Resting and reactive frontal brain electrical activity (EEG among a non-clinical sample of socially anxious adults: Does concurrent depressive mood matter?

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Elliott A Beaton

2008-03-01

Full Text Available Elliott A Beaton1, Louis A Schmidt2, Andrea R Ashbaugh2,5, Diane L Santesso2, Martin M Antony1,3,4, Randi E McCabe1,31Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada; 2Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, Ontario, Canada; 3Anxiety Treatment and Research Centre, St. Joseph’s Healthcare, Hamilton, Ontario, Canada; 4Department of Psychology, Ryerson University, Toronto, Ontario, Canada; 5Concordia University, Montreal, Quebec, CanadaAbstract: A number of studies have noted that the pattern of resting frontal brain electrical activity (EEG is related to individual differences in affective style in healthy infants, children, and adults and some clinical populations when symptoms are reduced or in remission. We measured self-reported trait shyness and sociability, concurrent depressive mood, and frontal brain electrical activity (EEG at rest and in anticipation of a speech task in a non-clinical sample of healthy young adults selected for high and low social anxiety. Although the patterns of resting and reactive frontal EEG asymmetry did not distinguish among individual differences in social anxiety, the pattern of resting frontal EEG asymmetry was related to trait shyness after controlling for concurrent depressive mood. Individuals who reported a higher degree of shyness were likely to exhibit greater relative right frontal EEG activity at rest. However, trait shyness was not related to frontal EEG asymmetry measured during the speech-preparation task, even after controlling for concurrent depressive mood. These findings replicate and extend prior work on resting frontal EEG asymmetry and individual differences in affective style in adults. Findings also highlight the importance of considering concurrent emotional states of participants when examining psychophysiological correlates of personality.Keywords: social anxiety, shyness, sociability

Specific or nonspecific? Evaluation of band, baseline, and cognitive specificity of sensorimotor rhythm- and gamma-based neurofeedback.

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Kober, Silvia Erika; Witte, Matthias; Neuper, Christa; Wood, Guilherme

2017-10-01

Neurofeedback (NF) is often criticized because of the lack of empirical evidence of its specificity. Our present study thus focused on the specificity of NF on three levels: band specificity, cognitive specificity, and baseline specificity. Ten healthy middle-aged individuals performed ten sessions of SMR (sensorimotor rhythm, 12-15Hz) NF training. A second group (N=10) received feedback of a narrow gamma band (40-43Hz). Effects of NF on EEG resting measurements (tonic EEG) and cognitive functions (memory, intelligence) were evaluated using a pre-post design. Both training groups were able to linearly increase the target training frequencies (either SMR or gamma), indicating the trainability of these EEG frequencies. Both NF training protocols led to nonspecific changes in other frequency bands during NF training. While SMR NF only led to concomitant changes in slower frequencies, gamma training affected nearly the whole power spectrum. SMR NF specifically improved memory functions. Gamma training showed only marginal effects on cognitive functions. SMR power assessed during resting measurements significantly increased after SMR NF training compared to a pre-assessment, indicating specific effects of SMR NF on baseline/tonic EEG. The gamma group did not show any pre-post changes in their EEG resting activity. In conclusion, SMR NF specifically affects cognitive functions (cognitive specificity) and tonic EEG (baseline specificity), while increasing SMR during NF training nonspecifically affects slower EEG frequencies as well (band non-specificity). Gamma NF was associated with nonspecific effects on the EEG power spectrum during training, which did not lead to considerable changes in cognitive functions or baseline EEG activity. Copyright © 2017 Elsevier B.V. All rights reserved.

From swing to cane: Sex differences of EEG resting-state temporal patterns during maturation and aging

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M.I. Tomescu

2018-06-01

Full Text Available While many insights on brain development and aging have been gained by studying resting-state networks with fMRI, relating these changes to cognitive functions is limited by the temporal resolution of fMRI. In order to better grasp short-lasting and dynamically changing mental activities, an increasing number of studies utilize EEG to define resting-state networks, thereby often using the concept of EEG microstates. These are brief (around 100 ms periods of stable scalp potential fields that are influenced by cognitive states and are sensitive to neuropsychiatric diseases. Despite the rising popularity of the EEG microstate approach, information about age changes is sparse and nothing is known about sex differences. Here we investigated age and sex related changes of the temporal dynamics of EEG microstates in 179 healthy individuals (6–87 years old, 90 females, 204-channel EEG. We show strong sex-specific changes in microstate dynamics during adolescence as well as at older age. In addition, males and females differ in the duration and occurrence of specific microstates. These results are of relevance for the comparison of studies in populations of different age and sex and for the understanding of the changes in neuropsychiatric diseases.

Effects of Soft Drinks on Resting State EEG and Brain-Computer Interface Performance.

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Meng, Jianjun; Mundahl, John; Streitz, Taylor; Maile, Kaitlin; Gulachek, Nicholas; He, Jeffrey; He, Bin

2017-01-01

Motor imagery-based (MI based) brain-computer interface (BCI) using electroencephalography (EEG) allows users to directly control a computer or external device by modulating and decoding the brain waves. A variety of factors could potentially affect the performance of BCI such as the health status of subjects or the environment. In this study, we investigated the effects of soft drinks and regular coffee on EEG signals under resting state and on the performance of MI based BCI. Twenty-six healthy human subjects participated in three or four BCI sessions with a resting period in each session. During each session, the subjects drank an unlabeled soft drink with either sugar (Caffeine Free Coca-Cola), caffeine (Diet Coke), neither ingredient (Caffeine Free Diet Coke), or a regular coffee if there was a fourth session. The resting state spectral power in each condition was compared; the analysis showed that power in alpha and beta band after caffeine consumption were decreased substantially compared to control and sugar condition. Although the attenuation of powers in the frequency range used for the online BCI control signal was shown, group averaged BCI online performance after consuming caffeine was similar to those of other conditions. This work, for the first time, shows the effect of caffeine, sugar intake on the online BCI performance and resting state brain signal.

Characterizing Alzheimer's disease severity via resting-awake EEG amplitude modulation analysis.

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Francisco J Fraga

Full Text Available Changes in electroencephalography (EEG amplitude modulations have recently been linked with early-stage Alzheimer's disease (AD. Existing tools available to perform such analysis (e.g., detrended fluctuation analysis, however, provide limited gains in discriminability power over traditional spectral based EEG analysis. In this paper, we explore the use of an innovative EEG amplitude modulation analysis technique based on spectro-temporal signal processing. More specifically, full-band EEG signals are first decomposed into the five well-known frequency bands and the envelopes are then extracted via a Hilbert transform. Each of the five envelopes are further decomposed into four so-called modulation bands, which were chosen to coincide with the delta, theta, alpha and beta frequency bands. Experiments on a resting-awake EEG dataset collected from 76 participants (27 healthy controls, 27 diagnosed with mild-AD, and 22 with moderate-AD showed significant differences in amplitude modulations between the three groups. Most notably, i delta modulation of the beta frequency band disappeared with an increase in disease severity (from mild to moderate AD, ii delta modulation of the theta band appeared with an increase in severity, and iii delta modulation of the beta frequency band showed to be a reliable discriminant feature between healthy controls and mild-AD patients. Taken together, it is hoped that the developed tool can be used to assist clinicians not only with early detection of Alzheimer's disease, but also to monitor its progression.

"I am resting but rest less well with you." The moderating effect of anxious attachment style on alpha power during EEG resting state in a social context

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Verbeke, W.J.M.I.; Pozharliev, R.; van Strien, J.W.; Belschak, F.; Bagozzi, R.P.

2014-01-01

We took EEG recordings to measure task-free resting-state cortical brain activity in 35 participants under two conditions, alone (A) or together (T). We also investigated whether psychological attachment styles shape human cortical activity differently in these two settings. The results indicate

Posture Used in fMRI-PET Elicits Reduced Cortical Activity and Altered Hemispheric Asymmetry with Respect to Sitting Position: An EEG Resting State Study

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Chiara Spironelli

2017-12-01

Full Text Available Horizontal body position is a posture typically adopted for sleeping or during brain imaging recording in both neuroscience experiments and diagnostic situations. Recent literature showed how this position and similar ones with head down are associated to reduced plasticity, impaired pain and emotional responses. The present study aimed at further understanding the decrease of cortical activity associated with horizontal body position by measuring high-frequency EEG bands – typically associated with high-level cognitive activation – in a resting state experimental condition. To this end, two groups of 16 female students were randomly assigned to either sitting control (SC or 2-h horizontal Bed Rest condition (hBR while EEG was recorded from 38 scalp recording sites. The hBR group underwent several body transitions, from sitting to supine, and from supine to sitting. Results revealed a clear effect of horizontal posture: the hBR group showed, compared to its baseline and to SC, reduced High-Beta and Gamma EEG band amplitudes throughout the 2-h of hBR condition. In addition, before and after the supine condition, hBR group as well as SC exhibited a greater left vs. right frontal activation in both EEG bands while, on the contrary, the supine position induced a bilateral and reduced activation in hBR participants. The cortical sources significantly more active in SC compared with hBR participants included the left Inferior Frontal Gyrus and left Insula. Results are discussed in relation to the differences among neuroimaging methods (e.g., fMRI, EEG, NIRS, which can be partially explained by posture-induced neural network changes.

Resting state brain dynamics and its transients: a combined TMS-EEG study.

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Bonnard, Mireille; Chen, Sophie; Gaychet, Jérôme; Carrere, Marcel; Woodman, Marmaduke; Giusiano, Bernard; Jirsa, Viktor

2016-08-04

The brain at rest exhibits a spatio-temporally rich dynamics which adheres to systematic behaviours that persist in task paradigms but appear altered in disease. Despite this hypothesis, many rest state paradigms do not act directly upon the rest state and therefore cannot confirm hypotheses about its mechanisms. To address this challenge, we combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to study brain's relaxation toward rest following a transient perturbation. Specifically, TMS targeted either the medial prefrontal cortex (MPFC), i.e. part of the Default Mode Network (DMN) or the superior parietal lobule (SPL), involved in the Dorsal Attention Network. TMS was triggered by a given brain state, namely an increase in occipital alpha rhythm power. Following the initial TMS-Evoked Potential, TMS at MPFC enhances the induced occipital alpha rhythm, called Event Related Synchronisation, with a longer transient lifetime than TMS at SPL, and a higher amplitude. Our findings show a strong coupling between MPFC and the occipital alpha power. Although the rest state is organized around a core of resting state networks, the DMN functionally takes a special role among these resting state networks.

[Effects of unstructured video exposure on EEG power in situations of forced attention and rest].

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Dan'ko, S G; Boĭtsova, Iu A; Kachalova, L M

2011-01-01

Group 1 (N = 30) and group 2 (N = 22) of healthy volunteers participated in the experiment. EEG registration took place while the examinees were in the resting states: with closed eyes; with opened eyes; with opened eyes and being under exposure to TV channel noises (white noise). Group 1 had also to fulfill a task to count randomly appearing symbols on a screen and group 2 had to fulfill a task to find an image in the noises. Averaged values of EEG power in each of the derivations in each of the derivations were calculated for an every examinee and for each of the states. The estimations were done in delta, theta, alpha1, alpha2, beta1, beta2, gamma frequency bands. The received results demonstrate that exposure to unstructured non-informative video noise can lead to significant changes of EEG power in a variety of frequency bands which are most prominent in the band alpha2. The changes are topically widespread, reflecting systemic changes in corresponding brain mechanisms, but are much less intensive if compared to changes between resting states with opened and closed eyes.

Cross coherence independent component analysis in resting and action states EEG discrimination

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Almurshedi, A; Ismail, A K

2014-01-01

Cross Coherence time frequency transform and independent component analysis (ICA) method were used to analyse the electroencephalogram (EEG) signals in resting and action states during open and close eyes conditions. From the topographical scalp distributions of delta, theta, alpha, and beta power spectrum can clearly discriminate between the signal when the eyes were open or closed, but it was difficult to distinguish between resting and action states when the eyes were closed. In open eyes condition, the frontal area (Fp1, Fp2) was activated (higher power) in delta and theta bands whilst occipital (O1, O2) and partial (P3, P4, Pz) area of brain was activated alpha band in closed eyes condition. The cross coherence method of time frequency analysis is capable of discrimination between rest and action brain signals in closed eyes condition

EEG frequency PCA in EEG-ERP dynamics.

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Barry, Robert J; De Blasio, Frances M

2018-05-01

Principal components analysis (PCA) has long been used to decompose the ERP into components, and these mathematical entities are increasingly accepted as meaningful and useful representatives of the electrophysiological components constituting the ERP. A similar expansion appears to be beginning in regard to decomposition of the EEG amplitude spectrum into frequency components via frequency PCA. However, to date, there has been no exploration of the brain's dynamic EEG-ERP linkages using PCA decomposition to assess components in each measure. Here, we recorded intrinsic EEG in both eyes-closed and eyes-open resting conditions, followed by an equiprobable go/no-go task. Frequency PCA of the EEG, including the nontask resting and within-task prestimulus periods, found seven frequency components within the delta to beta range. These differentially predicted PCA-derived go and no-go N1 and P3 ERP components. This demonstration suggests that it may be beneficial in future brain dynamics studies to implement PCA for the derivation of data-driven components from both the ERP and EEG. © 2017 Society for Psychophysiological Research.

Resting State EEG in Children With Learning Disabilities: An Independent Component Analysis Approach.

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Jäncke, Lutz; Alahmadi, Nsreen

2016-01-01

In this study, the neurophysiological underpinnings of learning disabilities (LD) in children are examined using resting state EEG. We were particularly interested in the neurophysiological differences between children with learning disabilities not otherwise specified (LD-NOS), learning disabilities with verbal disabilities (LD-Verbal), and healthy control (HC) children. We applied 2 different approaches to examine the differences between the different groups. First, we calculated theta/beta and theta/alpha ratios in order to quantify the relationship between slow and fast EEG oscillations. Second, we used a recently developed method for analyzing spectral EEG, namely the group independent component analysis (gICA) model. Using these measures, we identified substantial differences between LD and HC children and between LD-NOS and LD-Verbal children in terms of their spectral EEG profiles. We obtained the following findings: (a) theta/beta and theta/alpha ratios were substantially larger in LD than in HC children, with no difference between LD-NOS and LD-Verbal children; (b) there was substantial slowing of EEG oscillations, especially for gICs located in frontal scalp positions, with LD-NOS children demonstrating the strongest slowing; (c) the estimated intracortical sources of these gICs were mostly located in brain areas involved in the control of executive functions, attention, planning, and language; and (d) the LD-Verbal children demonstrated substantial differences in EEG oscillations compared with LD-NOS children, and these differences were localized in language-related brain areas. The general pattern of atypical neurophysiological activation found in LD children suggests that they suffer from neurophysiological dysfunction in brain areas involved with the control of attention, executive functions, planning, and language functions. LD-Verbal children also demonstrate atypical activation, especially in language-related brain areas. These atypical

Early Changes in Alpha Band Power and DMN BOLD Activity in Alzheimer’s Disease: A Simultaneous Resting State EEG-fMRI Study

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Katharina Brueggen

2017-10-01

Full Text Available Simultaneous resting state functional magnetic resonance imaging (rsfMRI–resting state electroencephalography (rsEEG studies in healthy adults showed robust positive associations of signal power in the alpha band with BOLD signal in the thalamus, and more heterogeneous associations in cortical default mode network (DMN regions. Negative associations were found in occipital regions. In Alzheimer’s disease (AD, rsfMRI studies revealed a disruption of the DMN, while rsEEG studies consistently reported a reduced power within the alpha band. The present study is the first to employ simultaneous rsfMRI-rsEEG in an AD sample, investigating the association of alpha band power and BOLD signal, compared to healthy controls (HC. We hypothesized to find reduced positive associations in DMN regions and reduced negative associations in occipital regions in the AD group. Simultaneous resting state fMRI–EEG was recorded in 14 patients with mild AD and 14 HC, matched for age and gender. Power within the EEG alpha band (8–12 Hz, 8–10 Hz, and 10–12 Hz was computed from occipital electrodes and served as regressor in voxel-wise linear regression analyses, to assess the association with the BOLD signal. Compared to HC, the AD group showed significantly decreased positive associations between BOLD signal and occipital alpha band power in clusters in the superior, middle and inferior frontal cortex, inferior temporal lobe and thalamus (p < 0.01, uncorr., cluster size ≥ 50 voxels. This group effect was more pronounced in the upper alpha sub-band, compared to the lower alpha sub-band. Notably, we observed a high inter-individual heterogeneity. Negative associations were only reduced in the lower alpha range in the hippocampus, putamen and cerebellum. The present study gives first insights into the relationship of resting-state EEG and fMRI characteristics in an AD sample. The results suggest that positive associations between alpha band power and BOLD

Lasting modulation effects of rTMS on neural activity and connectivity as revealed by resting-state EEG.

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Ding, Lei; Shou, Guofa; Yuan, Han; Urbano, Diamond; Cha, Yoon-Hee

2014-07-01

The long-lasting neuromodulatory effects of repetitive transcranial magnetic stimulation (rTMS) are of great interest for therapeutic applications in various neurological and psychiatric disorders, due to which functional connectivity among brain regions is profoundly disturbed. Classic TMS studies selectively alter neural activity in specific brain regions and observe neural activity changes on nonperturbed areas to infer underlying connectivity and its changes. Less has been indicated in direct measures of functional connectivity and/or neural network and on how connectivity/network alterations occur. Here, we developed a novel analysis framework to directly investigate both neural activity and connectivity changes induced by rTMS from resting-state EEG (rsEEG) acquired in a group of subjects with a chronic disorder of imbalance, known as the mal de debarquement syndrome (MdDS). Resting-state activity in multiple functional brain areas was identified through a data-driven blind source separation analysis on rsEEG data, and the connectivity among them was characterized using a phase synchronization measure. Our study revealed that there were significant long-lasting changes in resting-state neural activity, in theta, low alpha, and high alpha bands and neural networks in theta, low alpha, high alpha and beta bands, over broad cortical areas 4 to 5 h after the last application of rTMS in a consecutive five-day protocol. Our results of rsEEG connectivity further indicated that the changes, mainly in the alpha band, over the parietal and occipital cortices from pre- to post-TMS sessions were significantly correlated, in both magnitude and direction, to symptom changes in this group of subjects with MdDS. This connectivity measure not only suggested that rTMS can generate positive treatment effects in MdDS patients, but also revealed new potential targets for future therapeutic trials to improve treatment effects. It is promising that the new connectivity measure

Single-trial log transformation is optimal in frequency analysis of resting EEG alpha.

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Smulders, Fren T Y; Ten Oever, Sanne; Donkers, Franc C L; Quaedflieg, Conny W E M; van de Ven, Vincent

2018-02-01

The appropriate definition and scaling of the magnitude of electroencephalogram (EEG) oscillations is an underdeveloped area. The aim of this study was to optimize the analysis of resting EEG alpha magnitude, focusing on alpha peak frequency and nonlinear transformation of alpha power. A family of nonlinear transforms, Box-Cox transforms, were applied to find the transform that (a) maximized a non-disputed effect: the increase in alpha magnitude when the eyes are closed (Berger effect), and (b) made the distribution of alpha magnitude closest to normal across epochs within each participant, or across participants. The transformations were performed either at the single epoch level or at the epoch-average level. Alpha peak frequency showed large individual differences, yet good correspondence between various ways to estimate it in 2 min of eyes-closed and 2 min of eyes-open resting EEG data. Both alpha magnitude and the Berger effect were larger for individual alpha than for a generic (8-12 Hz) alpha band. The log-transform on single epochs (a) maximized the t-value of the contrast between the eyes-open and eyes-closed conditions when tested within each participant, and (b) rendered near-normally distributed alpha power across epochs and participants, thereby making further transformation of epoch averages superfluous. The results suggest that the log-normal distribution is a fundamental property of variations in alpha power across time in the order of seconds. Moreover, effects on alpha power appear to be multiplicative rather than additive. These findings support the use of the log-transform on single epochs to achieve appropriate scaling of alpha magnitude. © 2018 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

The association between high levels of cumulative life stress and aberrant resting state EEG dynamics in old age.

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Marshall, Amanda C; Cooper, Nicholas R

2017-07-01

Cumulative experienced stress produces shortcomings in old adults' cognitive performance. These are reflected in electrophysiological changes tied to task execution. This study explored whether stress-related aberrations in older adults' electroencephalographic (EEG) activity were also apparent in the system at rest. To this effect, the amount of stressful life events experienced by 60 young and 60 elderly participants were assessed in conjunction with resting state power changes in the delta, theta, alpha, and beta frequencies during a resting EEG recording. Findings revealed elevated levels of delta power among elderly individuals reporting high levels of cumulative life stress. These differed significantly from young high and low stress individuals and old adults with low levels of stress. Increases of delta activity have been linked to the emergence of conditions such as Alzheimer's Disease and Mild Cognitive Impairment. Thus, a potential interpretation of our findings associates large amounts of cumulative stress with an increased risk of developing age-related cognitive pathologies in later life. Copyright © 2017 Elsevier B.V. All rights reserved.

Classification of single normal and Alzheimer’s disease individuals from cortical sources of resting state EEG rhythms

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Claudio eBabiloni

2016-02-01

Full Text Available Previous studies have shown abnormal power and functional connectivity of resting state electroencephalographic (EEG rhythms in groups of Alzheimer’s disease (AD compared to healthy elderly (Nold subjects. Here we tested the best classification rate of 120 AD patients and 100 matched Nold subjects using EEG markers based on cortical sources of power and functional connectivity of these rhythms. EEG data were recorded during resting state eyes-closed condition. Exact low-resolution brain electromagnetic tomography (eLORETA estimated the power and functional connectivity of cortical sources in frontal, central, parietal, occipital, temporal, and limbic regions. Delta (2-4 Hz, theta (4-8 Hz, alpha 1 (8-10.5 Hz, alpha 2 (10.5-13 Hz, beta 1 (13-20 Hz, beta 2 (20-30 Hz, and gamma (30-40 Hz were the frequency bands of interest. The classification rates of interest were those with an area under the receiver operating characteristic curve (AUROC higher than 0.7 as a threshold for a moderate classification rate (i.e. 70%. Results showed that the following EEG markers overcame this threshold: (i central, parietal, occipital, temporal, and limbic delta/alpha 1 current density; (ii central, parietal, occipital temporal, and limbic delta/alpha 2 current density; (iii frontal theta/alpha 1 current density; (iv occipital delta/alpha 1 inter-hemispherical connectivity; (v occipital-temporal theta/alpha 1 right and left intra-hemispherical connectivity; and (vi parietal-limbic alpha 1 right intra-hemispherical connectivity. Occipital delta/alpha 1 current density showed the best classification rate (sensitivity of 73.3%, specificity of 78%, accuracy of 75.5%, and AUROC of 82%. These results suggest that EEG source markers can classify Nold and AD individuals with a moderate classification rate higher than 80%.

Changes in Resting EEG in Colombian Ex-combatants ith Antisocial Personality Disorder.

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Ramos, Claudia; Duque-Grajales, Jon; Rendón, Jorge; Montoya-Betancur, Alejandro; Baena, Ana; Pineda, David; Tobón, Carlos

Although the social and economic consequences of Colombian internal conflicts mainly affected the civilian population, they also had other implications. The ex-combatants, the other side of the conflict, have been the subject of many studies that question their personality structures and antisocial features. Results suggest that ex-combatants usually have characteristics of an antisocial personality disorder (ASPD) that is related with their behaviour. Quantitative EEG (qEEG) was used to evaluate differences in cortical activity patterns between an ex-combatants group and a control group. The Psychopathy Checklist-Revised (PCL-R) was used to assess the presence of ASPD in the ex-combatants group, as well as the Diagnostic Interview for Genetic Studies (DIGS) for other mental disorders classified in the DCI-10. There are significant differences in psychopathy levels between groups, as well as in alpha-2 and beta waves, especially in left temporal and frontal areas for alpha-2 waves and left temporal-central regions for beta waves. qEEG measurements allow spectral resting potential to be differentiated between groups that are related with features typically involved in antisocial personality disorder, and to correlate them with patterns in the questionnaires and clinical interview. Copyright © 2017 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Resting-state EEG delta power is associated with psychological pain in adults with a history of depression.

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Meerwijk, Esther L; Ford, Judith M; Weiss, Sandra J

2015-02-01

Psychological pain is a prominent symptom of clinical depression. We asked if frontal alpha asymmetry, frontal EEG power, and frontal fractal dimension asymmetry predicted psychological pain in adults with a history of depression. Resting-state frontal EEG (F3/F4) was recorded while participants (N=35) sat upright with their eyes closed. Frontal delta power predicted psychological pain while controlling for depressive symptoms, with participants who exhibited less power experiencing greater psychological pain. Frontal fractal dimension asymmetry, a nonlinear measure of complexity, also predicted psychological pain, such that greater left than right complexity was associated with greater psychological pain. Frontal alpha asymmetry did not contribute unique variance to any regression model of psychological pain. As resting-state delta power is associated with the brain's default mode network, results suggest that the default mode network was less activated during high psychological pain. Findings are consistent with a state of arousal associated with psychological pain. Copyright © 2015 Elsevier B.V. All rights reserved.

EEG-MEG Integration Enhances the Characterization of Functional and Effective Connectivity in the Resting State Network

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Mideksa, Kidist Gebremariam; Anwar, Abdul Rauf; Stephani, Ulrich; Deuschl, Günther; Freitag, Christine M.; Siniatchkin, Michael

2015-01-01

At the sensor level many aspects, such as spectral power, functional and effective connectivity as well as relative-power-ratio ratio (RPR) and spatial resolution have been comprehensively investigated through both electroencephalography (EEG) and magnetoencephalography (MEG). Despite this, differences between both modalities have not yet been systematically studied by direct comparison. It remains an open question as to whether the integration of EEG and MEG data would improve the information obtained from the above mentioned parameters. Here, EEG (64-channel system) and MEG (275 sensor system) were recorded simultaneously in conditions with eyes open (EO) and eyes closed (EC) in 29 healthy adults. Spectral power, functional and effective connectivity, RPR, and spatial resolution were analyzed at five different frequency bands (delta, theta, alpha, beta and gamma). Networks of functional and effective connectivity were described using a spatial filter approach called the dynamic imaging of coherent sources (DICS) followed by the renormalized partial directed coherence (RPDC). Absolute mean power at the sensor level was significantly higher in EEG than in MEG data in both EO and EC conditions. At the source level, there was a trend towards a better performance of the combined EEG+MEG analysis compared with separate EEG or MEG analyses for the source mean power, functional correlation, effective connectivity for both EO and EC. The network of coherent sources and the spatial resolution were similar for both the EEG and MEG data if they were analyzed separately. Results indicate that the combined approach has several advantages over the separate analyses of both EEG and MEG. Moreover, by a direct comparison of EEG and MEG, EEG was characterized by significantly higher values in all measured parameters in both sensor and source level. All the above conclusions are specific to the resting state task and the specific analysis used in this study to have general

When frequencies never synchronize: the golden mean and the resting EEG.

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Pletzer, Belinda; Kerschbaum, Hubert; Klimesch, Wolfgang

2010-06-04

The classical frequency bands of the EEG can be described as a geometric series with a ratio (between neighbouring frequencies) of 1.618, which is the golden mean. Here we show that a synchronization of the excitatory phases of two oscillations with frequencies f1 and f2 is impossible (in a mathematical sense) when their ratio equals the golden mean, because their excitatory phases never meet. Thus, in a mathematical sense, the golden mean provides a totally uncoupled ('desynchronized') processing state which most likely reflects a 'resting' brain, which is not involved in selective information processing. However, excitatory phases of the f1- and f2-oscillations occasionally come close enough to coincide in a physiological sense. These coincidences are more frequent, the higher the frequencies f1 and f2. We demonstrate that the pattern of excitatory phase meetings provided by the golden mean as the 'most irrational' number is least frequent and most irregular. Thus, in a physiological sense, the golden mean provides (i) the highest physiologically possible desynchronized state in the resting brain, (ii) the possibility for spontaneous and most irregular (!) coupling and uncoupling between rhythms and (iii) the opportunity for a transition from resting state to activity. These characteristics have already been discussed to lay the ground for a healthy interplay between various physiological processes (Buchmann, 2002). Copyright 2010 Elsevier B.V. All rights reserved.

Genetic variability in the human cannabinoid receptor 1 is associated with resting state EEG theta power in humans.

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Heitland, I; Kenemans, J L; Böcker, K B E; Baas, J M P

2014-11-01

It has long been postulated that exogenous cannabinoids have a profound effect on human cognitive functioning. These cannabinoid effects are thought to depend, at least in parts, on alterations of phase-locking of local field potential neuronal firing. The latter can be measured as activity in the theta frequency band (4-7Hz) by electroencephalogram. Theta oscillations are supposed to serve as a mechanism in neural representations of behaviorally relevant information. However, it remains unknown whether variability in endogenous cannabinoid activity is involved in theta rhythms and therefore, may serve as an individual differences index of human cognitive functioning. To clarify this issue, we recorded resting state EEG activity in 164 healthy human subjects and extracted EEG power across frequency bands (δ, θ, α, and β). To assess variability in the endocannabinoid system, two genetic polymorphisms (rs1049353, rs2180619) within the cannabinoid receptor 1 (CB1) were determined in all participants. As expected, we observed significant effects of rs1049353 on EEG power in the theta band at frontal, central and parietal electrode regions. Crucially, these effects were specific for the theta band, with no effects on activity in the other frequency bands. Rs2180619 showed no significant associations with theta power after Bonferroni correction. Taken together, we provide novel evidence in humans showing that genetic variability in the cannabinoid receptor 1 is associated with resting state EEG power in the theta frequency band. This extends prior findings of exogenous cannabinoid effects on theta power to the endogenous cannabinoid system. Copyright © 2014 Elsevier B.V. All rights reserved.

