Nonlinear Dimension Reduction and Activation Detection for fMRI Dataset

@article{Shen2006NonlinearDR,
  title={Nonlinear Dimension Reduction and Activation Detection for fMRI Dataset},
  author={Xilin Shen and François G. Meyer},
  journal={2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06)},
  year={2006},
  pages={90-90}
}
Functional magnetic resonance imaging (fMRI) has been established as a powerful method for brain mapping. Different physical phenomena contribute to the dynamical changes in the fMRI signal, the task-related hemodynamic responses, non-task-related physiological rhythms, machine and motion artifacts, etc. In this paper, we propose a new approach for fMRI data analysis. Each fMRI time series is viewed as a point in RT . We are interested in learning the organization of the points in high… CONTINUE READING
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