Beyond Reversal: A Critical Role for Human Orbitofrontal Cortex in Flexible Learning from Probabilistic Feedback
Why this work is in the frame
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Bibliographic record
Abstract
Damage to the orbitofrontal cortex (OFC) has been linked to impaired reinforcement processing and maladaptive behavior in changing environments across species. Flexible stimulus-outcome learning, canonically captured by reversal learning tasks, has been shown to rely critically on OFC in rats, monkeys, and humans. However, the precise role of OFC in this learning remains unclear. Furthermore, whether other frontal regions also contribute has not been definitively established, particularly in humans. In the present study, a reversal learning task with probabilistic feedback was administered to 39 patients with focal lesions affecting various sectors of the frontal lobes and to 51 healthy, demographically matched control subjects. Standard groupwise comparisons were supplemented with voxel-based lesion-symptom mapping to identify regions within the frontal lobes critical for task performance. Learning in this dynamic stimulus-reinforcement environment was considered both in terms of overall performance and at the trial-by-trial level. In this challenging, probabilistic context, OFC damage disrupted both initial and reversal learning. Trial-by-trial performance patterns suggest that OFC plays a critical role in interpreting feedback from a particular trial within the broader context of the outcome history across trials rather than in simply suppressing preexisting stimulus-outcome associations. The findings show that OFC, and not other prefrontal regions, plays a necessary role in flexible stimulus-reinforcement learning in humans.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.006 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it