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Journal articles on the topic 'Theta/beta ratios'
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Sokhadze, E. M., B. Hillard, M. Eng, A. S. El-Baz, A. Tasman, and L. Sears. "ELECTROENCEPHALOGRAPHIC BIOFEEDBACK IMPROVES FOCUSED ATTENTION IN ATTENTION DEFICIT/HYPERACTIVITY DISORDER." Bulletin of Siberian Medicine 12, no. 2 (2013): 182–94. http://dx.doi.org/10.20538/1682-0363-2013-2-182-194.
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EEG biofeedback (so called neurofeedback) is considered as an efficacious treatment for ADHD. We propose that operant conditioning of EEG in neurofeedback training mode, aimed to mitigate inattention and low arousal in ADHD, will be accompanied by changes in EEG bands' relative power. Patients were 18 children diagnosed with ADHD. The neurofeedback protocol (“Focus/Alertness” by Peak Achievement Trainer, Neurotek, KY) used to train patients has focused attention training procedure, which according to specifications, represents wide band EEG amplitude suppression training. Quantitative EEG analysis was completed on each of 25 min long twelve sessions to determine the relative power of each of the EEG bands of interest throughout each session, and from the first session to the last session. Additional statistical analysis was performed to determine significant changes in relative power within sessions (from minute 1 to minute 25), and between sessions (from session 1 to session 12) for an individual patient. We performed analysis of relative power of Theta, Alpha, Low and High Beta, Theta/Alpha, Theta/Beta, and Theta/Low Beta and Theta/High Beta ratios. We performed also analysis between the “Focus”measure and changes in relative power of above EEG rhythms and their ratios. Additional secondary measures of patients’ post-neurofeedback outcomes were assessed using an audio-visual selective attention test (IVA + Plus) and behavioral evaluation scores from Aberrant Behavior Checklist. We found that, as expected, Theta/Low Beta and Theta/Alpha ratios decreased significantly from Session 1 to Session 12 and from minute 1 to minute 25 within sessions. The ‘Focus” measure of protocol showed high negative correlation with both Theta/Alpha and Theta/Beta ratios. The findings regarding EEG changes resulting from self-regulation training along with behavioral evaluations will help in elucidation of neural mechanisms of neurofeedback aimed to improve focused attention and alertness in ADHD.
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Alahmadi, Nsreen. "Classifying Children with Learning Disabilities on the Basis of Resting State EEG Measures Using a Linear Discriminant Analysis." Zeitschrift für Neuropsychologie 26, no. 4 (2015): 249–56. http://dx.doi.org/10.1024/1016-264x/a000161.
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Abstract. This study examines the usefulness of easy to obtain EEG measures to discriminate learning-disabled children (LD) from healthy control children. Here the spectral power in the delta, theta, alpha, and beta EEG bands and various power ratios (theta/alpha, theta/beta, beta/alpha, beta/theta, beta/[alpha+theta], [delta+theta]/alpha, alpha/delta, and [theta+alpha]/beta) are applied. These measures were subjected to a factor analysis with varimax rotation revealing four factors explaining 90 % of the entire variance. Factor 1 represents the power of the slow EEG frequency bands delta and theta, factor 2 the relationship between fast and slow frequency bands, factor 3 the slow to fast ratios, and factor 4 the absolute power of nearly all frequency bands. Group differences were found for three factor scores (1, 3, and 4). The linear discriminant analysis with the four factor scores as dependent and the group allocation as independent variables revealed a correct classification of 86 %. Although this classification is far from being perfect it is nevertheless reasonable high and statistically significant. Thus, EEG measures like the one used in this study might support the diagnosis of this difficult to diagnose disability. In addition, the EEG measures identified provide a deeper insight into the neural underpinnings of this disability. Based on this knowledge it might be possible to design new therapeutic strategies to treat LD.
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Sari Gokten, Emel, Emine Elif Tulay, Birsu Beser, et al. "Predictive Value of Slow and Fast EEG Oscillations for Methylphenidate Response in ADHD." Clinical EEG and Neuroscience 50, no. 5 (2019): 332–38. http://dx.doi.org/10.1177/1550059419863206.
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Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder and is characterized by symptoms of inattention and/or hyperactivity and impulsivity. In the current study, we obtained quantitative EEG (QEEG) recordings of 51 children aged between 6 and 12 years before the initiation of methylphenidate treatment. The relationship between changes in the scores of ADHD symptoms and initial QEEG features (power/power ratios values) were assessed. In addition, the children were classified as responder and nonresponder according to the ratio of their response to the medication (>25% improvement after medication). Logistic regression analyses were performed to analyze the accuracy of QEEG features for predicting responders. The findings indicate that patients with increased delta power at F8, theta power at Fz, F4, C3, Cz, T5, and gamma power at T6 and decreased beta powers at F8 and P3 showed more improvement in ADHD hyperactivity symptoms. In addition, increased delta/beta power ratio at F8 and theta/beta power ratio at F8, F3, Fz, F4, C3, Cz, P3, and T5 showed negative correlations with Conners’ score difference of hyperactivity as well. This means, those with greater theta/beta and delta/beta powers showed more improvement in hyperactivity following medication. Theta power at Cz and T5 and theta/beta power ratios at C3, Cz, and T5 have significantly classified responders and nonresponders according to the logistic binary regression analysis. The results show that slow and fast oscillations may have predictive value for treatment response in ADHD. Future studies should seek for more sensitive biomarkers.
