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Record W2071902994 · doi:10.1139/y04-045

Somatosensory paths proceeding to spinal cord and brain — centripetal and centrifugal control for human movement

2004· review· en· W2071902994 on OpenAlexvenueno aff
J. D. Brooke

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2004
Typereview
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsSomatosensory systemNeuroscienceReflexSpinal cordSomatosensory evoked potentialMotor controlSensory systemPsychology

Abstract

fetched live from OpenAlex

The flow of fast-conducting somatosensory information proceeding from the human leg, and entering sensorimotor control processes, is modulated according to the demands of limb movement. Both centripetal (proceeding in from sensory receptor discharge) and centrifugal (proceeding out from motor control centres) convergences can cause modulation, as seen in human, dog, and cat studies. Spinal H-reflexes appear to be strongly centripetally modulated in magnitude, as do initial somatosensory-evoked potentials recorded from the scalp following transmission in fast-conducting afferents from the leg. From the brain and from locomotor pattern-generators, there is also centrifugal control onto fast-conducting somatosensory pathways from the leg, both serving spinal reflexes and ascending to the brain. One expression of the centrifugal control appears to be pattern-generator modulation of cutaneous reflexes. Centrifugal control also can be seen premovement, as spinal H-reflex facilitation. Further, it can be observed as reduction of reception at somatosensory cerebral cortex, when motor learning has occurred or when stimuli are less salient for the task. Fourteen research developments have been identified that involve the generalizability of effects, specific mechanisms, and somatosensory modulation in predictive control.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.945
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.045
GPT teacher head0.339
Teacher spread0.293 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations14
Published2004
Admission routes1
Has abstractyes

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