Assessment of changes in the electrical activity of the brain during general anesthesia using portable electroencephalography

Introduction: The analysis of the electrical activity of the brain using scalp electrodes with electroencephalography (EEG) could reveal the depth of anesthesia of a patient during surgery. However, conventional EEG equipment, due to its price and size, are not a practical option for the operating room and the commercial units used in surgery do not provide access to the electrical activity. The availability of low-cost portable technologies could provide for further research on the brain activity under general anesthesia and facilitate our quest for new markers of depth of anesthesia. Objective: To assess the capabilities of a portable EEG technology to capture brain rhythms associated with the state of consciousness and the general anesthesia status of surgical patients anesthetized with propofol. Methods: Observational, cross-sectional trial that reviewed 10 EEG recordings captured using OpenBCI portable low-cost technology, in female patients undergoing general anesthesia with propofol. The signal from the frontal electrodes was analyzed with spectral analysis and the results were compared against the reports in the literature. Results: The signal captured with frontal electrodes, particularly α rhythm, enabled the distinction between resting with eyes closed and with eyes opened in a conscious state, and sustained anesthesia during surgery. Conclusions: It is possible to differentiate a resting state from sustained anesthesia, replicating previous findings with conventional technologies. These results pave the way to the use of portable technologies such as the OpenBCI tool, to explore the brain dynamics during anesthesia.

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Conditional Entropy: A Potential Digital Marker for Stress

Entropy ◽

10.3390/e23030286 ◽

2021 ◽

Vol 23 (3) ◽

pp. 286

Author(s):

Soheil Keshmiri

Keyword(s):

Resting State ◽

Nearest Neighbor ◽

Brain Activity ◽

Solution Concept ◽

Conditional Entropy ◽

K Nearest Neighbor ◽

Brain Response ◽

Substantial Progress ◽

Eeg Recordings ◽

The Brain

Recent decades have witnessed a substantial progress in the utilization of brain activity for the identification of stress digital markers. In particular, the success of entropic measures for this purpose is very appealing, considering (1) their suitability for capturing both linear and non-linear characteristics of brain activity recordings and (2) their direct association with the brain signal variability. These findings rely on external stimuli to induce the brain stress response. On the other hand, research suggests that the use of different types of experimentally induced psychological and physical stressors could potentially yield differential impacts on the brain response to stress and therefore should be dissociated from more general patterns. The present study takes a step toward addressing this issue by introducing conditional entropy (CE) as a potential electroencephalography (EEG)-based resting-state digital marker of stress. For this purpose, we use the resting-state multi-channel EEG recordings of 20 individuals whose responses to stress-related questionnaires show significantly higher and lower level of stress. Through the application of representational similarity analysis (RSA) and K-nearest-neighbor (KNN) classification, we verify the potential that the use of CE can offer to the solution concept of finding an effective digital marker for stress.

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Consciousness Emanates from the Neuronal Network of Coordination, A Fact Endorsed by Preserved Consciousness in Focal Ischemic Infarctions

NeuroQuantology ◽

10.14704/nq.2021.19.3.nq21023 ◽

2021 ◽

Vol 19 (3) ◽

pp. 17-25

Author(s):

Dr. Sohail Adnan ◽

Dr. Mubasher Shah ◽

Dr. Syed Fahim Shah ◽

Dr. Fahad Naim ◽

Dr. Akhtar Ali ◽

...

Keyword(s):

