Stress Elevates Frontal Midline Theta in Feedback-based Category Learning of Exceptions
Bibliographic record
Abstract
Adapting behavior based on category knowledge is a fundamental cognitive function, which can be achieved via different learning strategies relying on different systems in the brain. Whereas the learning of typical category members has been linked to implicit, prototype abstraction learning, which relies predominantly on prefrontal areas, the learning of exceptions is associated with explicit, exemplar-based learning, which has been linked to the hippocampus. Stress is known to foster implicit learning strategies at the expense of explicit learning. Procedural, prefrontal learning and cognitive control processes are reflected in frontal midline theta (4-8 Hz) oscillations during feedback processing. In the current study, we examined the effect of acute stress on feedback-based category learning of typical category members and exceptions and the oscillatory correlates of feedback processing in the EEG. A computational modeling procedure was applied to estimate the use of abstraction and exemplar strategies during category learning. We tested healthy, male participants who underwent either the socially evaluated cold pressor test or a nonstressful control procedure before they learned to categorize typical members and exceptions based on feedback. The groups did not differ significantly in their categorization accuracy or use of categorization strategies. In the EEG, however, stressed participants revealed elevated theta power specifically during the learning of exceptions, whereas the theta power during the learning of typical members did not differ between the groups. Elevated frontal theta power may reflect an increased involvement of medial prefrontal areas in the learning of exceptions under stress.
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How this classification was reachedexpand
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".