Functional coupling of the mesencephalic locomotor region and V2a reticulospinal neurons driving forward locomotion
Bibliographic record
Abstract
Abstract Locomotion in vertebrates relies on high brain centers converging onto the mesencephalic locomotor region (MLR). How the MLR recruits brainstem reticulospinal neurons (RSNs) to initiate locomotion is incompletely understood due to the challenge of recording these cells in vivo. To tackle this question, we leveraged the transparency and genetic accessibility of larval zebrafish. In this model organism, we uncovered the locus of the MLR as a small region dorsal to the locus coeruleus containing glutamatergic and cholinergic neurons. MLR stimulations reliably elicited forward bouts of controlled duration and speed. We find that the MLR elicits forward locomotion by recruiting V2a RSNs in the pontine and retropontine regions, and gradually in the medulla. Remarkably, recruited V2a RSNs in the medulla act as maintain cells encoding speed of forward locomotion. Altogether, our study reveals that the MLR recruits genetically-identified reticulospinal neurons in the medulla to control the kinematics of exploration.
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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 | 0.000 |
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".