This study examined neural signatures associated conflict-monitoring, recognition and feedback processing in a novel feedback Concealed Information Test (fCIT), and also examined whether all the ERPs can be used to detect concealed autobiographical information. Participants were randomly assigned to one of two groups (guilty or innocent) and then tested in the fCIT while undergoing electroencephalograms (EEGs). Results show that the probe (participants’ name) elicited more negative N200, more positive recognition P300 than irrelevants among guilty participants, and feedback following the probe elicited a larger feedback P300 than feedback following irrelevants. Further, we found that all indicators, including conflict-monitoring N200, recognition P300, and feedback P300, could significantly discriminate between guilty and innocent participants. Combining them is highly effective in discriminating between guilty and innocent participants (AUC = 0.96). These findings not only shed light on the neural processing of fCIT, but also suggest the potential of using fCIT to detect concealed autobiographical information.

To explore the forensic application of neuroimaging-based concealed information test (CIT) with combined multiple measurements, the simultaneously recorded data of functional near-infrared spectroscopy (fNIRS), skin conductance responses (SCRs), heart rate (HR), and reaction time (RT) is collected in order to detect participants’ concealed information in a standard CIT with a mock crime scenario. We hypothesized the fNIRS-based neuroimaging data could successfully detect deception, and the combination of multiple indicators could integrate multidimensional information triggered by deception, thus providing enhanced efficiency in deception detection. The results validated the hypotheses that fNIRS-based neuroimaging data could effectively discriminate between guilty and innocent participants after a mock crime. Furthermore, the use of multiple indicators resulted in a much higher detection efficiency (AUC = 0.96 with fNIRS channel 8) compared to the use of a single indicator (AUC = 0.66-0.86). These results illustrate the potential of the combination of fNIRS and multiple indicators for deception detection with a mock crime scenario and further facilitate the forensic application of fNIRS-based CIT.