Instigation and control of treadmill locomotion in high decerebrate cats by stimulation of the hook bundle of Russell in the cerebellum
Bibliographic record
Abstract
In high decerebrate cats, pulse train microstimulation of a restricted region of the midline cerebellar white matter produced a generalized increase in postural muscle tone in the neck, trunk, and limb extensor muscles, and air-stepping of all four legs on a stationary surface. On the moving belt of a treadmill, such stimulation produced well coordinated, fore- and hindlimb locomotion as evoked by stimulating the mesencephalic locomotor region (MLR). Microinjection of a neural tracer into the cerebellar locomotion-inducing site resulted in a bilateral retrograde labeling of cells limited to the fastigial nuclei simultaneously with anterograde labeling of fibers projecting bilaterally to the medial pontomedullary reticular formation (mPMRF) the vestibular complex and upper cervical segments. These results have led to our proposition that the effective cerebellar locomotor region (CLR) corresponds to the midline region of the hook bundle of Russell. Passing through this structure are crossed fastigioreticular and fastigiovestibular fibers, together with fastigiospinal fibers. Subsequently, we showed that CLR stimulation resulted in simultaneous short-latency synaptic activation of long-descending reticulospinal and vestibulospinal cells with high synaptic security. Clearly, the fastigial nucleus possesses potential capability to recruit and regulate posture- and locomotor-related subprograms which are distributed within the brainstem and spinal cord by the in-parallel activation of fastigiospinal, fastigioreticular, and fastigiovestibular pathways.Key words: cerebellar locomotor region (CLR), fastigial nucleus, hook bundle of Russell, reticulospinal cell, vestibulospinal cell.
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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) | 0.001 | 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".