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Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI
Published on: November 27, 2019
Low entropy maps as patterns of the pathological alteration specificity of brain regions: A meta-analysis dataset
Donato Liloia1,2,3, Franco Cauda1,2,3, Andrea Nani1,2,3
1GCS-FMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.
Abstract:
The data presented in this article are related to the research article entitled "The alteration landscape of the cerebral cortex" (Cauda et al., 2018). Here, we applied a metric called alteration negentropy (A-negentropy) on a large human neuroimaging dataset, in order to denote the "low structural alteration variety" of the altered brain areas. Furthermore, we reported the overview of the selection strategy, as well as the description and distribution of the selected studies from the voxel-based morphometry database of BrainMap (Vanasse et al., 2018). For all of the analyzed brain areas, we reported the number of pathologies affecting them (both local maxima and mean value), as well as the peak and average values of A-negentropy. Regions altered by a small number of brain disorders exhibit high values of A-negentropy.
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