Reduction in Reward-Driven Behavior Depends on the Basolateral But Not Central Nucleus of the Amygdala in Female Rats
Bibliographic record
Abstract
Adaptive behavior depends on a dynamic balance between acquisition and extinction memories. Male and female rodents differ in extinction learning rates, suggesting potential sex-based differences in this balance. In males, deletion of extinction-recruited neurons in the central nucleus (CN) of the amygdala impairs extinction retrieval, shifting behavior toward acquisition (Lay et al., 2023). Here, we tested whether this mechanism also operates in females. In contrast to previously reported findings in males, deleting extinction-recruited CN neurons after single or extended extinction training had no effect on extinction retrieval in female rats. This lack of behavioral impact was not due to sex differences in CN activation during extinction. However, during early extinction, females showed greater activity in the basolateral amygdala (BLA) than males. Deletion of this BLA ensemble produced a more substantial reduction in conditioned approach than in non-deletion controls. These findings uncover a potential interplay between the CN and BLA in regulating conditioned approach in females. While ablation of extinction-recruited CN neurons do not modulate extinction retrieval in females, targeted BLA neuronal ablation during early extinction shifts behavior toward low, extinction-level responding. Thus heightened BLA activation during early extinction may prevent the emergence of extinction-like behavior in females. These findings, taken together with those reported by Lay et al. (2023), offer new insights into potential sex-based differences in the neural mechanisms underlying extinction and may inform the development of sex-based treatments for cue-triggered appetitive behaviors.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".