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The increasing descending drive needed to sustain submaximal isometric torque makes it difficult to isolate fatigue-related changes to neural excitability because evoked electromyography (EMG) responses are influenced by the relative activation of the motoneuron pool. Hence, it is becoming increasingly common to investigate fatigue using a sustained contraction with maintained output from the motoneuron pool; i.e., matched-surface EMG. Although this approach controls motoneuron pool output, it is unknown how cortical contributions to ongoing muscle activity or common modulation between muscles are altered during a matched-EMG contraction. During separate visits, 16 participants performed a sustained 10-min isometric elbow flexion contraction at 20% maximal voluntary contraction (MVC) torque or the level of integrated biceps brachii EMG recorded at 20% MVC torque. Electroencephalographic and surface EMG recordings were obtained from the sensorimotor area and biceps and triceps brachii, respectively. The matched-torque contraction caused increased corticomuscular coherence for biceps brachii (∼75%) and intermuscular coherence (∼97%), but reduced MVC torque (∼33%), voluntary activation (∼9%), and torque steadiness (∼83%). In contrast, the matched-EMG contraction caused reduced MVC torque (∼21%), with no change in coherence, voluntary activation, or EMG steadiness. Furthermore, participants reported higher ratings of perceived effort scores by 6 min into the matched-torque compared with matched-EMG contraction. These findings indicate that, during a matched-torque contraction, the nervous system enhanced common oscillatory activity to continue the task, but this did not prevent degradation of performance (torque steadiness). In contrast, when motoneuron pool output was maintained, other neural strategies were used to preserve muscle output. NEW & NOTEWORTHY Sustained electromyography (EMG) tasks offer valuable insights into fatigue-related changes to neural excitability, yet nothing is known about communication between the cortex and active muscles. A 10-min matched-EMG contraction reduced maximal torque-generating capacity but did not alter corticomuscular coherence (CMC), intermuscular coherence (IMC), or task performance (EMG steadiness). In contrast, a matched-torque contraction increased CMC and IMC yet further impaired maximal torque and compromised torque steadiness, which reveals unique neural strategies for the two tasks.

Introduction: When an isometric contraction is sustained at a submaximal torque, activation of the motoneuron pool increases, making it difficult to interpret neural excitability alterations. Thus, more recently, isometric contractions with maintained electromyographic (EMG) activity (matched-EMG) are being used to induce fatigue; however, little is known about the neurophysiological adjustments that occur to satisfy the requirements of the task., Methods: For our study, 16 participants performed a 10-min sustained isometric elbow flexion contraction at 20% maximal voluntary contraction (MVC) torque or the level of integrated biceps brachii EMG recorded at 20% MVC torque. Surface EMG was used to assess global median frequency, and four fine-wire electrode pairs were used to obtain motor unit (MU) discharge rate from biceps brachii. Torque or EMG steadiness was also assessed throughout the fatiguing contractions., Results: MU discharge rate increased and torque steadiness decreased during the matched-torque contraction; however, MU discharge rate decreased during the matched-EMG contraction, and no changes occurred for EMG steadiness. Data pooled for the two contractions revealed a decrease in global median frequency. Lastly, a greater loss of MVC torque was observed immediately after the matched-torque compared with matched-EMG contraction., Conclusions: These findings indicate that, during a matched-torque fatiguing contraction, the nervous system increases MU discharge rates at the cost of poorer steadiness to maintain the requisite torque. In contrast, during a matched-EMG fatiguing contraction, a reduction of MU discharge rates allows for maintenance of EMG steadiness., (Copyright © 2024 by the American College of Sports Medicine.)

According to current guidelines, when measuring voluntary activation (VA) using transcranial magnetic stimulation (TMS), stimulator output (SO) should not exceed the intensity that, during a maximal voluntary contraction (MVC), elicits a motor evoked potential (MEP) from the antagonist muscle >15%-20% of its maximal M-wave amplitude. However, VA is based on agonist evoked-torque responses [i.e., superimposed twitch (SIT) and estimated resting twitch (ERT)], which means limiting SO based on electromyographic (EMG) responses will often lead to a submaximal SIT and ERT, possibly underestimating VA. Therefore, the purpose of this study was to compare elbow flexor VA calculated using the original method (i.e., intensity based on MEP size; SO MEP ) and a method based solely on eliciting the largest SIT at 50% MVC torque (SO SIT ), regardless of triceps brachii MEP size. Fifteen healthy, young participants performed 10 sets of brief contractions at 100%, 75%, and 50% MVC torque, with TMS delivered at SO MEP (73.0 ± 13.5%) or SO SIT (92.0 ± 10.8%) for five sets each. Although the mean ERT torque was greater using SO SIT (15.2 ± 4.8 Nm) compared with SO MEP (13.0 ± 3.7 Nm; P = 0.031), the SIT amplitude at 100% MVC torque was not different (SO MEP : 0.69 ± 0.49 Nm vs. SO SIT : 0.74 ± 0.52 Nm; P = 0.604). Despite the ERT disparity, VA scores were not different between SO MEP (94.6 ± 3.5%) and SO SIT (95.0 ± 3.3%; P = 0.572). Even though SO SIT did not lead to a higher VA score than the SO MEP method, it has the benefit of yielding the same result without the need to record antagonist EMG or perform MVCs when determining SO, which can induce fatigue before measuring VA. NEW & NOTEWORTHY When using transcranial magnetic stimulation (TMS) to determine voluntary activation (VA) of the elbow flexors, we hypothesized that a stimulator output designed to limit antagonist muscle activity would evoke submaximal agonist superimposed twitch amplitudes, thus underestimating VA. Contrary to our hypothesis, VA was not greater with an output based on maximal superimposed twitch amplitude. Nevertheless, our findings advance methodological practices by simplifying the equipment and minimizing the time required to determine VA using TMS.