Cerebral Cortex ◽

Neuronal Network ◽

Brain Activity ◽

Cross Sectional Study ◽

Difficult Problem ◽

Altered Consciousness ◽

Cross Sectional ◽

Consciousness Disorder ◽

The Right ◽

The Brain

Background: Consciousness has remained a difficult problem for the scientists to explore its relationship to the brain activity. This is the first paper that presents the significance of focal areas of the cerebral cortex for consciousness. Objectives: To determine if consciousness is produced by the activity of the whole brain or one of its focal areas. Methods: We have performed a prospective cross-sectional study in eighty patients of acute ischemic stroke. The neurovascular territory of the middle cerebral artery (MCA) was sectioned into four similar areas. The association of any of these focal areas to consciousness was observed after their dysfunction with ischemic strokes. Results: Of the eighty patients, 57.5 % were males and 42.5 % were females. Mean age was 63 years ± 7 SD. The righthanded patients were 90 % (72) of the whole sample. Focal areas of the right MCA were generally less prone to consciousness disorder. Average statistics of the focal infarctions of the right MCA showed no tendency for consciousness disorder on the Glasgow coma scale (GCS) [Mean GCS of all focal areas; 14.5, SD; 0.71, 95 % CI; 14.27 to 14.72, P= 0.0000004]. Altered consciousness with focal infarctions of the territory of left MCA was also less likely [Mean GCS of all focal areas; 14.2, SD; 1.01, 95 % CI; 13.88 to 14.51, P= 0.0004]. Conclusion: Consciousness is not determined by the activity of a focal area of the cerebral cortex. Perhaps, we get our consciousness from the activity of “Neuronal Network of Coordination”.

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Testing MD-Link, a Low-Cost Mobile Electrocardiography Monitoring Device, in Patients With Irregular Heartbeat: Protocol for a Cross-Sectional Study (Preprint)

10.2196/preprints.8762 ◽

2017 ◽

Author(s):

Precious J Kilimo ◽

Tai Le ◽

Ngoc T Phan ◽

Huy-Dung Han ◽

Hoc T Hoang ◽

...

Keyword(s):

Electrical Activity ◽

Mobile Device ◽

Low Cost ◽

Cross Sectional Study ◽

Lead Wire ◽

Daily Routine ◽

Monitoring Device ◽

Ecg Monitoring ◽

Sectional Study ◽

Cross Sectional

BACKGROUND Having mobile devices that provide patients with the ability to record and monitor the electrical activity of their heart enhances patient self-care and the early detection of irregular heartbeat (cardiac arrhythmia), yet few such devices exist in Vietnam. Challenges exist for introducing mobile electrocardiography (ECG) monitoring devices in Vietnam, including patient accessibility and affordability. A low-cost mobile ECG monitoring device designed and developed in Vietnam, which allows patients to easily measure their heart’s electrical activity and navigate recordings, may be a solution. OBJECTIVE The aim of this project is to assess the usability of the MD-Link system, a newly developed mobile handheld 1-lead ECG device, in detecting patients with irregular heartbeat. We will compare its outputs to the standard printed outputs of a 12-lead electrocardiogram generated by the Nihon Kohden Cardiofax S Electrocardiograph Model ECG-1250K. METHODS We will conduct a cross-sectional study in two stages, including the measurement of ECG signals of patients using the MD-Link and the Nihon Kohden Cardiofax S and analysis of the selected standard outputs collected from the ECG recordings of the MD-Link and the Nihon Kohden Cardiofax S. The MD-Link consists of (1) a mobile device (eg, a smartphone); (2) a lead wire with 2 disposable electrodes; and (3) an easy-to-use mobile app interface enabling the upload and accurate display of ECG recordings to patients and their clinicians. Our research team, consisting of members from Dartmouth College; the Institute of Health, Population and Development; Hanoi University of Science and Technology; and physicians and nurses from Thanh Chan Clinic, will assist in carrying out this project. RESULTS We will proceed with a publication plan that includes a project report and, ultimately, articles for peer-reviewed journals. We also hope to disseminate our work at relevant conferences to provide more coverage and exposure to the MD-Link mobile device. Recruitment and data collection were completed in January 2018. Data analysis started in February 2018 and is ongoing. Results are expected mid-2019. CONCLUSIONS At the end of this project, we will have developed and tested the MD-Link, a low-cost mobile ECG monitoring device, with some supportive comparisons to standard ECG devices commonly used in heart clinics or hospitals in Vietnam. Our long-term goal is for the MD-Link to be easily accessible, affordable, and to fit into a patient’s daily routine, thus improving the care and treatment of patients with cardiovascular diseases (CVDs). INTERNATIONAL REGISTERED REPOR RR1-10.2196/8762

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The ecological cocktail party: Measuring brain activity during an auditory oddball task with background noise

