Serotonergic Modulation of Locomotor Activity From Basal Vertebrates to Mammals
Bibliographic record
Abstract
During the last 50 years, the serotonergic (5-HT) system was reported to exert a complex modulation of locomotor activity. Here, we focus on two key factors that likely contribute to such complexity. First, locomotion is modulated directly and indirectly by 5-HT neurons. The locomotor circuitry is directly innervated by 5-HT neurons in the caudal brainstem and spinal cord. Also, indirect control of locomotor activity results from ascending projections of 5-HT cells in the rostral brainstem that innervate multiple brain centers involved in motor action planning. Second, each approach used to manipulate the 5-HT system likely engages different 5-HT-dependent mechanisms. This includes the recruitment of different 5-HT receptors, which can have excitatory or inhibitory effects on cell activity. These receptors can be located far or close to the 5-HT release sites, making their activation dependent on the level of 5-HT released. Here we review the activity of different 5-HT nuclei during locomotor activity, and the locomotor effects of 5-HT precursors, exogenous 5-HT, selective 5-HT reuptake inhibitors (SSRI), electrical or chemical stimulation of 5-HT neurons, genetic deletions, optogenetic and chemogenetic manipulations. We highlight both the coherent and controversial aspects of 5-HT modulation of locomotor activity from basal vertebrates to mammals. This mini review may hopefully inspire future studies aiming at dissecting the complex effects of 5-HT on locomotor function.
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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) | 0.002 | 0.001 |
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".