Electroencephalogram

OBJECTIVE: To remove signal contamination in electroencephalogram (EEG) traces coming from ocular, motion, and muscular artifacts which degrade signal quality. To do this in real-time, with low computational overhead, on a mobile platform in a channel count independent manner to enable portable Brain-Computer Interface (BCI) applications. METHODS: We propose a Deep AutoEncoder (DAE) neural network for single-channel EEG artifact removal, and implement it on a smartphone via TensorFlow Lite...

Time discrimination, a critical aspect of auditory perception, is influenced by numerous factors. Previous research has suggested that musical experience can restructure the brain, thereby enhancing time discrimination. However, this phenomenon remains underexplored. In this study, we seek to elucidate the enhancing effect of musical experience on time discrimination, utilizing both behavioral and electroencephalogram methodologies. Additionally, we aim to explore, through brain connectivity analysis, the role of increased connectivity in brain regions associated with auditory perception as a potential contributory factor to time discrimination induced by musical experience...

Incorrect bispectral index (BIS) values have been reported due to interference with this monitoring system. We report a case of a 46-year-old woman who underwent liposuction and breast lipofilling, where we observed a misinterpretation by the BIS algorithm that has not yet been reported. Concurrently with abdominal and thigh liposuction, an increase in the BIS value was observed. The importance of examining electroencephalogram (EEG) and density spectral array (DSA) readings during liposuction procedures is highlighted in this case report, extending our observations beyond just the numerical BIS value, which is not always reliable...

BACKGROUND: The thalamus system plays critical roles in the regulation of reversible unconsciousness induced by general anesthetics, especially the arousal stage of general anesthesia (GA). But the function of thalamus in GA-induced loss of consciousness (LOC) is little known. The thalamic reticular nucleus (TRN) is the only GABAergic neurons-composed nucleus in the thalamus, which is composed of parvalbumin (PV) and somatostatin (SST)-expressing GABAergic neurons. The anterior sector of TRN (aTRN) is indicated to participate in the induction of anesthesia, but the roles remain unclear...

Growing electroencephalogram (EEG) studies have linked the abnormities of functional brain networks with disorders of consciousness (DOC). However, due to network data's high-dimensional and non-Euclidean properties, it is difficult to exploit the brain connectivity information that can effectively detect the consciousness levels of DOC patients via deep learning. To take maximum advantage of network information in assessing impaired consciousness, we utilized the functional connectivity with convolutional neural network (CNN) and employed three rearrangement schemes to improve the evaluation performance of brain networks...

Although our knowledge of autism spectrum disorder (ASD) has been deepened, the accurate diagnosis of ASD from normal individuals is still left behind. In this study, we proposed to apply the spatial pattern of the network topology (SPN) to identify children with ASD from normal ones. Based on two independent batches of electroencephalogram datasets collected separately, the accurate recognition of ASD from normal children was achieved by applying the proposed SPN features. Since decreased long-range connectivity was identified for children with ASD, the SPN features extracted from the distinctive topological architecture between two groups in the first dataset were used to validate the capacity of SPN in classifying ASD, and the SPN features achieved the highest accuracy of 92...

This study explored selective exposure and confirmation bias in the choices participants made about which political videos to watch, and whether their political positions changed after they watched videos that either agreed with or opposed their positions on two controversial issues in South Korea: North Korea policy and social welfare policy. The participants completed questionnaires before and after they watched the videos, were asked to select thumbnails of videos before they watched any, and had their brain wave activity measured through electroencephalogram (EEG) as they watched both types of videos...

The single macroscopic flow on the boundary of a closed curve equals the sum of the countless microscopic flows in the enclosed area. According to the dictates of the Green's theorem, the counterclockwise movements on the border of a two-dimensional shape must equal all the counterclockwise movements taking place inside the shape. This mathematical approach might be useful to analyse neuroscientific data sets for its potential capability to describe the whole cortical activity in terms of electric flows occurring in peripheral brain areas...

Thanks to the advent of affective computing, designing an automatic human emotion recognition system for clinical and non-clinical applications has attracted the attention of many researchers. Currently, multi-channel electroencephalogram (EEG)-based emotion recognition is a fundamental but challenging issue. This experiment envisioned developing a new scheme for automated EEG affect recognition. An innovative nonlinear feature engineering approach was presented based on Lemniscate of Bernoulli's Map (LBM), which belongs to the family of chaotic maps, in line with the EEG's nonlinear nature...

Visual joint attention, the ability to track gaze and recognize intent, plays a key role in the development of social and language skills in health humans, which is performed abnormally hard in autism spectrum disorder (ASD). The traditional convolutional neural network, EEGnet, is an effective model for decoding technology, but few studies have utilized this model to address attentional training in ASD patients. In this study, EEGNet was used to decode the P300 signal elicited by training and the saliency map method was used to visualize the cognitive properties of ASD patients during visual attention...

