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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | McKeown, M.J. Junning Li Xuemei Huang Wang, J.Z. |
| Copyright Year | 2007 |
| Description | Author affiliation: Brain Res. Centre, British Columbia Univ., Vancouver, BC (McKeown, M.J.) |
| Abstract | Large intersubject variability is a well-described feature of fMRI studies, making inter-group inference, of critical importance for biological interpretation, difficult. Therefore, traditional approaches involve spatially transforming the data of each subject and heavily spatially smoothing the data. Here we propose an alternate method: after first defining individually-specific regions of interest (ROIs) of each subject, we utilize local linear discriminant analysis (LLDA) to jointly optimize the individually-specific and group linear combinations of ROIs that maximally discriminates between groups characterized by either disease status or task. The proposed method was applied to fMRI data recorded from eight normal subjects performing a motor task, and it was shown to successfully detect activation in multiple cortical and subcortical structures that were not present when the data were traditionally analyzed by warping the data to a common space. We suggest that the proposed method for group fMRI data analysis may be more suitable when examining co-activation in small subcortical regions susceptible to misregistration, or examining older or neurological patient populations. |
| File Size | 166340 |
| File Format | |
| ISBN | 1424407273 |
| ISSN | 15206149 |
| DOI | 10.1109/ICASSP.2007.366677 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-04-15 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Linear discriminant analysis Data analysis Magnetic analysis Biological system modeling Brain modeling Animal structures Nervous system Smoothing methods Optimization methods Diseases Regions of Interest Discriminant Analysis FMRI Group Analysis |
| Content Type | Text |
| Resource Type | Article |
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