Thesis
Reference
Neuroimagery of language control mechanism and semantic processing in the bilingual brain with a special emphasis on the
effects of second language proficiency
MOUTHON, Michael Sébastien
Abstract
Clinical and experimental findings on the bilingualism support two fundamental assumptions:
1) languages mastered by a bilingual use the same neural substrates, and therefore a common brain network; 2) a control mechanism is needed to avoid mixing between the languages. In addition, it seems that these neural substrates are modulated by the proficiency of the languages. This thesis proposes to clarify some aspects related to the influence of the used language (first or second), as well as to the second language proficiency, on the brain mechanisms involved in producing and understanding language. To this end, this work examines two aspects on a population of translators with the help of functional magnetic resonance imaging (fMRI): a) the dissociation between neural substrates involved in language selection and in cognitive control; b) neural substrates involved in written word comprehension, with special emphasis on semantic processing and on early word recognition during visual processing.
MOUTHON, Michael Sébastien. Neuroimagery of language control mechanism and semantic processing in the bilingual brain with a special emphasis on the effects of second language proficiency. Thèse de doctorat : Univ. Genève et Lausanne, 2011, no.
Neur. 77
URN : urn:nbn:ch:unige-182336
DOI : 10.13097/archive-ouverte/unige:18233
Available at:
http://archive-ouverte.unige.ch/unige:18233
Disclaimer: layout of this document may differ from the published version.
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DOCTORAT EN NEUROSCIENCES des Universités de Genève
et de Lausanne
UNIVERSITÉ DE GENÈVE FACULTÉ DES SCIENCES Professeur Jean-Marie ANNONI, directeur de thèse
Professeur Asaid KHATEB, co-directeur de thèse
TITRE DE LA THÈSE
NEUROIMAGERY OF LANGUAGE CONTROL MECHANISMS AND SEMANTIC PROCESSING IN THE BILINGUAL BRAIN WITH A SPECIAL EMPHASIS ON THE EFFECTS OF SECOND LANGUAGE
PROFICIENCY THÈSE Présentée à la Faculté des Sciences de l’Université de Genève
pour obtenir le grade de Docteur en Neurosciences
par
Michaël Sébastien MOUTHON de Lancy (Genève)
Thèse N° 77 Genève
Editeur ou imprimeur : Université de Genève 2011
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Je voudrais remercier toutes les personnes qui ont contribué à cette thèse :
Tout d’abord, le professeur Jean-Marie ANNONI, directeur de thèse, pour ses encouragements, sa supervision et le temps qu’il a toujours trouvé pour travailler avec moi.
Un remerciement particulier au professeur Asaid KHATEB, co-directeur de thèse, qui a consacré beaucoup de temps sur ce projet malgré sa récente nomination à l’Université de Haïfa en Israël. Il a grandement participé à l’amélioration du manuscrit de thèse. Il a partagé avec moi sa précieuse expérience en neuroimagerie et a notamment tenu le rôle de responsable scientifique dans ce projet.
Mes remerciements également :
Au Prof. Ulrich FRAUENFELDER, au Dr. François LAZEYRAS ainsi qu’au MD. Jubin ABUTALEBI, jurés de ma thèse, pour leur évaluation ainsi que leur précieux commentaire sur ce travail qui m’a permis de l’améliorer.
Au professeur Alan PEGNA qui m’a hébergé au sein de son laboratoire (Laboratory of experimental neuropsychology [LENPsy]), qui m’a prodigué ses précieux conseils lors des analyses EEG et qui a relu une partie de mon travail.
À l’équipe genevoise du Centre d’Imagerie Biomédicale (CIBM), spécialement au Dr.
François LAZEYRAS (directeur du corps de recherche d’Imagerie par Résonance Magnétique (IRM) à l’Hôpital Cantonal de Genève) ainsi qu’au Dr. Stéphane SIMON pour son enseignement et sa supervision lors des enregistrements et de l’utilisation des techniques d’Imagerie par Résonnance Magnétique (IRM).
Aux membres de la faculté de Traduction et Interprétation de l’Université de Genève (ETI), notamment au Prof. Hannelore LEE-JAHNKE (directrice de la division allemande) qui nous a facilité le recrutement de ses étudiants. Merci aussi à Mme Caroline LEHR qui a recruté les sujets et qui s’est occupée de l’évaluation de leur niveau de maîtrise de la seconde langue.
À Mme Tatiana ABOULAFIA qui a travaillé avec moi au début de ce projet (notamment au niveau du design de l’expérience de sélection de langage). Je lui souhaite bonne chance dans sa future carrière clinique.
À Mme Ann TRAVIS pour sa relecture de la langue anglaise de ce manuscrit.
À tous les membres de ma famille, pour m’avoir soutenu dans la réalisation de ce projet.
Au Fond National Suisse pour la Recherche (FNS) (Subvention no. 325100-118362) et au Centre Inter-facultaire de Neurosciences de Genève pour leur support financier à ce projet, ainsi qu’à l’école Doctorale Lémanique de Neurosciences (LN) pour leur apport de connaissances.
IV
L’homme possède la fascinante capacité à pouvoir communiquer dans plusieurs langues différentes. Les constatations cliniques et expérimentales nous permettent d’énoncer deux postulats de départ : 1) les langues maîtrisées par un bilingue utilisent les mêmes substrats neuronaux et donc des réseaux cérébraux communs ; 2) cette proximité structurelle nécessite des mécanismes de contrôles qui permettent de ne pas mélanger les langues. Il semble cependant que ces substrats neuronaux dépendent de la maîtrise des langues. Ce travail de thèse propose de préciser certains aspects associés à l’influence de l’utilisation de la première ou de la seconde langue sur les mécanismes cérébraux impliqués dans la production et la compréhension langagière, ainsi que l’influence de la maîtrise de la seconde langue sur ceux-ci. Dans ce but, ce travail étudie plus spécifiquement deux de ces aspects : a) la dissociation des substrats neuronaux impliqués dans les mécanismes de contrôle de la première ou seconde langue avec ceux impliqués dans le contrôle cognitif ; b) les substrats neuronaux impliqués dans la compréhension des langages écrits, notamment lors du traitement sémantique ainsi que lors la reconnaissance visuel précoce des mots.
Nous nous sommes intéressés aux régions cérébrales impliquées dans ces traitements, en étudiant la modification de leurs activations fonctionnelles en fonction de la langue utilisée (première ou seconde) ainsi que de la maitrise de la seconde langue. Pour ce faire, l’activité cérébrale de bilingues performants, issus de deux niveaux différents de formation à l’école de traduction de l’Université de Genève, a été étudié au moyen de la technique d’imagerie par résonnance magnétique fonctionnelle (IRMf).