EEG Brain Wave Activity at Rest and during Evoked Attention in Children with Attention-Deficit/Hyperactivity Disorder and Effects of Methylphenidate.

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Thomas, Bianca Lee; Viljoen, Margaretha

2016-01-01

The aim of this study was to assess baseline EEG brain wave activity in children with attention-deficit/hyperactivity disorder (ADHD) and to examine the effects of evoked attention and methylphenidate on this activity. Children with ADHD (n = 19) were tested while they were stimulant free and during a period in which they were on stimulant (methylphenidate) medication. Control subjects (n = 18) were tested once. EEG brain wave activity was tested both at baseline and during focussed attention. Attention was evoked and EEG brain wave activity was determined by means of the BioGraph Infiniti biofeedback apparatus. The main finding of this study was that control subjects and stimulant-free children with ADHD exhibited the expected reactivity in high alpha-wave activity (11-12 Hz) from baseline to focussed attention; however, methylphenidate appeared to abolish this reactivity. Methylphenidate attenuates the normal cortical response to a cognitive challenge. © 2016 S. Karger AG, Basel.

Age-related Multiscale Changes in Brain Signal Variability in Pre-task versus Post-task Resting-state EEG.

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Wang, Hongye; McIntosh, Anthony R; Kovacevic, Natasa; Karachalios, Maria; Protzner, Andrea B

2016-07-01

Recent empirical work suggests that, during healthy aging, the variability of network dynamics changes during task performance. Such variability appears to reflect the spontaneous formation and dissolution of different functional networks. We sought to extend these observations into resting-state dynamics. We recorded EEG in young, middle-aged, and older adults during a "rest-task-rest" design and investigated if aging modifies the interaction between resting-state activity and external stimulus-induced activity. Using multiscale entropy as our measure of variability, we found that, with increasing age, resting-state dynamics shifts from distributed to more local neural processing, especially at posterior sources. In the young group, resting-state dynamics also changed from pre- to post-task, where fine-scale entropy increased in task-positive regions and coarse-scale entropy increased in the posterior cingulate, a key region associated with the default mode network. Lastly, pre- and post-task resting-state dynamics were linked to performance on the intervening task for all age groups, but this relationship became weaker with increasing age. Our results suggest that age-related changes in resting-state dynamics occur across different spatial and temporal scales and have consequences for information processing capacity.

An Investigation of Stimulant Effects on the EEG of Children With Attention-Deficit/Hyperactivity Disorder.

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Clarke, Adam R; Barry, Robert J; Baker, Iris E; McCarthy, Rory; Selikowitz, Mark

2017-07-01

Stimulant medications are the most commonly prescribed treatment for Attention-Deficit/Hyperactivity Disorder (AD/HD). These medications result in a normalization of the EEG. However, past research has found that complete normalization of the EEG is not always achieved. One reason for this may be that studies have used different medications interchangeably, or groups of subjects on different stimulants. This study investigated whether methylphenidate and dexamphetamine produce different levels of normalization of the EEG in children with AD/HD. Three groups of 20 boys participated in this study. There were 2 groups with a diagnosis of AD/HD; one group, good responders to methylphenidate, and the second, good responders to dexamphetamine. The third group was a normal control group. Baseline EEGs were recorded using an eyes-closed resting condition, and analyzed for total power and relative delta, theta, alpha, and beta. Subjects were placed on a 6-month trial of methylphenidate or dexamphetamine, after which a second EEG was recorded. At baseline, the children with AD/HD had elevated relative theta, less relative alpha and beta compared with controls. Baseline differences were found between the two medication groups, with the dexamphetamine group having greater EEG abnormalities than the methylphenidate group. The results indicate that good responders to methylphenidate and dexamphetamine have different EEG profiles when assessed before medication, and these differences may represent different underlying central nervous system deficits. The 2 medications were found to result in substantial normalization of the EEG, with no significant differences in EEG changes occurring between the 2 medications. This indicates that the degree of pretreatment EEG abnormality was the major factor contributing to the degree of normalization of the EEG. As good responders to the 2 medications appear to have different central nervous system abnormalities, it is recommended that

Infraslow Electroencephalographic and Dynamic Resting State Network Activity.

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Grooms, Joshua K; Thompson, Garth J; Pan, Wen-Ju; Billings, Jacob; Schumacher, Eric H; Epstein, Charles M; Keilholz, Shella D

2017-06-01

A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies.

How motor, cognitive and musical expertise shapes the brain: Focus on fMRI and EEG resting-state functional connectivity

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Cantou, Pauline; Platel, Hervé; Desgranges, Béatrice

2017-01-01

about functional cerebral reorganization due to expertise at the whole-brain level and might facilitate comparison across studies. Resting-state functional MRI and EEG makes it possible to explore the functional traces of expertise in the brain by measuring temporal correlations of blood oxygen level......, to determine whether there is a domain-specific neural signature of expertise. After highlighting expertise-related changes within resting-state networks for each domain, we discuss their specificity to the trained activity and the methodological considerations concerning different conditions and analyses used......-dependent (BOLD) and spontaneous neural activity fluctuations at rest. Since these correlations are thought to reflect a prior history co-activation of brain regions, we propose reviewing studies that focused on the effects of expertise in the motor, cognitive and musical domains on brain plasticity at rest...

EEG resting state functional connectivity analysis in children with benign epilepsy with centrotemporal spikes

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Azeez eAdebimpe

2016-03-01

Full Text Available In this study, we investigated changes in functional connectivity of the brain networks in patients with benign epilepsy with centrotemporal spikes compared to healthy controls using high-density EEG data collected under eyes-closed resting state condition. EEG source reconstruction was performed with exact Low Resolution Electromagnetic Tomography (eLORETA. We investigated functional connectivity (FC between 84 Brodmann areas using lagged phase synchronization (LPS in four frequency bands (δ, θ, α, and β. We further computed the network degree, clustering coefficient and efficiency. Compared to controls, patients displayed higher θ and α and lower β lagged phase synchronization values. In these frequency bands, patients were also characterized by less well ordered brain networks exhibiting higher global degrees and efficiencies and lower clustering coefficients. In the beta band, patients exhibited reduced functional segregation and integration due to loss of both local and long-distance functional connections. These findings suggest that benign epileptic brain networks might be functionally disrupted due to their altered functional organization especially in the α and β frequency bands.

Investigation of True High Frequency Electrical Substrates of fMRI-Based Resting State Networks Using Parallel Independent Component Analysis of Simultaneous EEG/fMRI Data.

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Kyathanahally, Sreenath P; Wang, Yun; Calhoun, Vince D; Deshpande, Gopikrishna

2017-01-01

Previous work using simultaneously acquired electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data has shown that the slow temporal dynamics of resting state brain networks (RSNs), e.g., default mode network (DMN), visual network (VN), obtained from fMRI are correlated with smoothed and down sampled versions of various EEG features such as microstates and band-limited power envelopes. Therefore, even though the down sampled and smoothed envelope of EEG gamma band power is correlated with fMRI fluctuations in the RSNs, it does not mean that the electrical substrates of the RSNs fluctuate with periods state fMRI fluctuations in the RSNs, researchers have speculated that truly high frequency electrical substrates may exist for the RSNs, which would make resting fluctuations obtained from fMRI more meaningful to typically occurring fast neuronal processes in the sub-100 ms time scale. In this study, we test this critical hypothesis using an integrated framework involving simultaneous EEG/fMRI acquisition, fast fMRI sampling ( TR = 200 ms) using multiband EPI (MB EPI), and EEG/fMRI fusion using parallel independent component analysis (pICA) which does not require the down sampling of EEG to fMRI temporal resolution . Our results demonstrate that with faster sampling, high frequency electrical substrates (fluctuating with periods <100 ms time scale) of the RSNs can be observed. This provides a sounder neurophysiological basis for the RSNs.

Brain electric correlates of strong belief in paranormal phenomena: intracerebral EEG source and regional Omega complexity analyses.

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Pizzagalli, D; Lehmann, D; Gianotti, L; Koenig, T; Tanaka, H; Wackermann, J; Brugger, P

2000-12-22

The neurocognitive processes underlying the formation and maintenance of paranormal beliefs are important for understanding schizotypal ideation. Behavioral studies indicated that both schizotypal and paranormal ideation are based on an overreliance on the right hemisphere, whose coarse rather than focussed semantic processing may favor the emergence of 'loose' and 'uncommon' associations. To elucidate the electrophysiological basis of these behavioral observations, 35-channel resting EEG was recorded in pre-screened female strong believers and disbelievers during resting baseline. EEG data were subjected to FFT-Dipole-Approximation analysis, a reference-free frequency-domain dipole source modeling, and Regional (hemispheric) Omega Complexity analysis, a linear approach estimating the complexity of the trajectories of momentary EEG map series in state space. Compared to disbelievers, believers showed: more right-located sources of the beta2 band (18.5-21 Hz, excitatory activity); reduced interhemispheric differences in Omega complexity values; higher scores on the Magical Ideation scale; more general negative affect; and more hypnagogic-like reveries after a 4-min eyes-closed resting period. Thus, subjects differing in their declared paranormal belief displayed different active, cerebral neural populations during resting, task-free conditions. As hypothesized, believers showed relatively higher right hemispheric activation and reduced hemispheric asymmetry of functional complexity. These markers may constitute the neurophysiological basis for paranormal and schizotypal ideation.

EEG classification for motor imagery and resting state in BCI applications using multi-class Adaboost extreme learning machine

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Gao, Lin; Cheng, Wei; Zhang, Jinhua; Wang, Jue

2016-08-01

Brain-computer interface (BCI) systems provide an alternative communication and control approach for people with limited motor function. Therefore, the feature extraction and classification approach should differentiate the relative unusual state of motion intention from a common resting state. In this paper, we sought a novel approach for multi-class classification in BCI applications. We collected electroencephalographic (EEG) signals registered by electrodes placed over the scalp during left hand motor imagery, right hand motor imagery, and resting state for ten healthy human subjects. We proposed using the Kolmogorov complexity (Kc) for feature extraction and a multi-class Adaboost classifier with extreme learning machine as base classifier for classification, in order to classify the three-class EEG samples. An average classification accuracy of 79.5% was obtained for ten subjects, which greatly outperformed commonly used approaches. Thus, it is concluded that the proposed method could improve the performance for classification of motor imagery tasks for multi-class samples. It could be applied in further studies to generate the control commands to initiate the movement of a robotic exoskeleton or orthosis, which finally facilitates the rehabilitation of disabled people.

Schizophrenia patients and 22q11.2 deletion syndrome adolescents at risk express the same deviant patterns of resting state EEG microstates: A candidate endophenotype of schizophrenia

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Miralena I. Tomescu

2015-09-01

Full Text Available Schizophrenia is a complex psychiatric disorder and many of the factors contributing to its pathogenesis are poorly understood. In addition, identifying reliable neurophysiological markers would improve diagnosis and early identification of this disease. The 22q11.2 deletion syndrome (22q11DS is one major risk factor for schizophrenia. Here, we show further evidence that deviant temporal dynamics of EEG microstates are a potential neurophysiological marker by showing that the resting state patterns of 22q11DS are similar to those found in schizophrenia patients. The EEG microstates are recurrent topographic distributions of the ongoing scalp potential fields with temporal stability of around 80 ms that are mapping the fast reconfiguration of resting state networks. Five minutes of high-density EEG recordings was analysed from 27 adult chronic schizophrenia patients, 27 adult controls, 30 adolescents with 22q11DS, and 28 adolescent controls. In both patient groups we found increased class C, but decreased class D presence and high transition probabilities towards the class C microstates. Moreover, these aberrant temporal dynamics in the two patient groups were also expressed by perturbations of the long-range dependency of the EEG microstates. These findings point to a deficient function of the salience and attention resting state networks in schizophrenia and 22q11DS as class C and class D microstates were previously associated with these networks, respectively. These findings elucidate similarities between individuals at risk and schizophrenia patients and support the notion that abnormal temporal patterns of EEG microstates might constitute a marker for developing schizophrenia.

Test-retest reliability of cognitive EEG

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McEvoy, L. K.; Smith, M. E.; Gevins, A.

2000-01-01

OBJECTIVE: Task-related EEG is sensitive to changes in cognitive state produced by increased task difficulty and by transient impairment. If task-related EEG has high test-retest reliability, it could be used as part of a clinical test to assess changes in cognitive function. The aim of this study was to determine the reliability of the EEG recorded during the performance of a working memory (WM) task and a psychomotor vigilance task (PVT). METHODS: EEG was recorded while subjects rested quietly and while they performed the tasks. Within session (test-retest interval of approximately 1 h) and between session (test-retest interval of approximately 7 days) reliability was calculated for four EEG components: frontal midline theta at Fz, posterior theta at Pz, and slow and fast alpha at Pz. RESULTS: Task-related EEG was highly reliable within and between sessions (r0.9 for all components in WM task, and r0.8 for all components in the PVT). Resting EEG also showed high reliability, although the magnitude of the correlation was somewhat smaller than that of the task-related EEG (r0.7 for all 4 components). CONCLUSIONS: These results suggest that under appropriate conditions, task-related EEG has sufficient retest reliability for use in assessing clinical changes in cognitive status.

[EEG alpha indices in dependence on the menstrual cycle phase and salivary progesterone].

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Bazanova, O M; Kondratenko, A V; Kuz'minova, O I; Muravleva, K B; Petrova, S E

2014-01-01

The effects of the neurohumoral status on the EEG alpha - activity indices were studied in a within-subject design with 78 women aged 18-27 years during 1-2 menstrual cycle. Psychometric and EEG indices of alpha waves basal body temperature, saliva progesterone and cortisol level were monitored every 2-3 days. Menstrual and follicular recording sessions occurred before the ovulatory temperature rise, luteal recording session--after increasing progesterone level more than 20% respect to previous day and premenstrual sessions after decreasing progesterone level more that 20% respect to previous day. The design consisted of rest and task periods EEG, EMG and ECG recordings. Half the subjects began during their menstrual phase and half began during their luteal phase. All 5 phases were compared for differences between psychometric features EEG alpha activity, EMG and ECG baseline resting levels, as well as for reactivity to cognitive task. The results showed menstrual phase differences in all psychometric and alpha EEG indices. The cognitive fluency, alpha peak frequency, alpha band width, power in alpha-2 frequency range are maximal at luteal, alpha visual activation and reactivity to cognitive task performance--at follicular phase. The hypothesis that the EEG alpha activity depends on the hormonal status supported by the positive association salivary progesterone level with the alpha peak frequency, power in the alpha-2 band and negative--with the power of the alpha-1 band. According these results, we conclude that psycho-physiological recording sessions with women might be provided with a glance to phase of menstrual cycle.

Abnormal baseline brain activity in patients with neuromyelitis optica: A resting-state fMRI study

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Liu Yaou; Liang Peipeng; Duan Yunyun; Jia Xiuqin; Wang Fei; Yu Chunshui; Qin Wen; Dong Huiqing; Ye Jing; Li Kuncheng

2011-01-01

Purpose: Recent immunopathologic and MRI findings suggest that tissue damage in neuromyelitis optica (NMO) is not limited to spinal cord and optic nerve, but also in brain. Baseline brain activity can reveal the brain functional changes to the tissue damages and give clues to the pathophysiology of NMO, however, it has never been explored by resting-state functional MRI (fMRI). We used regional amplitude of low frequency fluctuation (ALFF) as an index in resting-state fMRI to investigate how baseline brain activity changes in patients with NMO. Methods: Resting-state fMRIs collected from seventeen NMO patients and seventeen age- and sex-matched normal controls were compared to investigate the ALFF difference between the two groups. The relationships between ALFF in regions with significant group differences and the EDSS (Expanded Disability Status Scale), disease duration were further explored. Results: Our results showed that NMO patients had significantly decreased ALFF in precuneus, posterior cingulate cortex (PCC) and lingual gyrus; and increased ALFF in middle frontal gyrus, caudate nucleus and thalamus, compared to normal controls. Moderate negative correlations were found between the EDSS and ALFF in the left middle frontal gyrus (r = -0.436, p = 0.040) and the left caudate (r = -0.542, p = 0.012). Conclusion: The abnormal baseline brain activity shown by resting-state fMRI in NMO is relevant to cognition, visual and motor systems. It implicates a complex baseline brain status of both functional impairments and adaptations caused by tissue damages in these systems, which gives clues to the pathophysiology of NMO.

Abnormal baseline brain activity in patients with neuromyelitis optica: A resting-state fMRI study

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Liu Yaou [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); Liang Peipeng [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); International WIC institute, Beijing University of Technology, Beijing 100024 (China); Duan Yunyun; Jia Xiuqin; Wang Fei; Yu Chunshui; Qin Wen [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); Dong Huiqing; Ye Jing [Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); Li Kuncheng, E-mail: likuncheng1955@yahoo.com.cn [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China)

2011-11-15

Purpose: Recent immunopathologic and MRI findings suggest that tissue damage in neuromyelitis optica (NMO) is not limited to spinal cord and optic nerve, but also in brain. Baseline brain activity can reveal the brain functional changes to the tissue damages and give clues to the pathophysiology of NMO, however, it has never been explored by resting-state functional MRI (fMRI). We used regional amplitude of low frequency fluctuation (ALFF) as an index in resting-state fMRI to investigate how baseline brain activity changes in patients with NMO. Methods: Resting-state fMRIs collected from seventeen NMO patients and seventeen age- and sex-matched normal controls were compared to investigate the ALFF difference between the two groups. The relationships between ALFF in regions with significant group differences and the EDSS (Expanded Disability Status Scale), disease duration were further explored. Results: Our results showed that NMO patients had significantly decreased ALFF in precuneus, posterior cingulate cortex (PCC) and lingual gyrus; and increased ALFF in middle frontal gyrus, caudate nucleus and thalamus, compared to normal controls. Moderate negative correlations were found between the EDSS and ALFF in the left middle frontal gyrus (r = -0.436, p = 0.040) and the left caudate (r = -0.542, p = 0.012). Conclusion: The abnormal baseline brain activity shown by resting-state fMRI in NMO is relevant to cognition, visual and motor systems. It implicates a complex baseline brain status of both functional impairments and adaptations caused by tissue damages in these systems, which gives clues to the pathophysiology of NMO.

Temporal lobe deficits in murderers: EEG findings undetected by PET.

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Gatzke-Kopp, L M; Raine, A; Buchsbaum, M; LaCasse, L

2001-01-01

This study evaluates electroencephalography (EEG) and positron emission tomography (PET) in the same subjects. Fourteen murderers were assessed by using both PET (while they were performing the continuous performance task) and EEG during a resting state. EEG revealed significant increases in slow-wave activity in the temporal, but not frontal, lobe in murderers, in contrast to prior PET findings that showed reduced prefrontal, but not temporal, glucose metabolism. Results suggest that resting EEG shows empirical utility distinct from PET activation findings.

Developmental trajectories of resting EEG power: an endophenotype of autism spectrum disorder.

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Adrienne L Tierney

Full Text Available Current research suggests that autism spectrum disorder (ASD is characterized by asynchronous neural oscillations. However, it is unclear whether changes in neural oscillations represent an index of the disorder or are shared more broadly among both affected and unaffected family members. Additionally, it remains unclear how early these differences emerge in development and whether they remain constant or change over time. In this study we examined developmental trajectories in spectral power in infants at high- or low-risk for ASD. Spectral power was extracted from resting EEG recorded over frontal regions of the scalp when infants were 6, 9, 12, 18 and 24 months of age. We used multilevel modeling to assess change over time between risk groups in the delta, theta, low alpha, high alpha, beta, and gamma frequency bands. The results indicated that across all bands, spectral power was lower in high-risk infants as compared to low-risk infants at 6-months of age. Furthermore high-risk infants showed different trajectories of change in spectral power in the subsequent developmental window indicating that not only are the patterns of change different, but that group differences are dynamic within the first two years of life. These findings remained the same after removing data from a subset of participants who displayed ASD related behaviors at 24 or 36 months. These differences in the nature of the trajectories of EEG power represent important endophenotypes of ASD.

A baseline for the multivariate comparison of resting state networks

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Elena A Allen

2011-02-01

Full Text Available As the size of functional and structural MRI datasets expands, it becomes increasingly important to establish a baseline from which diagnostic relevance may be determined, a processing strategy that efficiently prepares data for analysis, and a statistical approach that identifies important effects in a manner that is both robust and reproducible. In this paper, we introduce a multivariate analytic approach that optimizes sensitivity and reduces unnecessary testing. We demonstrate the utility of this mega-analytic approach by identifying the effects of age and gender on the resting state networks of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12 to 71 years. Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. Resting state networks were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described here, provide a useful baseline for future investigations of brain networks in health and disease.

Deviant dynamics of EEG resting state pattern in 22q11.2 deletion syndrome adolescents: A vulnerability marker of schizophrenia?

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Tomescu, Miralena I; Rihs, Tonia A; Becker, Robert; Britz, Juliane; Custo, Anna; Grouiller, Frédéric; Schneider, Maude; Debbané, Martin; Eliez, Stephan; Michel, Christoph M

2014-08-01

Previous studies have repeatedly found altered temporal characteristics of EEG microstates in schizophrenia. The aim of the present study was to investigate whether adolescents affected by the 22q11.2 deletion syndrome (22q11DS), known to have a 30 fold increased risk to develop schizophrenia, already show deviant EEG microstates. If this is the case, temporal alterations of EEG microstates in 22q11DS individuals could be considered as potential biomarkers for schizophrenia. We used high-density (204 channel) EEG to explore between-group microstate differences in 30 adolescents with 22q11DS and 28 age-matched controls. We found an increased presence of one microstate class (class C) in the 22q11DS adolescents with respect to controls that was associated with positive prodromal symptoms (hallucinations). A previous across-age study showed that the class C microstate was more present during adolescence and a combined EEG-fMRI study associated the class C microstate with the salience resting state network, a network known to be dysfunctional in schizophrenia. Therefore, the increased class C microstates could be indexing the increased risk of 22q11DS individuals to develop schizophrenia if confirmed by our ongoing longitudinal study comparing both the adult 22q11DS individuals with and without schizophrenia, as well as schizophrenic individuals with and without 22q11DS. Copyright © 2014 Elsevier B.V. All rights reserved.

Is 1/f sound more effective than simple resting in reducing stress response?

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Oh, Eun-Joo; Cho, Il-Young; Park, Soon-Kwon

2014-01-01

It has been previously demonstrated that listening to 1/f sound effectively reduces stress. However, these findings have been inconsistent and further study on the relationship between 1/f sound and the stress response is consequently necessary. The present study examined whether sound with 1/f properties (1/f sound) affects stress-induced electroencephalogram (EEG) changes. Twenty-six subjects who voluntarily participated in the study were randomly assigned to the experimental or control group. Data from four participants were excluded because of EEG artifacts. A mental arithmetic task was used as a stressor. Participants in the experiment group listened to 1/f sound for 5 minutes and 33 seconds, while participants in the control group sat quietly for the same duration. EEG recordings were obtained at various points throughout the experiment. After the experiment, participants completed a questionnaire on the affective impact of the 1/f sound. The results indicated that the mental arithmetic task effectively induced a stress response measurable by EEG. Relative theta power at all electrode sites was significantly lower than baseline in both the control and experimental group. Relative alpha power was significantly lower, and relative beta power was significantly higher in the T3 and T4 areas. Secondly, 1/f sound and simple resting affected task-associated EEG changes in a similar manner. Finally, participants reported in the questionnaire that they experienced a positive feeling in response to the 1/f sound. Our results suggest that a commercialized 1/f sound product is not more effective than simple resting in alleviating the physiological stress response.

Age-Related Changes in Resting-State EEG Activity in Attention Deficit/Hyperactivity Disorder: A Cross-Sectional Study

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Katarzyna Giertuga

2017-05-01

Full Text Available Numerous studies indicate that attention deficit/hyperactivity disorder (ADHD is related to some developmental trends, as its symptoms change widely over time. Nevertheless, the etiology of this phenomenon remains ambiguous. There is a disagreement whether ADHD is related to deviations in brain development or to a delay in brain maturation. The model of deviated brain development suggests that the ADHD brain matures in a fundamentally different way, and does not reach normal maturity at any developmental stage. On the contrary, the delayed brain maturation model assumes that the ADHD brain indeed matures in a different, delayed way in comparison to healthy age-matched controls, yet eventually reaches proper maturation. We investigated age-related changes in resting-state EEG activity to find evidence to support one of the alternative models. A total of 141 children and teenagers participated in the study; 67 diagnosed with ADHD and 74 healthy controls. The absolute power of delta, theta, alpha, and beta frequency bands was analyzed. We observed a significant developmental pattern of decreasing absolute EEG power in both groups. Nonetheless, ADHD was characterized by consistently lower absolute EGG power, mostly in the theta frequency band, in comparison to healthy controls. Our results are in line with the deviant brain maturation theory of ADHD, as the observed effects of age-related changes in EEG power are parallel but different in the two groups.

Resting-state theta band connectivity and graph analysis in generalized social anxiety disorder.

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Xing, Mengqi; Tadayonnejad, Reza; MacNamara, Annmarie; Ajilore, Olusola; DiGangi, Julia; Phan, K Luan; Leow, Alex; Klumpp, Heide

2017-01-01

Functional magnetic resonance imaging (fMRI) resting-state studies show generalized social anxiety disorder (gSAD) is associated with disturbances in networks involved in emotion regulation, emotion processing, and perceptual functions, suggesting a network framework is integral to elucidating the pathophysiology of gSAD. However, fMRI does not measure the fast dynamic interconnections of functional networks. Therefore, we examined whole-brain functional connectomics with electroencephalogram (EEG) during resting-state. Resting-state EEG data was recorded for 32 patients with gSAD and 32 demographically-matched healthy controls (HC). Sensor-level connectivity analysis was applied on EEG data by using Weighted Phase Lag Index (WPLI) and graph analysis based on WPLI was used to determine clustering coefficient and characteristic path length to estimate local integration and global segregation of networks. WPLI results showed increased oscillatory midline coherence in the theta frequency band indicating higher connectivity in the gSAD relative to HC group during rest. Additionally, WPLI values positively correlated with state anxiety levels within the gSAD group but not the HC group. Our graph theory based connectomics analysis demonstrated increased clustering coefficient and decreased characteristic path length in theta-based whole brain functional organization in subjects with gSAD compared to HC. Theta-dependent interconnectivity was associated with state anxiety in gSAD and an increase in information processing efficiency in gSAD (compared to controls). Results may represent enhanced baseline self-focused attention, which is consistent with cognitive models of gSAD and fMRI studies implicating emotion dysregulation and disturbances in task negative networks (e.g., default mode network) in gSAD.

The Amsterdam Resting-State Questionnaire reveals multiple phenotypes of resting-state cognition

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Diaz, B. Alexander; Van Der Sluis, Sophie; Moens, Sarah; Benjamins, Jeroen S.; Migliorati, Filippo; Stoffers, Diederick; Den Braber, Anouk; Poil, Simon-Shlomo; Hardstone, Richard; Van't Ent, Dennis; Boomsma, Dorret I.; De Geus, Eco; Mansvelder, Huibert D.; Van Someren, Eus J. W.; Linkenkaer-Hansen, Klaus

2013-01-01

Resting-state neuroimaging is a dominant paradigm for studying brain function in health and disease. It is attractive for clinical research because of its simplicity for patients, straightforward standardization, and sensitivity to brain disorders. Importantly, non-sensory experiences like mind wandering may arise from ongoing brain activity. However, little is known about the link between ongoing brain activity and cognition, as phenotypes of resting-state cognition—and tools to quantify them—have been lacking. To facilitate rapid and structured measurements of resting-state cognition we developed a 50-item self-report survey, the Amsterdam Resting-State Questionnaire (ARSQ). Based on ARSQ data from 813 participants assessed after 5 min eyes-closed rest in their home, we identified seven dimensions of resting-state cognition using factor analysis: Discontinuity of Mind, Theory of Mind, Self, Planning, Sleepiness, Comfort, and Somatic Awareness. Further, we showed that the structure of cognition was similar during resting-state fMRI and EEG, and that the test-retest correlations were remarkably high for all dimensions. To explore whether inter-individual variation of resting-state cognition is related to health status, we correlated ARSQ-derived factor scores with psychometric scales measuring depression, anxiety, and sleep quality. Mental health correlated positively with Comfort and negatively with Discontinuity of Mind. Finally, we show that sleepiness may partially explain a resting-state EEG profile previously associated with Alzheimer's disease. These findings indicate that the ARSQ readily provides information about cognitive phenotypes and that it is a promising tool for research on the neural correlates of resting-state cognition in health and disease. PMID:23964225

The wandering mood: psychological and neural determinants of rest-related negative affect

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Michal eGruberger

2013-12-01

Full Text Available Rest related negative affect (RRNA has gained scientific interest in the past decade. However, it is mostly studied within the context of mind-wandering (MW, and the relevance of other psychological and neural aspects of the resting state to its' occurrence has never been studied. Several indications associate RRNA with internally directed attention, yet the nature of this relation remains largely unknown. Moreover, the role of neural networks associated with rest related phenomenology - the default mode (DMN, executive (EXE and salience (SAL networks, has not been studied in this context. To this end, we explored two 5- (baseline and 15-minute resting-state simultaneous fMRI-EEG scans of 29 participants. As vigilance has been shown to affect attention, and thus its availability for inward allocation, EEG-based vigilance levels were computed for each participant. Questionnaires for affective assessment were administered before and after scans, and retrospective reports of MW were additionally collected. Results revealed increased negative affect following rest, but only among participants who retained high vigilance levels. Among low-vigilance participants, changes in negative affect were negligible, despite reports of MW occurrence in both groups. In addition, in the high-vigilance group only, a significant increase in functional connectivity (FC levels was found between the DMN-related ventral anterior cingulate cortex (ACC,associated with emotional processing, and the EXE-related dorsal ACC, associated with monitoring of self and other's behavior. These heightened FC levels further correlated with reported negative affect among this group. Taken together, these results demonstrate that, rather than an unavoidable outcome of the resting state, RRNA depends on internal allocation of attention at rest. Results are discussed in terms of two rest-related possible scenarios which defer in mental and neural processing, and subsequently, in the

The wandering mood: psychological and neural determinants of rest-related negative affect.

