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Record W2792344800 · doi:10.1101/247213

Two distinct proprioceptive representations of voluntary movements in primate spinal neurons

2018· preprint· en· W2792344800 on OpenAlexfundno aff
Saeka Tomatsu, Gee-Hee Kim, Joachim Confais, Tomohiko Takei, Kazuhiko Seki

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2018
Typepreprint
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsnot available
FundersPrecursory Research for Embryonic Science and TechnologyNational Institute for Physiological SciencesJapan Science and Technology AgencyQueen's UniversityNational Institutes of HealthMinistry of Education, Culture, Sports, Science and TechnologyUniversity of Washington
KeywordsProprioceptionNeuroscienceAfferentRepresentation (politics)Sensory systemMovement (music)PrimatePremovement neuronal activitySpike (software development)BiologyPsychologyComputer sciencePhysics

Abstract

fetched live from OpenAlex

Abstract When willingly setting our body in motion, we simultaneously know where and how our limbs are moving. While this indicates that proprioceptive information is readily represented in the neurons of the central nervous system, it is still unclear how. We recorded the activity of spinal neurons with direct projections from muscle spindle afferents in four monkeys, while they performed simple wrist movements. Against the assumption that these spinal neurons act as a simple relay of afferent input, we found the majority (56%) of neurons had firing patterns incongruent with a simple representation of spindle activity, and the minority had congruent patterns. Two groups of neurons showed distinct intrinsic characteristics (spike width, base firing rate and firing irregularity), and distinct control of their input-output gain. These results are the first demonstration that proprioceptive representation is achieved by the coordinated activity of distinct groups of neurons during volitional movement.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.274
Teacher spread0.247 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2018
Admission routes1
Has abstractyes

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