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Abdelfattah, Sherif M., Kathryn E. Merrick, and Hussein A. Abbass. "Theta-Beta Ratios Are Prominent EEG Features for Visual Tracking Tasks." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60, no. 1 (2016): 21–25. http://dx.doi.org/10.1177/1541931213601005.
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Yi Wen, Tee, and Siti Armiza Mohd Aris. "Electroencephalogram (EEG) stress analysis on alpha/beta ratio and theta/beta ratio." Indonesian Journal of Electrical Engineering and Computer Science 17, no. 1 (2020): 175. http://dx.doi.org/10.11591/ijeecs.v17.i1.pp175-182.
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<span>This paper presents an analysis of stress feature using the power ratio of frequency bands including Alpha to Beta and Theta to Beta. In this study, electroencephalography (EEG) acquisition tool was utilized to collect brain signals from 40 subjects and objectively reflected stress features induced by virtual reality (VR) technology. The EEG signals were analyzed using Welch’s fast Fourier transform (FFT) to extract power spectral density (PSD) features which represented the power of a signal distributed over a range of frequencies. Slow wave versus fast wave (SW/FW) of EEG has been studied to discriminate stress from resting baseline. The results showed the Alpha/Beta ratio and Theta/Beta ratio are negatively correlated with stress and indicated that the power ratios can discriminate the data characteristics of brainwaves for stress assessment.</span>
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Huang, Ching-Wen, Chung-Ju Huang, Chiao-Ling Hung, Chia-Hao Shih, and Tsung-Min Hung. "Physical Fitness and Resting EEG in Children With Attention Deficit Hyperactivity Disorder." Journal of Psychophysiology 29, no. 1 (2015): 26–32. http://dx.doi.org/10.1027/0269-8803/a000131.
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Children with attention deficit hyperactivity disorder (ADHD) are characterized by a deviant pattern of brain oscillations during resting state, particularly elevated theta power and increased theta/alpha and theta/beta ratios that are related to cognitive functioning. Physical fitness has been found beneficial to cognitive performance in a wide age population. The purpose of the present study was to investigate the relationship between physical fitness and resting-state electroencephalographic (EEG) oscillations in children with ADHD. EEG was recorded during eyes-open resting for 28 children (23 boys and 5 girls, 8.66 ± 1.10 years) with ADHD, and a battery of physical fitness assessments including flexibility, muscular endurance, power, and agility tests were administered. The results indicated that ADHD children with higher power fitness exhibited a smaller theta/alpha ratio than those with lower power fitness. These findings suggest that power fitness may be associated with improved attentional self-control in children with ADHD.
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van Dijk, Hanneke, Roger deBeus, Cynthia Kerson, et al. "Different Spectral Analysis Methods for the Theta/Beta Ratio Calculate Different Ratios But Do Not Distinguish ADHD from Controls." Applied Psychophysiology and Biofeedback 45, no. 3 (2020): 165–73. http://dx.doi.org/10.1007/s10484-020-09471-2.
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Abstract There has been ongoing research on the ratio of theta to beta power (Theta/Beta Ratio, TBR) as an EEG-based test in the diagnosis of ADHD. Earlier studies reported significant TBR differences between patients with ADHD and controls. However, a recent meta-analysis revealed a marked decline of effect size for the difference in TBR between ADHD and controls for studies published in the past decade. Here, we test if differences in EEG processing explain the heterogeneity of findings. We analyzed EEG data from two multi-center clinical studies. Five different EEG signal processing algorithms were applied to calculate the TBR. Differences between resulting TBRs were subsequently assessed for clinical usability in the iSPOT-A dataset. Although there were significant differences in the resulting TBRs, none distinguished between children with and without ADHD, and no consistent associations with ADHD symptoms arose. Different methods for EEG signal processing result in significantly different TBRs. However, none of the methods significantly distinguished between ADHD and healthy controls in our sample. The secular effect size decline for the TBR is most likely explained by factors other than differences in EEG signal processing, e.g. fewer hours of sleep in participants and differences in inclusion criteria for healthy controls.
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Wischnewski, Miles, Mie L. Joergensen, Boukje Compen, and Dennis J. L. G. Schutter. "Frontal Beta Transcranial Alternating Current Stimulation Improves Reversal Learning." Cerebral Cortex 30, no. 5 (2020): 3286–95. http://dx.doi.org/10.1093/cercor/bhz309.
