Dissociable brain activity for high-stakes deception detection in young and older adults
Bibliographic record
Abstract
While anyone can fall victim to deception with deleterious impact, age-related changes in financial, cognitive, socioemotional, and neurobiological factors convey greater risk to older adults. Neural responses underlying deception detection may elucidate age-related vulnerability or resilience to deception. Here, we examined 53 young (18-33 years) and 50 older (55-78 years) adults who underwent functional magnetic resonance imaging while aiming to detect deception in naturalistic, high-stakes videos (i.e. pleas for information about a missing relative, where later some of the pleaders were found guilty in the murder of the missing relative). Behaviourally, young and older adults had comparably poor performance at detecting deceptive pleas. Further, we observed a multivariate pattern of brain activity, including visual and parietal areas that differentiated genuine from deceptive pleas across age groups. Reflecting individual variation, older adults with higher sensitivity to deception had stronger activation of brain regions associated with mentalizing (e.g. medial prefrontal cortex) and cognitive control (e.g. anterior cingulate cortex, dorsolateral prefrontal cortex) during deception detection. Together, our findings build on extant models of decision-making in ageing to show that age differences in brain function may facilitate compensation among some older adults to identify deception.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".