Effect of levodopa on both verbal and motor representations of action in Parkinson's disease: a fMRI study.

Previous studies have demonstrated that non-demented Parkinson's disease (PD) patients have a specific impairment of verb production compared with noun generation. One interpretation of this deficit suggested the influence of striato-frontal dysfunction on action-related verb processing. The aim of our study was to investigate cerebral changes after motor improvement due to dopaminergic medication on the neural circuitry supporting action representation in the brain as mediated by verb generation and motor imagery in PD patients. Functional magnetic resonance imaging on 8 PD patients in "ON" dopaminergic treatment state (DTS) and in "OFF" DTS was used to explore the brain activity during three different tasks: Object Naming (ObjN), Generation of Action Verbs (GenA) in which patients were asked to overtly say an action associated with a picture and mental simulation of action (MSoA) was investigated by asking subjects to mentally simulate an action related to a depicted object. The distribution of brain activities associated with these tasks whatever DTS was very similar to results of previous studies. The results showed that brain activity related to semantics of action is modified by dopaminergic treatment in PD patients. This cerebral reorganisation concerns mainly motor and premotor cortex suggesting an involvement of the putaminal motor loop according to the "motor" theory of verb processing.

L'enseignement et l'apprentissage de la conjugaison en FLE : comment réduire les difficultés engendrées par l'orthographe ?

French verb morphology has always been a major challenge for learners as well as teachers of French as a foreign language. Learning difficulties arise not only from the inherent complexity of the conjugation system itself, but mostly from the traditional description found in specialized books, grammars, etc. French spelling alone tends to complexify the actual oral verb morphology by more than 60%, thus hindering efficient learning. Following Dubois (1967), Csécsy (1968), Pouradier Duteil (1997), etc., I suggest an alternative approach, exclusively based on phonetic transcription, and starting with plural forms instead of singular ones (Mayer 1969). For more than 500 verbs of the 2nd and 3rd groups, this strategy allows learners to first memorize the present tense plural form e.g. /illiz/ (ils lisent, "they read") and take the stem's final consonant away to get the singular /illi/ (il lit, "he reads").

Comparaison de la diversité et de la densité morphologiques dans trois types de données

This paper compares the inflectional diversity and density of adjectives and verbs in French CS, CDS, and ADS samples in a social perspective. The aim of the study is to show that the relation between CS, CDS, and ADS is not identical as far as verb and adjective inflection is concerned. We firstly expected verb inflectional morphology to be less diverse and dense in CDS and CS than in ADS. Conversely, we predicted adjective inflectional diversity and density to be higher in CDS and CS. Interestingly the findings do not exactly match the first prediction. The social implications of the study are discussed.

Textual autocorrelation : formalism and illustrations

Abstract Textual autocorrelation is a broad and pervasive concept, referring to the similarity between nearby textual units: lexical repetitions along consecutive sentences, semantic association between neighbouring lexemes, persistence of discourse types (narrative, descriptive, dialogal...) and so on. Textual autocorrelation can also be negative, as illustrated by alternating phonological or morpho-syntactic categories, or the succession of word lengths. This contribution proposes a general Markov formalism for textual navigation, and inspired by spatial statistics. The formalism can express well-known constructs in textual data analysis, such as term-document matrices, references and hyperlinks navigation, (web) information retrieval, and in particular textual autocorrelation, as measured by Moran's I relatively to the exchange matrix associated to neighbourhoods of various possible types. Four case studies (word lengths alternation, lexical repulsion, parts of speech autocorrelation, and semantic autocorrelation) illustrate the theory. In particular, one observes a short-range repulsion between nouns together with a short-range attraction between verbs, both at the lexical and semantic levels. Résumé: Le concept d'autocorrélation textuelle, fort vaste, réfère à la similarité entre unités textuelles voisines: répétitions lexicales entre phrases successives, association sémantique entre lexèmes voisins, persistance du type de discours (narratif, descriptif, dialogal...) et ainsi de suite. L'autocorrélation textuelle peut être également négative, comme l'illustrent l'alternance entre les catégories phonologiques ou morpho-syntaxiques, ou la succession des longueurs de mots. Cette contribution propose un formalisme markovien général pour la navigation textuelle, inspiré par la statistique spatiale. Le formalisme est capable d'exprimer des constructions bien connues en analyse des données textuelles, telles que les matrices termes-documents, les références et la navigation par hyperliens, la recherche documentaire sur internet, et, en particulier, l'autocorélation textuelle, telle que mesurée par le I de Moran relatif à une matrice d'échange associée à des voisinages de différents types possibles. Quatre cas d'étude illustrent la théorie: alternance des longueurs de mots, répulsion lexicale, autocorrélation des catégories morpho-syntaxiques et autocorrélation sémantique. On observe en particulier une répulsion à courte portée entre les noms, ainsi qu'une attraction à courte portée entre les verbes, tant au niveau lexical que sémantique.

Epistemological tensions between linguistic description and ordinary speakers' intuitive knowledge: examples from French verb morphology

In this article, I address epistemological questions regarding the status of linguistic rules and the pervasive--though seldom discussed--tension that arises between theory-driven object perception by linguists on the one hand, and ordinary speakers' possible intuitive knowledge on the other hand. Several issues will be discussed using examples from French verb morphology, based on the 6500 verbs from Le Petit Robert dictionary (2013).

Classification supervisée multi-étiquette en actes de dialogue: analyse discriminante et transformations de Schoenberg

Abstract This work studies the multi-label classification of turns in simple English Wikipedia talk pages into dialog acts. The treated dataset was created and multi-labeled by (Ferschke et al., 2012). The first part analyses dependences between labels, in order to examine the annotation coherence and to determine a classification method. Then, a multi-label classification is computed, after transforming the problem into binary relevance. Regarding features, whereas (Ferschke et al., 2012) use features such as uni-, bi-, and trigrams, time distance between turns or the indentation level of the turn, other features are considered here: lemmas, part-of-speech tags and the meaning of verbs (according to WordNet). The dataset authors applied approaches such as Naive Bayes or Support Vector Machines. The present paper proposes, as an alternative, to use Schoenberg transformations which, following the example of kernel methods, transform original Euclidean distances into other Euclidean distances, in a space of high dimensionality. Résumé Ce travail étudie la classification supervisée multi-étiquette en actes de dialogue des tours de parole des contributeurs aux pages de discussion de Simple English Wikipedia (Wikipédia en anglais simple). Le jeu de données considéré a été créé et multi-étiqueté par (Ferschke et al., 2012). Une première partie analyse les relations entre les étiquettes pour examiner la cohérence des annotations et pour déterminer une méthode de classification. Ensuite, une classification supervisée multi-étiquette est effectuée, après recodage binaire des étiquettes. Concernant les variables, alors que (Ferschke et al., 2012) utilisent des caractéristiques telles que les uni-, bi- et trigrammes, le temps entre les tours de parole ou l'indentation d'un tour de parole, d'autres descripteurs sont considérés ici : les lemmes, les catégories morphosyntaxiques et le sens des verbes (selon WordNet). Les auteurs du jeu de données ont employé des approches telles que le Naive Bayes ou les Séparateurs à Vastes Marges (SVM) pour la classification. Cet article propose, de façon alternative, d'utiliser et d'étendre l'analyse discriminante linéaire aux transformations de Schoenberg qui, à l'instar des méthodes à noyau, transforment les distances euclidiennes originales en d'autres distances euclidiennes, dans un espace de haute dimensionnalité.