Marqueurs discursifs de neurodégénérescence liée à la pathologie Alzheimer

La maladie d’Alzheimer (MA) et les aphasies progressives primaires (APP) s’accompagnent de perturbations du langage expressif parfois subtiles, mais précoces dans l’évolution de ces maladies neurodégénératives. Considérés dans une approche automatisée, ces changements pourraient constituer des marqueurs de dégénérescence identifiés de façon non invasive et peu onéreuse. À ce titre, ils font l’objet d’études visant à automatiser leur utilisation clinique. Cependant, l’intégration des marqueurs langagiers à une approche diagnostique centrée sur les biomarqueurs reste à faire. À cette fin, la présente thèse a deux objectifs. D’abord, recenser systématiquement les marqueurs du discours qui distinguent le mieux les personnes avec une MA de témoins en santé. Ensuite, appliquer une approche automatisée et à un large éventail de marqueurs de discours pour identifier, dans un groupe hétérogène de patients avec une APP, lesquels ont une pathologie Alzheimer sous-jacente. Afin de mettre en contexte ces deux objectifs, nous proposons une introduction générale comprenant les éléments suivants : la pathophysiologie de la MA et des APP, le rôle croissant des biomarqueurs dans la prise de décision clinique dans les maladies neurodégénératives, les études pionnières du discours en neurodégénérescence, ainsi que de récentes études computationnelles sur les marqueurs de discours dans la MA et les APP. Nos résultats font émerger un patron multidimensionnel (acoustique, lexical, syntaxique, sémantique et pragmatique) de changements langagiers qui distinguent les personnes avec une MA de témoins en santé, avec une prépondérance des marqueurs lexicosémantiques. Dans le groupe de patients avec une APP avec une imagerie amyloïde positive ou négative, nous mesurons ensuite le pouvoir de classification d’un court échantillon de discours et montrons qu’il peut être avantageusement comparé à d’autres biomarqueurs. Nous discutons du patron spécifique de marqueurs discriminants pour ce sous-groupe de patients, notamment l’importance des marqueurs psycholinguistiques pour prédire le résultat de l’imagerie amyloïde à partir du discours.Alzheimer’s disease (AD) and primary progressive aphasias (PPA) feature changes in expressive language that appear early in the course of the disease. Within an automated analysis framework, these language changes could offer a non-invasive and inexpensive alternative to the collection of biomarkers which are not readily available in most settings. Current research is thus focused on the automated analysis of language data for clinical use. The usefulness of connected speech (CS) markers has not yet been established in a diagnostic perspective focused on biomarkers. To this aim, the present thesis contains two phases. First, we systematically review the CS markers that best differentiate persons with AD from healthy controls. Second, we automatically extract a wide array of CS markers in a heterogenous group of PPA patients by combining expert knowledge and the latest natural language processing software. A machine-learning classification approach identifies PPA patients for the presence of underlying AD pathology. The most discriminant CS features are identified. To integrate the two phases of the thesis, we provide a general introduction with the following sections: the pathophysiology of AD and PPAs, the growing importance of biomarkers in clinical decision-making for neurodegenerative diseases, the seminal studies of CS in neurodegenerative diseases, and the latest computational studies of CS markers in AD and PPA. Our results bring forth a multidimensional pattern (acoustic, lexical, syntactic, semantic, pragmatic) of language changes that distinguish people with AD from healthy controls, with an emphasis on lexical-semantic features. In the group of PPA patients with either positive or negative amyloid imaging, we then describe the classificatory power of a short sample of CS and show that it compares favorably to other biomarkers. We discuss the specific pattern of discriminant markers for this subgroup of patients, in particular the role of psycholinguistics

Connected speech features from picture description in Alzheimer's disease: a systematic review

The language changes that occur over the course of Alzheimer’s disease (AD) can impact communication abilities and have profound functional consequences. Picture description tasks can be used to approximate everyday communication abilities of AD patients. As various methods and variables have been studied over the years, current knowledge about the most affected features of AD discourse in the context of picture descriptions is difficult to summarize. This systematic review aims to provide researchers with an overview of the most common areas of impairment in AD discourse as they appear in picture description tasks. Based on the 44 articles fulfilling inclusion criteria, our findings reflect a multidimensional pattern of changes in the production (speech rate), syntactic (length of utterance), lexical (word-frequency and use of pronouns), fluency (repetitions and word-finding difficulties), semantic (information units), and discourse (efficiency) domains. We discuss our findings in the light of current research and point to potential scientific and clinical uses of picture description tasks in the context of AD

