Single trial ERP reading based on Parallel Factor Analysis
The extraction of task-related single trial ERP information has recently gained much interest, not only in studies on ERPs alone, but also in simultaneous EEG-fMRI applications. The investigation of these single trial data, however, requires a specific decomposition to retrieve the task-related activity from the originally acquired raw data. In this study, this is achieved with source extraction based on parallel factor analysis (PARAFAC). We show that differences between distinct task-related conditions can be captured in the trial signatures of specific PARAFAC components when applied to single trial ERP data arranged in channels x time x trials arrays. The performance of this method is illustrated for data from a visual detection task, acquired in normal circumstances and simultaneously with fMRI. We also checked whether the obtained trial signatures correlated with the fMRI data, but with this approach no significant results were found.