Journal
NEUROIMAGE
Volume 57, Issue 3, Pages 839-855Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2011.05.055
Keywords
Multimodal canonical correlation analysis (mCCA); Independent component analysis (ICA); Functional MRI (fMRI); Diffusion tensor imaging (DTI); Schizophrenia; Bipolar disorder; Fractional anisotropy (FA)
Funding
- National Institutes of Health [R01MH072681-01, R01EB 006841, R01EB 005846]
- DOE [DE-FG02-08ER64581]
- [R01MH43775]
- [R01MH074797]
- [R01MH077945]
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [1016619] Funding Source: National Science Foundation
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [1017718] Funding Source: National Science Foundation
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Diverse structural and functional brain alterations have been identified in both schizophrenia and bipolar disorder, but with variable replicability, significant overlap and often in limited number of subjects. In this paper, we aimed to clarify differences between bipolar disorder and schizophrenia by combining fMRI (collected during an auditory oddball task) and diffusion tensor imaging (DTI) data. We proposed a fusion method, multimodal CCA+ joint ICA, which increases flexibility in statistical assumptions beyond existing approaches and can achieve higher estimation accuracy. The data collected from 164 participants (62 healthy controls, 54 schizophrenia and 48 bipolar) were extracted into features (contrast maps for fMRI and fractional anisotropy (FA) for DTI) and analyzed in multiple facets to investigate the group differences for each pair-wised groups and each modality. Specifically, both patient groups shared significant dysfunction in dorsolateral prefrontal cortex and thalamus, as well as reduced white matter (WM) integrity in anterior thalamic radiation and uncinate fasciculus. Schizophrenia and bipolar subjects were separated by functional differences in medial frontal and visual cortex, as well as WM tracts associated with occipital and frontal lobes. Both patients and controls showed similar spatial distributions in motor and parietal regions, but exhibited significant variations in temporal lobe. Furthermore, there were different group trends for age effects on loading parameters in motor cortex and multiple WM regions, suggesting that brain dysfunction and WM disruptions occurred in identified regions for both disorders. Most importantly, we can visualize an underlying function structure network by evaluating the joint components with strong links between DTI and fMRI. Our findings suggest that although the two patient groups showed several distinct brain patterns from each other and healthy controls, they also shared common abnormalities in prefrontal thalamic WM integrity and in frontal brain mechanisms. (c) 2011 Elsevier Inc. All rights reserved.
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