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Abstract Electroencephalogram (EEG) studies suggest an association between beta (13–30 Hz) power and reversal learning performance. In search for direct evidence concerning the involvement of beta oscillations in reversal learning, transcranial alternating current stimulation (tACS) was applied in a double-blind, sham-controlled and between-subjects design. Exogenous oscillatory currents were administered bilaterally to the frontal cortex at 20 Hz with an intensity of 1 mA peak-to-peak and the effects on reward-punishment based reversal learning were evaluated in hundred-and-eight healthy volunteers. Pre- and post-tACS resting state EEG recordings were analyzed. Results showed that beta-tACS improved rule implementation during reversal learning and decreases left and right resting-state frontal theta/beta EEG ratios following tACS. Our findings provide the first behavioral and electrophysiological evidence for exogenous 20 Hz oscillatory electric field potentials administered over to the frontal cortex to improve reversal learning.
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Fernández, T., W. Herrera, T. Harmony, et al. "EEG and Behavioral Changes following Neurofeedback Treatment in Learning Disabled Children." Clinical Electroencephalography 34, no. 3 (2003): 145–52. http://dx.doi.org/10.1177/155005940303400308.
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Neurofeedback (NFB) is an operant conditioning procedure, by which the subject learns to control his/her EEG activity. On one hand, Learning Disabled (LD) children have higher values of theta EEG absolute and relative power than normal children, and on the other hand, it has been shown that minimum alpha absolute power is necessary for adequate performance. Ten LD children were selected with higher than normal ratios of theta to alpha absolute power (theta/alpha). The Test Of Variables of Attention (TOVA) was applied. Children were divided into two groups in order to maintain similar IQ values, TOVA values, socioeconomical status, and gender for each group. In the experimental group, NFB was applied in the region with highest ratio, triggering a sound each time the ratio fell below a threshold value. Noncontingent reinforcement was given to the other group. Twenty half-hour sessions were applied, at a rate of 2 per week. At the end of the 20 sessions, TOVA, WISC and EEG were obtained. There was significant improvement in WISC performance in the experimental group that was not observed in the control group. EEG absolute power decreased in delta, theta, alpha and beta bands in the experimental group. Control children only showed a decrease in relative power in the delta band. All changes observed in the experimental group and not observed in the control group indicate better cognitive performance and the presence of greater EEG maturation in the experimental group, which suggests that changes were due not only to development but also to NFB treatment.
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Guner, Derya, Bedile Irem Tiftikcioglu, Nilgun Tuncay, and Yasar Zorlu. "Contribution of Quantitative EEG to the Diagnosis of Early Cognitive Impairment in Patients With Idiopathic Parkinson’s Disease." Clinical EEG and Neuroscience 48, no. 5 (2016): 348–54. http://dx.doi.org/10.1177/1550059416662412.
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Cognitive dysfunction can emerge during the clinical course of Parkinson’s disease (PD) even beginning in early stages, which requires extended neuropsychological tests for diagnosis. There is need for rapid, feasible, and practical tests in clinical practice to diagnose and monitor the patients without causing any discomfort. We investigated the utility of quantitative analysis of digital EEG (qEEG) for diagnosing subtle cognitive impairment in PD patients without evident cognitive deficits (ie, “normal cognition”). We enrolled 45 patients with PD and age- matched 39 healthy controls in the study. All participants had Mini-Mental State Examination (MMSE) score greater than 25. qEEG analysis and extensive neuropsychological assessment battery were applied to all participants. Test scores for frontal executive functions, verbal memory processes, attention span, and visuospatial functions were significantly lower than healthy controls ( P < .01). qEEG analysis revealed a significant increase in delta, theta, and beta frequencies, and decrease in alpha frequency band in cerebral bioelectrical activity in patient group. In addition, power spectral ratios ([alpha + beta] / [delta + theta]) in frontal, central, temporal, parietal, and occipital regions were significantly decreased in patients compared with the controls. The slowing in EEG was moderately correlated with MMSE scores ( r = 0.411-0.593; P < .01). However, qEEG analysis and extensive neuropsychological assessment battery were only in weak correlation ( r = 0.230-0.486; P < .05). In conclusion, qEEG analysis could increase the diagnostic power in detecting subtle cognitive impairment in PD patients without evident cognitive deficit, perhaps years before the clinical onset of dementia.
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Šverko, Zoran, Ivan Markovinović, Miroslav Vrankić, and Saša Vlahinić. "EEG data processing in ADHD diagnosis and neurofeedback." Engineering review 40, no. 3 (2020): 116–23. http://dx.doi.org/10.30765/er.40.3.12.
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In this paper, EEG data processing was conducted in order to define the parameters for neurofeedback. A new survey was conducted based on a brief review of previous research. Two groups of participants were chosen: ADHD (3) and nonADHD (14). The main part of this study includes EEG signal data pre-processing and processing. We have outlined statistical features of observed EEG signals such as mean value, grand-mean value and their ratios. It can be concluded that an increase in grand-mean values of power theta-low beta ratio on Cz electrode gives confirmation of previous research. The value of alpha-delta power ratio higher than 1 on C3, Cz, P3, Pz, P4 in ADHD group is proposed as a new approach to classification. Based on these conclusions we will design a neurofeedback protocol as a continuation of this work.
