Does Muscle Fatigue Alter EEG Bands of Brain Hemispheres?

Background: Muscle fatigue has been known to influence brain activity, but very little is known about how cortical centers respond to muscle fatigue.Objective: This study was conducted to investigate the effects of muscle contraction and fatigue induced by two different percent of maximal voluntary contraction (MVC) on Electroencephalography (EEG) signals.Methods: EEG signals were recorded from twenty-one healthy human subjects during three phases (rest, pre fatigue and post fatigue) contraction of Adductor pollicis muscle (APM) at 30% and 70% MVC. The mean powers of EEG bands (alpha, beta and gamma) were computed offline in the frequency domain.Results: None of the three phases with each percent of MVC revealed significant differences for all bands (p>0.05). Comparison of two hemispheres showed right hemisphere gamma band activity was enhanced during pre-fatigue state at 30% MVC (p= 0.042) and post-fatigue state at 70% MVC (p= 0.028). Right hemisphere beta band activity also increased prominently at 70% MVC in post-fatigue condition (p = 0.030).Conclusion: These results suggest muscle contraction and fatigue at 30% and 70% MVC have no significant effect on EEG activity, but the trends of beta and gamma band activities are almost similar in each percent of 30% and 70% MVC. Right brain hemisphere shows more activity than left hemisphere in beta and gamma rhythm after fatigue state at 70% MVC.

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Alpha-to-beta- and gamma-band activity reflect predictive coding in affective visual processing

Scientific Reports ◽

10.1038/s41598-021-02939-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Andreas Strube ◽

Michael Rose ◽

Sepideh Fazeli ◽

Christian Büchel

Keyword(s):

Visual Processing ◽

Predictive Coding ◽

Stimulus Presentation ◽

Gamma Band ◽

Prediction Errors ◽

Beta Band ◽

Picture Processing ◽

Gamma Band Activity ◽

Spectral Patterns ◽

Band Activity

AbstractProcessing of negative affective pictures typically leads to desynchronization of alpha-to-beta frequencies (ERD) and synchronization of gamma frequencies (ERS). Given that in predictive coding higher frequencies have been associated with prediction errors, while lower frequencies have been linked to expectations, we tested the hypothesis that alpha-to-beta ERD and gamma ERS induced by aversive pictures are associated with expectations and prediction errors, respectively. We recorded EEG while volunteers were involved in a probabilistically cued affective picture task using three different negative valences to produce expectations and prediction errors. Our data show that alpha-to-beta band activity after stimulus presentation was related to the expected valence of the stimulus as predicted by a cue. The absolute mismatch of the expected and actual valence, which denotes an absolute prediction error was related to increases in alpha, beta and gamma band activity. This demonstrates that top-down predictions and bottom-up prediction errors are represented in typical spectral patterns associated with affective picture processing. This study provides direct experimental evidence that negative affective picture processing can be described by neuronal predictive coding computations.

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Computation and Evaluation of Features of Surface Electromyogram to Identify the Force of Muscle Contraction and Muscle Fatigue

BioMed Research International ◽

10.1155/2014/197960 ◽

2014 ◽

Vol 2014 ◽

pp. 1-6 ◽

Cited By ~ 20

Author(s):

Sridhar P. Arjunan ◽

Dinesh K. Kumar ◽

Ganesh Naik

Keyword(s):

Muscle Contraction ◽

Muscle Fatigue ◽

Root Mean Square ◽

Linear Regression Analysis ◽

Maximum Voluntary Contraction ◽

Voluntary Contraction ◽

Median Frequency ◽

Mean Square ◽

Surface Electromyogram ◽

The Relationship

The relationship between force of muscle contraction and muscle fatigue with six different features of surface electromyogram (sEMG) was determined by conducting experiments on thirty-five volunteers. The participants performed isometric contractions at 50%, 75%, and 100% of their maximum voluntary contraction (MVC). Six features were considered in this study:normalised spectral index (NSM5), median frequency, root mean square, waveform length, normalised root mean square (NRMS), and increase in synchronization (IIS) index. Analysis of variance (ANOVA) and linear regression analysis were performed to determine the significance of the feature with respect to the three factors: muscle force, muscle fatigue, and subject. The results show that IIS index of sEMG had the highest correlation with muscle fatigue and the relationship was statistically significant (P<0.01), while NSM5 associated best with level of muscle contraction (%MVC) (P<0.01). Both of these features were not affected by the intersubject variations (P>0.05).

