C-ICT for Discovery of Multiple Associations in Multimodal Imaging Data: Application to Fusion of fMRI and DTI Data

Chunying Jia, Mohammad A.B.S. Akhonda, Qunfang Long, Vince Daniel Calhoun, Shari Waldstein, Tulay Adali

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Fusing datasets from different brain signal modalities improves accuracy in finding biomarkers of neuropsychiatric diseases. Several approaches, such as joint independent component analysis (ICA) and independent vector analysis (IVA), are useful but fall short of exploring multiple associations between different modalities, especially for the case where one underlying component in one modality might have multiple associations with others in another modality. This relationship is possible since one component in a given modality might have associations such as subject covariation with multiple components in another modality. We show that the consecutive independence and correlation transform (C-ICT) model, which successively performs ICA and canonical correlation analysis, is able to discover such multiple associations. C-ICT has been demonstrated to be useful for the fusion of functional magnetic resonance imaging (fMRI) and electroencephalography data but has not been tested for other data combinations. In this study, we apply the C-ICT to fuse fMRI and MRI-based diffusion tensor imaging (DTI) datasets collected from healthy controls and patients with schizophrenia. In addition to independent components that show significant differences between the two groups in the fMRI and DTI datasets separately, we find multiple associations between these components from the two modalities, which provide a unique potential biomarker for schizophrenia.

Original languageEnglish (US)
Title of host publication2019 53rd Annual Conference on Information Sciences and Systems, CISS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728111513
DOIs
Publication statusPublished - Apr 16 2019
Externally publishedYes
Event53rd Annual Conference on Information Sciences and Systems, CISS 2019 - Baltimore, United States
Duration: Mar 20 2019Mar 22 2019

Publication series

Name2019 53rd Annual Conference on Information Sciences and Systems, CISS 2019

Conference

Conference53rd Annual Conference on Information Sciences and Systems, CISS 2019
CountryUnited States
CityBaltimore
Period3/20/193/22/19

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ASJC Scopus subject areas

  • Information Systems

Cite this

Jia, C., Akhonda, M. A. B. S., Long, Q., Calhoun, V. D., Waldstein, S., & Adali, T. (2019). C-ICT for Discovery of Multiple Associations in Multimodal Imaging Data: Application to Fusion of fMRI and DTI Data. In 2019 53rd Annual Conference on Information Sciences and Systems, CISS 2019 [8692878] (2019 53rd Annual Conference on Information Sciences and Systems, CISS 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CISS.2019.8692878