Beta EEG Bands Research Articles

Evidence of language-related left hypofrontality in Major Depression: An EEG Beta band study

Major depression (MDD) has been associated with an altered EEG frontal asymmetry measured in resting state; nevertheless, this association has showed a weak consistency across studies. In the present study, which starts from an evolutionistic view of psychiatric disorders, we investigated frontal asymmetry in MDD, using language as a probe to test the integrity of large inter- and intra-hemispheric networks and processes. Thirty MDD patients (22 women) and 32 matched controls (HC) were recruited for an EEG recording in resting state and during two linguistic tasks, phonological and semantic. Normalized alpha and beta EEG spectral bands were measured across all three conditions in the two groups. EEG alpha amplitude showed no hemispheric asymmetry, regardless of group, both at rest and during linguistic tasks. During resting state, analysis of EEG beta revealed a lack of hemispheric asymmetry in both groups, but during linguistic tasks, HC exhibited the typical greater left frontal beta activation, whereas MDD patients showed a lack of frontal asymmetry and a significantly lower activation of left frontal sites. In depressed patients, positive affect was negatively correlated with depression levels and positively correlated with left frontal EEG beta amplitude. Language represents the human process that requires the largest level of integration between and within the hemispheres; thus, language asymmetry was a valid probe to test the left frontal alteration encompassing highly impairing psychiatric disorders, such as schizophrenia and MDD. Indeed, these severe diseases are marked by delusions, ruminations, thought disorders, and hallucinations, all of which have a clear linguistic or metalinguistic basis.

Evaluating the Acute Effect of Stereoscopic Recovery by Dichoptic Stimulation Using Electroencephalogram.

Amblyopia is a common developmental disorder in adolescents and children. Stereoscopic loss is a symptom of amblyopia that can seriously affect the quality of patient's life. Recent studies have shown that the push-pull perceptual learning protocol had a positive effect on stereoscopic recovery. In this study, we developed a stereoscopic training method using a polarized visualization system according to the push-pull protocol. Dichoptic stimulation for 36 anisometropic and amblyopic subjects and 33 children with normal visual acuity (VA) has been conducted. Electroencephalogram (EEG) was used to evaluate the neurophysiological changes before, during, and after stimulation. For the anisometropic and amblyopic subjects, the statistical analysis demonstrated significant differences (p < 0.01) in the beta rhythm at the middle temporal and occipital lobes, while the EEG from the normal VA subjects indicated no significant changes when comparing the results before and after training. We concluded that the dichoptic training in our study can activate the middle temporal visual area and visual cortex. The EEG changes can be used to evaluate the training effects. This study also found that the beta band EEG acquired during visual stimulation at the dorsal visual stream can be potentially used for predicting acute training effect. The results facilitated the optimization of the individual training plan.

Prediction of treatment resistance in obsessive compulsive disorder patients based on EEG complexity as a biomarker

ObjectiveThis study aimed to identify an Electroencephalography (EEG) complexity biomarker that could predict treatment resistance in Obsessive compulsive disorder (OCD) patients. Additionally, the statistical differences between EEG complexity values in treatment-resistant and treatment-responsive patients were determined. Moreover, the existence of correlations between EEG complexity and Yale-Brown Obsessive Compulsive Scale (YBOCS) score were evaluated. MethodsEEG data for 29 treatment-resistant and 28 treatment-responsive OCD patients were retrospectively evaluated. Approximate entropy (ApEn) method was used to extract the EEG complexity from both whole EEG data and filtered EEG data, according to 4 common frequency bands, namely delta, theta, alpha, and beta. The random forests method was used to classify ApEn complexity. ResultsApEn complexity extracted from beta band EEG segments discriminated treatment-responsive and treatment-resistant OCD patients with an accuracy of 89.66% (sensitivity: 89.44%; specificity: 90.64%). Beta band EEG complexity was lower in the treatment-resistant patients and the severity of OCD, as measured by YBOCS score, was inversely correlated with complexity values. ConclusionsThe results indicate that, EEG complexity could be considered a biomarker for predicting treatment response in OCD patients. SignificanceThe prediction of treatment response in OCD patients might help clinicians devise and administer individualized treatment plans.

