Quantitative EEG Changes in Youth With ASD Following Brief Mindfulness Meditation Exercise by Busra T. Susam, Nathan T. Riek, Kelly Beck, Safaa Eldeeb, Caitlin M. Hudac, Philip A. Gable, Caitlin Conner, Murat Akcakaya, Susan White, Carla Mazefsky

“…Assessing the role of mindfulness in improving emotion regulation is challenging given the reliance on self-report tools. Electroencephalography (EEG) has successfully quantified neural responses to emotional arousal and meditation in other populations, making it ideal to objectively measure neural responses before and after mindfulness (MF) practice among individuals with ASD. …”
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A Machine Learning Approach Involving Functional Connectivity Features to Classify Rest-EEG Psychogenic Non-Epileptic Seizures from Healthy Controls by Giuseppe Varone, Wadii Boulila, Michele Lo Giudice, Bilel Benjdira, Nadia Mammone, Cosimo Ieracitano, Kia Dashtipour, Sabrina Neri, Sara Gasparini, Francesco Carlo Morabito, Amir Hussain, Umberto Aguglia

“…Until now, clinicians are not able to evaluate the Psychogenic Non-Epileptic Seizures (PNES) from the rest-electroencephalography (EEG) readout. No EEG marker can help differentiate PNES cases from healthy subjects. …”
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Investigating the Intervention Parameters of Endogenous Paired Associative Stimulation (ePAS) by Gemma Alder, Nada Signal, Alain C. Vandal, Sharon Olsen, Mads Jochumsen, Imran Khan Niazi, Denise Taylor

“…Endogenous paired associative stimulation (ePAS) involves the repeated pairing of a single pulse of peripheral electrical stimulation (PES) with endogenous movement-related cortical potentials (MRCPs), which are derived from electroencephalography. However, little is known about the optimal parameters for its delivery. …”
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Electroencephalographic frequency activity of patients with bipolar disorder by M. Mnif, L. Triki, N. Smaoui, D. Jardak, S. Omri, I. Gassara, R. Feki, M. Maalej, J. Ben Thabeut, L. Zouari, N. Charfi, K. Masmoudi, M. Maalej

“…However, it is underdiagnosed. Electroencephalography (EEG) has been proposed as a neurophysiological biomarker to delineate psychotic disorders. …”
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Effect of 24-form simplified Tai Chi on executive inhibitory control of college students: a randomized controlled trial of EEG by Min Wang, Bei Lyu

“…Executive inhibitory control was assessed using the Stroop Color and Word Test, and resting brain electrical activity in the frontal area was recorded through Electroencephalography.ResultACC was influenced by group, group-time interaction, and Stroop task-time interaction. …”
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Reliability of resting-state electrophysiology in fragile X syndrome by Rui Liu, Ernest V. Pedapati, Lauren M. Schmitt, Rebecca C. Shaffer, Elizabeth G. Smith, Kelli C. Dominick, Lisa A. DeStefano, Grace Westerkamp, Paul Horn, John A. Sweeney, Craig A. Erickson

“…Previous studies have shown electrophysiological changes in the brain using electroencephalography (EEG) in individuals with FXS and animal models. …”
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Coupling Effects of Cross-Corticomuscular Association during Object Manipulation Tasks on Different Haptic Sensations by Cristian D. Guerrero-Mendez, Cristian F. Blanco-Diaz, Hamilton Rivera-Flor, Alberto F. De Souza, Sebastian Jaramillo-Isaza, Andres F. Ruiz-Olaya, Teodiano F. Bastos-Filho

“…This study aims to examine the corticomuscular connectivity of three Electroencephalography (EEG) channels and five muscles during object manipulation tasks involving contact surfaces of Sandpaper, Suede, and Silk. …”
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Effectiveness of Mindfulness-Based Cognitive Therapy in reducing psychological distress and improving sleep in patients with Inflammatory Bowel Disease: study protocol for a multic... by Milou M ter Avest, Annelieke S M van Velthoven, Anne E M Speckens, Gerard Dijkstra, Martin Dresler, Carmen S Horjus, Tessa E H Römkens, Ellen M Witteman, Willemijn A van Dop, Quirine M Bredero, Loes H C Nissen, Marloes J Huijbers

“…In addition, the effect of MBCT on sleep quality (including actigraphy and electroencephalography recordings), fatigue, disease activity, perceived disease control, QoL and positive mental health will be examined. …”
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The association between the presence and burden of periodic discharges and outcome in septic patients: an observational prospective study by Lorenzo Ferlini, Christelle Maenhout, Ilaria Alice Crippa, Armin Alvaro Quispe-Cornejo, Jacques Creteur, Fabio Silvio Taccone, Nicolas Gaspard

“…Abstract Background Sepsis-associated encephalopathy (SAE) is frequent in septic patients. Electroencephalography (EEG) is very sensitive to detect early epileptic abnormalities, such as seizures and periodic discharges (PDs), and to quantify their duration (the so-called burden). …”
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Combined Use of EMG and EEG Techniques for Neuromotor Assessment in Rehabilitative Applications: A Systematic Review by Cristina Brambilla, Ileana Pirovano, Robert Mihai Mira, Giovanna Rizzo, Alessandro Scano, Alfonso Mastropietro

“…Electroencephalography (EEG) and electromyography (EMG) are widespread and well-known quantitative techniques used for gathering biological signals at cortical and muscular levels, respectively. …”
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Neurobiological Underpinnings of Hyperarousal in Depression: A Comprehensive Review by Musi Xie, Ying Huang, Wendan Cai, Bingqi Zhang, Haonan Huang, Qingwei Li, Pengmin Qin, Junrong Han

