Search

Traumatic brain injury (TBI) often results in balance impairment, increasing the risk of falls, and the chances of further injuries. However, the underlying neural mechanisms of postural control after TBI are not well understood. To this end, we conducted a pilot study to explore the neural mechanisms of unpredictable balance perturbations in 17 chronic TBI participants and 15 matched healthy controls (HC) using the EEG, MRI, and diffusion tensor imaging (DTI) data. As quantitative measures of the functional integration and segregation of the brain networks during the postural task, we computed the global graph-theoretic network measures (global efficiency and modularity) of brain functional connectivity derived from source-space EEG in different frequency bands. We observed that the TBI group showed a lower balance performance as measured by the center of pressure displacement during the task, and the Berg Balance Scale (BBS). They also showed reduced brain activation and connectivity during the balance task. Furthermore, the decrease in brain network segregation in alpha-band from baseline to task was smaller in TBI than HC. The DTI findings revealed widespread structural damage. In terms of the neural correlates, we observed a distinct role played by different frequency bands: theta-band modularity during the task was negatively correlated with the BBS in the TBI group; lower beta-band network connectivity was associated with the reduction in white matter structural integrity. Our future studies will focus on how postural training will modulate the functional brain networks in TBI., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

The neurophysiological mechanism of cancer-related fatigue (CRF) remains poorly understood. EEG was examined during a sustained submaximal contraction (SC) task to further understand our prior research findings of greater central contribution to early fatigue during SC in CRF. Advanced cancer patients and matched healthy controls performed an elbow flexor SC until task failure while undergoing neuromuscular testing and EEG recording. EEG power changes over left and right sensorimotor cortices were analyzed and correlated with brief fatigue inventory (BFI) score and evoked muscle force, a measure of central fatigue. Brain electrical activity changes during the SC differed in CRF from healthy subjects mainly in the theta (4-8 Hz) and beta (12-30 Hz) bands in the contralateral (to the fatigued limb) hemisphere; changes were correlated with the evoked force. Also, the gamma band (30-50 Hz) power decrease during the SC did not return to baseline after 2 min of rest in CRF, an effect correlated with BFI score. In conclusion, altered brain electrical activity during a fatigue task in patients is associated with central fatigue during SC or fatigue symptoms, suggesting its potential contribution to CRF during motor performance. This information should guide the development and use of rehabilitative interventions that target the central nervous system to maximize function recovery., Competing Interests: The authors declare that there is no conflict of interest regarding the publication of this paper., (Copyright © 2020 Didier Allexandre et al.)

30-60% of traumatic brain injury (TBI) patients suffer from long-term balance deficit. Even though motor preparation and execution are altered and slowed in TBI, their relative contribution and importance to posture instability remain poorly understood. This study investigates the impaired cortical dynamics and neuromuscular response in TBI in response to balance perturbation and its relation to balance deficit. 12 TBI and 6 healthy control (HC) participants took the Berg Balance Scale (BBS) test and participated in a balance perturbation task where they were subjected to random anterior/posterior translation, while brain (EEG), muscle (EMG) activities, and center of pressure (COP) were continuously recorded. Using independent component analysis (ICA), the component most responsible for the N1 component of the perturbation evoked potential (PEP) was selected and its amplitude and latency were extracted. Balance task performance was measured by computing the COP displacement during the task. TBI had a significantly lower BBS, larger COP displacement and lower N1 amplitude compared to the HC group. No group differences was found for N1 latency and muscle activity onset delay to the perturbation. BBS was correlated with the COP displacement and N1 amplitude, and COP displacement was correlated with N1 latency. TBI balance deficit may be associated with more impaired than delayed cortical response to balance perturbation.

The overall goal of this study is to investigate the role of parietal cortex in the control of walking in persons with Multiple Sclerosis (pwMS). We examined within-brain connectivity and cortico-muscular connectivity as pwMS and healthy control (HC) participants walked on an instrumented treadmill. Cortical activity was collected using EEG, muscle activity was collected using wireless EMG modules, and gait data were obtained by using the instrumented treadmill. Results show significant activation of sensorimotor and posterior parietal cortex during walking in both groups. Connectivity between parietal (posterior cingulate cortex PCC) and premotor regions (pars opercularis), and between PCC and contralateral muscles were higher in the healthy control group. Higher connectivity correlated with higher walking speed.

