Depth of anaesthesia assessment based on adult electroencephalograph beta frequency band

2016 ◽  
Vol 39 (3) ◽  
pp. 773-781 ◽  
Author(s):  
Tianning Li ◽  
Peng Wen
Keyword(s):  
Frequency Band ◽  
Depth Of Anaesthesia ◽  
Beta Frequency Band ◽  
Beta Frequency

scholarly journals Depth of Anaesthesia Assessment Based on Spectral Entropy

2020 ◽  
Author(s):  
Jee Sook Ra ◽  
Tianning Li ◽  
Yan Li
Keyword(s):  
Frequency Band ◽  
Pearson Correlation ◽  
Signal Quality ◽  
Spectral Entropy ◽  
Eeg Signals ◽  
Depth Of Anaesthesia ◽  
Gamma Frequency ◽  
Beta Frequency Band ◽  
Deep Anaesthesia ◽  
Beta Frequency

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.

Analysis of correlation between body mass index (BMI) and brain wave using EEG for Alpha and Beta frequency band

2009 ◽  
Author(s):  
Ros Shilawani S. Abdul Kadir ◽  
Azlan Hakimi Yahaya Rashid ◽  
Husna Abdul Rahman ◽  
Mohd Nasir Taib ◽  
Zunairah Hj. Murat ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Frequency Band ◽  
Brain Wave ◽  
Beta Frequency Band ◽  
Beta Frequency

scholarly journals Surprise About Sensory Event Timing Drives Cortical Transients in the Beta Frequency Band

2018 ◽  
Author(s):  
T. Meindertsma ◽  
N.A. Kloosterman ◽  
A.K. Engel ◽  
E.J. Wagenmakers ◽  
T.H. Donner
Keyword(s):  
Frequency Band ◽  
Ideal Observer ◽  
Beta Band ◽  
Statistical Structure ◽  
Population Activity ◽  
Sensory Event ◽  
Event Timing ◽  
Beta Frequency Band ◽  
Observer Model ◽  
Beta Frequency

AbstractLearning the statistical structure of the environment is crucial for adaptive behavior. Humans and non-human decision-makers seem to track such structure through a process of probabilistic inference, which enables predictions about behaviorally relevant events. Deviations from such predictions cause surprise, which in turn helps improve inference. Surprise about the timing of behaviorally relevant sensory events drives phasic responses of neuromodulatory brainstem systems, which project to the cerebral cortex. Here, we developed a computational model-based magnetoencephalography (MEG) approach for mapping the resulting cortical transients across space, time, and frequency, in the human brain (N=28, 17 female). We used a Bayesian ideal observer model to learn the statistics of the timing of changes in a simple visual detection task. This model yielded quantitative trial-by-trial estimates of temporal surprise. The model-based surprise variable predicted trial-by trial variations in reaction time more strongly than the externally observable interval timings alone. Trial-by-trial variations in surprise were negatively correlated with the power of cortical population activity measured with MEG. This surprise-related power suppression occurred transiently around the behavioral response, specifically in the beta frequency band. It peaked in parietal and prefrontal cortices, remote from the motor cortical suppression of beta power related to overt report (button press) of change detection. Our results indicate that surprise about sensory event timing transiently suppresses ongoing beta-band oscillations in association cortex. This transient suppression of frontal beta-band oscillations might reflect an active reset triggered by surprise, and is in line with the idea that beta-oscillations help maintain cognitive sets.Significance statementThe brain continuously tracks the statistical structure of the environment to anticipate behaviorally relevant events. Deviations from such predictions cause surprise, which in turn drives neural activity in subcortical brain regions that project to the cerebral cortex. We used magnetoencephalography in humans to map out surprise-related modulations of cortical population activity across space, time, and frequency. Surprise was elicited by variable timing of visual stimulus changes requiring a behavioral response. Surprise was quantified by means of an ideal observer model. Surprise predicted behavior as well as a transient suppression of beta frequency band oscillations in frontal cortical regions. Our results are in line with conceptual accounts that have linked neural oscillations in the beta-band to the maintenance of cognitive sets.

scholarly journals Language and motor processing in reading and typing: Insights from beta-frequency band power modulations