Concernant le réseau cérébral impliqué dans le contrôle des langues, les études antérieures ont permis de mettre en évidence l’implication de certaines structures cérébrales comme les noyaux caudés, le cortex cingulaire antérieur, le cortex préfrontal et le gyrus supramarginal. Notre étude IRMf propose de mieux caractériser l’implication de ces structures dans le réseau de contrôle des langues et d’étudier l’influence qu’un changement de
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sélection de tâches et une sélection de langues sont comparées. Nos analyses ont confirmé l’implication de ces régions cérébrales mentionnées ci-dessus, avec un engagement plus important lors de la sélection de la langue la moins bien maîtrisée. Nous avons montré que certaines structures sont impliquées pendant la sélection des deux langues (comme le cortex cingulaire antérieur) alors que d’autres sont recrutées uniquement pendant la sélection de la seconde (comme les noyaux caudés). Nous avons également observé que la maîtrise de la seconde langue module l’activité dans certaines régions cérébrales, et cela même si la sélection concernait la première langue. Ces analyses indiquent que la sélection de la langue utilise certains modules cérébraux spécifiques qui sont recrutés graduellement selon la difficulté de la tâche et la complexité des aspects linguistiques à traiter.
Concernant l’étude de la compréhension écrite, nous avons utilisé un paradigme de détection d’incongruence sémantique dans des paires de mots écris. Cette tâche nous permet d’étudier les mécanismes cérébraux impliqués dans le traitement de l’information sémantique et dans la reconnaissance visuelle des mots. Plusieurs travaux de neuroimagerie utilisant cette procédure ont suggéré que les structures temporales moyennes jouent un rôle important dans le traitement sémantique alors que la région temporo-occipital gauche est impliquée dans la reconnaissance du mot écrit (visual word form area). Sur cette base, nous avons étudié ces deux régions cérébrales à l’aide de l’IRMf. Nos analyses suggèrent que les régions temporales, impliquées dans le traitement de l’information sémantique, n’étaient influencées ni par la langue écrite, ni par la maîtrise de la seconde langue. Dans le cas de la région temporo-occipital gauche, une meilleure expertise dans la seconde langue a eu pour effet de diminuer son activation lors de la reconnaissance des mots de la seconde langue ainsi que des mots de la première langue.
Ainsi, ce projet a permis d’enrichir nos connaissances fondamentales sur l’organisation des langues dans le cerveau, ce qui pourrait aider à l’avenir le diagnostique et le traitement de certaines pathologies neurologiques liées au langage comme l’aphasie.
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Human beings have the fascinating ability to use different languages in their everyday life. Clinical and experimental findings support two fundamental assumptions: 1) languages mastered by a bilingual use the same neural substrates, and therefore a common brain network; 2) a control mechanism is needed to avoid mixing between the languages. However, it seems that these neural substrates are modulated by the proficiency of the languages. This thesis proposes to clarify some aspects related to the influence of the used language (first or second), as well as to the second language proficiency, on the brain mechanisms involved in producing and understanding language. To this end, this work examines specifically two of these aspects: a) the dissociation between neural substrates involved in language selection (of the first or second) and in cognitive control; b) neural substrates involved in written word comprehension, with special emphasis on semantic processing and on early word recognition during visual processing.
This thesis studies the modulation of functional activations in the cerebral regions involved during this processing, by the language used (first or second) as well as by the second language proficiency. To this aim, cerebral activity was studied in two groups of proficient bilinguals at Geneva University who were training to become professional translators (the two groups were at different levels in their training), and used the technique of functional magnetic resonance imaging (fMRI).
Regarding the brain network involved in language control, previous literature has pointed to the participation of various brain regions including the caudate nucleus (CN), the anterior cingulate cortex (ACC), the prefrontal cortex (PFC) and the supramarginal gyrus. The present fMRI research aims at distinguishing more clearly the so-called "language control"
network and assessing the influence of the bilinguals’ second language proficiency on it. For this purpose, brain activation is compared between cognitive control and language selection processes. Our analyses confirm the involvement of the CN, ACC and PFC in language
VII
weaker language. We show that some structures are involved during the selection of both languages (e.g., the ACC), while others are involved only during the selection of the weaker second language (the CN). We observe that proficiency in the second language modulates activity in several brain areas, even when the task concerns the selection of the first language.
These analyses indicate that language selection uses specific brain modules which are recruited gradually, depending on the difficulty of the task at hand and the complexity of the language aspect to process.
Regarding the written comprehension, we use the popular experimental paradigm of semantic incongruity detection in pairs of written words. This task permits the study of the cerebral mechanisms involved in semantic processing and early visual word recognition.
Several neuroimaging studies using this procedure suggested that the bilateral middle temporal cortex plays an important role in semantic processing and that the left temporo- occipital cortex (visual word form area) is more involved in written word recognition. On this basis, we study the modulations of these cerebral regions through fMRI. Our functional results suggest that the neural substrates involved in the processing of semantic information are independent of written language or of second language proficiency. In the case of the left temporo-occipital region, our analysis indicates that an improvement in second language expertise decreases the involvement of this region during word recognition of the second as well as first language.
Thus, this project improves our fundamental knowledge of language organization inside the brain. We hope that our findings will help in the diagnosis and treatment of neural pathologies linked to language, such as aphasia.
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First use of these terms in the manuscript is highlighted by the symbol *.
Age of acquisition = refers to the age from which a person starts to learn a new language. In this manuscript, it refers to the acquisition of the second language.
Aphasia = refers to a language disorder acquired following a focal brain lesion.
Contrast estimates = Estimation of the contrast intensity in the 90% confidence intervals for the studied conditions versus the baseline.
Early visual word recognition = refers to the first step of word recognition during the processing of visual information. It involves the extraction of abstract information (letters, strings, words) from written language.
Language assessment = refers to the proficiency evaluation test of the second language done by the participants. For more details, see the section Experimental population.
Language exposure = refers to the amount of time using a specific language on a daily base.
It is also described as language immersion.
Language proficiency = refers to the level of competence in an acquired language including comprehension and production abilities.
Language representation = refers in this thesis to the neural substrates (anatomically and/or functionally defined) used by the first language or the second language in the brain.
Mixing = refers to cohabitation between two elements. In the case of bilingualism, it refers to a bilingual context where several languages are present.
Modulate = verb used in this manuscript to express the influence of a factor on another element. For example “L2 representation was modulated by L2 proficiency” means that L2 representation was changed according to the level of L2 proficiency.
N400 component = refers to a negative electrophysiological peak around 350-400 ms after stimulus onset associated with semantic incongruity detection.
N400 effect = refers to semantic incongruity detection observed through fMRI by comparison between semantically unrelated and related stimulations (SU vs. SR).
