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

Ashourvan et al. apply a pairwise maximum entropy model to intracranial EEG data from epileptic patients to infer structure-function relationships. Their results indicate that the pairwise MEM model provides insight into the structural connectivity of the brain and how it gives rise to activity patt...

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Main Authors: Arian Ashourvan, Preya Shah, Adam Pines, Shi Gu, Christopher W. Lynn, Danielle S. Bassett, Kathryn A. Davis, Brian Litt
Format: Article
Language:English
Published: Nature Portfolio 2021-02-01
Series:Communications Biology
Online Access:https://doi.org/10.1038/s42003-021-01700-6
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author Arian Ashourvan
Preya Shah
Adam Pines
Shi Gu
Christopher W. Lynn
Danielle S. Bassett
Kathryn A. Davis
Brian Litt
author_facet Arian Ashourvan
Preya Shah
Adam Pines
Shi Gu
Christopher W. Lynn
Danielle S. Bassett
Kathryn A. Davis
Brian Litt
author_sort Arian Ashourvan
collection DOAJ
description Ashourvan et al. apply a pairwise maximum entropy model to intracranial EEG data from epileptic patients to infer structure-function relationships. Their results indicate that the pairwise MEM model provides insight into the structural connectivity of the brain and how it gives rise to activity patterns.
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spelling doaj.art-2301190b8e5e43c093d3344655d94afa2022-12-21T20:28:34ZengNature PortfolioCommunications Biology2399-36422021-02-014111510.1038/s42003-021-01700-6Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation statesArian Ashourvan0Preya Shah1Adam Pines2Shi Gu3Christopher W. Lynn4Danielle S. Bassett5Kathryn A. Davis6Brian Litt7Department of Bioengineering, School of Engineering and Applied Science, University of PennsylvaniaDepartment of Bioengineering, School of Engineering and Applied Science, University of PennsylvaniaDepartment of Bioengineering, School of Engineering and Applied Science, University of PennsylvaniaDepartment of Computer Science and Engineering, University of Electronic Science and Technology of ChinaDepartment of Physics & Astronomy, School of Arts & Sciences, University of PennsylvaniaDepartment of Bioengineering, School of Engineering and Applied Science, University of PennsylvaniaDepartment of Bioengineering, School of Engineering and Applied Science, University of PennsylvaniaDepartment of Bioengineering, School of Engineering and Applied Science, University of PennsylvaniaAshourvan et al. apply a pairwise maximum entropy model to intracranial EEG data from epileptic patients to infer structure-function relationships. Their results indicate that the pairwise MEM model provides insight into the structural connectivity of the brain and how it gives rise to activity patterns.https://doi.org/10.1038/s42003-021-01700-6
spellingShingle Arian Ashourvan
Preya Shah
Adam Pines
Shi Gu
Christopher W. Lynn
Danielle S. Bassett
Kathryn A. Davis
Brian Litt
Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states
Communications Biology
title Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states
title_full Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states
title_fullStr Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states
title_full_unstemmed Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states
title_short Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states
title_sort pairwise maximum entropy model explains the role of white matter structure in shaping emergent co activation states
url https://doi.org/10.1038/s42003-021-01700-6
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