnosed with dyslexia increase with age and become even greater after school entry. Similarly, Caglar-Ryeng et al. (2020), in their longitudinal study of late talkers with and without risk of dyslexia, found only moderate effect sizes between groups at age 4;6 years, but significant effects at age 6. To sum up, research on children of pre-school age has found only minor differences in vocabulary skills between AFR and NAFR children, and, overall, such difficulties are confirmed to be limited to expressive vocabulary. However, the research confirms the progressive differentiation in vocabulary measures between individuals with dyslexia and typically developing peers starting around school-entry age, as they become most apparent only by the age of 6 years. Different hypotheses can be made to explain findings in children of pre-school age. The first possibility is that differences depend on the methodology used for the studies. Some may have included children who later obtained a diagnosis of specific language impairment alongside that of dyslexia, and those may be the children with vocabulary issues. A second possibility is that vocabulary measures for infants, toddlers and pre-schoolers are not sensitive enough or that they merge receptive and expressive data, when only the latter seem to be related to dyslexia (Caglar-Ryeng et al., 2020; Snowling et al., 2019; van Viersen et al., 2018). A third possibility is that issues with expressive vocabulary are not directly related to dyslexia but are due to environmental factors, such as growing up in a family with a history of the disorder (Pennington, 2006), or other socioeconomic variables such as maternal language

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and education (Fernald et al., 2013; Kalashnikova & Burnham, 2018; Lyytinen et al., 2001; Tamis-LeMonda et al., 2001) and lack of early exposure to print materials (Montag et al., 2015). Such problems might be later worsened by reduced reading experience. On the other hand, early expressive vocabulary issues may in fact be connected to dyslexia, and the vocabulary growth in children with the disorder may reflect a different developmental trajectory. Snowling et al. (2016) hypothesize that such children might start like their typically developing peers and deviate from the typical trajectory and develop evident difficulties only around school age. This idea is compatible with van Viersen et al.’s (2017) findings that the vocabulary spurt observed in some AFR children in the second year of life seems to have a later onset, especially for expressive vocabulary. Receptive vocabulary would instead have a slow initial growth but a weaker deceleration until the age of 3 years. All in all, great caution should be exercised in drawing conclusions from such diverse results. Early vocabulary quality does not seem to be a reliable predictor of dyslexia, since it is frequently characterized by low development stability (Duff et al., 2015), and many factors may be responsible for different developmental paths (Wolf & Segal, 1999). Similarly, there is no agreement as to the lexical profile of adult dyslexics: some studies have found no significant differences (Cavalli et al., 2016; Wiseheart et al., 2009; Wiseheart & Altmann, 2018), thus pointing towards a progressive compensation in vocabulary knowledge, while many others have reported reduced vocabulary in this population (Łockiewicz et al., 2019; Swanson, 2012; Swanson & Hsieh, 2009; Wolf & Segal, 1999), thus confirming the increasing differentiation hypothesis. 3.2 Dyslexia and lexical learning skills

Research on lexical learning abilities in people with dyslexia may provide some insight into whether the disparities in vocabulary knowledge observed are due to environmental factors and experimental conditions alone, or if, to the contrary, they may be a manifestation or consequence of the deficits associated with the disorder (see also Noccetti, Chapter 11, this volume). One hypothesis is that differences in vocabulary size may derive from problems with novel word learning, due to the phonological issues already present in dyslexic infants. Several studies have confirmed such difficulties (Elbro & Jensen, 2005; Kalashnikova et al., 2020; Mayringer & Wimmer, 2000). Kalashnikova et al. (2020) found that infants at risk have significantly higher discrimination thresholds, suggesting a degree of early auditory insensitivity that may be potentially detrimental for the encoding and storage of novel information and which may impact early vocabulary growth. Issues with lexical learning in dyslexic children have been reported in Paired

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Associate Learning tasks (PAL; Clayton et al., 2018; Elbro & Jensen, 2005; Litt et al., 2013; Thomson & Goswami, 2010; Vellutino et al., 1995). The participants performed well with word-referent associations but experienced difficulties in encoding and retrieving detailed phonological representations of new words. Kalashnikova et al. (2020) studied PAL at a very early age in at-risk infants of 19 months of age and excluded general deficits in associative learning. These children were quite successful in visual–visual and verbal–visual learning, but they performed worse than controls in tasks in which they had to retrieve learned labels for production, thus confirming the issues with expressive rather than receptive vocabulary. Moreover, a correlation between greater vocabulary size and amount of learning was found: infants with smaller vocabularies showed reduced lexical processing efficiency, which the authors interpreted as either an issue with lexical access or with label recognition due to ‘lower specificity in the mapping or in the phonological representation of the novel word’ (Kalashnikova et al., 2020: 12). Similar patterns have been observed in older children (Di Betta & Romani, 2006; Edwards et al., 2004; Gupta & Tisdale, 2009; Litt & Nation, 2014; Messbauer & de Jong, 2003; Snowling et al., 1991) and in adults with dyslexia, both in their first language (Rasamimanana et al., 2020; Simi, 2021) and in a foreign language (Cappelli & Noccetti, 2016; Dóczi & Kormos, 2016; Noccetti & Cappelli, 2018; Sarkadi, 2008). This may provide support to the hypothesis of a delayed (van Viersen et al., 2017) or different (Adolf et al., 2021; Snowling & Melby-Lervag, 2016) trajectory independent from reading experience, in which an initial slower vocabulary growth may cause a smaller degree of learning, ultimately resulting in the expanding gap described in the literature. Di Betta and Romani (2006) hypothesize that this could also be amplified by the fact that difficulties with lexical learning ‘might be more prevalent in and more characteristic of dyslexic adults than of dyslexic children’ (2006: 378). In spite of these differences in novel word learning, the lexical profile of people with dyslexia does not appear to be so compromised as to emerge as a generalized and consistent distinctive deficit in their communicative profile. Future research will have to confirm the existence of differences in vocabulary knowledge and whether they depend on word learning issues. Interestingly, recent experimental studies employing neuroimaging techniques and investigating the effects of the disorder at the electrophysiological level have revealed a mismatch between behavioural and neural markers of dyslexia (Rasamimanana et al., 2020; Schulz et al., 2008), confirming atypical brain functioning when lexical learning or processing are involved, even when they did not result in significantly different behavioural manifestations. Multiple reasons may be imagined for this discrepancy. Some ‘high-achieving individuals with dyslexia [...] may normally increase their vocabulary

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skills’ (Rasamimanana et al., 2020: 12). Another possibility is that the well-known diversity in the cognitive features of dyslexic people may result in very diverse lexical profiles, or else, good vocabulary skills may be due to compensation. If a novel word learning deficit exists, as most studies seem to conclude, multiple factors can be held responsible for it. The major underlying cause is recognized in the phonological deficit associated with developmental dyslexia. Good phonological processing is known to drive good vocabulary learning. This is a cascading effect due to phonetic-phonological-lexical continuity (Cooper & Wang, 2013; Dittinger et al., 2017; Messbauer & de Jong, 2003; Rasamimanana et al., 2020; Wong & Perrachione, 2007): efficient processing results in better phonological representations of new words and stronger word form-meaning associations. Moreover, good phonological skills provide learners with better sensitivity to sound regularities (Daikhin et al., 2017; Vandermosten et al., 2019). Phonological short-term memory (PSTM) is especially important in this regard. A causal relation between poor PSTM and reduced phonological vocabulary size has been proven to effect nonword repetition, which is taken to be a task that simulates very closely what happens when we encounter a word form for the first time (Gupta & Tisdale, 2009). Several studies have found correlations between measures of PSTM and vocabulary learning and size (Gathercole et al., 1992; Gupta, 2003; Gupta & Tisdale, 2009) and have concluded that the learning of a novel lexical item would depend ‘on how well it could be processed as a novel word or nonword’ (Gupta & Tisdale, 2009: 482). Others have hypothesized that this relation may be indirect and mediated by phonological vocabulary size (Edwards et al., 2004; Snowling, 2006). On the other hand, some scholars maintain that phonological problems might not be the major determining factor. Di Betta and Romani (2006) have proposed that, in adult dyslexics, phonological abilities may have a smaller role in new word learning than in children, and that dyslexia may be associated with a more abstract lexical learning impairment, a ‘specific genetic deficit in encoding and/or retaining sequences of units (phonological, visual or more abstract)’ (2006: 397). They claim that poor lexical learning may be due to a combination of poor PSTM, a deficit in visuo-sequential memory and ‘a separate impairment in setting up and/or retaining good quality lexical representation’ (2006: 397). This would result in a reduced ability to create new mental representations from a set of previously unrelated items and therefore emerge as poor lexical knowledge in some people with dyslexia. Others support the serial-order deficit hypothesis (Bogaerts et al., 2015; Cowan et al., 2017). Cowan et al. (2017) analysed working memory measures in dyslexic children. Interestingly, they found important serial order memory deficits, but

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they observed that they were the only measures significantly distinguishing them from typically developing peers once matched for non-verbal intelligence and language skills if they also had associated SLI. Otherwise, phonological memory remained the best predictor of lexical learning and reading performance. Ultimately, then, it seems that problems with lexical learning could be identified with memory issues (of diverse type), and thus with the ability to create and consolidate memory traces. There is, however, much agreement that this impairment, whatever the source, would only impact the ability to encode and retain the formal aspects of linguistic representations. Obidziński and Nieznański (2017) have tried to offer an explanation of the effects of dyslexia on the formal properties of vocabulary, resorting to the Fuzzy-trace Theory (FTT; Brainerd & Reyna, 2004, 2005; Reyna, 2012). This is based on the idea that the process of encoding information creates two parallel and independent memory traces representing the same stimuli. One, the verbatim trace, is a symbolic representation of the surface form of a stimulus, precise and linked to perception. The other, the gist trace, is the representation of semantic properties, less precise and more durable. Issues with the creation of one of these types of traces would render memory retrieval challenging. Obidziński and Nieznański (2017) confirm the impairment in the memory of verbatim traces in dyslexics (Miles et al., 2006), especially in the case of ‘recollection rejection processes’, which occurs when false memories triggered by a specific stimulus, need to be rejected; a process that requires differentiating between similar objects. They hypothesize that the difficulties observed in reading, as well as in word learning skills, might both derive from a deficit in such ability, which would not only be limited to similarity between sounds or characters, but would include similarities of meaning too (i.e. issues with synonyms; cf. Golubovic & Tubin, 2013). The gist memory traces, however, would be preserved and possibly better developed than in non-dyslexics, and they would eventually assist the formation and retrieval of verbatim traces (see Brainerd et al., 2006 and Fletcher et al., 2002, for different views on this matter). Differences in memory traces and vocabulary learning were also observed in Smith et al.’s (2018) study on sleepassociated memory consolidation. They found a reduced role of sleep in vocabulary consolidation in dyslexia, although they could not exclude that it was dependent on lower levels of learning prior to sleep. It cannot, therefore, be excluded that the phonological and memory deficits found in people with dyslexia might result in worse word learning skills and consequently in reduced vocabulary, regardless of exposure to reading materials. Over time, many might manage to compensate and develop a lexical repertoire comparable to that of typical readers, although differences might still be identifiable with neural and electrophysiological scrutiny.

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4 Dyslexia and Semantics

From a behavioural point of view, the semantic skills of people with developmental dyslexia are, by and large, considered to be intact (Cavalli et al., 2016; Rasamimanana et al., 2020; Schiff et al., 2019; Vellutino et al., 1995; Wiseheart & Altmann, 2018). However, as in the case of vocabulary skills, different positions have been proposed by scholars investigating the manifestations of the disorder in different writing systems (Ben-Dror et al., 1995; Chik et al., 2012; Wang et al., 2017; Xiao & Ho, 2014) and its neural and electrophysiological markers (Rasamimanana et al., 2020; Shulz et al., 2008; Wang et al., 2017). Those in support of the most widely accepted view – that semantic abilities are well preserved – rely on data showing that dyslexic people are as successful as non-dyslexic controls in learning the meaning of different words (e.g. concepts, referents and associations; Xiao & Ho, 2014), even though it might take more meaningful encounters in order for them to learn their formal properties. Moreover, no problems have been reported with visual–visual semantic associations (Kalashnikova et al., 2020). Further evidence comes from studies on memory traces: gist traces (i.e. the mental representations of the semantic properties of a novel stimulus) have been found to be well formed (Obidziński & Nieznański, 2017) and possibly of better quality than those of non-dyslexic peers (Blau, 2013; Miles et al., 2006). Fluency tasks are among the most common tests used to assess lexico-semantic skills. When a word is learnt, it is stored in a mental lexicon organized in semantic networks (Collins & Loftus, 1975). The latter are formed by clusters of words interlocked by semantic relatedness (Hills et al., 2009; Marshall et al., 2018; Mengisidou et al., 2020; Rogers & McClelland, 2008). In a semantic fluency task (Newcombe, 1969), informants are asked to provide as many words belonging to a specific semantic field as they can in a limited amount of time (for example, nouns denotating fruits, animals, etc.). This requires access to information stored in long-term memory and makes considerable demands on higher-order cognitive abilities (Smith-Spark et al., 2017). The number of clusters produced (i.e. how many) and their size (i.e. how many lexical items in each one) are taken to be a measure of the lexical organization and efficiency of lexical retrieval processes (Marshall et al., 2018), since ‘producing successive semantically related items reveals relations between items in a semantic network’ and since retrieval ‘is facilitated by inter-item associations between a given item and other items whose semantic representations partly overlap’ (Mengisidou et al., 2020: 2). Individual differences in language development, including dyslexia, are associated with differences in the connectivity between words in the network. Thus, some people may have more clusters than others,

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and these clusters may be interconnected to different extents (Beckage et al., 2011). For this reason, semantic fluency is considered to reflect the quality of lexico-semantic representations, which depend on the experience with both oral and written language (Dyson et al., 2017; Nation, 2017). Encountering words in many different contexts leads to richer and more nuanced networks, in which each item develops many connections to other items based on lexical co-occurrence in diverse linguistic environments (Nation, 2017). As mentioned in section 2, ‘lexical quality’ (Perfetti & Hart, 2002) is crucial for reading accuracy and reading comprehension (Perfetti & Stafura, 2014). Semantic fluency performance may, therefore, provide very useful information on the organization of semantic representations in the mental lexicon of people with developmental dyslexia, and contribute to verifying whether the differences observed at the lexical level are reflected in a less sophisticated network of semantic connections (Messer & Dockrell, 2006). Similar to what we observe in research on dyslexia and vocabulary knowledge, the data relative to semantic fluency performance are inconsistent. Some studies have found no differences between dyslexic and typically developing children (Brosnan et al., 2002; Landerl et al., 2009; Marzocchi et al., 2008), while others have reported that the former’s scores were significantly lower than the latter’s (Mengisidou et al., 2020; Reiter et al., 2005; Varvara et al., 2014). Interesting insights have been offered by the qualitative analysis of the lexical items given by participants in semantic fluency tasks. Mielnik et al. (2015) found that there was no difference in the size of the clusters produced by Polish teenagers of 16–18 years of age, but that they provided fewer of them compared to the control group. Similar results were obtained by Mengisidou et al. (2020). They interpret the data as evidence that dyslexia is not associated with poor semantic structure but, rather, with issues of retrieval from a lexicon with intact semantic structure. Lexical retrieval is in fact facilitated by associations between words. Thus, richer semantic connections (both in terms of number and strength) make it easier to retrieve items from a subcategory and therefore lead to the production of larger clusters (i.e. they will include more items from a specific domain). Dyslexic people seem to produce items within normal range in terms of quantity, but these belong to fewer clusters. Mengisidou et al. (2020) conclude that lexical retrieval issues make it difficult for them to exhaust a subcategory and switch to another under time constraints. Their behaviour in semantic fluency tasks could thus be explained by the Retrieval-Slowing Model (Rohrer et al., 1995) rather than by hypotheses of issues in word learning and in establishing lexicalsemantic representations that may lead to an impoverished network of semantic connections. This is compatible with the analysis of the data from different semantic tasks discussed in Cappelli (2019), in which

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Italian dyslexic university students were asked to organize a series of lexical items in semantic sets and to complete word series in their native language and in a foreign language (English). In Italian, they used an equal number of lexical items but grouped them in fewer clusters and according to different (and more experiential) criteria in comparison to age-matched peers. They produced a comparable number of items in the series, connected to one of several possible fields shared by the stimulus words provided. In the foreign language, on the other hand, they used fewer items in the classification task in a larger number of clusters and according to similar criteria as the controls. They produced fewer words in the series. This was taken to indicate that in their native language their vocabulary is well developed in size but might lack depth or have a different internal organization. In other words, they may have developed partial semantic representations of individual lexical items, and, consequently, have reduced semantic networks, where only some of the senses or meanings are present due to fewer encounters with these words in diverse contexts (in line with Nation’s (2017) Lexical Legacy Hypothesis). On the contrary, their foreign language vocabulary may simply be limited because of the difficulties encountered by dyslexic foreign language learners with traditional vocabulary teaching (Cappelli & Noccetti, 2016; Noccetti & Cappelli, 2018; Noccetti, Chapter 11, this volume), but they may be more typically organized in terms of different clusters, due to the specific and explicit vocabulary instruction received. It is generally believed that a reciprocal connection between semantics and phonology exists in the mental lexicon (Li et al., 2004; Savill et al., 2017; van Rijthoven et al., 2018). Well-developed semantic abilities may, therefore, assist people with dyslexia in the development of phonological abilities and may support their working memory (Betjemann & Keenan, 2008; Hennessey et al., 2012; Nation & Snowling, 1998; Nobre & Salles, 2016; Rasamimanana et al., 2020; Robichon et al., 2002; van der Kleij et al., 2017; van Goch et al., 2014; Vellutino et al., 2004). Intact semantic skills, moreover, may exercise a positive influence on word reading and learning and facilitate the process of learning to read (Cavalli et al., 2016; Plaut & Booth, 2000; Rasamimanana et al., 2020; van Viersen et al., 2017). These ideas support the ‘semantic compensation hypothesis’ (Cavalli et al., 2016; Haft et al., 2016; Stanovich, 1980), which predicts that people with dyslexia use semantic knowledge and information provided by the context to cope with their phonological deficits and to reach typical readers’ levels of performance in word processing. Savill et al. (2017) have found that, in word learning tasks, semantic knowledge may increase the stability of phonological traces, thus establishing a direct bidirectional connection between the semantic and the phonological systems. Dyslexics may use their semantic skills to ‘bootstrap’ impaired decoding processes (Nation & Snowling, 1998) and to improve oral