“…Evidence suggests that a hyperarousal state in depression is characterized by abnormalities in sleep behavior, physiological (e.g., heart rate, skin conductance, pupil diameter) and electroencephalography (EEG) features, and altered activity in subcortical (e.g., hypothalamus and locus coeruleus) and cortical regions. …”
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Neurophysiological hallmarks of Huntington’s disease progression: an EEG and fMRI connectivity study by Natalya V. Ponomareva, Natalya V. Ponomareva, Sergey A. Klyushnikov, Natalia Abramycheva, Rodion N. Konovalov, Marina Krotenkova, Ekaterina Kolesnikova, Daria Malina, Gusel Urazgildeeva, Elena Kanavets, Andrey Mitrofanov, Vitaly Fokin, Evgeny Rogaev, Evgeny Rogaev, Sergey N. Illarioshkin

“…Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) can provide corroborative data on neurophysiological alterations in Huntington’s disease (HD). …”
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A Nanoclay-Enhanced Hydrogel for Self-Adhesive Wearable Electrophysiology Electrodes with High Sensitivity and Stability by Fushuai Wang, Lang Yang, Ye Sun, Yiming Cai, Xin Xu, Zhenzhong Liu, Qijie Liu, Hongliang Zhao, Chunxin Ma, Jun Liu

“…Hydrogel-based wet electrodes are the most important biosensors for electromyography (EMG), electrocardiogram (ECG), and electroencephalography (EEG); but, are limited by poor strength and weak adhesion. …”
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Novel compound heterozygous mutations in the AFG3L2 gene in a Chinese child with microcephaly, early-onset seizures, and cerebral atrophy by Tingting Jin, Ying Kuang, Shulin Luo, Rongpin Wang, Kun Chen, Minmin Jiang, Lingyan Ren, Zhaolin Sun, Lifen Duan, Shengwen Huang

“…The child underwent physical and neurological examinations, laboratory tests, electroencephalography (EEG), and brain magnetic resonance imaging (MRI). …”
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Inter-subject correlations of EEG reflect subjective arousal and acoustic features of music by Fuyu Ueno, Fuyu Ueno, Sotaro Shimada

“…Therefore, here, we aimed to investigate whether the ISCs of electroencephalography (EEG) during music listening represent a preference for music reflecting engagement or interest of a large population in music.MethodsFirst, we selected 21 pieces of music from the Billboard Japan Hot 100 chart of 2017, which served as an indicator of preference reflecting the engagement and interest of a large population. …”
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A Multi-Scale Temporal Convolutional Network with Attention Mechanism for Force Level Classification during Motor Imagery of Unilateral Upper-Limb Movements by Junpeng Sheng, Jialin Xu, Han Li, Zhen Liu, Huilin Zhou, Yimeng You, Tao Song, Guokun Zuo

“…Based on the event-related de-synchronization (ERD) feature analysis of the electroencephalography (EEG) signals generated by the brain’s force change motor imagination, we proposed a multi-scale temporal convolutional network with attention mechanism (MSTCN-AM) algorithm to recognize ERD features of MI-EEG signals. …”
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Triple network activation causes tinnitus in patients with sudden sensorineural hearing loss: A model-based volume-entropy analysis by Seung Jae Lee, Jaemin Park, Sang-Yeon Lee, Sang-Yeon Lee, Sang-Yeon Lee, Ja-Won Koo, Ja-Won Koo, Ja-Won Koo, Sven Vanneste, Dirk De Ridder, Seonhee Lim, Jae-Jin Song, Jae-Jin Song, Jae-Jin Song

“…Tinnitus can develop in the setting of sudden sensorineural hearing loss (SSNHL), but the underlying mechanism is largely unknown. Using electroencephalography, we investigated differences in afferent node capacity between 15 SSNHL patients without tinnitus (NT) and 30 SSNHL patients with tinnitus (T). …”
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Single-trial P300 classification algorithm based on centralized multi-person data fusion CNN by Pu Du, Penghai Li, Longlong Cheng, Longlong Cheng, Xueqing Li, Jianxian Su

“…IntroductionCurrently, it is still a challenge to detect single-trial P300 from electroencephalography (EEG) signals. In this paper, to address the typical problems faced by existing single-trial P300 classification, such as complex, time-consuming and low accuracy processes, a single-trial P300 classification algorithm based on multiplayer data fusion convolutional neural network (CNN) is proposed to construct a centralized collaborative brain-computer interfaces (cBCI) for fast and highly accurate classification of P300 EEG signals.MethodsIn this paper, two multi-person data fusion methods (parallel data fusion and serial data fusion) are used in the data pre-processing stage to fuse multi-person EEG information stimulated by the same task instructions, and then the fused data is fed as input to the CNN for classification. …”
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Neurophysiological signatures of sensory-processing sensitivity by Nicole Meinersen-Schmidt, Nike Walter, Patricia Kulla, Thomas Loew, Thilo Hinterberger, Joachim Kruse

“…As hitherto no electroencephalography (EEG) study has been carried out, the aim of this work was to determine whether the self-reported level of SPS correlates with the EEG activity in different frequency bands.MethodsOne hundred fifteen participants were measured with 64-channel EEG during a task-free resting state. …”
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SincNet-Based Hybrid Neural Network for Motor Imagery EEG Decoding by Chang Liu, Jing Jin, Ian Daly, Shurui Li, Hao Sun, Yitao Huang, Xingyu Wang, Andrzej Cichocki

“…Most current studies choose filter cut-frequencies based on experience or intuition, resulting in sub-optimal use of MI-related spectral information in the electroencephalography (EEG). To improve information utilization, we propose a SincNet-based hybrid neural network (SHNN) for MI-based BCIs. …”
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