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Record W2903465385 · doi:10.1113/jp277018

Spinal control of muscle synergies for adult mammalian locomotion

2018· article· en· W2903465385 on OpenAlexafffund
Étienne Desrochers, Jonathan Harnie, Adam Doelman, Marie‐France Hurteau, Alain Frigon

Bibliographic record

VenueThe Journal of Physiology · 2018
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsSpinal cordAnatomyTreadmillMotor unit recruitmentElectromyographyNeurosciencePhysical medicine and rehabilitationMotor controlCATSMedicineBiologyPhysical therapy

Abstract

fetched live from OpenAlex

KEY POINTS: The control of locomotion is thought to be generated by activating groups of muscles that perform similar actions, which are termed muscle synergies. Here, we investigated if muscle synergies are controlled at the level of the spinal cord. We did this by comparing muscle activity in the legs of cats during stepping on a treadmill before and after a complete spinal transection that abolishes commands from the brain. We show that muscle synergies were maintained following spinal transection, validating the concept that muscle synergies for locomotion are primarily controlled by circuits of neurons within the spinal cord. ABSTRACT: Locomotion is thought to involve the sequential activation of functional modules or muscle synergies. Here, we tested the hypothesis that muscle synergies for locomotion are organized within the spinal cord. We recorded bursts of muscle activity in the same cats (n = 7) before and after spinal transection during tied-belt locomotion at three speeds and split-belt locomotion at three left-right speed differences. We identified seven muscles synergies before (intact state) and after (spinal state) spinal transection. The muscles comprising the different synergies were the same in the intact and spinal states as well as at different speeds or left-right speed differences. However, there were some significant shifts in the onsets and offsets of certain synergies as a function of state, speed and left-right speed differences. The most notable difference between the intact and spinal states was a change in the timing between the knee flexor and hip flexor muscle synergies. In the intact state, the knee flexor synergy preceded the hip flexor synergy, whereas in the spinal state both synergies occurred concurrently. Afferent inputs also appear important for the expression of some muscle synergies, specifically those involving biphasic patterns of muscle activity. We propose that muscle synergies for locomotion are primarily organized within the spinal cord, although their full expression and proper timing requires inputs from supraspinal structures and/or limb afferents.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score0.157

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.010
GPT teacher head0.233
Teacher spread0.223 · 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

Citations60
Published2018
Admission routes2
Has abstractyes

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