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Gruberger, Michal; Maron-Katz, Adi; Sharon, Haggai; Hendler, Talma; Ben-Simon, Eti

2013-01-01

Rest related negative affect (RRNA) has gained scientific interest in the past decade. However, it is mostly studied within the context of mind-wandering (MW), and the relevance of other psychological and neural aspects of the resting state to its' occurrence has never been studied. Several indications associate RRNA with internally directed attention, yet the nature of this relation remains largely unknown. Moreover, the role of neural networks associated with rest related phenomenology - the default mode (DMN), executive (EXE), and salience (SAL) networks, has not been studied in this context. To this end, we explored two 5 (baseline) and 15-minute resting-state simultaneous fMRI-EEG scans of 29 participants. As vigilance has been shown to affect attention, and thus its availability for inward allocation, EEG-based vigilance levels were computed for each participant. Questionnaires for affective assessment were administered before and after scans, and retrospective reports of MW were additionally collected. Results revealed increased negative affect following rest, but only among participants who retained high vigilance levels. Among low-vigilance participants, changes in negative affect were negligible, despite reports of MW occurrence in both groups. In addition, in the high-vigilance group only, a significant increase in functional connectivity (FC) levels was found between the DMN-related ventral anterior cingulate cortex (ACC), associated with emotional processing, and the EXE-related dorsal ACC, associated with monitoring of self and other's behavior. These heightened FC levels further correlated with reported negative affect among this group. Taken together, these results demonstrate that, rather than an unavoidable outcome of the resting state, RRNA depends on internal allocation of attention at rest. Results are discussed in terms of two rest-related possible scenarios which defer in mental and neural processing, and subsequently, in the occurrence of

The Amsterdam Resting-State Questionnaire reveals multiple phenotypes of resting-state cognition

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B. Alexander eDiaz

2013-08-01

Full Text Available Resting-state neuroimaging is a dominant paradigm for studying brain function in health and disease. It is attractive for clinical research because of its simplicity for patients, straightforward standardization, and sensitivity to brain disorders. Importantly, non-sensory experiences like mind wandering may arise from ongoing brain activity. However, little is known about the link between ongoing brain activity and cognition, as phenotypes of resting-state cognition—and tools to quantify them—have been lacking. To facilitate rapid and structured measurements of resting-state cognition we developed a 50-item self-report survey, the Amsterdam Resting-State Questionnaire (ARSQ. Based on ARSQ data from 813 participants assessed after five minutes eyes-closed rest in their home, we identified seven dimensions of resting-state cognition using factor analysis: Discontinuity of Mind, Theory of Mind, Self, Planning, Sleepiness, Comfort, and Somatic Awareness. Further, we showed that the structure of cognition was similar during resting-state fMRI and EEG, and that the test-retest correlations were remarkably high for all dimensions. To explore whether inter-individual variation of resting-state cognition is related to health status, we correlated ARSQ-derived factor scores with psychometric scales measuring depression, anxiety, and sleep quality. Mental health correlated positively with Comfort and negatively with Discontinuity of Mind. Finally, we show that sleepiness may partially explain a resting-state EEG profile previously associated with Alzheimer’s disease. These findings indicate that the ARSQ readily provides information about cognitive phenotypes and that it is a promising tool for research on the neural correlates of resting-state cognition in health and disease.

EEG current source density and the phenomenology of the default network.

Science.gov (United States)

Cannon, Rex L; Baldwin, Debora R

2012-10-01

In recent years, there has been an increasing line of research dedicated to the investigation of the default mode network (DMN) of the brain and resting state networks. However, the mental activity of the DMN has not been rigorously assessed to date. The specific aims of the current study were 2-fold: First, we sought to determine whether the current source density (CSD) levels in the DMN would correspond to other neuroimaging techniques. Second, we sought to understand the subjective mental activity of the DMN during baseline recordings. This study was conducted with 63 nonclinical participants, 34 female and 29 males with a mean age of 19.2 years (standard deviation = 2.0). The participants were recorded in 8 conditions. First, 4-minute eyes-closed baseline (ECB) and eyes-opened baseline (EOB) were obtained. The participants then completed 3 assessment instruments and 3 image conditions while the electroencephalography (EEG) was continuously recorded. Participants completed subjective reports for baselines and image conditions. These were rated by 3 independent raters and compared for reliability using a random effects model with an absolute agreement definition. The mean CSD between all conditions differed significantly, in many but not all regions of interest in the DMN. Interestingly, as suggested by other studies, the DMN appears preferential to self-relevant, self-specific, or self-perceptive processes. The reliability analyses show α for interrater agreement for ECB at .95 and EOB at .96. The subjective reports obtained from the participants regarding the mental activities employed during baseline recordings correspond to attentional and self-regulatory processes, which may also implicate the resting state or DMN as playing a direct role in the maintenance of a complex behavior (eg, being still, attending, and self-regulating). Thus, attention and self-regulation constitute the phenomenology of the resting state (DMN) in this study. The results also

EEG Suppression Associated with Apneic Episodes in a Neonate

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Evonne Low

2012-01-01

Full Text Available We describe the EEG findings from an ex-preterm neonate at term equivalent age who presented with intermittent but prolonged apneic episodes which were presumed to be seizures. A total of 8 apneic episodes were captured (duration 23–376 seconds during EEG monitoring. The baseline EEG activity was appropriate for corrected gestational age and no electrographic seizure activity was recorded. The average baseline heart rate was 168 beats per minute (bpm and the baseline oxygen saturation level was in the mid-nineties. Periods of complete EEG suppression lasting 68 and 179 seconds, respectively, were recorded during 2 of these 8 apneic episodes. Both episodes were accompanied by bradycardia less than 70 bpm and oxygen saturation levels of less than 20%. Short but severe episodes of apnea can cause complete EEG suppression in the neonate.

Donepezil impairs memory in healthy older subjects: behavioural, EEG and simultaneous EEG/fMRI biomarkers.

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Joshua H Balsters

Full Text Available Rising life expectancies coupled with an increasing awareness of age-related cognitive decline have led to the unwarranted use of psychopharmaceuticals, including acetylcholinesterase inhibitors (AChEIs, by significant numbers of healthy older individuals. This trend has developed despite very limited data regarding the effectiveness of such drugs on non-clinical groups and recent work indicates that AChEIs can have negative cognitive effects in healthy populations. For the first time, we use a combination of EEG and simultaneous EEG/fMRI to examine the effects of a commonly prescribed AChEI (donepezil on cognition in healthy older participants. The short- and long-term impact of donepezil was assessed using two double-blind, placebo-controlled trials. In both cases, we utilised cognitive (paired associates learning (CPAL and electrophysiological measures (resting EEG power that have demonstrated high-sensitivity to age-related cognitive decline. Experiment 1 tested the effects of 5 mg/per day dosage on cognitive and EEG markers at 6-hour, 2-week and 4-week follow-ups. In experiment 2, the same markers were further scrutinised using simultaneous EEG/fMRI after a single 5 mg dose. Experiment 1 found significant negative effects of donepezil on CPAL and resting Alpha and Beta band power. Experiment 2 replicated these results and found additional drug-related increases in the Delta band. EEG/fMRI analyses revealed that these oscillatory differences were associated with activity differences in the left hippocampus (Delta, right frontal-parietal network (Alpha, and default-mode network (Beta. We demonstrate the utility of simple cognitive and EEG measures in evaluating drug responses after acute and chronic donepezil administration. The presentation of previously established markers of age-related cognitive decline indicates that AChEIs can impair cognitive function in healthy older individuals. To our knowledge this is the first study to identify

Mutual information identifies spurious Hurst phenomena in resting state EEG and fMRI data

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von Wegner, Frederic; Laufs, Helmut; Tagliazucchi, Enzo

2018-02-01

Long-range memory in time series is often quantified by the Hurst exponent H , a measure of the signal's variance across several time scales. We analyze neurophysiological time series from electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) resting state experiments with two standard Hurst exponent estimators and with the time-lagged mutual information function applied to discretized versions of the signals. A confidence interval for the mutual information function is obtained from surrogate Markov processes with equilibrium distribution and transition matrix identical to the underlying signal. For EEG signals, we construct an additional mutual information confidence interval from a short-range correlated, tenth-order autoregressive model. We reproduce the previously described Hurst phenomenon (H >0.5 ) in the analytical amplitude of alpha frequency band oscillations, in EEG microstate sequences, and in fMRI signals, but we show that the Hurst phenomenon occurs without long-range memory in the information-theoretical sense. We find that the mutual information function of neurophysiological data behaves differently from fractional Gaussian noise (fGn), for which the Hurst phenomenon is a sufficient condition to prove long-range memory. Two other well-characterized, short-range correlated stochastic processes (Ornstein-Uhlenbeck, Cox-Ingersoll-Ross) also yield H >0.5 , whereas their mutual information functions lie within the Markovian confidence intervals, similar to neural signals. In these processes, which do not have long-range memory by construction, a spurious Hurst phenomenon occurs due to slow relaxation times and heteroscedasticity (time-varying conditional variance). In summary, we find that mutual information correctly distinguishes long-range from short-range dependence in the theoretical and experimental cases discussed. Our results also suggest that the stationary fGn process is not sufficient to describe neural data, which

A Comparative Study of Different EEG Reference Choices for Diagnosing Unipolar Depression.

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Mumtaz, Wajid; Malik, Aamir Saeed

2018-06-02

The choice of an electroencephalogram (EEG) reference has fundamental importance and could be critical during clinical decision-making because an impure EEG reference could falsify the clinical measurements and subsequent inferences. In this research, the suitability of three EEG references was compared while classifying depressed and healthy brains using a machine-learning (ML)-based validation method. In this research, the EEG data of 30 unipolar depressed subjects and 30 age-matched healthy controls were recorded. The EEG data were analyzed in three different EEG references, the link-ear reference (LE), average reference (AR), and reference electrode standardization technique (REST). The EEG-based functional connectivity (FC) was computed. Also, the graph-based measures, such as the distances between nodes, minimum spanning tree, and maximum flow between the nodes for each channel pair, were calculated. An ML scheme provided a mechanism to compare the performances of the extracted features that involved a general framework such as the feature extraction (graph-based theoretic measures), feature selection, classification, and validation. For comparison purposes, the performance metrics such as the classification accuracies, sensitivities, specificities, and F scores were computed. When comparing the three references, the diagnostic accuracy showed better performances during the REST, while the LE and AR showed less discrimination between the two groups. Based on the results, it can be concluded that the choice of appropriate reference is critical during the clinical scenario. The REST reference is recommended for future applications of EEG-based diagnosis of mental illnesses.

Frontal EEG asymmetry in borderline personality disorder is associated with alexithymia.

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Flasbeck, Vera; Popkirov, Stoyan; Brüne, Martin

2017-01-01

Frontal EEG asymmetry is a widely studied correlate of emotion processing and psychopathology. Recent research suggests that frontal EEG asymmetry during resting state is related to approach/withdrawal motivation and is also found in affective disorders such as major depressive disorder. Patients with borderline personality disorder (BPD) show aberrant behavior in relation to both approach and withdrawal motivation, which may arguably be associated with their difficulties in emotion processing. The occurrence and significance of frontal EEG asymmetry in BPD, however, has received little attention. Thirty-seven BPD patients and 39 controls underwent resting EEG and completed several psychometric questionnaires. While there were no between-group differences in frontal EEG asymmetry, in BPD frontal EEG asymmetry scores correlated significantly with alexithymia. That is, higher alexithymia scores were associated with relatively lower right-frontal activity. A subsequent analysis corroborated the significant interaction between frontal EEG asymmetry and alexithymia, which was moderated by group. Our findings reveal that lower right frontal EEG asymmetry is associated with alexithymia in patients with BPD. This finding is in accordance with neurophysiological models of alexithymia that implicate a right hemisphere impairment in emotion processing, and could suggest frontal EEG asymmetry as a potential biomarker of relevant psychopathology in these patients.

Altered resting state EEG in chronic pancreatitis patients: toward a marker for chronic pain

NARCIS (Netherlands)

Vries, M. de; Wilder-Smith, O.H.G.; Jongsma, M.L.A.; Broeke, E.N. van den; Arns, M.W.; Goor, H. van; Rijn, C.M. van

2013-01-01

OBJECTIVES: Electroencephalography (EEG) may be a promising source of physiological biomarkers accompanying chronic pain. Several studies in patients with chronic neuropathic pain have reported alterations in central pain processing, manifested as slowed EEG rhythmicity and increased EEG power in

Altered resting state EEG in chronic pancreatitis patients: toward a marker for chronic pain

NARCIS (Netherlands)

Vries, M. de; Wilder-Smith, O.H.G.; Jongsma, M.L.A.; Broeke, E.N. van den; Arns, M.W.; Goor, H. van; Rijn, C.M. van

2013-01-01

Objectives: Electroencephalography (EEG) may be a promising source of physiological biomarkers accompanying chronic pain. Several studies in patients with chronic neuropathic pain have reported alterations in central pain processing, manifested as slowed EEG rhythmicity and increased EEG power in

A Comparative Study of Standardized Infinity Reference and Average Reference for EEG of Three Typical Brain States

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Gaoxing Zheng

2018-03-01

Full Text Available The choice of different reference electrodes plays an important role in deciphering the functional meaning of electroencephalography (EEG signals. In recent years, the infinity zero reference using the reference electrode standard technique (REST has been increasingly applied, while the average reference (AR was generally advocated as the best available reference option in previous classical EEG studies. Here, we designed EEG experiments and performed a direct comparison between the influences of REST and AR on EEG-revealed brain activity features for three typical brain behavior states (eyes-closed, eyes-open and music-listening. The analysis results revealed the following observations: (1 there is no significant difference in the alpha-wave-blocking effect during the eyes-open state compared with the eyes-closed state for both REST and AR references; (2 there was clear frontal EEG asymmetry during the resting state, and the degree of lateralization under REST was higher than that under AR; (3 the global brain functional connectivity density (FCD and local FCD have higher values for REST than for AR under different behavior states; and (4 the value of the small-world network characteristic in the eyes-closed state is significantly (in full, alpha, beta and gamma frequency bands higher than that in the eyes-open state, and the small-world effect under the REST reference is higher than that under AR. In addition, the music-listening state has a higher small-world network effect than the eyes-closed state. The above results suggest that typical EEG features might be more clearly presented by applying the REST reference than by applying AR when using a 64-channel recording.

Reduced Temporal-Central EEG Alpha Coherence during Joint Attention Perception in Adolescents with Autism Spectrum Disorder

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Jaime, Mark; McMahon, Camilla M.; Davidson, Bridget C.; Newell, Lisa C.; Mundy, Peter C.; Henderson, Heather A.

2016-01-01

Although prior studies have demonstrated reduced resting state EEG coherence in adults with autism spectrum disorder (ASD), no studies have explored the nature of EEG coherence during joint attention. We examined the EEG coherence of the joint attention network in adolescents with and without ASD during congruent and incongruent joint attention perception and an eyes-open resting condition. Across conditions, adolescents with ASD showed reduced right hemisphere temporal–central alpha coherence compared to typically developing adolescents. Greater right temporal–central alpha coherence during joint attention was positively associated with social cognitive performance in typical development but not in ASD. These results suggest that, in addition to a resting state, EEG coherence during joint attention perception is reduced in ASD. PMID:26659813

Reduced Temporal-Central EEG Alpha Coherence during Joint Attention Perception in Adolescents with Autism Spectrum Disorder

OpenAIRE

Jaime, Mark; McMahon, Camilla M.; Davidson, Bridget C.; Newell, Lisa C.; Mundy, Peter C.; Henderson, Heather A.

2016-01-01

Although prior studies have demonstrated reduced resting state EEG coherence in adults with autism spectrum disorder (ASD), no studies have explored the nature of EEG coherence during joint attention. We examined the EEG coherence of the joint attention network in adolescents with and without ASD during congruent and incongruent joint attention perception and an eyes-open resting condition. Across conditions, adolescents with ASD showed reduced right hemisphere temporal?central alpha coherenc...

Information-Theoretical Analysis of EEG Microstate Sequences in Python

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Frederic von Wegner

2018-06-01

Full Text Available We present an open-source Python package to compute information-theoretical quantities for electroencephalographic data. Electroencephalography (EEG measures the electrical potential generated by the cerebral cortex and the set of spatial patterns projected by the brain's electrical potential on the scalp surface can be clustered into a set of representative maps called EEG microstates. Microstate time series are obtained by competitively fitting the microstate maps back into the EEG data set, i.e., by substituting the EEG data at a given time with the label of the microstate that has the highest similarity with the actual EEG topography. As microstate sequences consist of non-metric random variables, e.g., the letters A–D, we recently introduced information-theoretical measures to quantify these time series. In wakeful resting state EEG recordings, we found new characteristics of microstate sequences such as periodicities related to EEG frequency bands. The algorithms used are here provided as an open-source package and their use is explained in a tutorial style. The package is self-contained and the programming style is procedural, focusing on code intelligibility and easy portability. Using a sample EEG file, we demonstrate how to perform EEG microstate segmentation using the modified K-means approach, and how to compute and visualize the recently introduced information-theoretical tests and quantities. The time-lagged mutual information function is derived as a discrete symbolic alternative to the autocorrelation function for metric time series and confidence intervals are computed from Markov chain surrogate data. The software package provides an open-source extension to the existing implementations of the microstate transform and is specifically designed to analyze resting state EEG recordings.

A 15O-H2O PET study of meditation and the resting state of normal consciousness

DEFF Research Database (Denmark)

Lou, H C; Kjaer, T W; Friberg, L

1999-01-01

The aim of the present study was to examine whether the neural structures subserving meditation can be reproducibly measured, and, if so, whether they are different from those supporting the resting state of normal consciousness. Cerebral blood flow distribution was investigated with the 15O-H20...... PET technique in nine young adults, who were highly experienced yoga teachers, during the relaxation meditation (Yoga Nidra), and during the resting state of normal consciousness. In addition, global CBF was measured in two of the subjects. Spectral EEG analysis was performed throughout...... the investigations. In meditation, differential activity was seen, with the noticeable exception of V1, in the posterior sensory and associative cortices known to participate in imagery tasks. In the resting state of normal consciousness (compared with meditation as a baseline), differential activity was found...

EEG correlates of virtual reality hypnosis.

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White, David; Ciorciari, Joseph; Carbis, Colin; Liley, David

2009-01-01

The study investigated hypnosis-related electroencephalographic (EEG) coherence and power spectra changes in high and low hypnotizables (Stanford Hypnotic Clinical Scale) induced by a virtual reality hypnosis (VRH) induction system. In this study, the EEG from 17 participants (Mean age = 21.35, SD = 1.58) were compared based on their hypnotizability score. The EEG recording associated with a 2-minute, eyes-closed baseline state was compared to the EEG during a hypnosis-related state. This novel induction system was able to produce EEG findings consistent with previous hypnosis literature. Interactions of significance were found with EEG beta coherence. The high susceptibility group (n = 7) showed decreased coherence, while the low susceptibility group (n = 10) demonstrated an increase in coherence between medial frontal and lateral left prefrontal sites. Methodological and efficacy issues are discussed.

Modification of EEG power spectra and EEG connectivity in autobiographical memory: a sLORETA study.

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Imperatori, Claudio; Brunetti, Riccardo; Farina, Benedetto; Speranza, Anna Maria; Losurdo, Anna; Testani, Elisa; Contardi, Anna; Della Marca, Giacomo

2014-08-01

The aim of the present study was to explore the modifications of scalp EEG power spectra and EEG connectivity during the autobiographical memory test (AM-T) and during the retrieval of an autobiographical event (the high school final examination, Task 2). Seventeen healthy volunteers were enrolled (9 women and 8 men, mean age 23.4 ± 2.8 years, range 19-30). EEG was recorded at baseline and while performing the autobiographical memory (AM) tasks, by means of 19 surface electrodes and a nasopharyngeal electrode. EEG analysis was conducted by means of the standardized LOw Resolution Electric Tomography (sLORETA) software. Power spectra and lagged EEG coherence were compared between EEG acquired during the memory tasks and baseline recording. The frequency bands considered were as follows: delta (0.5-4 Hz); theta (4.5-7.5 Hz); alpha (8-12.5 Hz); beta1 (13-17.5 Hz); beta2 (18-30 Hz); gamma (30.5-60 Hz). During AM-T, we observed a significant delta power increase in left frontal and midline cortices (T = 3.554; p < 0.05) and increased EEG connectivity in delta band in prefrontal, temporal, parietal, and occipital areas, and for gamma bands in the left temporo-parietal regions (T = 4.154; p < 0.05). In Task 2, we measured an increased power in the gamma band located in the left posterior midline areas (T = 3.960; p < 0.05) and a significant increase in delta band connectivity in the prefrontal, temporal, parietal, and occipital areas, and in the gamma band involving right temporo-parietal areas (T = 4.579; p < 0.05). These results indicate that AM retrieval engages in a complex network which is mediated by both low- (delta) and high-frequency (gamma) EEG bands.

How do reference montage and electrodes setup affect the measured scalp EEG potentials?

Science.gov (United States)

Hu, Shiang; Lai, Yongxiu; Valdes-Sosa, Pedro A.; Bringas-Vega, Maria L.; Yao, Dezhong

2018-04-01

Objective. Human scalp electroencephalogram (EEG) is widely applied in cognitive neuroscience and clinical studies due to its non-invasiveness and ultra-high time resolution. However, the representativeness of the measured EEG potentials for the underneath neural activities is still a problem under debate. This study aims to investigate systematically how both reference montage and electrodes setup affect the accuracy of EEG potentials. Approach. First, the standard EEG potentials are generated by the forward calculation with a single dipole in the neural source space, for eleven channel numbers (10, 16, 21, 32, 64, 85, 96, 128, 129, 257, 335). Here, the reference is the ideal infinity implicitly determined by forward theory. Then, the standard EEG potentials are transformed to recordings with different references including five mono-polar references (Left earlobe, Fz, Pz, Oz, Cz), and three re-references (linked mastoids (LM), average reference (AR) and reference electrode standardization technique (REST)). Finally, the relative errors between the standard EEG potentials and the transformed ones are evaluated in terms of channel number, scalp regions, electrodes layout, dipole source position and orientation, as well as sensor noise and head model. Main results. Mono-polar reference recordings are usually of large distortions; thus, a re-reference after online mono-polar recording should be adopted in general to mitigate this effect. Among the three re-references, REST is generally superior to AR for all factors compared, and LM performs worst. REST is insensitive to head model perturbation. AR is subject to electrodes coverage and dipole orientation but no close relation with channel number. Significance. These results indicate that REST would be the first choice of re-reference and AR may be an alternative option for high level sensor noise case. Our findings may provide the helpful suggestions on how to obtain the EEG potentials as accurately as possible for

Study on EEG power and coherence in patients with mild cognitive impairment during working memory task

Institute of Scientific and Technical Information of China (English)

JIANG Zheng-yan

2005-01-01

To investigate the features of electroencephalography (EEG) power and coherence at rest and during a working memory task of patients with mild cognitive impairment (MCI). Thirty-five patients (17 males, 18 females; 52～71 years old) and 34 sex- and age-matched controls (17 males, 17 females; 51～63 years old) were recruited in the present study. Mini-Mental State Examination (MMSE) of 35 patients with MCI and 34 normal controls revealed that the scores of MCI patients did not differ significantly from those of normal controls (P＞0.05). Then, EEGs at rest and during working memory task with three levels of working memory load were recorded. The EEG power was computed over 10 channels: right and left frontal (F3, F4), central (C3,C4), parietal (P3, P4), temporal (TS, T6) and occipital (O1, O2); inter-hemispheric coherences were computed from five electrode pairs of F3-F4, C3-C4, P3-P4, T5-T6 and O1-O2 for delta (1.0～3.5 Hz), theta (4.0～7.5 Hz), alpha-1 (8.0～10.0 Hz), alpha-2 (10.5～13.0 Hz), beta-1 (13.5～18.0 Hz) and beta-2 (18.5～30.0 Hz) frequency bands. All values of the EEG power of MCI patients were found to be higher than those of normal controls at rest and during working memory tasks. Furthermore, the values of EEG power in the theta, alpha-1, alpha-2 and beta-1 bands of patients with MCI were significantly high (P＜0.05) in comparison with those of normal controls. Correlation analysis indicated a significant negative correlation between the EEG powers and MMSE scores. In addition, during working memory tasks, the EEG coherences in all bands were significantly higher in the MCI group in comparison with those in the control group (P＜0.05). However, there was no significant difference in EEG coherences between two groups at rest. These findings comprise evidence that MCI patients have higher EEG power at rest, and higher EEG power and coherence during working conditions. It suggests that MCI may be associated with compensatory processes at

Radiotelemetry recording of electroencephalogram in piglets during rest.

Science.gov (United States)

Saito, Toshiyuki; Watanabe, Yasuko; Nemoto, Tetsu; Kasuya, Etsuko; Sakumoto, Ryosuke

2005-04-13

A wireless recording system was developed to study the electroencephalogram (EEG) in unrestrained, male Landrace piglets. Under general anesthesia, ball-tipped silver/silver chloride electrodes for EEG recording were implanted onto the dura matter of the parietal and frontal cortex of the piglets. A pair of miniature preamplifiers and transmitters was then mounted on the surface of the skull. To examine whether other bioelectrical activities interfere with the EEG measurements, an electrocardiogram (ECG) or electromyogram (EMG) of the neck was simultaneously recorded with the EEG. Next, wire electrodes for recording movement of the eyelid were implanted with EEG electrodes, and EEG and eyelid movements were simultaneously measured. Power spectral analysis using a Fast Fourier Transformation (FFT) algorithm indicates that EEG was successfully recorded in unrestrained piglets, at rest, during the daytime in the absence of interference from ECG, EMG or eyelid movements. These data indicate the feasibility of using our radiotelemetry system for measurement of EEG under these conditions.

A Baseline for the Multivariate Comparison of Resting-State Networks

Science.gov (United States)

Allen, Elena A.; Erhardt, Erik B.; Damaraju, Eswar; Gruner, William; Segall, Judith M.; Silva, Rogers F.; Havlicek, Martin; Rachakonda, Srinivas; Fries, Jill; Kalyanam, Ravi; Michael, Andrew M.; Caprihan, Arvind; Turner, Jessica A.; Eichele, Tom; Adelsheim, Steven; Bryan, Angela D.; Bustillo, Juan; Clark, Vincent P.; Feldstein Ewing, Sarah W.; Filbey, Francesca; Ford, Corey C.; Hutchison, Kent; Jung, Rex E.; Kiehl, Kent A.; Kodituwakku, Piyadasa; Komesu, Yuko M.; Mayer, Andrew R.; Pearlson, Godfrey D.; Phillips, John P.; Sadek, Joseph R.; Stevens, Michael; Teuscher, Ursina; Thoma, Robert J.; Calhoun, Vince D.

2011-01-01

As the size of functional and structural MRI datasets expands, it becomes increasingly important to establish a baseline from which diagnostic relevance may be determined, a processing strategy that efficiently prepares data for analysis, and a statistical approach that identifies important effects in a manner that is both robust and reproducible. In this paper, we introduce a multivariate analytic approach that optimizes sensitivity and reduces unnecessary testing. We demonstrate the utility of this mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12–71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described here, provide a useful baseline for future investigations of brain networks in health and disease. PMID:21442040

Analysis of Small Muscle Movement Effects on EEG Signals

Science.gov (United States)

2016-12-22

different conditions are recorded in this experiment. These conditions are the resting state, left finger keyboard press, right finger keyboard...51 4.3.2. Right and Left Finger Keyboard Press Conditions ..................................... 57 4.4. Detection of Hand...solving Gamma 30 Hz and higher Blending of multiple brain functions ; Muscle related artifacts 2.2. EEG Artifacts EEG recordings are intended to

Modification of EEG functional connectivity and EEG power spectra in overweight and obese patients with food addiction: An eLORETA study.