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Top-down beta enhances bottom-up gamma

10.1101/054288 ◽

2016 ◽

Cited By ~ 2

Author(s):

Craig G. Richter ◽

William H. Thompson ◽

Conrado A. Bosman ◽

Pascal Fries

Keyword(s):

Gamma Band ◽

Visual Area ◽

Beta Band ◽

Top Down ◽

Bottom Up ◽

Area V4 ◽

Frequency Interaction ◽

Area 7A ◽

Alpha Beta ◽

Band Activity

AbstractSeveral recent studies have demonstrated that the bottom-up signaling of a visual stimulus is subserved by interareal gamma-band synchronization, whereas top-down influences are mediated by alpha-beta band synchronization. These processes may implement top-down control of stimulus processing if top-down and bottom-up mediating rhythms are coupled via cross-frequency interaction. To test this possibility, we investigated Granger-causal influences among awake male macaque primary visual area V1, higher visual area V4 and parietal control area 7a during attentional task performance. Top-down 7a-to-V1 beta-band influences enhanced visually driven V1-to-V4 gamma-band influences. This enhancement was spatially specific and largest when beta-band activity preceded gamma-band activity by ∼0.1 s, suggesting a causal effect of top-down processes on bottom-up processes. We propose that this cross-frequency interaction mechanistically subserves the attentional control of stimulus selection.Significance StatementContemporary research indicates that the alpha-beta frequency band underlies top-down control, while the gamma-band mediates bottom-up stimulus processing. This arrangement inspires an attractive hypothesis, which posits that top-down beta-band influences directly modulate bottom-up gamma band influences via cross-frequency interaction. We evaluate this hypothesis determining that beta-band top-down influences from parietal area 7a to visual area V1 are correlated with bottom-up gamma frequency oscillations from V1 to area V4, in a spatially specific manner, and that this correlation is maximal when top-down activity precedes bottom-up activity. These results show that for top-down processes such as spatial attention, elevated top-down beta-band influences directly enhance feedforward stimulus induced gamma-band processing, leading to enhancement of the selected stimulus.

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Painful cutaneous laser stimuli induce event-related gamma-band activity in the lateral thalamus of humans

Journal of Neurophysiology ◽

10.1152/jn.00778.2014 ◽

2015 ◽

Vol 113 (5) ◽

pp. 1564-1573 ◽

Cited By ~ 8

Author(s):

J. H. Kim ◽

J. H. Chien ◽

C. C. Liu ◽

F. A. Lenz

Keyword(s):

Experimental Pain ◽

Gamma Band ◽

Beta Band ◽

Gamma Activation ◽

High Gamma ◽

Gamma Band Activity ◽

Cross Frequency Coupling ◽

Induce Event ◽

Band Activity ◽

Deep Brain

Although the thalamus is an important module in “pain networks,” there are few studies of the effect of experimental pain upon thalamic oscillations. We have now examined the hypothesis that, during a series of painful cutaneous laser stimuli, thalamic signals will show stimulus-related gamma-band spectral activity, which is modulated by attention to vs. distraction from the painful stimulus. When the series of laser stimuli was presented, attention was focused by counting the laser stimuli (count laser task), while distraction was produced by counting backward (count back plus laser task). We have studied the effect of a cutaneous laser on thalamic local field potentials and EEG activity during awake procedures (deep brain stimulation implants) for the treatment of essential tremor. At different delays after the stimulus, three low gamma- (30–50 Hz) and two high gamma-band (70–90 Hz) activations were observed during the two tasks. Greater high-gamma activation was found during the count laser task for the earlier window, while greater high-gamma activation was found during the count back plus laser task for the later window. Thalamic signals were coherent with EEG signals in the beta band, which indicated significant synchrony. Thalamic cross-frequency coupling analysis indicated that the phase of the lower frequency activity (theta to beta) modulated the amplitude of the higher frequency activity (low and high gamma) more strongly during the count laser task than during the count back plus laser task. This modulation might result in multiplexed signals each encoding a different aspect of pain.

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Gamma-rhythmic Gain Modulation

10.1101/060582 ◽

2016 ◽

Author(s):

Jianguang Ni ◽

Thomas Wunderle ◽

Christopher M. Lewis ◽

Robert Desimone ◽

Ilka Diester ◽

...

