65 years of research on dopamine's role in classical fear conditioning and extinction: A systematic review
Bibliographic record
Abstract
Abstract Dopamine, a catecholamine neurotransmitter, has historically been associated with the encoding of reward, whereas its role in aversion has received less attention. Here, we systematically gathered the vast evidence of the role of dopamine in the simplest forms of aversive learning: classical fear conditioning and extinction. In the past, crude methods were used to augment or inhibit dopamine to study its relationship with fear conditioning and extinction. More advanced techniques such as conditional genetic, chemogenic and optogenetic approaches now provide causal evidence for dopamine's role in these learning processes. Dopamine neurons encode conditioned stimuli during fear conditioning and extinction and convey the signal via activation of D 1–4 receptor sites particularly in the amygdala, prefrontal cortex and striatum. The coordinated activation of dopamine receptors allows for the continuous formation, consolidation, retrieval and updating of fear and extinction memory in a dynamic and reciprocal manner. Based on the reviewed literature, we conclude that dopamine is crucial for the encoding of classical fear conditioning and extinction and contributes in a way that is comparable to its role in encoding reward.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".