期刊
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
卷 33, 期 2, 页码 131-139出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compmedimag.2008.10.011
关键词
FMRI; Brain connectivity; Brain network
资金
- NWPU Foundation for Fundamental Research
- U.S. National Institutes of Health [NIH NIBIB K01, K01 EB 006878]
Since the mid of 1990s, functional connectivity study using fMRI (fcMRI) has drawn increasing attention of neuroscientists and computer scientists, since it opens a new window to explore functional network of human brain with relatively high resolution. A variety of methods for fcMRI study have been proposed. This paper intends to provide a technical review on computational methodologies developed for fcMRI analysis. From our perspective, these computational methods are classified into two general categories: model-driven methods and data-driven methods. Data-driven methods are a large family, and thus are further sub-classified into decomposition-based methods and clustering analysis methods. For each type of methods, principles, main contributors, and their advantages and drawbacks are discussed. Finally, potential applications of fcMRl are overviewed. (C) 2008 Elsevier Ltd. All rights reserved.
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