The ventromedial prefrontal cortex and intention representation in prospective memory
Bibliographic record
Abstract
Prospective memory (PM) consists of (i) a retrospective component, i.e. memory for the intentions and for the cues that should trigger an action, and (ii) a prospective component of monitoring and identifying these cues and the timely execution of the action. Here, we tested patients with damage to ventromedial prefrontal cortex (vmPFC; N = 5) and matched controls (N = 12) for (i) the presence of an intention superiority effect (ISE) indexing prieviliged processing of memories associated with intended actions (retrospective PM) and (ii) the cognitive cost that monitoring for a prospective cue exerts on performing an ongoing task (prospective PM). We found that control participants showed a clear ISE, which was absent in patients as a group, and individually absent in 4 out of the 5 patients whose lesions encroached on posterior vmPFC. A patient with more anterior mPFC damage had normal ISE. Conversely, all patients showed normal reaction time cost for an ongoing task when a prospective task was added, if the prospective cue was aligned with the ongoing task focus of attention. When prospective cues were outside the focus of attention of the ongoing task, one patient with additional damage to the Caudate Nucleus failed the PM task completely. The other 4 patients continued to perform within normal controls' range. Together these data suggest a unique role for sub-callosal vmPFC in PM, bolstering the implicit processing of environmental cues that are relevant for realizing future intentions. This is consistent with vmPFC's role in context-sensitive value processing based on prior experiences.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".