Science.gov (United States)

Imperatori, Claudio; Fabbricatore, Mariantonietta; Innamorati, Marco; Farina, Benedetto; Quintiliani, Maria Isabella; Lamis, Dorian A; Mazzucchi, Edoardo; Contardi, Anna; Vollono, Catello; Della Marca, Giacomo

2015-12-01

We evaluated the modifications of electroencephalographic (EEG) power spectra and EEG connectivity in overweight and obese patients with elevated food addiction (FA) symptoms. Fourteen overweight and obese patients (3 men and 11 women) with three or more FA symptoms and fourteen overweight and obese patients (3 men and 11 women) with two or less FA symptoms were included in the study. EEG was recorded during three different conditions: 1) five minutes resting state (RS), 2) five minutes resting state after a single taste of a chocolate milkshake (ML-RS), and 3) five minutes resting state after a single taste of control neutral solution (N-RS). EEG analyses were conducted by means of the exact Low Resolution Electric Tomography software (eLORETA). Significant modification was observed only in the ML-RS condition. Compared to controls, patients with three or more FA symptoms showed an increase of delta power in the right middle frontal gyrus (Brodmann Area [BA] 8) and in the right precentral gyrus (BA 9), and theta power in the right insula (BA 13) and in the right inferior frontal gyrus (BA 47). Furthermore, compared to controls, patients with three or more FA symptoms showed an increase of functional connectivity in fronto-parietal areas in both the theta and alpha band. The increase of functional connectivity was also positively associated with the number of FA symptoms. Taken together, our results show that FA has similar neurophysiological correlates of other forms of substance-related and addictive disorders suggesting similar psychopathological mechanisms.

Non-linear Analysis of Scalp EEG by Using Bispectra: The Effect of the Reference Choice

Directory of Open Access Journals (Sweden)

Federico Chella

2017-05-01

Full Text Available Bispectral analysis is a signal processing technique that makes it possible to capture the non-linear and non-Gaussian properties of the EEG signals. It has found various applications in EEG research and clinical practice, including the assessment of anesthetic depth, the identification of epileptic seizures, and more recently, the evaluation of non-linear cross-frequency brain functional connectivity. However, the validity and reliability of the indices drawn from bispectral analysis of EEG signals are potentially biased by the use of a non-neutral EEG reference. The present study aims at investigating the effects of the reference choice on the analysis of the non-linear features of EEG signals through bicoherence, as well as on the estimation of cross-frequency EEG connectivity through two different non-linear measures, i.e., the cross-bicoherence and the antisymmetric cross-bicoherence. To this end, four commonly used reference schemes were considered: the vertex electrode (Cz, the digitally linked mastoids, the average reference, and the Reference Electrode Standardization Technique (REST. The reference effects were assessed both in simulations and in a real EEG experiment. The simulations allowed to investigated: (i the effects of the electrode density on the performance of the above references in the estimation of bispectral measures; and (ii the effects of the head model accuracy in the performance of the REST. For real data, the EEG signals recorded from 10 subjects during eyes open resting state were examined, and the distortions induced by the reference choice in the patterns of alpha-beta bicoherence, cross-bicoherence, and antisymmetric cross-bicoherence were assessed. The results showed significant differences in the findings depending on the chosen reference, with the REST providing superior performance than all the other references in approximating the ideal neutral reference. In conclusion, this study highlights the importance of

Reproducible localization of interictal epileptiform discharges using EEG-triggered fMRI

International Nuclear Information System (INIS)

Symms, M.R.; Allen, P.J.; Fish, D.R.; Barker, G.J.

1999-01-01

We report preliminary experiences using fMRI triggered by EEG to localize the site of interictal epileptiform activity. EEG was recorded in the scanner and monitored on-line; the recording quality was good enough to allow the clear identification of spikes in the EEG. Snap-shot EPI was performed 2-4 s after an epileptiform discharge ('spike') or after at least 10 s of background activity ('rest') was observed. A pixel-by-pixel t-test was performed between the 'rest' and the 'spike' images to determine areas of significant activation. Significant activation was obtained in a patient with epilepsy. To assess the reliability and reproducibility of the technique, the patient was scanned on four separate occasions with similar areas being activated in all the studies, confirming the validity of the result. (author)

Analysis of Altered Baseline Brain Activity in Drug-Naive Adult Patients with Social Anxiety Disorder Using Resting-State Functional MRI

OpenAIRE

Qiu, Changjian; Feng, Yuan; Meng, Yajing; Liao, Wei; Huang, Xiaoqi; Lui, Su; Zhu, Chunyan; Chen, Huafu; Gong, Qiyong; Zhang, Wei

2015-01-01

Objective We hypothesize that the amplitude of low-frequency fluctuations (ALFF) is involved in the altered regional baseline brain function in social anxiety disorder (SAD). The aim of the study was to analyze the altered baseline brain activity in drug-naive adult patients with SAD. Methods We investigated spontaneous and baseline brain activities by obtaining the resting-state functional magnetic resonance imaging data of 20 drug-na?ve adult SAD patients and 19 healthy controls. Voxels wer...

Evidence for age-associated disinhibition of the wake drive provided by scoring principal components of the resting EEG spectrum in sleep-provoking conditions.

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Putilov, Arcady A; Donskaya, Olga G

2016-01-01

Age-associated changes in different bandwidths of the human electroencephalographic (EEG) spectrum are well documented, but their functional significance is poorly understood. This spectrum seems to represent summation of simultaneous influences of several sleep-wake regulatory processes. Scoring of its orthogonal (uncorrelated) principal components can help in separation of the brain signatures of these processes. In particular, the opposite age-associated changes were documented for scores on the two largest (1st and 2nd) principal components of the sleep EEG spectrum. A decrease of the first score and an increase of the second score can reflect, respectively, the weakening of the sleep drive and disinhibition of the opposing wake drive with age. In order to support the suggestion of age-associated disinhibition of the wake drive from the antagonistic influence of the sleep drive, we analyzed principal component scores of the resting EEG spectra obtained in sleep deprivation experiments with 81 healthy young adults aged between 19 and 26 and 40 healthy older adults aged between 45 and 66 years. At the second day of the sleep deprivation experiments, frontal scores on the 1st principal component of the EEG spectrum demonstrated an age-associated reduction of response to eyes closed relaxation. Scores on the 2nd principal component were either initially increased during wakefulness or less responsive to such sleep-provoking conditions (frontal and occipital scores, respectively). These results are in line with the suggestion of disinhibition of the wake drive with age. They provide an explanation of why older adults are less vulnerable to sleep deprivation than young adults.

The Relationship of Cognitive Performance and the Theta-Alpha Power Ratio Is Age-Dependent: An EEG Study of Short Term Memory and Reasoning during Task and Resting-State in Healthy Young and Old Adults

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Janet P. Trammell

2017-11-01

Full Text Available Objective: The Theta-Alpha ratio (TAR is known to differ based upon age and cognitive ability, with pathological electroencephalography (EEG patterns routinely found within neurodegenerative disorders of older adults. We hypothesized that cognitive ability would predict EEG metrics differently within healthy young and old adults, and that healthy old adults not showing age-expected EEG activity may be more likely to demonstrate cognitive deficits relative to old adults showing these expected changes.Methods: In 216 EEG blocks collected in 16 young and 20 old adults during rest (eyes open, eyes closed and cognitive tasks (short-term memory [STM]; matrix reasoning [RM; Raven's matrices], models assessed the contributing roles of cognitive ability, age, and task in predicting the TAR. A general linear mixed-effects regression model was used to model this relationship, including interaction effects to test whether increased cognitive ability predicted TAR differently for young and old adults at rest and during cognitive tasks.Results: The relationship between cognitive ability and the TAR across all blocks showed age-dependency, and cognitive performance at the CZ midline location predicted the TAR measure when accounting for the effect of age (p < 0.05, chi-square test of nested models. Age significantly interacted with STM performance in predicting the TAR (p < 0.05; increases in STM were associated with increased TAR in young adults, but not in old adults. RM showed similar interaction effects with aging and TAR (p < 0.10.Conclusion: EEG correlates of cognitive ability are age-dependent. Adults who did not show age-related EEG changes were more likely to exhibit cognitive deficits than those who showed age-related changes. This suggests that healthy aging should produce moderate changes in Alpha and TAR measures, and the absence of such changes signals impaired cognitive functioning.

Stop and revive? The effectiveness of nap and active rest breaks for reducing driver sleepiness.

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Watling, Christopher N; Smith, Simon S; Horswill, Mark S

2014-11-01

The purpose of this study was to compare the effects of two commonly utilized sleepiness countermeasures: a nap break and an active rest break. The effects of the countermeasures were evaluated by physiological (EEG), subjective, and driving performance measures. Participants completed 2 h of simulated driving, followed by a 15-min nap break or a 15-min active rest break, then completed the final hour of simulated driving. The nap break reduced EEG and subjective sleepiness. The active rest break did not reduce EEG sleepiness, with sleepiness levels eventually increasing, and resulted in an immediate reduction of subjective sleepiness. No difference was found between the two breaks for the driving performance measure. The immediate reduction of subjective sleepiness after the active rest break could leave drivers with erroneous perceptions of their sleepiness, particularly with increases of physiological sleepiness after the break. Copyright © 2014 Society for Psychophysiological Research.

Functional Connectivity Changes in Resting-State EEG as Potential Biomarker for Amyotrophic Lateral Sclerosis.

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Iyer, Parameswaran Mahadeva; Egan, Catriona; Pinto-Grau, Marta; Burke, Tom; Elamin, Marwa; Nasseroleslami, Bahman; Pender, Niall; Lalor, Edmund C; Hardiman, Orla

2015-01-01

Amyotrophic Lateral Sclerosis (ALS) is heterogeneous and overlaps with frontotemporal dementia. Spectral EEG can predict damage in structural and functional networks in frontotemporal dementia but has never been applied to ALS. 18 incident ALS patients with normal cognition and 17 age matched controls underwent 128 channel EEG and neuropsychology assessment. The EEG data was analyzed using FieldTrip software in MATLAB to calculate simple connectivity measures and scalp network measures. sLORETA was used in nodal analysis for source localization and same methods were applied as above to calculate nodal network measures. Graph theory measures were used to assess network integrity. Cross spectral density in alpha band was higher in patients. In ALS patients, increased degree values of the network nodes was noted in the central and frontal regions in the theta band across seven of the different connectivity maps (pEEG has potential utility as a biomarker in ALS.

Widespread EEG changes precede focal seizures.

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Piero Perucca

Full Text Available The process by which the brain transitions into an epileptic seizure is unknown. In this study, we investigated whether the transition to seizure is associated with changes in brain dynamics detectable in the wideband EEG, and whether differences exist across underlying pathologies. Depth electrode ictal EEG recordings from 40 consecutive patients with pharmacoresistant lesional focal epilepsy were low-pass filtered at 500 Hz and sampled at 2,000 Hz. Predefined EEG sections were selected immediately before (immediate preictal, and 30 seconds before the earliest EEG sign suggestive of seizure activity (baseline. Spectral analysis, visual inspection and discrete wavelet transform were used to detect standard (delta, theta, alpha, beta and gamma and high-frequency bands (ripples and fast ripples. At the group level, each EEG frequency band activity increased significantly from baseline to the immediate preictal section, mostly in a progressive manner and independently of any modification in the state of vigilance. Preictal increases in each frequency band activity were widespread, being observed in the seizure-onset zone and lesional tissue, as well as in remote regions. These changes occurred in all the investigated pathologies (mesial temporal atrophy/sclerosis, local/regional cortical atrophy, and malformations of cortical development, but were more pronounced in mesial temporal atrophy/sclerosis. Our findings indicate that a brain state change with distinctive features, in the form of unidirectional changes across the entire EEG bandwidth, occurs immediately prior to seizure onset. We postulate that these changes might reflect a facilitating state of the brain which enables a susceptible region to generate seizures.

Simultaneous trimodal MR-PET-EEG imaging for the investigation of resting state networks in humans

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Neuner, Irene [RWTH Aachen (Germany); Institute of Neuroscience and Medicine - 4, Forschungszentrum Juelich GmbH (Germany); Mauler, Joerg; Arrubla, Jorge; Kops, Elena Rota; Tellmann, Lutz; Scheins, Jurgen; Herzog, Hans [Institute of Neuroscience and Medicine - 4, Forschungszentrum Juelich GmbH (Germany); Langen, Karl Josef; Shah, Jon [RWTH Aachen (Germany)

2015-05-18

Glucose is the principal source of energy for the brain and its relationship to neuronal activity are poorly understood. The human brain uses 80% of its energy for ongoing neural activity that occurs in isolation from any particular stimulus. A promising tool for the investigation of glucose metabolism and its relationship to neuronal activity is simultaneous trimodal MR-PET-EEG data imaging. We here demonstrate the first in vivo human trimodal data at 3T. In one session MR, FDG-PET and EEG data were recorded simultaneously at a 3T hybrid MR-BrainPET scanner (Siemens, Germany) equipped with a 32 channel MR-compatible EEG system (Brain Products, Germany) in 11 healthy volunteers (11 males, mean age: 25.2 years SD: 1.2). MR and EEG data acquisition MP-RAGE (TR = 2250 ms, TE= 3.03 ms, 176 sagittal slices. 1 mm, GRAPPA factor 2. MR-based attenuation correction of PET data via UTE: flip angle=15. Two different echo times TE1=0.07 and TE2=2.46 ms, TR=200 ms. EPI sequence (TR: 2.2 s, TE: 30 ms, FOV: 200 mm, 165 volumes, The subjects were requested to close their eyes and relax EEG data were recorded using a 32-channel MR compatible EEG system. App. 200 MBq/μmol FDG were injected, data were acquired in list mode and iteratively reconstructed with all necessary corrections into 153 slices with 256 x 256 voxels sized 1.25 mm{sup 3}. The trimodal approach, recording PET data, MR data and EEG data simultaneously was successful. The high neuronal activity of the structures within the default mode network occurs on the basis of a high glucose consumption rate within the default node network. The activity of the default mode is not tied to a special EEG frequency band.

Simultaneous trimodal MR-PET-EEG imaging for the investigation of resting state networks in humans

International Nuclear Information System (INIS)

Neuner, Irene; Mauler, Joerg; Arrubla, Jorge; Kops, Elena Rota; Tellmann, Lutz; Scheins, Jurgen; Herzog, Hans; Langen, Karl Josef; Shah, Jon

2015-01-01

Glucose is the principal source of energy for the brain and its relationship to neuronal activity are poorly understood. The human brain uses 80% of its energy for ongoing neural activity that occurs in isolation from any particular stimulus. A promising tool for the investigation of glucose metabolism and its relationship to neuronal activity is simultaneous trimodal MR-PET-EEG data imaging. We here demonstrate the first in vivo human trimodal data at 3T. In one session MR, FDG-PET and EEG data were recorded simultaneously at a 3T hybrid MR-BrainPET scanner (Siemens, Germany) equipped with a 32 channel MR-compatible EEG system (Brain Products, Germany) in 11 healthy volunteers (11 males, mean age: 25.2 years SD: 1.2). MR and EEG data acquisition MP-RAGE (TR = 2250 ms, TE= 3.03 ms, 176 sagittal slices. 1 mm, GRAPPA factor 2. MR-based attenuation correction of PET data via UTE: flip angle=15. Two different echo times TE1=0.07 and TE2=2.46 ms, TR=200 ms. EPI sequence (TR: 2.2 s, TE: 30 ms, FOV: 200 mm, 165 volumes, The subjects were requested to close their eyes and relax EEG data were recorded using a 32-channel MR compatible EEG system. App. 200 MBq/μmol FDG were injected, data were acquired in list mode and iteratively reconstructed with all necessary corrections into 153 slices with 256 x 256 voxels sized 1.25 mm 3 . The trimodal approach, recording PET data, MR data and EEG data simultaneously was successful. The high neuronal activity of the structures within the default mode network occurs on the basis of a high glucose consumption rate within the default node network. The activity of the default mode is not tied to a special EEG frequency band.

The hemodynamic response of the alpha rhythm: an EEG/fMRI study.

NARCIS (Netherlands)

de Munck, J.C.; Goncalves, S.I.; Huijboom, L.; Kuijer, J.P.; Pouwels, P.J.; Heethaar, R.M.; Lopes da Silva, F.H.

2007-01-01

EEG was recorded during fMRI scanning of 16 normal controls in resting condition with eyes closed. Time variations of the occipital alpha band amplitudes were correlated to the fMRI signal variations to obtain insight into the hemodynamic correlates of the EEG alpha activity. Contrary to earlier

Memories of attachment hamper EEG cortical connectivity in dissociative patients.

Science.gov (United States)

Farina, Benedetto; Speranza, Anna Maria; Dittoni, Serena; Gnoni, Valentina; Trentini, Cristina; Vergano, Carola Maggiora; Liotti, Giovanni; Brunetti, Riccardo; Testani, Elisa; Della Marca, Giacomo

2014-08-01

In this study, we evaluated cortical connectivity modifications by electroencephalography (EEG) lagged coherence analysis, in subjects with dissociative disorders and in controls, after retrieval of attachment memories. We asked thirteen patients with dissociative disorders and thirteen age- and sex-matched healthy controls to retrieve personal attachment-related autobiographical memories through adult attachment interviews (AAI). EEG was recorded in the closed eyes resting state before and after the AAI. EEG lagged coherence before and after AAI was compared in all subjects. In the control group, memories of attachment promoted a widespread increase in EEG connectivity, in particular in the high-frequency EEG bands. Compared to controls, dissociative patients did not show an increase in EEG connectivity after the AAI. Conclusions: These results shed light on the neurophysiology of the disintegrative effect of retrieval of traumatic attachment memories in dissociative patients.

Short and long-term effects of sham-controlled prefrontal EEG-neurofeedback training in healthy subjects.

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Engelbregt, H J; Keeser, D; van Eijk, L; Suiker, E M; Eichhorn, D; Karch, S; Deijen, J B; Pogarell, O

2016-04-01

In this study we evaluated long-term effects of frontal beta EEG-neurofeedback training (E-NFT) on healthy subjects. We hypothesized that E-NFT can change frontal beta activity in the long-term and that changes in frontal beta EEG activity are accompanied by altered cognitive performance. 25 healthy subjects were included and randomly assigned to active or sham E-NFT. On average the subjects underwent 15 E-NFT training sessions with a training duration of 45 min. Resting-state EEG was recorded prior to E-NFT training (t1) and in a 3-year follow-up (t3). Compared to sham E-NFT, which was used for the control group, real E-NFT increased beta activity in a predictable way. This increase was maintained over a period of three years post training. However, E-NFT did not result in significantly improved cognitive performance. Based on our results, we conclude that EEG-NFT can selectively modify EEG beta activity both in short and long-term. This is a sham controlled EEG neurofeedback study demonstrating long-term effects in resting state EEG. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Improving the Specificity of EEG for Diagnosing Alzheimer's Disease

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François-B. Vialatte

2011-01-01

Full Text Available Objective. EEG has great potential as a cost-effective screening tool for Alzheimer's disease (AD. However, the specificity of EEG is not yet sufficient to be used in clinical practice. In an earlier study, we presented preliminary results suggesting improved specificity of EEG to early stages of Alzheimer's disease. The key to this improvement is a new method for extracting sparse oscillatory events from EEG signals in the time-frequency domain. Here we provide a more detailed analysis, demonstrating improved EEG specificity for clinical screening of MCI (mild cognitive impairment patients. Methods. EEG data was recorded of MCI patients and age-matched control subjects, in rest condition with eyes closed. EEG frequency bands of interest were θ (3.5–7.5 Hz, α1 (7.5–9.5 Hz, α2 (9.5–12.5 Hz, and β (12.5–25 Hz. The EEG signals were transformed in the time-frequency domain using complex Morlet wavelets; the resulting time-frequency maps are represented by sparse bump models. Results. Enhanced EEG power in the θ range is more easily detected through sparse bump modeling; this phenomenon explains the improved EEG specificity obtained in our previous studies. Conclusions. Sparse bump modeling yields informative features in EEG signal. These features increase the specificity of EEG for diagnosing AD.

Effect of passive concentration as instructional set for training enhancement of EEG alpha.

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Knox, S S

1980-12-01

The technique of passive concentration, employed by autogenic training and Transcendental Meditation for achieving relaxation, was tested here as a technique for enhancing EEG alpha. Of 30 subjects displaying between 15% and 74% alpha in their resting EEGs recruited, 10 had to be eliminated. The remaining 20 constituted two groups. One was instructed only to attempt to maintain a tone indicating alpha but given no information about technique (control group). The other was given additional instructions in passive concentration (experimental group). Both were given four 5-min. trials a day for 4 consecutive days. Heart rate and skin conductance were measured to monitor autonomic arousal. The group receiving instructions in passive concentration had significantly less alpha than the control group, which did not increase amount of alpha above baseline. The reduction of alpha in the experimental group was interpreted as resulting from beginning long training periods (20 min. per day), a practice advocated by Transcendental Meditation but discouraged by autogenic training. It was concluded that the relevance of passive concentration for alpha enhancement is doubtful.

Estimating repetitive spatiotemporal patterns from resting-state brain activity data.

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Takeda, Yusuke; Hiroe, Nobuo; Yamashita, Okito; Sato, Masa-Aki

2016-06-01

Repetitive spatiotemporal patterns in spontaneous brain activities have been widely examined in non-human studies. These studies have reported that such patterns reflect past experiences embedded in neural circuits. In human magnetoencephalography (MEG) and electroencephalography (EEG) studies, however, spatiotemporal patterns in resting-state brain activities have not been extensively examined. This is because estimating spatiotemporal patterns from resting-state MEG/EEG data is difficult due to their unknown onsets. Here, we propose a method to estimate repetitive spatiotemporal patterns from resting-state brain activity data, including MEG/EEG. Without the information of onsets, the proposed method can estimate several spatiotemporal patterns, even if they are overlapping. We verified the performance of the method by detailed simulation tests. Furthermore, we examined whether the proposed method could estimate the visual evoked magnetic fields (VEFs) without using stimulus onset information. The proposed method successfully detected the stimulus onsets and estimated the VEFs, implying the applicability of this method to real MEG data. The proposed method was applied to resting-state functional magnetic resonance imaging (fMRI) data and MEG data. The results revealed informative spatiotemporal patterns representing consecutive brain activities that dynamically change with time. Using this method, it is possible to reveal discrete events spontaneously occurring in our brains, such as memory retrieval. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Do resting brain dynamics predict oddball evoked-potential?

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Lee Tien-Wen

2011-11-01

Full Text Available Abstract Background The oddball paradigm is widely applied to the investigation of cognitive function in neuroscience and in neuropsychiatry. Whether cortical oscillation in the resting state can predict the elicited oddball event-related potential (ERP is still not clear. This study explored the relationship between resting electroencephalography (EEG and oddball ERPs. The regional powers of 18 electrodes across delta, theta, alpha and beta frequencies were correlated with the amplitude and latency of N1, P2, N2 and P3 components of oddball ERPs. A multivariate analysis based on partial least squares (PLS was applied to further examine the spatial pattern revealed by multiple correlations. Results Higher synchronization in the resting state, especially at the alpha spectrum, is associated with higher neural responsiveness and faster neural propagation, as indicated by the higher amplitude change of N1/N2 and shorter latency of P2. None of the resting quantitative EEG indices predict P3 latency and amplitude. The PLS analysis confirms that the resting cortical dynamics which explains N1/N2 amplitude and P2 latency does not show regional specificity, indicating a global property of the brain. Conclusions This study differs from previous approaches by relating dynamics in the resting state to neural responsiveness in the activation state. Our analyses suggest that the neural characteristics carried by resting brain dynamics modulate the earlier/automatic stage of target detection.

Associations among family socioeconomic status, EEG power at birth, and cognitive skills during infancy

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Natalie H. Brito

2016-06-01

Full Text Available Past research has demonstrated links between cortical activity, measured via EEG power, and cognitive processes during infancy. In a separate line of research, family socioeconomic status (SES has been strongly associated with children’s early cognitive development, with socioeconomic disparities emerging during the second year of life for both language and declarative memory skills. The present study examined associations among resting EEG power at birth, SES, and language and memory skills at 15-months in a sample of full-term infants. Results indicate no associations between SES and EEG power at birth. However, EEG power at birth was related to both language and memory outcomes at 15-months. Specifically, frontal power (24–48 Hz was positively correlated with later Visual Paired Comparison (VPC memory scores. Power (24–35 Hz in the parietal region was positively correlated with later PLS-Auditory Comprehension language scores. These findings suggest that SES disparities in brain activity may not be apparent at birth, but measures of resting neonatal EEG power are correlated with later memory and language skills independently of SES.

Neural correlate of resting-state functional connectivity under α2 adrenergic receptor agonist, medetomidine.

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Nasrallah, Fatima A; Lew, Si Kang; Low, Amanda Si-Min; Chuang, Kai-Hsiang

2014-01-01

Correlative fluctuations in functional MRI (fMRI) signals across the brain at rest have been taken as a measure of functional connectivity, but the neural basis of this resting-state MRI (rsMRI) signal is not clear. Previously, we found that the α2 adrenergic agonist, medetomidine, suppressed the rsMRI correlation dose-dependently but not the stimulus evoked activation. To understand the underlying electrophysiology and neurovascular coupling, which might be altered due to the vasoconstrictive nature of medetomidine, somatosensory evoked potential (SEP) and resting electroencephalography (EEG) were measured and correlated with corresponding BOLD signals in rat brains under three dosages of medetomidine. The SEP elicited by electrical stimulation to both forepaws was unchanged regardless of medetomidine dosage, which was consistent with the BOLD activation. Identical relationship between the SEP and BOLD signal under different medetomidine dosages indicates that the neurovascular coupling was not affected. Under resting state, EEG power was the same but a depression of inter-hemispheric EEG coherence in the gamma band was observed at higher medetomidine dosage. Different from medetomidine, both resting EEG power and BOLD power and coherence were significantly suppressed with increased isoflurane level. Such reduction was likely due to suppressed neural activity as shown by diminished SEP and BOLD activation under isoflurane, suggesting different mechanisms of losing synchrony at resting-state. Even though, similarity between electrophysiology and BOLD under stimulation and resting-state implicates a tight neurovascular coupling in both medetomidine and isoflurane. Our results confirm that medetomidine does not suppress neural activity but dissociates connectivity in the somatosensory cortex. The differential effect of medetomidine and its receptor specific action supports the neuronal origin of functional connectivity and implicates the mechanism of its sedative

Paradoxical dopaminergic drug effects in extraversion: Dose- and time-dependent effects of Sulpiride on EEG theta activity

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Mira-Lynn eChavanon

2013-04-01

Full Text Available Dopaminergic drugs frequently produce paradoxical effects depending on baseline performance levels, genotype or personality traits. The present study for the first time aimed to specify the mechanisms underlying such opposite effects using the following recently reported scenario as an example: Depending on the personality trait agentic extraversion (aE; i.e. assertiveness, dominance, ambition, positive emotionality the selective dopamine D2 receptor antagonist sulpiride (200 mg had opposite effects on resting posterior versus anterior theta activity in the electroencephalogram (EEG. In order to better describe these opposite pharmaco-EEG effects and to generate hypotheses regarding the underlying mechanisms, we measured the EEG intermittently over five hours in 80 healthy male volunteers extremely high or low in aE who had received either placebo or one of three doses of sulpiride (50 mg, 200 mg, or 400 mg. The findings suggest a model postulating stronger pre- versus postsynaptic subreceptor effects in high aE individuals compared to low aE individuals. Future studies may now systematically apply the model to other examples of paradoxical dopaminergic drug effects and examine the molecular basis of individual differences in pre- versus postsynaptic dopamine D2 subreceptor sensitivities and densities.

Atypical Laterality of Resting Gamma Oscillations in Autism Spectrum Disorders

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Maxwell, Christina R.; Villalobos, Michele E.; Schultz, Robert T.; Herpertz-Dahlmann, Beate; Konrad, Kerstin; Kohls, Gregor

2015-01-01

Abnormal brain oscillatory activity has been found in autism spectrum disorders (ASD) and proposed as a potential biomarker. While several studies have investigated gamma oscillations in ASD, none have examined resting gamma power across multiple brain regions. This study investigated resting gamma power using EEG in 15 boys with ASD and 18 age…

Preoperational radiation surveillance of the WIPP project by EEG during 1992

International Nuclear Information System (INIS)

Kenney, J.W.

1994-02-01

The purpose of the EEG preoperational monitoring program is to document the existing concentrations of selected radionuclides in various environmental media collected from the vicinity of the WIPP site to provide a basis of comparison of any effects of future WT-PP operations. The basic methodology for conducting environmental surveillance both on-site and off-site was outlined by Spiegler (1984). This report represents a continuation of the EEG baseline data beginning in 1985, previously reported in EEG-43, EEG-47, EEG-49 and EEG-51. Such radionuclide baseline data are important in order to determine whether future WIPP operations with radioactive waste have affected concentrations of these radionuclides in the environment. EEG data are consistent with similar environmental measurements obtained by DOE beginning in 1985. Since late 1985, the EEG has collected or received as split samples 2 443 air filters with particulates, 202 water samples, 16 biota samples and 13 soil/sediment samples. A total of 5,946 specific radionuclide analyses have been performed on these samples. As reported previously by EEG (EEG-43, EEG-47, EEG-49 and EEG-51), observed concentrations of U-238 daughter radionuclides were not in equilibrium with the parent radionuclide in water samples. This observation is consistent with different radionuclide mobility in the environment. In a notice of proposed rule making for 40 CFR 141 (US EPA 1991), the Environmental Protection Agency (EPA) National Primary Drinking Water Regulations reflect this in the calculated activity-to-mass ratio of 1.3 pCi/μg of uranium using a geometric mean of the U-234:U-238 ratio in water supplies of 2.7. Ra-226 and Ra- 228 were reported in a number of water samples in concentrations similar to those previously published by EEG and DOE

Directed Motor-Auditory EEG Connectivity Is Modulated by Music Tempo.

