On why Collet's doubts regarding the PCA are misplaced

Collet's (1989) doubts regarding the efficacy of principal component analysis (PCA) as a tool in the study of event-related brain potentials (ERPs) are unpersuasive. The substantive point reported by Collet is that data points are autocorrelated over the time period during which a single, PCA-defined, ERP component predominates. Such autocorrelation has long been recognized by investigators in the field, and its confirmation by autoregressive modeling does not provide useful information about issues central to ERP data analysis. Furthermore, because he fails to take a full count of the number of parameters used in his autoregressive model his argument from parsimony is flawed. In any event, Collet's argument misperceives the heuristic mode in which PCA is used in actual studies.