A Brainstem Neural Substrate for Stopping Locomotion
Bibliographic record
Abstract
Locomotion occurs sporadically and needs to be started, maintained, and stopped. The neural substrate underlying the activation of locomotion is partly known, but little is known about mechanisms involved in termination of locomotion. Recently, reticulospinal neurons (stop cells) were found to play a crucial role in stopping locomotion in the lamprey: their activation halts ongoing locomotion and their inactivation slows down the termination process. Intracellular recordings of these cells revealed a distinct activity pattern, with a burst of action potentials at the beginning of a locomotor bout and one at the end (termination burst). The termination burst was shown to be time linked to the end of locomotion, but the mechanisms by which it is triggered have remained unknown. We studied this in larval sea lampreys (Petromyzon marinus; the sex of the animals was not taken into account). We found that the mesencephalic locomotor region (MLR), which is known to initiate and control locomotion, stops ongoing locomotion by providing synaptic inputs that trigger the termination burst in stop cells. When locomotion is elicited by MLR stimulation, a second MLR stimulation stops the locomotor bout if it is of lower intensity than the initial stimulation. This occurs for MLR-induced, sensory-evoked, and spontaneous locomotion. Furthermore, we show that glutamatergic and, most likely, monosynaptic projections from the MLR activate stop cells during locomotion. Therefore, activation of the MLR not only initiates locomotion, but can also control the end of a locomotor bout. These results provide new insights onto the neural mechanisms responsible for stopping locomotion. SIGNIFICANCE STATEMENTThe mesencephalic locomotor region (MLR) is a brainstem region well known to initiate and control locomotion. Since its discovery in cats in the 1960s, the MLR has been identified in all vertebrate species tested from lampreys to humans. We now demonstrate that stimulation of the MLR not only activates locomotion, but can also stop it. This is achieved through a descending glutamatergic signal, most likely monosynaptic, from the MLR to the reticular formation that activates reticulospinal stop cells. Together, our findings have uncovered a neural mechanism for stopping locomotion and bring new insights into the function of the MLR.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".