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Nicolaou, Nicoletta; Malik, Asad; Daly, Ian; Weaver, James; Hwang, Faustina; Kirke, Alexis; Roesch, Etienne B; Williams, Duncan; Miranda, Eduardo R; Nasuto, Slawomir J

2017-01-01

Beat perception is fundamental to how we experience music, and yet the mechanism behind this spontaneous building of the internal beat representation is largely unknown. Existing findings support links between the tempo (speed) of the beat and enhancement of electroencephalogram (EEG) activity at tempo-related frequencies, but there are no studies looking at how tempo may affect the underlying long-range interactions between EEG activity at different electrodes. The present study investigates these long-range interactions using EEG activity recorded from 21 volunteers listening to music stimuli played at 4 different tempi (50, 100, 150 and 200 beats per minute). The music stimuli consisted of piano excerpts designed to convey the emotion of "peacefulness". Noise stimuli with an identical acoustic content to the music excerpts were also presented for comparison purposes. The brain activity interactions were characterized with the imaginary part of coherence (iCOH) in the frequency range 1.5-18 Hz (δ, θ, α and lower β) between all pairs of EEG electrodes for the four tempi and the music/noise conditions, as well as a baseline resting state (RS) condition obtained at the start of the experimental task. Our findings can be summarized as follows: (a) there was an ongoing long-range interaction in the RS engaging fronto-posterior areas; (b) this interaction was maintained in both music and noise, but its strength and directionality were modulated as a result of acoustic stimulation; (c) the topological patterns of iCOH were similar for music, noise and RS, however statistically significant differences in strength and direction of iCOH were identified; and (d) tempo had an effect on the direction and strength of motor-auditory interactions. Our findings are in line with existing literature and illustrate a part of the mechanism by which musical stimuli with different tempi can entrain changes in cortical activity.

Directed Motor-Auditory EEG Connectivity Is Modulated by Music Tempo

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Nicoletta Nicolaou

2017-10-01

Full Text Available Beat perception is fundamental to how we experience music, and yet the mechanism behind this spontaneous building of the internal beat representation is largely unknown. Existing findings support links between the tempo (speed of the beat and enhancement of electroencephalogram (EEG activity at tempo-related frequencies, but there are no studies looking at how tempo may affect the underlying long-range interactions between EEG activity at different electrodes. The present study investigates these long-range interactions using EEG activity recorded from 21 volunteers listening to music stimuli played at 4 different tempi (50, 100, 150 and 200 beats per minute. The music stimuli consisted of piano excerpts designed to convey the emotion of “peacefulness”. Noise stimuli with an identical acoustic content to the music excerpts were also presented for comparison purposes. The brain activity interactions were characterized with the imaginary part of coherence (iCOH in the frequency range 1.5–18 Hz (δ, θ, α and lower β between all pairs of EEG electrodes for the four tempi and the music/noise conditions, as well as a baseline resting state (RS condition obtained at the start of the experimental task. Our findings can be summarized as follows: (a there was an ongoing long-range interaction in the RS engaging fronto-posterior areas; (b this interaction was maintained in both music and noise, but its strength and directionality were modulated as a result of acoustic stimulation; (c the topological patterns of iCOH were similar for music, noise and RS, however statistically significant differences in strength and direction of iCOH were identified; and (d tempo had an effect on the direction and strength of motor-auditory interactions. Our findings are in line with existing literature and illustrate a part of the mechanism by which musical stimuli with different tempi can entrain changes in cortical activity.

Directed Motor-Auditory EEG Connectivity Is Modulated by Music Tempo

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Nicolaou, Nicoletta; Malik, Asad; Daly, Ian; Weaver, James; Hwang, Faustina; Kirke, Alexis; Roesch, Etienne B.; Williams, Duncan; Miranda, Eduardo R.; Nasuto, Slawomir J.

2017-01-01

Beat perception is fundamental to how we experience music, and yet the mechanism behind this spontaneous building of the internal beat representation is largely unknown. Existing findings support links between the tempo (speed) of the beat and enhancement of electroencephalogram (EEG) activity at tempo-related frequencies, but there are no studies looking at how tempo may affect the underlying long-range interactions between EEG activity at different electrodes. The present study investigates these long-range interactions using EEG activity recorded from 21 volunteers listening to music stimuli played at 4 different tempi (50, 100, 150 and 200 beats per minute). The music stimuli consisted of piano excerpts designed to convey the emotion of “peacefulness”. Noise stimuli with an identical acoustic content to the music excerpts were also presented for comparison purposes. The brain activity interactions were characterized with the imaginary part of coherence (iCOH) in the frequency range 1.5–18 Hz (δ, θ, α and lower β) between all pairs of EEG electrodes for the four tempi and the music/noise conditions, as well as a baseline resting state (RS) condition obtained at the start of the experimental task. Our findings can be summarized as follows: (a) there was an ongoing long-range interaction in the RS engaging fronto-posterior areas; (b) this interaction was maintained in both music and noise, but its strength and directionality were modulated as a result of acoustic stimulation; (c) the topological patterns of iCOH were similar for music, noise and RS, however statistically significant differences in strength and direction of iCOH were identified; and (d) tempo had an effect on the direction and strength of motor-auditory interactions. Our findings are in line with existing literature and illustrate a part of the mechanism by which musical stimuli with different tempi can entrain changes in cortical activity. PMID:29093672

Distinguishing rhythmic from non-rhythmic brain activity during rest in healthy neurocognitive aging.

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Caplan, Jeremy B; Bottomley, Monica; Kang, Pardeep; Dixon, Roger A

2015-05-15

Rhythmic brain activity at low frequencies (healthy neurocognitive aging are mixed. Here we address two reasons conventional spectral analyses may have led to inconsistent results. First, spectral-power measures are compared to a baseline condition; when resting activity is the signal of interest, it is unclear what the baseline should be. Second, conventional methods do not clearly differentiate power due to rhythmic versus non-rhythmic activity. The Better OSCillation detection method (BOSC; Caplan et al., 2001; Whitten et al., 2011) avoids these problems by using the signal's own spectral characteristics as a reference to detect elevations in power lasting a few cycles. We recorded electroencephalographic (EEG) signal during rest, alternating eyes open and closed, in healthy younger (18-25 years) and older (60-74 years) participants. Topographic plots suggested the conventional and BOSC analyses measured different sources of activity, particularly at frequencies, like delta (1-4Hz), at which rhythms are sporadic; topographies were more similar in the 8-12Hz alpha band. There was little theta-band activity meeting the BOSC method's criteria, suggesting prior findings of theta power in healthy aging may reflect non-rhythmic signal. In contrast, delta oscillations were present at higher levels than theta in both age groups. In summary, applying strict and standardized criteria for rhythmicity, slow rhythms appear present in the resting brain at delta and alpha, but not theta frequencies, and appear unchanged in healthy aging. Copyright © 2015 Elsevier Inc. All rights reserved.

Insights on the neural basis of motor plasticity induced by theta burst stimulation from TMS-EEG

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VERNET, Marine; BASHIR, Shahid; YOO, Woo-Kyoung; PEREZ, Jennifer M.; NAJIB, Umer; PASCUAL-LEONE, Alvaro

2014-01-01

Transcranial magnetic stimulation (TMS) is a useful tool to induce and measure plasticity in the human brain. However, the cortical effects are generally indirectly evaluated with motor-evoked potentials (MEPs) reflective of modulation of cortico-spinal excitability. In this study, we aim to provide direct measures of cortical plasticity by combining TMS with electroencephalography (EEG). Continuous theta-burst stimulation (cTBS) was applied over the primary motor cortex (M1) of young healthy adults; and we measured modulation of (i) motor evoked-potentials (MEPs), (ii) TMS-induced EEG evoked potentials (TEPs), (iii) TMS-induced EEG synchronization and (iv) eyes-closed resting EEG. Our results show the expected cTBS-induced decrease in MEPs size, which we found to be paralleled by a modulation of a combination of TEPs. Furthermore, we found that cTBS increased the power in the theta band of eyes-closed resting EEG, whereas it decreased single-pulse TMS-induced power in the theta and alpha bands. In addition, cTBS decreased the power in the beta band of eyes-closed resting EEG, whereas it increased single-pulse TMS-induced power in the beta band. We suggest that cTBS acts by modulating the phase alignment between already active oscillators; it synchronizes low frequency (theta and/or alpha) oscillators and desynchronizes high frequency (beta) oscillators. These results provide novel insights into the cortical effects of cTBS and could be useful for exploring cTBS-induced plasticity outside of the motor cortex. PMID:23190020

Tonic pain and continuous EEG: prediction of subjective pain perception by alpha-1 power during stimulation and at rest.

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Nir, Rony-Reuven; Sinai, Alon; Moont, Ruth; Harari, Eyal; Yarnitsky, David

2012-03-01

Pain neurophysiology has been chiefly characterized via event-related potentials (ERPs), which are exerted using brief, phase-locked noxious stimuli. Striving for objectively characterizing clinical pain states using more natural, prolonged stimuli, tonic pain has been recently associated with the individual peak frequency of alpha oscillations. This finding encouraged us to explore whether alpha power, reflecting the magnitude of the synchronized activity within this frequency range, will demonstrate a corresponding relationship with subjective perception of tonic pain. Five-minute-long continuous EEG was recorded in 18 healthy volunteers under: (i) resting-state; (ii) innocuous temperature; and (iii) psychophysically-anchored noxious temperature. Numerical pain scores (NPSs) collected during the application of tonic noxious stimuli were tested for correlation with alpha-1 and alpha-2 power. NPSs and alpha power remained stable throughout the recording conditions (Ps⩾0.381). In the noxious condition, alpha-1 power obtained at the bilateral temporal scalp was negatively correlated with NPSs (Ps⩽0.04). Additionally, resting-state alpha-1 power recorded at the bilateral temporal scalp was negatively correlated with NPSs reported during the noxious condition (Ps⩽0.038). Current findings suggest alpha-1 power may serve as a direct, objective and experimentally stable measure of subjective perception of tonic pain. Furthermore, resting-state alpha-1 power might reflect individuals' inherent tonic pain responsiveness. The relevance of alpha-1 power to tonic pain perception may deepen the understanding of the mechanisms underlying the processing of prolonged noxious stimulation. Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Brief Report: Reduced Temporal-Central EEG Alpha Coherence during Joint Attention Perception in Adolescents with Autism Spectrum Disorder

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Jaime, Mark; McMahon, Camilla M.; Davidson, Bridget C.; Newell, Lisa C.; Mundy, Peter C.; Henderson, Heather A.

2016-01-01

Although prior studies have demonstrated reduced resting state EEG coherence in adults with autism spectrum disorder (ASD), no studies have explored the nature of EEG coherence during joint attention. We examined the EEG coherence of the joint attention network in adolescents with and without ASD during congruent and incongruent joint attention…

The Role of Hemispheral Asymmetry and Regional Activity of Quantitative EEG in Children with Stuttering

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Ozge, Aynur; Toros, Fevziye; Comelekoglu, Ulku

2004-01-01

We investigated the role of delayed cerebral maturation, hemisphere asymmetry and regional differences in children with stuttering and healthy controls during resting state and hyperventilation, using conventional EEG techniques and quantitative EEG (QEEG) analysis. This cross-sectional case control study included 26 children with stuttering and…

Frontal EEG asymmetry in borderline personality disorder is associated with alexithymia

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Flasbeck, Vera; Popkirov, Stoyan; Brüne, Martin

2017-01-01

Background Frontal EEG asymmetry is a widely studied correlate of emotion processing and psychopathology. Recent research suggests that frontal EEG asymmetry during resting state is related to approach/withdrawal motivation and is also found in affective disorders such as major depressive disorder. Patients with borderline personality disorder (BPD) show aberrant behavior in relation to both approach and withdrawal motivation, which may arguably be associated with their difficulties in emotio...

Alzheimer's disease: relationship between cognitive aspects and power and coherence EEG measures

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Lineu C. Fonseca

2011-12-01

Full Text Available OBJECTIVE: To evaluate the relationship between specific cognitive aspects and quantitative EEG measures, in patients with mild or moderate Alzheimer's disease (AD. METHOD: Thirty-eight AD patients and 31 controls were assessed by CERAD neuropsychological battery (Consortium to Establish a Registry for AD and the electroencephalogram (EEG. The absolute power and coherences EEG measures were calculated at rest. The correlations between the cognitive variables and the EEG were evaluated. RESULTS: In the AD group there were significant correlations between different coherence EEG measures and Mini-Mental State Examination, verbal fluency, modified Boston naming, word list memory with repetition, word list recall and recognition, and constructional praxis (p<0.01. These correlations were all negative for the delta and theta bands and positive for alpha and beta. There were no correlations between cognitive aspects and absolute EEG power. CONCLUSION: The coherence EEG measures reflect different forms in the relationship between regions related to various cognitive dysfunctions.

Attention-induced deactivations in very low frequency EEG oscillations: differential localisation according to ADHD symptom status.

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Samantha J Broyd

Full Text Available BACKGROUND: The default-mode network (DMN is characterised by coherent very low frequency (VLF brain oscillations. The cognitive significance of this VLF profile remains unclear, partly because of the temporally constrained nature of the blood oxygen-level dependent (BOLD signal. Previously we have identified a VLF EEG network of scalp locations that shares many features of the DMN. Here we explore the intracranial sources of VLF EEG and examine their overlap with the DMN in adults with high and low ADHD ratings. METHODOLOGY/PRINCIPAL FINDINGS: DC-EEG was recorded using an equidistant 66 channel electrode montage in 25 adult participants with high- and 25 participants with low-ratings of ADHD symptoms during a rest condition and an attention demanding Eriksen task. VLF EEG power was calculated in the VLF band (0.02 to 0.2 Hz for the rest and task condition and compared for high and low ADHD participants. sLORETA was used to identify brain sources associated with the attention-induced deactivation of VLF EEG power, and to examine these sources in relation to ADHD symptoms. There was significant deactivation of VLF EEG power between the rest and task condition for the whole sample. Using s-LORETA the sources of this deactivation were localised to medial prefrontal regions, posterior cingulate cortex/precuneus and temporal regions. However, deactivation sources were different for high and low ADHD groups: In the low ADHD group attention-induced VLF EEG deactivation was most significant in medial prefrontal regions while for the high ADHD group this deactivation was predominantly localised to the temporal lobes. CONCLUSIONS/SIGNIFICANCE: Attention-induced VLF EEG deactivations have intracranial sources that appear to overlap with those of the DMN. Furthermore, these seem to be related to ADHD symptom status, with high ADHD adults failing to significantly deactivate medial prefrontal regions while at the same time showing significant attenuation of

Resting-state beta and gamma activity in Internet addiction.

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Choi, Jung-Seok; Park, Su Mi; Lee, Jaewon; Hwang, Jae Yeon; Jung, Hee Yeon; Choi, Sam-Wook; Kim, Dai Jin; Oh, Sohee; Lee, Jun-Young

2013-09-01

Internet addiction is the inability to control one's use of the Internet and is related to impulsivity. Although a few studies have examined neurophysiological activity as individuals with Internet addiction engage in cognitive processing, no information on spontaneous EEG activity in the eyes-closed resting-state is available. We investigated resting-state EEG activities in beta and gamma bands and examined their relationships with impulsivity among individuals with Internet addiction and healthy controls. Twenty-one drug-naïve patients with Internet addiction (age: 23.33 ± 3.50 years) and 20 age-, sex-, and IQ-matched healthy controls (age: 22.40 ± 2.33 years) were enrolled in this study. Severity of Internet addiction was identified by the total score on Young's Internet Addiction Test. Impulsivity was measured with the Barratt Impulsiveness Scale-11 and a stop-signal task. Resting-state EEG during eyes closed was recorded, and the absolute/relative power of beta and gamma bands was analyzed. The Internet addiction group showed high impulsivity and impaired inhibitory control. The generalized estimating equation showed that the Internet-addiction group showed lower absolute power on the beta band than did the control group (estimate = -3.370, p Internet-addiction group showed higher absolute power on the gamma band than did the control group (estimate = 0.434, p Internet addiction as well as with the extent of impulsivity. The present study suggests that resting-state fast-wave brain activity is related to the impulsivity characterizing Internet addiction. These differences may be neurobiological markers for the pathophysiology of Internet addiction. Copyright © 2013 Elsevier B.V. All rights reserved.

Consciousness Indexing and Outcome Prediction with Resting-State EEG in Severe Disorders of Consciousness.

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Stefan, Sabina; Schorr, Barbara; Lopez-Rolon, Alex; Kolassa, Iris-Tatjana; Shock, Jonathan P; Rosenfelder, Martin; Heck, Suzette; Bender, Andreas

2018-04-17

We applied the following methods to resting-state EEG data from patients with disorders of consciousness (DOC) for consciousness indexing and outcome prediction: microstates, entropy (i.e. approximate, permutation), power in alpha and delta frequency bands, and connectivity (i.e. weighted symbolic mutual information, symbolic transfer entropy, complex network analysis). Patients with unresponsive wakefulness syndrome (UWS) and patients in a minimally conscious state (MCS) were classified into these two categories by fitting and testing a generalised linear model. We aimed subsequently to develop an automated system for outcome prediction in severe DOC by selecting an optimal subset of features using sequential floating forward selection (SFFS). The two outcome categories were defined as UWS or dead, and MCS or emerged from MCS. Percentage of time spent in microstate D in the alpha frequency band performed best at distinguishing MCS from UWS patients. The average clustering coefficient obtained from thresholding beta coherence performed best at predicting outcome. The optimal subset of features selected with SFFS consisted of the frequency of microstate A in the 2-20 Hz frequency band, path length obtained from thresholding alpha coherence, and average path length obtained from thresholding alpha coherence. Combining these features seemed to afford high prediction power. Python and MATLAB toolboxes for the above calculations are freely available under the GNU public license for non-commercial use ( https://qeeg.wordpress.com ).

Optimising EEG-fMRI for Localisation of Focal Epilepsy in Children.

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Maria Centeno

Full Text Available Early surgical intervention in children with drug resistant epilepsy has benefits but requires using tolerable and minimally invasive tests. EEG-fMRI studies have demonstrated good sensitivity for the localization of epileptic focus but a poor yield although the reasons for this have not been systematically addressed. While adults EEG-fMRI studies are performed in the "resting state"; children are commonly sedated however, this has associated risks and potential confounds. In this study, we assessed the impact of the following factors on the tolerability and results of EEG-fMRI in children: viewing a movie inside the scanner; movement; occurrence of interictal epileptiform discharges (IED; scan duration and design efficiency. This work's motivation is to optimize EEG-fMRI parameters to make this test widely available to paediatric population.Forty-six children with focal epilepsy and 20 controls (6-18 underwent EEG-fMRI. For two 10 minutes sessions subjects were told to lie still with eyes closed, as it is classically performed in adult studies ("rest sessions", for another two sessions, subjects watched a child friendly stimulation i.e. movie ("movie sessions". IED were mapped with EEG-fMRI for each session and across sessions. The resulting maps were classified as concordant/discordant with the presumed epileptogenic focus for each subject.Movement increased with scan duration, but the movie reduced movement by ~40% when played within the first 20 minutes. There was no effect of movie on the occurrence of IED, nor in the concordance of the test. Ability of EEG-fMRI to map the epileptogenic region was similar for the 20 and 40 minute scan durations. Design efficiency was predictive of concordance.A child friendly natural stimulus improves the tolerability of EEG-fMRI and reduces in-scanner movement without having an effect on IED occurrence and quality of EEG-fMRI maps. This allowed us to scan children as young as 6 and obtain localising

Analysis and correction of ballistocardiogram contamination of EEG recordings in MR

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Jaeger, L.; Hoffmann, A.; Reiser, M.F.; Werhahn, K.J.

2005-01-01

Purpose: to examine the influence of cardiac activity-related head movements and varying blood pulse frequencies on the shape of electroencephalography (EEG) recordings in a high magnetic field, and to implement a post-processing technique to eliminate cardiac activity-related artifacts. Material and methods: respiratory thoracic movements, changes of blood pulse frequency and passive head movements to 20 healthy subjects were examined outside and inside an MR magnet at rest in a simultaneously recorded 21-channel surface EEG. An electrocardiogram (ECG) was recorded simultaneously. On the basis of the correlation of the left ventricular ejection time (LVET) with the heart-rate, a post-processing heart-rate dependent subtraction of the cardiac activity-related artifacts of the EEG was developed. The quality of the post-processed EEG was tested by detecting alpha-activity in the pre- and post-processed EEGs. Results: inside the magnet, passive head motion but not respiratory thoracic movements resulted in EEG artifacts that correlated strongly with cardiac activity-related artifacts of the EEG. The blood pulse frequency influenced the appearance of the cardiac activity-related artifacts of the EEG. The removal of the cardiac activity-related artifacts of the EEG by the implemented post-processing algorithm resulted in an EEG of diagnostic quality with detected alpha-activity. Conclusion: when recording an EEG in MR environment, heart rate-dependent subtraction of EEG artifacts caused by ballistocardiogram contamination is essential to obtain EEG recordings of diagnostic quality and reliability. (orig.)

The Mozart Effect: A quantitative EEG study.

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Verrusio, Walter; Ettorre, Evaristo; Vicenzini, Edoardo; Vanacore, Nicola; Cacciafesta, Mauro; Mecarelli, Oriano

2015-09-01

The aim of this study is to investigate the influence of Mozart's music on brain activity through spectral analysis of the EEG in young healthy adults (Adults), in healthy elderly (Elderly) and in elderly with Mild Cognitive Impairment (MCI). EEG recording was performed at basal rest conditions and after listening to Mozart's K448 or "Fur Elise" Beethoven's sonatas. After listening to Mozart, an increase of alpha band and median frequency index of background alpha rhythm activity (a pattern of brain wave activity linked to memory, cognition and open mind to problem solving) was observed both in Adults and in Elderly. No changes were observed in MCI. After listening to Beethoven, no changes in EEG activity were detected. This results may be representative of the fact that said Mozart's music is able to "activate" neuronal cortical circuits related to attentive and cognitive functions. Copyright © 2015 Elsevier Inc. All rights reserved.

Effective brain network analysis with resting-state EEG data: a comparison between heroin abstinent and non-addicted subjects

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Hu, Bin; Dong, Qunxi; Hao, Yanrong; Zhao, Qinglin; Shen, Jian; Zheng, Fang

2017-08-01

Objective. Neuro-electrophysiological tools have been widely used in heroin addiction studies. Previous studies indicated that chronic heroin abuse would result in abnormal functional organization of the brain, while few heroin addiction studies have applied the effective connectivity tool to analyze the brain functional system (BFS) alterations induced by heroin abuse. The present study aims to identify the abnormality of resting-state heroin abstinent BFS using source decomposition and effective connectivity tools. Approach. The resting-state electroencephalograph (EEG) signals were acquired from 15 male heroin abstinent (HA) subjects and 14 male non-addicted (NA) controls. Multivariate autoregressive models combined independent component analysis (MVARICA) was applied for blind source decomposition. Generalized partial directed coherence (GPDC) was applied for effective brain connectivity analysis. Effective brain networks of both HA and NA groups were constructed. The two groups of effective cortical networks were compared by the bootstrap method. Abnormal causal interactions between decomposed source regions were estimated in the 1-45 Hz frequency domain. Main results. This work suggested: (a) there were clear effective network alterations in heroin abstinent subject groups; (b) the parietal region was a dominant hub of the abnormally weaker causal pathways, and the left occipital region was a dominant hub of the abnormally stronger causal pathways. Significance. These findings provide direct evidence that chronic heroin abuse induces brain functional abnormalities. The potential value of combining effective connectivity analysis and brain source decomposition methods in exploring brain alterations of heroin addicts is also implied.

The relation between electroencephalogram asymmetry and attention biases to threat at baseline and under stress

OpenAIRE

Pérez-Edgar, Koraly; Kujawa, Autumn; Nelson, S. Katherine; Cole, Claire; Zapp, Daniel J.

2013-01-01

Electroencephalogram (EEG) asymmetry in the alpha frequency band has been implicated in emotion processing and broad approach-withdrawal motivation systems. Questions remain regarding the cognitive mechanisms that may help elucidate the observed links between EEG asymmetry and patterns of socioemotional functioning. The current study observed frontal EEG asymmetry patterns at rest and under social threat among young adults (N=45, M=21.1 years). Asymmetries were, in turn, associated with perfo...

Engagement Assessment Using EEG Signals

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Li, Feng; Li, Jiang; McKenzie, Frederic; Zhang, Guangfan; Wang, Wei; Pepe, Aaron; Xu, Roger; Schnell, Thomas; Anderson, Nick; Heitkamp, Dean

2012-01-01

In this paper, we present methods to analyze and improve an EEG-based engagement assessment approach, consisting of data preprocessing, feature extraction and engagement state classification. During data preprocessing, spikes, baseline drift and saturation caused by recording devices in EEG signals are identified and eliminated, and a wavelet based method is utilized to remove ocular and muscular artifacts in the EEG recordings. In feature extraction, power spectrum densities with 1 Hz bin are calculated as features, and these features are analyzed using the Fisher score and the one way ANOVA method. In the classification step, a committee classifier is trained based on the extracted features to assess engagement status. Finally, experiment results showed that there exist significant differences in the extracted features among different subjects, and we have implemented a feature normalization procedure to mitigate the differences and significantly improved the engagement assessment performance.

Temporo-insular enhancement of EEG low and high frequencies in patients with chronic tinnitus. QEEG study of chronic tinnitus patients

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Weisz Nathan

2010-03-01

Full Text Available Abstract Background The physiopathological mechanism underlying the tinnitus phenomenon is still the subject of an ongoing debate. Since oscillatory EEG activity is increasingly recognized as a fundamental hallmark of cortical integrative functions, this study investigates deviations from the norm of different resting EEG parameters in patients suffering from chronic tinnitus. Results Spectral parameters of resting EEG of male tinnitus patients (n = 8, mean age 54 years were compared to those of age-matched healthy males (n = 15, mean age 58.8 years. On average, the patient group exhibited higher spectral power over the frequency range of 2-100 Hz. Using LORETA source analysis, the generators of delta, theta, alpha and beta power increases were localized dominantly to left auditory (Brodmann Areas (BA 41,42, 22, temporo-parietal, insular posterior, cingulate anterior and parahippocampal cortical areas. Conclusions Tinnitus patients show a deviation from the norm of different resting EEG parameters, characterized by an overproduction of resting state delta, theta and beta brain activities, providing further support for the microphysiological and magnetoencephalographic evidence pointing to a thalamocortical dysrhythmic process at the source of tinnitus. These results also provide further confirmation that reciprocal involvements of both auditory and associative/paralimbic areas are essential in the generation of tinnitus.

[Electroencephalographic characteristic of cognitive-specific alerting attention in verbal learning--III: Localized characteristics of EEG spatial synchronization].

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Dan'ko, S G; Kachalova, L M; Solov'eva, M L

2010-01-01

Electroencephalograms (EEG) were recorder in 19 standard derivations in 88 healthy subjects, while they were in the states: rest with eyes open; memorization (learning) of verbal bilingual semantic pairs (Latin and Russian languages); the retrieval of the rote information from memory (control). We compared estimates of EEG coherence in these states for the frequency bands theta (4-7 Hz), alpha-1 (7-10 Hz), alpha-2 (10-13 Hz), beta-1 (13-18 Hz), beta-2 (18-30 Hz), gamma (30-40 Hz). When compared with the rest most strongly expressed: for memorization a decrease of coherence in the pairs of derivations from frontal and central areas of the cortex in the EEG frequency bands; for retrieval an increase of coherence in interhemispheric derivation pairs of pariental-occipital region in majority of the frequency bands. For the retrieval also increases of coherence in the beta2 and gamma bands, along with coherence decreases at low frequencies take place in pairs formed by derivations from the parieto-occipital region with derivations from the frontal and the central ones. Dynamics of EEG coherence in comparisons of memorization and retrieval from the rest and each are expressed significantly more in the interhemispheric and crosshemispheric pairs of derivations than in the intrahemispheric pairs. Revealed topographic specificity of the dynamics of EEG coherence by changing the states is considered in terms of ideas about cognitive-specific forms of sustained goal-directed mental attention.

Spontaneous Slow Fluctuation of EEG Alpha Rhythm Reflects Activity in Deep-Brain Structures: A Simultaneous EEG-fMRI Study.

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Kei Omata

Full Text Available The emergence of the occipital alpha rhythm on brain electroencephalogram (EEG is associated with brain activity in the cerebral neocortex and deep brain structures. To further understand the mechanisms of alpha rhythm power fluctuation, we performed simultaneous EEGs and functional magnetic resonance imaging recordings in human subjects during a resting state and explored the dynamic relationship between alpha power fluctuation and blood oxygenation level-dependent (BOLD signals of the brain. Based on the frequency characteristics of the alpha power time series (APTS during 20-minute EEG recordings, we divided the APTS into two components: fast fluctuation (0.04-0.167 Hz and slow fluctuation (0-0.04 Hz. Analysis of the correlation between the MRI signal and each component revealed that the slow fluctuation component of alpha power was positively correlated with BOLD signal changes in the brain stem and the medial part of the thalamus and anterior cingulate cortex, while the fast fluctuation component was correlated with the lateral part of the thalamus and the anterior cingulate cortex, but not the brain stem. In summary, these data suggest that different subcortical structures contribute to slow and fast modulations of alpha spectra on brain EEG.