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reading fluency (Rose & Rouhani, 2012). People with dyslexia who are more capable of exploiting their semantic abilities in this way may develop better vocabulary, which, in turn, may have a ‘protective effect’ against reading comprehension and expressive language issues deriving from other deficits commonly associated with the disorder (e.g. poor working-memory abilities; Bishop & Snowling, 2004; Haft et al., 2016; Wiseheart & Altmann, 2018). The semantic compensation hypothesis can also explain difficulties and generalized slowness in reading comprehension tasks. If dyslexic readers must rely on semantic (and morphological) skills more than typically developing peers to overcome phonological obstacles (Burani, Chapter 5, this volume), this may come at a processing cost (Breznitz & Meyler, 2003), which in turn increases processing times and reduces the cognitive resources available to reach comprehension (Deacon et al., 2019; Rasamimanana et al., 2020; Schiff et al., 2019). The description of the semantic profile of dyslexic people that can be derived from the literature examined to this point relies mostly on behavioural studies on speakers of alphabetical languages. Recently, studies have started to appear investigating the effects of dyslexia on speakers of non-alphabetical languages, and they have offered a different picture. In their overview of the disorder across languages, Deacon et al. (2019) found evidence of deficits in semantic processing in speakers of Polish (Jednoróg et al., 2010), Finnish (Helenius et al., 1999), German (Schulz et al., 2008), Hebrew (Ben-Dror et al., 1995) and Chinese (Chik et al., 2012; Xiao & Ho, 2014). Whereas many of these studies found that differences in semantic skills were greatly reduced once reading level was taken into account, Xiao and Ho (2014) observed that, for the Chinese children who participated in their research, weaknesses in some semantic tasks remained and they concluded that these may be a ‘potential source of poor word and sentence reading in Chinese developmental dyslexia’ (2014: 74). Chinese word formation and the Chinese writing system rely greatly on semantic compounding, and therefore on connections between orthography, morphology and semantics. Issues with morphology or with establishing orthography– semantic links may then result in difficulties in learning to read (Xiao & Ho, 2014). Similar issues were found by Wang et al. (2017), who concluded that ‘Chinese dyslexic children have semantic processing defects’ (2017: 221). More specifically, they found category sorting deficiencies and semantic integration difficulties that led their informants to decision-making difficulties during semantic processing. Wang et al.’s (2017) conclusions are based on neurocognitive data. They report on an event-potential related study. It is quite interesting that differences in semantic functioning in dyslexia have emerged mainly through investigations of neural rather than behavioural markers of dyslexia. Both Shulz et al. (2008) and

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Rasamimanana et al. (2020) found that, from a behavioural point of view, dyslexic and non-dyslexic children and young adults performed in a similarly accurate way in associative picture-novel word learning and in reading comprehension tasks involving congruous vs. incongruous sentence endings, although dyslexics were significantly slower. From an electrophysiological perspective, instead, differences were observed in the N200 and N400 components: the former is taken to reflect contextual influences and phonological processing and the latter is an index of semantic processing (Dittinger et al., 2017). In addition, they found that dyslexic participants recruited both hemispheres and mobilized more frontal resources than the controls in performing the tasks, while showing less activation in left-hemispheric regions and reduced inferior parietal activation during sentence reading. Wang et al. (2017) reported reduced brain activity associated with semantic processing and semantic integration in dyslexic children. Likewise, Helenius et al. (1999) observed the same effects in adults, which led Schulz et al. (2008) to suggest that this reduction in ‘semantic sensitivity’ may develop with age, but only when reading is involved. Overall, since the behavioural data do not reveal any significant semantic deficit, the only constant significant difference between dyslexic and typical individuals being in speed rather than accuracy, the vast majority of studies conclude that it is still possible that discrepancies in brain functioning may be a reflection of semantic compensation rather than a proof of semantic deficits. In other words, they would reflect the effort required to compensate phonological and memory deficits with semantic skills (Rasamimanana et al., 2020; Silva et al., 2016). Moreover, given the fact that most variances were observed when reading was involved, another explanation that has been proposed is that ‘high demand on phonological working memory leads to activation differences between participants with and without dyslexia in a nearby superior frontal region’ (Schulz et al., 2008: 165). To sum up, research on the semantic abilities of people with dyslexia reveals that, although at the neurocognitive level some differences during semantic processing might be identifiable, at the behavioural level people with dyslexia appear to have well-preserved semantic skills, on which they greatly rely to overcome the phonological and memory issues hindering effective vocabulary and reading development in alphabetical languages. Further research is necessary to confirm whether the same compensatory effects can be found for non-alphabetic languages. Finally, much remains to be explained as to the reasons why, in spite of seemingly intact semantic abilities, some dyslexic people’s reading comprehension is below biographical and/or reading age and why, at least in a considerable number of studies, their vocabulary knowledge is said to differ from that of typical readers, whether in size, depth or both. Since this has been observed especially in expressive tasks, both written

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and oral (Łockiewicz et al., 2019; Wiseheart & Altmann, 2018), some indications may come from research on lexical retrieval. 5 Rapid Naming, Working Memory and Lexical Retrieval

Discussing the role of rapid naming efficiency in vocabulary and semantic skills is beyond the scope of this overview (see Noccetti, Chapter 11, this volume). However, given the complexity of factors contributing to determining the lexico-semantic profile of dyslexic people and of the picture we have tried to outline, a few words are in order. Issues with word retrieval and naming speed are considered a distinctive marker of dyslexia. Rapid naming skills are sometimes subsumed under phonological processes (Araújo & Faisca, 2019), and deficits in this area are seen to reflect difficulties in accessing and retrieving phonological information from long-term memory (Araújo & Faisca, 2019; Clarke et al., 2005; Snowling & Melby-Lervåg, 2016). Swanson and Hsieh (2009) claim that rapid naming issues ‘play just as important a role as phonological processes in predicting overall differences between adults with and without reading disorders’ (2009: 384). It should be noted, however, that they are found in all age groups (Araújo et al., 2015), although some studies have discovered that the deficit becomes more severe with age (Fernandes et al., 2017) and may not be easily compensated for (Jones et al., 2009; Silva et al., 2016). People with dyslexia seem to have issues with rapid naming regardless of the nature of the elements to be retrieved; but, unsurprisingly, they are especially inefficient with digit and letter naming. It is plausible, then, to assume that the issues observed in vocabulary size and semantic fluency are an epiphenomenon, i.e. the result of word retrieval and naming speed deficits rather than of reduced or atypical lexical storage. Most tests assessing productive vocabulary as well as semantic fluency tasks indeed require participants to produce words, often under time constraints, and retrieval issues would result in poor expressive performance. This may emerge in a more generalized way besides word retrieval, such as in less precise and fluent sentence production (Wiseheart & Altmann, 2018). It remains an open question whether slowed rapid naming is caused by inefficiencies with underlying cognitive processes (i.e. verbal memory) or by their processing demands. Rapid naming deficits are reliable predictors of dyslexia (Torppa et al., 2015), and dyslexic children with better rapid naming skills grow up to be better compensated adults (Eloranta et al., 2019). This may point to the fact that general processing efficiency determines rapid naming speed (Papadopoulos et al., 2016), since compensation greatly relies on semantic abilities, which in turn are also strictly connected to efficient processing abilities capable of ensuring sufficiently rapid integration of information.

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Working memory seems, therefore, to be a crucial piece of this puzzle, underlying both naming speed and the compensatory potential of semantic abilities. Working memory deficits are well attested in dyslexia (Wiseheart & Altmann, 2018) and are also known to be related to vocabulary learning and reading difficulties in children (Cowan et al., 2017; Majerus & Cowan, 2016; Papadopoulos et al., 2016), which may be another argument in support of reading’s lesser role in shaping the lexical and semantic skills of dyslexic people. 6 Concluding Remarks

Since reading and reading comprehension are inextricably tied to vocabulary knowledge and semantic skills, understanding the lexicosemantic abilities of people with dyslexia is key to gaining a complete picture of their linguistic and communicative profile. Much work is still needed because, although the past 20 years have certainly seen a growing interest in these matters, no consistent conclusions have been reached. Overall, the vast majority of the studies agree that, at a behavioural level, people with dyslexia have intact semantic abilities, which they rely on to compensate for their deficient phonology. Different conclusions have been reached by recent studies on non-alphabetical languages. Neuroimaging and electrophysiological explorations have also found differences in brain functioning during semantic processing, which points to a mismatch between the neural and the behavioural manifestations of dyslexia in semantic tasks. Research on lexical abilities has also reached inconsistent conclusions. Most studies seem to converge on reduced vocabulary knowledge, with a gap between dyslexic and typically developing children emerging or becoming more evident at school-entry age, and progressively widening over the years. Some studies have found differences at pre-school age, too. On the other hand, a few other studies have refuted disparities in vocabulary in well-compensated adult dyslexics (e.g. university students). Most of the issues observed were limited to expressive vocabulary and emerged in more complex productive tasks (e.g. sentence production and narration). Receptive vocabulary is believed to be typically spared and comparable in terms of size, depth, and organization to that of typical readers. It is not possible to say with certainty where the source of the possible differences in the lexical developmental trajectory of people with dyslexia lies. Those in favour of the view that vocabulary issues are (at least partially) independent of reduced exposure to the written text rely on evidence of deficits in lexical and serial learning, on reduced phonological sensitivity, on difficulties with verbal working memory and memory trace formation. These would make it necessary for dyslexics to have more numerous meaningful encounters with individual lexical items before they are stored in memory. Moreover, they may affect the quality

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of some of the representations in the mental lexicon and make them more fragile or unstable even after they have been set up, and therefore more difficult to retrieve. Associated word retrieval and rapid naming issues may derive from this instability or may be the cause of the inability to promptly retrieve words that have been stored. Those in favour of a view of dyslexia as an exclusively phonological reading disorder support the hypothesis that vocabulary or semantic issues are but a reflection of socioeconomic or environmental factors and of reduced reading experience. Without denying other impairments such as rapid naming and working memory deficits, they generally subsume them under issues with the phonological component of language and greater emphasis is placed on the complexity of the interplay among the many different cognitive underpinnings of reading and reading comprehension. Comparing dyslexic and illiterate people’s profiles, Huettig et al. (2018) go even as far as to claim that all markers of dyslexia result solely from reduced or suboptimal reading experience. There is no denying that reading habits and reading comprehension contribute to vocabulary growth and to semantic abilities (Cain, 2006, 2009; Cain & Oakhill, 2011; Duff et al., 2015; Yeari, 2017). Cain and Oakhill (2011) have demonstrated that the effect is confirmed over and above general cognitive skills. However, as they point out, the real driving forces behind lexical development may be inferential and memory abilities rather than reading per se: ‘Reading habits provide opportunities for vocabulary learning and reading comprehension skills supports vocabulary development’ (2011: 440). Moreover, recognizing the importance of reading in developing lexical and semantic abilities does not exclude a reciprocal effect. Perfetti and Hart (2002)’s Lexical Quality Hypothesis places at the very heart of the model the quality of lexical representations while, at the same time, underlying how reading experience is the main source of such a quality (at least in our society). More experienced readers typically have higher lexical knowledge, which makes them faster readers and better comprehenders. This does not exclude that some individuals may have underlying cognitive issues which make the process more difficult, resulting in the individual differences at the lexico-semantic level discussed in this chapter. A few words of caution are in order. Firstly, dyslexia is a developmental disorder, and this means that its manifestations at different ages may vary. Although many of the key features may remain prominent throughout the lifespan, the nature of the relationship between the deficits may change. Thus, Rose and Rouhani (2012) have shown that word-reading skills and reading and oral fluency are strongly correlated in childhood, but their relationship decreases in dyslexic adolescents, when vocabulary knowledge begins to play a more central role. Secondly, dyslexia is not associated with a univocal cognitive profile, and individual differences have been traced back to complex combinations of phonological and non-phonological factors. A great

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diversity characterizes people with the disorder (Bishop & Snowling, 2004) and this can have a decisive impact on findings on ‘secondary markers’, such as vocabulary abilities. Lexical and semantic skills (as well as the behavioural outcomes of tasks designed to test them) depend on a wide array of higher order processes, including memory, attention, phonological and auditory skills, to name but a few. It is fair to assume that individual differences in any of these aspects might result in individual differences in vocabulary knowledge or semantic processing and, therefore, in linguistic and communicative behaviour. The very type of measures used to assess lexico-semantic abilities may produce data that are influenced by this intricate interplay of factors. Data obtained from receptive vocabulary tests relying on picture-(oral) word matching (e.g. the Peabody Picture Vocabulary Test), for example, may yield better results than expressive tasks such as the WAIS Vocabulary component, fluency tests, or tests based on written materials. In order to isolate distinctive features, future research will need to operate increasingly finer distinctions between participants with dyslexia and participants with dyslexia associated with specific language impairment (see Adolf et al., 2021 and Casalini et al., Chapter 2, this volume) or other issues (e.g. ADHD, high levels of anxiety, etc.). Even if future research should prove that semantic and vocabulary deficits cannot ultimately be listed as distinctive markers of the disorder from a ‘clinical’ point of view, because dyslexia rarely manifests as an isolated disorder, the behavioural and processing differences found in many children and young adults remain nonetheless extremely relevant from a linguistic and educational perspective, as they may be a significant part of the individual linguistic experience of these people, as readers, learners and speakers. Elbro (2010) claims that, although vocabulary and semantic abilities may not influence reading disabilities directly, differences in these domains may lead to an increased perception of ‘reading handicaps’ (2010: 474), as they are often used to determine general knowledge scores in education. In other words, differences in the lexico-semantic component of language, even though still within typical range, may be perceived as (or, indeed, become) an obstacle to effective communication and to academic success. For this reason, research on dyslexia should ultimately aim to reduce and possibly remove those obstacles. Note (1) https://dyslexiaida.org/definition-of-dyslexia/ (last accessed December 2020).

References Adolf, S.M., Adlof, S.M., Baron, L.S., Bell, B.A. and Scoggins, J. (2021) Spoken word learning in children with developmental language disorder or dyslexia. Journal of Speech, Language, and Hearing Research 64 (7), 2734–2749.

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Alt, M., Hogan, T., Green, S., Gray, S., Cabbage, K. and Cowan, N. (2017) Word learning deficits in children with dyslexia. Journal of Speech, Language, and Hearing Research 60 (4), 1012–1028. Álvarez-Cañizo, M., Suárez-Coalla, P. and Cuetos, F. (2015) The role of reading fluency in children’s text comprehension. Frontiers in Psychology 6, Article 1810. Araújo, S. and Faísca, L. (2019) A meta-analytic review of naming-speed deficits in developmental dyslexia. Scientific Studies of Reading 23 (5), 349–368. Araújo, S., Reis, A., Petersson, K.M. and Faísca, L. (2015) Rapid automatized naming and reading performance: A meta-analysis. Journal of Educational Psychology 107, 868–883. Beckage, N., Smith, L. and Hills, T. (2011) Small worlds and semantic network growth in typical and late talkers. PLoS ONE 6, e19348. Ben-Dror, I., Bentin, S. and Frost, R. (1995) Semantic, phonologic, and morphologic skills in reading disabled and normal children: Evidence from perception and production of spoken Hebrew. Reading Research Quarterly 30 (4), 876–893. Betjemann, R.S. and Keenan, J.M. (2008) Phonological and semantic priming in children with reading disability. Child Development 79, 1086–1102. Bishop, D.V. and Snowling, M.J. (2004) Developmental dyslexia and specific language impairment: Same or different? Psychological Bulletin 130 (6), 858–886. Blau, M.J. (2013) The effect of semantic features on gist and verbatim memory in young adults with language learning disabilities. Unpublished master’s thesis, University of Texas at Austin. Bogaerts, L., Szmalec, A., Hachmann, W.M., Page, M.P. and Duyck, W. (2015) Linking memory and language: Evidence for a serial-order learning impairment in dyslexia. Research in Developmental Disabilities 43, 106–122. Boksa, E. (2018) Construction of longer written statements by dyslexic students within the framework of linguistic education – analysis of the semantic structure of the discourse. International Journal of Current Advanced Research 7 (2), 9891–9896. Brainerd, C.J. and Reyna, V.F. (2004) Fuzzy-trace theory and memory development. Developmental Review 24, 396–439. Brainerd, C.J. and Reyna, V.F. (2005) The Science of False Memory. New York, NY: Oxford University Press. Brainerd, C.J., Forrest, T.J., Karibian, D. and Reyna, V.F. (2006) Development of the falsememory illusion. Developmental Psychology 42, 962–979. Breznitz, Z. and Meyler, A. (2003) Speed of lower-level auditory and visual processing as a basic factor in dyslexia: Electrophysiological evidence. Brain and Language 85 (2), 166–184. Brosnan, M., Demetre, J., Hamill, S., Robson, K., Shepherd, H. and Cody, G. (2002) Executive functioning in adults and children with developmental dyslexia. Neuropsychologia 40, 2144–2155. Caglar-Ryeng, Ø., Eklund, K. and Nergård-Nilssen, T. (2019) Lexical and grammatical development in children at family risk of dyslexia from early childhood to school entry: A cross-lagged analysis. Journal of Child Language 46 (6), 1102–1126. Caglar-Ryeng, Ø., Eklund, K. and Nergård-Nilssen, T. (2020) School-entry language outcomes in late talkers with and without a family risk of dyslexia. Dyslexia 27 (1), 29–49. Cain, K. (2006) Children’s reading comprehension: The role of working memory in normal and impaired development. In S.J. Pickering (ed.) Working Memory and Education (pp. 62–91). Cambridge, MA: Academic Press. Cain, K. (2009) Making sense of text: Skills that support text comprehension and its development. Perspectives on Language and Literacy 35 (2), 11–14. Cain, K. and Oakhill, J. (2011) Matthew effects in young readers: Reading comprehension and reading experience aid vocabulary development. Journal of Learning Disabilities 44 (5), 431–443.

232  Part 2: Theoretical and Experimental Linguistic Research on Dyslexia

Cappelli, G. (2019) Pragmatic and lexical skills of learners with dyslexia and EFL learning. In M.M. Coppola, F. Di Blasio and S. Francesconi (eds) Contact Zones: Cultural, Linguistic and Literary Connections in English (pp. 55–74). Trento: Trento University Press. Cappelli, G. and Noccetti, S. (2016) Teaching specialised vocabulary to dyslexic adult second-language learners: A proposal for multimodal lexical input processing enhancement. In V. Bonsignori and B. Crawford Camiciottoli (eds) Multimodality Across Communicative Settings, Discourse Domains and Genres (pp. 37–64). Newcastle upon Tyne: Cambridge Scholars Publishing. Cappelli, G., Noccetti, S., Arcara, G. and Bambini, V. (2018) Pragmatic competence and its relationship with the linguistic and cognitive profile of young adults with dyslexia. Dyslexia 24 (3), 294–306. Cardillo, R., Basso Garcia, R., Mammarella, I.C. and Cornoldi, C. (2018) Pragmatics of language and theory of mind in children with dyslexia with associated language difficulties or non-verbal learning disabilities. Applied Neuropsychology: Child 7 (3), 245–256. Cavalli, E., Casalis, S., El Ahmadi, A., Zira, M., Poracchia-George, F. and Colé, P. (2016) Vocabulary skills are well developed in university students with dyslexia: Evidence from multiple case studies. Research in Developmental Disabilities 51, 89–102. Chen, A., Wijnen, F., Koster, C. and Schnack, H. (2017) Individualized early prediction of familial risk of dyslexia: A study of infant vocabulary development. Frontiers in Psychology 8, Article 156, 1–13. Chik, P.P.M., Ho, C.S.H., Yeung, P.S., Wong, Y.K., Chan, D.W.O., Chung, K.K.H. and Lo, L.Y. (2012) Contribution of discourse and morphosyntax skills to reading comprehension in Chinese dyslexic and typically developing children. Annals of Dyslexia 62 (1), 1–18. Clarke, P., Hulme, C. and Snowling, M.J. (2005) Individual differences in RAN and reading: A response timing analysis. Journal of Research in Reading 28 (2), 73–86. Clayton, F.J., Sears, C., Davis, A. and Hulme, C. (2018) Verbal task demands are key in explaining the relationship between paired-associate learning and reading ability. Journal of Experimental Child Psychology 171, 46–54. Collins, A.M. and Loftus, E.F. (1975) A spreading activation theory of semantic processing. Psychological Review 82, 407–428. Coltheart, M. (2006) Dual route and connectionist models of reading: An overview. London Review of Education 4 (1), 5–17. Coltheart, M., Rastle, K., Perry, C., Langdon, R. and Ziegler, J. (2001) DRC: A dual route cascaded model of visual word recognition and reading aloud. Psychological Review 108, 204–256. Cooper, A. and Wang, Y. (2013) Effects of tone training on Cantonese tone-word learning. Journal of the Acoustical Society of America 134 (2), 133–139. Corkett, J.K. and Parrila, R. (2008) Use of context in the word recognition process by adults with a significant history of reading difficulties. Annals of Dyslexia 58 (2), 139–161. Cowan, N., Hogan, T.P., Alt, M., Green, S., Cabbage, K.L., Brinkley, S. and Gray, S. (2017) Short-term memory in childhood dyslexia: Deficient serial order in multiple modalities. Dyslexia 23, 209–233. Daikhin, L., Raviv, O. and Ahissar, M. (2017) Auditory stimulus processing and task learning are adequate in dyslexia, but benefits from regularities are reduced. Journal of Speech, Language, and Hearing Research 60 (2), 471–479. Deacon, S.H., Tong, X. and Mimeau, C. (2019) 15 Morphological and semantic processing in developmental dyslexia. In L. Verhoeven, C. Perfetti and K. Pugh (eds) Developmental Dyslexia Across Languages and Writing Systems (pp. 327–349). Cambridge: Cambridge University Press. Di Betta, A.M. and Romani, C. (2006) Lexical learning and dysgraphia in a group of adults with developmental dyslexia. Cognitive Neuropsychology 23 (3), 376–400.

