Dopamine and Pain Sensitivity: Neither Sulpiride nor Acute Phenylalanine and Tyrosine Depletion Have Effects on Thermal Pain Sensations in Healthy Volunteers
Bibliographic record
Abstract
Based on animal studies and some indirect clinical evidence, dopamine has been suggested to have anti-nociceptive effects. Here, we investigated directly the effects of increased and decreased availability of extracellular dopamine on pain perception in healthy volunteers. In Study 1, participants ingested, in separate sessions, a placebo and a low dose of the centrally acting D2-receptor antagonist sulpiride, intended to increase synaptic dopamine via predominant pre-synaptic blockade. No effects were seen on thermal pain thresholds, tolerance, or temporal summation. Study 2 used the acute phenylalanine and tyrosine depletion (APTD) method to transiently decrease dopamine availability. In one session participants ingested a mixture that depletes the dopamine amino acid precursors, phenylalanine and tyrosine. In the other session they ingested a nutritionally balanced control mixture. APTD led to a small mood-lowering response following aversive thermal stimulation, but had no effects on the perception of cold, warm, or pain stimuli. In both studies the experimental manipulation of dopaminergic neurotransmission was successful as indicated by manipulation checks. The results contradict proposals that dopamine has direct anti-nociceptive effects in acute experimental pain. Based on dopamine's well-known role in reward processing, we hypothesize that also in the context of pain, dopamine acts on stimulus salience and might play a role in the initiation of avoidance behavior rather than having direct antinociceptive effects in acute experimental pain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.003 | 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".