2020 ◽  
Vol 204 ◽  
pp. 104758 ◽  
Author(s):  
Michele Scaltritti ◽  
Caterina Suitner ◽  
Francesca Peressotti
Keyword(s):  
Frequency Band ◽  
Motor Processing ◽  
Band Power ◽  
Beta Frequency Band ◽  
Beta Frequency

scholarly journals Surprise About Sensory Event Timing Drives Cortical Transients in the Beta Frequency Band

2018 ◽  
Vol 38 (35) ◽  
pp. 7600-7610 ◽  
Author(s):  
Thomas Meindertsma ◽  
Niels A. Kloosterman ◽  
Andreas K. Engel ◽  
Eric-Jan Wagenmakers ◽  
Tobias H. Donner
Keyword(s):  
Frequency Band ◽  
Sensory Event ◽  
Event Timing ◽  
Beta Frequency Band ◽  
Beta Frequency

scholarly journals Prefrontal-posterior coupling mediates emotion transitions and their influence on executive function

2019 ◽  
Author(s):  
Yu Hao ◽  
Lin Yao ◽  
Derek. M. Smith ◽  
Edward Sorel ◽  
Adam K. Anderson ◽  
...  
Keyword(s):  
Executive Function ◽  
Chronic Stress ◽  
Frequency Band ◽  
Self Regulation ◽  
Dynamic Conditions ◽  
Brain Functions ◽  
Affective Stimuli ◽  
Beta Frequency Band ◽  
Static Conditions ◽  
Beta Frequency

ABSTRACTAlthough emotions often result from dynamic experiences with self-regulation unfolding over time, most research has focused on responses to affective stimuli from a rather static perspective. We studied and analyzed emotion transitions, attempting to reveal brain functions related to affect dynamics. EEG responses were examined during exposure to stable versus changing emotion-eliciting images (static vs dynamic conditions) plus their impact on executive function (EF) assessed with the flanker task. During dynamic conditions, reduced prefrontal to posterior EEG coherence in the beta frequency band and greater left frontal activity occurred compared to the static conditions. Among individuals suffering higher chronic stress, subsequent EF was hindered after dynamic conditions. Furthermore, the adverse effects of emotion transitions on EF for more chronically stressed individuals were mediated by prefrontal-posterior coherence in low beta frequency band during emotional image sequences. Emotion appears to influence EF through changes in large-scale synchronization. Individuals high in chronic stress are vulnerable to these effects.

scholarly journals Rectification of EMG in low force contractions improves detection of motor unit coherence in the beta-frequency band

2013 ◽  
Vol 110 (8) ◽  
pp. 1744-1750 ◽  
Author(s):  
Nicholas J. Ward ◽  
Simon F. Farmer ◽  
Luc Berthouze ◽  
David M. Halliday
Keyword(s):  
Spectral Analysis ◽  
Experimental Evidence ◽  
Motor Unit ◽  
Frequency Band ◽  
Middle Finger ◽  
Surface Emg ◽  
Partial Coherence ◽  
Single Motor Units ◽  
Beta Frequency Band ◽  
Beta Frequency

Rectification of surface EMG before spectral analysis is a well-established preprocessing method used in the detection of motor unit firing patterns. A number of recent studies have called into question the need for rectification before spectral analysis, pointing out that there is no supporting experimental evidence to justify rectification. We present an analysis of 190 records from 13 subjects consisting of simultaneous recordings of paired single motor units and surface EMG from the extensor digitorum longus muscle during middle finger extension against gravity (unloaded condition) and against gravity plus inertial loading (loaded condition). We directly examine the hypothesis that rectified surface EMG is a better predictor of the frequency components of motor unit synchronization than the unrectified (or raw) EMG in the beta-frequency band (15–32 Hz). We use multivariate analysis and estimate the partial coherence between the paired single units using both rectified and unrectified surface EMG as a predictor. We use a residual partial correlation measure to quantify the difference between raw and rectified EMG as predictor and analyze unloaded and loaded conditions separately. The residual correlation for the unloaded condition is 22% with raw EMG and 3.5% with rectified EMG and for the loaded condition it is 5.2% with raw EMG and 1.4% with rectified EMG. We interpret these results as strong supporting experimental evidence in favor of using the preprocessing step of surface EMG rectification before spectral analysis.

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