Participants = refers to the bilingual people who participated on a voluntary base for the experimental part of our studies. They may also be called subjects in this manuscript.
Prime = in the experiment of Chapter 2, it refers to the first word presented during a trial.
Switching = refers to the process of task change, usually associated with a cognitive cost. In the case of language, it refers to the selection change of the used lexicon.
Target = in the experiment of Chapter 2, it refers to the second word presented during a trial.
Voxel(s) = defined a pixel in 3 dimensions, smallest component of an MRI image.
X Languages
L1 = the dominant language, which is often acquired first (mother tongue), with the highest proficiency
L2 = the acquired language with the second highest proficiency
Brain Regions
ACC = Anterior Cingulate Cortex CN = Caudate Nucleus
DLPFC = Dorso-Lateral Prefrontal Cortex IFG = Inferior Frontal Gyrus
iO = inferior occipital PFC = Prefrontal Cortex
STS = Superior Temporal Gyrus vOT = ventral occipitotemporal VWFA = Visual Word Form Area
Experimental terms BA = Brodmann area
DCM = Dynamic Causal Modeling DTI = Diffusion Tensor Imaging
(f)MRI = (functional) Magnetic Resonance Imaging EEG = Electroencephalography
ERP = Evoked Related Potential
HP = group of participants with the highest proficiency in their second language (L2) ISI = Interstimulus Interval
LP = group of participants with the lowest proficiency in their second language (L2) MEG = Magnetoencephalography
ms = milliseconds ROI = Region of interest S.D. = Standard Deviation
TMS = Transcranial Magnetic Stimulation
[Tal] = Talairach and Tournoux stereotaxic space (Talairach & Tournoux, 1988)
XI TSc = Task Selection context
TSc-Dig = condition of digit judgment during the Task Selection context TSc-Let = condition of letter judgment during the Task Selection context LSc = Language Selection context
LSc-L1 = Picture naming in first language during Language Selection context LSc-L2 = Picture naming in second language during Language Selection context SLc = Simple Letter context with letter judgment only
SNc = Simple Naming context in the first language only
Written word comprehension project
L1L1_SR; L1L1_SU = Prime* and target* words written in L1 semantically related (SR) or not (SU) L2L2_SR; L2L2_SU = Prime and target words written in L2
L2L1_SR; L2L1_SU = Prime word written in L2 and target word in L1 L1L2_SR; L1L2_SU = Prime word written in L1 and target word in L2
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REMERCIEMENTS ... II
RÉSUMÉ ... IV ABSTRACT ... VI
DEFINITIONS ... VIII TABLE OF CONTENTS ... XII LIST OF FIGURES ... XIV
LIST OF TABLES ... XVI
INTRODUCTION ... 1
1) Neural substrates associated with bilingualism and important factors which modulate them ... 4
A) Divergence of representation ... 4
B) Convergence of representations ... 5
Determinant factors in language representation ... 6
2) Language selection during bilingual production ... 10
3) Semantic processing and early visual word recognition in the written comprehension ... 20
EXPERIMENTAL POPULATION ... 39
CHAPTER 1: LANGUAGE SELECTION MECHANISMS AND MODULATION BY L2 PROFICIENCY ... 45
MATERIAL AND METHODS ... 47
RESULTS ... 56
1) Behavioral Results ... 56
2) Functional results ... 60
Task selection (TSc) and L1 language selection (LSc) contrasts ... 60
Difference between LSc and TSc contrasts and effects of proficiency ... 62
Selection of L2 nouns in LSc and effects of proficiency ... 66
Additional region of interest analysis ... 70
DISCUSSION ... 74
CHAPTER 1: CONCLUSION ... 86
CHAPTER 2: WRITTEN WORD COMPREHENSION IN BILINGUALS AND MODULATION BY THE L2 PROFICIENCY ... 87
MATERIAL AND METHODS ... 89
RESULTS ... 96
1) Behavioral Results ... 96
2) Functional results ... 100
Effects of the semantic relatedness ... 100
Language and proficiency effects on written word recognition ... 106
The influence of language mixing ... 112
DISCUSSION ... 114
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CHAPTER 2: CONCLUSION ... 127
GENERAL DISCUSSION AND CONCLUSION ... 129
1) Summary of the thesis project ... 132
Language selection during oral production ... 132
Semantic processing and early word recognition in written comprehension ... 134
2) Approach used to study language proficiency ... 138
3) Future perspective for research on language representation modulations ... 140
Final remarks ... 148
REFERENCES ... 149
APPENDIX ... 177
Appendix 1: Experimental stimulations used during the language selection project (Chapter1) ... 178
Appendix 2: Experimental stimulations used during the written word comprehension project (Chapter2) ... 194
Appendix 3: French version of the text used during the L2 proficiency assessment... 200
Appendix 4: German version of the text used during the L2 proficiency assessment... 203
Appendix 5: Self‐assessment questioner on the L2 proficiency ... 206
Appendix 6: Self‐evaluation of the languages daily exposure ... 208
Appendix 7: Supplementary activation tables for the Chapter 1 ... 209
Appendix 8: Publications and public communications produced during the thesis ... 215
XIV INTRODUCTION (I)
Figure I.1: Illustration of the language selection network ... 15
Figure I.2: The revised hierarchical model for bilinguals ... 24
Figure I.3: BIA+ model ... 26
CHAPTER 1: LANGUAGE SELECTION (1) Figure 1.1: Experimental protocol ... 49
Figure 1.2: Illustration of the performances interaction ... 57
Figure 1.3: Illustration of selection activities ... 61
Figure 1.4: Selection of L1 ... 64
Figure 1.5: Selection of L2 ... 67
Figure 1.6: ROI analysis on the head of the caudate nucleus ... 71
Figure 1.7: ROI analysis in the left supramarginal gyrus ... 73
CHAPTER 2: WRITTEN WORD COMPREHENSION (2) Figure 2.1: Experimental protocol ... 92
Figure 2.2: Illustration of the RT interactions ... 97
Figure 2.3: Illustration of the performances interactions ... 99
Figure 2.4: N400 contrast and its modulation by experimental factors ... 103
Figure 2.5: Language as well as proficiency effects and VWFA ... 108
Figure 2.6: Language mixing effect ... 112
GENERAL DISCUSSION AND CONCLUSION (C) Figure C.1: Theoretical model of the relations inside the language selection network ... 146
XVI INTRODUCTION (I)
Table I.1: Brain regions implicated in the semantic processing ... 22
Table I.2: Experimental questions investigated in this thesis project and their prediction.38 CHAPTER 1: LANGUAGE SELECTION (1) Table 1.1: Behavioral results ... 59
Table 1.2: Interaction between the LSc and TSc contrasts ... 65
Table 1.3: Comparison between L2 vs. L1 naming in LSc ... 68
Table 1.4: Proficiency difference (LP vs. HP) of the L2 and L1 comparison ... 69
CHAPTER 2: WRITTEN WORD COMPREHENSION (2) Table 2.1: Specificities for each experimental set ... 89
Table 2.2: Summary of the behavioral measures ... 100
Table 2.3: Comparison between SU vs. SR conditions (N400 contrast) ... 104
Table 2.4: Influence of the L2 proficiency on the N400 contrast ... 105
Table 2.5: Target language effect (L2 vs. L1) ... 109
Table 2.6: L2 proficiency effect (LP vs. HP) ... 111
Table 2.7: Language mixing (Mix vs. Unmix) ... 113
GENERAL DISCUSSION AND CONCLUSION (C) Table C.1: Summary of experimental questions and their associated results ... 131
APPENDIX (A) Table A.1: Task selection (TSc) contrast ... 209
Table A.2: Language selection (LSc) contrast ... 210
Table A.3: Conjunction between TSc and LSc contrasts ... 211
Table A.4: Activations details of the LSc‐L2 vs. LSc‐L1 comparison ... 212
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1
Introduction
