scholarly journals Preshooting Electroencephalographic Activity of Professional Shooters in a Competitive State

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Jie Zhang ◽  
Yunxu Shi ◽  
Chienkai Wang ◽  
Chunmei Cao ◽  
Changshui Zhang ◽  
...  
Keyword(s):  
Alpha Power ◽  
Average Reference ◽  
Significant Linear Correlation ◽  
Beta Power ◽  
Neural Efficiency ◽  
Competitive Shooting ◽  
Electroencephalographic Activity ◽  
Electrocardiogram Ecg ◽  
Electroencephalogram Eeg ◽  
Air Rifle

This study investigated the influence of competitive state on cerebral cortex activity of professional shooters with 10 m air rifle before shooting. Generally, professional athletes have higher neural efficiency compared with ordinary people. We recruited 11 national shooters to complete 60 shots under both noncompetitive and competitive shooting conditions, and simultaneously collected their electroencephalogram (EEG) and electrocardiogram (ECG) information. Theta, alpha, and beta power were computed in the last three seconds preceding each shot from average-reference 29-channel EEG, while EEG characteristics under two conditions were analyzed. The results showed a significant linear correlation between shooting accuracy and EEG power of anterior frontal, central, temporal, and occipital regions in beta and theta bands. In addition, the theta power in occipital regions, alpha power in frontal-central and left occipital regions, and beta power in frontal and mid-occipital regions were higher than those in noncompetitive state. However, heart rate (HR) and shooting accuracy did not change significantly under the two conditions. These findings reveal the changes of cortical activity underlying competition shooting as well as providing further understanding of the neural mechanisms of the shooting process and lay a foundation for the subsequent neuromodulation research.

scholarly journals The influence of induction speed on the frontal (processed) EEG

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
D. P. Obert ◽  
P. Sepúlveda ◽  
S. Kratzer ◽  
G. Schneider ◽  
M. Kreuzer
Keyword(s):  
Injection Rate ◽  
Alpha Power ◽  
Verbal Command ◽  
Spectral Edge Frequency ◽  
Induction Group ◽  
Power Spectral ◽  
Beta Power ◽  
Processed Eeg ◽  
Electroencephalogram Eeg ◽  
Slow Injection

Abstract The intravenous injection of the anaesthetic propofol is clinical routine to induce loss of responsiveness (LOR). However, there are only a few studies investigating the influence of the injection rate on the frontal electroencephalogram (EEG) during LOR. Therefore, we focused on changes of the frontal EEG especially during this period. We included 18 patients which were randomly assigned to a slow or fast induction group and recorded the frontal EEG. Based on this data, we calculated the power spectral density, the band powers and band ratios. To analyse the behaviour of processed EEG parameters we calculated the beta ratio, the spectral entropy, and the spectral edge frequency. Due to the prolonged induction period in the slow injection group we were able to distinguish loss of responsiveness to verbal command (LOvR) from loss of responsiveness to painful stimulus (LOpR) whereas in the fast induction group we could not. At LOpR, we observed a higher relative alpha and beta power in the slow induction group while the relative power in the delta range was lower than in the fast induction group. When concentrating on the slow induction group the increase in relative alpha power pre-LOpR and even before LOvR indicated that frontal EEG patterns, which have been suggested as an indicator of unconsciousness, can develop before LOR. Further, LOvR was best reflected by an increase of the alpha to delta ratio, and LOpR was indicated by a decrease of the beta to alpha ratio. These findings highlight the different spectral properties of the EEG at various levels of responsiveness and underline the influence of the propofol injection rate on the frontal EEG during induction of general anesthesia.

