Contribution of Decreased Serotonin Release to the Antidyskinetic Effects of Deep Brain Stimulation in a Rodent Model of Tardive Dyskinesia: Comparison of the Subthalamic and Entopeduncular Nuclei
Bibliographic record
Abstract
Mechanisms whereby deep brain stimulation (DBS) of the subthalamic nucleus (STN) or internal globus pallidus (GPi) reduces dyskinesias remain largely unknown. Using vacuous chewing movements (VCMs) induced by chronic haloperidol as a model of tardive dyskinesia (TD) in rats, we confirmed the antidyskinetic effects of DBS applied to the STN or entopeduncular nucleus (EPN, the rodent homolog of the GPi). We conducted a series of experiments to investigate the role of serotonin (5-HT) in these effects. We found that neurotoxic lesions of the dorsal raphe nuclei (DRN) significantly decreased HAL-induced VCMs. Acute 8-OH-DPAT administration, under conditions known to suppress raphe neuronal firing, also reduced VCMs. Immediate early gene mapping using zif268 in situ hybridization revealed that STN-DBS inhibited activity of DRN and MRN neurons. Microdialysis experiments indicated that STN-DBS decreased 5-HT release in the dorsolateral caudate-putamen, an area implicated in the etiology of HAL-induced VCMs. DBS applied to the EPN also suppressed VCMs but did not alter 5-HT release or raphe neuron activation. While these findings suggested a role for decreased 5-HT release in the mechanisms of STN DBS, further microdialysis experiments showed that when the 5-HT lowering effects of STN DBS were prevented by pretreatment with fluoxetine or fenfluramine, the ability of DBS to suppress VCMs remained unaltered. These results suggest that EPN- and STN-DBS have different effects on the 5-HT system. While decreasing 5-HT function is sufficient to suppress HAL-induced VCMs, 5-HT decrease is not necessary for the beneficial motor effects of DBS in this model.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".