ArticleHuman brain mapping2022
Detecting spontaneous deception in the brain.
Article in Human brain mapping, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- Distinguishing deception from its confounds by improving the validity of fMRI-based neural prediction.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- The neurosociological paradigm of the metaverse.Frontiers in psychology · 2024Article
- Detecting spontaneous deception in the brain.Human brain mapping · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Deception detection can be of great value during the juristic investigation. Although the neural signatures of deception have been widely documented, most prior studies were biased by difficulty levels. That is, deceptive behavior typically required more effort, making deception detection possibly effort detection. Furthermore, no study has examined the generalizability across instructed and spontaneous responses and across participants. To explore these issues, we used a dual-task paradigm, where the difficulty level was balanced between truth-telling and lying, and the instructed and spontaneous truth-telling and lying were collected independently. Using Multivoxel pattern analysis, we were able to decode truth-telling versus lying with a balanced difficulty level. Results showed that the angular gyrus (AG), inferior frontal gyrus (IFG), and postcentral gyrus could differentiate lying from truth-telling. Critically, linear classifiers trained to distinguish instructed truthful and deceptive responses could correctly differentiate spontaneous truthful and deceptive responses in AG and IFG with above-chance accuracy. In addition, with a leave-one-participant-out analysis, multivoxel neural patterns from AG could classify if the left-out participant was lying or not in a trial. These results indicate the commonality of neural responses subserved instructed and spontaneous deceptive behavior as well as the feasibility of cross-participant deception validation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.