Abstract #4143
A New Model for Canonical Correlation Analysis with Spatial Constraints
Martin Miguel Merener 1 , Richard Byrd 2 , Rajesh R. Nandy 3 , and Dietmar Cordes 1,4
1
Physics, Ryerson University, Toronto,
Ontario, Canada,
2
Computer
Science, University of Colorado Boulder, Boulder, CO,
United States,
3
School
of Public Health, University of North Texas, Fort Worth,
TX, United States,
4
Department
of Psychology and Neuroscience, University of Colorado
Boulder, CO, United States
This study provides important improvements in fMRI data
analysis techniques for the detection of active brain
areas. We propose and study a family of constraints for
CCA, which naturally generalizes two interesting
previously studied models. The solutions for these
models can be found numerically and efficiently. For
several choices of these constraints, the performance of
the method in determining active voxels is excellent as
measured via ROC simulations, and provide a significant
improvement compared to previously published models in
constrained CCA.
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