Difference between revisions of "TIBM: Brain connectivity"
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* 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 [https://icube-publis.unistra.fr/2-PROS13 2-PROS13]. | * 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 [https://icube-publis.unistra.fr/2-PROS13 2-PROS13]. | ||
− | Functional connectivity is | + | Functional connectivity is usually investigated via functional MRI sequences (fMRI). |
− | * A method of detecting functional networks from a brain multilevel | + | * A method of detecting functional networks from a brain multilevel parcellation into functionally homogeneous areas was proposed [https://icube-publis.unistra.fr/7-KFTF11 7-KFTF11]. |
+ | |||
* Tools from graph theory have also been implemented for the study of consciousness in comatose patients [https://icube-publis.unistra.fr/2-AKSR11 AKSR11-2], [https : //icube-publis.unistra.fr/2-ADVR12 2-ADVR12]. | * Tools from graph theory have also been implemented for the study of consciousness in comatose patients [https://icube-publis.unistra.fr/2-AKSR11 AKSR11-2], [https : //icube-publis.unistra.fr/2-ADVR12 2-ADVR12]. | ||
* New Work started on the analysis of the dynamics of functional connectivity, in particular on the interaction between brain networks scale to rest the subject. These networks are resting extracts analyzed by independent spatial components of fMRI data. The high number of components produced by subject, a method of automatic selection of the components of interest has been developed [4-https://icube-publis.unistra.fr/4-STRA15 STRA15]. In addition, approaches have been proposed to study the interactions of these networks from an analysis Hidden Markov Models product coupled, or the overall dynamic threshold coupled correlations between their time courses [https: / /icube-publis.unistra.fr/5-STRA15 5-STRA15], [4-https://icube-publis.unistra.fr/4-STAF16 STAF16]. | * New Work started on the analysis of the dynamics of functional connectivity, in particular on the interaction between brain networks scale to rest the subject. These networks are resting extracts analyzed by independent spatial components of fMRI data. The high number of components produced by subject, a method of automatic selection of the components of interest has been developed [4-https://icube-publis.unistra.fr/4-STRA15 STRA15]. In addition, approaches have been proposed to study the interactions of these networks from an analysis Hidden Markov Models product coupled, or the overall dynamic threshold coupled correlations between their time courses [https: / /icube-publis.unistra.fr/5-STRA15 5-STRA15], [4-https://icube-publis.unistra.fr/4-STAF16 STAF16]. |
Revision as of 17:55, 7 October 2016
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.
Functional connectivity is usually investigated via functional MRI sequences (fMRI).
L’étude de la connectivité anatomique et fonctionnelle cérébrale est l’une des problématiques majeures des neurosciences, avec pour objectif une meilleure compréhension de l’organisation et du fonctionnement cérébral, que ce soit chez les individus sains ou pathologiques. La connectivité anatomique est généralement étudiée grâce à des séquences d’IRMd.
La connectivité fonctionnelle est quant à elle généralement étudiée via des séquences d’IRM fonctionnelle (IRMf).
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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