Resting-state EEG beta band power predicts quality of life outcomes in patients with depressive disorders: A longitudinal investigation

BackgroundQuality of life is severely impaired in patients with depressive disorders. Previous studies have focused on biomarkers predicting depressive symptomatology; however, studies investigating biomarkers predicting quality of life outcomes are limited. Improving quality of life is important because it is related not only to mental health but also to physical health. We need to develop a biomarker related to quality of life as a therapeutic target for patients with depressive disorders. Resting-state electroencephalography (EEG) is easy to record in clinical settings. The index of bandwidth spectral power predicts treatment response in depressive disorders and thus may be a candidate biomarker. However, no longitudinal studies have investigated whether EEG-recorded power could predict quality of life outcomes in patients with depressive disorders. MethodsThe resting-state EEG-recorded bandwidth spectral power at baseline and the World Health Organization Quality of Life (QOL)-26 scores at 3-year follow-up were measured in 44 patients with depressive disorders. ResultsThe high beta band power (20–30 Hz) at baseline significantly predicted QOL at the 3-year follow-up after considering depressive symptoms and medication effects in a longitudinal investigation in patients with depressive disorders (β = 0.38, p = 0.01). LimitationsWe did not have healthy subjects as a comparison group in this study. ConclusionsOur findings suggest that resting-state beta activity has the potential to be a useful biomarker for predicting future quality of life outcomes in patients with depressive disorders.

Frequency domain analysis for the classification of parkinson’s disease patients

In this paper, Emotional recognition in Parkinson’s disease (PD) has been analyzed in frequency domain using Entropy, Energy-Entropy and Teager Energy-Entropy features. Classification results were observed using three classifiers namely Probabilistic Neural Network, K-Nearest Neighbors Algorithm and Support Vector Machine. Emotional EEG stimuli such as happiness, sadness, fear, anger, surprise, and disgust were used to categorize the PD patients and healthy controls (HC). For each EEG signal, the alpha, beta and gamma band frequency features are obtained for three different feature extraction methods (Spectral Entropy, Spectral Energy-Entropy, and Spectral Teager Energy-Entropy). The proposed Spectral Energy–Entropy feature performs well for all six emotions for different classifiers when compared to other features, whereas different features with classifiers give variant results for few emotions with highest accuracy of 96.8%.

Role of the cortex in visuomotor control of arm stability.

Whereas numerous motor control theories describe the control of arm trajectory during reach, the control of stabilization in a constant arm position (i.e., visuomotor control of arm posture) is less clear. Three potential mechanisms have been proposed for visuomotor control of arm posture: 1) increased impedance of the arm through co-contraction of antagonistic muscles, 2) corrective muscle activity via spinal/supraspinal reflex circuits, and/or 3) intermittent voluntary corrections to errors in position. We examined the cortical mechanisms of visuomotor control of arm posture and tested the hypothesis that cortical error networks contribute to arm stabilization. We collected electroencephalography (EEG) data from 10 young healthy participants across four experimental planar movement tasks. We examined brain activity associated with intermittent voluntary corrections of position error and antagonist co-contraction during stabilization. EEG beta-band (13-26 Hz) power fluctuations were used as indicators of brain activity, and coherence between EEG electrodes was used as a measure of functional connectivity between brain regions. Cortical activity in the sensory, motor, and visual areas during arm stabilization was similar to activity during volitional arm movements and was larger than activity during co-contraction of the arm. However, cortical connectivity between the sensorimotor and visual regions was higher during arm stabilization compared with volitional arm movements and co-contraction of the arm. The difference in cortical activity and connectivity between tasks might be attributed to an underlying visuomotor error network used to update motor commands for visuomotor control of arm posture.NEW & NOTEWORTHY We examined cortical activity and connectivity during control of stabilization in a constant arm position (i.e., visuomotor control of arm posture). Our findings provide evidence for cortical involvement during control of stabilization in a constant arm position. A visuomotor error network appears to be active and may update motor commands for visuomotor control of arm posture.

