Is ventromedial prefrontal cortex critical for behavior change without external reinforcement?
Bibliographic record
Abstract
Cue-approach training (CAT) is a novel paradigm that has been shown to induce preference changes towards items without external reinforcements. In the task, the mere association of a neutral cue and a speeded button response has been shown to induce a behavioral choice preference change lasting for months. This paradigm includes several phases: after the training of individual items, behavior change is manifested in binary choices of items with similar initial values. Neuroimaging data have implicated the ventromedial prefrontal cortex (vmPFC) in the choice phase of this task. However, the neural mechanisms underlying the preference changes induced by training remain unclear. Here, we asked whether the ventromedial frontal lobe (VMF) is critical for the non-reinforced preference change induced by CAT. For this purpose, 11 participants with focal lesions involving the VMF and 30 healthy age-matched controls performed the CAT. The VMF group was similar to the healthy age-matched control group in the ranking and training phases. As a group, the healthy age-matched controls exhibited a training-induced behavior change, while the VMF group did not. However, on an individual level analysis we found that some of the VMF participants showed a significant preference shift. Thus, we find mixed evidence for the role of VMF in this paradigm. This is another step towards defining the mechanisms underlying the novel form of behavioral change that occurs with CAT.
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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) | 0.002 | 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".