Despite the perceived importance of antagonist muscle activity, it is unknown if motor unit (MU) behavior at recruitment differs when a muscle acts as an antagonist versus agonist. Fourteen healthy participants performed ramped, isometric elbow flexor or extensor contractions to 50% or 100% maximal voluntary contraction (MVC) torque. Surface and fine-wire intramuscular electromyographic (EMG) recordings were sampled from biceps and triceps brachii. During agonist contractions, low-threshold MUs (recruited at <10% MVC torque) were sampled in all participants, with a total of 107 and 90 for biceps and triceps brachii, respectively. For ramped MVCs, antagonist surface EMG coactivation (% amplitude during agonist MVC) was 8.3 ± 6.6% for biceps and 15.2 ± 7.3% for triceps brachii. However, antagonist single MU activity was recorded from only four participants, with only one of these individuals having antagonist MUs recorded from both muscles. All antagonist MUs were successfully detected during agonist contractions, but many (∼40%) had a recruitment threshold >10% MVC torque. For MUs recorded during both agonist and antagonist contractions, discharge rate at recruitment was seemingly lower for antagonist than agonist contractions. Coexistence of typical levels of surface EMG-derived coactivation with scant antagonist MU recordings suggests that coactivation in these muscles is primarily the result of cross talk. Based on the limited antagonist MU data detected, MUs recruited early during an agonist contraction are not necessarily among those first recruited during an antagonist contraction. These findings highlight the possibility of a modification of orderly recruitment when a motoneuron pool is acting as an antagonist. NEW & NOTEWORTHY Modest levels of coactivation are widely considered essential for appropriate motor control; however, minimal attention has been given to recruitment patterns of motor units (MUs) from antagonist muscles. Despite the successful recording of many low-threshold MUs during agonist contractions, we recorded no antagonist MUs in most participants. Of the units recorded, only ∼60% matched those recruited at <10% of maximal torque when the muscle acted as an agonist, which suggests a modified recruitment order for antagonist MUs.

Sleep deprivation (SD) is prevalent and impairs motor function; however, little is known about its effect on perceived and performance fatigability, especially in females. To examine the effects of 24 h of SD on these attributes of fatigue, nine females completed a 20-min isometric, sustained elbow flexion contraction, followed by 10 min of recovery. The superimposed twitch (SIT) elicited via transcranial magnetic stimulation (TMS) assessed supraspinal drive. Biceps brachii electromyographic data indicated neural excitability in response to stimulation over the motor cortex (motor evoked potential; MEP), corticospinal tract (cervicomedullary motor evoked potential; CMEP), and brachial plexus (maximal M-wave; Mmax). MEPs and CMEPs were recorded during a TMS-induced silent period. At baseline, ratings of perceived effort (RPE; 2.9 vs. 1.6) and fatigue (RPF; 6.9 vs. 2.9), were higher for SD than control. Across the 20-min contraction, RPE increased from 2.2 to 7.6, SIT and MEP/CMEP increased by 284 and 474%, respectively, whereas maximal voluntary isometric contraction (MVC) torque and CMEP/Mmax decreased by 26 and 57%, respectively. No differences were found across conditions for MVC, SIT, Mmax, CMEP/Mmax, or MEP/CMEP prior to, during, and after the fatiguing task. During recovery, RPE (4.9 vs. 3.4), RPF (7.6 vs. 2.8), and perception of task difficulty (5.5 vs. 4.5) were greater for SD than control. Acute SD does not appear to alter performance fatigability development and subsequent recovery; however, it increases perceptions of fatigue, effort, and task difficulty. Thus, the disconnect between perceived and actual neuromuscular capacity following a sustained, submaximal isometric task is exacerbated by SD. Highlights Sleep deprivation did not alter supraspinal drive or neural excitability during and after a 20-min submaximal elbow flexion contractionSleep deprivation increased perceived fatigue and perception of task difficultyThe disconnect between perceived and performance fatigability is exacerbated in a sleep-deprived state.

