beta frequency band
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2021 ◽  
Vol 15 ◽  
Author(s):  
Satoko Koganemaru ◽  
Fumiya Mizuno ◽  
Toshimitsu Takahashi ◽  
Yuu Takemura ◽  
Hiroshi Irisawa ◽  
...  

Swallowing in humans involves many cortical areas although it is partly mediated by a series of brainstem reflexes. Cortical motor commands are sent to muscles during swallow. Previous works using magnetoencephalography showed event-related desynchronization (ERD) during swallow and corticomuscular coherence (CMC) during tongue movements in the bilateral sensorimotor and motor-related areas. However, there have been few analogous works that use electroencephalography (EEG). We investigated the ERD and CMC in the bilateral sensorimotor, premotor, and inferior prefrontal areas during volitional swallow by EEG recordings in 18 healthy human subjects. As a result, we found a significant ERD in the beta frequency band and CMC in the theta, alpha, and beta frequency bands during swallow in those cortical areas. These results suggest that EEG can detect the desynchronized activity and oscillatory interaction between the cortex and pharyngeal muscles in the bilateral sensorimotor, premotor, and inferior prefrontal areas during volitional swallow in humans.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Francesco Luciano Donati ◽  
Matteo Fecchio ◽  
Davide Maestri ◽  
Mattia Cornali ◽  
Chiara Camilla Derchi ◽  
...  

AbstractDisturbances of conscious awareness, or self-disorders, are a defining feature of schizophrenia. These include symptoms such as delusions of control, i.e. the belief that one’s actions are controlled by an external agent. Models of self-disorders point at altered neural mechanisms of source monitoring, i.e. the ability of the brain to discriminate self-generated stimuli from those driven by the environment. However, evidence supporting this putative relationship is currently lacking. We performed electroencephalography (EEG) during self-paced, brisk right fist closures in ten (M = 9; F = 1) patients with Early-Course Schizophrenia (ECSCZ) and age and gender-matched healthy volunteers. We measured the Readiness Potential (RP), i.e. an EEG feature preceding self-generated movements, and movement-related EEG spectral changes. Self-disorders in ECSCZ were assessed with the Examination of Anomalous Self-Experience (EASE). Patients showed a markedly reduced RP and altered post-movement Event-Related Synchronization (ERS) in the beta frequency band (14–24 Hz) compared to healthy controls. Importantly, smaller RP and weaker ERS were associated with higher EASE scores in ECSCZ. Our data suggest that disturbances of neural correlates preceding and following self-initiated movements may reflect the severity of self-disorders in patients suffering from ECSCZ. These findings point towards deficits in basic mechanisms of sensorimotor integration as a substrate for self-disorders.


Nutrients ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 2186
Author(s):  
Ting-Yu Su ◽  
Pi-Lien Hung ◽  
Chien Chen ◽  
Ying-Jui Lin ◽  
Syu-Jyun Peng

Ketogenic diet therapies (KDTs) are widely used treatments for epilepsy, but the factors influencing their responsiveness remain unknown. This study aimed to explore the predictors or associated factors for KDTs effectiveness by evaluating the subtle changes in brain functional connectivity (FC) before and after KDTs. Segments of interictal sleep electroencephalography (EEG) were acquired before and after six months of KDTs. Analyses of FC were based on network-based statistics and graph theory, with a focus on different frequency bands. Seventeen responders and 14 non-responders were enrolled. After six months of KDTs, the responders exhibited a significant functional connectivity strength decrease compared with the non-responders; reductions in global efficiency, clustering coefficient, and nodal strength in the beta frequency band for a consecutive range of weighted proportional thresholds were observed in the responders. The alteration of betweenness centrality was significantly and positively correlated with seizure reduction rate in alpha, beta, and theta frequency bands in weighted adjacency matrices with densities of 90%. We conclude that KDTs tended to modify minor-to-moderate-intensity brain connections; the reduction of global connectivity and the increment of betweenness centrality after six months of KDTs were associated with better KD effectiveness.


BJPsych Open ◽  
2021 ◽  
Vol 7 (S1) ◽  
pp. S37-S38
Author(s):  
Paul M Briley ◽  
Elizabeth B Liddle ◽  
Karen J Mullinger ◽  
Molly Simmonite ◽  
Lena Palaniyappan ◽  
...  

