TY - JOUR
T1 - Spatial Variance in Resting fMRI Networks of Schizophrenia Patients
T2 - An Independent Vector Analysis
AU - Gopal, Shruti
AU - Miller, Robyn L.
AU - Michael, Andrew
AU - Adali, Tulay
AU - Cetin, Mustafa
AU - Rachakonda, Srinivas
AU - Bustillo, Juan R.
AU - Cahill, Nathan
AU - Baum, Stefi A.
AU - Calhoun, Vince D.
N1 - Funding Information:
Supplementary material is available at http://schizophreniabulletin. oxfordjournals.org. The references "[a]--[o]", cited in the text refers to the bibliography data provided in the supplementary material. National Institutes of Health''s Center of Biomedical Research Excellence (5P20GM103472); National Science Foundation''s Information and Intelligent Systems (1017718); Computing and Communication Foundations (1117056).
Publisher Copyright:
© 2015 The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.
PY - 2016/1/1
Y1 - 2016/1/1
N2 - 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.
AB - 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.
KW - IVA
KW - resting fMRI
KW - schizophrenia
KW - spatial variability
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U2 - 10.1093/schbul/sbv085
DO - 10.1093/schbul/sbv085
M3 - Article
C2 - 26106217
AN - SCOPUS:84954348735
SN - 0586-7614
VL - 42
SP - 152
EP - 160
JO - Schizophrenia bulletin
JF - Schizophrenia bulletin
IS - 1
ER -