The Impact of Dyslexia on Lexico-Semantic Abilities: An Overview  233

Dittinger, E., Chobert, J., Ziegler, J.C. and Besson, M. (2017) Fast brain plasticity during word learning in musically-trained children. Frontiers in Human Neuroscience 11, 233. Dóczi, B. and Kormos, J. (2016) Longitudinal Developments in Vocabulary Knowledge and Lexical Organization. Oxford: Oxford University Press. Duff, D., Tomblin, J.B. and Catts, H. (2015) The influence of reading on vocabulary growth: A case for a Matthew effect. Journal of Speech, Language, and Hearing Research 58 (3), 853–864. Dunn, L.M. and Dunn, D.M. (2007) PPVT-4: Peabody Picture Vocabulary Test. Minneapolis, MN: Pearson Assesments. Dyson, H., Best, W., Solity, J. and Hulme, C. (2017) Training mispronunciation correction and word meanings improves children’s ability to learn to read words. Scientific Studies of Reading 21, 392–407. Edwards, J., Beckman, M.E. and Munson, B. (2004) The interaction between vocabulary size and phonotactic probability effects on children’s production accuracy and fluency in nonword repetition. Journal of Speech, Language, and Hearing Research 47, 421–436. Elbro, C. (2010) Dyslexia as disability or handicap: When does vocabulary matter? Journal of Learning Disabilities 43 (5), 469–478. Elbro, C. and Jensen, M.N. (2005) Quality of phonological representations, verbal learning, and phoneme awareness in dyslexic and normal readers. Scandinavian Journal of Psychology 46, 375–384. Eloranta, A.K., Närhi, V.M., Eklund, K.M., Ahonen, T.P. and Aro, T.I. (2019) Resolving reading disability. Childhood predictors and adult-age outcomes. Dyslexia 25 (1), 20–37. Fernald, A., Marchman, V.A. and Weisleder, A. (2013) SES differences in language processing skill and vocabulary are evident at 18 months. Developmental Science 16 (2), 234–248. Fernandes, T., Araújo, S., Sucena, A., Reis, A. and Castro, S.L. (2017) The 1-min screening test for reading problems in college students: Psychometric properties of the 1-min TIL. Dyslexia 23 (1), 66–87. Fletcher, J.M., Forman, B.R., Boudousquie, A., Barnes, M.A., Schatschneider, C. and Francis, D.J. (2002) Assessment of reading and learning disabilities: A research-based intervention-oriented approach. Journal of School Psychology 40, 27–63. Galaburda, A.M., LoTurco, J., Ramus, F., Fitch, R.H. and Rosen, G.D. (2006) From genes to behavior in developmental dyslexia. Nature Neuroscience 9 (10), 1213–1217. Gathercole, S.E., Willis, C., Emslie, H. and Baddeley, A.D. (1992) Phonological memory and vocabulary development during the early school years: A longitudinal study. Developmental Psychology 28, 887–898. Georgiou, G.K., Papadopoulos, T.C., Fella, A. and Parrila, R. (2012) Rapid naming speed components and reading development in a consistent orthography. Journal of Experimental Child Psychology 112 (1), 1–17. Georgiou, G.K., Martinez, D., Vieira, A.P.A., Antoniuk, A., Romero, S. and Guo, K. (2021) A meta-analytic review of comprehension deficits in students with dyslexia. Annals of Dyslexia 1–45. Golubovic, S.M. and Tubin, S. (2013) Semantic abilities in children with dyslexia. Paper presented at the 21st World Congress of Neurology, Vienna, Austria, 21–26 September 2013. Griffiths, C.B. (2007) Pragmatic abilities in adults with and without dyslexia: A pilot study. Dyslexia 13, 276–296. Gupta, P. (2003) Examining the relationship between word learning, nonword repetition, and immediate serial recall in adults. Quarterly Journal of Experimental Psychology 56, 1213–1236. Gupta, P. and Tisdale, J. (2009) Does phonological short-term memory causally determine vocabulary learning? Toward a computational resolution of the debate. Journal of Memory and Language 61, 481–502.

234  Part 2: Theoretical and Experimental Linguistic Research on Dyslexia

Haft, S.L., Myers, C.A. and Hoeft, F. (2016), Socioemotional and cognitive resilience in children with reading disabilities. Current Opinion in Behavioral Sciences 10, 133–141. Hatcher, J., Snowling, M.J. and Griffiths, Y.M. (2002) Cognitive assessment of dyslexic students in higher education. The British Journal of Educational Psychology 72, 119–133. Helenius, P., Salmelin, R. and Connolly, J.F. (1999) Semantic cortical activation in dyslexic readers. Journal of Cognitive Neuroscience 11 (5), 535–550. Hennessey, N.W., Deadman, A. and Williams, C. (2012) Semantic effects on word naming in children with developmental dyslexia. Journal of Research in Reading 35, 267–286. Hills, T.T., Maouene, M., Maouene, J., Sheya, A. and Smith, L.B. (2009) Categorical structure among shared features in networks of early learned nouns. Cognition 112, 381–396. Huettig, F., Lachmann, T., Reis, A. and Petersson, K.M. (2018) Distinguishing cause from effect. Many deficits associated with developmental dyslexia may be a consequence of reduced and suboptimal reading experience. Language, Cognition and Neuroscience 33 (3), 333–350. Hulme, C., Nash, H.M., Gooch, D., Lervåg, A. and Snowling, M.J. (2015) The foundations of literacy development in children at FR of dyslexia. Psychological Science 26 (12), 1877–1886. Jednoróg, K., Marchewka, A., Tacikowski, P. and Grabowska, A. (2010) Implicit phonological and semantic processing in children with developmental dyslexia: Evidence from event related potentials. Neuropsychologia 48 (9), 2447–2457. Jones, M.W., Branigan, H.P. and Kelly, M.L. (2009) Dyslexic and nondyslexic reading fluency: Rapid automatized naming and the importance of continuous lists. Psychonomic Bulletin & Review 16 (3), 567–572. Kalashnikova, M. and Burnham, D. (2018) Infant-directed speech from seven to nineteen months has similar acoustic properties but different functions. Journal of Child Language 45, 1035–1053. Kalashnikova, M., Goswami, U. and Burnham, D. (2020) Novel word learning deficits in infants at family risk for dyslexia. Dyslexia 26 (1), 3–17. Kormos, J. (2020) Specific learning difficulties in second language learning and teaching. Language Teaching 53 (2), 129–143. Koster, C., Been, P.H. and Diepstra, H.D. (2005) Differences at 17 months: Productive familial risk for dyslexia and typically developing infants. Journal of Speech Language and Hearing Research 48 (2), 426–438. Laasonen, M., Service, E., Lipsanen, J. and Virsu, V. (2012) Adult developmental dyslexia in a shallow orthography: Are there subgroups? Reading and Writing 25, 71–108. Landerl, K., Fussenegger, B., Moll, K. and Willburger, E. (2009) Dyslexia and dyscalculia: Two learning disorders with different cognitive profiles. Journal of Experimental Child Psychology 103, 309–324. Langedijk, A. (2019) Predicting dyslexia and vocabulary age. Unpublished Bachelor Thesis, Utrecht University. Li, P., Farkas, I. and MacWhinney, B. (2004) Early lexical development in a self-organizing neural network. Neural Networks 17, 1345–1362. Litt, R.A. and Nation, K. (2014) The nature and specificity of paired associate learning deficits in children with dyslexia. Journal of Memory and Language 71, 71–88. Litt, R.A., de Jong, P.F., van Bergen, E. and Nation, K. (2013) Dissociating crossmodal and verbal demands in paired associate learning (PAL): What drives the PAL-reading relationship? Journal of Experimental Child Psychology 115 (1), 137–149. Livingston, L.A. and Happé, F. (2017) Conceptualising compensation in neurodevelopmental disorders: Reflections from autism spectrum disorder. Neuroscience & Biobehavioral Reviews 80, 729–742. Łockiewicz, M., Jaskulska, M. and Fawcett, A. (2019) The analysis of free writing, vocabulary, and dyslexia in English as a native and foreign language (English vs. Polish students). Health Psychology Report 7 (1), 57–68.

The Impact of Dyslexia on Lexico-Semantic Abilities: An Overview  235

Lyytinen, P. and Lyytinen, H. (2004) Growth and predictive relations of vocabulary and inflectional morphology in children with and without familial risk for dyslexia. Applied Psycholinguistics 25 (3), 397–411. Lyytinen, H., Aro, M., Eklund, K., Erskine, J., Guttorm, T., Laakso, M.L., Leppänen, P.H.T., Lyytinen, P., Poikkeus, A.M. and Torppa, M. (2004) The development of children at familial risk for dyslexia: Birth to early school age. Annals of Dyslexia 54 (2), 184–220. Lyytinen, H., Ahonen, T., Eklund, K., Guttorm, T.K., Laakso, M.L., Leinonen, S., Leppänen, P.H.T., Lyytinen, P., Poikkeus, A.M., Puolakanaho, P., Richardson, U. and Viholainen, H. (2001) Developmental pathways of children with and without familial risk for dyslexia during the first years of life. Developmental Neuropsychology 20 (2), 535–554. Majerus, S. and Cowan, N. (2016) The nature of verbal short-term impairment in dyslexia: The importance of serial order. Frontiers in Psychology 7, Article 1522. Marshall, C.R., Jones, A., Fastell, A., Atkinson, J., Botting, N. and Morgan, G. (2018) Semantic fluency in deaf children who use spoken and signed language in comparison with hearing peers. International Journal of Language and Communication Disorders 53, 157–170. Marzocchi, G.M., Oosterlaan, J., Zuddas, A., Cavolina, P., Geurts, H., Redigolo, D., Vio, C. and Sergeant, J.A. (2008) Contrasting deficits on executive functions between ADHD and reading disabled children. Journal of Child Psychology and Psychiatry 49, 543–552. Mayringer, H. and Wimmer, H. (2000) Pseudoname learning by German-speaking children with dyslexia: Evidence for a phonological learning deficit. Journal of Experimental Child Psychology 75, 116–133. Meara, P.M. and Jones, G. (1990) The Eurocentres Vocabulary Size Tests: 10KA. Zurich: Eurocentres. Mengisidou, M., Marshall, C.R. and Stavrakaki, S. (2020) Semantic fluency difficulties in developmental dyslexia and developmental language disorder (DLD): Poor semantic structure of the lexicon or slower retrieval processes? International Journal of Language & Communication Disorders 55 (2), 200–215. Messbauer, V.C.S. and de Jong, P.F. (2003) Word, nonword, and visual paired associate learning in Dutch dyslexic children. Journal of Experimental Child Psychology 84, 77–96. Messer, D. and Dockrell, J.E. (2006) Children’s naming and word-finding difficulties: Descriptions and explanations. Journal of Speech, Language, and Hearing Research 49, 309–324. Mielnik, A., Łockiewicz, M. and Bogdanowicz, M. (2015) Semantic and phonological verbal fluency in students with dyslexia. Acta Neuropsychologica 13, 253–266. Miles, T.R., Thierry, G., Roberts, J. and Schiffeldrin, J. (2006) Verbatim and gist recall of sentences by dyslexic and non-dyslexic adults. Dyslexia 12, 177–194. Montag, J.L., Jones, M.N. and Smith, L.B. (2015) The words children hear: Picture books and the statistics for language learning. Psychological Science 26 (9), 1489–1496. Nash, H.M., Hulme, C., Gooch, D. and Snowling, M.J. (2013) Preschool language profiles of children at FR of dyslexia: Continuities with specific language impairment. Journal of Child Psychology and Psychiatry 54 (9), 958–968. Nation, I. (2001) Learning Vocabulary in Another Language. Cambridge: Cambridge University Press. Nation, I. and Beglar, D. (2007) A vocabulary size test. The Language Teacher 31 (7), 9–13. Nation, K. (2017) Nurturing a lexical legacy: Reading experience is critical for the development of word reading skill. NPJ Science of Learning 2, art. 3. Nation, K. and Snowling, M.J. (1998) Individual differences in contextual facilitation: Evidence from dyslexia and poor reading comprehension. Child Development 69 (4), 996–1011. Newcombe, F. (1969) Missile Wounds of the Brain. Oxford: Oxford University Press.

236  Part 2: Theoretical and Experimental Linguistic Research on Dyslexia

Nicolson, R. and Fawcett, A. (1990) Automaticity: A new framework for dyslexia research? Cognition 35 (2), 159–182. Nobre, A.D.P. and Salles, J.F.D. (2016) Lexical–semantic processing and reading: Relations between semantic priming, visual word recognition and reading comprehension. Educational Psychology 36, 753–770. Noccetti, S. and Cappelli, G. (2018) Blended learning and memory-training techniques for specialised vocabulary learning in adult EFL learners with dyslexia. In B. Garzelli and E. Ghia (eds) Le lingue dei centri linguistici nelle sfide europee e internazionali: formazione e mercato del lavoro (pp. 181–198). Pisa: ETS. Noordenbos, M.W. and Serniclaes, W. (2015) The categorical perception deficit in dyslexia: A meta-analysis. Scientific Studies of Reading 19 (5), 340–359. Obidziński, M. and Nieznański, M. (2017) False memory for orthographically versus semantically similar words in adolescents with dyslexia: A fuzzy-trace theory perspective. Annals of Dyslexia 67 (3), 318–332. Ouellette, G. and Shaw, E. (2014) Oral vocabulary and reading comprehension: An intricate affair. L’Année Psychologique 114 (04), 623–645. Papadopoulos, T.C., Spanoudis, G.C. and Georgiou, G.K. (2016) How is RAN related to reading fluency? A comprehensive examination of the prominent theoretical accounts. Frontiers in Psychology 7, Article 1217, 1–15. Parrila, R., Georgiou, G. and Corkett, J. (2007) University students with a significant history of reading difficulties: What is and is not compensated? Exceptionality Education International 17 (2), 195–220. Pennington, B. (2006) From single to multiple deficit models of developmental disorders. Cognition 101 (2), 385–413. Perfetti, C.A. (1985) Reading Ability. Oxford: Oxford University Press. Perfetti, C.A. (1999) Comprehending written language: A blueprint of the reader. In C. Brown and P. Hagoort (eds) The Neurocognition of Language (pp. 167–208). Oxford: Oxford University Press. Perfetti, C.A. and Hart, L. (2002) The lexical quality hypothesis. In L. Verhoeven, C. Elbro and P. Reitsma (eds) Precursors of Functional Literacy (pp. 189–213). Amsterdam: John Benjamins. Perfetti, C. and Stafura, J. (2014) Word knowledge in a theory of reading comprehension. Scientific Studies of Reading 18 (1), 22–37. Perfetti, C.A., Wlotko, E.W. and Hart, L.A. (2005) Word learning and individual differences in word learning reflected in event-related potentials. Journal of Experimental Psychology: Learning, Memory, and Cognition 31, 1281 Perfetti, C., Yang, C.L. and Schmalhofer, F. (2008) Comprehension skill and word-to-text integration processes. Applied Cognitive Psychology 22, 303–318. Plaut, D.C. and Booth, J.R. (2000) Individual and developmental differences in semantic priming: Empirical and computational support for a single-mechanism account of lexical processing. Psychological Review 107, 786–823. Protopapas, A., Mouzaki, A., Sideridis, G.D., Kotsolakou, A. and Simos, P.G. (2013) The role of vocabulary in the context of the simple view of reading. Reading & Writing Quarterly: Overcoming Learning Difficulties 29 (2), 168–202. Ransby, M.J. and Swanson, H.L. (2003) Reading comprehension skills of young adults with childhood diagnoses of dyslexia. Journal of Learning Disabilities 36 (6), 538–555. Rasamimanana, M., Barbaroux, M., Colé, P. and Besson, M. (2020) Semantic compensation and novel word learning in university students with dyslexia. Neuropsychologia 139, 107358. Read, J. (1998) Validating a test to measure depth of vocabulary knowledge. In A. J. Kunnan (ed.) Validation in Language Assessment (pp. 41–60). Mahwah, NJ: Lawrence Erlbaum. Read, J. (2004) Plumbing the depths: How should the construct of vocabulary knowledge be defined. In B. Laufer and P. Bogaards (eds) Vocabulary in a Second Language: Selection, Acquisition and Testing (pp. 209–227). Amsterdam: John Benjamins.