10.1101/371435 ◽

2018 ◽

Author(s):

Joanna E. M. Scanlon ◽

Danielle L. Cormier ◽

Kimberley A. Townsend ◽

Jonathan W.P. Kuziek ◽

Kyle E. Mathewson

Keyword(s):

White Noise ◽

New Technologies ◽

Brain Activity ◽

Real Life ◽

Auditory Oddball ◽

Oddball Task ◽

Eeg Recordings ◽

Auditory Oddball Task ◽

The Brain ◽

Sound Condition

AbstractMost experiments using EEG recordings take place in highly isolated and restricted environments, limiting their applicability to real-life scenarios. New technologies for mobile EEG are changing this by allowing EEG recording to take place outside of the laboratory. However, before results from experiments performed outside the laboratory can be fully understood, the effects of ecological stimuli on brain activity during cognitive tasks must be examined. In this experiment, participants performed an auditory oddball task while also listening to concurrent background noises of silence, white noise and outdoor ecological sounds, as well as a condition in which the tones themselves were at a low volume. We found a significantly increased N1 and decreased P2 when participants performed the task with outdoor sounds and white noise in the background, with the largest differences in the outdoor sound condition. This modulation in the N1 and P2 replicates what we have previously found outside while people ride bicycles (Scanlon et al., 2017b). No behavioural differences were found in response to the target tones. We interpret these modulations in early ERPs as indicative of sensory filtering of background sounds, and that ecologically valid sounds require more filtering than synthetic sounds. Our results reveal that much of what we understand about the brain will need to be updated as we step outside the lab.

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Fronto-Temporal Analysis of EEG Signals of Patients with Depression: Characterisation, Nonlinear Dynamics and Surrogate Analysis

10.5772/intechopen.94254 ◽

2020 ◽

Author(s):

Subha D. Puthankattil

Keyword(s):

Time Series ◽

Unipolar Depression ◽

Temporal Analysis ◽

Mental States ◽

Eeg Signals ◽

Biosignal Analysis ◽

Eyes Closed ◽

Eyes Open ◽

Eeg Recordings ◽

The Brain

The recent advances in signal processing techniques have enabled the analysis of biosignals from brain so as to enhance the predictive capability of mental states. Biosignal analysis has been successfully used to characterise EEG signals of unipolar depression patients. Methods of characterisation of EEG signals and the use of nonlinear parameters are the major highlights of this chapter. Bipolar frontopolar-temporal EEG recordings obtained under eyes open and eyes closed conditions are used for the analysis. A discussion on the reliability of the use of energy distribution and Relative Wavelet Energy calculations for distinguishing unipolar depression patients from healthy controls is presented. The potential of the application of Wavelet Entropy to differentiate states of the brain under normal and pathologic condition is introduced. Details are given on the suitability of ascertaining certain nonlinear indices on the feature extraction, assuming the time series to be highly nonlinear. The assumption of nonlinearity of the measured EEG time series is further verified using surrogate analysis. The studies discussed in this chapter indicate lower values of nonlinear measures for patients. The higher values of signal energy associated with the delta bands of depression patients in the lower frequency range are regarded as a major characteristic indicative of a state of depression. The chapter concludes by presenting the important results in this direction that may lead to better insight on the brain activity and cognitive processes. These measures are hence posited to be potential biomarkers for the detection of depression.

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Use of Multiple EEG Features and Artificial Neural Network to Monitor the Depth of Anesthesia

Sensors ◽

10.3390/s19112499 ◽

2019 ◽

Vol 19 (11) ◽

pp. 2499 ◽

Cited By ~ 5

Author(s):