Modulation of the Visual to Auditory Human Inhibitory Brain Network: An EEG Dipole Source Localization Study.

Auditory alarms are used to direct people’s attention to critical events in complicated environments. The capacity for identifying the auditory alarms in order to take the right action in our daily life is critical. In this work, we investigate how auditory alarms affect the neural networks of human inhibition. We used a famous stop-signal or go/no-go task to measure the effect of visual stimuli and auditory alarms on the human brain. In this experiment, go-trials used visual stimulation, via a square or circle symbol, and stop trials used auditory stimulation, via an auditory alarm. Electroencephalography (EEG) signals from twelve subjects were acquired and analyzed using an advanced EEG dipole source localization method via independent component analysis (ICA) and EEG-coherence analysis. Behaviorally, the visual stimulus elicited a significantly higher accuracy rate (96.35%) than the auditory stimulus (57.07%) during inhibitory control. EEG theta and beta band power increases in the right middle frontal gyrus (rMFG) were associated with human inhibitory control. In addition, delta, theta, alpha, and beta band increases in the right cingulate gyrus (rCG) and delta band increases in both right superior temporal gyrus (rSTG) and left superior temporal gyrus (lSTG) were associated with the network changes induced by auditory alarms. We further observed that theta-alpha and beta bands between lSTG-rMFG and lSTG-rSTG pathways had higher connectivity magnitudes in the brain network when performing the visual tasks changed to receiving the auditory alarms. These findings could be useful for further understanding the human brain in realistic environments.

EEG power spectrum analysis for schizophrenia during mental activity.

Cognitive dysfunction is a core defect for schizophrenia subjects. This is due to structural and functional abnormalities of the brain which can be determined using Electroencephalogram (EEG). The objective of this study is to analyze EEG in patients with schizophrenia using power spectral density during mental activity. The subjects included in this study are 52 schizophrenia subjects and 29 Normal subjects. EEG is recorded under resting condition and during mental activity. Two modified odd ball paradigms are designed to stimulate mental activity and named as stimulus 1 and stimulus 2. EEG signal is filtered using FIR band pass filter to extract delta, theta, alpha, and beta band EEG. This method measures powers of each band using Welch power spectral density method called absolute power. The absolute power of alpha band is low and beta band is high for schizophrenia subjects compared to normal subjects during rest and two stimuli. Student's t-test is used to find the significant features (p < 0.05) at each recording condition. The significant features from each recording condition are used to classify Schizophrenia using both BPN and SVM classifier. SVM classifier is produced maximum sensitivity of 91% when features from allrecording conditions are combined together. Thus this work concludes that the mental activity EEG supports for classifying Schizophrenia from normal and hence absolute band powers can be used as features to identify Schizophrenia.

Abstract #130: EEG Beta-band Coherence for Prognosis of Motor Recovery in Stroke Patients with tDCS-BCI Intervention

Abstract #130: EEG Beta-band Coherence for Prognosis of Motor Recovery in Stroke Patients with tDCS-BCI Intervention

EEG Beta band frequency domain evaluation for assessing stress and anxiety in resting, eyes closed, basal conditions

The study presents a frequency domain, instead of a relative power intensity comparison framework domain, that evaluates the degree of anxiety and stress brain network activated in high beta oscillation (22-30 Hz), during a resting, EC basal condition of EEG recording. The parameter measured served as an evaluator of the brain spontaneous, self-generated, global de-synchronizing, workload endogenous attractors that displace the EEG oscillatory dynamics toward free energy-consuming processing loops. The distinction of the high beta EEG waves as related with stress and anxiety, together with an approach based primarily on the inter-channel frequency correlation, rather than only the power activation of the frequency beta range, allowed us to supplement with new finding and ways to evaluate the impact of self-generated processing attractors that kept our brain apart from natural tendency to re-synchronize, save and reorganize energy.

