Spatiotemporal clustering of fMRI time series in the spectral domain.

@article{Meyer-2005, abstract = {We propose a new method for the analysis of functional magnetic resonance images (fMRI). The decision that a voxel v0 is activated is based not solely on the value of the fMRI signal at v0, but rather on the comparison of all time series s(v)(t) in a small neighborhood Nv0 around v0. Our approach explicitly takes into account the intrinsic spatiotemporal correlations that exist in the data. We focus on experimental designs with periodic stimuli, and therefore we can capture most of the features of the BOLD signal with a low dimensional subspace in the frequency domain. The presence of activated time series can be detected by partitioning the time series in this low dimensional space. Experiments with simulated data, and experimental fMRI data, demonstrate that our approach can outperform standard methods of analysis, such as the t-test.}, address = {Department of Electrical Engineering, University of Colorado at Boulder, Boulder, CO 80309, USA. francois.meyer@colorado.edu}, author = {Meyer, F. G. and Chinrungrueng, J. }, citeulike-article-id = {610870}, doi = {10.1016/j.media.2004.07.002}, issn = {1361-8415}, journal = {Med Image Anal}, keywords = {clustering, fmri, fnak, kmeans}, month = {February}, number = {1}, pages = {51--68}, posted-at = {2006-05-01 18:27:37}, priority = {2}, title = {Spatiotemporal clustering of fMRI time series in the spectral domain.}, url = {http://dx.doi.org/10.1016/j.media.2004.07.002}, volume = {9}, year = {2005} }

TY - JOUR ID - Meyer-2005 L3 - citeulike-article-id:610870 TI - Spatiotemporal clustering of fMRI time series in the spectral domain. JF - Med Image Anal VL - 9 IS - 1 SP - 51 EP - 68 AD - Department of Electrical Engineering, University of Colorado at Boulder, Boulder, CO 80309, USA. francois.meyer@colorado.edu SN - 1361-8415 N2 - We propose a new method for the analysis of functional magnetic resonance images (fMRI). The decision that a voxel v0 is activated is based not solely on the value of the fMRI signal at v0, but rather on the comparison of all time series s(v)(t) in a small neighborhood Nv0 around v0. Our approach explicitly takes into account the intrinsic spatiotemporal correlations that exist in the data. We focus on experimental designs with periodic stimuli, and therefore we can capture most of the features of the BOLD signal with a low dimensional subspace in the frequency domain. The presence of activated time series can be detected by partitioning the time series in this low dimensional space. Experiments with simulated data, and experimental fMRI data, demonstrate that our approach can outperform standard methods of analysis, such as the t-test. KW - clustering KW - fmri KW - fnak KW - kmeans AU - Meyer, FG AU - Chinrungrueng, J PY - 2005/02// UR - http://dx.doi.org/10.1016/j.media.2004.07.002 ER -