Data stream synchronization for defining meaningful fMRI classification problems
We challenge a popular approach to labelling fMRI data for predictive modelling. We propose a new labelling method based on data stream synchronization. We validate the proposed method experimentally on real fMRI data. We observe major classification accuracy improvement and model complexity reduction.
data stream synchronization fmri classification pattern recognition machine learning smart filtering