Polysomnographic Findings in Nights Preceding a Migraine Attack

Cephalalgia ◽  
2001 ◽  
Vol 21 (1) ◽  
pp. 31-37 ◽  
Author(s):  
R Göder ◽  
G Fritzer ◽  
A Kapsokalyvas ◽  
P Kropp ◽  
U Niederberger ◽  
...  
Keyword(s):  
Slow Wave Sleep ◽  
Power Spectra ◽  
Cortical Activation ◽  
Alpha Power ◽  
Sleep Regulation ◽  
Beta Power ◽  
Rem Density ◽  
Sleep Parameters ◽  
Sleep Alterations ◽  
Electroencephalogram Eeg

Sleep recordings were performed in eight patients to analyse sleep alterations preceding migraine attacks. Polysomnographic recordings from nights before an attack were compared with nights without following migraine. We analysed standard sleep parameters and electroencephalogram (EEG) power spectra. The main findings preceding migraine attacks were a significant decrease in the number of arousals, a decrease in rapid eye movement (REM) density, a significant decrease of beta power in the slow wave sleep, and a decrease of alpha power during the first REM period. The results suggest a decrease in cortical activation during sleep preceding migraine attacks. According to the models of sleep regulation, alterations in the function of aminergic or cholinergic brainstem nuclei have to be discussed.

scholarly journals The Effect of Forest Video Using Virtual Reality on the Stress Reduction of University Students Focused on C University in Korea

2021 ◽  
Vol 18 (23) ◽  
pp. 12805
Author(s):  
Seong-Hee Jo ◽  
Jin-Seok Park ◽  
Poung-Sik Yeon
Keyword(s):  
College Students ◽  
Virtual Reality ◽  
Stress Reduction ◽  
Physiological Stress ◽  
Group Analysis ◽  
Control Group ◽  
Alpha Power ◽  
Beta Power ◽  
Electroencephalogram Eeg ◽  
Positive Effect

The purpose of this study is to study the effect of forest videos using virtual reality (VR) on the stress of college students. The study subjects were 60 college students who watched two-dimensional (2D) and VR videos, and we compared their control heart rate variability (HRV) and electroencephalogram (EEG). As a result, it was found that the VR group had a positive effect on high frequency (HF), standard deviation of all NN intervals (SDNN), and root-mean-square of successive differences (RMSSD) compared with the control group, and the VR group had a positive effect on HF compared with the 2D group. Second, EEG, a physiological indicator, showed statistical differences in Relative Alpha Power (RA), Relative Beta Power (RB), and Ratio of SMR–Mid Beta to Theta (RSMT) in VR groups in intra-group analysis. Among them, it was investigated that watching forest videos on VR became a state of concentration and immersion due to the increase in RSMT. As a result of the above, it was investigated that forest videos using VR had a positive effect on the physiological stress on college students. Therefore, it is expected that a positive effect will occur if VR is used as an alternative to stress management for college students.

scholarly journals Neurophysiological and behavioural effects of conventional and high definition tDCS

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fabio Masina ◽  
Giorgio Arcara ◽  
Eleonora Galletti ◽  
Isabella Cinque ◽  
Luciano Gamberini ◽  
...  
Keyword(s):  
Response Times ◽  
Power Reduction ◽  
Alpha Power ◽  
High Definition ◽  
Mixed Effect ◽  
State Dependency ◽  
Mixed Effect Models ◽  
Beta Power ◽  
Neurophysiological Data ◽  
Spectrum Density

AbstractHigh-definition transcranial direct current stimulation (HD-tDCS) seems to overcome a drawback of traditional bipolar tDCS: the wide-spread diffusion of the electric field. Nevertheless, most of the differences that characterise the two techniques are based on mathematical simulations and not on real, behavioural and neurophysiological, data. The study aims to compare a widespread tDCS montage (i.e., a Conventional bipolar montage with extracephalic return electrode) and HD-tDCS, investigating differences both at a behavioural level, in terms of dexterity performance, and a neurophysiological level, as modifications of alpha and beta power as measured with EEG. Thirty participants took part in three sessions, one for each montage: Conventional tDCS, HD-tDCS, and sham. In all the conditions, the anode was placed over C4, while the cathode/s placed according to the montage. At baseline, during, and after each stimulation condition, dexterity was assessed with a Finger Tapping Task. In addition, resting-state EEG was recorded at baseline and after the stimulation. Power spectrum density was calculated, selecting two frequency bands: alpha (8–12 Hz) and beta (18–22 Hz). Linear mixed effect models (LMMs) were used to analyse the modulation induced by tDCS. To evaluate differences among the montages and consider state-dependency phenomenon, the post-stimulation measurements were covariate-adjusted for baseline levels. We observed that HD-tDCS induced an alpha power reduction in participants with lower alpha at baseline. Conversely, Conventional tDCS induced a beta power reduction in participants with higher beta at baseline. Furthermore, data showed a trend towards a behavioural effect of HD-tDCS in participants with lower beta at baseline showing faster response times. Conventional and HD-tDCS distinctively modulated cortical activity. The study highlights the importance of considering state-dependency to determine the effects of tDCS on individuals.

