Cholinergic Modulation of Locomotor Circuits in Vertebrates
Bibliographic record
Abstract
Locomotion is a basic motor act essential for survival. Amongst other things, it allows animals to move in their environment to seek food, escape predators, or seek mates for reproduction. The neural mechanisms involved in the control of locomotion have been examined in many vertebrate species and a clearer picture is progressively emerging. The basic muscle synergies responsible for propulsion are generated by neural networks located in the spinal cord. In turn, descending supraspinal inputs are responsible for starting, maintaining, and stopping locomotion as well as for steering and controlling speed. Several neurotransmitter systems play a crucial role in modulating the neural activity during locomotion. For instance, cholinergic inputs act both at the spinal and supraspinal levels and the underlying mechanisms are the focus of the present review. Much information gained on supraspinal cholinergic modulation of locomotion was obtained from the lamprey model. Nicotinic cholinergic inputs increase the level of excitation of brainstem descending command neurons, the reticulospinal neurons (RSNs), whereas muscarinic inputs activate a select group of hindbrain neurons that project to the RSNs to boost their level of excitation. Muscarinic inputs also reduce the transmission of sensory inputs in the brainstem, a phenomenon that could help in sustaining goal directed locomotion. In the spinal cord, intrinsic cholinergic inputs strongly modulate the activity of interneurons and motoneurons to control the locomotor output. Altogether, the present review underlines the importance of the cholinergic inputs in the modulation of locomotor activity in vertebrates.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".