Functional magnetic resonance imaging study of external source memory and its relation to cognitive insight in non‐clinical subjects
Bibliographic record
Abstract
AIM: Previous research has linked cognitive insight (a measure of self-reflectiveness and self-certainty) in psychosis with neurocognitive and neuroanatomical disturbances in the fronto-hippocampal neural network. The authors' goal was to use functional magnetic resonance imaging (fMRI) to investigate the neural correlates of cognitive insight during an external source memory paradigm in non-clinical subjects. METHODS: At encoding, 24 non-clinical subjects travelled through a virtual city where they came across 20 separate people, each paired with a unique object in a distinct location. fMRI data were then acquired while participants viewed images of the city, and completed source recognition memory judgments of where and with whom objects were seen, which is known to involve prefrontal cortex. Cognitive insight was assessed with the Beck Cognitive Insight Scale. RESULTS: External source memory was associated with neural activity in a widespread network consisting of frontal cortex, including ventrolateral prefrontal cortex (VLPFC), temporal and occipital cortices. Activation in VLPFC correlated with higher self-reflectiveness and activation in midbrain correlated with lower self-certainty during source memory attributions. Neither self-reflectiveness nor self-certainty significantly correlated with source memory accuracy. CONCLUSION: By means of virtual reality and in the context of an external source memory paradigm, the study identified a preliminary functional neural basis for cognitive insight in the VLPFC in healthy people that accords with our fronto-hippocampal theoretical model as well as recent neuroimaging data in people with psychosis. The results may facilitate the understanding of the role of neural mechanisms in psychotic disorders associated with cognitive insight distortions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".