Countering Cross-Individual Variance in Event Related Potentials with Functional Profiling

The practical use of ERP deception detection is confounded by low signal-to-noise ratio of EEG and the high inter-participant variation in form (and even polarity) of ERP components. In this study, a simple method called the Weight Template (WT) is proposed for classifying brain responses of individuals into deceiving and non-deceiving. The performance of our method was evaluated on a number of identity deception data sets and on artificial EEG data sets. A comparison was made with a standard method used to measure P3 presence, called Peak-to-Peak. In the real experimental data, the WT showed higher performance in terms of sensitivity and specificity. In the artificial EEG data, in ERPs with low Signal-to-Noise Ratio (SNR), the WT was more resistant to noise and provided more accurate measures.