Clinical utility of portable electrophysiology to measure fatigue in treatment-naïve non-small cell lung cancer.

Cancer-related fatigue (CRF) biology remains poorly understood. Responsible mechanisms may be central or peripheral and originate anywhere from the brain to muscle fiber. Objective measurement is complex and previously limited to specialized laboratories. Portable electroencephalography (EEG) and electromyography (EMG) may enhance objective measurement. This study evaluated the feasibility and acceptability of portable EMG-EEG in CRF assessment. A prospective observational feasibility study compared ten outpatients with inoperable, treatment-naïve non-small cell lung cancer and CRF to ten healthy volunteers. All completed a sustained isometric hand-grip contraction at 30% maximal level until self-perceived exhaustion. 128-channel EEG and 2-channel EMG signals of forearm muscles were recorded. Device acceptability was evaluated by questionnaire. The task was evaluated in two stages; first and last 20s. CRF cohort perceived exhaustion earlier than volunteers (mean 137 ± 76s vs 208 ± 51s). As fatigue progressed, EMG amplitude increased significantly (CRF p =0.02; volunteers: p =0.04) in both groups as did EMG beta band power (CRF p =0.008; volunteers: p =0.006). The increase was significantly less in CRF (amplitude p =0.032; beta power: p =0.014). EEG beta band power in the contralateral motor cortex increased significantly (CRF p =0.03; volunteers: p =0.019) in both cohorts but to greater extent (p =0.024) in CRF. One hundred percent device acceptability was reported. A laboratory-based evaluation was successfully adapted to the outpatient setting during routine visits. High acceptability supports clinical utility. In CRF, a higher degree of cortical activation was required to drive a much lower level of muscle performance. This suggests impairment of both central and peripheral mechanisms in CRF.

An EEG Experimental Study Evaluating the Performance of Texas Instruments ADS1299.

Texas Instruments ADS1299 is an attractive choice for low cost electroencephalography (EEG) devices owing to its low power consumption and low input referred noise. To date, there have been no rigorous evaluations of its performance. In this EEG experimental study we evaluated the performance of the ADS1299 against a high quality laboratory-based system. Two self-paced lower limb motor tasks were performed by 22 healthy participants. Recorded power across delta, theta, alpha, and beta EEG bands, the power ratio across the motor tasks, pre-movement noise, and signal-to-noise ratio were obtained for evaluation. The amplitude and time of the negative peak in the movement-related cortical potentials (MRCPs) extracted from the EEG data were also obtained. Using linear mixed models, no statistically significant differences (p > 0.05) were found in any of these measures across the two systems. These findings were further supported by evaluation of cosine similarity, waveform differences, and topographic maps. There were statistically significant differences in MRCPs across the motor tasks in both systems. We conclude that the performance of the ADS1299 in combination with wet Ag/AgCl electrodes is analogous to that of a laboratory-based system in a low frequency (<40 Hz) EEG recording.

Analysis of Electroencephalography Event-Related Desynchronisation and Synchronisation Induced by Lower-Limb Stepping Motor Imagery

