Literature DB >> 28549798

Whole-brain connectivity dynamics reflect both task-specific and individual-specific modulation: A multitask study.

Hua Xie1, Vince D Calhoun2, Javier Gonzalez-Castillo3, Eswar Damaraju2, Robyn Miller4, Peter A Bandettini5, Sunanda Mitra6.   

Abstract

Functional connectivity (FC) has been widely used to study the functional organization of temporally correlated and spatially distributed brain regions. Recent studies of FC dynamics, quantified by windowed correlations, provide new insights to analyze dynamic, context-dependent reconfiguration of brain networks. A set of reoccurring whole-brain connectivity patterns at rest, referred to as FC states, have been identified, hypothetically reflecting underlying cognitive processes or mental states. We posit that the mean FC information for a given subject represents a significant contribution to the group-level FC dynamics. We show that the subject-specific FC profile, termed as FC individuality, can be removed to increase sensitivity to cognitively relevant FC states. To assess the impact of the FC individuality and task-specific FC modulation on the group-level FC dynamics analysis, we generate and analyze group studies of four subjects engaging in four cognitive conditions (rest, simple math, two-back memory, and visual attention task). We also propose a model to quantitatively evaluate the effect of two factors, namely, subject-specific and task-specific modulation on FC dynamics. We show that FC individuality is a predominant factor in group-level FC variability, and the embedded cognitively relevant FC states are clearly visible after removing the individual's connectivity profile. Our results challenge the current understanding of FC states and emphasize the importance of individual heterogeneity in connectivity dynamics analysis.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cognitively relevant FC state; Connectivity dynamics; FC individuality

Mesh:

Year:  2017        PMID: 28549798      PMCID: PMC5700856          DOI: 10.1016/j.neuroimage.2017.05.050

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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