Ventrolateral and dorsomedial frontal cortex lesions impair mnemonic context retrieval
Bibliographic record
Abstract
The prefrontal cortex appears to contribute to the mnemonic retrieval of the context within which stimuli are experienced, but only under certain conditions that remain to be clarified. Patients with lesions to the frontal cortex, the temporal lobe and neurologically intact individuals were tested for context memory retrieval when verbal stimuli (words) had been experienced across multiple (unstable context condition) or unique (stable context condition) contexts; basic recognition memory of these words-in-contexts was also tested. Patients with lesions to the right ventrolateral prefrontal cortex (VLPFC) were impaired on context retrieval only when the words had been seen in multiple contexts, demonstrating that this prefrontal region is critical for active retrieval processing necessary to disambiguate memory items embedded across multiple contexts. Patients with lesions to the left dorsomedial prefrontal region were impaired on both context retrieval conditions, regardless of the stability of the stimulus-to-context associations. Conversely, prefrontal lesions sparing the ventrolateral and dorsomedial regions did not impair context retrieval. Only patients with temporal lobe excisions were impaired on basic recognition memory. The results demonstrate a basic contribution of the left dorsomedial frontal region to mnemonic context retrieval, with the VLPFC engaged, selectively, when contextual relations are unstable and require disambiguation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".