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A review of multivariate methods for multimodal fusion of brain imaging data
Open accessAbstract
The development of various neuroimaging techniques is rapidly improving the measurements of brain function/structure. However, despite improvements in individual modalities, it is becoming increasingly clear that the most effective research approaches will utilize multi-modal fusion, which takes advantage of the fact that each modality provides a limited view of the brain. The goal of multimodal fusion is to capitalize on the strength of each modality in a joint analysis, rather than a separate analysis of each. This is a more complicated endeavor that must be approached more carefully and efficient methods should be developed to draw generalized and valid conclusions from high dimensional data with a limited number of subjects. Numerous research efforts have been reported in the field based on various statistical approaches, e.g. independent component analysis (ICA), canonical correlation analysis (CCA) and partial least squares (PLS). In this review paper, we survey a number of multivariate methods appearing in previous reports, which are performed with or without prior information and may have utility for identifying potential brain illness biomarkers. We also discuss the possible strengths and limitations of each method, and review their applications to brain imaging data.
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Metadata
- Authors
- Sui, J., Adali, T., Yu, Q., Chen, J., & Calhoun, V. D.
- Venue
- Journal of Neuroscience Methods
- Publisher
- Elsevier BV
- Published
- 2012-02
- Volume
- 204
- Issue
- 1
- Pages
- 68-81
- ISSN
- 0165-0270 (ISSN-L)
- OpenAlex
- W2065131965
- Cited by
- 401
- References
- 75
- FWCI
- 6.63
- Type
- journal article
- Language
- en
- Open access
- green
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- Funders
- National Institutes of Health (R01EB 006841, R01EB 005846)
- National Sciences Foundation (1017718, 1016619)
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- Sui, J., Adali, T., Yu, Q., Chen, J., & Calhoun, V. D. (2012). A review of multivariate methods for multimodal fusion of brain imaging data. Journal of Neuroscience Methods. https://doi.org/10.1016/j.jneumeth.2011.10.031
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