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Record W2129701521 · doi:10.1242/jeb.072637

Recruitment of faster motor units is associated with greater rates of fascicle strain and rapid changes in muscle force during locomotion

2012· article· en· W2129701521 on OpenAlexaff
Sabrina S. M. Lee, Maria de Boef Miara, Allison S. Arnold, Andrew A. Biewener, James M. Wakeling

Bibliographic record

VenueJournal of Experimental Biology · 2012
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsSimon Fraser University
FundersNational Institute of Arthritis and Musculoskeletal and Skin Diseases
KeywordsFascicleMotor unitMotor unit recruitmentElectromyographyStrain (injury)Physical medicine and rehabilitationSonomicrometryTendonAnatomyBiologyMedicineCardiology

Abstract

fetched live from OpenAlex

Animals modulate the power output needed for different locomotor tasks by changing muscle forces and fascicle strain rates. To generate the necessary forces, appropriate motor units must be recruited. Faster motor units have faster activation-deactivation rates than slower motor units, and they contract at higher strain rates; therefore, recruitment of faster motor units may be advantageous for tasks that involve rapid movements or high rates of work. This study identified motor unit recruitment patterns in the gastrocnemii muscles of goats and examined whether faster motor units are recruited when locomotor speed is increased. The study also examined whether locomotor tasks that elicit faster (or slower) motor units are associated with increased (or decreased) in vivo tendon forces, force rise and relaxation rates, fascicle strains and/or strain rates. Electromyography (EMG), sonomicrometry and muscle-tendon force data were collected from the lateral and medial gastrocnemius muscles of goats during level walking, trotting and galloping and during inclined walking and trotting. EMG signals were analyzed using wavelet and principal component analyses to quantify changes in the EMG frequency spectra across the different locomotor conditions. Fascicle strain and strain rate were calculated from the sonomicrometric data, and force rise and relaxation rates were determined from the tendon force data. The results of this study showed that faster motor units were recruited as goats increased their locomotor speeds from level walking to galloping. Slow inclined walking elicited EMG intensities similar to those of fast level galloping but different EMG frequency spectra, indicating that recruitment of the different motor unit types depended, in part, on characteristics of the task. For the locomotor tasks and muscles analyzed here, recruitment patterns were generally associated with in vivo fascicle strain rates, EMG intensity and tendon force. Together, these data provide new evidence that changes in motor unit recruitment have an underlying mechanical basis, at least for certain locomotor tasks.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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

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 head0.048
GPT teacher head0.275
Teacher spread0.226 · 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 designObservational
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

Citations30
Published2012
Admission routes1
Has abstractyes

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