Independent Component Analysis of Electroencephalographic Data
Makeig, Scott, Bell, Anthony J., Jung, Tzyy-Ping, Sejnowski, Terrence J.
–Neural Information Processing Systems
Because of the distance between the skull and brain and their different resistivities, electroencephalographic (EEG) data collected from any point on the human scalp includes activity generated within a large brain area. This spatial smearing of EEG data by volume conduction does not involve significant time delays, however, suggesting that the Independent Component Analysis (ICA) algorithm of Bell and Sejnowski [1] is suitable for performing blind source separation on EEG data.
Neural Information Processing Systems
Dec-31-1996