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Spatial Variance in Resting fMRI Networks of Schizophrenia Patients: An Independent Vector Analysis

Spatial variability in resting functional MRI (fMRI) brain networks has not been well studied in schizophrenia, a disease known for both neurodevelopmental and widespread anatomic changes. Motivated by abundant evidence of neuroanatomical variability from previous studies of schizophrenia, we draw u...

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Published in:Schizophrenia bulletin 2016-01, Vol.42 (1), p.152-160
Main Authors: Gopal, Shruti, Miller, Robyn L, Michael, Andrew, Adali, Tulay, Cetin, Mustafa, Rachakonda, Srinivas, Bustillo, Juan R, Cahill, Nathan, Baum, Stefi A, Calhoun, Vince D
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container_title Schizophrenia bulletin
container_volume 42
creator Gopal, Shruti
Miller, Robyn L
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Rachakonda, Srinivas
Bustillo, Juan R
Cahill, Nathan
Baum, Stefi A
Calhoun, Vince D
description Spatial variability in resting functional MRI (fMRI) brain networks has not been well studied in schizophrenia, a disease known for both neurodevelopmental and widespread anatomic changes. Motivated by abundant evidence of neuroanatomical variability from previous studies of schizophrenia, we draw upon a relatively new approach called independent vector analysis (IVA) to assess this variability in resting fMRI networks. IVA is a blind-source separation algorithm, which segregates fMRI data into temporally coherent but spatially independent networks and has been shown to be especially good at capturing spatial variability among subjects in the extracted networks. We introduce several new ways to quantify differences in variability of IVA-derived networks between schizophrenia patients (SZs = 82) and healthy controls (HCs = 89). Voxelwise amplitude analyses showed significant group differences in the spatial maps of auditory cortex, the basal ganglia, the sensorimotor network, and visual cortex. Tests for differences (HC-SZ) in the spatial variability maps suggest, that at rest, SZs exhibit more activity within externally focused sensory and integrative network and less activity in the default mode network thought to be related to internal reflection. Additionally, tests for difference of variance between groups further emphasize that SZs exhibit greater network variability. These results, consistent with our prediction of increased spatial variability within SZs, enhance our understanding of the disease and suggest that it is not just the amplitude of connectivity that is different in schizophrenia, but also the consistency in spatial connectivity patterns across subjects.
doi_str_mv 10.1093/schbul/sbv085
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source PubMed; Oxford Journals Online
subjects Adolescent
Adult
Aged
Algorithms
Auditory Cortex - physiopathology
Basal Ganglia - physiopathology
Brain - physiopathology
Brain Mapping
Case-Control Studies
Female
Functional Neuroimaging
Humans
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Male
Middle Aged
Neural Pathways - physiopathology
Psychotic Disorders - physiopathology
Regular
Schizophrenia - physiopathology
Sensorimotor Cortex - physiopathology
Visual Cortex - physiopathology
Young Adult
title Spatial Variance in Resting fMRI Networks of Schizophrenia Patients: An Independent Vector Analysis
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