Purpose: Persistent fatigue and cognitive dysfunction are poorly understood potential long-term effects of adjuvant chemotherapy. In this pilot study, we assessed the value of electroencephalogram (EEG) power measurements as a means to evaluate physical and mental fatigue associated with chemotherapy., Patients and Methods: Women planning to undergo adjuvant chemotherapy for breast cancer and healthy controls underwent neurophysiologic assessments at baseline, during the time of chemotherapy treatment, and at 1 year. Repeated measures analysis of variance was used to analyze the data., Results: Compared with controls, patients reported more subjective fatigue at baseline that increased during chemotherapy and did not entirely resolve by 1 year. Performance on endurance testing was similar in patients versus controls at all time points; however, values of EEG power increased after a physical task in patients during chemotherapy but not controls. Compared with controls, subjective mental fatigue was similar for patients at baseline and 1 year but worsened during chemotherapy. Patients performed similarly to controls on formal cognitive testing at all time points, but EEG activity after the cognitive task was increased in patients only during chemotherapy., Conclusion: EEG power measurement has the potential to provide a sensitive neurophysiologic correlate of cancer treatment-related fatigue and cognitive dysfunction.

Voluntary muscle fatigue is a progressive process. A recent study demonstrated muscle fatigue-induced weakening of functional corticomuscular coupling measured by coherence between the brain [electroencephalogram (EEG)] and muscle [electromyogram (EMG)] signals after a relatively long-duration muscle contraction. Comparing the EEG-EMG coherence before versus after fatigue or between data of two long-duration time blocks is not adequate to reveal the dynamic nature of the fatigue process. The purpose of this study was to address this issue by quantifying single-trial EEG-EMG coherence and EEG, EMG power based on wavelet transform. Eight healthy subjects performed 200 maximal intermittent handgrip contractions in a single session with handgrip force, EEG and EMG signals acquired simultaneously. The EEG and EMG data during each 2-s handgrip was subjected to single trial EEG-EMG wavelet energy spectrum and coherence computation. The EEG-EMG coherence and energy spectrum at beta (15 ~ 35 Hz) and gamma (35-50 Hz) frequency bands were statistically analyzed in 2-block (75 trials per block), 5-block (30 trials/block), and 10-block (15 trials/block) data settings. The energy of both the EEG and EMG signals decreased significantly with muscle fatigue. The EEG-EMG coherence had a significant reduction for the 2-block comparison. More detailed dynamical changing and inter-subject variation of the EEG-EMG coherence and energy were revealed by 5- and 10-block comparisons. These results show feasibility of wavelet transform-based measurement of the EEG-EMG coherence and corresponding energy based on single-trial data, which provides extra information to demonstrate a time course of dynamic adaptations of the functional corticomuscular coupling, as well as brain and muscle signals during muscle fatigue.

This study investigates time-dependent associations between source strength estimated from high-density scalp electroencephalogram (EEG) and force of voluntary handgrip contraction at different intensity levels. We first estimate source strength from raw EEG signals collected during voluntary muscle contractions at different levels and then propose a functional random-effects model approach in which both functional fixed effects and functional random-effects are considered for the data. Two estimation procedures for the functional model are discussed. The first estimation procedure is a two-step method which involves no iterations. It can flexibly use different smoothing methods and smoothing parameters. The second estimation procedure benefits from the connection between linear mixed models and regression splines and can be fitted using existing software. Functional ANOVA is then suggested to assess the experimental effects from the functional point of view. The statistical analysis shows that the time-dependent source strength function exhibits a nonlinear feature, where a bump is detected around the force onset time. However, there is the lack of significant variations in source strength on different force levels and different cortical areas. The proposed functional random-effects model procedure can be applied to other types of functional data in neuroscience.

Coherence between electromyography (EMG) and electroencephalography (EEG) or magnetoencephalography (MEG) is frequently examined to gain insights on neuromuscular binding. Commonly, EMG signals are rectified before coherence is computed. However, the appropriateness of EMG rectification in computing EMG-EEG/MEG coherence has never been validated. Since rectification is a non-linear operation and alters the EMG power spectrum, such a validation is important to ensure the accuracy of coherence calculation. In this study we experimentally investigated the effects of EMG rectification on EMG power spectra and its coherence with EEG/MEG signals. Subjects performed sustained isometric index finger abduction at approximately 5-10% maximal voluntary force (in both EEG-EMG and MEG-EMG experiments) and index finger tapping at approximately 2-4Hz (in EEG-EMG experiment only). Bipolar surface EMG data from the first dorsal interosseus (FDI) and EEG/MEG signals from the contralateral primary sensorimotor area (C3) were recorded simultaneously. Power spectra and coherence with the EEG/MEG were calculated before and after EMG rectification. The results show that rectification shifts EMG power to lower frequencies, possibly enhancing peaks of motor unit firing. Coherences with the EEG/MEG signals were not significantly changed by EMG rectification, indicating EMG rectification is overall an appropriate procedure in power and coherence analyses.

