Unfortunately, single-trial analysis of EEG is seldom performed. The main reason for this is that EEG recorded at the scalp constitutes a mixture of a number of sources signals, therefore, activity associated with a single process, being mixed with signals arising from other processes as well as on-going “background” oscillations, is difficult to identify within each trial. Here, EEG data are decomposed with independent component analysis (ICA), which, as described below, un-mixes the different source signals recorded at the scalp, enabling activity from independent processes to be identified in single-trials (Makeig et al., 1997, 2004; Onton et al., 2006) and variability within individuals to be measured.
