Background
Multivariate pattern analysis is an alternative method of analyzing functional magnetic
resonance imaging (fMRI) data, which is capable of decoding distributed neural representations.
We applied this method to test the hypothesis of the impairment in distributed representations
in schizophrenia. We also compared the results of this method with traditional general
linear model (GLM)-based univariate analysis.
Methods
Nineteen schizophrenia and 15 control subjects viewed two runs of stimuli—exemplars
of faces, scenes, objects, and scrambled images. To verify engagement with stimuli,
subjects completed a 1-back matching task. A multivoxel pattern classifier was trained
to identify category-specific activity patterns on one run of fMRI data. Classification
testing was conducted on the remaining run. Correlation of voxelwise activity across
runs evaluated variance over time in activity patterns.
Results
Patients performed the task less accurately. This group difference was reflected in
the pattern analysis results with diminished classification accuracy in patients compared
with control subjects, 59% and 72%, respectively. In contrast, there was no group
difference in GLM-based univariate measures. In both groups, classification accuracy
was significantly correlated with behavioral measures. Both groups showed highly significant
correlation between interrun correlations and classification accuracy.
Conclusions
Distributed representations of visual objects are impaired in schizophrenia. This
impairment is correlated with diminished task performance, suggesting that decreased
integrity of cortical activity patterns is reflected in impaired behavior. Comparisons
with univariate results suggest greater sensitivity of pattern analysis in detecting
group differences in neural activity and reduced likelihood of nonspecific factors
driving these results.
Key Words
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Article info
Publication history
Published online: September 29, 2008
Accepted:
July 24,
2008
Received in revised form:
July 7,
2008
Received:
December 19,
2007
Identification
Copyright
© 2008 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
