Functional network connectivity during rest and task conditions: A comparative study

Mohammad R. Arbabshirani, Martin Havlicek, Kent A. Kiehl, Godfrey D. Pearlson, Vince D. Calhoun

Research output: Contribution to journalArticle

Abstract

Functional connectivity (FC) examines temporal statistical dependencies among distant brain regions by means of seed-based analysis or independent component analysis (ICA). Spatial ICA also makes it possible to investigate FC at the network level, termed functional network connectivity (FNC). The dynamics of each network (ICA component), which may consist of several remote regions is described by the ICA time-course of that network; hence, FNC studies statistical dependencies among ICA time-courses. In this article, we compare comprehensively FNC in the resting state and during performance of an auditory oddball (AOD) task in 28 healthy subjects on relevant (nonartifactual) brain networks. The results show global FNC decrease during the performance of the task. In addition, we show that specific networks enlarge and/or demonstrate higher activity during the performance of the task. The results suggest that performing an active task like AOD may be facilitated by recruiting more neurons and higher activation of related networks rather than collaboration among different brain networks. We also evaluated the impact of temporal filtering on FNC analyses. Results showed that the results are not significantly affected by filtering.

Original languageEnglish (US)
Pages (from-to)2959-2971
Number of pages13
JournalHuman Brain Mapping
Volume34
Issue number11
DOIs
StatePublished - Nov 1 2013
Externally publishedYes

Keywords

  • FMRI
  • Functional network connectivity
  • Independent component analysis

ASJC Scopus subject areas

  • Anatomy
  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Clinical Neurology

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