Antagonist Muscle Prefatigue Increases the Intracortical Communication between Contralateral Motor Cortices during Elbow Extension Contraction

Halo Sport Transcranial Direct Current Stimulation Improved Muscular Endurance Performance and Neuromuscular Efficiency During an Isometric Submaximal Fatiguing Elbow Flexion Task

The present study examined the effects of transcranial direct current stimulation (tDCS) using Halo Sport on the time to exhaustion (TTE) in relation with muscle activities and corticomuscular coupling of agonist and antagonist muscles during a sustained isometric fatiguing contraction performed with the elbow flexors. Twenty healthy male college students were randomly assigned to tDCS group and control group. The two group participants performed two experimental sessions which consisted of pre-fatigue isometric maximal voluntary contraction (MVC), sustained submaximal voluntary contractions (30% maximal torque) performed to exhaustion, and post-fatigue MVC with the right elbow flexor muscles. Sham stimulation (90 s) and tDCS (20 min) were applied for control and tDCS group participants 20 min prior to the second session test, respectively. MVC strength in pre- and post-fatigue test, TTE, electroencephalogram (EEG), and electromyography (EMG) of biceps brachii (BB) and triceps brachii (TB) were recorded during the tests. It was found that tDCS using the Halo Sport device significantly increased TTE and thus improved muscular endurance performance. The improvement may be partly related to the improvement of neuromuscular efficiency as reflected by decrease of antagonistic muscle coactivation activities, which may be related to cortical originated central processing mechanism of neuromuscular activities.

Directed Information Flow Analysis Reveals Muscle Fatigue-Related Changes in Muscle Networks and Corticomuscular Coupling

As a common neurophysiological phenomenon, voluntary muscle fatigue is accompanied by changes in both the central nervous system and peripheral muscles. Considering the effectiveness of the muscle network and the functional corticomuscular coupling (FCMC) in analyzing motor function, muscle fatigue can be analyzed by quantitating the intermuscular coupling and corticomuscular coupling. However, existing coherence-based research on muscle fatigue are limited by the inability of the coherence algorithm to identify the coupling direction, which cannot further reveal the underlying neural mechanism of muscle fatigue. To address this problem, we applied the time-delayed maximal information coefficient (TDMIC) method to quantitate the directional informational interaction in the muscle network and FCMC during a right-hand stabilized grip task. Eight healthy subjects were recruited to the present study. For the muscle networks, the beta-band information flow increased significantly due to muscle fatigue, and the information flow between the synergist muscles were stronger than that between the synergist and antagonist muscles. The information flow in the muscle network mainly flows to flexor digitorum superficialis (FDS), flexor carpi ulnar (FCU), and brachioradialis (BR). For the FCMC, muscle fatigue caused a significant decrease in the beta- and gamma-band bidirectional information flow. Further analysis revealed that the beta-band information flow was significantly stronger in the descending direction [electroencephalogram (EEG) to surface electromyography (sEMG)] than that in the ascending direction (sEMG to EEG) during pre-fatigue tasks. After muscle fatigue, the beta-band information flow in the ascending direction was significantly stronger than that in the descending direction. The present study demonstrates the influence of muscle fatigue on information flow in muscle networks and FCMC. We proposes that beta-band intermuscular and corticomuscular informational interaction plays an adjusting role in autonomous movement completion under muscle fatigue. Directed information flow analysis can be used as an effective method to explore the neural mechanism of muscle fatigue on the macroscopic scale.

Antagonistic muscle prefatigue weakens the functional corticomuscular coupling during isometric elbow extension contraction

OBJECTIVE

During muscle fatigue, acute changes in the interaction between the sensorimotor cortex and peripheral neurons have been widely studied. However, it is still unclear about the effect of antagonist muscle prefatigue on corticomuscular coupling and central modulation. The purpose of this study was to investigate the changes in the magnitude of electroencephalogram-electromyography (EEG-EMG) coherence and phase synchronization index (PSI) induced by antagonistic muscle prefatigue.

METHODS

Twelve young male volunteers conducted a 30-s long, nonfatiguing isometric elbow extension with a target force level of 20% maximum voluntary contraction (MVC) before and after a fatiguing sustained elbow flexion contraction at 20% MVC until task failure. Coherence and PSI between the EEG recorded over the sensorimotor cortex and the surface EMG of the triceps brachii (TB) muscle were quantified for the pre- and post-fatigue elbow extension contractions.

RESULTS

Coherence and PSI in the gamma frequency band (35-60 Hz) were found significantly decreased in the postfatigue elbow extension contraction than the prefatigue contraction. The power of the EEG in the beta and gamma band were significantly increased, while the EMG power showed no significant changes when the antagonistic muscle was prefatigued. PSI in the gamma frequency band between the EMG of the TB muscle and the EEG were found significantly decreased during postfatigue elbow extension contraction compared with prefatigue contraction.

