Abstract
In the pursuit of new methods for concealed memory detection, event-related potential components (ERP) have been placed at the forefront of research. No method, however, is scientifically complete without a theory and the present study therefore aimed to unravel the cognitive processes underlying these ERPs (i.e., orienting and arousal inhibition). This was accomplished by using a Concealed Information Test (CIT) in which participants were once motivated to conceal and once motivated to reveal their identity. The results showed a similarly strong P3 CIT effect in the two motivational conditions, which was enhanced for high salience compared to low salience identity items. Similar results were observed when using a multivariate machine-learning algorithm – suggesting that brain-based concealed memory detection is driven mainly by orientation to salient stimuli, rather than by arousal inhibition. In addition, the algorithm, trained and tested on the ERPs of different identity items, achieved detection rates exceeding those achieved by the P3. This implies that CIT researchers and practitioners could potentially rely on the entire ERP waveform instead of a-priori selecting separate components. Together these results enrich current understanding of the mechanisms underlying neurophysiological responding to concealed information and pave the way for novel and powerful algorithms which could be used in real-life forensic investigations.
| Original language | English |
|---|---|
| Pages (from-to) | 41-55 |
| Number of pages | 15 |
| Journal | Cortex |
| Volume | 136 |
| DOIs | |
| State | Published - Mar 2021 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2020 Elsevier Ltd
Funding
This research was funded by a grant No. 238/15 , from the Israel Science Foundation, Israel, to GBS . LYD is supported by the Jack H. Skirball research fund, Israel . We wish to thank Shani Vaknine, Maayan Davidesko, Geffen Markusfeld and Michal Rabinovits for their assistance in data collection and Maayan Davidesko and Rotem Krispil for their assistance in the data analyses.
| Funders | Funder number |
|---|---|
| Israel Science Foundation |
Keywords
- Arousal inhibition
- Concealed Information Test (CIT)
- Event-related potentials
- Machine learning
- Orienting response