Biofeedback of slow cortical potentials. II. Analysis of single event-related slow potentials by time series analysis

A single trial analysis of slow cortical potentials treating the EEG as a time series was developed. The method was applied to data resulting from an experiment on self-regulation of slow cortical potentials (SCP). Parametric models of the EEG were developed on the basis of autoregressive filter models and a two-component model of SCP (during 6 sec intervals), taking into account ocular influences as a further parameter. Results from different models were compared with each other and with results of averaging SCP data. For the present data time series analysis and traditional analysis provided qualitatively equal results, but fewer trials were necessary for analysis in the single trial approach and more detailed structures of the data became evident. If the EEG was filtered above 5 Hz it could be described by an autoregressive filter model of low order. Ocular influences were estimated as too small in a non-filtered EEG compared to the filtered EEG.