Yue Gu ◽

Zhenhu Liang ◽

Satoshi Hagihira

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Brain Activity ◽

Permutation Entropy ◽

Depth Of Anesthesia ◽

Spectral Edge Frequency ◽

Artificial Neural ◽

Artificial Neural Network Ann ◽

Electroencephalogram Eeg ◽

The Brain

The electroencephalogram (EEG) can reflect brain activity and contains abundant information of different anesthetic states of the brain. It has been widely used for monitoring depth of anesthesia (DoA). In this study, we propose a method that combines multiple EEG-based features with artificial neural network (ANN) to assess the DoA. Multiple EEG-based features can express the states of the brain more comprehensively during anesthesia. First, four parameters including permutation entropy, 95% spectral edge frequency, BetaRatio and SynchFastSlow were extracted from the EEG signal. Then, the four parameters were set as the inputs to an ANN which used bispectral index (BIS) as the reference output. 16 patient datasets during propofol anesthesia were used to evaluate this method. The results indicated that the accuracies of detecting each state were 86.4% (awake), 73.6% (light anesthesia), 84.4% (general anesthesia), and 14% (deep anesthesia). The correlation coefficient between BIS and the index of this method was 0.892 ( p < 0.001 ). The results showed that the proposed method could well distinguish between awake and other anesthesia states. This method is promising and feasible for a monitoring system to assess the DoA.

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EEG Derived Brain Activity Reflects Treatment Response from Vagus Nerve Stimulation in Patients with Epilepsy

International Journal of Neural Systems ◽

10.1142/s0129065716500489 ◽

2017 ◽

Vol 27 (04) ◽

pp. 1650048 ◽

Cited By ~ 13

Author(s):

Simon Wostyn ◽

Willeke Staljanssens ◽

Leen De Taeye ◽

Gregor Strobbe ◽

Stefanie Gadeyne ◽

...

Keyword(s):

Vagus Nerve ◽

Seizure Frequency ◽

Mechanism Of Action ◽

Nerve Stimulation ◽

Vagus Nerve Stimulation ◽

Brain Activity ◽

P300 Amplitude ◽

Eeg Recordings ◽

Patients With Epilepsy ◽

The Brain

The mechanism of action of vagus nerve stimulation (VNS) is yet to be elucidated. To that end, the effects of VNS on the brain of epileptic patients were studied. Both when VNS was switched “On” and “Off”, the brain activity of responders (R, seizure frequency reduction of over 50%) was compared to the brain activity of nonresponders (NR, seizure frequency reduction of less than 50%). Using EEG recordings, a significant increase in P300 amplitude for R and a significant decrease in P300 amplitude for NR were found. We found biomarkers for checking the efficacy of VNS with accuracy up to 94%. The results show that P300 features recorded in nonmidline electrodes are better P300 biomarkers for VNS efficacy than P300 features recorded in midline electrodes. Using source localization and connectivity analyses, the activity of the limbic system, insula and orbitofrontal cortex was found to be dependent on VNS switched “On” versus “Off” or patient group (R versus NR). The results suggest an important role for these areas in the mechanism of action of VNS, although a larger patient study should be done to confirm the findings.

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Dynamics of Brain Electric Field during Recall of Salpuri Dance Performance

Perceptual and Motor Skills ◽

10.2466/pms.2002.95.3.955 ◽

2002 ◽

Vol 95 (3) ◽

pp. 955-962 ◽

Cited By ~ 10

Author(s):

Jong Ran Park ◽

Takami Yagyu ◽

Naomi Saito ◽

Toshihiko Kinoshita ◽

Takane Hirai

Keyword(s):

Electrical Activity ◽

Resting State ◽

Brain Activity ◽

Wave Activity ◽

Global Field Power ◽

Brain Wave ◽

Frontal Midline Theta ◽

The Subject ◽

Brain Wave Activity ◽

The Brain

The brain wave activity of a professional Salpuri dancer was observed while the subject recalled her performance of the Salpuri dance when sitting in a chair with closed eyes. As she recalled the feeling of the ecstatic trance state induced by the dance, an increase in alpha brain activity was observed together with marked frontal midline theta activity. Compared to a resting state, the dynamics of the electrical activity in the brain showed an increase in the global field power integral and a decrease in generalized frequency and spatial complexity.