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The term “language” defines the sets of codes that humans use to communicate ideas, intentions and feelings inside a group. The presence of different geographical and ethnic groups in the world has led to the development of a wide variety of languages throughout history. The development of communication between these groups and their globalization through a huge network (immigration, culture, politics, tourism, etc.) has highlighted the special ability of humans to learn and speak several languages. This ability is commonly called “bilingualism” and plays a crucial role in the building of our societies. Several definitions of bilingualism can be found in the literature. For example, a restrictive definition assumes a simultaneous learning of two languages during childhood which will reach similar proficiency (Bloomfield, 1933). A less restrictive view defines a bilingual as a person who has mastered at least one of the three basic linguistic abilities (comprehension, speaking or writing) in a language other than his mother tongue (Macnamara, 1967). In this project, we will consider the following psycholinguistic definition: bilingualism is the ability to express oneself in a mother tongue (called L1), and at least in a second learned language (called L2) in daily life (Grosjean, 1998). This ability allows bilinguals to understand and express themselves through an oral or written modality in both acquired languages. Note that the proficiency level between L1 and L2 is not necessarily identical. The definition of bilingualism can be extended to distinguish between periods of acquisition for L2. Thus, people who learn their second language before around 7-10 years old are called “early bilinguals”, while people who learn after this period are called “late bilinguals” (Khateb, 2009; Lenneberg, 1967; Saur et al., 2009).
A fundamental distinction is made between types of linguistic knowledge acquired throughout life. Primarily, the “mental lexicon” contains all memorized information about words, including their sound (phonetic), spelling (orthographic) and their meaning (semantic).
The second type of knowledge is the “mental grammar” which contains the rules, operations,
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and constraints which permit the combination of lexical forms and abstract representations into complex linguistic structures such as sentences (syntax). The theoretical declarative/procedural model, based on neurolinguistic and psycholinguistic evidence, proposes that these two types of knowledge are managed by two memory systems (M.
Ullman, 2001; M. T. Ullman, 2001; Ullman, 2004). The lexical memory would depend on the declarative memory which is mainly rooted in temporal lobe structures (hippocampus and related regions). This memory is involved in learning, representations and the use of semantic and episodic knowledge. In the other case, the grammatical memory depends more on the procedural memory which is rooted in the left fronto/basal-ganglia structures. This type of memory is involved in unconscious learning and the execution of long-established motor plans, skills or habits.
Since the 20th century, people have been interested in understanding how the human brain manages one or several languages. This question has, for the most part, been investigated by psycholinguists and neuroscientists using various methods such as clinical observations, behavioral experiments and/or neuroimaging techniques. This thesis studies some important aspects of how the “bilingual brain” manages more than one language and the way this processing is modulated* by L2 proficiency. By way of introduction to these problems, we will initially develop some aspects of brain representation associated with bilingualism which are important in understanding their impact on the “speaking brain”.
Secondly, we will present the problem of the neural substrates involved in the management of different languages, which is the topic for study in Chapter 1. Thirdly, we will tackle the subject of neural models and the influence of bilingualism on language representations*
involved during written comprehension, looking specifically at the semantic aspects and the early recognition of words in visual areas. This last point is the topic for study in Chapter 2 of this thesis.
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1) Neural substrates associated with bilingualism and important factors which modulate them
The research on neural substrates associated with languages (also called language representation in this thesis) has focused its attention in particular on the representation of L1 and L2 in the brain. Two competitive results on this question could be found: representations are shared by the languages (A) or are different according the language used (B). These conepts were originally developed by (D. Green, 2003) and significantly extented by (J.
Abutalebi & Green, 2007). We are going to review various clinical and experimental evidences for each of these cases (divergence/convergence) as well as the important factors which have an effect on them.
A) Divergence of representation
A.I) Clinical evidence: The question of language representation in bilinguals was originally raised on the basis of clinical observations of aphasic* patients (Aglioti &
Fabbro, 1993; Albert & Obler, 1978; Fabbro, 2001b; Garcia-Caballero et al., 2007;
Gomez-Tortosa, Martin, Gaviria, Charbel, & Ausman, 1995; Ibrahim, 2009; Meinzer, Obleser, Flaisch, Eulitz, & Rockstroh, 2007; Paradis, 1977, 1983, 1995). Several of these reports showed an unequal pattern of impairment between the two languages (selective impairment) while others highlighted an unequal pattern of recovery (selective recovery). These observations suggested that each language was represented in distinct cerebral areas. For example, clinical observations of four bilingual aphasics with lesions circumscribed to the left basal ganglia showed worse grammatical performance in their dominant language (L1) than in the non-dominant one (L2) (Fabbro & Paradis, 1995).
A.II) Experimental evidence: Electrocortical brain stimulation reports also provided evidence for separate representations because stimulation at different cerebral
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localizations affected the languages unequally (Bello et al., 2006; Lucas, McKhann, &
Ojemann, 2004; Ojemann, 1983; Ojemann & Whitaker, 1978; Rapport, Tan, &
Whitaker, 1983; Roux et al., 2004; Roux & Tremoulet, 2002; J. A. Walker, Quinones- Hinojosa, & Berger, 2004), for a review see (Giussani, Roux, Lubrano, Gaini, &
Bello, 2007). In particular, the left areas mainly located in posterior temporal, frontal and parietal areas induced language specific patterns (a decrease in production fluency) during various types of task such as object naming, reading, etc. Thereafter, the development of modern functional imaging techniques (positron emission tomography (PET) and functional magnetic resonance imaging (fMRI)) provided new and powerful tools for assessing the question of language representation. For example, some functional neuroimaging works found distinct brain activation between L1 and L2 using different experimental paradigms in regions such as Broca’s area, the cerebellum, the left supramarginal gyrus,… with higher responses by the right cerebral hemisphere for L2 in comparison to L1 [e.g., (Dehaene et al., 1997; Halsband, 2006;
Halsband, Krause, Sipila, Teras, & Laihinen, 2002; Marian, Spivey, & Hirsch, 2003)].