Bilateral upper-limb motor imagery has been demonstrated to be a useful mental task in electroencephalography (EEG)-based brain–computer interfaces (BCIs). By contrast, few studies have examined bilateral lower-limb motor imagery, and all of them have focused on imaginary foot movements. The left–right classification accuracy reported in these studies based on the EEG mu rhythm (8–13 Hz) and beta band (13–30 Hz) remains unsatisfactory. The present study investigated the possibility of using lower-limb stepping motor imagery as the mental task and analysed the EEG difference between imaginary left-leg stepping (L-stepping) and right-leg stepping (R-stepping) movements. An experimental paradigm was designed to collect 5-s motor imagery EEG signals at nine recording sites around the vertex of the brain. Results from eight able-bodied participants indicated that the commonly used mu event-related desynchronisation (ERD) feature exhibited no significant difference between the two imaginary movements for all recording sites and all time intervals within the 5-s motor imagery period. Regarding the other commonly used feature, beta event-related synchronisation, no significant difference between the two imagery tasks was observed for most of the recording sites and time intervals. Instead, theta band (4–8 Hz) ERD significantly differed between the L- and R-stepping imagery tasks at five sites (FC4, C3, CP3, Cz, CPz) within the first 2 s after motor imagery cue onset. The findings from the present study may be a basis for further development of BCI systems for decoding left and right stepping during mental exercise where the two motions are alternately imagined.

Daytime Effect of Monochromatic Blue Light on EEG Activity Depends on Duration and Timing of Exposure in Young Men.

Growing evidence suggests an alerting effect of monochromatic blue light on brain activity. Little is known about the moderation of those effects by timing and duration of exposure. The present electroencephalography (EEG ) study examined such moderations on delta, theta, alpha1, alpha2, and beta EEG bands. A counterbalanced repeated-measures design was applied. The 16-hr daytime period was divided into three sessions: 07:00-12:20, 12:20-17:40, and 17:40-23:00 (timing of exposure). Two light conditions comparable in luminance but differing in wavelength were applied, namely polychromatic white light and monochromatic blue light (460 nm). There were two durations of exposure—the shorter one lasting 30 min and the longer one lasting 4 hrs. Thirty male students participated in the study. Four factors analyses of variance (ANOV As, for light conditions, timing of exposure, duration of exposure, and brain area) were performed on each EEG band. Results indicated an alerting effect of short exposure to monochromatic blue light at midday and in the evening, which was demonstrated by a decrease in lower frequency bands (alpha1, delta, and theta, respectively). Long exposure to blue light may have a reverse effect, especially in the morning and at midday, when increases in lower frequency bands (theta in the morning and theta and alpha1 at midday) were observed. It can be concluded that the daytime effect of monochromatic blue light on EEG activity depends on timing and duration of exposure.

Exploring the relationship of phase and peak-frequency EEG alpha-band and beta-band activity to temporal judgments of stimulus duration

ABSTRACTPre-stimulus phase has been shown to influence temporal judgments concerning order, causality and simultaneity. One hypothesis is that phase cycles frame discrete perceptual snapshots over time. Yet, existing studies have explored the effect of pre-stimulus phase on fine-grained temporal judgments whereas no study has shown whether pre-stimulus phase influences sub-second temporal judgments lasting several phase cycles. If effects of phase on fine-grained temporal judgments reflect perceptual framing, then the perception of longer intervals might show some dependency on the frequency of phase cycles. Higher frequencies should promote increased temporal resolution and discrimination. We tested the relationship between the phase and frequency of oscillations and temporal judgments for longer durations. Participants judged the relative duration of two successive intervals lasting several phase cycles each. Pre-stimulus alpha-band and beta-band phase was associated with subsequent temporal judgments, although not sensitivity, therein providing evidence that pre-stimulus phase is related to temporal judgments that span a longer time-scale than has been previously demonstrated. Although we report evidence that peak-frequency of the alpha-band is related to one measure of task performance, this study does not provide evidence that higher peak frequencies of alpha- or beta-band activity are related to improved duration discrimination of longer intervals.