CONCLUSION

Antagonistic muscle prefatigue led to significantly lower gamma band corticomuscular coherence and phase coupling during an isometric elbow extension position task. The lower corticomuscular coupling may indicate a central modulation mechanism of antagonist muscle prefatigue that related to decreased descending common drive or joint instability compensation modulation mechanism.

Resistance-induced brain activity changes during cycle ergometer exercises

Background

EEGs are frequently employed to measure cerebral activations during physical exercise or in response to specific physical tasks. However, few studies have attempted to understand how exercise-state brain activity is modulated by exercise intensity.

Methods

Ten healthy subjects were recruited for sustained cycle ergometer exercises at low and high resistance, performed on two separate days a week apart. Exercise-state EEG spectral power and phase-locking values (PLV) are analyzed to assess brain activity modulated by exercise intensity.

Results

The high-resistance exercise produced significant changes in beta-band PLV from early to late pedal stages for electrode pairs F3-Cz, P3-Pz, and P3-P4, and in alpha-band PLV for P3-P4, as well as the significant change rate in alpha-band power for electrodes C3 and P3. On the contrary, the evidence for changes in brain activity during the low-resistance exercise was not found.

Conclusion

These results show that the cortical activation and cortico-cortical coupling are enhanced to take on more workload, maintaining high-resistance pedaling at the required speed, during the late stage of the exercise period.

Muscle Fatigue Enhance Beta Band EMG-EMG Coupling of Antagonistic Muscles in Patients With Post-stroke Spasticity

There is a significant influence of muscle fatigue on the coupling of antagonistic muscles while patients with post-stroke spasticity are characterized by abnormal antagonistic muscle coactivation activities. This study was designed to verify whether the coupling of antagonistic muscles in patients with post-stroke spasticity is influenced by muscle fatigue. Ten patients with chronic hemipare and spasticity and 12 healthy adults were recruited to participate in this study. Each participant performed a fatiguing isometric elbow flexion of the paretic side or right limb at 30% maximal voluntary contraction (MVC) level until exhaustion while surface electromyographic (sEMG) signals were collected from the biceps brachii (BB) and triceps brachii (TB) muscles during the sustained contraction. sEMG signals were divided into the first (minimal fatigue) and second halves (severe fatigue) of the contraction. The power and coherence between the sEMG signals of the BB and TB in the alpha (8–12 Hz), beta (15–35 Hz), and gamma (35–60 Hz) frequency bands associated with minimal fatigue and severe fatigue were calculated. The coactivation ratio of the antagonistic TB muscle was also determined during the sustained fatiguing contraction. The results demonstrated that there was a significant decrease in maximal torque during the post-fatigue contraction compared to that during the pre-fatigue contraction in both stroke and healthy group. In the stroke group, EMG-EMG coherence between the BB and TB in the alpha and beta frequency bands was significantly increased in severe fatigue compared to minimal fatigue, while coactivation of antagonistic muscle increased progressively during the sustained fatiguing contraction. In the healthy group, coactivation of the antagonistic muscle showed no significant changes during the fatiguing contraction and no significant coherence was found in the alpha, beta and gamma frequency bands between the first and second halves of the contraction. Therefore, the muscle fatigue significantly increases the coupling of antagonistic muscles in patients with post-stroke spasticity, which may be related to the increased common corticospinal drive from motor cortex to the antagonistic muscles. The increase in antagonistic muscle coupling induced by muscle fatigue may provide suggestions for the design of training program for patients with post-stroke spasticity.

A Comparative Study of EMG Indices in Muscle Fatigue Evaluation Based on Grey Relational Analysis during All-Out Cycling Exercise

The increased popularization of cycling has brought an increase in cycling-related injuries, which has been suggested to be associated with muscle fatigue. However, it still remains unclear on the utility of different EMG indices in muscle fatigue evaluation induced by cycling exercise. In this study, ten cyclist volunteers performed a 30-second all-out cycling exercise after a warm-up period. Surface electromyography (sEMG) from vastus lateralis muscle (VL) and power output and cadence were recorded and EMG RMS, MF and MPF based on Fourier Transform, MDF and MNF based on wavelet packet transformation, and C(n) based on Lempel–Ziv complexity algorithm were calculated. Utility of the indices was compared based on the grey rational grade of sEMG indices and power output and cadence. The results suggested that MNF derived from wavelet packet transformation was significantly higher than other EMG indices, indicating the potential application for fatigue evaluation induced by all-out cycling exercise.