Identifying task-related brain functional states via cortical networks

Shiva Salsabilian, Li Zhu, Christian R. Lee, David J. Margolis, Laleh Najafizadeh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

A long standing goal of neuroscience studies has been to understand how brain functions are related to behavior. In this paper, we investigate changes in brain functional networks under two behavioral conditions (lick (L) and no-lick (NL)) across two frequency bands. Cortical activity in Thy1-GCaMP6s transgenic calcium reporter mice is recorded during L/NL activity experiments using widefield calcium imaging. We demonstrate how cortical connectivity can be used to identify behavior-related brain states. Connectivity links that significantly contribute to the network difference of L and NL behavioral conditions are spatially localized in two frequency bands. The effectiveness of cortical networks in predicting L and NL behavior are assessed using commonly-used classifiers. Results demonstrate that frequency-dependent cortical network analysis can be utilized to decode the brain states associated with behavior.

Original languageEnglish (US)
Title of host publication2020 IEEE International Symposium on Circuits and Systems, ISCAS 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728133201
StatePublished - 2020
Event52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020 - Virtual, Online
Duration: Oct 10 2020Oct 21 2020

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2020-October
ISSN (Print)0271-4310

Conference

Conference52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020
CityVirtual, Online
Period10/10/2010/21/20

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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