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Spatial entropy of brain network landscapes

Poster Session D - Monday, March 9, 2026, 8:00 – 10:00 am PDT, Fairview/Kitsilano Ballroom

Clayton McIntyre¹ (), Shannon O'Donnell¹, Mohammadreza Khodaei¹, Robert Lyday¹, Jonathan Burdette¹, Paul Laurienti¹; ¹Wake Forest University

We introduce a method for mapping the spatial entropy of functional brain network community structure images in brain space. Entropy maps indicate the extent to which the network communities present in a local area are ordered or disordered. We demonstrate how spatial entropy can be quantified for each voxel in the brain according to the network community affiliations of surrounding voxels. This process results in interpretable maps of brain network entropy. We show that regional entropy decreases in regions associated with the central executive network during 2-back working memory scans relative to resting-state scans. We also show that regional entropy decreases in the auditory cortex during music-listening scans relative to rest. We suggest that these regional entropy reductions reflect self-organization of neural processes in support of functionally localized cognitive tasks. Analyses in this work provide a framework for future analyses of spatial entropy in complex networks that can be mapped to Euclidean space – both within the brain and in other contexts.

Topic Area: METHODS: Neuroimaging