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Etude de la connectivité fonctionnelle dans les pathologies de mouvement de Parkinson et de Huntington en utilisant l’approche par graine et la théorie des graphes

Abstract : Functional magnetic resonance imaging (fMRI) is a technique that allows exploring neuronal activity using an endogenous contrast based on the oxygenation level of hemoglobin. This contrast is called BOLD (Blood oxygenated Level Dependent). It has been shown that fluctuations in the BOLD signal at rest, correlated in distant brain regions, defining long-distance brain functional networks. This is called functional connectivity. The latter represents the spontaneous activity of the brain and it is measured by fMRI at rest. Our research project has therefore combined a methodological aspect and two applications in the field of movement pathologies. In the first part of our project we studied data preprocessing strategies. The objective was to study the influence of the preprocessing steps and their order of application on the brain networks’ topology. We compared 12 different pretreatment strategies. In these strategies we applied the standard and most used techniques but with a different order of application. The following two studies used resting-state fMRI to study: Huntington's disease and Parkinson's disease. In these pathologies, we focused on the study of the brain networks addressed through the study of functional connectivity. We determined whether resting-state fMRI and graph theory measures were able to identify robust biomarkers of Huntington's disease progression in a longitudinal study. In the second study, we investigated the role of cholinergic basal nuclei of the forebrain and their connections in the onset of cognitive problems presented in Parkinson's disease. The seed-based analysis is a suitable method for this type of question.
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https://tel.archives-ouvertes.fr/tel-01803944
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Submitted on : Thursday, May 31, 2018 - 10:32:06 AM
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  • HAL Id : tel-01803944, version 1

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Fatma Gargouri. Etude de la connectivité fonctionnelle dans les pathologies de mouvement de Parkinson et de Huntington en utilisant l’approche par graine et la théorie des graphes. Neurosciences [q-bio.NC]. Université Pierre et Marie Curie - Paris VI, 2017. Français. ⟨NNT : 2017PA066487⟩. ⟨tel-01803944⟩

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