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Variational Variable Selection To Assess Experimental Condition Relevance In Event-Related fMRI

Christine Bakhous 1 Florence Forbes 1 Thomas Vincent 1 Michel Dojat 2 Philippe Ciuciu 3 
1 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology
3 PARIETAL - Modelling brain structure, function and variability based on high-field MRI data
NEUROSPIN - Service NEUROSPIN, Inria Saclay - Ile de France
Abstract : Brain functional exploration investigates the nature of neural processing following cognitive or sensory stimulation. This goal is not fully accounted for in most functional Magnetic Resonance Imaging (fMRI) analysis which usually assumes that all delivered stimuli possibly generate a BOLD response everywhere in the brain although activation is likely to be induced by only some of them in specific brain regions. Generally, criteria are not available to select the relevant conditions or stimulus types (e.g. visual, auditory, etc.) prior to activation detection and the inclusion of irrelevant events may degrade the results, particularly when the Hemodynamic Response Function (HRF) is jointly estimated. To face this issue, we propose an efficient variational procedure that automatically selects the conditions according to the brain activity they elicit. It follows an improved activation detection and local HRF estimation that we illustrate on synthetic and real fMRI data.
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Submitted on : Saturday, September 7, 2013 - 5:31:18 PM
Last modification on : Saturday, April 2, 2022 - 3:10:17 AM
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Christine Bakhous, Florence Forbes, Thomas Vincent, Michel Dojat, Philippe Ciuciu. Variational Variable Selection To Assess Experimental Condition Relevance In Event-Related fMRI. ISBI 2013 - 10th IEEE International Symposium on Biomedical Imaging, Apr 2013, San Francisco, United States. pp.1508-1511, ⟨10.1109/ISBI.2013.6556821⟩. ⟨hal-00859391⟩



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