Blind Separation of Event-Related Brain Responses into Independent Components
Abstract : Functional imaging of brain activity based on changes in blood flow does not supply information about the relative timing of brief bursts of neural activity in different brain areas. Multichannel electric or magnetic recordings from the scalp provide high temporal resolution, but are not easily decomposed into the separate activities of multiple brain networks. We report here a method for the blind separation of event-related brain responses into spatially stationary and temporally independent subcomponents using an Independent Component Analysis algorithm. Applied to electroencephalographic responses from an auditory detection task, each of the most active identified sources accounted for all or part of a previously identified response component. This spatiotemporal decomposition was robust to changes in sensors and input data length, and was stable within subjects. The method can be used to assess the timing, strength, and stability of event-related activity in brain networks during cognitive tasks, regardless of source location.