Analyzing Event-Related Potentials: The Utility of High and Low Pass Filtering in Improving the Relationship Between Various Amplitude Measures and Principal Components Analysis Factor Scores

The present investigation sought to determine whether the relationship between event-related potential (ERP) principal components analysis (PCA) factor scores and analogous waveform amplitude measures could be improved by high- and low-pass filtering the waveforms at a suitable cutoff value. Visual oddball ERPs were submitted to a varimax-rotated PCA performed on the variance/covariance matrix. Principal components corresponding to P300 and Slow Wave were obtained. In keeping with the fact that the variance/covariance PCA analyzes sources of variance around the grand mean waveform, the grand mean waveform was subtracted from each of the original waveforms, and baseline-referenced amplitude measurements were then made of P300 and Slow Wave. P300 was measured both as the maximum positive peak between 275 and 425 ms, and as the average amplitude during that interval. Slow Wave was measured as the average amplitude during the interval 400–700 ms. The P300 measurements were then repeated after high-pass filtering the difference waveforms at 2 Hz. Slow Wave measurements were repeated after low-pass filtering at 2 Hz. The value of 2 Hz was chosen as giving a reasonable cutoff based upon estimates of the wavelengths of the two components derived from inspection of their respective factor loading vectors. The correlation between factor scores and amplitude measurements was .94 for unfiltered Slow Wave and actually declined slightly but significantly to .91 when the waveforms were low-pass filtered. It would appear that Slow Wave factor scores emerging from a PCA can be fairly well approximated by a time-band measurement algorithm, and that this approximation is not improved by low-pass filtering. For both filtered and unfiltered measurements of P300, the amplitude/factor score correlation was significantly higher for the time-band method than for the peak method. Further, high-pass filtering at 2 Hz improved the time-band/factor score correlation significantly from .62 to .75. This improvement is probably because the unfiltered measurements were tapping sources of variance due both to the higher frequency P300 component as well as a simultaneously active, lower frequency Slow Wave component. Theoretical implications of these findings are discussed.