B) Convergence of representation
B.I) Clinical evidence: Common language representation between languages was supported by some clinical studies. For instance, several aphasic patients showed a similar impairment in both languages after a stroke (parallel recovery) [e.g., (Fabbro, 2001a; Laganaro & Overton Venet, 2001; Watamori & Sasanuma, 1976)]. Another interesting case study published by Marangolo et al. showed the recovery of both impaired languages of a bilingual woman with chronic aphasia* after a rehabilitation therapy only in L2 (Marangolo, Rizzi, Peran, Piras, & Sabatini, 2009). This parallel recovery, although only one language was treated, strongly suggested that both languages shared similar neural substrates.
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B.II) Experimental evidence: Several results of neuroimagery also supported the language representation convergence view. For example, the overlapping between brain activation during L1 and L2 picture naming (A. E. Hernandez, Dapretto, Mazziotta, & Bookheimer, 2001; A. E. Hernandez, Martinez, & Kohnert, 2000) or semantic judgment tasks (Illes et al., 1999) suggested that the languages shared similar neural substrates. However, the convergence did not mean that the processing between the languages would be identical. Indeed, the network has to be trained to manage distinct linguistic patterns. For example, a difference in activation intensities could be observed between languages in this network, probably due to better performances in L1 than in L2 (J. Abutalebi & Green, 2007).
To summarize, there is evidence in the literature to support these two main versions of language representation in bilinguals (similar brain networks or not). Notably, a higher number of functional results supported the convergence hypothesis, while clinical results provided stronger evidence for the divergence hypothesis. Thus, the question of language representation in bilinguals has not received a clear answer. This variation in results could be attributed to modulations caused by several factors such as proficiency*, age of acquisition*, exposition* (Chee, Hon, Lee, & Soon, 2001; Illes et al., 1999; Klein, Milner, Zatorre, Zhao,
& Nikelski, 1999; Perani & Cappa, 1998; Pillai et al., 2003; Ruschemeyer, Fiebach, Kempe,
& Friederici, 2005; Tatsuno & Sakai, 2005). This is why we intend to review the influences of these factors on language representation.
Determinant factors in language representation
The age of acquisition of a new language was expected to have an important influence on its representation. Indeed, several scientists hypothesized the existence of a critical time period between infancy and puberty in which the learning of a new language is more efficient (Lenneberg, 1967; Penfield & Roberts, 1959). There was much evidence to
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indicate that proficiency in grammar and pronunciation declined with a later age of acquisition [e.g., (Birdsong & Molis, 2001; Flege, Yeni-Komshian, & Liu, 1999; J. S.
Johnson & Newport, 1989; Wartenburger et al., 2003)]. This critical period hypothesis could reflect a maturational change in brain processing. Indeed, Newport and Goldowsky hypothesized that language learning abilities decrease over maturation due to memory limitation which usually simplifies the computation of form-meaning relationships to reduce formulaic learning (Goldowsky & Newport, 1993; Newport, 1990). Moreover, the adaptation of Ullman’s declarative/procedural model to bilinguals suggested that the representation of L2 knowledge should differ in comparison to L1, especially for late bilinguals (M. Ullman, 2001). In this case, the grammatical processing, which was associated with the procedural memory in L1, would be more dependent on declarative memory for L2, while its lexical knowledge involved the same type of memory. This shift to declarative memory for syntactic knowledge might be related to conscious (explicit) learning and retrieval of information, using non-automatic grammatical rules (as in a pedagogic environment) as well as the memorizing of pre-existing grammatical structures such as expressions, sentences, idioms, etc. Thus, based on these theories, it was expected that while certain aspects of language representation are shared by L1 and L2, the dependency of declarative memory (modulated by the L2’s age of acquisition) could lead to different representations between languages. This shift should be more important for late learners than early learners, and dependency on procedural memory should increase with practice.
The effect of age of acquisition was investigated by different experimental studies. For instance, language representation for monolinguals and bilinguals was shown to be lateralized in the left hemisphere of the brain (Broca, 1861; De Freitas & Dubrovsky, 1976; Rapport et al., 1983; Seghier, Lazeyras, Pegna, Annoni, & Khateb, 2008; Soares, 1982; Soares &
Grosjean, 1981; Wernicke, 1874), while some studies reported that the laterality of the L2
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representation was modulated by several factors, such as the L2’s age of acquisition. For early language acquisition, it was more left-lateralized than for late acquisition, which also involved the right hemisphere more (Albert & Obler, 1978; Neville et al., 1997; Vaid & Hall, 1991;
Vaid & Hull, 2002). However, the effect of acquisition age on the laterality of the language representations is not clear because a different pattern was also observed. Indeed, a recent meta-analysis of 66 behavioral studies concluded that a bilateral lateralization of both languages occurs in early acquisition (before six years old), and left lateralization in late acquisition (Hull & Vaid, 2007). Apart from this question of laterality, the functional work of Kim et al. also suggested that the age of acquisition of the second language is a critical factor for the functional organization of the human brain (Kim, Relkin, Lee, & Hirsch, 1997).
Indeed, they found that the two languages involved two different regions in Broca’s area for late bilinguals and a common region for early bilinguals.
Language proficiency and exposure* were shown to play a greater role in language representation than the age of acquisition [e.g., (J. Abutalebi, Cappa, & Perani, 2001; Illes et al., 1999; Perani & Cappa, 1998)] or the order of language acquisition (Basnight-Brown &
Altarriba, 2007; M. K. Leonard et al., 2011). Various results in literature suggested that the brain’s representations of L1 and L2 converged on the same network when the L2 proficiency increases (J. Abutalebi, 2008). In particular, neuroimaging studies reported similar brain activation for both languages when L2 proficiency was comparable to L1 [e.g., (Chee, Caplan et al., 1999; A. E. Hernandez et al., 2001; A. E. Hernandez et al., 2000; Klein, Milner, Zatorre, Meyer, & Evans, 1995; Klein et al., 1999; Klein et al., 2006)], while low L2 proficiency engaged supplementary brain activity [e.g., (Briellmann et al., 2004; Chee et al., 2001; Marian et al., 2007; Pillai et al., 2003; Vingerhoets et al., 2003)]. In this case, Perani and Abutalebi suggested that differences between L1 and L2 representations were linked to the unequal computational demands which dynamically change with the L2 proficiency
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(Perani & Abutalebi, 2005). Exposure to a language also had an important effect on language representation. For example, it has been found that L2 could replace L1 if bilinguals were no longer exposed to it. This case was observed by fMRI in an adopted Korean population of children in France who were no longer exposed to the Korean language (Pallier et al., 2003).
