Hemispheric differences in amygdala contributions to response monitoring
Bibliographic record
Abstract
The amygdala detects aversive events and coordinates with the rostral anterior cingulate cortex to adapt behavior. We assessed error-related activation in these regions and its relation to task performance using functional MRI and a saccadic paradigm. Both amygdalae showed increased activation during error versus correct antisaccade trials that was correlated with error-related activation in the corresponding rostral anterior cingulate cortex. Together, activation in the right amygdala and right rostral anterior cingulate cortex predicted greater accuracy. In contrast, the left amygdala activation predicted a higher error rate. These findings support a role for the amygdala in response monitoring. Consistent with proposed specializations of the right and left amygdala in aversive conditioning, we hypothesize that right amygdala-rostral anterior cingulate cortex interactions mediate learning to avoid errors, whereas left error-related amygdala activation underpins detrimental negative affect.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".