The Influence of Somatosensory Cortex on Climbing Fiber Responses in the Lateral Hemispheres of the Rat Cerebellum after Peripheral Tactile Stimulation
Bibliographic record
Abstract
This report describes the temporal relationship between the latency of responses to peripheral stimulation in primary somatosensory (SI) cerebral cortex and the timing of climbing fiber inputs to the lateral hemispheres of the rat cerebellum. Examined in the tactilely responsive regions of crus IIa in the rat, the results show that SI influences the timing of both evoked and spontaneous climbing fiber activity in these cerebellar regions without affecting the rate or probability of complex spike discharge. By reversibly blocking SI activity, we demonstrate that the absence of cortical input results in a lengthening of climbing fiber response latency to peripheral stimuli. Similarly, enhancing the cortical input by subthreshold electrical stimulation of SI results in a shortening of climbing fiber response latency. These results provide a new explanation for the tendency of the inferior olive to oscillate at 7-12 Hz and is consistent with the hypothesis that the inferior olive provides the cerebellum information about the timing of cortical computational cycles. Results are discussed in the context of previous and current hypotheses concerning the physiology and function of the inferior olive/climbing fiber system and are interpreted to provide additional evidence of a role for the cerebellum in the tactile somatosensory system.
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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".