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Williamson, N., S. W. Armfield, and M. P. Kirkpatrick. "Transition to oscillatory flow in a differentially heated cavity with a conducting partition." Journal of Fluid Mechanics 693 (November 28, 2011): 93–114. http://dx.doi.org/10.1017/jfm.2011.471.
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AbstractNumerical evidence is presented for previously unreported flow behaviour in a two-dimensional rectangular side-heated cavity partitioned in the centre by vertical wall with an infinite conductivity. In this flow heat is transferred between both sides of the cavity through the conducting wall with natural convection boundary layers forming on all vertical surfaces. Simulations have been conducted over the range of Rayleigh numbers $\mathit{Ra}= 0. 6\text{{\ndash}} 1. 6\ensuremath{\times} 1{0}^{10} $ at Prandtl number $\mathit{Pr}= 7. 5$ and at aspect ratios of $H/ W= 1\text{{\ndash}} 2$ where $H$ and $W$ are the height and width of the cavity. It was found that the thermal coupling of the boundary layers on either side of the conducting partition causes the cavity flow to become absolutely unstable for a Rayleigh number at which otherwise similar non-partitioned cavity flow is steady but convectively unstable. Additionally, unlike the non-partitioned cavity, which eventually bifurcates to a multi-modal oscillatory regime, this bifurcation is manifested as a single mode oscillation with ${f}^{+ } = f{\nu }^{1/ 3} / \mathop{ (g\ensuremath{\beta} \mrm{\Delta} \theta )}\nolimits ^{2/ 3} \approx 0. 0145$, where $ \mrm{\Delta} \theta $ is the temperature difference between the hot and cold walls, $g$ is the gravitational acceleration, $f$ is the oscillation frequency and $\nu $ and $\ensuremath{\beta} $ are the fluid viscosity and coefficient of thermal expansion respectively. The critical Rayleigh number for this transition occurs between $\mathit{Ra}= 1. 0\text{{\ndash}} 1. 2\ensuremath{\times} 1{0}^{10} $ for $H/ W= 2$ and $\mathit{Ra}= 1. 2\text{{\ndash}} 1. 4\ensuremath{\times} 1{0}^{10} $ for $H/ W= 1$, indicating that the instability has an aspect ratio dependence.
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Markiewicz, Renata, and Beata Dobrowolska. "Cognitive and Social Rehabilitation in Schizophrenia—From Neurophysiology to Neuromodulation. Pilot Study." International Journal of Environmental Research and Public Health 17, no. 11 (2020): 4034. http://dx.doi.org/10.3390/ijerph17114034.
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The aim of this pilot study was to analyse the influence of Galvanic Skin Response (GSR) Biofeedback training in a group of 18 men with schizophrenia at the remission stage. The results were verified according to: Positive and Negative Syndrome Scale (PANSS), Acceptance of Illness Scale (AIS), Self-efficacy Scale (GSES), Beck Cognitive Insight Scale (BCIS) scales, Colour Trial Test (CTT-1, CTT-2), d2 psychological tests, Quantitative Electroencephalogram (QEEG) Biofeedback, auditory event-related potentials (ERPs), and serum levels of brain-derived neurotrophic factor (BDNF). The results were compared in the same patients after 3 months. Statistically significant changes were noted in results for the variables on the PANSS scale. For the BDNF variable, a statistically significant increase occurred, indicating that GSR Biofeedback training may influence serum levels of the neurotrophic factor. Statistically significant changes were noted in results for the variables on the BCIS, AIS, and GSES indicating an improvement in the cognitive and social functioning. Changes were noted for results for theta/beta and theta/Sensory Motor Rhythm (SMR) ratios, which indicate an improvement in concentration and attention. Changes were noted for the N1 wave amplitude in the frontal brain region (F-z), and for the P2 wave latency in the central brain region (C-z), which indicates an improvement in the initial perceptual analysis. The use of GSR Biofeedback in a group of patients with schizophrenia gives interesting results, but requires further in-depth research.
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Gorantla, Vasavi R., Sarah Tedesco, Merin Chandanathil, et al. "Associations of Alpha and Beta Interhemispheric EEG Coherences with Indices of Attentional Control and Academic Performance." Behavioural Neurology 2020 (February 5, 2020): 1–7. http://dx.doi.org/10.1155/2020/4672340.
