NDLI: Three-Way (N-way) Fusion of Brain Imaging Data Based on mCCA+jICA and Its Application to Discriminating Schizophrenia

Content Provider	PubMed Central
Author	Sui, Jing He, Hao Pearlson, Godfrey D. Adali, Tülay Kiehl, Kent A. Yu, Qingbao Clark, Vince P. Castro, Eduardo White, Tonya Mueller, Bryon A. Ho, Beng C. Andreasen, Nancy C. Calhoun, Vince D.
Copyright Year	2012
Abstract	Multi-modal fusion is an effective approach to better understand brain diseases. However, most such instances have been limited to pair-wise fusion; because there are often more than two imaging modalities available per subject, there is a need for approaches that can combine multiple datasets optimally. In this paper, we extended our previous two-way fusion model called “multimodal CCA +joint ICA”, to three or N way fusion, that enables robust identification of correspondence among N data types and allows one to investigate the important question of whether certain disease risk factors are shared or distinct across multiple modalities. We compared “mCCA+jICA” with its alternatives in a 3-way fusion simulation and verified its advantages in both decomposition accuracy and modal linkage detection. We also applied it to real functional Magnetic Resonance Imaging (fMRI)-Diffusion Tensor Imaging (DTI) and structural MRI fusion to elucidate the abnormal architecture underlying schizophrenia (n=97) relative to healthy controls (n=116). Both modality-common and modality-unique abnormal regions were identified in schizophrenia. Specifically, the visual cortex in fMRI, the anterior thalamic radiation (ATR) and forceps minor in DTI, and the parietal lobule, cuneus and thalamus in sMRI were linked and discriminated between patients and controls. One fMRI component with regions of activity in motor cortex and superior temporal gyrus individually discriminated schizophrenia from controls. Finally, three components showed significant correlation with duration of illness (DOI), suggesting that lower gray matter volumes in parietal, frontal, temporal lobe and cerebellum are associated with increased DOI, along with white matter disruption in ATR and cortico-spinal tracts. Findings suggest that the identified fractional anisotropy changes may relate to the corresponding functional/structural changes in brain that are thought to play a role in the clinical expression of schizophrenia. The proposed “mCCA +jICA” method showed promise for elucidating the joint or coupled neuronal abnormalities underlying mental illnesses and improves our understanding of the disease process.
Related Links	http://dx.doi.org/10.1016/j.neuroimage.2012.10.051
Ending Page	132
Page Count	14
Starting Page	119
File Format	PDF
ISSN	10959572
e-ISSN	10959572
Journal	NeuroImage
Volume Number	0
Language	English
Publisher Date	2013-02-01
Access Restriction	Open
Subject Keyword	Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Neurology Cognitive Neuroscience

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