In the last 50 years, the study of brain development has brought major discoveries to education and medicine, changing the lives of millions of children and families. However, collecting behavioral and neurophysiological data from children has specific challenges, such as high rates of data loss and participant dropout. We have developed a science camp method to collect data from children using the benefits of positive peer interactions and interactive and engaging activities, to allow researchers to better collect data repeatedly and reliably from groups of children. A key advantage of this approach is that by increasing participant engagement, attention is also increased, thereby increasing data quality, reducing data loss, and lowering attrition rates. This protocol describes the step-by-step procedure for facilitation of a science camp, including behavioral, electrophysiological, and participatory engagement activities. As this method is robust but also flexible, we anticipate that it can also be applied to different demographics and research needs., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Márquez-García et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Prior studies have suggested that oscillatory activity in cortical networks can modulate stimulus-evoked responses through time-varying fluctuations in neural excitation-inhibition dynamics. Studies combining transcranial magnetic stimulation (TMS) with electromyography (EMG) and electroencephalography (EEG) can provide direct measurements to examine how instantaneous fluctuations in cortical oscillations contribute to variability in TMS-induced corticospinal responses. However, the results of these studies have been conflicting, as some reports showed consistent phase effects of sensorimotor mu-rhythms with increased excitability at the negative mu peaks, while others failed to replicate these findings or reported unspecific mu-phase effects across subjects. Given the lack of consistent results, we systematically examined the modulatory effects of instantaneous and pre-stimulus sensorimotor mu-rhythms on corticospinal responses with offline EEG-based motor evoked potential (MEP) classification analyses across five identical visits. Instantaneous sensorimotor mu-phase or pre-stimulus mu-power alone did not significantly modulate MEP responses. Instantaneous mu-power analyses showed weak effects with larger MEPs during high-power trials at the overall group level analyses, but this trend was not reproducible across visits. However, TMS delivered at the negative peak of high magnitude mu-oscillations generated the largest MEPs across all visits, with significant differences compared to other peak-phase combinations. High power effects on MEPs were only observed at the trough phase of ongoing mu oscillations originating from the stimulated region, indicating site and phase specificity, respectively. More importantly, such phase-dependent power effects on corticospinal excitability were reproducible across multiple visits. We provide further evidence that fluctuations in corticospinal excitability indexed by MEP amplitudes are partially driven by dynamic interactions between the magnitude and the phase of ongoing sensorimotor mu oscillations at the time of TMS, and suggest promising insights for (re)designing neuromodulatory TMS protocols targeted to specific cortical oscillatory states.

Children with autism spectrum disorder (ASD) experience difficulties with social communication, making it challenging to interpret contextual information that aids in accurately interpreting language. To investigate how the brain processes the contextual information and how this is different in ASD, we compared event-related potentials (ERPs) in response to processing visual and auditory congruent and incongruent information. Two groups of children participated in the study: 37 typically developing children and 15 children with ASD (age range = 6 to 12). We applied a language task involving auditory sentences describing congruent or incongruent images. We investigated two ERP components associated with language processing: the N400 and P600. Our results showed how children with ASD present significant differences in their neural responses in comparison with the TD group, even when their reaction times and correct trials are not significantly different from the TD group., (© 2022. The Author(s).)