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Introduction. Heretofore, research on optimizing academic performance has suffered from an inability to translate what is known about an individual’s learning behaviors to how effectively they are able to use the critical nodes and hubs in their cerebral cortex for learning. A previous study from our laboratory suggests that lower theta-beta ratios (TBRs) measured by EEG may be associated with higher academic performance in a medical school curriculum. Methods. In this study, we tested the hypothesis that TBR and academic performance may be correlated with EEG coherence, a measure of brain connectivity. We analyzed the interhemispheric coherences of the subjects involved in our prior study. TBR and coherence measurements were made at 19 scalp electrode recording sites and 171 electrode combinations with eyes open and closed (EO, EC). Control data were acquired during a session of acclimation to the research protocol 3 d before an initial examination in anatomy-physiology (control exam) and were repeated five weeks later, 3 d before a second exam covering different anatomy-physiology topics (comparison exam). Results. Between the control and comparison exams, beta coherences increased significantly at the frontal pole, frontal, parietal, midtemporal, posterior temporal, and occipital recording sites under the EO condition and at the inferior frontal, central, midtemporal, and posterior temporal sites under the EC condition. Alpha coherences increased significantly at the same sites and under the same EO/EC conditions as found for the beta coherences. The beta coherences were negatively correlated with the TBR and were positively correlated with the comparison exam score at the midfrontal electrode site (F3-F4) but only under the EO condition. Beta and alpha coherences at the midfrontal, inferior frontal midtemporal, posterior temporal, and occipital sites were also negatively correlated with the average TBR under the EO condition. Conclusions. Lower TBR, an indicator of attentional control, was associated with higher alpha and beta interhemispheric coherences measured with eyes open at sites overlying the frontal, temporal, and occipital cortices. Changes in EEG coherences and TBRs might be useful as neurophysiological measures of neuroplasticity and the efficacy of strategies for preventing academic underachievement and treatments for improving academic performance.
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Wu, Yunfeng, Yuchen Yao, Yugui Xiao, et al. "SEPARATION AND IDENTIFICATION OF RHYTHM COMPONENTS OF LOCAL FIELD POTENTIAL SIGNALS IN AWAKE MICE USING ENSEMBLE EMPIRICAL MODE DECOMPOSITION." Biomedical Engineering: Applications, Basis and Communications 29, no. 04 (2017): 1750029. http://dx.doi.org/10.4015/s1016237217500296.
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Decomposition of local field potential (LFP) signals with different oscillatory rhythms is useful for analysis of various neuronal activities in mice. In this paper, we first removed the power-line interference with high signal fidelity by using a notch filter with infinite impulse response. Next, we applied the ensemble empirical mode decomposition (EEMD) method to separate the LFP signal into low-frequency, Delta, Theta, Beta, Gamma, Ripple, and high-frequency oscillations, in the form of different intrinsic mode functions (IMFs). The LFP signal components with different frequency bands were identified and then reconstructed from the IMFs within the same frequency range by analyzing their power spectral ratios (PSRs). Then, normalized autocorrelation functions of the resting respiratory signal and the reconstructed Delta oscillations were computed to estimate the corresponding power spectral densities by means of the Fourier transform. The results of LFP signal decomposition and oscillatory rhythm reconstruction demonstrated the effectiveness of the EEMD and PSR analysis methods. The coherence analysis results indicate that the primary periodicity peak of the Delta LFP component is definitely linked to that of resting respiration in an awake mouse. Our major contribution is to establish a novel LFP signal separation and identification procedure by combining the EEMD method with appropriate parameter setting and the power spectral analysis approach.
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Brito, Rodrigo, Adriana Baltar, Marina Berenguer-Rocha, et al. "Intrahemispheric EEG: A New Perspective for Quantitative EEG Assessment in Poststroke Individuals." Neural Plasticity 2021 (September 21, 2021): 1–8. http://dx.doi.org/10.1155/2021/5664647.
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The ratio between slower and faster frequencies of brain activity may change after stroke. However, few studies have used quantitative electroencephalography (qEEG) index of ratios between slower and faster frequencies such as the delta/alpha ratio (DAR) and the power ratio index (PRI; delta + theta / alpha + beta ) for investigating the difference between the affected and unaffected hemisphere poststroke. Here, we proposed a new perspective for analyzing DAR and PRI within each hemisphere and investigated the motor impairment-related interhemispheric frequency oscillations. Forty-seven poststroke subjects and twelve healthy controls were included in the study. Severity of upper limb motor impairment was classified according to the Fugl–Meyer assessment in mild/moderate ( n = 25 ) and severe ( n = 22 ). The qEEG indexes (PRI and DAR) were computed for each hemisphere (intrahemispheric index) and for both hemispheres (cerebral index). Considering the cerebral index (DAR and PRI), our results showed a slowing in brain activity in poststroke patients when compared to healthy controls. Only the intrahemispheric PRI index was able to find significant interhemispheric differences of frequency oscillations. Despite being unable to detect interhemispheric differences, the DAR index seems to be more sensitive to detect motor impairment-related frequency oscillations. The intrahemispheric PRI index may provide insights into therapeutic approaches for interhemispheric asymmetry after stroke.
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Abu Nawas, Khairul Amrizal, Mahfuzah Mustafa, Rosdiyana Samad, Dwi Pebrianti, and Nor Rul Hasma Abdullah. "K-NN Classification of Brain Dominance." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 4 (2018): 2494. http://dx.doi.org/10.11591/ijece.v8i4.pp2494-2502.