Brain activity while listening to Korean sentences (maternal language) for these people, who became proficient in French at adulthood, was similar to an unknown language. In addition, cerebral activity and performance during a recognize/translate task in Korean were similar between this adopted population and native French people. These observations suggested that daily exposure to the French language had replaced the representations of the maternal language.
This review showed that the age of acquisition and language proficiency have an important impact on the language representation. It is why we decided to study more specifically the effect of the L2 proficiency on neural substrates associated with the language processing. However, we are conscious that the modulations caused by L2 proficiency are difficult to differentiate from age of acquisition and exposure (Moreno & Kutas, 2005), because these factors are interdependent (Birdsong & Molis, 2001; J. S. Johnson & Newport, 1989). To limit the influence of this last factor, we tested a population of bilinguals with similar age of acquisition for their L2.
In this first section, we showed that several issues related to the influences on language representation in bilinguals, during the production or the comprehension needs to be clarified to better understand the brain mechanisms which support the human ability to use two languages. In this thesis, we propose to investigate two of these issues: language selection during spoken word production (Chapter 1) and the comprehension of written words, more specifically semantic processing and the early visual word recognition
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processing* (Chapter 2). Moreover, the modulation by L2 proficiency of language representation and processing will be specifically investigated to better understand its importance on the neural substrates associated with the bilingualism. More specific questions addressed by each chapter are summarized in Table I.2 (on page 38 of this manuscript).
This research was performed by means of two different functional magnetic resonance imaging (fMRI) experiments. We chose to use this technique in our project because its high spatial resolution allowed inferences to be made about the brain’s networks and their modulations across the experimental conditions. To this end, two groups of participants* with different L2 proficiency levels were recruited from a population of bilinguals with similar ages of acquisition (mainly late learners with acquisition after seven years old) and language exposure. Each of them was following a pre-graduate learning program at the Geneva University Translation School in their L1 and L2 (which guaranteed a regular and similar exposure to both languages for each group). The proficiency of these healthy participants was established on the basis of their course level (Bachelor and Master) and on their language assessment* score evaluated by a standard examination protocol of their faculty.
2) Language selection during bilingual production
It is important to distinguish a bilingual person from bilingual behavior, i.e., the communicative context in which a bilingual expresses him/herself. Grosjean distinguished two types of bilingual behavior: when speaking to a monolingual person or when speaking to another bilingual person (Grosjean, 1998). He proposed that bilinguals choose one language and deactivate (not totally) the other in monolingual mode (Grosjean, 1985). In a bilingual context, they choose one language of reference and activate the other as a function of their need. When a bilingual speaks to a monolingual person, he forces himself to stay in the
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language of the receiver. In the case of two bilinguals with the same L1 and L2, they speak a mix of both languages (bilingual context). They can switch from one to the other depending on the situation. These concepts introduce the important question of how the bilingual brain manages (or controls) the use of the two or more languages? Which brain mechanisms allow bilinguals to communicate in one language rather than in another, but also to switch between them during the same conversation? This particular processing called "language control" or
"language selection" has been the focus of multiple clinical and experimental studies for more than a decade. Great progress in the knowledge of its neural basis has been achieved; however it is still not completely understood. The first part of this thesis aims to distinguish more clearly the brain networks involved in language selection. After a presentation of the original clinical results and theories, we are going to review the current knowledge of the brain’s correlates associated with this process.
The issue of a brain network involved in language selection was originally raised on the basis of clinical observations of bilingual aphasic patients (Albert & Obler, 1978;
Fabbro, 2001b; Paradis, 1977, 1983, 1995) and of brain stimulation reports (Lucas et al., 2004; Ojemann, 1983; Ojemann & Whitaker, 1978). After certain brain injuries, including to the anterior cingulated/the frontal cortex (Fabbro, Skrap, & Aglioti, 2000), the left insular cortex (Leemann, Laganaro, Schwitter, & Schnider, 2007), sub-cortical structures (J.
Abutalebi, Miozzo, & Cappa, 2000; Marien, Abutalebi, Engelborghs, & De Deyn, 2005), or brain electrostimultation in temporal superior sulcus (Moritz-Gasser & Duffau, 2009), some bilingual aphasics exhibited pathological switching* or language mixing* difficulties.
Following left basal ganglia damage (Aglioti, Beltramello, Girardi, & Fabbro, 1996; Aglioti
& Fabbro, 1993; Moretti et al., 2001), other aphasics showed selective recovery of one, but not of the other language. In addition, Paradis et al. reported the case of two bilingual aphasic
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patients who showed a paradoxical recovery pattern of spontaneous speech (Paradis, Goldblum, & Abidi, 1982). Indeed, they were able to speak in L1 but not in L2, and the following day they showed the inverse pattern (able to speak in L2 but not in L1). Another clinical observation showed a similar, paradoxical recovery (Nilipour & Ashayeri, 1989).
Altogether, such observations were interpreted in terms of impairment to the language control system (J. Abutalebi, 2008; J. Abutalebi et al., 2008; D. Green, 2003), which seemingly depends on a left hemispheric neural system that includes the basal ganglia, the prefrontal cortex and probably other brain regions. According to such an interpretation (D. Green, 2003), selective recovery of one language would be caused by brain damage that permanently inhibits the other non-recovered language. Pathological language mixing/switching would be the result of an injury that produces an uncontrolled selection of the language to be used.
On the basis of these observations, some authors put forward several theories to better explain the cognitive origin of language selection. Two major points of view were developed in the literature:
A) The Late Selection theory suggests that both lexicons of the target and non-target language stay active (Colomé, 2001). In this case, the competition occurs between lexical nodes, or lemma, in selecting the target language (Costa & Caramazza, 1999).
Selection mechanisms pick out the most highly-activated lexical node at a given moment, and the degree of activation of the non-target one will affect the ease of this selection (competition). In conclusion, the lexical selection is achieved without the need of an active inhibition of the non-target lexicon (Roelofs, 1998). The greatest evidence comes from the work of van Heuven et al. which showed that the number of orthographic neighbors (e.g., PORK[eng] / WORK[eng] or APPLE[eng] / APPEL[fr]) in the target and the non-target language interfered with the target word processing in L1 or L2 (van Heuven, Dijkstra, & Grainger, 1998). In addition, the spontaneous
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appearance of words which do not belong to the target language during a production suggests that lexical nodes of the non-target language stay active (Grainger, 1993;
Grainger & Dijkstra, 1992; Grosjean, 1992).
