Separating spatial and temporal activation patterns in fMRI using competitive subspace projection
The challenge for functional magnetic resonance imaging (fMRI) is to determine when and where the response due to an external stimulus occurs in the images. The temporal clustering analysis (TCA) method has been used to study brain activity after eating and drinking, in both the time and spatial domains. We propose a new method, competitive subspace projection (CSP), to represent data optimally compared to other subspace projection methods. This method is used to detect spatial and temporal activation patterns in fMRI associated with such behavior. The CSP and TCA methods are compared using both synthetic and real fMRI data. The results on both data sets show consistent conclusions can be drawn from these two methods while CSP is observed to have a better noise rejection capability than TCA.