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. 2015 Nov;41(6):1360-9.
doi: 10.1093/schbul/sbv013. Epub 2015 Mar 1.

Cognitive Effort and Schizophrenia Modulate Large-Scale Functional Brain Connectivity

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Free PMC article

Cognitive Effort and Schizophrenia Modulate Large-Scale Functional Brain Connectivity

Christine Lycke Brandt et al. Schizophr Bull. .
Free PMC article

Abstract

Schizophrenia (SZ) is characterized by cognitive dysfunction and disorganized thought, in addition to hallucinations and delusions, and is regarded a disorder of brain connectivity. Recent efforts have been made to characterize the underlying brain network organization and interactions. However, to which degree connectivity alterations in SZ vary across different levels of cognitive effort is unknown. Utilizing independent component analysis (ICA) and methods for delineating functional connectivity measures from functional magnetic resonance imaging (fMRI) data, we investigated the effects of cognitive effort, SZ and their interactions on between-network functional connectivity during 2 levels of cognitive load in a large and well-characterized sample of SZ patients (n = 99) and healthy individuals (n = 143). Cognitive load influenced a majority of the functional connections, including but not limited to fronto-parietal and default-mode networks, reflecting both decreases and increases in between-network synchronization. Reduced connectivity in SZ was identified in 2 large-scale functional connections across load conditions, with a particular involvement of an insular network. The results document an important role of interactions between insular, default-mode, and visual networks in SZ pathophysiology. The interplay between brain networks was robustly modulated by cognitive effort, but the reduced functional connectivity in SZ, primarily related to an insular network, was independent of cognitive load, indicating a relatively general brain network-level dysfunction.

Keywords: brain networks; cognition; independent component analysis; psychotic disorders.

Figures

Fig. 1.
Fig. 1.
Functional networks (components) included in the analyses: Bilateral fronto-parietal network (FP; 1), default-mode network (DMN; 2), visual network (VIS2; 3), motor network (MOT; 4), visual network (VIS1; 5), insula network (INS; 6), left fronto-parietal network (LFP; 7).
Fig. 2.
Fig. 2.
Effects of load, diagnosis, and their interactions on functional connectivity as revealed by (A) main analysis based on entire time series; (B) additional analyses based on residuals and experimental on-blocks only, yielding converging results across approaches. Numbers represent network numbers: (1) FP, (2) DMN, (3) VIS2, (4) MOT, (5) VIS1, (6) INS, and (7) LFP. Colors represent effect sizes (partial eta squared) for significant (P < .05, Bonferroni) correlations, where warm/cold colors represent increasing/decreasing connectivity, respectively, with increasing load. White dots show trend effects (nominal P < .05). Effects above the diagonal are based on partial correlations, while effects below the diagonal are based on full correlations.
Fig. 3.
Fig. 3.
Mean connectivity (z-scores) and standard errors within task conditions for each group in functional connections (correlations) showing effects of diagnosis in the main analysis.

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