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Reconstruction of the Human Brain Functional Structure Based on the Electroencephalography Data

Математическая биология и биоинформатика ◽

10.17537/2020.15.106 ◽

2020 ◽

Vol 15 (1) ◽

pp. 106-117 ◽

Cited By ~ 2

Author(s):

M.N. Ustinin ◽

S.D. Rykunov ◽

A.I. Boyko ◽

O.A. Maslova

Keyword(s):

Inverse Problem ◽

Time Series ◽

Alpha Rhythm ◽

Brain Activity ◽

Spectral Band ◽

Field Measurements ◽

Functional Structure ◽

Current Dipole ◽

Eyes Closed ◽

The Brain

New method for the data analysis was proposed, making it possible to transform multichannel time series into the spatial structure of the system under study. The method was successfully used to investigate biological and physical objects based on the magnetic field measurements. In this paper we further develop this method to analyze the data of the experiments where the electric field is measured. The brain activity in the state of subject “eyes closed” was registered by the 19-channel electric encephalograph, using the 10-20 scheme. The electroencephalograms were obtained in resting state and with arbitrary hands motions. Detailed multichannel spectra were obtained by the Fourier transform of the whole time series. All spectral data revealed the broad alpha rhythm peak in the frequency band 9-12 Hz. For all spectral components in this band the inverse problem was solved, and the 3D map of the brain activity was calculated. The inverse problem was solved in elementary current dipole model for one-layer spherical conductor without any restrictions for the source position. The combined analysis of the magnetic resonance image and the brain functional structure leads to the conclusion that this structure generally corresponds to the modern knowledge about the alpha rhythm. The 3D map of the vector field of the dominating directions of the alpha rhythm sources was also generated. The proposed method can be used to study the spatial distribution of the brain activity in any spectral band of the electroencephalography data.

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Oscillations, criticality and responsiveness in complex brain networks

10.1101/529982 ◽

2019 ◽

Author(s):

MinKyung Kim ◽

UnCheol Lee

Keyword(s):

Large Scale ◽

Brain Activity ◽

Conscious State ◽

Brain Network ◽

State Dependent ◽

Model Study ◽

Brain States ◽

Specific Stimulation ◽

The Brain ◽

Oscillation Properties

AbstractBrain networks during unconscious states resulting from sleep, anesthesia, or traumatic injuries are associated with a limited capacity for complex responses to stimulation. Even during the conscious resting state, responsiveness to stimulus is highly dependent on spontaneous brain activities. Many empirical findings have been suggested that the brain responsiveness is determined mainly by the ongoing brain activity when a stimulus is given. However, there has been no systematic study exploring how such various brain activities with high or low synchronization, amplitude, and phase response to stimuli. In this model study, we simulated large-scale brain network dynamics in three brain states (below, near, and above the critical state) and investigated a relationship between ongoing oscillation properties and a stimulus decomposing the brain activity into fundamental oscillation properties (instantaneous global synchronization, amplitude, and phase). We identified specific stimulation conditions that produce varying levels of brain responsiveness. When a single pulsatile stimulus was applied to globally desynchronized low amplitude of oscillation, the network generated a large response. By contrast, when a stimulus was applied to specific phases of oscillation that were globally synchronized with high amplitude activity, the response was inhibited. This study proposes the oscillatory conditions to induce specific stimulation outcomes in the brain that can be systematically derived from networked oscillator properties, and reveals the presence of state-dependent temporal windows for optimal brain stimulation. The identified relationship will help advance understanding of the small/large responsiveness of the brain in different states of consciousness and suggest state-dependent methods to modulate responsiveness.Author SummaryA responsiveness of the brain network to external stimulus is different across brain states such as wakefulness, sleep, anesthesia, and traumatic injuries. It has been shown that responsiveness of the brain during conscious state also varies due to the diverse transient states of the brain characterized by different global and local oscillation properties. In this computational model study using large-scale brain network, we hypothesized that the brain responsiveness is determined by the interactions of networked oscillators when a stimulus is applied to the brain. We examined relationships between responsiveness of the brain network, global synchronization levels, and instantaneous oscillation properties such as amplitude and phase in different brain states. We found specific stimulation conditions of the brain that produce large or small levels of responsiveness. The identified relationship suggests the existence of temporal windows that periodically inhibit sensory information processing during conscious state and develops state-dependent methods to modulate brain responsiveness considering dynamically changed functional brain network.

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