Quantitative change of EEG and respiration signals during mindfulness meditation

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2014-01-01

Background This study investigates measures of mindfulness meditation (MM) as a mental practice, in which a resting but alert state of mind is maintained. A population of older people with high stress level participated in this study, while electroencephalographic (EEG) and respiration signals were recorded during a MM intervention. The physiological signals during meditation and control conditions were analyzed with signal processing. Methods EEG and respiration data were collected and analyzed on 34 novice meditators after a 6-week meditation intervention. Collected data were analyzed with spectral analysis, phase analysis and classification to evaluate an objective marker for meditation. Results Different frequency bands showed differences in meditation and control conditions. Furthermore, we established a classifier using EEG and respiration signals with a higher accuracy (85%) at discriminating between meditation and control conditions than a classifier using the EEG signal only (78%). Conclusion Support vector machine (SVM) classifier with EEG and respiration feature vector is a viable objective marker for meditation ability. This classifier should be able to quantify different levels of meditation depth and meditation experience in future studies. PMID:24939519

Local and Widely Distributed EEG Activity in Schizophrenia With Prevalence of Negative Symptoms.

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Grin-Yatsenko, Vera A; Ponomarev, Valery A; Pronina, Marina V; Poliakov, Yury I; Plotnikova, Irina V; Kropotov, Juri D

2017-09-01

We evaluated EEG frequency abnormalities in resting state (eyes closed and eyes open) EEG in a group of chronic schizophrenia patients as compared with healthy subjects. The study included 3 methods of analysis of deviation of EEG characteristics: genuine EEG, current source density (CSD), and group independent component (gIC). All 3 methods have shown that the EEG in schizophrenia patients is characterized by enhanced low-frequency (delta and theta) and high-frequency (beta) activity in comparison with the control group. However, the spatial pattern of differences was dependent on the type of method used. Comparative analysis has shown that increased EEG power in schizophrenia patients apparently concerns both widely spatially distributed components and local components of signal. Furthermore, the observed differences in the delta and theta range can be described mainly by the local components, and those in the beta range mostly by spatially widely distributed ones. The possible nature of the widely distributed activity is discussed.

NIRS-EEG joint imaging during transcranial direct current stimulation: Online parameter estimation with an autoregressive model.

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Sood, Mehak; Besson, Pierre; Muthalib, Makii; Jindal, Utkarsh; Perrey, Stephane; Dutta, Anirban; Hayashibe, Mitsuhiro

2016-12-01

Transcranial direct current stimulation (tDCS) has been shown to perturb both cortical neural activity and hemodynamics during (online) and after the stimulation, however mechanisms of these tDCS-induced online and after-effects are not known. Here, online resting-state spontaneous brain activation may be relevant to monitor tDCS neuromodulatory effects that can be measured using electroencephalography (EEG) in conjunction with near-infrared spectroscopy (NIRS). We present a Kalman Filter based online parameter estimation of an autoregressive (ARX) model to track the transient coupling relation between the changes in EEG power spectrum and NIRS signals during anodal tDCS (2mA, 10min) using a 4×1 ring high-definition montage. Our online ARX parameter estimation technique using the cross-correlation between log (base-10) transformed EEG band-power (0.5-11.25Hz) and NIRS oxy-hemoglobin signal in the low frequency (≤0.1Hz) range was shown in 5 healthy subjects to be sensitive to detect transient EEG-NIRS coupling changes in resting-state spontaneous brain activation during anodal tDCS. Conventional sliding window cross-correlation calculations suffer a fundamental problem in computing the phase relationship as the signal in the window is considered time-invariant and the choice of the window length and step size are subjective. Here, Kalman Filter based method allowed online ARX parameter estimation using time-varying signals that could capture transients in the coupling relationship between EEG and NIRS signals. Our new online ARX model based tracking method allows continuous assessment of the transient coupling between the electrophysiological (EEG) and the hemodynamic (NIRS) signals representing resting-state spontaneous brain activation during anodal tDCS. Published by Elsevier B.V.

On the invariance of EEG-based signatures of individuality with application in biometric identification.

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Yunqi Wang; Najafizadeh, Laleh

2016-08-01

One of the main challenges in EEG-based biometric systems is to extract reliable signatures of individuality from recorded EEG data that are also invariant against time. In this paper, we investigate the invariability of features that are extracted based on the spatial distribution of the spectral power of EEG data corresponding to 2-second eyes-closed resting-state (ECRS) recording, in different scenarios. Eyes-closed resting-state EEG signals in 4 healthy adults are recorded in two different sessions with an interval of at least one week between sessions. The performance in terms of correct recognition rate (CRR) is examined when the training and testing datasets are chosen from the same recording session, and when the training and testing datasets are chosen from different sessions. It is shown that an CRR of 92% can be achieved based on the proposed features when the training and testing datasets are taken from different sessions. To reduce the number of recording channels, principal component analysis (PCA) is also employed to identify channels that carry the most discriminatory information across individuals. High CRR is obtained based on the data from channels mostly covering the occipital region. The results suggest that features based on the spatial distribution of the spectral power of the short-time (e.g. 2 seconds) ECRS recordings can have great potentials in EEG-based biometric identification systems.

Why some people discount more than others: Baseline activation in the dorsal PFC mediates the link between COMT genotype and impatient choice

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Lorena R. R. Gianotti

2012-05-01

Full Text Available Individuals differ widely in how steeply they discount future rewards. The sources of these stable individual differences in delay discounting (DD are largely unknown. One candidate is the COMT Val158Met polymorphism, known to modulate prefrontal dopamine levels and affect DD. To identify possible neural mechanisms by which this polymorphism may contribute to stable individual DD differences, we measured 73 participants’ neural baseline activation using resting electroencephalogram (EEG. Such neural baseline activation measures are highly heritable and stable over time, thus an ideal endophenotype candidate to explain how genes may influence behavior via individual differences in neural function. After EEG-recording, participants made a series of incentive-compatible intertemporal choices to determine the steepness of their DD. We found that COMT significantly affected DD and that this effect was mediated by baseline activation level in the left dorsal prefrontal cortex (DPFC: (i COMT had a significant effect on DD such that the number of Val alleles was positively correlated with steeper DD (higher numbers of Val alleles means greater COMT activity and thus lower dopamine levels. (ii A whole-brain search identified a cluster in left DPFC where baseline activation was correlated with DD; lower activation was associated with steeper DD. (iii COMT had a significant effect on the baseline activation level in this left DPFC cluster such that a higher number of Val alleles was associated with lower baseline activation. (iv The effect of COMT on DD was explained by the mediating effect of neural baseline activation in the left DPFC cluster. Our study thus establishes baseline activation level in left DPFC as salient neural signature in the form of an endophenotype that mediates the link between COMT and DD.

Absence of early epileptiform abnormalities predicts lack of seizures on continuous EEG.

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Shafi, Mouhsin M; Westover, M Brandon; Cole, Andrew J; Kilbride, Ronan D; Hoch, Daniel B; Cash, Sydney S

2012-10-23

To determine whether the absence of early epileptiform abnormalities predicts absence of later seizures on continuous EEG monitoring of hospitalized patients. We retrospectively reviewed 242 consecutive patients without a prior generalized convulsive seizure or active epilepsy who underwent continuous EEG monitoring lasting at least 18 hours for detection of nonconvulsive seizures or evaluation of unexplained altered mental status. The findings on the initial 30-minute screening EEG, subsequent continuous EEG recordings, and baseline clinical data were analyzed. We identified early EEG findings associated with absence of seizures on subsequent continuous EEG. Seizures were detected in 70 (29%) patients. A total of 52 patients had their first seizure in the initial 30 minutes of continuous EEG monitoring. Of the remaining 190 patients, 63 had epileptiform discharges on their initial EEG, 24 had triphasic waves, while 103 had no epileptiform abnormalities. Seizures were later detected in 22% (n = 14) of studies with epileptiform discharges on their initial EEG, vs 3% (n = 3) of the studies without epileptiform abnormalities on initial EEG (p monitoring is necessary.

Resting-state EEG oscillatory dynamics in fragile X syndrome: abnormal functional connectivity and brain network organization.

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Melle J W van der Molen

Full Text Available Disruptions in functional connectivity and dysfunctional brain networks are considered to be a neurological hallmark of neurodevelopmental disorders. Despite the vast literature on functional brain connectivity in typical brain development, surprisingly few attempts have been made to characterize brain network integrity in neurodevelopmental disorders. Here we used resting-state EEG to characterize functional brain connectivity and brain network organization in eight males with fragile X syndrome (FXS and 12 healthy male controls. Functional connectivity was calculated based on the phase lag index (PLI, a non-linear synchronization index that is less sensitive to the effects of volume conduction. Brain network organization was assessed with graph theoretical analysis. A decrease in global functional connectivity was observed in FXS males for upper alpha and beta frequency bands. For theta oscillations, we found increased connectivity in long-range (fronto-posterior and short-range (frontal-frontal and posterior-posterior clusters. Graph theoretical analysis yielded evidence of increased path length in the theta band, suggesting that information transfer between brain regions is particularly impaired for theta oscillations in FXS. These findings are discussed in terms of aberrant maturation of neuronal oscillatory dynamics, resulting in an imbalance in excitatory and inhibitory neuronal circuit activity.

Education research: evaluating the use of podcasting for residents during EEG instruction: a pilot study.

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Bensalem-Owen, Meriem; Chau, Destiny F; Sardam, Sean C; Fahy, Brenda G

2011-08-23

Educational methods for residents are shifting toward greater learner independence aided by technological advances. A Web-based program using a podcast was created for resident EEG instruction, replacing conventional didactics. The EEG curriculum also consisted of EEG interpretations under the tutelage of a neurophysiologist. This pilot study aimed to objectively evaluate the effectiveness of the podcast as a new teaching tool. A podcast for resident EEG instruction was implemented on the Web, replacing the traditional lecture. After Institutional Review Board approval, consent was obtained from the participating residents. Using 25-question evaluation tools, participants were assessed at baseline before any EEG instruction, and reassessed after podcasting and after 10 clinical EEG exposures. Each 25-item evaluation tool contained tracings used for clinical EEG interpretations. Scores after podcast training were also compared to scores after traditional didactic training from a previous study among anesthesiology trainees. Ten anesthesiology residents completed the study. The mean scores with standard deviations are 9.50 ± 2.92 at baseline, 13.40 ± 3.31 (p = 0.034) after the podcast, and 16.20 ± 1.87 (p = 0.019) after interpreting 10 EEGs. No differences were noted between the mean educational tool scores for those who underwent podcasting training compared to those who had undergone traditional didactic training. In this pilot study, podcast training was as effective as the prior conventional lecture in meeting the curricular goals of increasing EEG knowledge after 10 EEG interpretations as measured by assessment tools.

Children's Depressive Symptoms in Relation to EEG Frontal Asymmetry and Maternal Depression

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Feng, Xin; Forbes, Erika E.; Kovacs, Maria; George, Charles J.; Lopez-Duran, Nestor L.; Fox, Nathan A.; Cohn, Jeffrey F.

2012-01-01

This study examined the relations of school-age children's depressive symptoms, frontal EEG asymmetry, and maternal history of childhood-onset depression (COD). Participants were 73 children, 43 of whom had mothers with COD. Children's EEG was recorded at baseline and while watching happy and sad film clips. Depressive symptoms were measured using…

Measuring alterations in oscillatory brain networks in schizophrenia with resting-state MEG: State-of-the-art and methodological challenges.

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Alamian, Golnoush; Hincapié, Ana-Sofía; Pascarella, Annalisa; Thiery, Thomas; Combrisson, Etienne; Saive, Anne-Lise; Martel, Véronique; Althukov, Dmitrii; Haesebaert, Frédéric; Jerbi, Karim

2017-09-01

Neuroimaging studies provide evidence of disturbed resting-state brain networks in Schizophrenia (SZ). However, untangling the neuronal mechanisms that subserve these baseline alterations requires measurement of their electrophysiological underpinnings. This systematic review specifically investigates the contributions of resting-state Magnetoencephalography (MEG) in elucidating abnormal neural organization in SZ patients. A systematic literature review of resting-state MEG studies in SZ was conducted. This literature is discussed in relation to findings from resting-state fMRI and EEG, as well as to task-based MEG research in SZ population. Importantly, methodological limitations are considered and recommendations to overcome current limitations are proposed. Resting-state MEG literature in SZ points towards altered local and long-range oscillatory network dynamics in various frequency bands. Critical methodological challenges with respect to experiment design, and data collection and analysis need to be taken into consideration. Spontaneous MEG data show that local and global neural organization is altered in SZ patients. MEG is a highly promising tool to fill in knowledge gaps about the neurophysiology of SZ. However, to reach its fullest potential, basic methodological challenges need to be overcome. MEG-based resting-state power and connectivity findings could be great assets to clinical and translational research in psychiatry, and SZ in particular. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

The effects of cardiorespiratory fitness and acute aerobic exercise on executive functioning and EEG entropy in adolescents

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Michael John Hogan

2015-10-01

Full Text Available The current study examined the effects of cardiorespiratory fitness, identified with a continuous graded cycle ergometry, and aerobic exercise on cognitive functioning and entropy of the electroencephalogram (EEG in 30 adolescents between the ages of 13 and 14 years. Higher and lower fit participants performed an executive function task after a bout of acute exercise and after rest while watching a film. EEG entropy, using the sample entropy measure, was repeatedly measured during the 1500ms post-stimulus interval to evaluate changes in entropy over time. Analysis of the behavioural data for lower and higher fit groups revealed an interaction between fitness levels and acute physical exercise. Notably, lower fit, but not higher fit, participants had higher error rates for NoGo relative to Go trials in the rest condition, whereas in the acute exercise condition there were no differences in error rates between groups; higher fit participants also had significantly faster reaction times in the exercise condition in comparison with the rest condition. Analysis of EEG data revealed that higher fit participants demonstrated lower entropy post-stimulus than lower fit participants in the left frontal hemisphere, possibly indicating increased efficiency of early stage stimulus processing and more efficient allocation of cognitive resources to the task demands. The results suggest that EEG entropy is sensitive to stimulus processing demands and varies as a function of physical fitness levels, but not acute exercise. Physical fitness, in turn, may enhance cognition in adolescence by facilitating higher functionality of the attentional system in the context of lower levels of frontal EEG entropy.

Hearing the Sound in the Brain: Influences of Different EEG References

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Dan Wu

2018-03-01

Full Text Available If the scalp potential signals, the electroencephalogram (EEG, are due to neural “singers” in the brain, how could we listen to them with less distortion? One crucial point is that the data recording on the scalp should be faithful and accurate, thus the choice of reference electrode is a vital factor determining the faithfulness of the data. In this study, music on the scalp derived from data in the brain using three different reference electrodes were compared, including approximate zero reference—reference electrode standardization technique (REST, average reference (AR, and linked mastoids reference (LM. The classic music pieces in waveform format were used as simulated sources inside a head model, and they were forward calculated to scalp as standard potential recordings, i.e., waveform format music from the brain with true zero reference. Then these scalp music was re-referenced into REST, AR, and LM based data, and compared with the original forward data (true zero reference. For real data, the EEG recorded in an orthodontic pain control experiment were utilized for music generation with the three references, and the scale free index (SFI of these music pieces were compared. The results showed that in the simulation for only one source, different references do not change the music/waveform; for two sources or more, REST provide the most faithful music/waveform to the original ones inside the brain, and the distortions caused by AR and LM were spatial locations of both source and scalp electrode dependent. The brainwave music from the real EEG data showed that REST and AR make the differences of SFI between two states more recognized and found the frontal is the main region that producing the music. In conclusion, REST can reconstruct the true signals approximately, and it can be used to help to listen to the true voice of the neural singers in the brain.

EEG source imaging during two Qigong meditations.

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Faber, Pascal L; Lehmann, Dietrich; Tei, Shisei; Tsujiuchi, Takuya; Kumano, Hiroaki; Pascual-Marqui, Roberto D; Kochi, Kieko

2012-08-01

Experienced Qigong meditators who regularly perform the exercises "Thinking of Nothing" and "Qigong" were studied with multichannel EEG source imaging during their meditations. The intracerebral localization of brain electric activity during the two meditation conditions was compared using sLORETA functional EEG tomography. Differences between conditions were assessed using t statistics (corrected for multiple testing) on the normalized and log-transformed current density values of the sLORETA images. In the EEG alpha-2 frequency, 125 voxels differed significantly; all were more active during "Qigong" than "Thinking of Nothing," forming a single cluster in parietal Brodmann areas 5, 7, 31, and 40, all in the right hemisphere. In the EEG beta-1 frequency, 37 voxels differed significantly; all were more active during "Thinking of Nothing" than "Qigong," forming a single cluster in prefrontal Brodmann areas 6, 8, and 9, all in the left hemisphere. Compared to combined initial-final no-task resting, "Qigong" showed activation in posterior areas whereas "Thinking of Nothing" showed activation in anterior areas. The stronger activity of posterior (right) parietal areas during "Qigong" and anterior (left) prefrontal areas during "Thinking of Nothing" may reflect a predominance of self-reference, attention and input-centered processing in the "Qigong" meditation, and of control-centered processing in the "Thinking of Nothing" meditation.

Baseline brain activity changes in patients with clinically isolated syndrome revealed by resting-state functional MRI

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Liu, Yaou; Duan, Yunyun; Liang, Peipeng; Jia, Xiuqin; Yu, Chunshui [Dept. of Radiology, Xuanwu Hospital, Capital Medical Univ., Beijing (China); Ye, Jing [Dept. of Neurology, Xuanwu Hospital, Capital Medical Univ., Beijing (China); Butzkueven, Helmut [Dept. of Medicine, Univ. of Melbourne, Melbourne (Australia); Dong, Huiqing [Dept. of Neurology, Xuanwu Hospital, Capital Medical Univ., Beijing (China); Li, Kuncheng [Dept. of Radiology, Xuanwu Hospital, Capital Medical Univ., Beijing (China); Beijing Key Laboratory of MRI and Brain Informatics, Beijing (China)], E-mail: likuncheng1955@yahoo.com.cn

2012-11-15

Background A clinically isolated syndrome (CIS) is the first manifestation of multiple sclerosis (MS). Previous task-related functional MRI studies demonstrate functional reorganization in patients with CIS. Purpose To assess baseline brain activity changes in patients with CIS by using the technique of regional amplitude of low frequency fluctuation (ALFF) as an index in resting-state fMRI. Material and Methods Resting-state fMRIs data acquired from 37 patients with CIS and 37 age- and sex-matched normal controls were compared to investigate ALFF differences. The relationships between ALFF in regions with significant group differences and the EDSS (Expanded Disability Status Scale), disease duration, and T2 lesion volume (T2LV) were further explored. Results Patients with CIS had significantly decreased ALFF in the right anterior cingulate cortex, right caudate, right lingual gyrus, and right cuneus (P < 0.05 corrected for multiple comparisons using Monte Carlo simulation) compared to normal controls, while no significantly increased ALFF were observed in CIS. No significant correlation was found between the EDSS, disease duration, T2LV, and ALFF in regions with significant group differences. Conclusion In patients with CIS, resting-state fMRI demonstrates decreased activity in several brain regions. These results are in contrast to patients with established MS, in whom ALFF demonstrates several regions of increased activity. It is possible that this shift from decreased activity in CIS to increased activity in MS could reflect the dynamics of cortical reorganization.

Low Motivational Incongruence Predicts Successful EEG Resting-state Neurofeedback Performance in Healthy Adults.

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Diaz Hernandez, Laura; Rieger, Kathryn; Koenig, Thomas

2018-05-15

Neurofeedback is becoming increasingly sophisticated and widespread, although predictors of successful performance still remain scarce. Here, we explored the possible predictive value of psychological factors and report the results obtained from a neurofeedback training study designed to enhance the self-regulation of spontaneous EEG microstates of a particular type (microstate class D). Specifically, we were interested in life satisfaction (including motivational incongruence), body awareness, personality and trait anxiety. These variables were quantified with questionnaires before neurofeedback. Individual neurofeedback success was established by means of linear mixed models that accounted for the amount of observed target state (microstate class D contribution) as a function of time and training condition: baseline, training and transfer (results shown in Diaz Hernandez et al.). We found a series of significant negative correlations between motivational incongruence and mean percentage increase of microstate D during the condition transfer, across-sessions (36% of common variance) and mean percentage increase of microstate D during the condition training, within-session (42% of common variance). There were no significant correlations related to other questionnaires, besides a trend in a sub-scale of the Life Satisfaction questionnaire. We conclude that motivational incongruence may be a potential predictor for neurofeedback success, at least in the current protocol. The finding may be explained by the interfering effect on neurofeedback performance produced by incompatible simultaneously active psychological processes, which are indirectly measured by the Motivational Incongruence questionnaire. Copyright © 2016. Published by Elsevier Ltd.

Detrended Fluctuation Analysis of the Human EEG during Listening to Emotional Music

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无

2007-01-01

A nonlinear method named detrended fluctuation analysis (DFA) was utilized to investigate the scaling behavior of the human electroencephalogram (EEG) in three emotional music conditions (fear, happiness, sadness) and a rest condition (eyes-closed). The results showed that the EEG exhibited scaling behavior in two regions with two scaling exponents β1 and β2 which represented the complexity of higher and lower frequency activity besides β band respectively. As the emotional intensity decreased the value of β1 increased and the value of β2 decreased. The change of β1 was weakly correlated with the 'approach-withdrawal' model of emotion and both of fear and sad music made certain differences compared with the eyes-closed rest condition. The study shows that music is a powerful elicitor of emotion and that using nonlinear method can potentially contribute to the investigation of emotion.

Soft drink effects on sensorimotor rhythm brain computer interface performance and resting-state spectral power.

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Mundahl, John; Jianjun Meng; He, Jeffrey; Bin He

2016-08-01

Brain-computer interface (BCI) systems allow users to directly control computers and other machines by modulating their brain waves. In the present study, we investigated the effect of soft drinks on resting state (RS) EEG signals and BCI control. Eight healthy human volunteers each participated in three sessions of BCI cursor tasks and resting state EEG. During each session, the subjects drank an unlabeled soft drink with either sugar, caffeine, or neither ingredient. A comparison of resting state spectral power shows a substantial decrease in alpha and beta power after caffeine consumption relative to control. Despite attenuation of the frequency range used for the control signal, caffeine average BCI performance was the same as control. Our work provides a useful characterization of caffeine, the world's most popular stimulant, on brain signal frequencies and their effect on BCI performance.

Mining Time-Resolved Functional Brain Graphs to an EEG-Based Chronnectomic Brain Aged Index (CBAI

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Stavros I. Dimitriadis

2017-09-01

Full Text Available The brain at rest consists of spatially and temporal distributed but functionally connected regions that called intrinsic connectivity networks (ICNs. Resting state electroencephalography (rs-EEG is a way to characterize brain networks without confounds associated with task EEG such as task difficulty and performance. A novel framework of how to study dynamic functional connectivity under the notion of functional connectivity microstates (FCμstates and symbolic dynamics is further discussed. Furthermore, we introduced a way to construct a single integrated dynamic functional connectivity graph (IDFCG that preserves both the strength of the connections between every pair of sensors but also the type of dominant intrinsic coupling modes (DICM. The whole methodology is demonstrated in a significant and unexplored task for EEG which is the definition of an objective Chronnectomic Brain Aged index (CBAI extracted from resting-state data (N = 94 subjects with both eyes-open and eyes-closed conditions. Novel features have been defined based on symbolic dynamics and the notion of DICM and FCμstates. The transition rate of FCμstates, the symbolic dynamics based on the evolution of FCμstates (the Markovian Entropy, the complexity index, the probability distribution of DICM, the novel Flexibility Index that captures the dynamic reconfiguration of DICM per pair of EEG sensors and the relative signal power constitute a valuable pool of features that can build the proposed CBAI. Here we applied a feature selection technique and Extreme Learning Machine (ELM classifier to discriminate young adults from middle-aged and a Support Vector Regressor to build a linear model of the actual age based on EEG-based spatio-temporal features. The most significant type of features for both prediction of age and discrimination of young vs. adults age groups was the dynamic reconfiguration of dominant coupling modes derived from a subset of EEG sensor pairs. Specifically

Frontal alpha EEG asymmetry before and after behavioral activation treatment for depression.

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Gollan, Jackie K; Hoxha, Denada; Chihade, Dietta; Pflieger, Mark E; Rosebrock, Laina; Cacioppo, John

2014-05-01

Mid-frontal and mid-lateral (F3/F4 and F7/F8) EEG asymmetry has been associated with motivation and affect. We examined alpha EEG asymmetry in depressed and healthy participants before and after Behavioral Activation treatment for depression; examined the association between alpha EEG asymmetry and motivational systems and affect; and evaluated the utility of alpha EEG asymmetry in predicting remission. Depressed (n=37) and healthy participants (n=35) were assessed before and after treatment using a clinical interview, a task to measure baseline EEG, and questionnaires of behavioral activation and inhibition, avoidance, and affect. Alpha EEG asymmetry was significantly higher in depressed than healthy participants at pre-treatment, positively correlated with negative affect and behavioral inhibition, and inversely correlated with lower behavioral activation sensitivity. Heightened alpha EEG asymmetry in depressed participants was significantly associated with increased behavioral inhibition and negative emotion and was independent of clinical remission. Copyright © 2014 Elsevier B.V. All rights reserved.

EEG biofeedback

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Dvořáček, Michael

2010-01-01

Vznik EEG aktivity v mozku, rozdělení EEG vln podle frekvence, způsob měření EEG, přístroje pro měření EEG. Dále popis biofeedback metody, její možnosti a návrh biofeedback her. Popis zpracování naměřených EEG signálů. EEG generation, brain rhythms, methods of recording EEG, EEG recorder. Description of biofeedback, potentialities of biofeedback, proposal of biofeedback games. Description of processing measured EEG signals. B

Parametric and Nonparametric EEG Analysis for the Evaluation of EEG Activity in Young Children with Controlled Epilepsy

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Vangelis Sakkalis

2008-01-01

Full Text Available There is an important evidence of differences in the EEG frequency spectrum of control subjects as compared to epileptic subjects. In particular, the study of children presents difficulties due to the early stages of brain development and the various forms of epilepsy indications. In this study, we consider children that developed epileptic crises in the past but without any other clinical, psychological, or visible neurophysiological findings. The aim of the paper is to develop reliable techniques for testing if such controlled epilepsy induces related spectral differences in the EEG. Spectral features extracted by using nonparametric, signal representation techniques (Fourier and wavelet transform and a parametric, signal modeling technique (ARMA are compared and their effect on the classification of the two groups is analyzed. The subjects performed two different tasks: a control (rest task and a relatively difficult math task. The results show that spectral features extracted by modeling the EEG signals recorded from individual channels by an ARMA model give a higher discrimination between the two subject groups for the control task, where classification scores of up to 100% were obtained with a linear discriminant classifier.

Increase of EEG spectral theta power indicates higher risk of the development of severe cognitive decline in Parkinson’s disease after 3 years

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Vitalii V Cozac

2016-11-01

Full Text Available Objective: We investigated quantitative electroencephalography (qEEG and clinical parameters as potential risk factors of severe cognitive decline in Parkinson’s disease.Methods: We prospectively investigated 37 patients with Parkinson’s disease at baseline and follow-up (after 3 years. Patients had no severe cognitive impairment at baseline. We used a summary score of cognitive tests as the outcome at follow-up. At baseline we assessed motor, cognitive, and psychiatric factors; qEEG variables (global relative median power spectra were obtained by a fully automated processing of high-resolution EEG (256-channels. We used linear regression models with calculation of the explained variance to evaluate the relation of baseline parameters with cognitive deterioration.Results: The following baseline parameters significantly predicted severe cognitive decline: global relative median power theta (4-8 Hz, cognitive task performance in executive functions and working memory.Conclusions: Combination of neurocognitive tests and qEEG improves identification of patients with higher risk of cognitive decline in PD.

Association of autonomic nervous system and EEG scalp potential during playing 2D Grand Turismo 5.

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Subhani, Ahmad Rauf; Likun, Xia; Saeed Malik, Aamir

2012-01-01

Cerebral activation and autonomic nervous system have importance in studies such as mental stress. The aim of this study is to analyze variations in EEG scalp potential which may influence autonomic activation of heart while playing video games. Ten healthy participants were recruited in this study. Electroencephalogram (EEG) and electrocardiogram (ECG) signals were measured simultaneously during playing video game and rest conditions. Sympathetic and parasympathetic innervations of heart were evaluated from heart rate variability (HRV), derived from the ECG. Scalp potential was measured by the EEG. The results showed a significant upsurge in the value theta Fz/alpha Pz (p<0.001) while playing game. The results also showed tachycardia while playing video game as compared to rest condition (p<0.005). Normalized low frequency power and ratio of low frequency/high frequency power were significantly increased while playing video game and normalized high frequency power sank during video games. Results showed synchronized activity of cerebellum and sympathetic and parasympathetic innervation of heart.

Extracting attempted hand movements from EEGs in people with complete hand paralysis following stroke

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Abirami eMuralidharan

2011-03-01

Full Text Available This study examines the feasibility of using electroencephalograms (EEGs to rapidly detect the intent to open one’s hand in individuals with complete hand paralysis following a subcortical ischemic stroke. If detectable, this motor planning activity could be used in real time to trigger a motorized hand exoskeleton or an electrical stimulation device that opens/closes the hand. While EEG-triggered movement-assist devices could restore function, they may also promote recovery by reinforcing the use of remaining cortical circuits. EEGs were recorded while participants were cued to either relax or attempt to extend their fingers. Linear discriminant analysis was used to detect onset of finger extension from the EEGs in a leave-one-trial-out cross-validation process. In each testing trial, the classifier was applied in pseudo real time starting from an initial hand-relaxed phase, through movement planning, and into the initial attempted finger extension phase (finger extension phase estimated from typical time-to-movement-onset measured in the unaffected hand. The classifiers detected attempted finger-extension at a significantly higher rate during both motor planning and early attempted execution compared to rest. To reduce inappropriate triggering of a movement-assist device during rest, the classification threshold could be adjusted to require more certainty about one’s intent to move before triggering a device. Additionally, a device could be set to activate only after multiple time samples in a row were classified as finger extension events. These options resulted in some sessions with no false triggers while the person was resting, but moderate-to-high true trigger rates during attempted movements.

