TIBM: Brain connectivity

The study of brain anatomical and functional connectivity is one of the major issues of neuroscience, aiming at better understanding the organization and functioning of the brain, whether in healthy or diseased individuals. Anatomical connectivity is generally studied with diffusion MRI sequences. A new method of tractography based on particle filtering and using the Q-ball model was developed to extract the main fiber bundles of the white matter 2-PROS13. Functional connectivity is usually investigated via functional MRI sequences (fMRI). A method of detecting functional networks from a brain multilevel parcellation into functionally homogeneous areas was proposed 7-KFTF11. Tools from graph theory have also been implemented for the study of consciousness in comatose patients AKSR11-2, 2-ADVR12. New work started on the analysis of the dynamics of functional connectivity, in particular on the interaction between brain resting state networks at the scale of the subject. These resting state networks are extracted using spatial independent component analysis of fMRI data. To cope with the high number of components produced for each subject, a method for the automatic selection of the components of interest has been developed 4-STRA15. In addition, approaches have been proposed to study the interactions of these networks using different Hidden Markov Models 5-STRA15, 4-STAF16.

PhD thesis

• M. Sourty, Analyse de la dynamique temporelle et spatiale des réseaux cérébraux spontanés obtenus en imagerie par résonance magnétique fonctionnelle IRMf, septembre 2016
• J. Pontabry, Construction d'atlas en IRM de diffusion : application à l'étude de la maturation cérébrale, octobre 2013
• F. Renard, Création et utilisation d'atlas en IRM de diffusion. Application à l'étude des troubles de la conscience, septembre 2011
• S. Karkar, Parcellisation et analyse multi-niveaux de données IRM fonctionnelles - application à l'étude des réseaux de connectivité cérébrale, juin 2011
• S. Faisan, Analyse et fusion markovienne de séquences en imagerie 3D+t. Application à l'analyse de séquences d'images IRM fonctionnelles cérébrales., décembre 2004

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