Understanding cortical function can provide accurately targeted interventions after stroke. Initially, stroke survivors had prolonged cognitive planning time and elevated cognitive effort, highly correlated with motor control impairments. Exploratory results suggest that neurorehabilitation, accurately targeted to dyscoordination, weakness, and dysfunctional task component execution, can improve cognitive processes controlling motor function.

Background: It has been demonstrated that in young and healthy individuals, there is a strong association between the amplitude of EEG-derived motor activity-related cortical potential or EEG spectral power (ESP) and voluntary muscle force. This association suggests that the motor-related ESP may serve as an index of central nervous system function in controlling voluntary muscle activation Therefore, it may potentially be used as an objective marker to track changes in functional neuroplasticity due to neurological disorders, aging, and following rehabilitation therapies. To this end, the relationship between the band-specific ESP—combined spectral power of EEG oscillatory and aperiodic (noise) components—and voluntary elbow flexion (EF) force has been analyzed in elder and young individuals. Methods: 20 young (22.6 ± 0.87 year) and 28 elderly (74.79 ± 1.37 year) participants performed EF contractions at 20%, 50%, and 80% of maximum voluntary contraction (MVC) while high-density EEG signals were recorded. Both the absolute and relative ESPs were computed for the EEG frequency bands of interest. Results: The MVC force generated by the elderly was foreseeably lower than that of the young participants. Compared to young, the elderly cohort's (1) total ESP was significantly lower for the high (80% MVC) force task; (2) relative ESP in beta band was significantly elevated for the low and moderate (20% MVC and 50% MVC) force tasks; (3) absolute ESP failed to have a positive trend with force for EEG frequency bands of interest; and (4) beta-band relative ESP did not exhibit a significant decrease with increasing force levels. Conclusions: As opposed to young subjects, the beta-band relative ESP in elderly did not significantly decrease with increasing EF force values. This observation suggests the use of beta-band relative ESP as a potential biomarker for age-related motor control degeneration. [ABSTRACT FROM AUTHOR]

Neurophysiologic measurements were made on a patient with multiple lung cancers and severe cancer-related fatigue (CRF) who responded to 5 mg methylphenidate twice daily, titrated to 10 mg twice daily after 2 weeks. She remained at 10 mg twice daily for 8 months. Improvement in severe CRF (Brief Fatigue Inventory score) was associated with normalization of neurophysiologic tests. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: Cortical function is not well understood in stroke survivors with persistent dyscoordination. The study purpose was two-fold: 1) characterize cognitive planning time and cognitive effort level for a circle-drawing motor task in stroke survivors using shoulder/elbow muscles and 2) identify the relationship between cognitive effort level and movement smoothness. Methods: Twelve stroke survivors with shoulder/elbow coordination deficits (>12 mo) and eight controls were enrolled. The motor task was to draw a circle on a horizontal surface using only shoulder/elbow muscles. Outcome measures were: EEG-derived cognitive planning time, cognitive effort level, and movement smoothness. Comparisons between stroke and controls were made using t-tests. The Pearson''s correlation model was analyzed to determine the relationship between movement smoothness and cognitive effort level. Results: Stroke subjects showed a statistically significant prolonged motor planning time versus controls for both lesion and non-lesion sides (p =0.013 and 0.049, respectively). They also showed a statistically significant elevated effort level versus controls for both sides (p =0.016 and 0.013). The patients exhibited statistically significant poor movement smoothness in the medial/lateral and forward/backward movement directions versus controls (p =0.035 and 0.037, respectively). For stroke, there was a significant correlation between cognitive effort level on the non-lesion side and smoothness of movement in the medial/lateral and forward/backward directions (r =0.54, p =0.036 and r =0.76, p =0.002, respectively). On the lesion side, results were mixed (r =0.268, p =0.2 r =0.59, p =0.023, respectively). Conclusions: Stroke survivors with upper limb motor deficits exhibit a longer cognitive planning time and elevated cognitive effort for performance of a complex shoulder/elbow motor coordination task. The elevated cognitive effort level was associated with poor (jerky) motor performance, suggesting a potential role of the CNS in controlling movement smoothness of the arm. [Copyright &y& Elsevier]

