Multi-session extension of the joint-detection framework in fMRI

Solveig Badillo 1, 2 Thomas Vincent 3, * Philippe Ciuciu 2, 4
* Auteur correspondant
3 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : Modern cognitive experiments in functional Magnetic Resonance Imaging (fMRI) involve the repetition of the same paradigm over several short sessions (or runs) since long fMRI acquisitions usually place the subject in an uncomfortable situation and generate motion artifacts. Also, shorter sessions enable to better control the subject's cognitive state and guarantee his attention during task. The Joint Detection-Estimation (JDE) framework which aims at detecting evoked activity and estimating hemodynamic responses jointly, has been developed so far to treat each session independently and then build average contrasts of interest as already done in other packages (SPM, FSL). Here, we extend JDE to the multi-session context by proposing a new hierarchical Bayesian modeling including an additional layer to describe the link between session-specific and mean evoked activity. In contrast, the HRF shape to be estimated in each region is assumed constant across sessions. Our results on simulated and real multi-session datasets show that the proposed extension outperforms its ancestor both in terms of activated areas and HRF recovery.
Type de document :
Communication dans un congrès
ISBI 2013 - International Symposium on BIomedical Imaging: From Nano to Macro, Apr 2013, San Fransisco, United States. IEEE, pp.1512-1515, 2013, <10.1109/ISBI.2013.6556822>
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https://hal.inria.fr/hal-00854624
Contributeur : Solveig Badillo <>
Soumis le : lundi 2 septembre 2013 - 21:02:53
Dernière modification le : jeudi 9 février 2017 - 15:47:44
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Solveig Badillo, Thomas Vincent, Philippe Ciuciu. Multi-session extension of the joint-detection framework in fMRI. ISBI 2013 - International Symposium on BIomedical Imaging: From Nano to Macro, Apr 2013, San Fransisco, United States. IEEE, pp.1512-1515, 2013, <10.1109/ISBI.2013.6556822>. <hal-00854624>

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