EEG Signal Quality of a Subcutaneous Recording System Compared to Standard Surface Electrodes

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Jonas Duun-Henriksen

2015-01-01

Full Text Available Purpose. We provide a comprehensive verification of a new subcutaneous EEG recording device which promises robust and unobtrusive measurements over ultra-long time periods. The approach is evaluated against a state-of-the-art surface EEG electrode technology. Materials and Methods. An electrode powered by an inductive link was subcutaneously implanted on five subjects. Surface electrodes were placed at sites corresponding to the subcutaneous electrodes, and the EEG signals were evaluated with both quantitative (power spectral density and coherence analysis and qualitative (blinded subjective scoring by neurophysiologists analysis. Results. The power spectral density and coherence analysis were very similar during measurements of resting EEG. The scoring by neurophysiologists showed a higher EEG quality for the implanted system for different subject states (eyes open and eyes closed. This was most likely due to higher amplitude of the subcutaneous signals. During periods with artifacts, such as chewing, blinking, and eye movement, the two systems performed equally well. Conclusions. Subcutaneous measurements of EEG with the test device showed high quality as measured by both quantitative and more subjective qualitative methods. The signal might be superior to surface EEG in some aspects and provides a method of ultra-long term EEG recording in situations where this is required and where a small number of EEG electrodes are sufficient.

Neuronal correlates of maladaptive coping: an EEG-study in tinnitus patients.

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Sven Vanneste

Full Text Available Here we aimed to investigate the neuronal correlates of different coping styles in patients suffering from chronic tinnitus. Adaptive and maladaptive coping styles were determined in 85 tinnitus patients. Based on resting state EEG recordings, coping related differences in brain activity and connectivity were found. Maladaptive coping behavior was related to increases in subjective tinnitus loudness and distress, higher tinnitus severity and higher depression scores. EEG recordings demonstrated increased alpha activity over the left dorsolateral prefrontal cortex (DLPFC and subgenual anterior cingulate cortex (sgACC as well as increased connectivity in the default (i.e. resting state network in tinnitus patients with a maladaptive coping style. Correlation analysis revealed that the changes in the DLPFC correlate primarily with maladaptive coping behavior, whereas the changes in the sgACC correlate with tinnitus severity and depression. Our findings are in line with previous research in the field of depression that during resting state a alpha band hyperconnectivity exists within the default network for patients who use a maladaptive coping style, with the sgACC as the dysfunctional node and that the strength of the connectivity is related to focusing on negative mood and catastrophizing about the consequences of tinnitus.

Diagnostic Accuracy of microEEG: A Miniature, Wireless EEG Device

OpenAIRE

Grant, Arthur C.; Abdel-Baki, Samah G.; Omurtag, Ahmet; Sinert, Richard; Chari, Geetha; Malhotra, Schweta; Weedon, Jeremy; Fenton, Andre A.; Zehtabchi, Shahriar

2014-01-01

Measuring the diagnostic accuracy (DA) of an EEG device is unconventional and complicated by imperfect interrater reliability. We sought to compare the DA of a miniature, wireless, battery-powered EEG device (“microEEG”) to a reference EEG machine in emergency department (ED) patients with altered mental status (AMS). 225 ED patients with AMS underwent 3 EEGs. EEG1 (Nicolet Monitor, “reference”) and EEG2 (microEEG) were recorded simultaneously with EEG cup electrodes using a signal splitter. ...

Broadband Electrophysiological Dynamics Contribute to Global Resting-State fMRI Signal.

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Wen, Haiguang; Liu, Zhongming

2016-06-01

Spontaneous activity observed with resting-state fMRI is used widely to uncover the brain's intrinsic functional networks in health and disease. Although many networks appear modular and specific, global and nonspecific fMRI fluctuations also exist and both pose a challenge and present an opportunity for characterizing and understanding brain networks. Here, we used a multimodal approach to investigate the neural correlates to the global fMRI signal in the resting state. Like fMRI, resting-state power fluctuations of broadband and arrhythmic, or scale-free, macaque electrocorticography and human magnetoencephalography activity were correlated globally. The power fluctuations of scale-free human electroencephalography (EEG) were coupled with the global component of simultaneously acquired resting-state fMRI, with the global hemodynamic change lagging the broadband spectral change of EEG by ∼5 s. The levels of global and nonspecific fluctuation and synchronization in scale-free population activity also varied across and depended on arousal states. Together, these results suggest that the neural origin of global resting-state fMRI activity is the broadband power fluctuation in scale-free population activity observable with macroscopic electrical or magnetic recordings. Moreover, the global fluctuation in neurophysiological and hemodynamic activity is likely modulated through diffuse neuromodulation pathways that govern arousal states and vigilance levels. This study provides new insights into the neural origin of resting-state fMRI. Results demonstrate that the broadband power fluctuation of scale-free electrophysiology is globally synchronized and directly coupled with the global component of spontaneous fMRI signals, in contrast to modularly synchronized fluctuations in oscillatory neural activity. These findings lead to a new hypothesis that scale-free and oscillatory neural processes account for global and modular patterns of functional connectivity observed

EEG-fMRI Bayesian framework for neural activity estimation: a simulation study

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Croce, Pierpaolo; Basti, Alessio; Marzetti, Laura; Zappasodi, Filippo; Del Gratta, Cosimo

2016-12-01

Objective. Due to the complementary nature of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), and given the possibility of simultaneous acquisition, the joint data analysis can afford a better understanding of the underlying neural activity estimation. In this simulation study we want to show the benefit of the joint EEG-fMRI neural activity estimation in a Bayesian framework. Approach. We built a dynamic Bayesian framework in order to perform joint EEG-fMRI neural activity time course estimation. The neural activity is originated by a given brain area and detected by means of both measurement techniques. We have chosen a resting state neural activity situation to address the worst case in terms of the signal-to-noise ratio. To infer information by EEG and fMRI concurrently we used a tool belonging to the sequential Monte Carlo (SMC) methods: the particle filter (PF). Main results. First, despite a high computational cost, we showed the feasibility of such an approach. Second, we obtained an improvement in neural activity reconstruction when using both EEG and fMRI measurements. Significance. The proposed simulation shows the improvements in neural activity reconstruction with EEG-fMRI simultaneous data. The application of such an approach to real data allows a better comprehension of the neural dynamics.

Anterior EEG asymmetries and opponent process theory.

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Kline, John P; Blackhart, Ginette C; Williams, William C

2007-03-01

The opponent process theory of emotion [Solomon, R.L., and Corbit, J.D. (1974). An opponent-process theory of motivation: I. Temporal dynamics of affect. Psychological Review, 81, 119-143.] predicts a temporary reversal of emotional valence during the recovery from emotional stimulation. We hypothesized that this affective contrast would be apparent in asymmetrical activity patterns in the frontal lobes, and would be more apparent for left frontally active individuals. The present study tested this prediction by examining EEG asymmetries during and after blocked presentations of aversive pictures selected from the International Affective Picture System (IAPS). 12 neutral images, 12 aversive images, and 24 neutral images were presented in blocks. Participants who were right frontally active at baseline did not show changes in EEG asymmetry while viewing aversive slides or after cessation. Participants left frontally active at baseline, however, exhibited greater relative left frontal activity after aversive stimulation than before stimulation. Asymmetrical activity patterns in the frontal lobes may relate to affect regulatory processes, including contrasting opponent after-reactions to aversive stimuli.

Photic driving in the electroencephalogram of children and adolescents: harmonic structure and relation to the resting state

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V.V. Lazarev

2001-12-01

Full Text Available In order to identify latent bioelectrical oscillators, 15 normal subjects (aged 9-17 years, 8 males, 7 females were subjected to intermittent photic stimulation. The EEG amplitude spectra corresponding to the 11 fixed frequencies of stimulation presented (3-24 Hz were combined to form "profiles" of the driving reaction in the right occipital area. The driving response varied with frequency, and was demonstrable in 70-100% of cases (using as criterion peak amplitudes 20% larger than those of the neighbors. The strongest responses were observed at the frequency closest to the alpha peak of the resting EEG. A secondary profile maximum was in the theta band. In 10 subjects, this maximum exceeded half the alpha peak (with an average of 72.4% of the alpha peak, while in the resting spectra, theta amplitudes were much lower than the alpha maxima. This responsiveness in theta activity seems to be characteristic of prepubertal and pubertal subjects. The profiles and resting EEG spectra showed a highly significant Pearson's correlation, with the peak in the theta band of the profiles being the main difference observed between them. The correlation coefficient was significantly correlated with the ratio of the maxima in the theta and alpha bands (R = -0.77, P<0.001. The correlation coefficient between profile and resting spectrum may be a useful indicator in screening methods used to reveal latent cerebral oscillators. Profiles for the second and third harmonics were correlated with those of the first harmonic (fundamental frequency, when considering the corresponding EEG frequencies. Peak frequencies in all three profiles were close to those of the individual's background alpha rhythm, and peak amplitudes in higher harmonics were not much lower than those of the fundamental frequency (mean values of 84 and 63%, for second and third harmonics, respectively.

Binaural Beat: A Failure to Enhance EEG Power and Emotional Arousal

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Fran López-Caballero

2017-11-01

Full Text Available When two pure tones of slightly different frequencies are delivered simultaneously to the two ears, is generated a beat whose frequency corresponds to the frequency difference between them. That beat is known as acoustic beat. If these two tones are presented one to each ear, they still produce the sensation of the same beat, although no physical combination of the tones occurs outside the auditory system. This phenomenon is called binaural beat. In the present study, we explored the potential contribution of binaural beats to the enhancement of specific electroencephalographic (EEG bands, as previous studies suggest the potential usefulness of binaural beats as a brainwave entrainment tool. Additionally, we analyzed the effects of binaural-beat stimulation on two psychophysiological measures related to emotional arousal: heart rate and skin conductance. Beats of five different frequencies (4.53 Hz -theta-, 8.97 Hz -alpha-, 17.93 Hz -beta-, 34.49 Hz -gamma- or 57.3 Hz -upper-gamma were presented binaurally and acoustically for epochs of 3 min (Beat epochs, preceded and followed by pink noise epochs of 90 s (Baseline and Post epochs, respectively. In each of these epochs, we analyzed the EEG spectral power, as well as calculated the heart rate and skin conductance response (SCR. For all the beat frequencies used for stimulation, no significant changes between Baseline and Beat epochs were observed within the corresponding EEG bands, neither with binaural or with acoustic beats. Additional analysis of spectral EEG topographies yielded negative results for the effect of binaural beats in the scalp distribution of EEG spectral power. In the psychophysiological measures, no changes in heart rate and skin conductance were observed for any of the beat frequencies presented. Our results do not support binaural-beat stimulation as a potential tool for the enhancement of EEG oscillatory activity, nor to induce changes in emotional arousal.

Binaural Beat: A Failure to Enhance EEG Power and Emotional Arousal.

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López-Caballero, Fran; Escera, Carles

2017-01-01

When two pure tones of slightly different frequencies are delivered simultaneously to the two ears, is generated a beat whose frequency corresponds to the frequency difference between them. That beat is known as acoustic beat. If these two tones are presented one to each ear, they still produce the sensation of the same beat, although no physical combination of the tones occurs outside the auditory system. This phenomenon is called binaural beat. In the present study, we explored the potential contribution of binaural beats to the enhancement of specific electroencephalographic (EEG) bands, as previous studies suggest the potential usefulness of binaural beats as a brainwave entrainment tool. Additionally, we analyzed the effects of binaural-beat stimulation on two psychophysiological measures related to emotional arousal: heart rate and skin conductance. Beats of five different frequencies (4.53 Hz -theta-, 8.97 Hz -alpha-, 17.93 Hz -beta-, 34.49 Hz -gamma- or 57.3 Hz -upper-gamma) were presented binaurally and acoustically for epochs of 3 min (Beat epochs), preceded and followed by pink noise epochs of 90 s (Baseline and Post epochs, respectively). In each of these epochs, we analyzed the EEG spectral power, as well as calculated the heart rate and skin conductance response (SCR). For all the beat frequencies used for stimulation, no significant changes between Baseline and Beat epochs were observed within the corresponding EEG bands, neither with binaural or with acoustic beats. Additional analysis of spectral EEG topographies yielded negative results for the effect of binaural beats in the scalp distribution of EEG spectral power. In the psychophysiological measures, no changes in heart rate and skin conductance were observed for any of the beat frequencies presented. Our results do not support binaural-beat stimulation as a potential tool for the enhancement of EEG oscillatory activity, nor to induce changes in emotional arousal.

Alterations in Resting-State Activity Relate to Performance in a Verbal Recognition Task

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López Zunini, Rocío A.; Thivierge, Jean-Philippe; Kousaie, Shanna; Sheppard, Christine; Taler, Vanessa

2013-01-01

In the brain, resting-state activity refers to non-random patterns of intrinsic activity occurring when participants are not actively engaged in a task. We monitored resting-state activity using electroencephalogram (EEG) both before and after a verbal recognition task. We show a strong positive correlation between accuracy in verbal recognition and pre-task resting-state alpha power at posterior sites. We further characterized this effect by examining resting-state post-task activity. We found marked alterations in resting-state alpha power when comparing pre- and post-task periods, with more pronounced alterations in participants that attained higher task accuracy. These findings support a dynamical view of cognitive processes where patterns of ongoing brain activity can facilitate –or interfere– with optimal task performance. PMID:23785436

Lifespan Differences in Nonlinear Dynamics during Rest and Auditory Oddball Performance

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Muller, Viktor; Lindenberger, Ulman

2012-01-01

Electroencephalographic recordings (EEG) were used to assess age-associated differences in nonlinear brain dynamics during both rest and auditory oddball performance in children aged 9.0-12.8 years, younger adults, and older adults. We computed nonlinear coupling dynamics and dimensional complexity, and also determined spectral alpha power as an…

The Oft-Neglected Role of Parietal EEG Asymmetry and Risk for Major Depressive Disorder

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Stewart, Jennifer L.; Towers, David N.; Coan, James A.; Allen, John J.B.

2010-01-01

Relatively less right parietal activity may reflect reduced arousal and signify risk for major depressive disorder (MDD). Inconsistent findings with parietal electroencephalographic (EEG) asymmetry, however, suggest issues such as anxiety comorbidity and sex differences have yet to be resolved. Resting parietal EEG asymmetry was assessed in 306 individuals (31% male) with (n = 143) and without (n = 163) a DSM-IV diagnosis of lifetime MDD and no comorbid anxiety disorders. Past MDD+ women displayed relatively less right parietal activity than current MDD+ and MDD- women, replicating prior work. Recent caffeine intake, an index of arousal, moderated the relationship between depression and EEG asymmetry for women and men. Findings suggest that sex differences and arousal should be examined in studies of depression and regional brain activity. PMID:20525011

Group Independent Component Analysis (gICA) and Current Source Density (CSD) in the study of EEG in ADHD adults.

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Ponomarev, Valery A; Mueller, Andreas; Candrian, Gian; Grin-Yatsenko, Vera A; Kropotov, Juri D

2014-01-01

To investigate the performance of the spectral analysis of resting EEG, Current Source Density (CSD) and group independent components (gIC) in diagnosing ADHD adults. Power spectra of resting EEG, CSD and gIC (19 channels, linked ears reference, eyes open/closed) from 96 ADHD and 376 healthy adults were compared between eyes open and eyes closed conditions, and between groups of subjects. Pattern of differences in gIC and CSD spectral power between conditions was approximately similar, whereas it was more widely spatially distributed for EEG. Size effect (Cohen's d) of differences in gIC and CSD spectral power between groups of subjects was considerably greater than in the case of EEG. Significant reduction of gIC and CSD spectral power depending on conditions was found in ADHD patients. Reducing power in a wide frequency range in the fronto-central areas is a common phenomenon regardless of whether the eyes were open or closed. Spectral power of local EEG activity isolated by gICA or CSD in the fronto-central areas may be a suitable marker for discrimination of ADHD and healthy adults. Spectral analysis of gIC and CSD provides better sensitivity to discriminate ADHD and healthy adults. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Measurement of neurovascular coupling in human motor cortex using simultaneous transcranial doppler (TCD) and electroencephalography (EEG).

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Alam, Monzurul; Ahmed, Ghazanfar; Ling, Yan To; Zheng, Yong-Ping

2018-05-25

Event-related desynchronization (ERD) is a relative power decrease of electroencephalogram (EEG) signals in a specific frequency band during physical motor execution, while transcranial Doppler (TCD) measures cerebral blood flow velocity. The objective of this study was to investigate the neurovascular coupling in the motor cortex by using an integrated EEG and TCD system, and to find any difference in hemodynamic responses in healthy young male and female adults. Approach: 30 healthy volunteers, aged 20-30 years were recruited for this study. The subjects were asked to perform a motor task for the duration of a provided visual cue. Simultaneous EEG and TCD recording was carried out using a new integrated system to detect the ERD arising from the EEG signals, and to measure the mean blood flow velocity of the left and right middle cerebral arteries from bilateral TCD signals. Main Results: The results showed a significant decrease in EEG power in mu band (7.5-12.5 Hz) during the motor task compared to the resting phase. It showed significant increase in desynchronization on the contralateral side of the motor task compared to the ipsilateral side. Mean blood flow velocity during the task phase was significantly higher in comparison with the resting phase at the contralateral side. The results also showed a significantly higher increase in the percentage of mean blood flow velocity in the contralateral side of motor task compared to the ipsilateral side. However, no significant difference in desynchronization, or change of mean blood flow velocity was found between males and females. Significance: A combined TCD-EEG system successfully detects ERD and blood flow velocity in cerebral arteries, and can be used as a useful tool to study neurovascular coupling in the brain. There is no significant difference in the hemodynamic responses in healthy young males and females. © 2018 Institute of Physics and Engineering in Medicine.

Characterization of functional brain activity and connectivity using EEG and fMRI in patients with sickle cell disease.

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Case, Michelle; Zhang, Huishi; Mundahl, John; Datta, Yvonne; Nelson, Stephen; Gupta, Kalpna; He, Bin

2017-01-01

Sickle cell disease (SCD) is a red blood cell disorder that causes many complications including life-long pain. Treatment of pain remains challenging due to a poor understanding of the mechanisms and limitations to characterize and quantify pain. In the present study, we examined simultaneously recording functional MRI (fMRI) and electroencephalogram (EEG) to better understand neural connectivity as a consequence of chronic pain in SCD patients. We performed independent component analysis and seed-based connectivity on fMRI data. Spontaneous power and microstate analysis was performed on EEG-fMRI data. ICA analysis showed that patients lacked activity in the default mode network (DMN) and executive control network compared to controls. EEG-fMRI data revealed that the insula cortex's role in salience increases with age in patients. EEG microstate analysis showed patients had increased activity in pain processing regions. The cerebellum in patients showed a stronger connection to the periaqueductal gray matter (involved in pain inhibition), and negative connections to pain processing areas. These results suggest that patients have reduced activity of DMN and increased activity in pain processing regions during rest. The present findings suggest resting state connectivity differences between patients and controls can be used as novel biomarkers of SCD pain.

Tracking EEG changes in response to alpha and beta binaural beats.

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Vernon, D; Peryer, G; Louch, J; Shaw, M

2014-07-01

A binaural beat can be produced by presenting two tones of a differing frequency, one to each ear. Such auditory stimulation has been suggested to influence behaviour and cognition via the process of cortical entrainment. However, research so far has only shown the frequency following responses in the traditional EEG frequency ranges of delta, theta and gamma. Hence a primary aim of this research was to ascertain whether it would be possible to produce clear changes in the EEG in either the alpha or beta frequency ranges. Such changes, if possible, would have a number of important implications as well as potential applications. A secondary goal was to track any observable changes in the EEG throughout the entrainment epoch to gain some insight into the nature of the entrainment effects on any changes in an effort to identify more effective entrainment regimes. Twenty two healthy participants were recruited and randomly allocated to one of two groups, each of which was exposed to a distinct binaural beat frequency for ten 1-minute epochs. The first group listened to an alpha binaural beat of 10 Hz and the second to a beta binaural beat of 20 Hz. EEG was recorded from the left and right temporal regions during pre-exposure baselines, stimulus exposure epochs and post-exposure baselines. Analysis of changes in broad-band and narrow-band amplitudes, and frequency showed no effect of binaural beat frequency eliciting a frequency following effect in the EEG. Possible mediating factors are discussed and a number of recommendations are made regarding future studies, exploring entrainment effects from a binaural beat presentation. Copyright © 2012 Elsevier B.V. All rights reserved.

A Biologically Inspired Approach to Frequency Domain Feature Extraction for EEG Classification

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Nurhan Gursel Ozmen

2018-01-01

Full Text Available Classification of electroencephalogram (EEG signal is important in mental decoding for brain-computer interfaces (BCI. We introduced a feature extraction approach based on frequency domain analysis to improve the classification performance on different mental tasks using single-channel EEG. This biologically inspired method extracts the most discriminative spectral features from power spectral densities (PSDs of the EEG signals. We applied our method on a dataset of six subjects who performed five different imagination tasks: (i resting state, (ii mental arithmetic, (iii imagination of left hand movement, (iv imagination of right hand movement, and (v imagination of letter “A.” Pairwise and multiclass classifications were performed in single EEG channel using Linear Discriminant Analysis and Support Vector Machines. Our method produced results (mean classification accuracy of 83.06% for binary classification and 91.85% for multiclassification that are on par with the state-of-the-art methods, using single-channel EEG with low computational cost. Among all task pairs, mental arithmetic versus letter imagination yielded the best result (mean classification accuracy of 90.29%, indicating that this task pair could be the most suitable pair for a binary class BCI. This study contributes to the development of single-channel BCI, as well as finding the best task pair for user defined applications.

Corticospinal excitability changes to anodal tDCS elucidated with NIRS-EEG joint-imaging

DEFF Research Database (Denmark)

Jindal, Utkarsh; Sood, Mehak; Chowdhury, Shubhajit Roy

2015-01-01

Transcranial direct current stimulation (tDCS) has been shown to modulate corticospinal excitability. We used near-infrared spectroscopy (NIRS) - electroencephalography (EEG) joint-imaging during and after anodal tDCS to measure changes in mean cerebral haemoglobin oxygen saturation (rSO2) along...... with changes in the log-transformed mean-power of EEG within 0.5 Hz - 11.25 Hz. In two separate studies, we investigated local post-tDCS alterations from baseline at the site of anodal tDCS using NIRS-EEG/tDCS joint-imaging as well as local post-tDCS alterations in motor evoked potentials (MEP...... that the innovative technologies for portable NIRS-EEG neuroimaging may be leveraged to objectively quantify the progress (e.g., corticospinal excitability alterations) and dose tDCS intervention as an adjuvant treatment during neurorehabilitation....

Quantitative EEG and its Correlation with Cardiovascular, Cognition and mood State: an Integrated Study in Simulated Microgravity

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Zhang, Jianyuan; Hu, Bin; Chen, Wenjuan; Moore, Philip; Xu, Tingting; Dong, Qunxi; Liu, Zhenyu; Luo, Yuejia; Chen, Shanguang

2014-12-01

The focus of the study is the estimation of the effects of microgravity on the central nervous activity and its underlying influencing mechanisms. To validate the microgravity-induced physiological and psychological effects on EEG, quantitative EEG features, cardiovascular indicators, mood state, and cognitive performances data collection was achieved during a 45 day period using a -6°head-down bed rest (HDBR) integrated approach. The results demonstrated significant differences in EEG data, as an increased Theta wave, a decreased Beta wave and a reduced complexity of brain, accompanied with an increased heart rate and pulse rate, decreased positive emotion, and degraded emotion conflict monitoring performance. The canonical correlation analysis (CCA) based cardiovascular and cognitive related EEG model showed the cardiovascular effect on EEG mainly affected bilateral temporal region and the cognitive effect impacted parietal-occipital and frontal regions. The results obtained in the study support the use of an approach which combines a multi-factor influential mechanism hypothesis. The changes in the EEG data may be influenced by both cardiovascular and cognitive effects.

Usefulness of a simple sleep-deprived EEG protocol for epilepsy diagnosis in de novo subjects.

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Giorgi, Filippo S; Perini, Daria; Maestri, Michelangelo; Guida, Melania; Pizzanelli, Chiara; Caserta, Anna; Iudice, Alfonso; Bonanni, Enrica

2013-11-01

In case series concerning the role of EEG after sleep deprivation (SD-EEG) in epilepsy, patients' features and protocols vary dramatically from one report to another. In this study, we assessed the usefulness of a simple SD-EEG method in well characterized patients. Among the 963 adult subjects submitted to SD-EEG at our Center, in the period 2003-2010, we retrospectively selected for analysis only those: (1) evaluated for suspected epileptic seizures; (2) with a normal/non-specific baseline EEG; (3) still drug-free at the time of SD-EEG; (4) with an MRI analysis; (5) with at least 1 year follow-up. SD-EEG consisted in SD from 2:00 AM and laboratory EEG from 8:00 AM to 10:30 AM. We analyzed epileptic interictal abnormalities (IIAs) and their correlations with patients' features. Epilepsy was confirmed in 131 patients. SD-EEG showed IIAs in 41.2% of all patients with epilepsy, and a 91.1% specificity for epilepsy diagnosis; IIAs types observed during SD-EEG are different in generalized versus focal epilepsies; for focal epilepsies, the IIAs yield in SD-EEG is higher than in second routine EEG. This simple SD-EEG protocol is very useful in de novo patients with suspected seizures. This study sheds new light on the role of SD-EEG in specific epilepsy populations. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Increased power of resting-state gamma oscillations in autism spectrum disorder detected by routine electroencephalography

NARCIS (Netherlands)

van Diessen, Eric; Senders, Joeky; Jansen, Floor E.; Boersma, Maria; Bruining, Hilgo

2015-01-01

Experimental studies suggest that increased resting-state power of gamma oscillations is associated with autism spectrum disorder (ASD). To extend the clinical applicability of this finding, we retrospectively investigated routine electroencephalography (EEG) recordings of 19 patients with ASD and

Comparison of EEG propagation speeds under emotional stimuli on smartphone between the different anxiety states

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Asakawa, Tetsuya; Muramatsu, Ayumi; Hayashi, Takuto; Urata, Tatsuya; Taya, Masato; Mizuno-Matsumoto, Yuko

2014-01-01

The current study evaluated the effect of different anxiety states on information processing as measured by an electroencephalography (EEG) using emotional stimuli on a smartphone. Twenty-three healthy subjects were assessed for their anxiety states using The State Trait Anxiety Inventory (STAI) and divided into two groups: low anxiety (I, II) or high anxiety (III and IV, V). An EEG was performed while the participant was presented with emotionally laden audiovisual stimuli (resting, pleasant, and unpleasant sessions) and emotionally laden sentence stimuli (pleasant sentence, unpleasant sentence sessions) and EEG data was analyzed using propagation speed analysis. The propagation speed of the low anxiety group at the medial coronal for resting stimuli for all time segments was higher than those of high anxiety group. The low anxiety group propagation speeds at the medial sagittal for unpleasant stimuli in the 0–30 and 60–150 s time frames were higher than those of high anxiety group. The propagation speeds at 150 s for all stimuli in the low anxiety group were significantly higher than the correspondent propagation speeds of the high anxiety group. These events suggest that neural information processes concerning emotional stimuli differ based on current anxiety state. PMID:25540618

Interictal functional connectivity of human epileptic networks assessed by intracerebral EEG and BOLD signal fluctuations.

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Gaelle Bettus

Full Text Available In this study, we aimed to demonstrate whether spontaneous fluctuations in the blood oxygen level dependent (BOLD signal derived from resting state functional magnetic resonance imaging (fMRI reflect spontaneous neuronal activity in pathological brain regions as well as in regions spared by epileptiform discharges. This is a crucial issue as coherent fluctuations of fMRI signals between remote brain areas are now widely used to define functional connectivity in physiology and in pathophysiology. We quantified functional connectivity using non-linear measures of cross-correlation between signals obtained from intracerebral EEG (iEEG and resting-state functional MRI (fMRI in 5 patients suffering from intractable temporal lobe epilepsy (TLE. Functional connectivity was quantified with both modalities in areas exhibiting different electrophysiological states (epileptic and non affected regions during the interictal period. Functional connectivity as measured from the iEEG signal was higher in regions affected by electrical epileptiform abnormalities relative to non-affected areas, whereas an opposite pattern was found for functional connectivity measured from the BOLD signal. Significant negative correlations were found between the functional connectivities of iEEG and BOLD signal when considering all pairs of signals (theta, alpha, beta and broadband and when considering pairs of signals in regions spared by epileptiform discharges (in broadband signal. This suggests differential effects of epileptic phenomena on electrophysiological and hemodynamic signals and/or an alteration of the neurovascular coupling secondary to pathological plasticity in TLE even in regions spared by epileptiform discharges. In addition, indices of directionality calculated from both modalities were consistent showing that the epileptogenic regions exert a significant influence onto the non epileptic areas during the interictal period. This study shows that functional

Qualitative and quantitative EEG abnormalities in violent offenders with antisocial personality disorder.