The Impact of Dyslexia on Lexico-Semantic Abilities: An Overview  237

Reiter, A., Tucha, O. and Lange, K.W. (2005) Executive functions in children with dyslexia. Dyslexia 11, 116–131. Reyna, V.F. (2012) A new intuitionism: Meaning, memory, and development in fuzzy-trace theory. Judgment and Decision Making 7, 332–359. Robichon, F., Besson, M. and Habib, M. (2002) An electrophysiological study of dyslexic and control adults in a sentence reading task. Biological Psychology 59, 29–53. Rodd, J., Gaskell, G. and Marslen-Wilson, W. (2002) Making sense of semantic ambiguity: Semantic competition in lexical access. Journal of Memory and Language 46, 245266. Rogers, T.T. and McClelland, J.L. (2008) Précis of semantic cognition: A parallel distributed processing approach. Behavioral and Brain Sciences 31, 689–714. Rohrer, D., Wixted, J.T., Salmon, D.P. and Butters, N. (1995) Retrieval from semantic memory and its implications for Alzheimer’s disease. Journal of Experimental Psychology: Learning, Memory, and Cognition 21, 1127–1139. Rose, T. and Rouhani, P. (2012) Influence of verbal working memory depends on vocabulary: Oral reading fluency in adolescents with dyslexia. Mind, Brain, and Education 6 (1), 1–9. Sarkadi, Á. (2008) Vocabulary learning in dyslexia: The case of a Hungarian learner. In J. Kormos and E.H. Kontra (eds) Language Learners with Special Needs: An International Perspective (pp. 110–129). Bristol: Multilingual Matters. Savill, N., Ellis, A.W. and Jefferies, E. (2017) Newly-acquired words are more phonologically robust in verbal short-term memory when they have associated semantic representations. Neuropsychologia 98, 85–97. Schiff, R., Cohen, M., Marton, R. and Sasson, A. (2019) Auditory morphological knowledge in adults with dyslexia: The importance of semantic information. Scientific Studies of Reading 23 (4), 317–333. Schmitt, N. (2014) Size and depth of vocabulary knowledge: What the research shows. Language Learning 64 (4), 913–951. Schulz, E., Maurer, U., van der Mark, S., Bucher, K., Brem, S., Martin, E. and Brandeis, D. (2008) Impaired semantic processing during sentence reading in children with dyslexia: Combined fMRI and ERP evidence. Neuroimage 41 (1), 153–168. Silva, P.B., Ueki, K., Oliveira, D.G., Boggio, P.S. and Macedo, E.C. (2016) Early stages of sensory processing, but not semantic integration, are altered in dyslexic adults. Frontiers in Psychology 7, 430. Simi, N. (2018) APACS and BLED Santa Lucia, two tests for analyzing the perception of Italian humorous jokes in subjects with and without dyslexia. Frontiers in Psychology Conference Abstract: XPRAG.it 2018 - Second Experimental Pragmatics in Italy Conference. Simi, N. (2021) Developmental Dyslexia and Anaphora Resolution in English L1 and L2: The Effects of Referent Abstractness. Newcastle upon Tyne: Cambridge Scholars Publishing. Simmons, F. and Singleton, C. (2000) The reading comprehension abilities of dyslexic students in higher education. Dyslexia 6 (3), 178–192. Smith, F.R., Gaskell, M.G., Weighall, A.R., Warmington, M., Reid, A.M. and Henderson, L.M. (2018) Consolidation of vocabulary is associated with sleep in typically developing children, but not in children with dyslexia. Developmental Science 21 (5), e12639. Smith-Spark, J. and Fisk, J. (2007) Working memory functioning in developmental dyslexia. Memory 15 (1), 34–56. Smith-Spark, J.H., Henry, L.A., Messer, D.J. and Zięcik, A.P. (2017) Verbal and non-verbal fluency in adults with developmental dyslexia: Phonological processing or executive control problems? Dyslexia 23 (3), 234–250. Snowling, M.J. (2006) Nonword repetition and language learning disorders: A developmental contingency framework. Applied Psycholinguistics 27, 588–591. Snowling, M.J. (2019) Dyslexia: A Very Short Introduction. Oxford: Oxford University Press.

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Snowling, M.J. and Hulme, C. (2012) Annual research review: The nature and classification of reading disorders: A commentary on proposals for DSM-5. Journal of Child Psychology and Psychiatry 53 (5), 593–607. Snowling, M.J. and Melby-Lervag, M. (2016) Oral language deficits in familial dyslexia: A meta-analysis and review. Psychological Bulletin 142, 498–545. Snowling, M., Chiat, S. and Hulme, C. (1991) Words, nonwords, and phonological processes: Some comments on Gathercole, Willis, Emslie, and Baddeley. Applied Psycholinguistics 12, 369–373. Snowling, M.J., Gallagher, A. and Frith, U. (2003) Family risk of dyslexia is continuous: Individual differences in the precursors of reading skill. Child Development 74, 358– 373. Snowling, M.J., Muter, V. and Carroll, J.M. (2007) Children at FR of dyslexia: A follow-up in adolescence. Journal of Child Psychology and Psychiatry 48 (6), 609–618. Snowling, M.J., Nation, K., Moxham, P., Gallagher, A. and Frith, U. (1997) Phonological processing skills of dyslexic students in higher education: A preliminary report. Journal of Research in Reading 20, 31–41. Snowling, M.J., Nash, H.M., Gooch, D.C., Hayiou-Thomas, M.E., Hulme, C. and Wellcome Language and Reading Project Team (2019) Developmental outcomes for children at high risk of dyslexia and children with developmental language disorder. Child Development 90 (5), e548–e564. Song, S., Su, M., Kang, C., Liu, H., Zhang, Y., McBride-Chang, C., Tardif, T., Li, H., Liang, W., Zhang, Z. and Shu, H. (2015) Tracing children’s vocabulary development from preschool through the school-age years: An 8-year longitudinal study. Developmental Science 18, 119–131. Staels, E. and Van den Broeck, W. (2017) A specific implicit sequence learning deficit as an underlying cause of dyslexia? Investigating the role of attention in implicit learning tasks. Neuropsychology 31, 371–382. Stafura, J.Z. and Perfetti, C.A. (2017) Integrating word processing with text comprehension. In K. Cain, D.L. Compton and R.K. Parrila (eds) Theories of Reading Development (pp. 9–31). Amsterdam: John Benjamins. Stanovich, K.E. (1980) Toward an interactive-compensatory model of individual differences in the development of reading fluency. Reading Research Quarterly 16 (1), 32–71. Swanson, H.L. (2012) Adults with reading disabilities: Converting a meta-analysis to practice. Journal of Learning Disabilities 45 (1), 17–30. Swanson, H.L. and Hsieh, C.J. (2009) Reading disabilities in adults: A selective metaanalysis of the literature. Review of Educational Research 79 (4), 1362–1390. Sweins, P. (2015) Deficient rapid memory trace formation for novel words in developmental dyslexia. Unpublished dissertation, University of Helsinki. Tamis-LeMonda, C.S., Bornstein, M.H. and Baumwell, L. (2001) Maternal responsiveness and children’s achievement of language milestones. Child Development 72 (3), 748–767. Taylor, J.N. and Perfetti, C.A. (2016) Eye movements reveal readers’ lexical quality and reading experience. Reading and Writing 29 (6), 1069–1103. Thomson, J.M. and Goswami, U. (2010) Learning novel phonological representations in developmental dyslexia: Associations with basic auditory processing of rise time and phonological awareness. Reading & Writing 23, 453–469. Torppa, M., Eklund, K., van Bergen, E. and Lyytinen, H. (2015) Late-emerging and resolving dyslexia: A follow-up study from age 3 to 14. Journal of Abnormal Child Psychology 43, 1389–1401. Torppa, M., Lyytinen, P., Erskine, J., Eklund, K. and Lyytinen, H. (2010) Language development, literacy skills, and predictive connections to reading in Finnish children with and without familial risk for dyslexia. Journal of Learning Disabilities 43, 308–321. Van der Kleij, S.W., Segers, E., Groen, M.A. and Verhoeven, L. (2017) Response to intervention as a predictor of long-term reading outcomes in children with dyslexia. Dyslexia 23 (3), 268–282.

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van Goch, M.M., McQueen, J.M. and Verhoeven, L. (2014) Learning phonologically specific new words fosters rhyme awareness in Dutch preliterate children. Scientific Studies of Reading 18 (3), 155–172. van Rijthoven, R., Kleemans, T., Segers, E. and Verhoeven, L. (2018) Beyond the phonological deficit: Semantics contributes indirectly to decoding efficiency in children with dyslexia. Dyslexia 24 (4), 309–321. van Viersen, S., de Bree, E.H., Kroesbergen, E.H., Slot, E.M. and de Jong, P.F. (2015) Risk and protective factors in gifted children with dyslexia. Annals of Dyslexia 65 (3), 178–198. van Viersen, S., de Bree, E.H., Zee, M., Maassen, B., van der Leij, A. and de Jong, P.F. (2018) Pathways into literacy: The role of early oral language abilities and FR for dyslexia. Psychological Science 29 (3), 418–428. van Viersen, S., de Bree, E.H., Verdam, M., Krikhaar, E., Maassen, B., van der Leij, A. and de Jong, P.F. (2017) Delayed early vocabulary development in children at family risk of dyslexia. Journal of Speech, Language, and Hearing Research 60 (4), 937–949. Vandermosten, M., Wouters, J., Ghesquière, P. and Golestani, N. (2019) Statistical learning of speech sounds in dyslexic and typical reading children. Scientific Studies of Reading 23 (1), 116–127. Varvara, P., Varuzza, C., Sorrentino, A.C.P., Vicari, S. and Meneghini, D. (2014) Executive functions in developmental dyslexia. Frontiers in Human Neuroscience 8, 1–8. Vellutino, F.R., Scanlon, D.M. and Spearing, D. (1995) Semantic and phonological coding in poor and normal readers. Journal of Experimental Child Psychology 59 (1), 76–123. Vellutino, F.R., Fletcher, J.M., Snowling, M.J. and Scanlon, D.M. (2004) Specific reading disability (dyslexia): What have we learned in the past four decades? Journal of Child Psychology and Psychiatry 45, 2–40. Verhoeven, L. and van Leeuwe, J. (2008) Prediction of the development of reading comprehension: A longitudinal study. Applied Cognitive Psychology 22, 407–423. Walley, A.C., Metsala, J.L. and Garlock, V.M. (2003) Spoken vocabulary growth: Its role in the development of phoneme awareness and early reading ability. Reading and Writing: An Interdisciplinary Journal 16 (5), 5–20. Wang, E., Zhou, G., Wang, Y., Huang, H., Hou, Y. and Liu, J. (2017) Word recognition semantic processing defects in Chinese children with developmental dyslexia: An event-related potential study. NeuroQuantology 15 (2), 221–231. Webb, S. (2013) Depth of vocabulary knowledge. In C.A. Chapelle (ed.) The Encyclopedia of Applied Linguistics (pp. 346 –354). London: Blackwell. Wesche, M. and Paribakht, T.S. (1996) Assessing second language vocabulary knowledge: Depth versus breadth. Canadian Modern Language Review 53 (1), 13–40. Wiseheart, R. and Altmann, L.J. (2018) Spoken sentence production in college students with dyslexia: Working memory and vocabulary effects. International Journal of Language & Communication Disorders 53 (2), 355–369. Wiseheart, R., Altmann, L.J.P., Park, H. and Lombardino, L.J. (2009) Sentence comprehension in young adults with developmental dyslexia. Annals of Dyslexia 59 (2), 151–167. Wolf, M. and Segal, D. (1999) Retrieval rate, accuracy and vocabulary elaboration (RAVE) in reading-impaired children: A pilot intervention programme. Dyslexia 5 (1), 1–27. Wong, P.C. and Perrachione, T. K. (2007) Learning pitch patterns in lexical identification by native English-speaking adults. Applied Psycholinguistics 28 (4), 565–585. Xiao, X.Y. and Ho, C.S.H. (2014) Weaknesses in semantic, syntactic and oral language expression contribute to reading difficulties in Chinese dyslexic children. Dyslexia 20 (1), 74–98. Yeari, M. (2017) The role of working memory in inference generation during reading comprehension: Retention, (re)activation, or suppression of verbal information? Learning and Individual Differences 56, 1–12.

10 Dyslexia and Pragmatic Skills Gloria Cappelli, Sabrina Noccetti, Nicoletta Simi, Giorgio Arcara and Valentina Bambini

1 Introduction

Pragmatic impairment has been largely investigated in people with various cognitive disorders (Cummings, 2017, 2021; Schneider & Ifantidou, 2020). The impact of dyslexia on pragmatic abilities has, however, remained largely unexplored until very recently, although communication problems have been reported for the dyslexic population in numerous overviews of the disorder (Lovitt, 1989; McLoughlin et al., 2002; Riddick et al., 1997; Wallach & Liebergott, 1984). Some studies also report social and emotional problems, including distress with managing everyday life tasks (Griffiths, 2007; Miles et al., 2007), and problems in maintaining social interaction because of frequent misunderstanding of implicit statements or misreading of social situations (Chinn & Crossman, 1995; Hales, 1995). It is not surprising, therefore, that over the past 15 years, a growing interest in the pragmatic use of language and dyslexia has resulted in a number of studies that converge in the conclusion that people with dyslexia are less efficient in processing pragmatic meanings than their non-dyslexic peers (Cappelli et al., 2018; Cardillo et al., 2018; Ferrara et al., 2020; Griffiths, 2007). Dyslexia is traditionally defined as a specific learning disorder caused by difficulties in manipulating phonological segments, which results in an unexpected discrepancy between cognitive abilities and literacy skills. It is neurobiological in origin and manifests itself with a variety of symptoms ranging both in quality and severity (Ghidoni, Chapter 1, this volume). Its most common manifestations are poor decoding and spelling abilities, reduced graphemic competence, and reading difficulties. Several ‘secondary’ consequences, such as problems in reading comprehension and reduced reading experience, are also commonly recognized, and these can impact lexical development and background knowledge. Literacy difficulties, however, cannot account for the complexity of the communicative profiles observed in the dyslexic population. For this 240

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reason, much effort has been put into studying the abilities of people with dyslexia at various levels of the linguistic system, usually in association with other cognitive aspects. Evidence suggests that this specific learning disorder is associated with difficulties in non-word repetition and rapid naming (Melby-Lervåg et al., 2012; Ramus et al., 2013; Snowling, 2000) and impacts structural language skills at large (Arosio et al., 2017; Bishop & McDonald, 2009; Bishop & Snowling, 2004; Cantiani et al., 2013; Cardinaletti & Volpato, 2015; Hu et al., 2018; Joanisse et al., 2000). Over the past two decades, other problems have been observed in children and adults with reading disorders, including poor executive functioning (Altemeier et al., 2008; Baker & Ireland, 2007; Cardillo et al., 2018; Cutting et al., 2009; Ferrara et al., 2020; Horowitz-Kraus, 2014; Kasirer & Mashal, 2017; Locascio et al., 2010; Mashal & Kasirer, 2011; Sesma et al., 2009; Smith-Spark et al., 2016; Whitney et al., 2009), issues in working memory capacity (Baddeley, 1998; Gathercole et al., 1992), processing speed and skill automatization (Nicolson & Fawcett, 2008), vocabulary storage and retrieval (Cappelli, Chapter 9, this volume; Cappelli & Noccetti, 2016; Kormos & Smith, 2012; Noccetti, Chapter 11, this volume), text comprehension (Bishop, 1997; Ransby & Swanson, 2003; Simmons & Singleton, 2000; Xiao & Ho, 2014), and in the control of attentive resources (Lallier et al., 2009), including orienting spatial and temporal attention (Facoetti et al., 2010; Ruffino et al., 2014). Most of these issues have been associated with pragmatic difficulties in various clinical populations (Bosco et al., 2012; Martin & McDonald, 2003; Vulchanova et al., 2015). This chapter presents an overview of research on pragmatic efficiency and dyslexia. To the best of our knowledge, the studies that have discussed the impact of the disorder on pragmatic competence are still relatively few (Cappelli, 2019; Cappelli et al., 2018; Cardillo et al., 2018; Ferrara et al., 2020; Griffiths, 2007; Hu et al., 2019; Kasirer & Mashal, 2017; Kumari et al., 2016; Lam & Ho, 2014; Vender, 2017; for a review, see Troia, 2021), and mostly focus on discourse organization and the comprehension of figurative language. However, this rapidly growing body of research allows for some preliminary conclusions. Overall, individuals with dyslexia, both children and adults, have been found to perform worse than their typically developing peers (and sometimes below the cut-off used to determine an impairment) by the vast majority of the studies. Findings point towards pragmatic difficulties as a relevant yet still underestimated dimension of the communicative profile of people with dyslexia and as a potentially useful parameter for diagnostic purposes. 2 Measuring Pragmatic Skills

Communication is a complex social activity to which both linguistic and pragmatic skills contribute. Pragmatic competence is the capacity to

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use and interpret language appropriately for the context (Domaneschi & Bambini, 2020; Levinson, 1983; Sperber & Wilson, 1995). It allows us to carry out efficiently many different communicative tasks, both receptive and expressive, including encoding the message for the function it must perform, correctly identifying such function in a given context, choosing the appropriate register for the communicative situation, as well as drawing inferences to recover non-literal and implicitly communicated information (Ariel, 2010; Bambini, 2010; Stemmer, 2000). Pragmatic skills are therefore strictly connected to appropriate communication and social skills, and impairment in any of these areas may hinder educational success and have consequences for a range of everyday-life operations that are often taken for granted (Agostoni et al., 2021; Cappelli, 2019). Many activities carried out in school and university (including the foreign language classroom) rely on learners’ efficient pragmatic processing. Inability to interpret context-dependent aspects of language and associated indirect meanings results in poorer textual comprehension (Bishop, 1997; Buck, 2001; Kerbel & Grunwell, 1998; Tsou et al., 2006). Inferring rules and regularities from examples, resolving reference ambiguity, deriving novel word-meanings from the context, many reading and listening comprehension tasks (including those found in foreign language standardized tests), and appreciating figurative language in literary works, are all examples of activities that require good pragmatic skills, along with vocabulary knowledge (Cappelli, Chapter 9, this volume) and well-functioning working memory. A complex interplay of linguistic and cognitive resources is necessary for pragmatically successful behaviour. The rapid integration of much and varied linguistic and extra-linguistic contextual information comes with complex processing demands that exploit individual attention, memory, and mind-reading abilities (Bara, 2010; Sperber & Wilson, 2002). It is, therefore, not surprising that several cognitive and neural systems are involved in supporting efficient pragmatic processing, as reflected in the complex brain networks engaged for instance in the comprehension of non-literal language (e.g. figurative expressions such as metaphors and irony; Bambini et al., 2011; Spotorno et al., 2012). Pragmatic deficits have been observed in various clinical populations that are known to have impairments in such cognitive and neural systems (Cummings, 2017, 2021). From the linguistic behaviour point of view, pragmatic deficits have been associated with the inability to generate inferences, a tendency towards literal interpretation of non-literal language, such as metaphors and idiomatic expressions, and the inability to grasp emotive aspects of language and the global meaning of a story from excerpts. Pragmatic deficits have also been linked to limited sensitivity to contextual cues and anomalies in language production, such as verbosity or excessive synthesis, inappropriate language, and altered prosody in the most severe cases (Paradis, 1998).