Keyword(s):

Neuronal Response ◽

Effective Connectivity ◽

Reaction Times ◽

Gamma Band ◽

Gain Modulation ◽

Area V4 ◽

Gamma Rhythm ◽

Area 21A ◽

Gamma Band Activity ◽

Band Activity

SummaryCognition requires the dynamic modulation of effective connectivity, i.e. the modulation of the postsynaptic neuronal response to a given input. If postsynaptic neurons are rhythmically active, this might entail rhythmic gain modulation, such that inputs synchronized to phases of high gain benefit from enhanced effective connectivity. We show that visually induced gamma-band activity in awake macaque area V4 rhythmically modulates responses to unpredictable stimulus events. This modulation exceeded a simple additive superposition of a constant response onto ongoing gamma-rhythmic firing, demonstrating the modulation of multiplicative gain. Gamma phases leading to strongest neuronal responses also led to shortest behavioral reaction times, suggesting functional relevance of the effect. Furthermore, we find that constant optogenetic stimulation of anesthetized cat area 21a produces gamma-band activity entailing a similar gain modulation. As the gamma rhythm in area 21a did not spread backwards to area 17, this suggests that postsynaptic gamma is sufficient for gain modulation.

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Alpha-to-beta- and gamma-band activity reflect predictive coding in affective visual processing

10.1101/2021.06.03.446893 ◽

2021 ◽

Author(s):

Andreas Strube ◽

Michael Rose ◽

Sepideh Fazeli ◽

Christian Büchel

Keyword(s):

Visual Processing ◽

Predictive Coding ◽

Gamma Band ◽

Prediction Errors ◽

Beta Band ◽

Picture Processing ◽

Gamma Frequencies ◽

Gamma Band Activity ◽

Spectral Patterns ◽

Band Activity

Processing of negative affective pictures typically leads to desynchronization of alpha-to-beta frequencies (ERD) and synchronization of gamma frequencies (ERS). Given that in predictive coding higher frequencies have been associated with prediction errors, while lower frequencies have been linked to expectations, we tested the hypothesis that alpha-to-beta ERD and gamma ERS induced by aversive pictures are associated with expectations and prediction errors, respectively. We recorded EEG while volunteers were involved in a probabilistically cued affective picture task using three different negative valences to produce expectations and prediction errors. Our data show that alpha-to-beta band activity was related to the expected valence of the stimulus as predicted by a cue. The absolute mismatch of the expected and actual valence, which denotes an absolute prediction error was related to gamma band activity. This demonstrates that top-down predictions and bottom-up prediction errors are represented in specific spectral patterns associated with affective picture processing.

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Neurofeedback Training Protocol Based on Selecting Distinctive Features to Treat or Reduce ADHD Symptoms

Clinical EEG and Neuroscience ◽

10.1177/15500594211033435 ◽

2021 ◽

pp. 155005942110334

Author(s):

Parham Jalali ◽

Nasrin Sho’ouri

Keyword(s):

Treatment Protocol ◽

Adhd Symptoms ◽

Eeg Signals ◽

Beta Band ◽

Distinctive Features ◽

Children With Adhd ◽

Hyperactivity Disorder ◽

Distinguishing Features ◽

Band Activity ◽

Training Protocol

Resent research has shown that electroencephalography (EEG) theta/beta ratio (TBR) in cases with attention deficit hyperactivity disorder (ADHD) has thus far been reported lower than that in healthy individuals. Accordingly, utilizing EEG-TBR as a biomarker to diagnose ADHD has been called into question. Besides, employing known protocol to reduce EEG-TBR in the vertex (Cz) channel to treat ADHD via neurofeedback (NFB) has been doubted. The present study was to propose a new NFB treatment protocol to manage ADHD using EEG signals from 30 healthy controls and 30 children with ADHD through an attention-based task and to calculate relative power in their different frequency bands. Then, the most significant distinguishing features of EEG signals from both groups were determined via a genetic algorithm (GA). The results revealed that EEG-TBR values in children with ADHD were lower compared with those in healthy peers; however, such a difference was not statistically significant. Likewise, inhibiting alpha band activity and enhancing delta one in F7 or T5 channels was proposed as a new NFB treatment protocol for ADHD. No significant increase in EEG-TBR in the Cz channel among children with ADHD casts doubt on the effectiveness of using EEG-TBR inhibitory protocols in the Cz channel. Consequently, it was proposed to apply the new protocol along with reinforced beta-band activity to treat or reduce ADHD symptoms.

