Glutamatergic neurons of the gigantocellular reticular nucleus shape locomotor pattern and rhythm in the freely behaving mouse
Bibliographic record
Abstract
Because of their intermediate position between supraspinal locomotor centers and spinal circuits, gigantocellular reticular nucleus (GRN) neurons play a key role in motor command. However, the functional contribution of glutamatergic GRN neurons in initiating, maintaining, and stopping locomotion is still unclear. Combining electromyographic recordings with optogenetic manipulations in freely behaving mice, we investigate the functional contribution of glutamatergic brainstem neurons of the GRN to motor and locomotor activity. Short-pulse photostimulation of one side of the glutamatergic GRN did not elicit locomotion but evoked distinct motor responses in flexor and extensor muscles at rest and during locomotion. Glutamatergic GRN outputs to the spinal cord appear to be gated according to the spinal locomotor network state. Increasing the duration of photostimulation increased motor and postural tone at rest and reset locomotor rhythm during ongoing locomotion. In contrast, photoinhibition impaired locomotor pattern and rhythm. We conclude that unilateral activation of glutamatergic GRN neurons triggered motor activity and modified ongoing locomotor pattern and rhythm.
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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 | 0.000 |
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".