Community structure and modularity in networks of correlated brain activity

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dc.creatorSchwarz, Adam J.
dc.creatorGozzi, Alessandro
dc.creatorBifone, Angelo
dc.date2007-01-25
dc.date2007-01-30
dc.date.accessioned2026-07-07T07:43:41Z
dc.date.available2026-07-07T07:43:41Z
dc.descriptionWe present an approach to study functional segregation and integration in the living brain based on community structure decomposition determined by maximum modularity. We demonstrate this method with a network derived from functional imaging data with nodes defined by individual image pixels, and edges in terms of correlated signal changes. We found communities whose anatomical distributions correspond to biologically meaningful structures and include compelling functional subdivisions between anatomically equivalent brain regions.
dc.description10 pages, 2 figs [v2:] arXiv identifier added explicitly in header (not automatically tagged to original PDF upload)
dc.identifierhttps://arxiv.org/abs/q-bio/0701041
dc.identifierhttp://arxiv.org/abs/q-bio/0701041
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/122928
dc.subjectNeurons and Cognition
dc.titleCommunity structure and modularity in networks of correlated brain activity
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