Habit learning shapes activity dynamics in the central nucleus of the amygdala
Bibliographic record
Abstract
A habit develops as a motivated behavior that is strengthened by extended experience and feedback. While the performance component of a habit is relatively well studied, being linked to action-related neural dynamics in the basal ganglia and beyond, neural mechanisms for outcome feedback during habit formation, the reinforcement component, remain unknown. One candidate for this feedback mechanism is in the central nucleus of the amygdala (CeA). Here, we identify CeA neural firing dynamics in male and female rats that serve to promote habit formation. We used a novel maze task with rewards of differing identity and value to show that habits arise with task overtraining. After showing that overtraining engages CeA as shown through elevated cFos expression, we recorded in-vivo CeA activity across learning, and after outcome devaluation when habitual behavior is most identifiable. Neuronal activity changes tracked with habit formation. During learning, a group of recorded cells were significantly responsive at the choice point of maze trials while others encoded outcome consumption. By late training, neural activity exhibited a rapid depression at the choice point of the maze and excitation during reward receipt. In both cases, outcome magnitude, but not identity, was a significant modulator of neural activity. Additionally, a population of neurons tracked instantaneous changes in animal run speed. These speed cells dramatically decreased in number as habits formed. Together, these findings support a role for the CeA in providing reinforcement for habitual behavior, offering a signal that marks successful performance, while identifying speed representations in the CeA. Significance Statement Habits enable efficient behavior but can also become inflexibly maladaptive. Although the neural circuits underlying habitual action execution have been studied extensively, the mechanisms by which outcome feedback reinforces habit formation remain poorly understood. Here, we show that neural activity in the central nucleus of the amygdala evolves with habit development, shifting from representations of choice and reward consumption to reinforcement-related signals during overtraining. Activity reflected outcome magnitude rather than identity, consistent with a role for the central amygdala in reinforcement. We also identify a previously unrecognized population of CeA neurons that track animal running speed. Together, these findings implicate the CeA as a source of reinforcement signals that promote habit formation.
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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".