A data set of clinical studies of electroencephalogram recordings (EEG) following data acquisition protocols in control individuals (Eyes Closed Wakefulness - Eyes Open Wakefulness, Hyperventilation, and Optostimulation) are quantified with information theory metrics, namely permutation Shanon entropy and permutation Lempel Ziv complexity, to identify functional changes. This work implement Linear mixed-effects models (LMEMs) for confirmatory hypothesis testing. The results show that EEGs have high variability for both metrics and there is a positive correlation between them...

Humans are able to pay selective attention to music or speech in the presence of multiple sounds. It has been reported that in the speech domain, selective attention enhances the cross-correlation between the envelope of speech and electroencephalogram (EEG) while also affecting the spatial modulation of the alpha band. However, when multiple music pieces are performed at the same time, it is unclear how selective attention affects neural entrainment and spatial modulation. In this paper, we hypothesized that the entrainment to the attended music differs from that to the unattended music and that spatial modulation in the alpha band occurs in conjunction with attention...

The concept of the brain-computer interface (BCI) has become one of the popular research topics of recent times because it allows people to express their thoughts and control different applications and devices without actual movement. The communication between the brain and the computer or a machine is generally provided through Electroencephalogram (EEG) signals because they are cost-effective and easy to implement in normal life, not just in healthcare facilities. On the other hand, they are hard to process efficiently due to their nonlinearity and noisy nature...

The brain-computer interfaces (BCIs) facilitate the users to exploit information encoded in neural signals, specifically electroencephalogram (EEG), to control devices and for neural rehabilitation. Mental imagery (MI)-driven BCI predicts the user's pre-meditated mental objectives, which could be deployed as command signals. This paper presents a novel learning-based framework for classifying MI tasks using EEG-based BCI. In particular, our work focuses on the variation in inter-session data and the extraction of multi-spectral user-tailored features for robust performance...

Electroencephalogram (EEG) represents an effective, non-invasive technology to study mental workload. However, volume conduction, a common EEG artifact, influences functional connectivity analysis of EEG data. EEG coherence has been used traditionally to investigate functional connectivity between brain areas associated with mental workload, while weighted Phase Lag Index (wPLI) is a measure that improves on coherence by reducing susceptibility to volume conduction, a common EEG artifact. The goal of this study was to compare two methods of functional connectivity analysis, wPLI and coherence, in the context of mental workload evaluation...

BACKGROUND: Efficient, non-invasive monitoring may provide a more accurate and comprehensive understanding of seizure frequency and the development of some comorbidities in people with epilepsy. Novel keyboard technology measuring digital keypress statistics has demonstrated its practical value for neurodegenerative diseases including Parkinson's Disease and Dementia. Smartphones integrated into daily life may serve as a low-burden longitudinal monitoring system for patients with epilepsy...

OSA is known to increase the risk for SUDEP in persons with epilepsy, but the relationship between these two factors is not clear. Also, there is no study showing the acute responses to obstructive apnea in a chronic epilepsy model. Therefore, this study aimed to characterize cardiorespiratory responses to obstructive apnea and chemoreceptor stimulation in rats. In addition, we analyzed respiratory centers in the brain stem by immunohistochemistry. Epilepsy was induced with pilocarpine. About 30-60 days after the first spontaneous seizure, tracheal and thoracic balloons, and electrodes for recording the electroencephalogram, electromyogram, and electrocardiogram were implanted...

Sinusoidal galvanic vestibular stimulation (sGVS) induces robust modulation of muscle sympathetic nerve activity (MSNA) alongside perceptions of side-to-side movement, sometimes with an accompanying feeling of nausea. We recently showed that transcranial alternating current stimulation (tACS) of the dorsolateral prefrontal cortex (dlPFC) also modulates MSNA, but does not generate any perceptions. Here, we tested the hypothesis that when the two stimuli are given concurrently, the modulation of MSNA would be additive...

BACKGROUND: Dopaminergic neurons in the ventral tegmental area (VTA) are crucially involved in regulating arousal, making them a potential target for reversing general anesthesia. Electrical deep brain stimulation (DBS) of the VTA restores consciousness in animals anesthetized with drugs that primarily enhance GABAA receptors. However, it is unknown if VTA DBS restores consciousness in animals anesthetized with drugs that target other receptors. OBJECTIVE: To evaluate the efficacy of VTA DBS in restoring consciousness after exposure to four anesthetics with distinct receptor targets...

When two conflicting images are presented to each eye, a phenomenon called binocular rivalry occurs in which we initially perceive one image, and then our perception switches to the other over time. An enhancement of θ-band phase coherence in visual mismatch oscillatory response (vMOR) is reported to be involved in the facilitation of perceptual alternation when the deviant stimulus is presented unconsciously. In this study, we investigated the modulation effect of θ-band transcranial alternating current stimulation (tACS) on perceptual alternation in binocular rivalry, with a focus on its relationship with the θ-band vMOR...