Ventromedial Prefrontal Cortex Lesions Produce Early Functional Alterations during Remote Memory Retrieval
Bibliographic record
Abstract
We examined the role of ventromedial prefrontal cortex (VMPFC) in memory retrieval monitoring. Event-related potentials were recorded while patients with VMPFC lesions and matched controls viewed faces of personal acquaintances, and of famous and nonfamous people, and indicated whether they had personally encountered these individuals. Patients were more likely than controls to make both false positive and false negative errors. Both groups showed a large posterior negative wave peaking at approximately 170 ms after face onset (N170). In controls, the N170 was larger for both types of familiar faces, regardless of whether overt recognition occurred. Specifically, personal acquaintances that were erroneously judged as unfamiliar evoked the same electrophysiological response as those who were explicitly recognized. Patients' N170 was not modulated by familiarity suggesting VMPFC lesions disrupt early posterior memory-based preconscious cortical distinctions. Following the N170, there was a significant group difference over frontopolar scalp regions where patients were showing a smaller positive modulation at 230-260 ms for all stimulus types. In patients this modulation correlated highly with reaction times of correct responses, suggesting this early frontal modulation is related to the ability to make rapid correct decisions about memory content. Group differences over anterior sites were also noted at 350 ms after stimulus, reflecting a large sustained negativity of patients' waveforms, equal across conditions. The findings are consistent with a hypothesis of frontally mediated dual-monitoring system. An early automatic (preconscious) component is followed by a late elaborate process. We hypothesize that when both components are damaged, confabulation may occur.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".