Community structure and modularity in networks of correlated brain activity

Biology – Quantitative Biology – Neurons and Cognition

Scientific paper

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10 pages, 2 figs [v2:] arXiv identifier added explicitly in header (not automatically tagged to original PDF upload)

Scientific paper

We 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.

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