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Investigating pragmatic skills is quite complex, because they are extremely context dependent and involve a wide range of communicative situations and several structural aspects of language. Pragmatics cross-cuts all levels of linguistic analysis: therefore, isolating the purely pragmatic components of communicative behaviour is no easy task. Moreover, deficits in pragmatics become visible in specific contexts, which need to be recreated by researchers or clinicians if no naturalistic observation is possible (Bishop & Baird, 2001; Glumbić & Brojčin, 2012; Lam & Ho, 2014). It is probably for this reason that, as of today, only a few comprehensive pragmatic tests exist which have been standardized. The studies which have investigated pragmatic abilities in people with dyslexia have for the most part relied on specifically designed protocols to investigate specific issues. This is the case of Prutting and Kittchner’s (1987) pragmatic protocol, designed to assess the communicative skills of children and adults. This protocol consists of a questionnaire that experimenters must complete after observing participants engage in spontaneous, unstructured conversation with a partner for at least 15 minutes. The questionnaire comprises a total of 30 items divided into three sections dedicated to verbal, paralinguistic and non-verbal aspects, each of which focuses on assessing whether specific features of communication (e.g. speech acts, topic, turn taking, lexical selection, stylistic variation, prosody, kinesics and proxemics, etc.) are used appropriately or inappropriately. Another example is Mashal and Kasirer’s (2011) protocol for assessing children’s comprehension of metaphors and idioms. Drawing from previous studies (Faust & Mashal, 2007; Mashal et al., 2008), they designed two questionnaires that have been used later by other researchers. One assesses through multiple-choice questions the tendency to choose the literal vs. the correct reading of 20 idioms with plausible literal interpretation. Children must choose among four options: the correct sense, the literal sense, a literal distracter, and an unrelated interpretation. The second questionnaire has the same structure but focuses on children’s ability to understand conventional and novel metaphors and to distinguish them from unrelated word pairs (e.g. sport lemon). A standardized test that has been used to assess pragmatic abilities in at least two studies on dyslexia and pragmatics (Cappelli et al., 2018; Griffiths, 2007) is Bryan’s (1995) Right Hemisphere Language Battery (RHLB). The test’s psychometric properties have been extensively examined (Bryan, 1995), but it was developed to assess the pragmatic impairment in right-hemisphere damaged adult patients, and for this reason its ability to identify issues in non-brain damaged individuals and in children may be reduced. The RHLB includes eight subtests assessing inferential meaning comprehension, lexical–semantic skills, written and picture metaphor comprehension, the understanding of humour, sensitivity to emotional and linguistic prosody, and discursive

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abilities. Most skills are tested through multiple questions asked by an examiner. Specifically, inferential meaning comprehension is assessed through questions focusing on information implicitly given in four short texts describing a situation or an event. The humour subtest includes questions with multiple punchlines among which subjects must choose the most appropriate for each of the ten jokes presented. In the metaphor comprehension tests, participants must choose among three possible interpretations of a given metaphorical expression or among four pictures depicting its sense. The score obtained in each of the sections contributes to a composite score of pragmatic abilities. One of the first tests devised to assess children’s pragmatic abilities was the Children’s Communication Checklist (CCC; Bishop, 1998). A revised version was released in 2003 (CCC-2; Bishop, 2003). The test has been used with different populations and has proven useful in discriminating difficulties associated with different developmental and learning disorders (Bishop et al., 2011; Ferguson et al., 2011; Whitehouse et al., 2008), including dyslexia (Ferrara et al., 2020; Lam & Ho, 2014). CCC is a standardized checklist that allows carers (e.g. parents, teachers, etc.) to assess strengths and weaknesses in children’s communicative behaviour in many different social contexts through observation over an extended amount of time. Validity, reliability and internal consistency have been assessed (Bishop & Baird, 2001; Geurts, 2007; Norbury et al., 2004). More specifically, the checklist assesses both language skills and linguist pragmatic performance and requires that carers judge the frequency of specific behaviours on a 4-point scale (from 0 – never or less than once a week – to 3 – more than twice a week or always). The most recent version (CCC-2) encompasses 10 subscales (i.e. speech, syntax, semantics, coherence, inappropriate initiation, stereotyped language, use of context, non-verbal communication, social relationships, and interests) made of 7 items, each focusing on a specific aspect of communication. Questions are randomized and expressed both in positive and negative terms. The aim is to determine the proficiency of children in different linguistic, communicative and social domains. Groups of subscales give composite scores for different aspects. The composite score for pragmatic skills is given by the assessment of inappropriate initiation, stereotyped language, use of context, and non-verbal communication (Pragmatic Language Composite, PLC). Other composite scores are the Structural Language Composite (SLC), the General Communication Composite (GCC) and the Social Interaction Deviance Composite (SIDC). Although the Children’s Communication Checklist is widely used and internal consistency and inter-rater reliability seems good (Bishop & Baird, 2001), the fact that it relies only on child carers’ reports is a potential limitation, because subjective interpretations or inability to understand or correctly ‘classify’ behaviours cannot be completely excluded (Bishop & McDonald, 2009).

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Cardillo et al. (2018) resorted to the Metaphor, the Implicit Meaning Comprehension and the Situations subtests of the Abilità Pragmatiche nel Linguaggio Medea (APLM; Lorusso, 2009). This battery has been designed in Italian and is meant for children between 5 and 14 years of age. Besides the components already mentioned, it includes a test with comics aimed at assessing children’s ability to understand and respect the dialogic structure of communicative exchanges, a test that determines if the examinees can understand the meaning of expressions when they are used in specific situations and a Theory of Mind test. Another standardized battery developed more recently to assess pragmatics in adult Italian-speaking populations is Arcara and Bambini’s (2016) Assessment of Pragmatic Abilities and Cognitive Substrates (APACS). The APACS test has already been used to describe pragmatic language disorders in individuals with neurological (Arcara et al., 2020; Bambini, Arcara, Martinelli et al., 2016; Bambini, Bischetti et al., 2020; Carotenuto et al., 2018, Montemurro et al., 2019) and psychiatric illnesses (Bambini, Arcara, Bechi et al., 2016; Bambini, Arcara et al., 2020), and it has been translated in several other languages in a number of ongoing studies (on the Flemish version, see Bambini et al., 2021; on the Hebrew version, see Fussman & Mashal, 2022). The study of Cappelli et al. (2018) relied primarily on this test for their assessment of dyslexic young adults’ pragmatic skills. APACS includes a production section, with a semi-structured interview about autobiographical topics (Interview) and a photograph description task (Description), as well as a comprehension section, encompassing a task in which participants are asked to answer questions about narrative texts (Narratives), two multiple-choice tasks assessing the ability to infer non-literal meanings (Figurative Language 1) and verbal humour (Humour), and a task assessing the ability to understand non-literal meanings through verbal explanation of familiar idioms, novel metaphors and common proverbs (Figurative Language 2). Three composite scores are derived from the six tasks: Pragmatic Production, Pragmatic Comprehension, and APACS Total. As is evident, the choice of relying on one or the other testing protocol has been partly determined by the characteristics of the population under investigation (e.g. age, first language) and by the limited range of the options available. However, such choice has not proven inconsequential, because, to a certain extent, it has contributed to delimiting the phenomena on which individual studies have concentrated and which have ultimately been taken to be representative of the areas of linguistic pragmatics in which dyslexia can potentially be detrimental for pragmatic processing and behaviour. There is now growing agreement that (at least some) pragmatic domains are problematic for (at least some) people with dyslexia. Despite the limited specific attention received until very recently due

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to the difficulties mentioned above, this idea is indeed not foreign to dyslexia research. In 1991, Lapadat carried out a meta-analytic review of studies on the pragmatic skills of children of 3–12 years of age who had received a diagnosis of language and/or learning disorders. The author found ‘consistent and pervasive pragmatic deficits in conversation compared to non-disordered peers [...] across settings, conversational partners, age groups, and types of pragmatic skills measured’ (Lapadat, 1991: 147). She concluded that these data could not be explained by differences in the methodology or design of the studies included in the meta-analysis and that they were likely attributable to underlying language deficits rather than to insufficient social knowledge. The main limitation of Lapadat’s (1991)’s review was the heterogeneous nature of the studies included in the analysis and, most importantly, the fact that the latter themselves did not yet have the tools to operate a finer, diagnosis-based distinction among the participants. Before discussing more recent attempts at describing the pragmatic profile of people with dyslexia, a word of caution is in order. Although in recent years our knowledge of dyslexia, of the distinctive features of the individual learning disorders and of specific language impairment, has greatly advanced, the issue of participants’ homogeneity has not been completely resolved. Dyslexia has complex manifestations and it rarely occurs in isolation. For this reason, one of the persistent criticisms with respect to any experimental conclusion is that generalizations are hardly possible, unless the assessment of pragmatic skills is accompanied by a thorough evaluation of a complex set of cognitive and communicative aspects other than dyslexia which may be responsible for the difficulties observed (see, for instance, Troia, 2021). The vast majority of the studies discussed in sections 3 and 4 have attempted to operate increasingly finer distinctions among the participants and have reached important results that advance our knowledge of the communicative profile of people with dyslexia. And although in some cases further investigation and finer profiling may be necessary for clinical application, it is our firm conviction that the results of recent research in pragmatics and dyslexia can be of great use to all those practitioners who operate and interact with children, adolescents and adults with dyslexia in contexts in which efficient pragmatic behaviour potentially makes a difference in the emotional, social and academic life of these individuals. 3 Pragmatic Abilities in Children with Dyslexia

A few recent studies (Cardillo et al., 2018; Ferrara et al., 2020; Kumari et al., 2016; Lam & Ho, 2014) have tried to carry out a general assessment of pragmatic abilities in children with dyslexia. Others have focused on specific aspects, such as the comprehension and

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generation of metaphoric language (Kasirer & Mashal, 2017) and the derivation of scalar implicatures (Hu et al., 2019). Non-literal meaning comprehension is known to be challenging for non-typically developing children, as well as for neurological and psychiatric patients (Bambini, Arcara et al., 2020; Kalandadze et al., 2018; Thoma & Daum, 2006). Difficulties with non-literal meanings and figurative language are often associated with impairment in executive functions and with poor performance in Theory of Mind (ToM) tests, which assess the ability to attribute attitudes and mental states (including communicative intentions) and to predict the behaviour of others (Bambini, Arcara, Martinelli et al., 2016; Bambini, Arcara, Bechi et al., 2016; Bosco et al., 2017; Martin & McDonald, 2003; Wampers et al., 2017). For this reason, most studies on pragmatics and dyslexia have included evaluations of these abilities and correlated them with pragmatic skills. Cardillo et al. (2018) compared linguistic pragmatic and ToM skills of children with dyslexia and associated language difficulties of children with non-verbal learning disabilities. Participants were aged between 8 and 10. Their pragmatic abilities were assessed through the Metaphor, the Implicit Meaning Comprehension and the Situations subtests of the APL Medea battery (Lorusso, 2009) described above. Social perception abilities were tested through the ToM subtest from the Italian version of NEPSY-II (Korkman et al., 2007; Urgesi et al., 2011), which is divided into a verbal task focusing on the perception of another person’s point of view and a contextual task assessing understanding of the relationship between social contexts and emotions. The authors found that children with dyslexia performed worse than typically developing children in two out of three pragmatic tasks from the APL Medea battery, as well as in verbal ToM tasks. More specifically, difficulties were observed in understanding metaphors and recovering the meaning implicitly conveyed in texts. The children also showed difficulties in understanding others’ beliefs and intentions, but not in understanding the relationship between emotions and contexts. Some of these effects lost significance when vocabulary and reading scores were controlled for, thus indicating that at least some pragmatic difficulties might be directly related to the core areas of impairment characterizing dyslexia, in particular literacy. Cardillo et al. (2018) also performed a discriminant function analysis to distinguish between children with dyslexia, children with non-verbal learning disabilities, and typically developing children. Results indicated that two tasks – the pictorial metaphor comprehension task from the APL and the verbal Theory of Mind task – were able to predict to which group each child belonged, with a 52% accuracy in the case of dyslexia. Accuracy was 81% for typically developing children and 38% for children with non-verbal learning disabilities, indicating less crucial pragmatic difficulties in the latter population. Inefficient pragmatic and ToM skills, and especially problems with figurative language, which the

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authors attribute to the inability to suppress literal meaning and create a coherent representation of the intended metaphorical meaning, might therefore be relevant features of the communicative and cognitive profile of dyslexic children. Cardillo et al.’s (2018) results confirm trends reported in earlier studies on metaphor comprehension and learning disorders, such as Seidenberg and Bernstein (1986), Mashal and Kasirer (2011) and Kasirer and Mashal (2017). Mashal and Kasirer (2011) found that adolescents with specific learning disorders differ in idiom and conventional metaphor comprehension from their typically developing peers, but not in the comprehension of novel metaphors. These results were confirmed in Kasirer and Mashal (2017), which, building on their previous study, investigated age-level differences in the comprehension and generation of metaphoric language in children, adolescents and adults with dyslexia. Significant differences between children with and without dyslexia were observed in conventional metaphor comprehension. However, dyslexic adolescents and adults performed similarly to their non-dyslexic age-matched peers in conventional and novel metaphor comprehension as well as in metaphor generation. The authors concluded that conventional and novel metaphor comprehension relies on different abilities, and that the effect of vocabulary skills and executive functions might be greater in the interpretation of the former. Accordingly, they hypothesized that the differences observed in the performance of dyslexic children with this type of familiar figurative meaning may derive from a difficulty in efficiently integrating and retrieving meanings from the mental lexicon. In contrast, children with dyslexia appear to have no trouble in finding novel semantic connections between seemingly unrelated concepts or to generate metaphors. Kasirer and Mashal (2017) suggest that an increase in efficient executive functions due to frontal lobe maturation (Anderson et al., 2001) might contribute to closing the gap in metaphor comprehension and generation between people with and without dyslexia over time (but see Smith-Spark et al., 2016 and Spencer et al., 2020 for a discussion of executive functions deficits in adults with developmental dyslexia). Another pragmatic domain largely investigated in developmental disorders is scalar implicatures (Schaeken et al., 2018). Scalar implicatures are based on linguistic expressions such as ‘some/all’ or ‘sometimes/always’ that are part of a scale organized by informativity (Horn, 1972). Since listeners normally assume that speakers will be cooperative and truthful (Grice, 1975) when they use the weaker term (e.g. ‘some presents were beautiful’) and not the stronger term (e.g. ‘all presents were beautiful’), listeners will interpret the utterance as if the stronger term did not apply (i.e. not all presents). This line of reasoning is often referred to as a preference for the pragmatic interpretation above the logical one (Noveck, 2001). Hu et al. (2019)

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observed difficulties in the interpretation of scalar implicatures in Chinese children with dyslexia and ascribed the failure to understand this type of implicature to the fact that they may not have fully acquired the meaning of the Chinese words for ‘some’ and ‘all’. However, the authors hypothesized that these children may also be less capable of recognizing contextual relevance and, therefore, processing and pragmatic limitations might play a crucial role in the observed behaviour. Lam and Ho (2014) and Ferrara et al. (2020) have investigated pragmatic skills in children with dyslexia, focusing on broader communicative abilities assessed using the CCC-2 battery (Bishop, 2003; Italian adaptation by Di Sano et al., 2013). Kumari et al. (2016) have also adopted the same perspective relying on Prutting and Kittchner’s (1987) Pragmatic Protocol. The data from the three studies converge on suggesting mild pragmatic difficulties in children with dyslexia. More specifically, Lam and Ho (2014) compared information collected by the parents of 22 Chinese dyslexic children, 22 children with autistic spectrum disorder, and 24 neurotypical children. They found that children with dyslexia had reduced pragmatic skills compared to the control group and were relatively weak in structural language skills. Their Pragmatic language composite score was significantly lower, and major difficulties were observed due to inappropriate initiation of discourse and the inefficient use of context. However, children with dyslexia did not have any significant problems in social relationships and interests, differing from children with autism. Lam and Ho (2014) attributed the pragmatic difficulties observed in dyslexic children to processing issues, since pragmatic processing is a complex task, involving efficient semantic and syntactic skills, as well as the ability to process discourse information and effectively use contextual cues, which may be hindered by poor working memory, automatization deficits and structural language difficulties. Ferrara et al. (2020) have further differentiated between children with ASD, children with dyslexia without associated language disorder (DD), and children with dyslexia with associated language disorder (DDL). Their data confirm issues in structural language and pragmatic inefficiency in children with dyslexia compared to typically developing controls, with significantly lower scores in the Coherence, Use of context, and Interests tasks. The distinction between DD and DDL children is especially interesting. DD children scored lower than DDL children in the Interests, in the Pragmatic Language composite score and in the Social Interaction Deviance composite score. They were also outperformed in the non-verbal communication subscale. Ferrara et al. (2020: 1304) observe that DD children ‘seemed to have some difficulties in the domain of social competences, pragmatic abilities (such as the comprehension of idioms, irony and sense of humour) and the management of conversation in a group of peers’. Issues with the use

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of contextual cues were explained as possible secondary consequences of difficulties in other linguistic domains. DDL children’s Pragmatic Composite Score was comparable to that of the control group. The differences between DD and DDL children emerging from the data of Ferrara et al. were unexpected. However, Kumari et al. (2016) had previously reported similar results comparing children with dyslexia and dysgraphia and children with dyslexia without any other co-occurring learning deficit. They found that the former performed better in pragmatic tasks than the latter. Ferrara et al. (2020) hypothesize that DDL children’s better pragmatic skills and non-verbal communication might be due to early intervention. Children with a history of language disorder are identified and treated earlier than children without clear language delays or deficits. In these cases, dyslexia is diagnosed at a later stage, usually at school age, when children start to lag behind their peers in the acquisition of reading skills. It is indeed known that early intervention is a protective factor for linguistic and cognitive development, academic success and emotional well-being (Curtis et al., 2019). Another domain in which Ferrara et al. (2020) found children with dyslexia (both with and without language impairment) to obtain worse scores than both typically developing and autistic peers was narrative coherence. They argue that this may be explained again by structural language issues (e.g. phonology, semantics and syntax). Poor narratives would therefore be the manifestation of difficulties with manipulating sounds, word retrieval and syntactic constructions (Ferrara et al., 2020: 1309). Kumari et al. (2016: 230) also reported limited use of speech acts and conversational repair strategies, inadequate topic maintenance and turn taking, and reduced cohesion. Conversely, only children with co-occurring learning disorders (dyslexia, dysgraphia, and dyscalculia) were found to be impaired in non-verbal communication in their study. Overall, research agrees that children with dyslexia are less competent in pragmatic tasks than their unaffected peers, especially in understanding figurative uses of language (e.g. metaphors, idioms, humour) and inferring other types of meaning (e.g. scalar implicatures, implicit information), may exhibit deficits in ToM and executive functions, and that at least some of them may have difficulties in use of context, in organizing narratives and in the domain of social competences (e.g. in managing conversation in a group of peers). Most of these problems might be attributed to a complex interplay of mild structural language difficulties, reduced vocabulary (Cappelli, Chapter 9, this volume), poor working memory and executive functions (Smith-Spark et al., 2016; Spencer et al., 2020), and may decrease or disappear with neural development and age (Kasirer & Mashal, 2017). It is, however, not uncontroversial that pragmatic inefficiency with figurative language and inferential processing is limited to childhood

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and adolescence. Simmons and Singleton (2000), Griffiths (2007) and Cappelli et al. (2018) found issues in these areas in young adults as well. A persistence of pragmatic difficulties into adulthood cannot therefore be completely excluded, and further research is required to verify if different types of figurative language may be responsible for different outcomes, or whether it is in fact the testing methodology or the great diversity of the cognitive and linguistic profiles of dyslexic people that is responsible for the inconsistencies in the results across the lifespan. 4 Pragmatic Abilities in Adults with Dyslexia

To the best of our knowledge, only very few studies have focused on adults with dyslexia. Kasirer and Mashal (2017) considered various age groups, including adults with dyslexia, and, as mentioned above, found no significant difference in metaphor comprehension in this latter group with respect to the non-dyslexic adult group. In addition, adults without dyslexia were outperformed in metaphor generation. Griffiths (2007) and Cappelli et al. (2018) are the only other studies on pragmatic skills in young adults with dyslexia, and their research has focused on comparable groups of high-functioning adults enrolled in university with and without the disorder. Both found the pragmatic abilities of participants with dyslexia to be reduced compared to peers without dyslexia. Griffiths (2007) compared the results of 20 English-speaking university students with dyslexia and 20 controls on subtests from Fawcett and Nicolson’s (1998) Dyslexia Adult Screening Test (DAST) and on four adapted subtests from Bryan’s (1995) Right Hemisphere Language Battery assessing pragmatics in comprehension. Results evidenced marked difficulties in understanding humour and deriving inferential information from a storyline. Moreover, problems also emerged in figurative language comprehension. More general cognitive and linguistic abilities were evaluated and, as expected, participants showed deficits in the Phonemic Segmentation, Rapid Naming and Backward Digit Span subtests of DAST, indicative of reduced processing speed, working memory inefficiency and deficit in automatization. The DAST data consistently correlated with the RHLB scores, which led the author to hypothesize that cognitive inefficiency might produce cognitive overload that would in turn result in the inefficient processing of non-literal language. Cappelli et al. (2018) assessed the pragmatic skills of well compensated Italian-speaking young adults with dyslexia compared with controls. They employed the APACS test, as a comprehensive pragmatic assessment tool, also targeting production (Arcara & Bambini, 2016). In addition, to allow for a comparison with Griffiths’s (2007) study, pragmatic comprehension was also assessed with five subtests from

