Dopaminergic Plasticity in the Bilateral Hippocampus Following Threat Reversal in Humans
Bibliographic record
Abstract
Abstract When a cue no longer predicts a threat, a diminished ability to extinguish or reverse this association is thought to increase risk for stress-related disorders. Despite the clear clinical relevance, the mediating neurochemical mechanisms of threat reversal have received relatively little study. One neurotransmitter implicated in rodent research of changing associations with threat is dopamine. To study whether dopamine is involved in threat reversal in humans, we used high-resolution positron emission tomography (PET) coupled with 18F-fallypride. Twelve healthy volunteers (6 F/6 M) underwent three PET scans: (i) at baseline, (ii) following threat conditioning (the response to a cue associated with electric wrist shock), and (iii) following threat reversal (the response to the same cue now associated with safety). We observed moderate evidence of reduced dopamine D2/3 receptor availability, consistent with greater dopamine release, in the bilateral anterior hippocampus following threat reversal, in response to a safety cue that was previously associated with threat, as compared to both baseline and during exposure to the same cue prior to threat reversal. These findings offer the first preliminary evidence that the response to a previously threatening cue that has since become associated with safety involves dopaminergic neurotransmission within the hippocampus in healthy humans.
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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 | 0.001 |
| 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".