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Record W2890506629 · doi:10.3389/fphys.2018.01266

Intermediate Muscle Length and Tendon Vibration Optimize Corticospinal Excitability During Knee Extensors Local Vibration

2018· article· en· W2890506629 on OpenAlexaff
Robin Souron, Marie Oriol, Guillaume Y. Millet, Thomas Lapole

Bibliographic record

VenueFrontiers in Physiology · 2018
Typearticle
Languageen
FieldMedicine
TopicEffects of Vibration on Health
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsVastus medialisMedicineTendonPhysical medicine and rehabilitationElectromyographyAnatomy

Abstract

fetched live from OpenAlex

While local vibration (LV) has been recently proposed as a potential modality for neuromuscular conditioning, no practical recommendations to optimize its effects have been published. Because changes in corticospinal excitability may reflect at which degree the neuromuscular function is modulated during LV exposure, this study investigated the effects of muscle length and vibration site on LV-induced on motor evoked potentials (MEPs) changes. Twenty-one subjects participated in a single session in which MEPs were evoked on the relaxed knee extensors (KE) during three conditions, i.e. no vibration (CON), muscle (VIBMU) and tendon vibration (VIBTD). Three muscle lengths were tested for each condition, i.e. short/intermediate/long KE muscle length. Both VIBMU and VIBTD significantly increase MEPs compared to CON. Higher increases (P < 0.001) were found for VIBTD compared to VIBMU for vastus lateralis (mean increases of the three angles: + 241% vs. + 148%), vastus medialis (+ 273% vs. + 180%) and rectus femoris muscles (+ 191% vs. + 141%). The increase in MEPs amplitude was higher (p < 0.001) at an intermediate (mean pooled increase for VIBTD and VIBMU: + 265%, + 290% and + 212% for VL, VM and RF, respectively) compared to short (+ 136%, + 144% and + 127%) or long (+ 184%, + 246% and + 160%) muscle lengths. These results suggest that LV should be applied to the tendon at an intermediate muscle length to optimize the acute effects of LV on the KE neuromuscular function.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.871
Threshold uncertainty score0.749

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 studies0.0000.001
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 head0.009
GPT teacher head0.268
Teacher spread0.259 · 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 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

Citations11
Published2018
Admission routes1
Has abstractyes

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