Information-based analysis of the coupling between brain and heart reactions to olfactory stimulation

2021 ◽  
pp. 1-11
Author(s):  
Najmeh Pakniyat ◽  
Mohammad Hossein Babini ◽  
Vladimir V. Kulish ◽  
Hamidreza Namazi
Keyword(s):  
Time Series ◽  
Biomedical Science ◽  
Strongly Correlated ◽  
Eeg Signals ◽  
Ecg Signals ◽  
Olfactory Stimuli ◽  
Electrocardiogram Ecg ◽  
First Time ◽  
Electroencephalogram Eeg ◽  
The Brain

BACKGROUND: Analysis of the heart activity is one of the important areas of research in biomedical science and engineering. For this purpose, scientists analyze the activity of the heart in various conditions. Since the brain controls the heart’s activity, a relationship should exist among their activities. OBJECTIVE: In this research, for the first time the coupling between heart and brain activities was analyzed by information-based analysis. METHODS: Considering Shannon entropy as the indicator of the information of a system, we recorded electroencephalogram (EEG) and electrocardiogram (ECG) signals of 13 participants (7 M, 6 F, 18–22 years old) in different external stimulations (using pineapple, banana, vanilla, and lemon flavors as olfactory stimuli) and evaluated how the information of EEG signals and R-R time series (as heart rate variability (HRV)) are linked. RESULTS: The results indicate that the changes in the information of the R-R time series and EEG signals are strongly correlated (ρ=-0.9566). CONCLUSION: We conclude that heart and brain activities are related.

scholarly journals Fourier analysis: the simplification of a complex waveform into simple component sine waves of different amplitudes and frequencies

2020 ◽  
pp. S102-S103
Author(s):  
AI Mamoojee
Keyword(s):  
Fourier Analysis ◽  
Fundamental Frequency ◽  
Simple Wave ◽  
Sine Wave ◽  
Frequency Wave ◽  
Invasive Blood Pressure ◽  
Time Frequency ◽  
Simple Component ◽  
Electrocardiogram Ecg ◽  
Electroencephalogram Eeg

Fourier analysis is the simplification of a complex waveform into simple component sine waves of different amplitudes and frequencies. A discussion on Fourier analysis necessitates reiteration of the physics of waves. A wave is a series of repeating disturbances that propagate in space and time. Frequency: the number of oscillations, or cycles per second. It is measured in Hertz and denoted as 1/time or s-1. Fundamental frequency: the lowest frequency wave in a series. It is also known as the first harmonic. Every other wave in the series is an exact multiple of the fundamental frequency. Harmonic: whole number multiples of the fundamental frequency. Amplitude: the maximum disturbance or displacement from zero caused by the wave. This is the height of the wave. Period: time to complete one oscillation. Wavelength: physical length of one complete cycle. This can be between two crests or two troughs. The higher the frequency, the shorter the wavelength. Velocity: frequency x wavelength. Phase: displacement of one wave compared to another, described as 0°–360°. A sine wave is a simple wave. It can be depicted as the path of a point travelling round a circle at a constant speed, defined by the equation ‘y = sinx’. Combining sine waves of different frequency, amplitude and phase can yield any waveform, and, conversely, any wave can be simplified into its component sine waves. Fourier analysis is a mathematical method of analysing a complex periodic waveform to find its constituent frequencies (as sine waves). Complex waveforms can be analysed, with very simple results. Usually, few sine and cosine waves combine to create reasonably accurate representations of most waves. Fourier analysis finds its anaesthetic applications in invasive blood pressure, electrocardiogram (ECG) and electroencephalogram (EEG) signals, which are all periodic waveforms. It enables monitors to display accurate representations of these biological waveforms. Fourier analysis was developed by Joseph Fourier, a mathematician who analysed and altered periodic waveforms. It is done by computer programmes that plot the results of the analysis as a spectrum of frequencies with amplitude on the y-axis and frequency on the x-axis.

