Serotonin depletion impairs both Pavlovian and instrumental reversal learning in healthy humans
Bibliographic record
Abstract
Serotonin is involved in updating responses to changing environmental circumstances. Optimising behaviour to maximise reward and minimise punishment may require shifting strategies upon encountering new situations. Likewise, autonomic responses to threats are critical for survival yet must be modified as danger shifts from one source to another. Whilst numerous psychiatric disorders are characterised by behavioural and autonomic inflexibility, few studies have examined the contribution of serotonin in humans. We modelled both processes, respectively, in two independent experiments (N = 97). Experiment 1 assessed instrumental (stimulus-response-outcome) reversal learning whereby individuals learned through trial and error which action was most optimal for obtaining reward or avoiding punishment initially, and the contingencies subsequently reversed serially. Experiment 2 examined Pavlovian (stimulus-outcome) reversal learning assessed by the skin conductance response: one innately threatening stimulus predicted receipt of an uncomfortable electric shock and another did not; these contingencies swapped in a reversal phase. Upon depleting the serotonin precursor tryptophan-in a double-blind randomised placebo-controlled design-healthy volunteers showed impairments in updating both actions and autonomic responses to reflect changing contingencies. Reversal deficits in each domain, furthermore, were correlated with the extent of tryptophan depletion. Initial Pavlovian conditioning, moreover, which involved innately threatening stimuli, was potentiated by depletion. These results translate findings in experimental animals to humans and have implications for the neurochemical basis of cognitive inflexibility.
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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) | 0.001 | 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".