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the Batteria sul Linguaggio dell’Emisfero Destro SantaLucia (BLED; Rinaldi et al., 2006). The battery was specifically developed for Italian and follows the model of the Right Hemisphere Language Battery (Bryan, 1995) used in Griffiths’s study. The subtests included were Picture Metaphor, Written Metaphor, Inference, Requests, and Humour. Participants were also administered a series of standardized tests to assess verbal and non-verbal cognitive abilities, including executive functions and social cognition. On average, people with dyslexia showed a worse performance as compared with controls in all APACS tasks and composite scores, with the largest effect sizes found in Figurative Language 2 and Interview tasks. When tested with BLED, people with dyslexia performed significantly worse than controls in the Picture Metaphor task and in Humour, and a negative trend was also observed in the Written Metaphor and Inference tasks. Overall, 36% of the participants with dyslexia had a performance below the cut-off used to determine an impairment in the APACS Total score, while none of the control group did. The task which asked the participants to explain the meaning of figurative expressions (Figurative Language 2) proved the most challenging and the one where 84% of the individuals with dyslexia performed below cut-off. In what follows we offer some examples of the wrong, or only partially correct, answers (scored 0 or 1 on a 0–1–2 scale) provided in the Figurative Language 2 task by the participants enrolled in Cappelli et al. (2018). In some cases, participants provided partial explanations for the figurative expressions, as in example (1), in which the element of cleverness and success at gardening is missing: (1) Che cosa significa che gli italiani hanno il pollice verde? What does it mean that Italians have a green thumb? (a) (Participant nm7qphm, 23 years old) [...] che si dedicano al giardinaggio. [...] that they engage in gardening (b) (Participant n66xt65, 24 years old) [...] che amano il verde e vogliono curarlo [...] that they love greenery and want to take care of it

In other cases, they provided examples rather than explanations or completely misunderstood the text (examples 2–4): (2) Che cosa significa che i giardini di casa sono un’oasi dal lavoro e dalle preoccupazioni quotidiane? What does it mean that private gardens are an oasis from work and everyday worries? (a) (Participant 9jjku9z, 19 years old) [...] che tu ti stacchi dal lavoro e così ti riposi [...] that this way you take a break from work and so you can get rested

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(b) (Participant n66xt65, 24 years old) [...] che i terrazzi sono asettici [...] that balconies are aseptic

(3) Il controllore ha chiuso un occhio The conductor turned a blind eye (a) (Participant xzy8nj4, 21 years old) Non avevo il biglietto, quindi ha chiuso un occhio perché non mi ha fatto la multa per esempio e quindi è stato gentile I didn’t have a ticket, so he turned a blind eye, because he didn’t give me a fine for example, and so he was kind. (4) Certe voci sono trombe Some voices are trumpets (a) (Participant zxy5qm5, 23 years old) Dicono troppa verità They tell too much truth

Problems were observed also in the Interview task. Besides issues with structural language (e.g. gender and number agreement in nounadjective pairs, omissions, incorrect prepositions, lexical mistakes), some participants had trouble in maintaining appropriate informativeness (example 5): (5) Cosa ti piacerebbe fare come lavoro? What job would you like to do? (a) (Participant 2nwnskw, 24 years old) Nel settore, quindi mi piacerebbe imparare, cioè andare a fare tirocinio in un ingegnere a imparare diciamo a modo poi sul campo quello che ho studiato. In the sector, so I would like to learn, I mean, to have an internship in an engineer to learn let’s say the right way then on the field what I have studied

An exploratory analysis showed significant correlations between APACS scores and reading, vocabulary and working memory tests, but not with the tests assessing Theory of Mind abilities (Story-based Empathy Task; Dodich et al., 2015). No significant correlations were found with executive functions either, measured through verbal fluency tasks and the Wisconsin Card Sorting Test. In sum, by using a comprehensive pragmatic assessment tool, Cappelli et al. (2018) showed that in young adults with dyslexia pragmatic difficulties might affect both language comprehension and production, resulting in impaired conversational exchanges. The presence of pragmatic inefficiency was confirmed by the performance in the BLED, where significant differences between participants with dyslexia and controls were found for metaphor and humour comprehension subtests.

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5 Conclusions

Albeit relatively limited, the available literature on pragmatics and dyslexia allows us to derive a series of conclusions. First, studies converge in indicating diffuse pragmatic difficulties in dyslexia. Individuals with this disorder perform less well than controls across a range of pragmatic tasks, both expressive and receptive, with the greatest challenges posed by inferring meanings from figurative expressions and from texts. Issues may also emerge in conversation and narrative skills. This suggests that pragmatic inefficiency should be considered an important aspect of the linguistic and communicative profile of people with dyslexia. A second element emerging from the literature is that pragmatic difficulties affect both children and adults with dyslexia. However, it is not clear how these difficulties evolve along the lifespan since results are inconsistent across the studies available. This might be due to the tests used to assess pragmatic abilities. The studies that have employed materials specifically designed for adults have revealed persistent problems, especially with figurative language (Cappelli et al., 2018; Griffith, 2007), whereas studies employing the same tasks across age groups have evidenced no difficulties in adulthood (Kasirer & Mashal, 2017). Third, the literature shows that difficulties in pragmatics are related to defining features of the dyslexic profile, such as reading and vocabulary abilities, as well as working memory. Pragmatic difficulties in people with dyslexia might therefore be a consequence of the core aspects of this disorder, that is, of difficulties in processing language and information at a more basic level. It seems reasonable to hypothesize that reduced abilities in automatized language processing may cause overload, which manifests as difficulties at the pragmatic level. Problems in reading and accessing words, as well as in maintaining information in the memory buffer, might affect the ability to integrate linguistic and contextual information, to infer non-literal meanings, and to engage in context-appropriate conversation. Vocabulary issues may also contribute to pragmatic inefficiency in dyslexia, similar to what has been found for other neurodevelopmental conditions such as autism spectrum disorder (Kalandadze et al., 2018; Vulchanova et al., 2015). Conversely, correlations with the domains of executive functions and Theory of Mind skills have returned contrasting results, since contrary to Cardillo et al.’s (2018) findings, Cappelli et al. (2018) reported that the link with high-level executive functions and Theory of Mind was negligible in their data. According to the pattern in Cappelli et al. (2018), the pragmatic performance of adults with dyslexia does not seem therefore to be linked to non-verbal reasoning, flexibility or mind-reading skills. A possible explanation for this discrepancy might be that the link between pragmatics and Theory of Mind is stronger in development,

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while in adulthood the two domains are to some extent independent of one another. In this regard, adults with dyslexia differ from other adult clinical populations, such as people with traumatic brain injury, multiple sclerosis and schizophrenia, where the relationship between deficits in pragmatics, in Theory of Mind, and in executive functions has been found to be much stronger (Bambini, Arcara, Bechi et al., 2016; Bosco et al., 2017; Carotenuto et al., 2018; Parola et al., 2018). It is important to acknowledge also the limitations of the available literature on pragmatic abilities and dyslexia. The main limitation is certainly related to the small sample of participants recruited, which reduces the possibility of carrying out finer distinctions among individuals with different types of dyslexia and different comorbidities. For instance, some data (Ferrara et al., 2020) seem to indicate that pragmatic problems are more evident in children with dyslexia without associated language disorder than in children with dyslexia with associated language disorder. Similar distinctions need to be confirmed in further studies enrolling larger numbers of participants. This is indeed the direction that the literature is taking now, as illustrated for instance in a recent registered report seeking to compare conversational aspects in adults with autism and dyslexia (Wilson & Bishop, 2020). Although sample size and methodological rigour in general should most certainly be a concern addressed by future research, the available studies offer a consistent global picture of the pragmatic profile of people with dyslexia and shed light on potential and underestimated problems associated with this specific learning disorder. Applied to clinical settings, these findings (e.g. issues with figurative language) might be of relevance for diagnostic procedures. For example, they might be of special importance in the assessment of well compensated adults with dyslexia, who have overcome the other major difficulties associated with their condition (e.g. impaired reading speed and accuracy) but might retain pragmatic difficulties. Another relevant aspect emerging from the studies discussed concerns the importance of early intervention. Ferrara et al. (2020) have pointed out how the latter may be crucial in reducing differences in pragmatic abilities between children with and without dyslexia. In addition to interventions focused on the core issues in dyslexia, people with the disorder might benefit from training programmes directly targeting pragmatic skills. Indeed, although still in its infancy, the literature on pragmatic training has shown promising results in different populations (Bambini, Tonini et al., 2020; Bosco et al., 2016; Tonini et al., 2022). Helping individuals with dyslexia overcome pragmatic difficulties seems of great importance, given that inference plays a central role in text comprehension and thus in learning (Cain et al., 2001; Simmons & Singleton, 2000). The ability to infer the meaning of figurative language specifically predicts employment (Adamczyk et al.,

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2016), and, more generally, pragmatic competence correlates with social integration (Galski et al., 1998) and quality of life at large (Agostoni et al., 2021; Bambini, Arcara, Bechi et al., 2016). Extending treatment to include interventions focusing on the pragmatic skills of individuals with dyslexia should, thus, be of primary interest to favour the emotional well-being of people with this condition and to promote successful access to all levels of education and inclusion across their lifespan (Cappelli et al., 2018; MacCullagh et al., 2017). References Adamczyk, P., Daren, A., Sułecka, A., Błądziński, P., Cichocki, Ł., Kalisz, A., Gawęda, Ł. and Cechnicki, A. (2016) Do better communication skills promote sheltered employment in schizophrenia? Schizophrenia Research 176 (2), 331–339. Agostoni, G., Bambini, V., Bechi, M., Buonocore, M., Spangaro, M., Repaci, F., Cocchi, F., Bianchi, L., Guglielmino, C., Sapienza, J., Cavallaro, R. and Bosia, M. (2021) Communicative-pragmatic abilities mediate the relationship between cognition and daily functioning in schizophrenia. Neuropsychology 35 (1), 42–56. Altemeier, L.E., Abbott, R.D. and Berninger, V.W. (2008) Executive functions for reading and writing in typical literacy development and dyslexia. Journal of Clinical and Experimental Neuropsychology 30, 588–606. Anderson, V.A., Anderson, P., Northam, E., Jacobs, R. and Catroppa, C. (2001) Development of executive functions through late childhood and adolescence in an Australian sample. Developmental Neuropsychology 20, 385–406. Arcara, G. and Bambini, V. (2016) A test for the assessment of pragmatic abilities and cognitive substrates (APACS): Normative data and psychometric properties. Frontiers in Psychology 7, Article 70. Arcara, G., Tonini, E., Muriago, G., Mondin, E., Sgarabottolo, E., Bertagnoni, G., Semenza, C. and Bambini, V. (2020) Pragmatics and figurative language in individuals with traumatic brain injury: Fine-grained assessment and relevance-theoretic considerations. Aphasiology 34 (8), 1070–110. Ariel, M. (2010) Defining Pragmatics. Cambridge: Cambridge University Press. Arosio, F., Panzeri, F., Molteni, B., Magazù, S. and Guasti, M.T. (2017) The comprehension of Italian relative clauses in poor readers and in children with Specific Language Impairment. Glossa A Journal of General Linguistics 2 (1), 9. Baddeley, A.D. (1998) Working Memory. Oxford: Oxford University Press. Baker, S.F. and Ireland, J.L. (2007) The link between dyslexic traits, executive functioning, impulsivity and social self-esteem among an offender and non-offender sample. International Journal of Law Psychiatry 30, 492–503. doi: 10.1016/j.ijlp.2007.09.010. Bambini, V. (2010) Neuropragmatics: A foreword. Italian Journal of Linguistics 22 (1), 1–20. Bambini, V., Van Looy, L., Demiddele, K. and Schaeken, W. (2021) What is the contribution of executive functions to communicative-pragmatic skills? Insights from aging and different types of pragmatic inference. Cognitive Processing 22, 435–452. Bambini, V., Gentili, C., Ricciardi, E., Bertinetto, P.M. and Pietrini, P. (2011) Decomposing metaphor processing at the cognitive and neural level through functional magnetic resonance imaging. Brain Research Bulletin 86 (3–4), 203–216. Bambini, V., Arcara, G., Bechi, M., Buonocore, M., Cavallaro, R. and Bosia, M. (2016) The communicative impairment as a core feature of schizophrenia: Frequency of pragmatic deficit, cognitive substrates, and relation with quality of life. Comprehensive Psychiatry 71, 106–120.

Dyslexia and Pragmatic Skills  257

Bambini, V., Bischetti, L., Bonomi, C., Arcara, G., Lecce, S. and Ceroni, M. (2020) Beyond the motor account of Amyotrophic Lateral Sclerosis: Verbal humor and its relationship with the cognitive and pragmatic profile. International Journal of Language & Communication Disorders 55 (5), 751–764. Bambini, V., Tonini, E., Ceccato, I., Lecce, S., Marocchini, E. and Cavallini, E. (2020) How to improve social communication in aging: Pragmatic and cognitive interventions. Brain and Language 211, 104864. Bambini, V., Arcara, G., Bosinelli, F., Buonocore, M., Bechi, M., Cavallaro, R. and Bosia, M. (2020) A leopard cannot change its spots: A novel pragmatic account of concretism in schizophrenia. Neuropsychologia 139, 107332. Bambini, V., Arcara, G., Martinelli, I., Bernini, S., Alvisi, E., Moro, A., Cappa, S.F. and Ceroni, M. (2016) Communication and pragmatic breakdowns in amyotrophic lateral sclerosis patients. Brain and Language 153–154, 1–12. Bara, B.G. (2010) Cognitive Pragmatics. Cambridge, MA: MIT Press. Bishop, D.V.M. (1997) Uncommon Understanding: Development and Disorders of Language Comprehension in Children. London: Psychology Press/Erlbaum. Bishop, D.V.M. (1998) Development of the Children’s Communication Checklist (CCC): A method for assessing qualitative aspects of communicative impairment in children. Journal of Child Psychology and Psychiatry 39, 879–891. Bishop, D.V.M. (2003) The Children’s Communication Checklist-2. London: Psychological Corporation. Bishop, D.V.M. and Baird, G. (2001) Parent and teacher report of pragmatic aspects of communication: Use of the children’s communication checklist in a clinical setting. Developmental Medicine and Child Neurology 43 (12), 809–18. Bishop, D.V.M. and Snowling, M.J. (2004) Developmental dyslexia and specific language impairment: Same or different? Psychological Bulletin 130 (6), 858–886. Bishop, D.V.M. and McDonald, D. (2009) Identifying language impairment in children: Combining language test scores with parental report. International Journal of Language and Communication Disorders 44, 600–615. Bishop, D.V.M., Jacobs, P.A., Lachlan, K., Wellesley, D., Barnicoat, A., Boyd, P.A., Fryer, A., Middlemiss, P., Smithson, S., Metcalfe, K., Shears, D., Leggett, V., Nation, K. and Scerif, G. (2011) Autism, language and communication in children with sex chromosome trisomies. Archives of Disease in Childhood 96, 954–959. Bosco, F.M., Bono, A. and Bara, B.G. (2012) Recognition and repair of communicative failures: The interaction between Theory of Mind and cognitive complexity in schizophrenic patients. Journal of Communication Disorders 45 (3), 181–197. Bosco, F.M., Gabbatore, I., Gastaldo, L. and Sacco, K. (2016) Communicative-pragmatic treatment in schizophrenia: A pilot study. Frontiers in Psychology 7, Article 166. Bosco, F.M., Parola, A., Sacco, K., Zettin, M. and Angeleri, R. (2017) Communicativepragmatic disorders in traumatic brain injury: The role of theory of mind and executive functions. Brain and Language 168, 73–83. Bryan, K.L. (1995) The Right Hemisphere Language Battery (2nd edn). Kibworth: Far Communications. Buck, G. (2001) Assessing Listening. Cambridge: Cambridge University Press. Cain, K., Barnes, M.A., Bryant, P.E. and Oakhill, J.V. (2001) Comprehension skill, inference making ability and their relation to knowledge. Memory and Cognition 29 (6), 850–859. Cantiani, C., Lorusso, M.L., Perego, P., Molteni, M. and Guasti, M.T. (2013) Event-related potentials reveal anomalous morphosyntactic processing in developmental dyslexia. Applied Psycholinguistics 34 (6), 1135–1162. Cappelli, G. (2019) Pragmatic and lexical skills of learners with dyslexia and EFL learning. In M.M. Coppola, F. Di Blasio and S. Francesconi (eds) Contact Zones: Cultural, Linguistic and Literary Connections in English (pp. 55–74). Trento: Trento University Press.

258  Part 2: Theoretical and Experimental Linguistic Research on Dyslexia

Cappelli, G. and Noccetti, S. (2016) Teaching specialized vocabulary to dyslexic adult second-language learners: A proposal for multimodal lexical input enhancement. In V. Bonsignori and B. Crawford Camiciottoli (eds) Multimodality across Communicative Settings, Discourse Domains and Genres (pp. 37–64). Newcastle upon Tyne: Cambridge Scholars Publishing. Cappelli, G., Noccetti, S., Arcara, G. and Bambini, V. (2018) Pragmatic competence and its relationship with the linguistic and cognitive profile of young adults with dyslexia. Dyslexia 24 (3), 294–306. Cardillo, R., Basso Garcia, R., Mammarella, I.C. and Cornoldi, C. (2018) Pragmatics of language and theory of mind in children with dyslexia with associated language difficulties or non-verbal learning disabilities. Applied Neuropsychology: Child 7 (3), 245–256. Cardinaletti, A. and Volpato, F. (2015) On the comprehension and production of passive sentences and relative clauses by Italian university students with dyslexia. In E. Di Domenico, C. Hamann and S. Matteini (eds) Structures, Strategies and Beyond: Studies in Honour of Adriana Belletti (pp. 223–279). Amsterdam: John Benjamins. Carotenuto A., Arcara, G., Orefice, G., Cerillo, I., Giannino, V., Rasulo, M., Iodice, R. and Bambini, V. (2018) Communication in multiple sclerosis: Pragmatic deficit and its relation with cognition and social cognition. Archives of Clinical Neuropsychology 33, 194–205. Chinn, S.J. and Crossmann, M. (1995) Stress factors in the adolescent. In T.R. Miles and V. Varma (eds) Dyslexia and Stress (pp. 49–54). London: Whurr Publishers. Cummings, L. (ed.) (2017) Research in Clinical Pragmatics. Dordrecht: Springer. Cummings, L. (ed.) (2021) Handbook of Pragmatic Language Disorders. Complex and Underserved Populations. Cham: Springer Curtis, P.R., Kaiser, A.P., Estabrook, R. and Roberts, M.Y. (2019) The longitudinal effects of early language intervention on children’s problem behaviors. Child Development 90 (2), 576–592. Cutting, L.E., Materek, A., Cole, C.A., Levine, T.M. and Mahone, E.M. (2009) Effects of fluency, oral language, and executive function on reading comprehension performance. Annals of Dyslexia 59, 34–54. Di Sano, S., Saggino, A., Barbieri, M.S. and Surial, L. (2013) Children’s Communication Check list - Adattamento italiano (2nd edn). Firenze: Giunti OS. Dodich, A., Cerami, C., Canessa, N., Crespi, C., Iannaccone, S., Marcone, A., Realmuto, S., Lettieri, G., Perani, D. and Cappa, S.F. (2015) A novel task assessing intention and emotion attribution: Italian standardization and normative data of the Story-based Empathy Task. Neurological Sciences 36 (10), 1907–1912. Domaneschi, F. and Bambini, V. (2020) Pragmatic competence. In E. Fridland and C. Pavese (eds) The Routledge Handbook of Philosophy of Skill and Expertise (pp. 419–430). London: Routledge. Facoetti, A., Trussardi, A.N., Ruffino, M., Lorusso, M.L., Cattaneo, C., Galli, R., Molteni, M. and Zorzi, M. (2010) Multisensory spatial attention deficits are predictive of phonological decoding skills in development dyslexia. Journal of Cognitive Neuroscience 22, 1011–1025. Faust, M. and Mashal, N. (2007) The role of the right cerebral hemisphere in processing novel metaphoric expressions taken from poetry: A divided visual field study. Neuropsychologia 45 (4), 860–870. Fawcett, A.J. and Nicolson, R.I. (1998) The Dyslexia Adult Screening Test (DAST). Sidcup: The Psychological Corporation. Ferguson, M.A., Hall, R.L., Riley, A. and Moore, D.R. (2011) Communication, listening, cognitive and speech perception skills in children with auditory processing disorder (APD) or specific language impairment (SLI). Journal of Speech, Language, and Hearing Research 54 (1), 211–227. Ferrara, M., Camia, M., Cecere, V., Villata, V., Vivenzio, N., Scorza, M. and Padovani, R. (2020) Language and pragmatics across neurodevelopmental disorders: An investigation using the Italian version of CCC-2. Journal of Autism and Developmental Disorders 50, 1295–1309.

