Evidence for a Role for the Dorsal Anterior Cingulate Cortex in Disengaging from an Incorrect Action
Bibliographic record
Abstract
Adjusting for an error requires both disengaging from the wrong course of action and initiating a corrective response. The dorsal anterior cingulate cortex (dACC) has been implicated in both these processes in the decision-making and action monitoring literatures. Here, we aimed to distinguish between these putative functions with a variant of the Eriksen flanker task that manipulated response requirements (i.e. one or two finger responses). We found that two event-related potentials originating from the dACC (error-related negativity (ERN) and anterior N2) only reflected the representation of the incorrect response: these waveforms were larger when the incorrect response involved two fingers rather than one finger. The increase in ERN magnitude was also accompanied by a reduction in spontaneous error corrections. These results argue that activity in the dACC reflects a process involved in disengaging from an ongoing incorrect action, clearing the way for the correct response.
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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 | 0.002 |
| 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 | 0.001 |
| 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".