Langage et cerveau : vingt ans d'imagerie fonctionnelle [Language and the brain: 20 years of functional imagery]

La masse considérable de travaux publiés dans le domaine de la neuroimagerie fonctionnelle concernant les fonctions ou modalités du langage (compréhension et expression de la parole, lecture) ou les différents processus linguistiques qui les sous-tendent (sémantique, phonologie, syntaxe) permet de dégager de grandes tendances en termes de substrats anatomiques. Si les « fondamentaux » issus des origines aphasiologiques du domaine n'ont pas été bouleversés, certaines spécificités non explorées par l'approche lésionnelle sont identifiables. Les méta-analyses, en regroupant les résultats de la littérature, nous procurent aujourd'hui une vision globale des substrats cérébraux du langage. Cependant la variabilité inter-individuelle reste importante en raison de multiples facteurs dont certains sont mal identifiés ; cartographier exhaustivement les fonctions du langage à l'échelle individuelle reste une gageure. La quête des images du langage est sans doute aussi inachevable que celle de l'étude du langage lui-même.

Language lateralization in early and late bilinguals using an international vocabulary

In lateralized Lexical Decision Tasks (LDT), accuracy is commonly higher and reaction times are commonly faster for right visual field (RVF) than left visual field (LVF) presentations. This visual field differences are thought to demonstrate the left hemisphere's dominance for language. Unfortunately, different tasks and words are used between studies and languages making direct comparisons difficult. For example, high frequency words show a performance advantage over low frequency words. Moreover, demographic variables impact on lateralized behavior such as language knowledge (one versus several, early acquired versus late acquired). We here aim to alleviate some of these obstacles by presenting results from a lateralized LDT for which we selected words between 4 and 6 letters used in five different languages, i.e. English, French, German, Dutch and Italian. In this first study using these words, we compared performance of right- and left-handed students being either early or late bilinguals (acquired before or after the age of 6 years) from a French-speaking University in Switzerland. Results showed a left hemispheric advantage (accuracy, reaction times) for all groups, with a trend for early as compared to late bilinguals to be less accurate and taking longer in lexical decisions. These results show that the current words result in solid visual field differences, and do so irrespective of how many languages are spoken. While early bilinguals might experience a slight performance disadvantage, it was not affecting visual field differences.

Language Regression Associated With Autistic Regression and Electroencephalographic (EEG) Abnormalities: A Prospective Study.

We report a boy, referred at 25 months following a dramatic isolated language regression antedating autistic-like symptomatology. His sleep electroencephalogram (EEG) showed persistent focal epileptiform activity over the left parietal and vertex areas never associated with clinical seizures. He was started on adrenocorticotropic hormone (ACTH) with a significant improvement in language, behavior, and in EEG discharges in rapid eye movement (REM) sleep. Later course was characterized by fluctuations/regressions in language and behavior abilities, in phase with recrudescence of EEG abnormalities prompting additional ACTH courses that led to remarkable decrease in EEG abnormalities, improvement in language, and to a lesser degree, in autistic behavior. The timely documentation of regression episodes suggesting an "atypical" autistic regression, striking therapy-induced improvement, fluctuation of symptomatology over time could be ascribed to recurrent and persisting EEG abnormalities.

Neurophysiological origin of human brain asymmetry for speech and language.

The physiological basis of human cerebral asymmetry for language remains mysterious. We have used simultaneous physiological and anatomical measurements to investigate the issue. Concentrating on neural oscillatory activity in speech-specific frequency bands and exploring interactions between gestural (motor) and auditory-evoked activity, we find, in the absence of language-related processing, that left auditory, somatosensory, articulatory motor, and inferior parietal cortices show specific, lateralized, speech-related physiological properties. With the addition of ecologically valid audiovisual stimulation, activity in auditory cortex synchronizes with left-dominant input from the motor cortex at frequencies corresponding to syllabic, but not phonemic, speech rhythms. Our results support theories of language lateralization that posit a major role for intrinsic, hardwired perceptuomotor processing in syllabic parsing and are compatible both with the evolutionary view that speech arose from a combination of syllable-sized vocalizations and meaningful hand gestures and with developmental observations suggesting phonemic analysis is a developmentally acquired process.

Emotion, Affect, Sentiment: The Language and Aesthetics of Feeling

Bringing together experts from linguistics, medieval and modern literary studies, this volume offers a transhistorical look at the language and cultural work of emotion in a variety of written, oral and visual texts. Contributors engage with the recent so-called affective turn, but also examine the language and use of emotion from a variety of perspectives, touching on issues such as Romantic and Modernist aesthetics, the history of emotions, melodramatic and the Gothic, reception aesthetics, rudeness, and medicine.

