Neural basis of cognitive control signals in anterior cingulate cortex during delay discounting
Bibliographic record
Abstract
Summary Cognitive control involves allocating cognitive effort according to internal needs and task demands and 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. Decision-making in this this task can be guided by using either a lever-value tracking strategy, requiring a ‘resource-based’ form of cognitive effort or a lever-biased strategy requiring a ‘resistance-based’ form of cognitive effort. We found that ACC ensembles always tightly tracked lever value on each trial, indicative of a resource-based control signal. These signals were prevalent in the neural recordings and were influenced by the delay. A shorter delay was associated with devaluing of the immediate option and a longer delay was associated with overvaluing of the immediate option. In addition, ACC theta (6-12Hz) oscillations were observed at the choice point of rats exhibiting a resistance-based strategy. These data provide candidates of neural activity patterns in the ACC that underlie the use of ‘resource-based’ and ‘resistance-based’ cognitive effort. Furthermore, these data illustrate how strategies can be engaged under different conditions in individual subjects.
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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".