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Dimension Reduction and Spatiotemporal Regression: Applications to Neuroimaging
September/October 2003 (vol. 5 no. 5)
pp. 30-36
Kerby Shedden, University of Michigan
Ker-Chau Li, University of California, Los Angeles

One method for characterizing spatiotemporal variation in brain activity levels is based onthe use of statistical dimension reduction. This reduction finds temporal components in data that best preserve the spatiotemporal regression structure. The method does this by suppressing more prominent waveforms that do not vary in a spatially predictable pattern.

Citation:
Kerby Shedden, Ker-Chau Li, "Dimension Reduction and Spatiotemporal Regression: Applications to Neuroimaging," Computing in Science and Engineering, vol. 5, no. 5, pp. 30-36, Sept.-Oct. 2003, doi:10.1109/MCISE.2003.1225858
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