Prefrontal cortical and nucleus accumbens contributions to discriminative conditioned suppression of reward-seeking
Bibliographic record
Abstract
Fear can potently inhibit ongoing behavior, including reward-seeking, yet the neural circuits that underlie such suppression remain to be clarified. Prior studies have demonstrated that distinct subregions of the rodent medial prefrontal cortex (mPFC) differentially affect fear behavior, whereby fear expression is promoted by the more dorsal prelimbic cortex (PL) and inhibited by the more ventral infralimbic cortex (IL). These mPFC regions project to subregions of the nucleus accumbens, the core (NAcC) and shell (NAcS), that differentially contribute to reward-seeking as well as affective processes that may be relevant to fear expression. Here, we investigated how these mPFC and NAc subregions contribute to discriminative fear conditioning, assessed by conditioned suppression of reward-seeking. Bilateral inactivation of the NAcS or PL reduced the expression of conditioned suppression to a shock-associated CS+, whereas NAcC inactivation reduced reward-seeking without affecting suppression. IL inactivation caused a general reduction in conditioned suppression following discriminative conditioning, but not when using a single-stimulus design. Pharmacological disconnection of the PL → NAcS pathway revealed that this projection mediates conditioned suppression. These data add to a growing literature implicating discrete cortico-striatal pathways in the suppression of reward-seeking in response to aversive stimuli. Dysfunction within related structures may contribute to aberrant patterns of behavior in psychiatric illnesses including substance use disorders.
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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) | 0.001 | 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 | 0.001 |
| 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".