Literature DB >> 23611864

Task-related concurrent but opposite modulations of overlapping functional networks as revealed by spatial ICA.

Jiansong Xu1, Sheng Zhang, Vince D Calhoun, John Monterosso, Chiang-Shan R Li, Patrick D Worhunsky, Michael Stevens, Godfrey D Pearlson, Marc N Potenza.   

Abstract

Animal studies indicate that different functional networks (FNs), each with a unique timecourse, may overlap at common brain regions. For understanding how different FNs overlap in the human brain and how the timecourses of overlapping FNs are modulated by cognitive tasks, we applied spatial independent component analysis (sICA) to functional magnetic resonance imaging (fMRI) data. These data were acquired from healthy participants while they performed a visual task with parametric loads of attention and working memory. sICA identified a total of 14 FNs, and they showed different extents of overlap at a majority of brain regions exhibiting any functional activity. More FNs overlapped at the higher-order association cortex including the anterior and posterior cingulate, precuneus, insula, and lateral and medial frontoparietal cortices (FPCs) than at the primary sensorimotor cortex. Furthermore, overlapping FNs exhibited concurrent but different task-related modulations of timecourses. FNs showing task-related up- vs. down-modulation of timecourses overlapped at both the lateral and medial FPCs and subcortical structures including the thalamus, striatum, and midbrain ventral tegmental area (VTA). Such task-related, concurrent, but opposite changes in timecourses in the same brain regions may not be detected by current analyses based on General-Linear-Model (GLM). The present findings indicate that multiple cognitive processes may associate with common brain regions and exhibit simultaneous but different modulations in timecourses during cognitive tasks.
Copyright © 2013 Elsevier Inc. All rights reserved.

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Year:  2013        PMID: 23611864      PMCID: PMC3677796          DOI: 10.1016/j.neuroimage.2013.04.038

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


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