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The Influence of Somatosensory Cortex on Climbing Fiber Responses in the Lateral Hemispheres of the Rat Cerebellum after Peripheral Tactile Stimulation

2002· article· en· W1586051490 on OpenAlexfundno aff
Ian E. Brown, James M. Bower

Bibliographic record

VenueJournal of Neuroscience · 2002
Typearticle
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsnot available
FundersMedical Research CouncilMedical Research Council CanadaNational Science Foundation
KeywordsClimbing fiberSomatosensory systemNeuroscienceClimbingCerebellumStimulationPsychologySensory stimulation therapyCerebellar cortexAnatomyBiology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.861
Threshold uncertainty score0.245

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.259
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations45
Published2002
Admission routes1
Has abstractyes

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