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Enregistrement W1993791452 · doi:10.1113/jphysiol.2011.220525

Tendon vibration does not alter decreased responsiveness of motoneurones in the absence of motor cortical input during fatigue

2011· letter· en· W1993791452 sur OpenAlexaff
Brad Harwood, Geoffrey A. Power, Matti D. Allen, William J. Booth

Notice bibliographique

RevueThe Journal of Physiology · 2011
Typeletter
Langueen
DomaineEngineering
ThématiqueMuscle activation and electromyography studies
Établissements canadiensWestern University
Organismes subventionnairesnon disponible
Mots-clésInhibitory postsynaptic potentialNeuroscienceExcitatory postsynaptic potentialPhysical medicine and rehabilitationMuscle fatigueSpinal cordStimulus (psychology)ElectromyographyPeripheralStimulationMedicinePsychologyInternal medicine

Résumé

récupéré en direct d'OpenAlex

Fatigue, defined as any exercise-induced reduction in the ability to generate muscle force or power, is task dependent and multifaceted in that both central and peripheral contributing factors to fatigue vary depending on the activity performed (Taylor & Gandevia, 2008). Therefore, identifying the potential site(s) of fatigue is of substantial importance in understanding the underlying mechanisms. The pioneering work of Merton (1954) concluded that the primary site of fatigue was peripheral, and central mechanisms do not contribute. Percutaneous electrical stimulation was applied to the ulnar nerve during a fatiguing maximal voluntary effort of the adductor pollicis resulting in no additional force output. In other words, the mechanical response to the electrical stimulus, the twitch, was ‘occluded’ or blocked indicating complete voluntary activation in a fatigued state. However, this technique does not permit assessment of the descending drive reaching the motoneurones and thus may not accurately reflect fatigue-induced alterations in voluntary drive. More recently, fatigue-associated changes to several supraspinal and spinal factors have been proposed as contributors to the development and recovery from, fatigue. Supraspinal factors include: inhibitory inputs within and between the motor cortices, and among other brain regions (Taylor & Gandevia, 2008). Spinal factors consist of excitatory and inhibitory inputs that converge onto the spinal cord above, and at the level of the motoneurone innervating the muscle group(s) of interest. Group I, II, III and IV afferents can provide excitatory and inhibitory inputs to the homonymous α and γ motoneurone pool. Increases of metabolic by-products, temperature and tension that occur with high-intensity fatigue may attenuate excitatory input from muscle afferents, or alternatively, contribute an inhibitory input to the motoneurones (Taylor & Gandevia, 2008). Furthermore, intrinsic motoneurone adaptation during sustained maximal voluntary isometric contraction (MVC) reduces motor output (Taylor & Gandevia, 2008). Despite the emergence of new techniques and methodologies, the site(s) responsible for central nervous system impairments during fatigue are unclear; however, the study we reviewed (McNeil et al. 2011) may provide new insight regarding influential factors of motoneurone responsiveness during high-intensity fatigue. Transcranial magnetic stimulation (TMS) of the motor cortex evokes a short latency electromyographic (EMG) response known as a motor evoked potential (MEP), followed by a silent period (SP) in the EMG recording when delivered during a MVC. By electrically stimulating the corticospinal pathway at the level of the mastoid processes, a cervicomedullary motor evoked potential (CMEP) is recorded at the muscle level. The relative contribution of supraspinal and spinal factors to fatigue can be inferred from a comparison of these two (MEP and CMEP) evoked potentials. During exercise, an increase in the area of the MEP response relative to the CMEP suggests an increase in motor cortex excitability, whereas a lengthening of the SP following delivery of TMS indicates intracortical inhibition. In a recent study, McNeil et al. (2009) observed similar increases in MEP and CMEP area in the biceps brachii early during a sustained 2 min MVC followed by a decrease in CMEP area (∼20%) and no decrease in MEP area in the final 30 s. The maintained MEP and decreased CMEP suggest a spinal mechanism is responsible for the reduction in motoneurone excitability during a maximal sustained fatiguing contraction (McNeil et al. 2009). However, this study also demonstrated the masking effect of descending drive on CMEP area by eliciting MEPs and CMEPs during unconditioned and conditioned states (McNeil et al. 2009). An unconditioned response is elicited while descending drive is intact, whereas a conditioned response is elicited during the SP following a conditioning stimulus (an initial TMS used to generate a SP) in which very little activity in background EMG is observed. McNeil et al. (2009) reported a near obliteration of the MEP and CMEP during a sustained MVC within 30 s when recorded during the SP implying a reduction in motoneurone excitability as the principal contributor to reduced motor output in the absence of voluntary