Foundations for an ontology of brain areas, circuits and functions

International audienc

A propositional representation model of anatomical and functional brain data

A great number of natural systems can be represented by complex networks. Recent developments in the domain of complex networks have been translated to the neurosciences. The associated graph theoretical analysis of data provides a powerful framework to describe human brain structural and functional networks. In this work we propose a graph-based framework which is composed of: i) the definition of a propositional representation model of the anatomical and functional brain data and ii) the treatment of the embedded graph data by neurocomputational tools as a way to explore and visualize the graphs with the objective to enlarge anatomo-functional knowledge. The XML-based language GraphML is used for the representation of the data. The development of neurocomputational tools is doing with the software Gephi and the software Matlab. We will apply these framework and tools to a database belonging to the Center of Cognitive Anatomy (CAC) which provides neuropsychological data for patients presenting sequels of focal brain damage

Modélisation et outils logiciels pour une connaissance anatomo-fonctionnelle du Cerveau humain

Dans cette thèse, nous revisitons la méthode de la neuropsychologie définie comme l'étude des bases neurales des fonctions cognitives et comportementales par l'apport d'un modèle de représentation et d'organisation des données sur le cerveau et la création d'une base de données anatomo-fonctionnelles. Un Centre d'Anatomie Cognitive (C.A.C.) a été constitué afin de permettre le recueil et le traitement des données chez des patients présentant des lésions cérébrales. Des logiciels de mise en relation et de fusion des données anatomiques et fonctionnelles, ont été développés afin de produire des connaissances anatomo-fonctionnelles, notamment sous forme de règles anatomo-fonctionnelles. Nous décrivons les résultats des traitements appliqués à la base de données ; l'objectif étant de proposer aux experts une mise en perspective d 'utilisation du système informatique, montrant que des traitements appropriés sur des données modélisées de façon complexe constituent un outil de recherche. L'objectif général de cette thèse est de proposer un référentiel anatomo-fonctionnel pour aider à la compréhension du fonctionnement cérébral normal et pathologiqueLYON1-BU.Sciences (692662101) / SudocSudocFranceF

A core ontology of instruments used for neurological, behavioral and cognitive assessments

International audienceNeurosciences are progressively moving into a mass computational intensive era with the fusion of numerous large heterogeneous data sets from cellular to system level. To process and share this mass of information in a consistent and computational amenable form, computerized techniques – among them, ontologies - are currently designed to store, analyze and access this information. Recently, we proposed a multi-layered and multi-components ontology to deal with MR images and regions-of-interest that can be represented onto the images. In the present paper, we extend our initial ontology by adding a core ontology of subject data acquisition instruments modeling neuroclinical, neuropsychological and neurobehavioral tests used for neurological, behavioral and cognitive skills assessment. This ontology deals with instruments per se as specific artefacts, their variables and measured scores, and actions performed using instruments. In the paper, we underline the major aspects of our approach and emphasize its potential interest as a semantic reference for various neuroscience applications

Vers une Ontologie Anatomo-Fonctionnelle du Cerveau

National audienc

A Multilayer Ontology of Instruments for Neurological, Behavioral and Cognitive Assessments.

International audience: Advances in neuroscience are underpinned by large, multicenter studies and a mass of heterogeneous datasets. When investigating the relationships between brain anatomy and brain functions under normal and pathological conditions, measurements obtained from a broad range of brain imaging techniques are correlated with the information on each subject's neurologic states, cognitive assessments and behavioral scores derived from questionnaires and tests. The development of ontologies in neuroscience appears to be a valuable way of gathering and handling properly these heterogeneous data - particularly through the use of federated architectures. We recently proposed a multilayer ontology for sharing brain images and regions of interest in neuroimaging. Here, we report on an extension of this ontology to the representation of instruments used to assess brain and cognitive functions and behavior in humans. This extension consists of a 'core' ontology that accounts for the properties shared by all instruments supplemented by 'domain' ontologies that conceptualize standard instruments. We also specify how this core ontology has been refined to build domain ontologies dedicated to widely used instruments and how various scores used in the neurosciences are represented. Lastly, we discuss our design choices, the ontology's limitations and planned extensions aimed at querying and reasoning across distributed data sources

ECOCAPTURE@HOME: Protocol for the Remote Assessment of Apathy and Its Everyday-Life Consequences

International audienceApathy, a common neuropsychiatric symptom associated with dementia, has a strong impact on patients’ and caregivers’ quality of life. However, it is still poorly understood and hard to define. The main objective of the ECOCAPTURE programme is to define a behavioural signature of apathy using an ecological approach. Within this program, ECOCAPTURE@HOME is an observational study which aims to validate a method based on new technologies for the remote monitoring of apathy in real life. For this study, we plan to recruit 60 couples: 20 patient-caregiver dyads in which patients suffer from behavioral variant Fronto-Temporal Dementia, 20 patient-caregiver dyads in which patients suffer from Alzheimer Disease and 20 healthy control couples. These dyads will be followed for 28 consecutive days via multi-sensor bracelets collecting passive data (acceleration, electrodermal activity, blood volume pulse). Active data will also be collected by questionnaires on a smartphone application. Using a pool of metrics extracted from these passive and active data, we will validate a measurement model for three behavioural markers of apathy (i.e., daytime activity, quality of sleep, and emotional arousal). The final purpose is to facilitate the follow-up and precise diagnosis of apathy, towards a personalised treatment of this condition within everyday life