Reading the criminal mind Exploring novel methods of memory detection

To examine whether a criminal suspect has implicating crime knowledge, recognition of crime-related details can be detected using memory detection. Wide application of this method faces challenges such as leakage, countermeasures, selection of testitems, and limited applicability. The current dissertation aims to address these challenges and enhance the effectiveness of the method.
Firstly, the dissertation examined which modality is optimal for memory detection and whether encoding and testing modalities interact. The results highlight the importance of matching the modality of the testitems with the modality in which crime-related information was encoded to improve detection efficiency.
Secondly, the dissertation explored the promising new development of memory detection based on eye movements, including its potential of solving the leakage problem. Results indicated that it was possible to distinguish the guilty participants from the naïve as well as the informed innocent ones based on their eye movements.
Thirdly, the possibility of moving memory detection based on eye movements online was explored. By replicating three eye-tracking studies online, the dissertation demonstrates that webcam-based eye-tracking is viable for studies with relatively large effects and moderate eye-tracking precision.
Lastly, the dissertation tested whether gaze behavior toward the modified parts of the crime scene could reveal its recognition in virtual reality. The study showed that guilty participants looked more and earlier at the modifications than innocent participants, making it possible to significantly distinguish the two groups.
The findings of this research have practical implications for memory detection as well as theoretical implications for the memory literature.