Rhythmic activity of feline dorsal and ventral spinocerebellar tract neurons during fictive motor actions
Bibliographic record
Abstract
Neurons of the dorsal spinocerebellar tracts (DSCT) have been described to be rhythmically active during walking on a treadmill in decerebrate cats, but this activity ceased following deafferentation of the hindlimb. This observation supported the hypothesis that DSCT neurons primarily relay the activity of hindlimb afferents during locomotion, but lack input from the spinal central pattern generator. The ventral spinocerebellar tract (VSCT) neurons, on the other hand, were found to be active during actual locomotion (on a treadmill) even after deafferentation, as well as during fictive locomotion (without phasic afferent feedback). In this study, we compared the activity of DSCT and VSCT neurons during fictive rhythmic motor behaviors. We used decerebrate cat preparations in which fictive motor tasks can be evoked while the animal is paralyzed and there is no rhythmic sensory input from hindlimb nerves. Spinocerebellar tract cells with cell bodies located in the lumbar segments were identified by electrophysiological techniques and examined by extra- and intracellular microelectrode recordings. During fictive locomotion, 57/81 DSCT and 30/30 VSCT neurons showed phasic, cycle-related activity. During fictive scratch, 19/29 DSCT neurons showed activity related to the scratch cycle. We provide evidence for the first time that locomotor and scratch drive potentials are present not only in VSCT, but also in the majority of DSCT neurons. These results demonstrate that both spinocerebellar tracts receive input from the central pattern generator circuitry, often sufficient to elicit firing in the absence of sensory input.
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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) | 0.000 | 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".