The purpose of this study was to investigate the relationship between EEG-derived motor activity-related cortical potential (MRCP) and voluntary muscle activation. Eight healthy volunteers participated in two experimental sessions. In one session, subjects performed isometric elbow-flexion contractions at four intensity levels [10%, 35%, 60%, and 85% maximal voluntary contraction (MVC)]. In another session, a given elbow-flexion force (35% MVC) was generated at three different rates (slow, intermediate, and fast). Thirty to 40 contractions were performed at each force level or rate. EEG signals were recorded from the scalp overlying the supplementary motor area (SMA) and contralateral sensorimotor cortex, and EMG signals were recorded from the skin surface overlying the belly of the biceps brachii and brachioradialis muscles during all contractions. In each trial, the force was used as the triggering signal for MRCP averaging. MRCP amplitude was measured from the beginning to the peak of the negative slope. The magnitude of MRCP from both EEG recording locations (sensorimotor cortex and SMA) was highly correlated with elbow-flexion force, rate of rising of force, and muscle EMG signals. These results suggest that MRCP represents cortical motor commands that scale the level of muscle activation. [ABSTRACT FROM AUTHOR]

Abstract: Nonlinear dynamics has been introduced to the analysis of biological data and increasingly recognized to be functionally relevant. The purpose of this study was to examine chaotic properties of human scalp EEG signals associated with voluntary motor tasks using the largest Lyapunov exponent (L1). 64-channel scalp EEG data were recorded from eight healthy subjects in two tasks: (1) intermittent handgrip contractions at 20, 40, 60, and 80% of maximal voluntary contraction (MVC) with 20 trials at each level. No significant fatigue were induced; (2) intermittent handgrip MVCs (100 trials) that resulted in significant fatigue. The L1 values of all EEG channels were calculated in each trial first then averaged across the 20 trials at each force level (Task 1) or over each of the 5-trial blocks (Task 2) before the group means were obtained. A multivariate statistical model was used to examine the effect of force and fatigue on L1. L1 values were greater with higher force (Task 1), and decreased significantly with fatigue (Task 2). The L1 of the EEG signals changes systematically and correlates significantly with muscle force and fatigue. The results suggest that nonlinear chaotic index L1 may serve as a quantitative measure for motor control-related cortical signal adaptations. [Copyright &y& Elsevier]

Abstract: Objective: To investigate the functional connection between motor cortex and muscles, we measured electroencephalogram–electromyogram (EEG–EMG) coherence of stroke patients and controls. Methods: Eight healthy controls and 21 patients with shoulder and elbow coordination deficits were enrolled. All subjects performed a reaching task involving shoulder flexion and elbow extension. EMG of the anterior deltoid (AD) and brachii muscles (BB, TB) and 64-channel scalp EEG were recorded during the task. Time-frequency coherence was calculated using the bivariate autoregressive model. Results: Stroke patients had significantly lower corticomuscular coherence compared with healthy controls for the AD and BB muscles at both the beta (20–30Hz) and lower gamma (30–40Hz) bands during the movement. BH procedure (FDR) identified a reduced corticomuscular coherence for stroke patients in 11 of 15 scalp area–muscle combinations. There was no statistically significant difference between stroke patients and control subjects according to coherence in other frequency bands. Conclusion: Poorly recovered stroke survivors with persistent upper-limb motor deficits exhibited significantly lower gamma-band corticomuscular coherence in performing a reaching task. Significance: The study suggests poor brain-muscle communication or poor integration of the EEG and EMG signals in higher frequency band during reaching task may reflect an underlying mechanism producing movement deficits post-stroke. [Copyright &y& Elsevier]

Abstract: Objective: Recent research has shown dissociation between changes in brain and muscle signals during voluntary muscle fatigue, which may suggest weakening of functional corticomuscular coupling. However, this weakening of brain–muscle coupling has never been directly evaluated. The purpose of this study was to address this issue by quantifying EEG–EMG coherence at times when muscles experienced minimal versus significant fatigue. Methods: Nine healthy subjects sustained an isometric elbow flexion at 30% maximal level until exhaustion while their brain (EEG) and muscle (EMG) activities were recorded. The entire duration of the EEG and EMG recordings was divided into the first half (stage 1 with minimal fatigue) and second half (stage 2 with severer fatigue). The EEG–EMG coherence and power spectrum in each stage was computed. Results: The power of both EEG and EMG increased significantly while their coherence decreased significantly in stage 2 compared with stage 1 at beta (15–35 Hz) band. Conclusions: Despite an elevation of the power for both the EEG and EMG activities with muscle fatigue, the fatigue weakens strength of brain–muscle signal coupling at beta frequency band. Significance: Weakening of corticomuscular coupling may be a major neural mechanism contributing to muscle fatigue and associated performance impairment. [Copyright &y& Elsevier]