AimsTo identify the BOLD (blood oxygenation level dependent) correlates of bursts of beta frequency band electrophysiological activity, and to compare BOLD responses between healthy controls and patients with psychotic illness.The post movement beta rebound (PMBR) is a transient increase in power in the beta frequency band (13-30 Hz), recorded with methods such as electroencephalography (EEG), following the completion of a movement. PMBR size is reduced in patients with schizophrenia and inversely correlated with severity of illness. PMBR size is inversely correlated with measures of schizotypy in non-clinical groups. Therefore, beta-band activity may reflect a fundamental neural process whose disruption plays an important role in the pathophysiology of schizophrenia. Recent work has found that changes in beta power reflect changes in the probability-of-occurrence of transient bursts of beta-frequency activity. Understanding the generators of beta bursts could help unravel the pathophysiology of psychotic illness and thus identify novel treatment targets.MethodEEG data were recorded simultaneously with BOLD data measured with 3T functional magnetic resonance imaging (fMRI), whilst participants performed an n-back working memory task. We included seventy-eight participants – 32 patients with schizophrenia, 16 with bipolar disorder and 30 healthy controls. Beta bursts were identified in the EEG data using a thresholding method and burst timings were used as markers in an event-related fMRI design convolved with a conventional haemodynamic response function. A region of interest analysis compared beta-event-related BOLD activity between patients and controls.ResultBeta bursts phasically activated brain regions implicated in coding task-relevant content (specifically, regions involved in the phonological representation of letter stimuli, as well as areas representing motor responses). Further, bursts were associated with suppression of tonically-active regions. In the EEG, PMBR was greater in controls than patients, and, in patients, PMBR size was positively correlated with Global Assessment of Functioning scores, and negatively correlated with persisting symptoms of disorganisation and performance on a digit symbol substition test. Despite this, patients showed greater, more extensive, burst-related BOLD activation than controls.ConclusionOur findings are consistent with a recent model in which beta bursts serve to reactivate latently-maintained, task-relevant, sensorimotor information. The increased BOLD response associated with bursts in patients, despite reduced PMBR, could reflect inefficiency of burst-mediated cortical synchrony, or it may suggest that the sensorimotor information reactivated by beta bursts is less precisely specified in psychosis. We propose that dysfunction of the mechanisms by which beta bursts reactivate task-relevant content can manifest as disorganisation and working memory deficits, and may contribute to persisting symptoms and impairment in psychosis.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Jee Sook Ra ◽  
Tianning Li ◽  
Yan Li

AbstractAnaesthesia is a state of temporary controlled loss of awareness induced for medical operations. An accurate assessment of the depth of anaesthesia (DoA) helps anesthesiologists to avoid awareness during surgery and keep the recovery period short. However, the existing DoA algorithms have limitations, such as not robust enough for different patients and having time delay in assessment. In this study, to develop a reliable DoA measurement method, pre-denoised electroencephalograph (EEG) signals are divided into ten frequency bands (α, β1, β2, β3, β4, β, βγ, γ, δ and θ), and the features are extracted from different frequency bands using spectral entropy (SE) methods. SE from the beta-gamma frequency band (21.5–38.5 Hz) and SE from the beta frequency band show the highest correlation (R-squared value: 0.8458 and 0.7312, respectively) with the most popular DoA index, bispectral index (BIS). In this research, a new DoA index is developed based on these two SE features for monitoring the DoA. The highest Pearson correlation coefficient by comparing the BIS index for testing data is 0.918, and the average is 0.80. In addition, the proposed index shows an earlier reaction than the BIS index when the patient goes from deep anaesthesia to moderate anaesthesia, which means it is more suitable for the real-time DoA assessment. In the case of poor signal quality (SQ), while the BIS index exhibits inflexibility with cases of poor SQ, the new proposed index shows reliable assessment results that reflect the clinical observations.


2021 ◽  
Vol 12 ◽  
Author(s):  
P. Archana Hebbar ◽  
Kausik Bhattacharya ◽  
Gowdham Prabhakar ◽  
Abhay A. Pashilkar ◽  
Pradipta Biswas

This paper discusses the utilization of pilots' physiological indications such as electroencephalographic (EEG) signals, ocular parameters, and pilot performance-based quantitative metrics to estimate cognitive workload. The study aims to derive a non-invasive technique to estimate pilot's cognitive workload and study their correlation with standard physiological parameters. Initially, we conducted a set of user trials using well-established psychometric tests for evaluating the effectiveness of pupil and gaze-based ocular metrics for estimating cognitive workload at different levels of task difficulty and lighting conditions. Later, we conducted user trials with the NALSim flight simulator using a business class Learjet aircraft model. We analyzed participants' ocular parameters, power levels of different EEG frequency bands, and flight parameters for estimating variations in cognitive workload. Results indicate that introduction of secondary task increases pilot's cognitive workload significantly. The beta frequency band of EEG, nearest neighborhood index specifying distribution of gaze fixation, L1 Norm of power spectral density of pupil diameter, and the duty cycle metric indicated variations in cognitive workload.