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<span>The brain dominance is referred to right brain and left brain. The brain dominance can be observed with an Electroencephalogram (EEG) signal to identify different types of electrical pattern in the brain and will form the foundation of one’s personality. The objective of this project is to analyze brain dominance by using Wavelet analysis. The Wavelet analysis is done in 2-D Gabor Wavelet and the result of 2-D Gabor Wavelet is validated with an establish brain dominance questionnaire. Twenty-one samples from University Malaysia Pahang (UMP) student are required to answer the establish brain dominance questionnaire has been collected in this experiment. Then, brainwave signal will record using Emotiv device. The threshold value is used to remove the artifact and noise from data collected to acquire a smoother signal. Next, the Band-pass filter is applied to the signal to extract the sub-band frequency components from Delta, Theta, Alpha, and Beta. After that, it will extract the energy of the signal from image feature extraction process. Next the features were classified by using K-Nearest Neighbor (K-NN) in two ratios which 70:30 and 80:20 that are training set and testing set (training: testing). The ratio of 70:30 gave the highest percentage of 83% accuracy while a ratio of 80:20 gave 100% accuracy. The result shows that 2-D Gabor Wavelet was able to classify brain dominance with accuracy 83% to 100%.</span>
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Tsimpanouli, M., R. D. Chervin, and S. V. Gliske. "0051 Respiratory Cycle-Related EEG Changes (RCREC) Predict Incidence and Recurrence of Cardiovascular Disease." Sleep 43, Supplement_1 (2020): A21. http://dx.doi.org/10.1093/sleep/zsaa056.050.
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Abstract Introduction Sleep-disordered breathing (SDB) is a common sleep disturbance and is associated with both incident and recurrent cardiovascular disease (CVD). Respiratory Cycle-Related EEG Changes (RCREC), an SDB biomarker, are thought to reflect inspiratory microarousals and are based on quantitative analysis of sleep EEG and breathing. The objective of this study was to assess whether RCREC may predict CVD incidence or recurrence in a large cohort of adults. The RCREC for several frequency bands have been previously shown to predict either higher or lower all-cause mortality in the same cohort. Methods Data were obtained from the Sleep Heart Health Study (SHHS), a multicenter longitudinal study that included polysomnograms in middle-aged to older adults. Information about CVD events was collected at baseline and for up to 16 years later. The RCREC values at baseline were computed in the delta, theta, alpha, sigma, beta, and gamma frequency bands during scored epochs of sleep. Cox Proportional Hazard models, were used to assess the relation of each RCREC frequency band and incidence or recurrence of CVD. These models were stratified by sex and adjusted for body-mass index, age, race, smoking status, diabetic status, hypertensive status, HDL cholesterol, LDL cholesterol, and the apnea-hypopnea index (AHI). Results There were 3,032 adults with sufficient data quality (mean age at baseline 62±11(SD) years, 58% female). Among 2,500 adults with no reported prior CVD history at baseline, the adjusted odds ratios (95% CI) for delta RCREC 0.948(0.920–0.977), theta RCREC 0.938(0.895–0.984), and alpha RCREC 0.946(0.902–0.993) separately suggested associations with lower CVD incidence, whereas gamma RCREC 1.017(1.001–1.032) predicted a marginal increase. Among 532 adults having prior CVD history at baseline, delta RCREC 0.958(0.927–0.989) and sigma RCREC 0.931(0.895–0.969) separately predicted decreased CVD recurrence. The apnea-hypopnea index (AHI) was not similarly predictive in any model. Conclusion The RCREC for several frequency bands, in contrast to AHI, may predict CVD incidence and recurrence. The directionality of the association was surprising and merits further exploration. Support NIH:NCATS-TL1-TR-002242, BD2K-K01-ES-026839, HL105999
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Antoniou, Panagiotis E., George Arfaras, Niki Pandria, et al. "Biosensor Real-Time Affective Analytics in Virtual and Mixed Reality Medical Education Serious Games: Cohort Study." JMIR Serious Games 8, no. 3 (2020): e17823. http://dx.doi.org/10.2196/17823.