Abstract: Accumulating evidence suggests that the overall level of cortical activation controlling a voluntary motor task that leads to significant muscle fatigue does not decrease as much as the activation level of the motoneuron pool projecting to the muscle. One possible explanation for this “muscle fatigue>cortical fatigue” phenomenon is that the brain is an organ with built-in redundancies: it has multiple motor centers and parallel pathways, and the center of activation may shift from one location to another when neurons in the previous location become fatigued. This hypothesis was tested by estimating the changes of source locations of high-density (64 channels) scalp electroencephalographic (EEG) signals collected during both fatigue and non-fatigue motor tasks. A current dipole model was used to estimate the EEG sources. The fatigue motor task induced significant muscle fatigue, and the non-fatigue task did not. The EEG signal source that indicated the center of brain activation showed substantial location shifts during the fatigue motor task. The shifts could not be explained by variations of source locations caused by error estimated from the non-fatigue task EEG and simulated data. Compared to the non-fatigue condition, the weighted-center of the source locations for all the participants shifted toward the right hemisphere (ipsilateral to the muscle activation), anterior, and inferior cortical regions under the fatigue condition. Fatigue did not alter dipole (source-signal) strength or the overall level of brain activation. The brain may avoid fatigue by shifting neuron populations that participate in a fatiguing motor task. [Copyright &y& Elsevier]

Abstract: Animal studies have shown that there are cell populations only discharging phasically before a motor task and others only active tonically during holding phase of the task. How muscle fatigue influences these two types of cell populations, however, is unknown. Because the phasic neurons are only active briefly before the task but the tonic ones are active continuously throughout the task, we hypothesized that fatigue would have a less effect on cortical signals during the preparation phase (representing phasic discharge) than that during the sustained phase (representing tonic discharge). Eight participants performed 200 handgrip maximal voluntary contractions (MVCs) with simultaneous recordings of scalp electroencephalographic (EEG), handgrip force, and finger flexor surface electromyographic (EMG) signals. Power spectrograms of the EEG during the preparation and sustained phases were analyzed in each of the five 40-trial blocks, with data from the first block representing a condition of moderate fatigue and the last, severe fatigue. Movement-related cortical potential (MRCP) was derived by trigger-averaging 40 EEG epochs in each block. The power of all EEG frequencies did not alter significantly during the preparation phase but decreased significantly during the sustained phase of the contraction. The MRCP negative potential (NP) related to motor task preparation only showed minimal changes. These results suggest that MVC-induced fatigue has differential effects on cortical signals during motor task preparation compared to its execution and maintenance. The signals of the two phases may represent activities of the two cortical cell populations previously found by animal studies. [Copyright &y& Elsevier]

Eccentric muscle contractions generate greater force at a lower level of activation and subject muscles to more severe damage than do concentric actions. A recent investigation has revealed that electroencephalogram (EEG)-derived movement-related cortical potential (MRCP) is greater and occurs earlier for controlling human eccentric than concentric submaximal muscle contractions. However, whether the central nervous system (CNS) control signals for high-intensity or maximal-effort eccentric movements differ from those for concentric actions is unknown. The purpose of this study was to determine whether the MRCP signals differ between the two types of maximal-effort contractions. Eight volunteers performed 40 maximal voluntary eccentric and 40 maximal voluntary concentric elbow flexor contractions on a Kin-Com isokinetic dynamometer. Scalp EEG signals (62 channels) were measured along with force, joint angle, and electromyographic (EMG) signals of the performing muscles. MRCP-based two-dimensional brain maps were created to illustrate spatial and temporal distributions of the MRCP signals. Although the level of elbow flexor muscle activity was lower during eccentric than concentric movements, MRCP-indicated cortical activation was greater both in amplitude and area dimension for the eccentric task. Detailed comparisons of individual electrode signals suggested that eccentric movements needed a significantly longer time for early preparation and a significantly greater magnitude of cortical activity for later movement execution. The extra preparation time and higher amplitude of activation may reflect CNS activities that account for the higher risk of injury, higher degree of movement difficulty, and unique motor unit activation pattern associated with maximal-level eccentric muscle actions. [Copyright &y& Elsevier]