Sleep deprivation is commonplace and impairs memory, inhibition, cognitive flexibility and attention. However, little is known about the neurophysiological impact of sleep deprivation in the context of go/no-go (GNG) task performance and emotion processing. To address this knowledge gap, 12 females performed two computerized GNG tasks (shapes; emotional facial expressions) and an object hit and avoid (OHA) task after a night of typical sleep and 24 h without sleep. Electroencephalographic (EEG) recordings were taken during a 3-minute eyes-open resting period as well as during GNG task performance. Resting EEG power in the theta band was 33% higher for the sleep-deprived than control condition (p < 0.05), whereas alpha activity was unchanged. When sleep deprived, participants had ~6% slower response times (go trials) and made ~7% more total errors during GNG tasks (p < 0.05). Reaction time and overall accuracy were ~25% and ~9% worse for the emotional compared to shape GNG task (p < 0.05), respectively, which suggests interference of emotion processing on task performance. Smaller differences in amplitude between go and no-go trials for the N2 and both the N2 and P3 event-related potential components were found during sleep deprivation for the emotional and shape GNG tasks, respectively (p < 0.05). No changes to the N170 component were found. Lastly, participants hit more distractors during the OHA task when sleep deprived (p < 0.05). Altogether, these results indicate sleep deprivation slows neural processing and impairs inhibitory task performance, possibly due to a more bottom-up, stimulus-driven approach to inhibiting motor responses., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Mental fatigue is commonplace but there is limited understanding of the neural underpinnings of its development, the time course of its recovery, and its impact on motor function. Hence, this study used neural (electroencephalography) and motor measures to investigate the development and recovery of mental fatigue. Twenty participants performed a 60-min N-back task, with neural activity compared within the task. Additionally, pre-task neural and motor measures were compared to assessments beginning at 0, 30 and 60 min post-task. Alpha power increased during the task and was greater than baseline at 30 and 60 min post-task. Motor skills were impaired at ∼10-17 min post-task but recovered at ∼40-47 min. Using a unique combination of neural and motor measures, our results suggest that attentiveness and, possibly, selectiveness in inhibiting irrelevant information are impaired after an acute mentally-fatiguing task. Notably, recovery time differed for neural and motor measures., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Ongoing low-frequency activity in the brain has been shown to indicate an inhibitory neural state; however, the effects of this low-frequency activity on event-related neural processes associated with movement preparation, including movement-related cortical potentials (MRCPs) or more specifically, the motor potential (MP), and event-related desynchronization (ERD) have not been assessed. Using data from 48 participants, the current study examined how ongoing mu and beta frequency activity at rest relates to the MP and mu and beta ERD during real or imagined movement of the fingers. Resting state EEG activity was collected for 1 min, prior to the real and imagined finger movement trials. 20 real and 20 imagined movement trials were collected for each hand. Resting beta activity correlated with MP amplitude during movement trials for both the right (r(47) = -0.304, p = 0.035) and left (r(47) = -0.468, p < 0.001) hands, whereas resting mu correlated with MP amplitude during motor imagery trials of both the right (r(47) = -0.289, p = 0.046) and left (r(47) = -0.330, p = 0.020) hands. Ongoing mu and beta activity was not significantly correlated with mu or beta ERD for both the movement and imagery trials. A connection between low-frequency activity and MP could inform biofeedback procedures that promote a reduction of this activity, ultimately allowing for easier identification of the intent to move., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Autism spectrum disorder (ASD) is an increasingly common neurodevelopmental disorder that affects 1 in 59 children. The cognitive profiles of individuals with ASD are varied, and the neurophysiological underpinnings of these developmental difficulties are unclear. While many studies have focused on overall group differences in the amplitude or latency of event related potential (ERP) responses, recent research suggests that increased intra-subject neural variability may also be a reliable indicator of atypical brain function in ASD. This study aimed to identify behavioral and neural variability responses during an emotional inhibitory control task in children with ASD compared to typically developing (TD) children. Children with ASD showed increased variability in response to both inhibitory and emotional stimuli, evidenced by greater reaction time variability and single-trial ERP variability of N200 and N170 amplitudes and/or latencies compared to TD children. These results suggest that the physiological basis of ASD may be more accurately explained by increased intra-subject variability, in addition to characteristic increases or decreases in the amplitude or latency of neural responses. Autism Res 2020, 13:221-229. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: The cognitive functions including memory, attention, executive functions, and perception, of individuals with ASD are varied, and the physiological underpinnings of these profiles are unclear. In this study, children with ASD showed increased intra-subject neural and behavioral variability in response to an emotional inhibitory control task compared to typically developing children. These results suggest that the physiological basis of ASD may also be explained by increased behavioral and neural variability in people with ASD, rather than simply characteristic increases or decreases in averaged brain responses., (© 2019 International Society for Autism Research, Wiley Periodicals, Inc.)

Autism Spectrum Disorder (ASD) is an increasingly common developmental disorder that affects 1 in 59 children. Despite this high prevalence of ASD, knowledge regarding the biological basis of its associated cognitive difficulties remains scant. In this study, we aimed to identify altered neurophysiological responses underlying inhibitory control and emotion processing difficulties in ASD, together with their associations with age and various domains of cognitive and social function. This was accomplished by assessing electroencephalographic recordings during an emotional go/nogo task alongside parent rating scales of behavior. Event related potential (ERP) N200 component amplitudes were reduced in children with ASD compared to typically developing (TD) children. No group differences were found, however, for task performance, P300 amplitude or latency, or N170 amplitude or latency, suggesting that individuals with ASD may only present conflict monitoring abnormalities, as reflected by the reduced N200 component, compared to TD individuals. Consistent with previous findings, increased age correlated with improved task performance scores and reduced N200 amplitude in the TD group, indicating that as these children develop, their neural systems become more efficient. These associations were not identified in the ASD group. Results also showed significant associations between increased N200 amplitudes and improved executive control abilities and decreased autism traits in TD children only. The newly discovered findings of decreased brain activation in children with ASD, alongside differences in correlations with age compared to TD children, provide a potential neurophysiological indicator of atypical development of inhibitory control mechanisms in these individuals.