Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states

Arian Ashourvan, Preya Shah, Adam Pines, Shi Gu, Christopher W. Lynn, Danielle S. Bassett, Kathryn A. Davis, Brian Litt

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

A major challenge in neuroscience is determining a quantitative relationship between the brain’s white matter structural connectivity and emergent activity. We seek to uncover the intrinsic relationship among brain regions fundamental to their functional activity by constructing a pairwise maximum entropy model (MEM) of the inter-ictal activation patterns of five patients with medically refractory epilepsy over an average of ~14 hours of band-passed intracranial EEG (iEEG) recordings per patient. We find that the pairwise MEM accurately predicts iEEG electrodes’ activation patterns’ probability and their pairwise correlations. We demonstrate that the estimated pairwise MEM’s interaction weights predict structural connectivity and its strength over several frequencies significantly beyond what is expected based solely on sampled regions’ distance in most patients. Together, the pairwise MEM offers a framework for explaining iEEG functional connectivity and provides insight into how the brain’s structural connectome gives rise to large-scale activation patterns by promoting co-activation between connected structures.

Original languageEnglish (US)
Article number210
JournalCommunications Biology
Volume4
Issue number1
DOIs
StatePublished - Dec 2021

All Science Journal Classification (ASJC) codes

  • Medicine (miscellaneous)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

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