Left mid‐ventrolateral prefrontal cortex: underlying principles of function
Bibliographic record
Abstract
There is a growing body of evidence indicating that the mid-ventrolateral prefrontal cortex in the left hemisphere is involved in some aspect of controlled verbal memory retrieval. Its precise role, however, remains unclear. We tested the hypothesis that when stimuli in memory are related to each other in multiple ways, and therefore familiarity, strong constant stimulus-stimulus links or contextual cues are not sufficient for successful retrieval, control processing emanating from the mid-ventrolateral prefrontal cortex is required to disambiguate and select the appropriate information among memory traces. We refer to this type of retrieval as active retrieval to distinguish it from automatic retrieval which depends on the simple reactivation of memory traces. Normal human subjects were scanned with functional magnetic resonance imaging while they performed three memory tasks that varied in their demands on active retrieval of verbal information. As the demands on active retrieval increased, there was an increase in the activity within the mid-ventrolateral prefrontal cortex, bilaterally, but with more prominent activity in the left hemisphere. These activity increases correlated with activity in the posterior temporal region which, in the left hemisphere, is involved in language processing. No significant activity increases were observed in any other prefrontal region. Furthermore, for the retrieval of well-learned verbally cued conditional motor associations, there were no activity increases in the mid-ventrolateral prefrontal cortex. The present findings provide strong support for the hypothesis that the mid-ventrolateral prefrontal cortex, particularly in the left hemisphere, plays a major role in the active retrieval of information from verbal memory.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".