2020 ◽  
Author(s):  
Kei Nakagawa ◽  
Naoto Kadono ◽  
Takafumi Mitsuhara ◽  
Eiichiro Tanaka ◽  
Louis Yuge

Abstract Background: A close-fitting assisted walking device (RE-Gait) designed to assist ankle movements might be a novel approach for acquiring the forefoot rocker function in the gait cycle. The purpose of the present study was to investigate the effects of using RE-Gait by evaluating the intramuscular coherence (IMC) of the two parts of the tibialis anterior muscles (TA) in the initial, mid, and terminal swing phase, which could indicate whether the common synaptic drive of motor neurons was populated.Methods: Seventeen healthy volunteers walked on a treadmill at a comfortable speed before, during, and immediately after 15-minute RE-Gait intervention (pre / RG / post). RE-Gait supported plantar flexion at toe lift-off in the terminal stance phase and dorsiflexion in the initial swing phase. Electromyograms of the right lower leg and gait parameters were analyzed for each session.Results: After RE-Gait intervention, the step length was significantly increased. IMC of the two parts of the TA muscles in the beta frequency band in the initial swing phase was significantly enhanced during RE-Gait intervention compared with pre session. In addition, IMCs in the beta and low-gamma frequency bands were significantly correlated with the enhancement ratio of the step length.Conclusions: These results suggest that robotic ankle planter flexion and dorsiflexion assistance in the pre- and initial swing phase would be effective for learning adaptively modified walking by activating corticospinal tracts. RE-Gait will be a useful tool for re-learning of gait with smooth switching with appropriate forefoot rocker function.


2020 ◽  
Author(s):  
Jee Sook Ra ◽  
Tianning Li ◽  
Yan Li

Abstract Anaesthesia is a state of temporary controlled loss of awareness induced for medical purposes. An accurate assessment of the depth of anaesthesia (DoA) has always been required. However, the current DoA algorithms have limitations such as inaccuracy or inflexibility. In this study, for more reliable DoA assessment, pre-denoised electroencephalograph (EEG) signals are divided into ten frequency bands (α, β1, β2, β3, β4, β, βγ, γ, δ and θ), and the basic complexity measure is done by using spectral entropy (SE). SE from beta-gamma frequency band (21.5 - 38.5 Hz) and SE from beta frequency band show the highest R squared value (0.8458 and 0.7312, respectively) with currently the most popular DoA index, bispectral index (BIS). A new DoA index is developed based on these two SE values for monitoring the DoA and evaluated by comparing with the BIS index. The highest Pearson correlation coefficient is 0.918, and the average is 0.80. In addition, the proposed index shows an earlier reaction than BIS index when the patient from deep anaesthesia to moderate anaesthesia, and the consistency in the case of poor signal quality (SQ) while the BIS Index exhibits inflexibility with cases of poor SQ.


2020 ◽  
Author(s):  
Simon Schwab

Microstates (MS), the fingerprints of the momentarily and time-varying states of the brain derived from electroencephalography (EEG), are associated with the resting state networks (RSNs). However, using MS fluctuations along different EEG frequency bands to model the functional MRI (fMRI) signal has not been investigated so far, or elucidated the role of the thalamus as a fundamental gateway and a putative key structure in cortical functional networks. Therefore, in the current study, we used MS predictors in standard frequency bands to predict blood oxygenation level dependent (BOLD) signal fluctuations. We discovered that multivariate modeling of BOLD-fMRI using six EEG-MS classes in eight frequency bands strongly correlated with thalamic areas and large-scale cortical networks. Thalamic nuclei exhibited distinct patterns of correlations for individual MS that were associated with specific EEG frequency bands. Anterior and ventral thalamic nuclei were sensitive to the beta frequency band, medial nuclei were sensitive to both alpha and beta frequency bands, and posterior nuclei such as the pulvinar were sensitive to delta and theta frequency bands. These results demonstrate that EEG-MS informed fMRI can elucidate thalamic activity not directly observable by EEG, which may be highly relevant to understand the rapid formation of thalamocortical networks.


2020 ◽  
Vol 204 ◽  
pp. 104758 ◽  
Author(s):  
Michele Scaltritti ◽  
Caterina Suitner ◽  
Francesca Peressotti

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