B) The Early Selection theory proposes that inhibition of the non-target language is necessary to solve the competition between the lexicons of the different languages (De Bot & Schreuder, 1993; D. W. Green, 1986, 1998; M. W. Lee & Williams, 2001) as reviewed by (J. Abutalebi et al., 2008). More precisely, the non-target language is actively inhibited in the early stages of processing before access to the lexicons (D. W.
Green, 1998), and only the target lexicon would stay active (this theory is called the Inhibitory Control model). Evidence of the Early Selection theory comes from the study of the cognitive cost of switching between languages. Using a naming paradigm, Meuter and Allport (1999) observed that the switch cost in producing a word in the dominant language (L1) after a production in the weak language (L2) was higher than in the opposite direction (L1→L2). This result could reflect the fact that the lexical access to the L1 word was slowed by the inhibition of this dominant language which was required in the production of the word in the less dominant language (L2) at the previous trial, according to the Inhibitory Control model (Meuter & Allport, 1999).
The cognitive origin of language selection remains uncertain because much evidence was found among the literature to support each of these theories. The study of the cerebral mechanisms and neural substrates implicated in this processing could help us to better understand how it works. Therefore, the first part of this thesis (Chapter 1) investigates this question, using fMRI neuroimaging techniques.
The brain network involved during language selection was investigated using various types of linguistic and non-linguistic paradigms, and suggested the participation of
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different brain areas which correspond mostly to the sites of injury reported in the clinical observations. Thus, various studies manipulating language control compounds (language selection/switching, interpretation/translation, interference, etc.) reported activation in the basal ganglia and in particular the left caudate nucleus (CN) (J. Abutalebi et al., 2008; J.
Abutalebi, Brambati et al., 2007; Ali, Green, Kherif, Devlin, & Price, 2009; Crinion et al., 2006; Gil Robles, Gatignol, Capelle, Mitchell, & Duffau, 2005; Price, Green, & von Studnitz, 1999; van Heuven, Schriefers, Dijkstra, & Hagoort, 2008). Activation was also observed in the bilateral anterior cingulate cortex (ACC) (J. Abutalebi et al., 2008; J. Abutalebi, Brambati et al., 2007; Price et al., 1999; Wang, Xue, Chen, Xue, & Dong, 2007), the prefrontal areas with the left inferior frontal gyrus (IFG) and dorso-lateral prefrontal cortex (DLPFC) (J.
Abutalebi et al., 2008; A. E. Hernandez, 2009; A. E. Hernandez et al., 2001; A. E. Hernandez et al., 2000; Holtzheimer, Fawaz, Wilson, & Avery, 2005; M. H. Lehtonen et al., 2005;
Nardone et al., 2011; Rodriguez-Fornells, Rotte, Heinze, Nosselt, & Munte, 2002; Rodriguez- Fornells et al., 2005; Wang et al., 2007), and the supramarginal gyrus (A. E. Hernandez et al., 2001; Mechelli et al., 2004; Price et al., 1999). To summary, a large number of brain regions might participate in language control, confirming that it depends more on a largely distributed system rather than on a specific cerebral module. The Figure I.1 illustrates this network on a MRI template brain.
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Figure I.1: Illustration of the language selection network. It is characterized by these four highlighted areas.
Regions are labeled in the left hemisphere for a practical reason but could involve also the right hemisphere (see in the text). This sketch is based on figure p.249 from (J. Abutalebi & Green, 2007).
To date, the existence of a brain network dedicated specifically to language control is still debated as all these regions participate in other linguistic and non-linguistic cognitive control processes. To give some examples, the basal ganglia (including the CN) participate in the planning and execution of plans for achieving goals (Grahn, Parkinson, & Owen, 2008), acquisition of orthographic representation (J. Abutalebi, Keim et al., 2007), learning and reinforcement of a stimulus-associated response (Flores & Disterhoft, 2009; Packard &
Knowlton, 2002; N. M. White, 2009). Other studies showed that CN activation correlated with the level of cognitive difficulty in planning tasks such as the Tower of London (Dagher, Owen, Boecker, & Brooks, 1999; Owen, Doyon, Petrides, & Evans, 1996). With regard to the ACC, it is known to have a major involvement in conflict detection/monitoring, response inhibition (Barch et al., 2001; M. Botvinick, Nystrom, Fissell, Carter, & Cohen, 1999; Kerns
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et al., 2004; van Veen & Carter, 2005) and error detection (Carter et al., 1998; Maril, Wagner,
& Schacter, 2001). Others have suggested the involvement of the ACC in conflict detection and in the recruitment of other control modules (such as the DLPFC) and for conflict resolution (Braver, Barch, Gray, Molfese, & Snyder, 2001; Carter et al., 2000; MacDonald, Cohen, Stenger, & Carter, 2000). In the case of the prefrontal cortex (PFC), its involvement was found in various language tasks (e.g., semantic categorization, word generation and recognition or rhyme detection) (Gerfo et al., 2008; Mainy et al., 2008; Seghier et al., 2004;
Vigneau et al., 2006), working memory and attention (J. A. Johnson, Strafella, & Zatorre, 2007; Nebel et al., 2005; Raye, Johnson, Mitchell, Reeder, & Greene, 2002) as well as cognitive control tasks (Brass, Ullsperger, Knoesche, von Cramon, & Phillips, 2005; Miller, 2000; West & Travers, 2008). Finally, the supramarginal gyrus has also been identified in various linguistic contexts, including phonological processing (Blumstein, 2009; Caplan, Gow,
& Makris, 1995; Emmorey, Mehta, & Grabowski, 2007; Prabhakaran, Blumstein, Myers, Hutchison, & Britton, 2006; Raizada & Poldrack, 2007), vocabulary acquisition (H. Lee et al., 2007) and language switching (Herschmann & Potzl, 1983; Kauders, 1983; Potzl, 1983; Price et al., 1999).
Without claiming to be exhaustive, this short overview demonstrates that brain areas revealed by functional paradigms manipulating language selection/control aspects show a large overlap with those involved in general cognitive control and attention mechanisms.
These results suggest that the language selection process is strongly dependent on the cognitive control networks [for review see (Ye & Zhou, 2009)]. Hence, the question remains to know whether or not some areas of the cognitive control network are more specifically engaged during language selection processes, and if yes, when and how they are involved?
