dorsal/arxiv
View SchemaCommunity structure and modularity in networks of correlated brain activity
| Authors | Adam J. Schwarz, Alessandro Gozzi, Angelo Bifone |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0701041 |
| URL | https://arxiv.org/abs/q-bio/0701041 |
Abstract
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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"date_created": "2026-03-02T18:01:35.411000Z",
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"record": {
"abstract": "We present an approach to study functional segregation and integration in the\nliving brain based on community structure decomposition determined by maximum\nmodularity. We demonstrate this method with a network derived from functional\nimaging data with nodes defined by individual image pixels, and edges in terms\nof correlated signal changes. We found communities whose anatomical\ndistributions correspond to biologically meaningful structures and include\ncompelling functional subdivisions between anatomically equivalent brain\nregions.",
"arxiv_id": "q-bio/0701041",
"authors": [
"Adam J. Schwarz",
"Alessandro Gozzi",
"Angelo Bifone"
],
"categories": [
"q-bio.NC"
],
"title": "Community structure and modularity in networks of correlated brain activity",
"url": "https://arxiv.org/abs/q-bio/0701041"
},
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