Apprentissage automatique de la morphologie : le cas des structures racine-schème

RÉSUMÉ Cette thèse porte sur le développement de méthodes algorithmiques pour découvrir automatiquement la structure morphologique des mots d'un corpus. On considère en particulier le cas des langues s'approchant du type introflexionnel, comme l'arabe ou l'hébreu. La tradition linguistique décrit la morphologie de ces langues en termes d'unités discontinues : les racines consonantiques et les schèmes vocaliques. Ce genre de structure constitue un défi pour les systèmes actuels d'apprentissage automatique, qui opèrent généralement avec des unités continues. La stratégie adoptée ici consiste à traiter le problème comme une séquence de deux sous-problèmes. Le premier est d'ordre phonologique : il s'agit de diviser les symboles (phonèmes, lettres) du corpus en deux groupes correspondant autant que possible aux consonnes et voyelles phonétiques. Le second est de nature morphologique et repose sur les résultats du premier : il s'agit d'établir l'inventaire des racines et schèmes du corpus et de déterminer leurs règles de combinaison. On examine la portée et les limites d'une approche basée sur deux hypothèses : (i) la distinction entre consonnes et voyelles peut être inférée sur la base de leur tendance à alterner dans la chaîne parlée; (ii) les racines et les schèmes peuvent être identifiés respectivement aux séquences de consonnes et voyelles découvertes précédemment. L'algorithme proposé utilise une méthode purement distributionnelle pour partitionner les symboles du corpus. Puis il applique des principes analogiques pour identifier un ensemble de candidats sérieux au titre de racine ou de schème, et pour élargir progressivement cet ensemble. Cette extension est soumise à une procédure d'évaluation basée sur le principe de la longueur de description minimale, dans- l'esprit de LINGUISTICA (Goldsmith, 2001). L'algorithme est implémenté sous la forme d'un programme informatique nommé ARABICA, et évalué sur un corpus de noms arabes, du point de vue de sa capacité à décrire le système du pluriel. Cette étude montre que des structures linguistiques complexes peuvent être découvertes en ne faisant qu'un minimum d'hypothèses a priori sur les phénomènes considérés. Elle illustre la synergie possible entre des mécanismes d'apprentissage portant sur des niveaux de description linguistique distincts, et cherche à déterminer quand et pourquoi cette coopération échoue. Elle conclut que la tension entre l'universalité de la distinction consonnes-voyelles et la spécificité de la structuration racine-schème est cruciale pour expliquer les forces et les faiblesses d'une telle approche. ABSTRACT This dissertation is concerned with the development of algorithmic methods for the unsupervised learning of natural language morphology, using a symbolically transcribed wordlist. It focuses on the case of languages approaching the introflectional type, such as Arabic or Hebrew. The morphology of such languages is traditionally described in terms of discontinuous units: consonantal roots and vocalic patterns. Inferring this kind of structure is a challenging task for current unsupervised learning systems, which generally operate with continuous units. In this study, the problem of learning root-and-pattern morphology is divided into a phonological and a morphological subproblem. The phonological component of the analysis seeks to partition the symbols of a corpus (phonemes, letters) into two subsets that correspond well with the phonetic definition of consonants and vowels; building around this result, the morphological component attempts to establish the list of roots and patterns in the corpus, and to infer the rules that govern their combinations. We assess the extent to which this can be done on the basis of two hypotheses: (i) the distinction between consonants and vowels can be learned by observing their tendency to alternate in speech; (ii) roots and patterns can be identified as sequences of the previously discovered consonants and vowels respectively. The proposed algorithm uses a purely distributional method for partitioning symbols. Then it applies analogical principles to identify a preliminary set of reliable roots and patterns, and gradually enlarge it. This extension process is guided by an evaluation procedure based on the minimum description length principle, in line with the approach to morphological learning embodied in LINGUISTICA (Goldsmith, 2001). The algorithm is implemented as a computer program named ARABICA; it is evaluated with regard to its ability to account for the system of plural formation in a corpus of Arabic nouns. This thesis shows that complex linguistic structures can be discovered without recourse to a rich set of a priori hypotheses about the phenomena under consideration. It illustrates the possible synergy between learning mechanisms operating at distinct levels of linguistic description, and attempts to determine where and why such a cooperation fails. It concludes that the tension between the universality of the consonant-vowel distinction and the specificity of root-and-pattern structure is crucial for understanding the advantages and weaknesses of this approach.