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Edge-centric functional network representations of human cerebral cortex reveal overlapping system-level architecture

Joshua Faskowitz, Farnaz Zamani Esfahlani, Youngheun Jo, Olaf Sporns, Richard F. Betzel
doi: https://doi.org/10.1101/799924
Joshua Faskowitz
1Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405
2Program in Neuroscience, Indiana University, Bloomington, IN 47405
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Farnaz Zamani Esfahlani
1Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405
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Youngheun Jo
1Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405
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Olaf Sporns
1Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405
2Program in Neuroscience, Indiana University, Bloomington, IN 47405
3Cognitive Science Program, Indiana University, Bloomington, IN 47405
4Network Science Institute, Indiana University, Bloomington, IN 47405
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Richard F. Betzel
1Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405
2Program in Neuroscience, Indiana University, Bloomington, IN 47405
3Cognitive Science Program, Indiana University, Bloomington, IN 47405
4Network Science Institute, Indiana University, Bloomington, IN 47405
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  • For correspondence: rbetzel@indiana.edu
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Abstract

Network neuroscience has relied on a node-centric network model in which cells, populations, and regions are linked to one another via anatomical or functional connections. This model cannot account for interactions of edges with one another. Here, we develop an edge-centric network model, which generates the novel constructs of “edge time series” and “edge functional connectivity” (eFC). Using network analysis, we show that at rest eFC is consistent across datasets and reproducible within the same individual over multiple scan sessions. We demonstrate that clustering eFC yields communities of edges that naturally divide the brain into overlapping clusters, with regions in sensorimotor and attentional networks exhibiting the greatest levels of overlap. We go on to show that eFC is systematically and consistently modulated by variation in sensory input. In future work, the edge-centric approach could be used to map the connectional architecture of brain circuits and for the development of brain-based biomarkers of disease and development.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted October 13, 2019.
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Edge-centric functional network representations of human cerebral cortex reveal overlapping system-level architecture
Joshua Faskowitz, Farnaz Zamani Esfahlani, Youngheun Jo, Olaf Sporns, Richard F. Betzel
bioRxiv 799924; doi: https://doi.org/10.1101/799924
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Edge-centric functional network representations of human cerebral cortex reveal overlapping system-level architecture
Joshua Faskowitz, Farnaz Zamani Esfahlani, Youngheun Jo, Olaf Sporns, Richard F. Betzel
bioRxiv 799924; doi: https://doi.org/10.1101/799924

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