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Rapport (Rapport De Recherche) Année : 2017

Generating and reporting peak and cluster tables for voxel-wise inference in FSL

Résumé

Mass univariate analyses, in which a statistical test is performed at each voxel in the brain, is the most widespread approach to analyzing task-evoked functional Magnetic Resonance Imaging (fMRI) data. Such analyses identify the brain areas that are significantly activated in response to a given stimulus. In the literature, the significant areas are usually summarised by providing a table, listing, for each significant region, the 3D positions of the local maxima along with corresponding statistical values. This tabular output is provided by all the major as dsa dneuroimaging software packages including SPM, FSL and AFNI. Yet, in the HTML report generated by FSL, peak and cluster tables are only provided for one type of inference (cluster-wise inference) but not when a voxel-wise threshold is specified. In this project, we proposed an update for FSL to generate and report peak and cluster tables for voxel-wise inferences.
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Dates et versions

inserm-01565182 , version 1 (19-07-2017)

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Camille Maumet, Thomas Nichols. Generating and reporting peak and cluster tables for voxel-wise inference in FSL. Research Ideas and Outcomes. 2017. ⟨inserm-01565182⟩
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