Principal component approach for mapping functional connectivity in event-related Fmri

摘要

In this paper, we present a method to analyze functional connectivity in event-related functional magnetic resonance imaging (fMRI) data. The connectivity between the chosen seed area and the other brain voxels is estimated using principal components derived from a correlation matrix of single trials. The approach is applied for two different event-related fMRI datasets: one with functional connectivity between visual and motor cortices and other without functional connectivity between those areas.