Neural basis of cognitive control signals in anterior cingulate cortex during delay discounting
Bibliographic record
Abstract
Cognitive control involves allocating cognitive effort according to internal needs and task demands. The anterior cingulate cortex (ACC) is hypothesized to play a central role in this process. We investigated the neural basis of cognitive control in the ACC of rats performing an adjusting-amount delay discounting task, with a 4s or 8s delay between lever choice and reward. A reinforcement learning model indicated that decision making on this task can be guided by either a value tracking strategy, requiring a 'resource-based' form of cognitive control or a delay-lever biased strategy requiring a 'resistance-based' form of cognitive control. This was then tested in vivo by multiple single unit recordings and local field potentials acquired from male rats performing the task. On this task, the behavioral manifestation of resistance-based control is an excessive focus on delayed lever choices which was observed during a substantial portion of 4s but not 8s delay sessions. On a neural level, this was associated with an increase in Theta (6-12Hz) oscillations prior to delay choices which was present exclusively on 4s delay sessions. By contrast, evidence of a resource-based control signal was found in spike trains that closely tracked lever value prior to choice, and was far more prevalent on 8s delay sessions. These data provide candidate neural signatures of 'resource-based' versus 'resistance-based' forms of cognitive control. While mediated by distinct neural mechanisms, either form could be engaged by individual subjects under different task conditions.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".