EEG frequency tagging using ultra-slow periodic heat stimulation of the skin reveals cortical activity specifically related to C fiber thermonociceptors

The recording of event-related brain potentials triggered by a transient heat stimulus is used extensively to study nociception and diagnose lesions or dysfunctions of the nociceptive system in humans. However, these responses are related exclusively to the activation of a specific subclass of nociceptive afferents: quickly-adapting thermonociceptors. In fact, except if the activation of Aδ fibers is avoided or if A fibers are blocked, these responses specifically reflect activity triggered by the activation of Type 2 quickly-adapting A fiber mechano-heat nociceptors (AMH-2). Here, we propose a novel method to isolate, in the human electroencephalogram (EEG), cortical activity related to the sustained periodic activation of heat-sensitive thermonociceptors, using very slow (0.2Hz) and long-lasting (75s) sinusoidal heat stimulation of the skin between baseline and 50°C. In a first experiment, we show that when such long-lasting thermal stimuli are applied to the hand dorsum of healthy volunteers, the slow rises and decreases of skin temperature elicit a consistent periodic EEG response at 0.2Hz and its harmonics, as well as a periodic modulation of the magnitude of theta, alpha and beta band EEG oscillations. In a second experiment, we demonstrate using an A fiber block that these EEG responses are predominantly conveyed by unmyelinated C fiber nociceptors. The proposed approach constitutes a novel mean to study C fiber function in humans, and to explore the cortical processing of tonic heat pain in physiological and pathological conditions.

Association between individual EEG characteristics and the level of intelligence

The aim of this study was to investigate the relationship between individual electroencephalogram (EEG) characteristics in the resting state and the level of nonverbal intelligence. The study involved 77 students of Demidov Yaroslavl State University. Analysis of the relationship between IQ and spectral parameters of EEG theta, alpha, and two subbands of beta oscillations revealed that the amplitude and power of alphaband EEG oscillations and low frequency beta-band EEG oscillations were positively correlated with the performance in the nonverbal intelligence test. The variety of brain periodic regimes was assessed using the correlation dimension (CD) of EEG. The correlation dimension can be used to quantify the degree of complexity of the nonlinear dynamical system. It was found that the value of the EEG correlation dimension was positively associated with the level of intelligence. The periodicity of the EEG signal was studied using autocorrelation analysis. It was shown that the autocorrelogram duration was negatively associated with IQ and the autocorrelogram amplitude was positively associated with IQ. A regression equation for predicting the level of nonverbal intelligence based on the power of theta- and beta-band oscillations, alpha-band oscillation indexes, and the amplitude and autocorrelation characteristics of the EEG signal was obtained.

Altered Language Asymmetry in patients with Major Depression: a Beta EEG band study

Altered Language Asymmetry in patients with Major Depression: a Beta EEG band study

Brain and Cardiorespiratory Responses to Exercise in Hot and Thermoneutral Conditions.

The aim of this study was to test whether or not concurrent evaluations of brain (electroencephalography [EEG]) and cardiorespiratory responses to exercise are influenced by environmental conditions. 10 adult male participants performed a standardized incremental exercise test to exhaustion on a cycle ergometer in an environment controlled laboratory on 2 separate occasions, in a randomized order; one in a hot condition (34.5°C) and one in a thermoneutral condition (20°C). EEG, heart rate and expired air were collected throughout. EEG data were decontaminated for artefacts, log-transformed and expressed as aggregated alpha and beta power responses across electrodes reflecting the frontal cortex of the brain. Performance outcomes showed there was no difference in V˙O2 peak across hot (42.5 ml/kg/min) and neutral (42.8 ml/kg/min) conditions, although ventilatory threshold (VT) occurred at a lower threshold (68%) in hot compared to neutral condition (74%) (p<0.05). EEG alpha and beta wave responses both demonstrated significant increases from baseline to VT (p<0.01). EEG beta-band activity was significantly elevated in the heat compared to the neutral condition. In conclusion, elevated EEG beta-band activity in response to incremental exercise in the heat suggests that beta-band activation and cortical awareness increases as exercise becomes increasingly intense.

Visualization of Brain Connectivity during Emotion induction

Visualization of Brain Connectivity during Emotion induction