Several previous studies have tried to answer these questions. For example, previous electrophysiological research by Khateb et al. compared a language selection task
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(participants were required to name images in a highly mixed bilingual context) and a task selection context (they were required either to name or to generate a verb related to images in L1). They found an electrical divergence between these selection processes at around 220 to 300 ms after the cue which followed stimulations informing the participant about the task to be accomplished (L1/L2 naming; L1 naming/L1 related verb generation). Its origin was estimated to be in the left middle frontal-precentral, supramarginal and angular gyri by inverse solution (Khateb, Abutalebi et al., 2007). Later, Abutalebi et al. used a similar experimental protocol using fMRI and highlighted an increase of activation (during naming in a mixed L1 condition as compared to a non-mixed L1) in the left CN, the ACC, part of the PFC and the IFG (J. Abutalebi et al., 2008). The results of these two studies showed that there is a difference of brain involvement between language and task selection, but did not permit the assertion/invalidation of the existence of specific neural substrates for language selection.
However, two modifications of their protocols might be necessary to improve these functional data regarding our question. First, the task control context ideally should be independent of the lexical access to avoid suppression of its contrasting related activities which could be important during the language selection process. Indeed, this was not the case in Abutalebi et al. (2008) (the naming or verb generation needed the retrieval of lexical information) which left some doubt about the reliability of the network highlighted by the comparison of language and task selection. Second, the experimental protocol should limit the needs of working memory, in order to determine if PFC activation reflected the language selection process from the memory load due to the experimental procedure. Indeed, the post-stimulation cueing used by Abutalebi et al. (2008) increased the working memory load and could induce additional conflict, which may make the interpretation of the PFC activation difficult. This is why the use of a cue presented at the same time as the stimulation (e.g., spatial position on the screen) would be a better choice. The first experiment proposed by this thesis aimed to respond to the
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question of the specificity of the language control network using a similar protocol such as Abutalebi et al. (2008), with several adaptations in line with previous remarks.
Although much evidence has shown that L2 proficiency modulates language representation in the brain (as discussed in the first part of this Introduction), its influence on language selection remains only marginally explored. One of the first pieces of evidence that language selection improves with linguistic abilities was the reduction of non-target language intrusions during L2 speech production when L2 proficiency increased (Poulisse &
Bongaerts, 1994). Further evidence is found in the asymmetrical switch cost during word production between the backward (L2→L1) and the forward (L1→L2) direction, as discussed in the Late Selection theory paragraph (Meuter & Allport, 1999); this was shown to vary according to language proficiency. Indeed, no difference between backward and forward switching was observed for highly proficient bilinguals, in contrast with lowly proficient ones (Costa & Santesteban, 2004). Following these results, we were interested in studying whether some parts of the neural network involved in language selection were modulated by L2 proficiency. Moreover, it could allow for a clearer distinction of this processing and of the involvement of its related neural substrates. Assuming that lexical selection in the less dominant language is more demanding than in L1 (Perani & Abutalebi, 2005), and is achieved through more controlled processing resources as compared to the dominant one which relies on more automatic resources (French & Jacquet, 2004), we hypothesize that brain activations during L2 selection might be decreased for highly proficient, in comparison to lowly proficient, bilinguals. This modulation would follow on from a more automatic access to L2 items and a reduction of between-languages competition [see (J. Abutalebi et al., 2008)].
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In order to determine if the dissociation between cognitive control and the language selection network exists, the work undertaken in Chapter 1 raised the following question: was there a difference at the neural level between the selection of a given language (which involved both networks) and the selection of a task in a monolingual context (which involved only the cognitive control network)? This issue was investigated using an fMRI study which compared brain activity elicited in a language selection context (LSc) and a non- linguistic task selection context (TSc) with an adapted protocol based on previous studies (J.
Abutalebi et al., 2008; Khateb, Abutalebi et al., 2007), with the language/task selection being primed by simultaneous cueing in order to minimize the load on the working memory. The comparison of brain activity in these two selection contexts, without interference from other types of activity such as lexical processes, should help to determine if some brain modules are found specifically in language selection and not in the task selection processes. In addition, the design of two tasks of comparable difficulty (whose reaction times and accuracy differences were expected to be similar for the tasks/language selection), as well as a poor working memory load (ensured by simultaneous cueing), was expected to improve the quality of this differentiation. Taking into consideration the consistency of previous results in this field, we expected to observe some distinct contributions from the left lateralized network formed by the CN, the ACC, the PFC and the supramarginal during the language selection (with higher activations in these regions for LSc than for TSc).
Our second question in this chapter was the following: does L2 proficiency modulate the neural substrates involved in the selection of L1 or L2 during an oral production?
This was investigated by comparing behavioral and fMRI data between the two groups of participants (LP and HP). Concerning the effect of language proficiency within the group, we postulated, as has already been shown, that there should be a difference in the neural substrates involved in L1 and L2 selection. Given the inhibitory mechanism of the non-
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selected languages proposed by the different selection models, we predicted that naming a stimulus in L2 in a bilingual context necessitates a stronger inhibition of the first language, i.e., a greater activation of this control network, than when compared to a second language inhibition when naming a word in L1. In the case of the comparison between the groups, L2 proficiency was expected to influence the language selection network (with higher involvement for LP than for HP participants). Indeed, its organization should be modified by a non-equivalent use frequency between the groups (HP participants were usually more exposed to language switching than LP). It should also adapt itself to the difference in use efficiency between the first or second language, which would be supposedly higher for LP than for HP. Questions and predictions are summarized in Table I.2 on page 38 of this manuscript.
3) Semantic processing and early visual word recognition in the written comprehension
Another important issue in the study of language representation in bilinguals concerns the neural substrates involved in written word comprehension. Does the brain network involved during the reading process differ according to the language used (L1/L2)? This processing is characterized by several steps (i.e., early visual word recognition → lexical access → integration of information) which raise the question as to whether the network modulation between the two languages may vary according to the depth of the word process.
As an example, we will focus on “deep” lexico-semantic access on the one hand and “early”
visual word recognition on the other hand during the second part of this thesis (Chapter 2).
After having reviewed different theoretical models of bilingual lexico-semantic representations and on visual word form recognition, we will focus on paradigms which may
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allow the evaluation of these two steps in the written comprehension process in bilingual participants. Our approach is mainly oriented towards neuroimaging data which permits us to study the influence of the language used and the language proficiency in these steps.
The semantic memory is composed of knowledge of words’ meaning, but also of abstract and concrete concepts acquired during life. The treatment of semantic information recruits a huge brain network composed of six distinct regions as summarized in Table I.1. In the specific case of bilinguals, researchers were especially interested to know if the lexico- semantic representations in the brain are similar for L1 and L2. This question was assessed in many ways (electroencephalography, functional imagery, clinical observation, brain stimulations, etc.) but remained subject to debate [for a recent review see (Midgley, Holcomb,
& Grainger, 2009)]. To review the knowledge on this question, we intend firstly to develop some psycholinguistic models; these will be followed by some experimental and clinical results.