Dyslexia and Pragmatic Skills  259

Fussman, S. and Mashal, N. (2022) Assessment of pragmatic abilities in adolescents with typical development. Frontiers in Communication 6, 1–14. Galski, T., Tompkins, C. and Johnston, M.V. (1998) Competence in discourse as a measure of social integration and quality of life in persons with traumatic brain injury. Brain Injury 12, 769–782. Gathercole, S.E., Willis, C.S., Emslie, H. and Baddeley, A.D. (1992) Phonological memory and vocabulary development during the early school years: A longitudinal study. Developmental Psychology 28 (5), 887–898. Geurts, H.M. (2007) CCC-2-NL: Children’s Communication Checklist-2. Amsterdam: Harcourt Assessment BV. Glumbić, N. and Brojčin, B. (2012) Factor structure of the Serbian version of the Children’s Communication Checklist-2. Research in Developmental Disabilities 33, 1352–1359. Grice, H.P. (1975) Logic and conversation. In P. Cole and J.L. Morgan (eds) Syntax and Semantics. Volume 3: Speech Acts (pp. 41–58). New York, NY: Academic Press. Griffiths, C.B. (2007) Pragmatic abilities in adults with and without dyslexia: A pilot study. Dyslexia 13, 276–296. Hales, G. (1995) Stress factors in the workplace. In T.R. Miles and V. Varma (eds) Dyslexia and Stress (pp. 73–88). London: Whurr Publishers. Horowitz-Kraus, T. (2014) Pinpointing the deficit in executive functions in adolescents with dyslexia performing the Wisconsin card sorting test: An ERP study. Journal of Learning Disabilities 47, 208–223. Horn, L. (1972) On the semantic properties of logical operators in English. PhD thesis, Los Angeles, CA: University of California. Hu, S., Vender, M., Fiorin, G. and Delfitto, D. (2018) Difficulties in comprehending affirmative and negative sentences: Evidence from Chinese children with reading difficulties. Journal of Learning Disabilities 51, 181–193. Hu, S., Zhou, P., Foppolo, F., Vender, M. and Delfitto, D. (2019) Scalar implicatures in Chinese children with reading difficulties. First Language 35 (5), 479–507. Joanisse, M.F., Manis, F.R., Keating, P. and Seidenberg, M.S. (2000) Language deficits in dyslexic children: Speech perception, phonology, and morphology. Journal of Experimental Child Psychology 77 (1), 30–60. Kalandadze, T., Norbury, C., Nærland, T. and Næss, K.-A.B. (2018) Figurative language comprehension in individuals with autism spectrum disorder: A meta-analytic review. Autism 22 (2), 99–117. Kasirer, A. and Mashal, N. (2017) Comprehension and generation of metaphoric language in children, adolescents and adults with dyslexia. Dyslexia 23, 99–118. Kerbel, D. and Grunwell, P. (1998) A study of idiom comprehension in children with semantic-pragmatic difficulties. Part II: Between-groups results and discussion. International Journal of Language & Communication Disorders 33, 23–44. Korkman, M., Kirk, U. and Kemp, S. (2007) NEPSY–II. San Antonio, TX: Pearson. Kormos, J. and Smith, A.M. (2012) Teaching Languages to Students with Specific Learning Differences. Bristol: Multilingual Matters. Kumari, S., Pyata, R., Afreen, B. and Paithankar, P.S. (2016) Pragmatic skills in children with different types of learning disability: A comparative study. Language in India 16 (9), 225–233. Lallier, M., Thierry, G., Tainturier, M.J., Donnadieu, S., Peyrin, C., Billard, C. and Valdois, S. (2009) Auditory and visual stream segregation in children and adults: An assessment of the amodality assumption of the ‘sluggish attentional shifting’ theory of dyslexia. Brain Research 1302, 132–147. Lam, K.-H. and Ho, C.S.-H. (2014) Pragmatic skills in Chinese dyslexic children: Evidence from a parental checklist. Asia Pacific Journal of Developmental Differences 1, 4–19. Lapadat, J.C. (1991) Pragmatic language skills of children with language and/or learning disabilities: A quantitative synthesis. Journal of Learning Disabilities 24, 147–158.

260  Part 2: Theoretical and Experimental Linguistic Research on Dyslexia

Levinson, S.C. (1983) Pragmatics. Cambridge: Cambridge University Press. Locascio, G., Mahone, E.M., Eason, S.H. and Cutting, L.E. (2010) Executive dysfunction among children with reading comprehension deficits. Journal of Learning Disabilities 43 (5), 441–454. Lorusso, M.L. (2009) APL Medea: Abilità Pragmatiche nel Linguaggio Medea. Florence: Giunti OS. Lovitt, C.T. (1989) Introduction to Learning Disability. Newton, MA: Allyn & Bacon. MacCullagh, L., Bosanquet, A. and Badcock, N.A. (2017) University students with dyslexia: A qualitative exploratory study of learning practices, challenges and strategies. Dyslexia 23, 3–23. Martin, I. and McDonald, S. (2003) Weak coherence, no theory of mind, or executive dysfunction? Solving the puzzle of pragmatic language disorders. Brain and Language 85, 451–466. Mashal, N. and Kasirer, A. (2011) Thinking maps enhance metaphoric competence in children with autism and learning disabilities. Research in Developmental Disabilities 32, 2045–2054. Mashal, N., Faust, M., Hendler, T. and Jung-Beeman, M. (2008) Hemispheric differences in processing the literal interpretation of idioms: Converging evidence from behavioral and fMRI studies. Cortex 44 (7), 848–860. McLoughlin, D., Leather, C. and Stringer, P. (2002) The Adult Dyslexic: Interventions and Outcomes. London: Whurr Publishers. Melby-Lervåg, M., Lervåg, A., Lyster, S.A.H., Klem, M., Hagtvet, B. and Hulme, C. (2012) Nonword-repetition ability does not appear to be a causal influence on children’s vocabulary development. Psychological Science 23 (10), 1092–1098. Miles, T.R., Gilroy, D. and Du Pre, E.A. (2007) Dyslexia at College. London: Routledge. Montemurro, S., Mondini, S., Signorini, M., Marchetto, A., Bambini, V. and Arcara, G. (2019) Pragmatic language disorder in Parkinson’s disease and the potential effect of cognitive reserve. Frontiers in Psychology 10, Article 1220. Nicolson, R.I. and Fawcett, A.J. (2008) Dyslexia, Learning and the Brain. Cambridge, MA: MIT Press. Norbury, C.F., Nash, M., Baird, G. and Bishop, D.V. (2004) Using a parental checklist to identify diagnostic groups in children with communication impairment: A validation of the Children’s Communication Checklist-2. International Journal of Language & Communication Disorders 39, 345–364. Noveck, I.A. (2001) When children are more logical than adults: Experimental investigations of scalar implicature. Cognition 78, 165–188. Paradis, M. (1998) The other side of language: Pragmatic competence. Journal of Neurolinguistics 11 (I–II), 1–10. Parola, A., Berardinelli, L. and Bosco, F.M. (2018) Cognitive abilities and theory of mind in explaining communicative-pragmatic disorders in patients with schizophrenia. Psychiatry Research 260, 144–151. Prutting, C.A. and Kittchner, D.M. (1987) A clinical appraisal of the pragmatic aspects of language. Journal of Speech & Hearing Disorders 52 (2), 105–119.  Ramus, F., Marshall, C.R., Rosen, S. and van der Lely, H.K. (2013) Phonological deficits in specific language impairment and developmental dyslexia: Towards a multidimensional model. Brain 136 (2), 630–645. Ransby, M.J. and Swanson, H.L. (2003) Reading comprehension skills of young adults with childhood diagnoses of dyslexia. Journal of Learning Disabilities 36 (6), 538–555. Riddick, B., Farmer, M. and Sterling, C. (1997) Students and Dyslexia: Growing Up with a Specific Learning Difficulty. London: Whurr Publishers. Rinaldi, M.C., Marangolo, P. and Lauriola, M. (2006) BLED – Batteria sul Linguaggio dell’emisfero Destro SantaLucia. Firenze: Giunti. Ruffino, M., Gori, S., Boccardi, D., Molteni, M. and Facoetti, A. (2014) Spatial and temporal attention in developmental dyslexia. Frontiers in Human Neuroscience 8, 331.

Dyslexia and Pragmatic Skills  261

Schaeken, W., Van Haeren, M. and Bambini, V. (2018) The understanding of scalar implicatures in children with autism spectrum disorder: Dichotomized responses to violations of informativeness. Frontiers in Psychology 9, Article 1266. Schneider, K.P. and Ifantidou, E. (eds) (2020) Developmental and Clinical Pragmatics. Berlin: Walter de Gruyter. Seidenberg, P.L. and Bernstein, D.K. (1986) The comprehension of similes and metaphors by learning disabled and nonlearning-disabled children. Language, Speech, and Hearing Services in Schools 17, 219–229. Sesma, H.W., Mahone, E.M., Levine, T., Eason, S.H. and Cutting, L.E. (2009) The contribution of executive skills to reading comprehension. Child Neuropsychology 15, 232–246. Simmons, F. and Singleton, C. (2000) The reading comprehension abilities of dyslexic students in higher education. Dyslexia 6 (3), 178–192. Smith-Spark, J.H., Henry, L.A., Messer, D.J., Edvardsdottir, E. and Zięcik, A.P. (2016) Executive functions in adults with developmental dyslexia. Research in Developmental Disabilities 53, 323–341. Snowling, M.J. (2000) Dyslexia (2nd edn). Oxford: Blackwell Publishers. Spencer, M., Richmond, M.C. and Cutting, L.E. (2020) Considering the role of executive function in reading comprehension: A structural equation modeling approach. Scientific Studies of Reading 24 (3), 179–199. Sperber, D. and Wilson, D. (1995) Relevance: Communication and Cognition (2nd edn). Oxford: Blackwell. Sperber, D. and Wilson, D. (2002) Pragmatics, modularity and mind-reading. Mind and Language 17, 3–23. Spotorno, N., Koun, E., Prado, J., Van Der Henst, J.B. and Noveck, I.A. (2012) Neural evidence that utterance-processing entails mentalizing: The case of irony. Neuroimage 63 (1), 25–39. Stemmer, B. (2000) Neuropragmatics in the 21st century. Brain and Language 71 (1), 233–236. Thoma, P. and Daum, I. (2006) Neurocognitive mechanisms of figurative language processing. Evidence from clinical dysfunctions. Neuroscience and Biobehavioural Review 30 (8), 1182–1205. Tonini, E., Lecce, S., Del Sette, P., Bianco, F., Canal, P. and Bambini, V. (2022) Efficacy and benefits of the MetaCom training to promote metaphor comprehension in typical development. First Language 42 (3), 466–496. Troia, G.A. (2021) Children and young people with written language disorders. In L. Cummings (ed.) Handbook of Pragmatic Language Disorders. Complex and Underserved Populations (pp. 651–671). Cham: Springer. Tsou, B., Lee, T.H.T., Tung, P., Man, Y., Chan, A., To, C.K.S., Ng, K.H., Cheung, S.P. and Chan, Y. (2006) Hong Kong Cantonese Oral Language Assessment Scale. Hong Kong: City University of Hong Kong. Urgesi, C., Campanella, F. and Fabbro, F. (2011) NEPSY-II. Contributo alla Taratura Italiana. Firenze: Giunti OS. Vender, M. (2017) Disentangling Dyslexia: Phonological and Processing Impairment in Developmental Dyslexia. Frankfurt: Peter Lang. Vulchanova, M., Saldaña, D., Chahboun, S. and Vulchanov, V. (2015) Figurative language processing in atypical populations: The ASD perspective. Frontiers in Human Neuroscience 9, 24. Wallach, G. and Liebergott, J. (1984) Who shall be called ‘learning disabled’: Some new directions. In G. Wallach and K. Butler (eds) Language Learning Disabilities in Schoolage Children (pp. 1–14). Baltimore, MD: Williams & Wilkin. Wampers, M., Schrauwen, S., De Hert, M., Gielen, L. and Schaeken, W. (2017) Patients with psychosis struggle with scalar implicatures. Schizophrenia Research 195, 97–102.

262  Part 2: Theoretical and Experimental Linguistic Research on Dyslexia

Whitehouse, A.J.O., Barry, J.G. and Bishop, D.V.M. (2008) Further defining the language impairment of autism: Is there a specific language impairment subtype? Journal of Communication Disorders 41, 319–336. Whitney, H.W., Mahone, E.M., Levine, T., Eason, S.H. and Cutting, L.E. (2009) The contribution of executive skills to reading comprehension. Child Neuropsychology 15, 232–246. Wilson, A.C. and Bishop, D.V.M. (2020) Registered report: Investigating a preference for certainty in conversation among autistic adults compared to dyslexic adults and the general population. PeerJ, 8: e10398. Xiao, X.Y. and Ho, C.S. (2014) Weaknesses in semantic, syntactic and oral language expression contribute to reading difficulties in Chinese dyslexic children. Dyslexia 20 (1), 74–98.

Part 3: Applied Linguistic Research and Dyslexia

11 Visual and Auditory Stimuli for Teaching EFL Vocabulary to Learners with Dyslexia Sabrina Noccetti

1 Introduction

This chapter presents the results of an experiment in which a group of adults with dyslexia (DD) and a control group of adults without dyslexia (ND), matched for age and years of education, are taught English-like non-words under two different experimental conditions. Under the first condition, the new words are presented with pictures illustrating their meaning (I-Words); under the second, the words are presented only in their written form and Italian translation (T-Words). The aim of the experiment is to discover if visual stimuli can facilitate recall and increase the rate of retrieval of novel object words. The more general aim of this chapter is to present an alternative method to teaching L2 vocabulary to students with developmental dyslexia. For people with dyslexia, word storage and retrieval are among the problems that affect the way they learn a foreign language (Cappelli, Chapter 9, this volume; Bailey & Snowling, 2002; Wolf & Goodglass, 1986). These difficulties are partly caused by a general deficit of their memory systems, verbal working memory and inefficient phonological processing skills (see Ghidoni, Chapter 1, this volume, for a review), which makes the learning process slow and precarious (see Gasperini, Chapter 3, this volume). L2 vocabulary learning is thus a challenge for students with dyslexia, especially if it is taught traditionally by means of written stimuli only. Vocabulary knowledge has proved essential both in the native and foreign language (FL) (Lewis, 2000; Nation, 2013; Willis & Ohashi, 2012). Intricate networks of words are acquired over time by exposure to significant and rich input data. Although vocabulary learning is a natural activity that humans perform from birth, its naturalness hides what is in 265

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fact a very challenging task. First and foremost, the acquisition of a new word implies the association of the phonological form with meaning, as well as the storage of necessary morphological and syntactic related information. Obviously, morphotactic and morphosemantic opacity and the lack of biunivocity in the relationship of form–meaning may add various degrees of complexity to the acquisition of vocabulary. Adequate vocabulary knowledge is related to the development of the morphosyntactic system of the language. It is necessary for communicating, for comprehending texts and, consequently, for cultural and cognitive enrichment (Hoey, 2005; Römer, 2009; Tomasello, 2003). Since it is a fundamental component of language, the breadth and depth of the lexicon is very likely proportional to the academic success of the individual, so that the wider the lexicon, the better the global learning outcomes will be. Vocabulary size, in terms of the number of known words and families, provides useful information about competence in a FL (Nation, 1993), and represents one of the most obvious differences between native speakers and foreign learners (Laufer, 1998). More generally, vocabulary is viewed as a source of concern by learners, who believe that their failure as FL speakers may depend on their scant vocabulary knowledge (Meara, 1980; Newton, 2019; Singleton, 1999). When vocabulary knowledge is neglected, or not sufficiently developed by educational curricula, FL learners may manifest difficulties in language production and comprehension. Therefore, it is evident that vocabulary needs to be one of the most important objectives of the educational environment in terms of teaching approaches and learners’ outcomes. Typically developing students can learn FL vocabulary with relative ease both incidentally, namely by natural exposure to the target language, and with focused approaches. Conversely, people with developmental dyslexia present well-documented deficits in FL vocabulary acquisition and word retrieval, especially when no specific learning strategies have been taught (cf. Cappelli, Chapter 9, this volume; Chung et al., 2010; Crombie, 1997; Ganschow & Sparks, 1987; Ho & Fong, 2005; Sparks et al., 1991). Such inefficiency manifests itself through semantic paraphasias, time delays for word retrieval, and with a more general and pervasive difficulty in speaking a foreign language. These compromised abilities are thought to depend on a phonological processing impairment (cf. Baddeley et al., 1988; Chung et al., 2010; Gathercole et al., 1992; Majerus et al., 2004; Service, 1992), on articulatory rehearsal process impairment (Ellis & Sinclair, 1996; Papagno et al., 1991), and on the inefficiency of memory systems (Gupta 2015; Kormos & Smith, 2012; Speciale et al. 2004). However, benefits for memorization, motivation and learning have been observed in students with cognitive disabilities (Narang & Gupta, 2014), and in the general population (Dale, 1969) after