scholarly journals Age-dependent electroencephalogram (EEG) patterns during sevoflurane general anesthesia in infants

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Laura Cornelissen ◽  
Seong-Eun Kim ◽  
Patrick L Purdon ◽  
Emery N Brown ◽  
Charles B Berde
Keyword(s):  
General Anesthesia ◽  
Temporal Dynamics ◽  
Brain Activity ◽  
Body Movement ◽  
Video Recording ◽  
Brain State ◽  
Alpha Power ◽  
State Monitoring ◽  
Spatio Temporal ◽  
Electroencephalogram Eeg

Electroencephalogram (EEG) approaches may provide important information about developmental changes in brain-state dynamics during general anesthesia. We used multi-electrode EEG, analyzed with multitaper spectral methods and video recording of body movement to characterize the spatio-temporal dynamics of brain activity in 36 infants 0–6 months old when awake, and during maintenance of and emergence from sevoflurane general anesthesia. During maintenance: (1) slow-delta oscillations were present in all ages; (2) theta and alpha oscillations emerged around 4 months; (3) unlike adults, all infants lacked frontal alpha predominance and coherence. Alpha power was greatest during maintenance, compared to awake and emergence in infants at 4–6 months. During emergence, theta and alpha power decreased with decreasing sevoflurane concentration in infants at 4–6 months. These EEG dynamic differences are likely due to developmental factors including regional differences in synaptogenesis, glucose metabolism, and myelination across the cortex. We demonstrate the need to apply age-adjusted analytic approaches to develop neurophysiologic-based strategies for pediatric anesthetic state monitoring.

Understanding the nonlinear behavior of EEG with advanced machine learning in artifact elimination

2021 ◽  
Author(s):  
Md Samiul Haque Sunny ◽  
Shifat Hossain ◽  
Nashrah Afroze ◽  
Md. Kamrul Hasan ◽  
Eklas Hossain ◽  
...  
Keyword(s):  
Nonlinear Behavior ◽  
Cognitive Status ◽  
Brain Diseases ◽  
Eeg Signal ◽  
Hilbert Huang Transform ◽  
Neuro Fuzzy ◽  
Research Goal ◽  
Adaptive Noise ◽  
Electrocardiogram Ecg ◽  
Electroencephalogram Eeg

Abstract Steady-state Visually Evoked Potential (SSVEP) based Electroencephalogram (EEG) signal is utilized in brain-computer interface paradigms, diagnosis of brain diseases, and measurement of the cognitive status of the human brain. However, various artifacts such as the Electrocardiogram (ECG), Electrooculogram (EOG), and Electromyogram (EMG) are present in the raw EEG signal, which adversely affect the EEG-based appliances. In this research, Adaptive Neuro-fuzzy Interface Systems (ANFIS) and Hilbert-Huang Transform (HHT) are primarily employed to remove the artifacts from EEG signals. This work proposes Adaptive Noise Cancellation (ANC) and ANFIS based methods for canceling EEG artifacts. A mathematical model of EEG with the aforementioned artifacts is determined to accomplish the research goal, and then those artifacts are eliminated based on their mathematical characteristics. ANC, ANFIS, and HHT algorithms are simulated on the MATLAB platform, and their performances are also justified by various error estimation criteria using hardware implementation.

