Descending Signals From the Pontomedullary Reticular Formation Are Bilateral, Asymmetric, and Gated During Reaching Movements in the Cat
Bibliographic record
Abstract
We examined the contribution of neurons within the pontomedullary reticular formation (PMRF) to the control of reaching movements in the cat. We recorded the activity of 127 reticular neurons, including 56 reticulospinal neurons, during movements of each forelimb; 67/127 of these neurons discharged prior to the onset of activity in the prime flexor muscles during the reach of the ipsilateral limb and form the focus of this report. Most neurons (63/67) showed similar patterns and levels of discharge activity during reaches of either limb, although activity was slightly greater during reach of the ipsilateral limb. In 26/67 cells, the initial change in discharge activity was time-locked to the go signal during reaches of either limb; we have argued that this early discharge contributes to the anticipatory postural adjustments that precede movement. In 11/26 cells, the initial change in activity was reciprocal for reaches with the left and right limbs, although activity during the movement was nonreciprocal. Spike-triggered averaging produced postspike facilitation or depression (PSD) in 12/50 cells during reaches of the limb ipsilateral to the recording site and in 17/49 cells during reach of the contralateral limb. Some cells produced PSD in ipsilateral extensor muscles before the start of the reach and during reaches made with the contralateral, but not the ipsilateral limb; this suggests the signal must be differentially gated. Overall, the results suggest a strong bilateral, albeit asymmetric, contribution from the PMRF to the control of posture and movement during voluntary movement.
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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 | 0.001 |
| 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) | 0.001 | 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".