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attending multimodal teaching programmes. Multimodality stimulates a multisensory mode of learning (cf. Aiello et al., 2013), which helps bypass pure phonological processing and offers multiple channels for memorization thereby improving the learner’s outcomes (Barcroft, 2015). In recent years, the embodied approaches to meaning understanding have highlighted that word meaning is constructed by means of sensorimotor features involving the systems used in perception and action (see Buccino & Mezzadri, 2015; Fischer & Zwaan, 2008; Stanfield & Zwaan, 2001). As a consequence, word meaning is constructed as a personal experience through an active interaction with the environment. The experience is thus fundamental for sensorimotor and linguistic development, which is believed to be subserved by the same neural substrates (see Buccino & Mezzadri, 2015). In childhood, multisensory environments guide perceptual learning, driving the child’s attention towards relevant events (Bahrick & Lickliter, 2012). Thus, the human brain becomes accustomed to operating in a multisensory manner and to learning how to integrate different kinds of information from multiple sensory sources (Bahrick & Lickliter, 2012; Heikkilä et al., 2018). Interesting results come from studies on the effect of multisensory semantic congruency of the stimuli. It has been demonstrated that when auditory and visual stimuli are congruent and presented simultaneously, the memory performance is facilitated. This is indicated by a more accurate and efficient recognition of one of the two congruent stimuli as opposed to the incongruent ones (Chen & Spence, 2010; Heikkilä et al., 2018; Laurienti et al., 2004). In general, there is convergent evidence that congruent multisensorial experience strengthens the encoding of both verbal and non-verbal material, as it leads to a more elaborate memory trace (Heikkilä et al., 2018; Murray et al., 2004). In particular, images are thought to be more effectively stored in the memory and more easily retrieved (Paivio et al., 1968). Visual stimuli have proved to be a key element in language disambiguation (cf. Knoeferle & Guerra, 2016) and are more easily retained than written words (cf. Fawcett et al., 2012; Standing et al., 1970). Therefore, their implementation in the case of dyslexia seems a promising way to mitigate learning difficulties. Images can bolster learning in the presence of both phonological deficit and difficulty in the perception of variations of auditory patterns, i.e. when the perception of isolated language is disrupted (Cassandro et al., 2019; Tallal, 1980). Previous research has shown that images boost the retention of novel words and favour their recall (Cappelli & Noccetti, 2016; Noccetti, 2018a, 2018b; Noccetti & Cappelli, 2018). The results of these studies are in line with what is known as the Picture Superiority Effect (Paivio et al., 1968), which proposes that pictures, together with the articulation of the word (the Production Effect), boost memory retention. Research has also highlighted that when words are associated with rich visual

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imagery, they are learned more easily than abstract terms because of the Concreteness Effect (Altarriba & Bauer, 2004; DeGroot, 1992; Farley et al., 2012). However, whenever abstract words are taught together with their representing pictures, the performance of the learners in receptive knowledge becomes more efficient. It is suggested that metaphorical, emotive and symbolic imagery play a facilitating role in recalling abstract words (Farley et al., 2012). In addition, the association between images and words is perceived as a helpful strategy in remembering the L1 word’s meaning. Pictures capture the attention of the students (Alhamami, 2014) and, in the case of learners with dyslexia, they might help bypass all the difficulties posed by their impaired phonological processing skills. The Orton–Gillingham learning approach, which was planned to include a combination of multisensory instructions, was the first method designed to teach literacy to children with dyslexia. Later, the method inspired other successful multimodal activities for teaching foreign languages to students with dyslexia (Kormos & Smith, 2012; Nijakowska, Chapter 14, this volume; Nijakowska et al., 2013; Schneider & Crombie, 2003; Sparks et al., 1991). However, to the best of my knowledge, the impact of the different sensory teaching modes on the acquisition rate of FL novel words in dyslexia has not been investigated. This kind of knowledge could help determine a preference for one mode over the other in the case of special learning needs, when more traditional methods have proved to be ineffective. 2 Vocabulary Learning: Effect of Frequency

Learning new vocabulary implies that the word sounds are first perceived and then produced. The correct discrimination of sounds creates a word template, either directly from the auditory input or indirectly from the mediation of the subvocal rehearsal of the written input. The stored template is functional to word retrieval and impacts on language proficiency. People with dyslexia may present a wide range of dysfunctions that affect language learning proficiency at various levels (Ramus, 2004). One of the most widely recognized disorders is their inefficiency in processing auditory stimuli (Galaburda et al., 1985; Stein & Walsh, 1997; Tallal et al., 1995) and in elaborating on sequences of sounds produced at a short interval from one another (Tallal et al., 1995). Such impairments may lead to an inadequate phonological representation of the stored word-sound templates. In turn, an incorrect representation can negatively affect word storage, word retrieval and, more generally, language fluency. Thus, acquiring a FL can be a demanding task for learners with dyslexia, especially when the FL phonotactics are very different from their native language. The phonological impairment

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of the dyslexic population is believed to depend both on the lack of automatization (see Nicolson et al., 2001) and on the inefficiency of the memory systems (see Ghidoni, Chapter 1, this volume). Vellutino et al. (2004) described dyslexia as a language-based disorder leading to an abnormal development of vocabulary and syntax, contributing to the line of thought that maintains that multiple disorders are more frequent than pure deficits (see also Casalini et al., Chapter 2, this volume; Marotta, Chapter 7, this volume). The naming speed deficit (Kormos & Smith, 2012; Jeffries & Everatt, 2004; Wolf & Bowers, 1999), which is often reported among subjects with dyslexia, is a factor connected to vocabulary acquisition, as it is influenced by ease of verbal access and retrieval. Newly acquired words are vulnerable and their retrieval is hindered by the numerous competitors that have had more practice by the learners and that have stronger neural traces. Indeed, the strength of a word trace, and consequently its accessibility, depends on the frequency with which it is practised. As a consequence, low-frequency words are less accessible than high-frequency words. Hence, frequency is one of those factors that has to be accounted for when teaching a foreign language. In associative network theories of learning, drawing on the Hebbian associative learning model, frequency strengthens the neural networks of associated items and favours their recall. Accordingly, when words are taught together with their representing images, they form an associative bundle, which gains strength by frequent stimulation, i.e. by frequent practice. Within the bundle, one item of the pair is recalled by means of the other which serves as a cue for recall (Hebb, 1949; Schmitt, 1997). Namely, when the image and the phonological form of the novel word are learnt together and associated by means of frequent repetition, the activation of one of the two elements of the bundle also activates the other one. For this reason, in such associative recognition conditions, the trace of the word form need not be searched among the other possible traces of the other word forms. Consequently, the entire process is more direct and accurate, with reduced possibilities of error than in free recall (Carpenter et al., 2006). It is also faster as it obviates the need for cleaning the memory traces created by wrong responses (Nobel & Shiffrin, 2001). Therefore, intensive and repetitive training can be particularly effective in the case of DD, where visuo-verbal integration needs to be practised, accelerated and automatized (Dahlin, 2011; Holmes et al., 2010). 3 Rapid Automatized Naming and RUN the RAN

Rapid Automatized Naming (RAN) is a task used to measure the speed of naming aloud pictures, objects, letters and digits. Divergence

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from the norm of naming speed is used to predict future reading skills, phonological awareness and verbal intelligence. The ability to name serial stimuli is a primary activity that is strictly connected to speaking, learning, and reading letters and words (Dehaene & Cohen, 2011). Naming is an automatized cognitive behaviour that demands the engagement of various cognitive and neurological processes, such as effective attention, working memory, word retrieval capacity and rapid articulation of sounds (Norton & Wolf, 2012; Pecini et al., 2019). RAN was initially used as a diagnostic instrument to identify and measure deficits in naming speed and automatization, which are generally impaired in people with dyslexia (see Pecini et al., 2018, 2019). It was then developed into a tele-rehabilitation programme. As a computer application, Run the RAN, was designed to train children with dyslexia (Pecini et al., 2018, 2019). The principal aim of the application was to increase the children’s ability to name rapidly, to facilitate recall and to induce the correct left-to-right eye movement of reading. In this experiment, Run the RAN was adapted to teach and practise English words, with the intent of fostering and automatizing verbal access and retrieval. The program maintained the basic structure of the original version (see below) but aimed to overcome some of the typical problems intrinsic to the foreign language teaching environment. First and foremost, Run the RAN increases the number of encounters with each novel word with up to 15 repetitions per item. The control of frequency is of fundamental importance in strengthening the mnestic trace of newly encountered words (Dahlin, 2011; Holmes et al., 2010), especially in foreign language learning contexts where there is limited time of exposure. In addition, the novel words are uttered in a loud voice. The loud articulation of the sounds substitutes and trains covert rehearsal processes, which are proved essential for the retention of language material but disrupted in dyslexics (see, for example, Beneventi, et al., 2009; Ellis & Sinclair, 1996; Khelifa-Gallois et al., 2015; Papagno et al., 1991; Spring & Capps, 1974). The combination of images and articulation are, in fact, potentially suitable for strengthening the memory trace (Murray et al., 2004, 2007; Paivio et al., 1968). Last but not least, repeating under pressure of time, but with a limited duration of the activity, helps the learners focus and sustain attention on the task. Thus, Run the RAN has features that can potentiate word retention and strengthen the association between two modes of presenting new stimuli – image/sound and written form/sound. If successful recalling is determined by the number of encounters with novel words, then each experimental item should be equally recalled for the effect of frequency, without any difference between the I-Words and the T-Words. However, for the image superiority effect, the I-Words should be better recalled than the T-words. First and foremost, the storage of T-Words demands double phonological and orthographic processing, i.e. in L1 and L2.

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Second, access to the lexical and semantic representation of the T-word is not direct but is mediated by the native language of the learner, even when the novel foreign words are not translated by a single word in L1 and need to be paraphrased, as in this experiment (see following section). Finally, the link between L1 and L2 needs to be created after the inhibition of the various phonological and semantic competitors. T-Words, then, are expected to be recalled less than I-Words. However, the rate of recall is expected to be high for the frequency effect. 4 Data 4.1 Participants

All the participants, both with and without dyslexia, were native speakers of Italian and attended different degree programmes at the University of Pisa. Bilingual students and students with psychiatric or neurological personal history, or those taking medications regularly, were excluded from the initial sample of 34 volunteer subjects. After a second selection, the participants who had not completed all the tasks in the allotted time were also excluded. This left 26 people, who were distributed into two groups composed of 13 young adults diagnosed with dyslexia (DD group) (Mage 21 years and 6 months, age range 19–34) and 13 controls of typically developing students without dyslexia (ND group) (Mage 19 years and 3 months, age range 18–21). One participant of the DD group was 34 years old, but she was not excluded because her competence in English equalled the rest of the students’ and because there are no significant differences between age 21 and age 34 from the point of view of psychological development (Brauer et al., 2013). The mean education period of the participants was 17.9 for the DD group and 16.3 for the ND group. All the students with dyslexia had a valid and recent diagnosis of DD, which enabled them to obtain tutorial assistance and gave them the right to take advantage of the compensatory measures provided for by law. The group of DD students was composed of 7 female and 6 male students, and the ND group was composed of 10 female and 3 male students. The latter group was selected among volunteers who matched the DD group for age and education. None of the participants had visual or hearing impairments. The study was approved by the local Ethics Committee. Informed consent was obtained from all participants. 4.2 Experimental design

The aim of the experiment was to compare both the efficacy of two different modalities for teaching English vocabulary, and the way they affect the recall rate after two weeks of training. With the first teaching

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modality, the target words were introduced by means of pictures, audio and written form. With the second modality, the target words were presented to the students by means of their Italian translation in audio and written form. Thus, there was a comparison between the use of images vs. the use of translation, the latter being one of the most common practices for teaching L2 vocabulary at school. Both groups of participants in the experiment, the DD group and the ND group, were administered two tests. The first was a battery of tests designed to measure memory and learning ability, TEMA (Ianes, 2011). The second was an assessment test, which was first administered immediately after the presentation of the words and then after a further two weeks. The following sections provide a more detailed description of the tests and the material used for this experiment. 4.3 Vocabulary: Target words

Forty monosyllabic non-words were selected from an online data­base (https://www.cogsci.mq.edu.au/cgi-bin/nwsrch.cgi) to avoid any bias on test results due to previous encounters with actual English words. The non-words selected were phonotactically plausible English mono­ morphemic words and were associated with a concrete meaning to avoid significant differences with their imageability level. The first group of 20 non-words, I-Words, was associated with pictures representing invented animals and objects (see Figure 11.1). The second group of 20 non-words, T-words, was provided with the Italian translation. Since they were non-existing words, each one was associated with referents that are not usually given a name in Italian. By means of example, the Italian translation was not a single word but resulted either in a (short) noun phrase (e.g. sfera di elastici ‘sphere of elastic bands’) or a compound-like plausible word (e.g. trovachiavi ‘key finder’)

Figure 11.1  Familiarization phase: I-Words

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Figure 11.2  Familiarization phase: T-Words

(see Figure 11.2). Each set was presented to the students in groups of five words at a time (see Figures 11.1 and 11.2), using slides that had been designed to follow the layout of the original Run the RAN training tool (Pecini et al., 2018). In this experiment, the adapted version of Run the RAN was used both to teach and to help recall the target non-words. It consisted of two phases: (a) learning or familiarization phase, and (b) training phase. During the familiarization phase (a), the students were asked to learn the non-words and to familiarize themselves with the pictures or the translations associated with them. They were asked to listen to the audio and to repeat the words until they felt confident about them. Then, as soon as the participants started the training phase (b), the files used for the familiarization phase (a) were blocked. Two videos had been prepared for the training phase (b) – one for the 20 I-Words and one for the 20 T-Words. In the videos, the pictures and the translations popped up on the screen in random order and at an ever increasing rate, until one item per second was shown. In order to control possible differences due to the frequency of encounters with each word during phase (b), the occurrence of each non-word was fixed at 15. During the training phase, the participants were asked to name the words as soon as they saw the corresponding picture on the screen and, for the T-Words group, the translation from English to Italian and vice-versa. Since the translations demanded more time to be read and named, pictures and translations were kept separate in two different training videos. Although the cognitive resources used to translate from one language to another are different to those employed in simple naming, nevertheless both tasks involve the learning ability of the students. Moreover, the difference between these modalities does not impact on the main objective of the experiment: that of observing which activity is more effective for learning vocabulary, both for ND and DD students.

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The task assigned to the learners also involved the acquisition of a new referent or concept. On the one hand, they were presented with the representation of non-existing referents (e.g. animals), on the other hand, they were asked to focus on new items and therefore on new concepts, even though the items were parts of familiar objects. Therefore, the task was complex as it also presumably demanded the creation of a new semantic representation. 4.4 Tests

Two main tests were taken by the students at two different times – the first test was performed immediately after the training, and the second was administered two weeks later, to check the recall rate of the learnt words. The tests measured the rate of learning and the differences between the I-Words and T-Words in the DD and ND groups. In the first test, T1, a picture had to be matched to a written I-Word chosen from a set of five and, vice-versa, a written I-Word had to be matched to a picture also chosen from a set of five. Likewise, in the second test, T2, a non-word had to be matched to one of five different translations and, vice versa, a translation to one of five non-words. Each correct answer was awarded 1 point, so that the maximum score was set at 20 for each word group. The words were assigned randomly to the two different test modes. Even though it would have been interesting to detect the preferences of the learners using one or the other testing modality, this would have meant that the time for the test would double, with negative effects on the students’ attention. A Test of Memory and Learning (TOMAL) was also administered to the ND and DD groups, in order to better understand if the results obtained in the assessment test could be related to memory capacity and to the index of attention and learning skills of the subjects. The version of TOMAL used in the experiment was TEMA, the adapted Italian version by Ianes (2011). TEMA is a standardized battery of tests that measures the strengths and weaknesses of different aspects of memory for subjects between 5;0 and 19;11. Therefore, in this experiment, it befitted the adult participants. TEMA is composed of 14 subtests. The score of each subtest is converted into a standardized score and a percentile established for different age groups. The sum of the standardized scores of some of the subtests is then related to several indexes that measure verbal memory, non-verbal memory, attention and learning (see Table 11.1). All indexes have a mean of 100 and a standard deviation of 15. Table 11.1 displays the list of subtests that are combined to calculate the indexes. By way of example, if the raw scores of each of the subtests used to measure the verbal memory index as shown in Table 11.1 are MFS 35,

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Table 11.1  TOMAL (TEMA) subtests for the indexes Verbal memory

Attention

Memory for Stories

(MFS)

Digits Forward

(DF)

Word Selective Reminding

(WSR)

Digits Backward

(DB)

Object Recall

(OR)

Letters Forward

(LF)

Digits Forward

(DF)

Letters Backward

(LB)

Paired Recall

(PR)

Manual Imitation

(MI)

Non-verbal memory

 

Learning

 

Facial Memory

(FM)

Word Selective Reminding

(WSR)

Visual Selective Reminding

(VSR)

Visual Selective Reminding

(VSR)

Abstract Visual Memory

(AVM)

Object Recall

(OR)

Visual Sequential Memory

(VSM)

Paired Recall

(PR)

Memory for Location

(MFL)

 

 

WSR 54, OR 56, DF 30, PR 30, the respective standard scores, stan­ dardized for the age group of adult subjects, are MFS 8, WSR 5, OR 10, DF 5, PR 13. Their sum, 41, corresponds to a verbal memory index of 88 and a percentile of 21. This index is correlated to the results that the participants obtained from the same set of tests. The results are discussed in the next section. 5 Results

The main objective of this experiment was to ascertain if there is a teaching method by which students with dyslexia can learn vocabulary more effectively. Two sets of English-like non-words were presented in two ways: either by means of their visual representation or by their Italian translation. In order to understand which one of the two teaching methods favours lexical acquisition, the following questions were addressed: (a) Is vocabulary learning favoured by visual input with respect to the written modality (i.e. translation), as it emerges from the differences in the recall rate of I-Words and T-Words after two weeks from the training session? (b) Are there significant differences between the DD and ND groups in the tests administered following the training and after two weeks? In order to answer these questions, the results obtained from the two tests immediately following the training and after two weeks were compared. Table 11.2 shows the mean and the standard deviation of the results of the two tests.

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Table 11.2  Mean and standard deviation of the assessment tests in ND and DD groups ND Mean Sd DD Mean Sd

Test 1-I

Test 1-T

Test 2-I

Test 2-T

19.6

18.4

18.5

14.3

2.6

1.7

4.5

Test 1-I

0.6

Test 1-T

Test 2-I

Test 2-T

17.0

13.2

14.2

7.3

4.5

6.1

3.9

4.9

Test 1-I (T1-I) and Test 1-T (T1-T) are the tests submitted after the training phase and relative to the words taught by means of images (I) and by means of their Italian translation (T). Test 2-I (T2-I) and Test 2-T (T2-T) are the tests submitted after two weeks and were aimed at comparing the recall rate of the words learned in the two modalities. The first analysis conducted to compare the scores of the two tests shows that both groups performed better with the words learned by means of images than by means of translation (cf. Table 11.2). Results showed that there was no significant difference in the scores for T1-I (MD 19.6, SD 0.6) and T1-T (MD 18.4, SD 2.6) conditions for ND group. Analogously, the results for the DD group showed no significant difference in the scores for T1-I (MD 17.0, SD 4.5) and T1-T (MD 13.2, SD 6.1). These results suggest that the two modalities of training for vocabulary learning do not lead to significant differences when testing immediately follows exposure to the newly learned words. Nonetheless, in a small sample of participants such as was used in this experiment, the data suggest a preference for T1-I modality of training. However, when the analysis was conducted to compare memory for words in T2-I and T2-T conditions, i.e. two weeks from the training, the results showed significant differences in the scores for the two tests. Namely, T2-I (MD 18.5, SD 1.7) and T2-T (MD 14.3, SD 4.5) for the ND group, and T2-I (MD 14.2, SD 3.9) and T2-T (MD 7.3, SD 4.9) for the DD group. These results point to the positive effect of images on word learning. Specifically, when DD (and also ND) students are exposed to images, their capacity to remember new words seems to increase with respect to the translation mode. The recall ability of English non-words (namely, the number of correctly recalled non-words in the single testing sessions) was submitted to a 3-way ANOVA, with Group (dyslexics versus controls) as the unrepeated factor and Teaching strategy (with vs. without images) and Time of recall (short-term vs. long-term) as repeated factors. A significant main effect was observed for all three variables, indicating a superior recall performance for controls (17.8 words) compared with dyslexics (13.0 words) (F (1,24) = 13.7, p = .001), for teaching with images

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(17.4 words) rather than without images (13.3 words) (F (1,24) = 35.8, p