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Brain Dynamics Through the Lens of Statistical Mechanics by Unifying Structure and Function

  • Igor Fortel
  • Mitchell Butler
  • Laura E. Korthauer
  • Liang Zhan
  • Olusola Ajilore
  • Ira Driscoll
  • Anastasios Sidiropoulos
  • Yanfu Zhang
  • Lei Guo
  • Heng Huang
  • Dan Schonfeld
  • Alex LeowEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11768)

Abstract

This paper introduces a novel method that unifies structural connectivity and functional time series to form a signed coupling interaction network or “signed resting state structural connectome” (signed rs-SC) to describe neural excitation and inhibition. We employ an energy representation of neural activity based on the Ising model from statistical mechanics, hereby bypassing traditional BOLD correlations. The spin model is a function of a coupling interaction (traditionally positive or negative) and spin-states of paired brain regions. Observed functional time series represent brain states over time. A maximum pseudolikelihood with a constraint is used to estimate the coupling interaction. The constraint is introduced as a penalty function such that the learned interactions are scaled relative to structural connectivity; the sign of the interactions may infer inhibition or excitation over an underlying structure. We evaluate our method by comparing a group of otherwise healthy APOE-e4 carriers with a control group of non APOE-e4 subjects. Our results identify a global shift in the excitation-inhibition balance of the APOE e4 signed rs-SC compared to the control group, providing the first connectomics-based support for hyperexcitation related to APOE e4.

Keywords

Ising model Maximum Likelihood Brain dynamics Functional connectivity Structure connectome MRI 

Notes

Acknowledgements

This study is funded in part by NIA AG056782 and NSF-IIS 1837956.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Igor Fortel
    • 1
  • Mitchell Butler
    • 1
  • Laura E. Korthauer
    • 2
    • 4
  • Liang Zhan
    • 3
  • Olusola Ajilore
    • 1
  • Ira Driscoll
    • 2
  • Anastasios Sidiropoulos
    • 1
  • Yanfu Zhang
    • 3
  • Lei Guo
    • 3
  • Heng Huang
    • 3
  • Dan Schonfeld
    • 1
  • Alex Leow
    • 1
    Email author
  1. 1.University of Illinois at ChicagoChicagoUSA
  2. 2.University of Wisconsin-MilwaukeeMilwaukeeUSA
  3. 3.University of PittsburghPittsburghUSA
  4. 4.Alpert Medical School of Brown UniversityProvidenceUSA

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