Serotonin 1A Receptors Alter Expression of Movement Representations
Bibliographic record
Abstract
Serotonin has a myriad of central functions involving mood, appetite, sleep, and memory and while its release within the spinal cord is particularly important for generating movement, the corresponding role on cortical movement representations (motor maps) is unknown. Using adult rats we determined that pharmacological depletion of serotonin (5-HT) via intracerebroventricular administration of 5,7 dihydroxytryptamine resulted in altered movements of the forelimb in a skilled reaching task as well as higher movement thresholds and smaller maps derived using high-resolution intracortical microstimulation (ICMS). We ruled out the possibility that reduced spinal cord excitability could account for the serotonin depletion-induced changes as we observed an enhanced Hoffman reflex (H-reflex), indicating a hyperexcitable spinal cord. Motor maps derived in 5-HT1A receptor knock-out mice also showed higher movement thresholds and smaller maps compared with wild-type controls. Direct cortical application of the 5-HT1A/7 agonist 8-OH-DPAT lowered movement thresholds in vivo and increased map size in 5-HT-depleted rats. In rats, electrical stimulation of the dorsal raphe lowered movement thresholds and this effect could be blocked by direct cortical application of the 5-HT1A antagonist WAY-100135, indicating that serotonin is primarily acting through the 5-HT1A receptor. Next we developed a novel in vitro ICMS preparation that allowed us to track layer V pyramidal cell excitability. Bath application of WAY-100135 raised the ICMS current intensity to induce action potential firing whereas the agonist 8-OH-DPAT had the opposite effect. Together our results demonstrate that serotonin, acting through 5-HT1A receptors, plays an excitatory role in forelimb motor map expression.
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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".