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Background The role of emotion is crucial to the learning process, as it is linked to motivation, interest, and attention. Affective states are expressed in the brain and in overall biological activity. Biosignals, like heart rate (HR), electrodermal activity (EDA), and electroencephalography (EEG) are physiological expressions affected by emotional state. Analyzing these biosignal recordings can point to a person’s emotional state. Contemporary medical education has progressed extensively towards diverse learning resources using virtual reality (VR) and mixed reality (MR) applications. Objective This paper aims to study the efficacy of wearable biosensors for affect detection in a learning process involving a serious game in the Microsoft HoloLens VR/MR platform. Methods A wearable array of sensors recording HR, EDA, and EEG signals was deployed during 2 educational activities conducted by 11 participants of diverse educational level (undergraduate, postgraduate, and specialist neurosurgeon doctors). The first scenario was a conventional virtual patient case used for establishing the personal biosignal baselines for the participant. The second was a case in a VR/MR environment regarding neuroanatomy. The affective measures that we recorded were EEG (theta/beta ratio and alpha rhythm), HR, and EDA. Results Results were recorded and aggregated across all 3 groups. Average EEG ratios of the virtual patient (VP) versus the MR serious game cases were recorded at 3.49 (SD 0.82) versus 3.23 (SD 0.94) for students, 2.59 (SD 0.96) versus 2.90 (SD 1.78) for neurosurgeons, and 2.33 (SD 0.26) versus 2.56 (SD 0.62) for postgraduate medical students. Average alpha rhythm of the VP versus the MR serious game cases were recorded at 7.77 (SD 1.62) μV versus 8.42 (SD 2.56) μV for students, 7.03 (SD 2.19) μV versus 7.15 (SD 1.86) μV for neurosurgeons, and 11.84 (SD 6.15) μV versus 9.55 (SD 3.12) μV for postgraduate medical students. Average HR of the VP versus the MR serious game cases were recorded at 87 (SD 13) versus 86 (SD 12) bpm for students, 81 (SD 7) versus 83 (SD 7) bpm for neurosurgeons, and 81 (SD 7) versus 77 (SD 6) bpm for postgraduate medical students. Average EDA of the VP versus the MR serious game cases were recorded at 1.198 (SD 1.467) μS versus 4.097 (SD 2.79) μS for students, 1.890 (SD 2.269) μS versus 5.407 (SD 5.391) μS for neurosurgeons, and 0.739 (SD 0.509) μS versus 2.498 (SD 1.72) μS for postgraduate medical students. The variations of these metrics have been correlated with existing theoretical interpretations regarding educationally relevant affective analytics, such as engagement and educational focus. Conclusions These results demonstrate that this novel sensor configuration can lead to credible affective state detection and can be used in platforms like intelligent tutoring systems for providing real-time, evidence-based, affective learning analytics using VR/MR-deployed medical education resources.
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Morin-Duchesne, Alexi, and Jesper Jacobsen. "Two-point boundary correlation functions of dense loop models." SciPost Physics 4, no. 6 (2018). http://dx.doi.org/10.21468/scipostphys.4.6.034.
Full textAbstract:
We investigate six types of two-point boundary correlation functions in the dense loop model. These are defined as ratios Z/Z^0Z/Z0 of partition functions on the m\times nm×n square lattice, with the boundary condition for ZZ depending on two points xx and yy. We consider: the insertion of an isolated defect (a) and a pair of defects (b) in a Dirichlet boundary condition, the transition (c) between Dirichlet and Neumann boundary conditions, and the connectivity of clusters (d), loops (e) and boundary segments (f) in a Neumann boundary condition.For the model of critical dense polymers, corresponding to a vanishing loop weight (\beta = 0β=0), we find determinant and pfaffian expressions for these correlators. We extract the conformal weights of the underlying conformal fields and find \Delta = -\frac18Δ=−18, 00, -\frac3{32}−332, \frac3838, 11, \tfrac \theta \pi (1+ \tfrac{2\theta}\pi)θπ(1+2θπ), where \thetaθ encodes the weight of one class of loops for the correlator of type f. These results are obtained by analysing the asymptotics of the exact expressions, and by using the Cardy-Peschel formula in the case where xx and yy are set to the corners. For type b, we find a \ln|x-y|ln|x−y| dependence from the asymptotics, and a \ln (\ln n)ln(lnn) term in the corner free energy. This is consistent with the interpretation of the boundary condition of type b as the insertion of a logarithmic field belonging to a rank two Jordan cell.For the other values of \beta = 2 \cos \lambdaβ=2cosλ, we use the hypothesis of conformal invariance to predict the conformal weights and find \Delta = \Delta_{1,2}Δ=Δ1,2, \Delta_{1,3}Δ1,3, \Delta_{0,\frac12}Δ0,12, \Delta_{1,0}Δ1,0, \Delta_{1,-1}Δ1,−1 and \Delta_{\frac{2\theta}\lambda+1,\frac{2\theta}\lambda+1}Δ2θλ+1,2θλ+1, extending the results of critical dense polymers. With the results for type f, we reproduce a Coulomb gas prediction for the valence bond entanglement entropy of Jacobsen and Saleur.
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Lin, Chi-Fang, Chung-Ju Huang, Yu-Jung Tsai, et al. "Resting Theta/Beta Ratios Mediate the Relationship Between Motor Competence and Inhibition in Children With Attention Deficit/Hyperactivity Disorder." Frontiers in Psychology 12 (June 3, 2021). http://dx.doi.org/10.3389/fpsyg.2021.649154.
Full textAbstract:
Despite that previous studies have supported relationships between motor ability and inhibitory function, and between resting brain theta/beta power ratios (TBR) and inhibition in children with attention deficit/hyperactivity disorder (ADHD), little research has examined the mechanism within these relationships. The purpose of this study was to investigate whether TBR would mediate the relationship between motor ability and inhibitory function. A total of 71 children with ADHD were recorded resting electroencephalographic (EEG) data during eyes-open. Motor abilities were evaluated by Movement Assessment Battery for Children-2 (MABC-2) and inhibitory ability were assessed by a modified Eriksen’s flanker task. The results of mediation analyses revealed that TBR could completely mediate the relationship between motor competence and response speed (indirect effect = −0.0004, 95% CI [−0.0010, −0.0001]) and accuracy (indirect effect = 0.0003, 95% CI [0.0000, 0.0010]) in the incongruent condition of the flanker task. This study suggests that TBR may be one of the mechanisms between motor ability and inhibition function in children with ADHD.
