|Title||Time-Dependent Demixing of Task-Relevant EEG Signals.|
|Publication Type||Journal Article|
|Year of Publication||2006|
|Authors||Jeremy Jeremy Hill, Farquhar, J, Lal, TN, Schölkopf, B|
Given a spatial filtering algorithm that has allowed us to identify task-relevant EEG sources, we present a simple approach for monitoring the activity of these sources while remaining relatively robust to changes in other (task-irrelevant) brain activity. The idea is to keep spatial *patterns* fixed rather than spatial filters, when transferring from training to test sessions or from one time window to another. We show that a fixed spatial pattern (FSP) approach, using a moving-window estimate of signal covariances, can be more robust to non-stationarity than a fixed spatial filter (FSF) approach.