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Identifying bidirectional total and non-linear information flow in functional corticomuscular coupling during a dorsiflexion task: a pilot study

Journal of NeuroEngineering and Rehabilitation ◽

10.1186/s12984-021-00872-w ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Tie Liang ◽

Qingyu Zhang ◽

Xiaoguang Liu ◽

Bin Dong ◽

Xiuling Liu ◽

...

Keyword(s):

Time Series ◽

Information Flow ◽

Gamma Band ◽

Motor Dysfunction ◽

Beta Band ◽

Short Time Series ◽

Information Interaction ◽

Stroke Group ◽

Short Time ◽

Maximal Information Coefficient

Abstract Background The key challenge to constructing functional corticomuscular coupling (FCMC) is to accurately identify the direction and strength of the information flow between scalp electroencephalography (EEG) and surface electromyography (SEMG). Traditional TE and TDMI methods have difficulty in identifying the information interaction for short time series as they tend to rely on long and stable data, so we propose a time-delayed maximal information coefficient (TDMIC) method. With this method, we aim to investigate the directional specificity of bidirectional total and nonlinear information flow on FCMC, and to explore the neural mechanisms underlying motor dysfunction in stroke patients. Methods We introduced a time-delayed parameter in the maximal information coefficient to capture the direction of information interaction between two time series. We employed the linear and non-linear system model based on short data to verify the validity of our algorithm. We then used the TDMIC method to study the characteristics of total and nonlinear information flow in FCMC during a dorsiflexion task for healthy controls and stroke patients. Results The simulation results showed that the TDMIC method can better detect the direction of information interaction compared with TE and TDMI methods. For healthy controls, the beta band (14–30 Hz) had higher information flow in FCMC than the gamma band (31–45 Hz). Furthermore, the beta-band total and nonlinear information flow in the descending direction (EEG to EMG) was significantly higher than that in the ascending direction (EMG to EEG), whereas in the gamma band the ascending direction had significantly higher information flow than the descending direction. Additionally, we found that the strong bidirectional information flow mainly acted on Cz, C3, CP3, P3 and CPz. Compared to controls, both the beta-and gamma-band bidirectional total and nonlinear information flows of the stroke group were significantly weaker. There is no significant difference in the direction of beta- and gamma-band information flow in stroke group. Conclusions The proposed method could effectively identify the information interaction between short time series. According to our experiment, the beta band mainly passes downward motor control information while the gamma band features upward sensory feedback information delivery. Our observation demonstrate that the center and contralateral sensorimotor cortex play a major role in lower limb motor control. The study further demonstrates that brain damage caused by stroke disrupts the bidirectional information interaction between cortex and effector muscles in the sensorimotor system, leading to motor dysfunction.

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Strengthened Corticosubcortical Functional Connectivity during Muscle Fatigue

Neural Plasticity ◽

10.1155/2016/1726848 ◽

2016 ◽

Vol 2016 ◽

pp. 1-11 ◽

Cited By ~ 5

Author(s):

Zhiguo Jiang ◽

Xiao-Feng Wang ◽

Guang H. Yue

Keyword(s):

Motor Control ◽

Functional Connectivity ◽

Quantile Regression ◽

Muscle Fatigue ◽

Motor Performance ◽

Primary Motor Cortex ◽

Motor Task ◽

Voluntary Contraction ◽

Control Network ◽

Subcortical Structures

The present study examined functional connectivity (FC) between functional MRI (fMRI) signals of the primary motor cortex (M1) and each of the three subcortical neural structures, cerebellum (CB), basal ganglia (BG), and thalamus (TL), during muscle fatigue using the quantile regression technique. Understanding activation relation between the subcortical structures and the M1 during prolonged motor performance should help delineate how central motor control network modulates acute perturbations at peripheral sensorimotor system such as muscle fatigue. Ten healthy subjects participated in the study and completed a 20-minute intermittent handgrip motor task at 50% of their maximal voluntary contraction (MVC) level. Quantile regression analyses were carried out to compare the FC between the contralateral (left) M1 and CB, BG, and TL in the minimal (beginning 100 s) versus significant (ending 100 s) fatigue stages. Widespread, statistically significant increases in FC were found in bilateral BG, CB, and TL with the left M1 during significant versus minimal fatigue stages. Our results imply that these subcortical nuclei are critical components in the motor control network and actively involved in modulating voluntary muscle fatigue, possibly, by working together with the M1 to strengthen the descending central command to prolong the motor performance.

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