Epileptic Seizure-Induced Hypoxemia in Infants with Apparent Life-Threatening Events

PEDIATRICS ◽  
1994 ◽  
Vol 94 (2) ◽  
pp. 148-156
Author(s):  
John Hewertson ◽  
Martin P. Samuels ◽  
David P. Southall ◽  
Christian F. Poets ◽  
Stewart G. Boyd ◽  
...  
Keyword(s):  
Median Duration ◽  
Epileptic Seizure ◽  
Sinus Tachycardia ◽  
Partial Seizures ◽  
Severe Hypoxemia ◽  
Life Threatening ◽  
Electrocardiogram Ecg ◽  
Electroencephalogram Eeg ◽  
Normal Standard ◽  
Median Interval

Objective. To describe the physiologic changes that occur during epileptic seizure (ES)-induced apparent life-threatening events (ALTE) and to provide an explanation for the mechanism whereby the hypoxemia characterizing these events occurred. Patients and design. Six infants were retrospectively selected from a group of 17 because they had ALTE documented on physiologic recordings where the first change in signals was in the electroencephalogram (EEG). The 17 infants had clinical features suggestive of partial seizures (but normal standard EEGs) and were from a sample of 172 infants with recurrent ALTE. All 17 infants underwent continuous recordings of breathing, electrocardiogram (ECG), oxygenation, and EEG, but only in 6 was an ES-induced ALTE recorded and the physiologic changes described. Results. Twenty-three ALTE were documented in six infants. Events commenced with an abnormality in the EEG, followed by a decrease in SaO2 after a median interval of 27 seconds (range 2 to 147). Despite resuscitation, the median duration of severe hypoxemia (SaO2 ≤60%) was 40 seconds (range 8 to 74). In 18 events (five infants) there was a median of four apneic pauses (range 1 to 9) preceding the decrease in SaO2 by a median duration of 24 seconds (range 3 to 48). The longest apneic pause per event lasted a median of 19 seconds (range 8 to 47). Breathing movements continued in five events (four infants), and expiratory airflow in one. Sinus tachycardia was found in 19 of the 23 events (six infants), but there were no cardiac arrhythmias. Conclusions. ES in infants can manifest as ALTE and be accompanied by potentially life-threatening episodes of severe hypoxemia and apnea, despite a normal EEG between events.

Cortical oscillations to measure anti-epileptic drug activity in clinical trials

2021 ◽  
Author(s):  
Andrea Biondi ◽  
Lorenzo Rocchi ◽  
Viviana Santoro ◽  
Gregory Beatch ◽  
Pierre Rossini ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Brain Activity ◽  
Systematic Evaluation ◽  
Alpha Power ◽  
Brain Oscillations ◽  
Cortical Oscillations ◽  
Anti Epileptic Drug ◽  
Beta Power ◽  
Gamma Power

Abstract The frequency analysis of electroencephalographic (EEG) activity, either spontaneous or evoked by transcranial magnetic stimulation (TMS-EEG), is a powerful tool to investigate changes in brain activity and excitability following the administration of antiepileptic drugs (AEDs). However, a systematic evaluation of the effect of AEDs on spontaneous and TMS-induced brain oscillations has not yet been provided. We studied the effects of lamotrigine, levetiracetam, and of a novel potassium channel opener (XEN1101) on TMS-induced and spontaneous brain oscillations in a group of healthy volunteers. Levetiracetam suppressed TMS-induced theta, alpha and beta power, whereas lamotrigine increased TMS-induced alpha power. XEN1101 decreased TMS-induced delta, theta and beta power. Resting-state EEG showed a decrease of theta band power after lamotrigine intake. Levetiracetam increased theta, beta and gamma power, while XEN1101 produced an increase of delta, theta, beta and gamma power. Different AEDs induce specific patterns of power changes in spontaneous and TMS-induced brain oscillations. Spontaneous and TMS-induced cortical oscillations represent a powerful tool to characterize the effect of AEDs on in vivo brain activity. Spectral fingerprints of specific AEDs should be further investigated to provide robust and objective biomarkers of biological effect in human clinical trials.

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