Cross-sectional analysis of picture descriptions of healthy young and older adults

It is poorly understood whether and how normal aging affects different aspects of connected speech production, such as fluency, informativity, efficiency, and vocabulary use. The present study crosssectionally investigates the effects of age on a broad variety of language production measures, using connected speech samples elicited by the two most frequently used picture description tasks. Twenty-six young (20-25 y.o.) and twenty-two older participants (55-90 y.o.) were included in this study. Speech samples were transcribed using the CLAN program and eight measures were extracted. Our results indicate that, in a picture description task, older adults produce more disruptions to fluency, but that lexical diversity, informativity, and efficiency of speech remain unaffected by age. The use of less frequent words by older adults might reflect a larger vocabulary size. These findings have implications for future studies assessing changes in connected speech production, in both healthy and clinical populations.Le vieillissement normal module certaines habiletés cognitives, mais on ne sait pas si, et de quelle manière, différents aspects de la production du discours continu, tels que la fluence, l’informativité, l’efficacité et l’utilisation du vocabulaire, sont affectés. La présente étude transversale examine les effets de l’âge sur plusieurs mesures langagières à partir d’échantillons de discours continu suscités par les deux tâches de description d’image les plus utilisées. Vingt-six jeunes (20-25 ans) et vingt-deux participants âgés (55-90 ans) ont été recrutés. Les échantillons ont été transcrits via le programme CLAN et huit mesures ont été extraites. Nos résultats indiquent que les adultes plus âgés produisent plus de bris de fluidité verbale, mais que la diversité lexicale, l’informativité et l’efficacité du langage ne sont pas affectées par l’âge. L’usage de mots moins fréquents par les adultes plus âgés pourrait refléter un vocabulaire plus étendu. Ces résultats ont des implications pour les études futures portant sur les changements dans la production de discours continu chez les populations saines et cliniques

Connected speech markers of amyloid burden in primary progressive aphasia

INTRODUCTION Positron emission tomography (PET) amyloid imaging has become an important part of the diagnostic workup for patients with primary progressive aphasia (PPA) and uncertain underlying pathology. Here, we employ a semi-automated analysis of connected speech (CS) with a twofold objective. First, to determine if quantitative CS features can help select primary progressive aphasia (PPA) patients with a higher probability of a positive PET amyloid imaging result. Second, to examine the relevant group differences from a clinical perspective. METHODS 117 CS samples from a well-characterised cohort of PPA patients who underwent PET amyloid imaging were collected. Expert consensus established PET amyloid status for each patient, and 40% of the sample was amyloid positive. RESULTS Leave-one-out cross-validation yields 77% classification accuracy (sensitivity: 74%, specificity: 79%). DISCUSSION Our results confirm the potential of CS analysis as a screening tool. Discriminant CS features from lexical, syntactic, pragmatic, and semantic domains are discussed

Spared speech fluency is associated with increased functional connectivity in the speech production network in semantic variant primary progressive aphasia

Semantic variant primary progressive aphasia is a clinical syndrome characterized by marked semantic deficits, anterior temporal lobe atrophy and reduced connectivity within a distributed set of regions belonging to the functional network associated with semantic processing. However, to fully depict the clinical signature of semantic variant primary progressive aphasia, it is necessary to also characterize preserved neural networks and linguistic abilities, such as those subserving speech production. In this case-control observational study, we employed whole-brain seed-based connectivity on task-free MRI data of 32 semantic variant primary progressive aphasia patients and 46 healthy controls to investigate the functional connectivity of the speech production network and its relationship with the underlying grey matter. We investigated brain-behaviour correlations with speech fluency measures collected through clinical tests (verbal agility) and connected speech (speech rate and articulation rate). As a control network, we also investigated functional connectivity within the affected semantic network. Patients presented with increased connectivity in the speech production network between left inferior frontal and supramarginal regions, independent of underlying grey matter volume. In semantic variant primary progressive aphasia patients, preserved (verbal agility) and increased (articulation rate) speech fluency measures correlated with increased connectivity between inferior frontal and supramarginal regions. As expected, patients demonstrated decreased functional connectivity in the semantic network (dependent on the underlying grey matter atrophy) associated with average nouns' age of acquisition during connected speech. Collectively, these results provide a compelling model for studying compensation mechanisms in response to disease that might inform the design of future rehabilitation strategies in semantic variant primary progressive aphasia