drive. However, the origin of a reduction in motoneurone excitability was less certain. The two leading hypotheses explaining fatigue at the motoneurone level in the SP during sustained MVC are the dysfacilitation of Ia and II afferent input from the muscle spindle, and intrinsic motoneurone adaptation (McNeil et al. 2009). Repetitive discharge of the motoneurone is believed to cause increased cation-activated potassium leak conductance (Button et al. 2007) reducing the responsiveness of motoneurones: termed motoneurone adaptation. Intrinsic motoneurone adaptation has been demonstrated directly in animals (Button et al. 2007) and indirectly in humans (Carpentier et al. 2001). Muscle spindle dysfacilitation and motoneurone adaptation served as the impetus for a recent study in The Journal of Physiology by McNeil et al. (2011). The study used TMS of the motor cortex and subcortical transmastoid electrical stimulation of the corticospinal tract in the presence and absence of tendon vibration to determine whether increased afferent input to the motoneurone pool postpones the reduction, and preserves the size, of conditioned CMEPs. The study consisted of two protocols, one investigating MEPs and the other investigating CMEPs. Both protocols used a conditioning stimulus (TMS) preceding a second stimulus (either TMS or transmastoid electrical stimulation) to elicit conditioned responses (conditioned MEPs or CMEPs, respectively). Each protocol began with participants performing 12 brief MVCs with either paired motor cortical–corticospinal or motor cortical–motor cortical stimuli with and without vibration. These MVCs provided control values for the normalization of subsequent conditioned MEPs and CMEPs. Tendon vibration was applied to the skin over the distal biceps tendon at ∼80 Hz using a handheld pneumatic vibrator to increase the level of Ia excitatory input from muscle spindles. Following the initial control MVCs, participants began a sustained MVC of the elbow flexors for 2 min. During the fatigue protocol, single (motor cortical or corticospinal) and paired (motor cortical-corticospinal or motor cortical-motor cortical) stimuli were delivered in an alternating fashion every 5 s beginning at 5 s in the presence and absence of tendon vibration. McNeil et al. (2011) used an experimentally tested “optimal frequency” range of vibration to elicit reflexes in the relaxed muscle and to increase torque during a sustained MVC. Tendon vibration, however, did not affect the size of conditioned MEPs or CMEPs during brief MVCs prior to the fatigue task. The inability to generate a facilitation of the conditioned MEPs and CMEPs using a 10 s, 80 Hz mechanical vibration of the muscle tendon during non-fatiguing contractions is surprising and questions the efficacy of the vibratory stimulus in this protocol. The sustained (fatiguing) 2 min MVC resulted in large, equivalent reductions of the conditioned MEPs and CMEPs independent of whether tendon vibration was applied. Similar reductions in conditioned MEPs and CMEPs were reported by the same authors in the absence of tendon vibration (McNeil et al. 2009). Despite the potential concerns associated with the vibratory stimulus, McNeil et al. (2011) suggested that the reduction in motoneurone excitability was a consequence of motoneurone adaptation, and not the result of reduced afferent input as a result of muscle spindle dysfacilitation. Motoneurone adaptation is closely related to many common characteristics of large motoneurones innervating fast motor units including high rheobase and low input resistance (Button et al. 2007). An increased cation concentration in the motoneurone is also the impetus for the opening of channels responsible for the activation of the persistent inward current, which greatly increases the gain of the current–frequency relationship of motoneurones. Thus, the same stimulus responsible for facilitation of motor output may also be responsible for the fatigue-associated declines in motoneurone excitability during sustained MVCs. Considering the task in the present study was performed maximally, one may assume all motoneurones in the motoneurone pool were active. With this in mind, the rapid, sizeable decline in motoneurone excitability is likely to be partially related to the changes in large motoneurone excitability. The biceps brachii is composed of near equal distribution of slow and fast motoneurones. Considering slow motoneurones are more sensitive to Ia afferent input, it is possible that a muscle with a slower motor unit composition may exhibit a heightened response to tendon vibration. To test this hypothesis, a muscle composed primarily of slow motoneurones, such as the soleus, could be investigated. The authors would like to acknowledge Dr Charles Rice for his valuable comments and assistance with this manuscript.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,004
Score d'incertitude au seuil0,014

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,020
Tête enseignante GPT0,238
Écart entre enseignants0,217 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2011
Routes d'admission1
Résumé présentoui

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