PCA (Principal Component Analysis)

This method estimates the brain activity from the data currently displayed on the screen. The data is scanned in specified time

intervals. Those segments are considered to represent brain activity where 1) the correlation between data and artifact topography

does not exceed a certain threshold and 2) the signal amplitudes are below a specified threshold. Of the remaining segments a

principal component analysis (PCA) is performed. All PCA components explaining more than the minimum variance specified in

the box Adaptive Model: PCA Topography are maintained. They span the brain signal subspace.