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Dastolfo-Hromack, C., A. Bush, A. Chrabaszcz, et al. "Articulatory Gain Predicts Motor Cortex and Subthalamic Nucleus Activity During Speech." Cerebral Cortex, September 1, 2021. http://dx.doi.org/10.1093/cercor/bhab251.
Full textAbstract:
Abstract Speaking precisely is important for effective verbal communication, and articulatory gain is one component of speech motor control that contributes to achieving this goal. Given that the basal ganglia have been proposed to regulate the speed and size of limb movement, that is, movement gain, we explored the basal ganglia contribution to articulatory gain, through local field potentials (LFP) recorded simultaneously from the subthalamic nucleus (STN), precentral gyrus, and postcentral gyrus. During STN deep brain stimulation implantation for Parkinson’s disease, participants read aloud consonant-vowel-consonant syllables. Articulatory gain was indirectly assessed using the F2 Ratio, an acoustic measurement of the second formant frequency of/i/vowels divided by/u/vowels. Mixed effects models demonstrated that the F2 Ratio correlated with alpha and theta activity in the precentral gyrus and STN. No correlations were observed for the postcentral gyrus. Functional connectivity analysis revealed that higher phase locking values for beta activity between the STN and precentral gyrus were correlated with lower F2 Ratios, suggesting that higher beta synchrony impairs articulatory precision. Effects were not related to disease severity. These data suggest that articulatory gain is encoded within the basal ganglia-cortical loop.
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Gagnon, Katia, Christianne Bolduc, Laurianne Bastien, and Roger Godbout. "REM Sleep EEG Activity and Clinical Correlates in Adults With Autism." Frontiers in Psychiatry 12 (June 8, 2021). http://dx.doi.org/10.3389/fpsyt.2021.659006.
Full textAbstract:
We tested the hypothesis of an atypical scalp distribution of electroencephalography (EEG) activity during Rapid Eye Movement (REM) sleep in young autistic adults. EEG spectral activity and ratios along the anteroposterior axis and across hemispheres were compared in 16 neurotypical (NT) young adults and 17 individuals with autism spectrum disorder (ASD). EEG spectral power was lower in the ASD group over the bilateral central and right parietal (beta activity) as well as bilateral occipital (beta, theta, and total activity) recording sites. The NT group displayed a significant posterior polarity of intra-hemispheric EEG activity while EEG activity was more evenly or anteriorly distributed in ASD participants. No significant inter-hemispheric EEG lateralization was found. Correlations between EEG distribution and ASD symptoms using the Autism Diagnostic Interview-Revised (ADI-R) showed that a higher posterior ratio was associated with a better ADI-R score on communication skills, whereas a higher anterior ratio was related to more restricted interests and repetitive behaviors. EEG activity thus appears to be atypically distributed over the scalp surface in young adults with autism during REM sleep within cerebral hemispheres, and this correlates with some ASD symptoms. These suggests the existence in autism of a common substrate between some of the symptoms of ASD and an atypical organization and/or functioning of the thalamo-cortical loop during REM sleep.
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Ajčević, Miloš, Giovanni Furlanis, Marcello Naccarato, et al. "Hyper-acute EEG alterations predict functional and morphological outcomes in thrombolysis-treated ischemic stroke: a wireless EEG study." Medical & Biological Engineering & Computing, December 4, 2020. http://dx.doi.org/10.1007/s11517-020-02280-z.
Full textAbstract:
AbstractOwing to the large inter-subject variability, early post-stroke prognosis is challenging, and objective biomarkers that can provide further prognostic information are still needed. The relation between quantitative EEG parameters in pre-thrombolysis hyper-acute phase and outcomes has still to be investigated. Hence, possible correlations between early EEG biomarkers, measured on bedside wireless EEG, and short-term/long-term functional and morphological outcomes were investigated in thrombolysis-treated strokes. EEG with a wireless device was performed in 20 patients with hyper-acute (< 4.5 h from onset) anterior ischemic stroke before reperfusion treatment. The correlations between outcome parameters (i.e., 7-day/12-month National Institutes of Health Stroke Scale NIHSS, 12-month modified Rankin Scale mRS, final infarct volume) and the pre-treatment EEG parameters were studied. Relative delta power and alpha power, delta/alpha (DAR), and (delta+theta)/(alpha+beta) (DTABR) ratios significantly correlated with NIHSS 7-day (rho = 0.80, − 0.81, 0.76, 0.75, respectively) and NIHSS 12-month (0.73, − 0.78, 0.74, 0.73, respectively), as well as with final infarct volume (0.75, − 0.70, 0.78, 0.62, respectively). A good outcome in terms of mRS ≤ 2 at 12 months was associated with DAR parameter (p = 0.008). The neurophysiological biomarkers obtained by non-invasive and portable technique as wireless EEG in the early pre-treatment phase may contribute as objective parameters to the short/long-term outcome prediction pivotal to better establish the treatment strategies.Graphical abstract