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Reyes, Ana Calzada; Amador, Alfredo Alvarez

2009-02-01

Resting eyes closed electroencephalogram was studied in a group of violent offenders evaluated at Psychiatric Department of the Legal Medicine Institute in Cuba (18 with antisocial personality disorder, ASPD, and 10 without psychiatric diagnosis). Characteristics of the EEG visual inspection and the use of frequency domain quantitative analysis techniques (narrow band spectral parameters) are described. Both groups were compared to Cuban normative database. High incidences of electroencephalographic abnormalities were found in both groups of violent offenders. The most frequent were: electrogenesis alterations, attenuated alpha rhythm and theta and delta activities increase in the frontal lobe. In the quantitative analysis theta and delta frequencies were increased and alpha activity was decreased in both groups. Differences appear for the topographical patterns present in subjects of both groups. EEG abnormalities were more severe in ASPD than in control group. Results suggest that EEG abnormalities in violent offenders should reflect aspects of brain dysfunction related to antisocial behaviour.

Predicting tDCS treatment outcomes of patients with major depressive disorder using automated EEG classification.

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Al-Kaysi, Alaa M; Al-Ani, Ahmed; Loo, Colleen K; Powell, Tamara Y; Martin, Donel M; Breakspear, Michael; Boonstra, Tjeerd W

2017-01-15

Transcranial direct current stimulation (tDCS) is a promising treatment for major depressive disorder (MDD). Standard tDCS treatment involves numerous sessions running over a few weeks. However, not all participants respond to this type of treatment. This study aims to investigate the feasibility of identifying MDD patients that respond to tDCS treatment based on resting-state electroencephalography (EEG) recorded prior to treatment commencing. We used machine learning to predict improvement in mood and cognition during tDCS treatment from baseline EEG power spectra. Ten participants with a current diagnosis of MDD were included. Power spectral density was assessed in five frequency bands: delta (0.5-4Hz), theta (4-8Hz), alpha (8-12Hz), beta (13-30Hz) and gamma (30-100Hz). Improvements in mood and cognition were assessed using the Montgomery-Åsberg Depression Rating Scale and Symbol Digit Modalities Test, respectively. We trained the classifiers using three algorithms (support vector machine, extreme learning machine and linear discriminant analysis) and a leave-one-out cross-validation approach. Mood labels were accurately predicted in 8 out of 10 participants using EEG channels FC4-AF8 (accuracy=76%, p=0.034). Cognition labels were accurately predicted in 10 out of 10 participants using channels pair CPz-CP2 (accuracy=92%, p=0.004). Due to the limited number of participants (n=10), the presented results mainly aim to serve as a proof of concept. These finding demonstrate the feasibility of using machine learning to identify patients that will respond to tDCS treatment. These promising results warrant a larger study to determine the clinical utility of this approach. Copyright © 2016 Elsevier B.V. All rights reserved.

Concealed, Unobtrusive Ear-Centered EEG Acquisition: cEEGrids for Transparent EEG

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Bleichner, Martin G.; Debener, Stefan

2017-01-01

Electroencephalography (EEG) is an important clinical tool and frequently used to study the brain-behavior relationship in humans noninvasively. Traditionally, EEG signals are recorded by positioning electrodes on the scalp and keeping them in place with glue, rubber bands, or elastic caps. This setup provides good coverage of the head, but is impractical for EEG acquisition in natural daily-life situations. Here, we propose the transparent EEG concept. Transparent EEG aims for motion tolerant, highly portable, unobtrusive, and near invisible data acquisition with minimum disturbance of a user's daily activities. In recent years several ear-centered EEG solutions that are compatible with the transparent EEG concept have been presented. We discuss work showing that miniature electrodes placed in and around the human ear are a feasible solution, as they are sensitive enough to pick up electrical signals stemming from various brain and non-brain sources. We also describe the cEEGrid flex-printed sensor array, which enables unobtrusive multi-channel EEG acquisition from around the ear. In a number of validation studies we found that the cEEGrid enables the recording of meaningful continuous EEG, event-related potentials and neural oscillations. Here, we explain the rationale underlying the cEEGrid ear-EEG solution, present possible use cases and identify open issues that need to be solved on the way toward transparent EEG. PMID:28439233

Comparison of Amplitude-Integrated EEG and Conventional EEG in a Cohort of Premature Infants.

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Meledin, Irina; Abu Tailakh, Muhammad; Gilat, Shlomo; Yogev, Hagai; Golan, Agneta; Novack, Victor; Shany, Eilon

2017-03-01

To compare amplitude-integrated EEG (aEEG) and conventional EEG (EEG) activity in premature neonates. Biweekly aEEG and EEG were simultaneously recorded in a cohort of infants born less than 34 weeks gestation. aEEG recordings were visually assessed for lower and upper border amplitude and bandwidth. EEG recordings were compressed for visual evaluation of continuity and assessed using a signal processing software for interburst intervals (IBI) and frequencies' amplitude. Ten-minute segments of aEEG and EEG indices were compared using regression analysis. A total of 189 recordings from 67 infants were made, from which 1697 aEEG/EEG pairs of 10-minute segments were assessed. Good concordance was found for visual assessment of continuity between the 2 methods. EEG IBI, alpha and theta frequencies' amplitudes were negatively correlated to the aEEG lower border while conceptional age (CA) was positively correlated to aEEG lower border ( P continuity and amplitude.

Automatic seizure detection: going from sEEG to iEEG

DEFF Research Database (Denmark)

Henriksen, Jonas; Remvig, Line Sofie; Madsen, Rasmus Elsborg

2010-01-01

Several different algorithms have been proposed for automatic detection of epileptic seizures based on both scalp and intracranial electroencephalography (sEEG and iEEG). Which modality that renders the best result is hard to assess though. From 16 patients with focal epilepsy, at least 24 hours...... of ictal and non-ictal iEEG were obtained. Characteristics of the seizures are represented by use of wavelet transformation (WT) features and classified by a support vector machine. When implementing a method used for sEEG on iEEG data, a great improvement in performance was obtained when the high...... frequency containing lower levels in the WT were included in the analysis. We were able to obtain a sensitivity of 96.4% and a false detection rate (FDR) of 0.20/h. In general, when implementing an automatic seizure detection algorithm made for sEEG on iEEG, great improvement can be obtained if a frequency...

Feature Extraction with GMDH-Type Neural Networks for EEG-Based Person Identification.

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Schetinin, Vitaly; Jakaite, Livija; Nyah, Ndifreke; Novakovic, Dusica; Krzanowski, Wojtek

2018-08-01

The brain activity observed on EEG electrodes is influenced by volume conduction and functional connectivity of a person performing a task. When the task is a biometric test the EEG signals represent the unique "brain print", which is defined by the functional connectivity that is represented by the interactions between electrodes, whilst the conduction components cause trivial correlations. Orthogonalization using autoregressive modeling minimizes the conduction components, and then the residuals are related to features correlated with the functional connectivity. However, the orthogonalization can be unreliable for high-dimensional EEG data. We have found that the dimensionality can be significantly reduced if the baselines required for estimating the residuals can be modeled by using relevant electrodes. In our approach, the required models are learnt by a Group Method of Data Handling (GMDH) algorithm which we have made capable of discovering reliable models from multidimensional EEG data. In our experiments on the EEG-MMI benchmark data which include 109 participants, the proposed method has correctly identified all the subjects and provided a statistically significant ([Formula: see text]) improvement of the identification accuracy. The experiments have shown that the proposed GMDH method can learn new features from multi-electrode EEG data, which are capable to improve the accuracy of biometric identification.

Surface EEG-Transcranial Direct Current Stimulation (tDCS) Closed-Loop System.

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Leite, Jorge; Morales-Quezada, Leon; Carvalho, Sandra; Thibaut, Aurore; Doruk, Deniz; Chen, Chiun-Fan; Schachter, Steven C; Rotenberg, Alexander; Fregni, Felipe

2017-09-01

Conventional transcranial direct current stimulation (tDCS) protocols rely on applying electrical current at a fixed intensity and duration without using surrogate markers to direct the interventions. This has led to some mixed results; especially because tDCS induced effects may vary depending on the ongoing level of brain activity. Therefore, the objective of this preliminary study was to assess the feasibility of an EEG-triggered tDCS system based on EEG online analysis of its frequency bands. Six healthy volunteers were randomized to participate in a double-blind sham-controlled crossover design to receive a single session of 10[Formula: see text]min 2[Formula: see text]mA cathodal and sham tDCS. tDCS trigger controller was based upon an algorithm designed to detect an increase in the relative beta power of more than 200%, accompanied by a decrease of 50% or more in the relative alpha power, based on baseline EEG recordings. EEG-tDCS closed-loop-system was able to detect the predefined EEG magnitude deviation and successfully triggered the stimulation in all participants. This preliminary study represents a proof-of-concept for the development of an EEG-tDCS closed-loop system in humans. We discuss and review here different methods of closed loop system that can be considered and potential clinical applications of such system.

Detecting Large-Scale Brain Networks Using EEG: Impact of Electrode Density, Head Modeling and Source Localization

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Liu, Quanying; Ganzetti, Marco; Wenderoth, Nicole; Mantini, Dante

2018-01-01

Resting state networks (RSNs) in the human brain were recently detected using high-density electroencephalography (hdEEG). This was done by using an advanced analysis workflow to estimate neural signals in the cortex and to assess functional connectivity (FC) between distant cortical regions. FC analyses were conducted either using temporal (tICA) or spatial independent component analysis (sICA). Notably, EEG-RSNs obtained with sICA were very similar to RSNs retrieved with sICA from functional magnetic resonance imaging data. It still remains to be clarified, however, what technological aspects of hdEEG acquisition and analysis primarily influence this correspondence. Here we examined to what extent the detection of EEG-RSN maps by sICA depends on the electrode density, the accuracy of the head model, and the source localization algorithm employed. Our analyses revealed that the collection of EEG data using a high-density montage is crucial for RSN detection by sICA, but also the use of appropriate methods for head modeling and source localization have a substantial effect on RSN reconstruction. Overall, our results confirm the potential of hdEEG for mapping the functional architecture of the human brain, and highlight at the same time the interplay between acquisition technology and innovative solutions in data analysis. PMID:29551969

EEG Topographic Mapping of Visual and Kinesthetic Imagery in Swimmers.

Science.gov (United States)

Wilson, V E; Dikman, Z; Bird, E I; Williams, J M; Harmison, R; Shaw-Thornton, L; Schwartz, G E

2016-03-01

This study investigated differences in QEEG measures between kinesthetic and visual imagery of a 100-m swim in 36 elite competitive swimmers. Background information and post-trial checks controlled for the modality of imagery, swimming skill level, preferred imagery style, intensity of image and task equality. Measures of EEG relative magnitude in theta, low (7-9 Hz) and high alpha (8-10 Hz), and low and high beta were taken from 19 scalp sites during baseline, visual, and kinesthetic imagery. QEEG magnitudes in the low alpha band during the visual and kinesthetic conditions were attenuated from baseline in low band alpha but no changes were seen in any other bands. Swimmers produced more low alpha EEG magnitude during visual versus kinesthetic imagery. This was interpreted as the swimmers having a greater efficiency at producing visual imagery. Participants who reported a strong intensity versus a weaker feeling of the image (kinesthetic) had less low alpha magnitude, i.e., there was use of more cortical resources, but not for the visual condition. These data suggest that low band (7-9 Hz) alpha distinguishes imagery modalities from baseline, visual imagery requires less cortical resources than kinesthetic imagery, and that intense feelings of swimming requires more brain activity than less intense feelings.

Differential resting-state EEG patterns associated with comorbid depression in Internet addiction.

Science.gov (United States)

Lee, Jaewon; Hwang, Jae Yeon; Park, Su Mi; Jung, Hee Yeon; Choi, Sam-Wook; Kim, Dai Jin; Lee, Jun-Young; Choi, Jung-Seok

2014-04-03

Many researchers have reported a relationship between Internet addiction and depression. In the present study, we compared the resting-state quantitative electroencephalography (QEEG) activity of treatment-seeking patients with comorbid Internet addiction and depression with those of treatment-seeking patients with Internet addiction without depression, and healthy controls to investigate the neurobiological markers that differentiate pure Internet addiction from Internet addiction with comorbid depression. Thirty-five patients diagnosed with Internet addiction and 34 age-, sex-, and IQ-matched healthy controls were enrolled in this study. Patients with Internet addiction were divided into two groups according to the presence (N=18) or absence (N=17) of depression. Resting-state, eye-closed QEEG was recorded, and the absolute and relative power of the brain were analyzed. The Internet addiction group without depression had decreased absolute delta and beta powers in all brain regions, whereas the Internet addiction group with depression had increased relative theta and decreased relative alpha power in all regions. These neurophysiological changes were not related to clinical variables. The current findings reflect differential resting-state QEEG patterns between both groups of participants with Internet addiction and healthy controls and also suggest that decreased absolute delta and beta powers are neurobiological markers of Internet addiction. Copyright © 2013 Elsevier Inc. All rights reserved.

Simple index of functional connectivity at rest in Multiple Sclerosis fatigue.

Science.gov (United States)

Buyukturkoglu, Korhan; Porcaro, Camillo; Cottone, Carlo; Cancelli, Andrea; Inglese, Matilde; Tecchio, Franca

2017-05-01

To investigate the EEG-derived functional connectivity at rest (FCR) patterns of fatigued Multiple Sclerosis (MS) patients in order to find good parameters for a future EEG-Neurofeedback intervention to reduce their fatigue symptoms. We evaluated FCR between hemispheric homologous areas, via spectral coherence between pairs of corresponding left and right bipolar derivations, in the Theta, Alpha and Beta bands. We estimated FCR in 18MS patients with different levels of fatigue and minimal clinical severity and in 11 age and gender matched healthy controls. We used correlation analysis to assess the relationship between the fatigue scores and the FCR values differing between fatigued MS patients and controls. Among FCR values differing between fatigued MS patients and controls, fatigue symptoms increased with higher Beta temporo-parietal FCR (p=0.00004). Also, positive correlations were found between the fatigue levels and the fronto-frontal FCR in Beta and Theta bands (p=0.0002 and p=0.001 respectively). We propose that a future EEG-Neurofeedback system against MS fatigue would train patients to decrease voluntarily the beta coherence between the homologous temporo-parietal areas. We extracted a feature for building an EEG-Neurofeedback system against fatigue in MS. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Are resting state spectral power measures related to executive functions in healthy young adults?

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Gordon, Shirley; Todder, Doron; Deutsch, Inbal; Garbi, Dror; Getter, Nir; Meiran, Nachshon

2018-01-08

Resting-state electroencephalogram (rsEEG) has been found to be associated with psychopathology, intelligence, problem solving, academic performance and is sometimes used as a supportive physiological indicator of enhancement in cognitive training interventions (e.g. neurofeedback, working memory training). In the current study, we measured rsEEG spectral power measures (relative power, between-band ratios and asymmetry) in one hundred sixty five young adults who were also tested on a battery of executive function (EF). We specifically focused on upper Alpha, Theta and Beta frequency bands given their putative role in EF. Our indices enabled finding correlations since they had decent-to-excellent internal and retest reliability and very little range restriction relative to a nation-wide representative large sample. Nonetheless, Bayesian statistical inference indicated support for the null hypothesis concerning lack of monotonic correlation between EF and rsEEG spectral power measures. Therefore, we conclude that, contrary to the quite common interpretation, these rsEEG spectral power measures do not indicate individual differences in the measured EF abilities. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Pervasive Approach to EEG-Based Depression Detection

Directory of Open Access Journals (Sweden)

Hanshu Cai

2018-01-01

Full Text Available Nowadays, depression is the world’s major health concern and economic burden worldwide. However, due to the limitations of current methods for depression diagnosis, a pervasive and objective approach is essential. In the present study, a psychophysiological database, containing 213 (92 depressed patients and 121 normal controls subjects, was constructed. The electroencephalogram (EEG signals of all participants under resting state and sound stimulation were collected using a pervasive prefrontal-lobe three-electrode EEG system at Fp1, Fp2, and Fpz electrode sites. After denoising using the Finite Impulse Response filter combining the Kalman derivation formula, Discrete Wavelet Transformation, and an Adaptive Predictor Filter, a total of 270 linear and nonlinear features were extracted. Then, the minimal-redundancy-maximal-relevance feature selection technique reduced the dimensionality of the feature space. Four classification methods (Support Vector Machine, K-Nearest Neighbor, Classification Trees, and Artificial Neural Network distinguished the depressed participants from normal controls. The classifiers’ performances were evaluated using 10-fold cross-validation. The results showed that K-Nearest Neighbor (KNN had the highest accuracy of 79.27%. The result also suggested that the absolute power of the theta wave might be a valid characteristic for discriminating depression. This study proves the feasibility of a pervasive three-electrode EEG acquisition system for depression diagnosis.

Modulation of epileptiform EEG discharges in juvenile myoclonic epilepsy: An investigation of reflex epileptic traits

DEFF Research Database (Denmark)

Beniczky, Sándor; Guaranha, Mirian Salvadori Bittar; Conradsen, Isa

2012-01-01

Purpose: Previous studies have suggested that cognitive tasks modulate (provoke or inhibit) the epileptiform electroencephalography (EEG) discharges (EDs) in patients with juvenile myoclonic epilepsy (JME). Their inhibitory effect was found to be especially frequent (64–90%). These studies...... arbitrarily defined modulation as a >100% increase or >50% decrease of the EDs compared with baseline, which may not sufficiently distinguish from spontaneous fluctuations. The aim of our study was to assess the modulation of EDs and the precipitation of myoclonic seizures by cognitive tasks...... and by conventional provocation methods, taking into account also the spontaneous fluctuation of EDs. Method: Sixty patients with JME underwent video‐EEG recordings including 50‐min baseline, sleep, hyperventilation, intermittent photic stimulation (IPS), and cognitive tasks. To account for spontaneous fluctuations...

EEG markers of cognitive impairments in patients with coronary artery disease

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I. V. Tarasova

2016-01-01

Full Text Available Objective: to identify the indicators of bioelectrical activity of the cerebral cortex, which are associated with cognitive impairments in patients with coronary artery disease (CAD.Patients and methods. The study included 122 male patients aged 45 to 69 years with CAD. Sixty of them were found to have mild cognitive impairments (MCI, their average Mini-Mental State Examination (MMSE score was 26.2±0.90; the other 62 patients had no cognitive impairment; their MMSE score was 28.5±0.86. All the patients underwent clinical and instrumental examinations and computer-based multichannel electroencephalography (EEG. Eyes-closed and eyes-open resting EEG monopolarly recorded in 62 standard leads of the 10-20 system. A binary logistic regression analysis was used to identify EEG predictors of MCI in patients with CAD.Results. The high power values of theta1-rhythm biopotentials with closed eyes in the frontal and occipital areas of the left hemisphere and those of alpha2-rhythm ones with open eyes in the frontal areas of the right hemisphere, and the high theta/alpha EEG power ratio are associated with an increased risk of MCI in CAD patients. The most important clinical and anamnestic factors associated with a decreased risk of MCI were higher education level, the lack of type 2 diabetes, and milder coronary bed lesions according to the SYNTAX scale. There was an association of the power values of the biopotentials and theta/alpha EEG power ratio and the development of MCI in CAD patients.

EEG Brain Activity in Dynamic Health Qigong Training: Same Effects for Mental Practice and Physical Training?

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Henz, Diana; Schöllhorn, Wolfgang I

2017-01-01

In recent years, there has been significant uptake of meditation and related relaxation techniques, as a means of alleviating stress and fostering an attentive mind. Several electroencephalogram (EEG) studies have reported changes in spectral band frequencies during Qigong meditation indicating a relaxed state. Much less is reported on effects of brain activation patterns induced by Qigong techniques involving bodily movement. In this study, we tested whether (1) physical Qigong training alters EEG theta and alpha activation, and (2) mental practice induces the same effect as a physical Qigong training. Subjects performed the dynamic Health Qigong technique Wu Qin Xi (five animals) physically and by mental practice in a within-subjects design. Experimental conditions were randomized. Two 2-min (eyes-open, eyes-closed) EEG sequences under resting conditions were recorded before and immediately after each 15-min exercise. Analyses of variance were performed for spectral power density data. Increased alpha power was found in posterior regions in mental practice and physical training for eyes-open and eyes-closed conditions. Theta power was increased after mental practice in central areas in eyes-open conditions, decreased in fronto-central areas in eyes-closed conditions. Results suggest that mental, as well as physical Qigong training, increases alpha activity and therefore induces a relaxed state of mind. The observed differences in theta activity indicate different attentional processes in physical and mental Qigong training. No difference in theta activity was obtained in physical and mental Qigong training for eyes-open and eyes-closed resting state. In contrast, mental practice of Qigong entails a high degree of internalized attention that correlates with theta activity, and that is dependent on eyes-open and eyes-closed resting state.

Sustained attention performance during sleep deprivation associates with instability in behavior and physiologic measures at baseline.

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Chua, Eric Chern-Pin; Yeo, Sing-Chen; Lee, Ivan Tian-Guang; Tan, Luuan-Chin; Lau, Pauline; Cai, Shiwei; Zhang, Xiaodong; Puvanendran, Kathiravelu; Gooley, Joshua J

2014-01-01

To identify baseline behavioral and physiologic markers that associate with individual differences in sustained attention during sleep deprivation. In a retrospective study, ocular, electrocardiogram, and electroencephalogram (EEG) measures were compared in subjects who were characterized as resilient (n = 15) or vulnerable (n = 15) to the effects of total sleep deprivation on sustained attention. Chronobiology and Sleep Laboratory, Duke-NUS Graduate Medical School Singapore. Healthy volunteers aged 22-32 years from the general population. Subjects were kept awake for at least 26 hours under constant environmental conditions. Every 2 hours, sustained attention was assessed using a 10-minute psychomotor vigilance task (PVT). During baseline sleep and recovery sleep, EEG slow wave activity was similar in resilient versus vulnerable subjects, suggesting that individual differences in vulnerability to sleep loss were not related to differences in homeostatic sleep regulation. Rather, irrespective of time elapsed since wake, subjects who were vulnerable to sleep deprivation exhibited slower and more variable PVT response times, lower and more variable heart rate, and higher and more variable EEG spectral power in the theta frequency band (6.0-7.5 Hz). Performance decrements in sustained attention during sleep deprivation associate with instability in behavioral and physiologic measures at baseline. Small individual differences in sustained attention that are present at baseline are amplified during prolonged wakefulness, thus contributing to large between-subjects differences in performance and sleepiness.

Simultaneous EEG and EMG biofeedback for peak performance in musicians.

Science.gov (United States)

Markovska-Simoska, Silvana; Pop-Jordanova, Nada; Georgiev, Dejan

2008-07-01

The aim of this study was to determine the effects of alpha neurofeedback and EMG biofeedback protocols for improvement of musical performance in violinists. The sample consisted of 12 music students (10 violinists and 2 viola players) from the Faculty of Music, Skopje (3 males, mean age of 20 +/- 0 and 9 females, mean age = 20.89 +/- 2.98). Six of them had a low alpha peak frequency (APF) ( 10 Hz). The sample was randomized in two groups. The students from the experimental group participated in 20 sessions of biofeedback (alpha/EMG), combined with music practice, while the students from the control group did only music practice. Average absolute power, interhemispheric coherence in the alpha band, alpha peak frequency (APF), individual alpha band width (IABW), amount of alpha suppression (AAS) and surface forehead integrated EMG power (IEMG), as well as a score on musical performance and inventories measuring anxiety, were assessed. Alpha-EEG/EMG-biofeedback was associated with a significant increase in average alpha power, APF and IABW in all the participants and with decreases in IEMG only in high-APF musicians. The biofeedback training success was positively correlated with the alpha power, IcoH, APF, IABW and baseline level of APF and IABW. Alpha-EEG/EMG biofeedback is capable of increasing voluntary self-regulation and the quality of musical performance. The efficiency of biofeedback training depends on the baseline EEG alpha activity status, in particular the APF.

PyEEG: an open source Python module for EEG/MEG feature extraction.

Science.gov (United States)

Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

2011-01-01

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction.

Mindfulness based cognitive therapy improves frontal control in bipolar disorder: a pilot EEG study

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Howells Fleur M

2012-02-01

Full Text Available Abstract Background Cognitive processing in Bipolar Disorder is characterized by a number of attentional abnormalities. Mindfulness Based Cognitive Therapy combines mindfulness meditation, a form of attentional training, along with aspects of cognitive therapy, and may improve attentional dysfunction in bipolar disorder patients. Methods 12 euthymic BD patients and 9 control participants underwent record of electroencephalography (EEG, band frequency analysis during resting states (eyes open, eyes closed and during the completion of a continuous performance task (A-X version, EEG event-related potential (ERP wave component analysis. The individuals with BD completed an 8-week MBCT intervention and record of EEG was repeated. Results (1 Brain activity, individuals with BD showed significantly decreased theta band power, increased beta band power, and decreased theta/beta ratios during the resting state, eyes closed, for frontal and cingulate cortices. Post MBCT intervention improvement over the right frontal cortex was seen in the individuals with BD, as beta band power decreased. (2 Brain activation, individuals with BD showed a significant P300-like wave form over the frontal cortex during the cue. Post MBCT intervention the P300-like waveform was significantly attenuated over the frontal cortex. Conclusions Individuals with BD show decreased attentional readiness and activation of non-relevant information processing during attentional processes. These data are the first that show, MBCT in BD improved attentional readiness, and attenuated activation of non-relevant information processing during attentional processes.

Classification of different reaching movements from the same limb using EEG

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Shiman, Farid; López-Larraz, Eduardo; Sarasola-Sanz, Andrea; Irastorza-Landa, Nerea; Spüler, Martin; Birbaumer, Niels; Ramos-Murguialday, Ander

2017-08-01

Objective. Brain-computer-interfaces (BCIs) have been proposed not only as assistive technologies but also as rehabilitation tools for lost functions. However, due to the stochastic nature, poor spatial resolution and signal to noise ratio from electroencephalography (EEG), multidimensional decoding has been the main obstacle to implement non-invasive BCIs in real-live rehabilitation scenarios. This study explores the classification of several functional reaching movements from the same limb using EEG oscillations in order to create a more versatile BCI for rehabilitation. Approach. Nine healthy participants performed four 3D center-out reaching tasks in four different sessions while wearing a passive robotic exoskeleton at their right upper limb. Kinematics data were acquired from the robotic exoskeleton. Multiclass extensions of Filter Bank Common Spatial Patterns (FBCSP) and a linear discriminant analysis (LDA) classifier were used to classify the EEG activity into four forward reaching movements (from a starting position towards four target positions), a backward movement (from any of the targets to the starting position and rest). Recalibrating the classifier using data from previous or the same session was also investigated and compared. Main results. Average EEG decoding accuracy were significantly above chance with 67%, 62.75%, and 50.3% when decoding three, four and six tasks from the same limb, respectively. Furthermore, classification accuracy could be increased when using data from the beginning of each session as training data to recalibrate the classifier. Significance. Our results demonstrate that classification from several functional movements performed by the same limb is possible with acceptable accuracy using EEG oscillations, especially if data from the same session are used to recalibrate the classifier. Therefore, an ecologically valid decoding could be used to control assistive or rehabilitation mutli-degrees of freedom (DoF) robotic devices

Effects of Inaccurate Identification of Interictal Epileptiform Discharges in Concurrent EEG-fMRI

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Gkiatis, K.; Bromis, K.; Kakkos, I.; Karanasiou, I. S.; Matsopoulos, G. K.; Garganis, K.

2017-11-01

Concurrent continuous EEG-fMRI is a novel multimodal technique that is finding its way into clinical practice in epilepsy. EEG timeseries are used to identify the timing of interictal epileptiform discharges (IEDs) which is then included in a GLM analysis in fMRI to localize the epileptic onset zone. Nevertheless, there are still some concerns about its reliability concerning BOLD changes correlated with IEDs. Even though IEDs are identified by an experienced neurologist-epiliptologist, the reliability and concordance of the mark-ups is depending on many factors including the level of fatigue, the amount of time that he spent or, in some cases, even the screen that is being used for the display of timeseries. This investigation is aiming to unravel the effect of misidentification or inaccuracy in the mark-ups of IEDs in the fMRI statistical parametric maps. Concurrent EEG-fMRI was conducted in six subjects with various types of epilepsy. IEDs were identified by an experienced neurologist-epiliptologist. Analysis of EEG was performed with EEGLAB and analysis of fMRI was conducted in FSL. Preliminary results revealed lower statistical significance for missing events or larger period of IEDs than the actual ones and the introduction of false positives and false negatives in statistical parametric maps when random events were included in the GLM on top of the IEDs. Our results suggest that mark-ups in EEG for simultaneous EEG-fMRI should be done with caution from an experienced and restful neurologist as it affects the fMRI results in various and unpredicted ways.

Quantitative Analysis of the Effects of Slow Wave Sleep Deprivation During the First 3 h of Sleep on Subsequent EEG Power Density

NARCIS (Netherlands)

Dijk, Derk Jan; Beersma, Domien G.M.; Daan, Serge; Bloem, Gerda M.; Hoofdakker, Rutger H. van den

1987-01-01

The relation between EEG power density during slow wave sleep (SWS) deprivation and power density during subsequent sleep was investigated. Nine young male adults slept in the laboratory for 3 consecutive nights. Spectral analysis of the EEG on the 2nd (baseline) night revealed an exponential

EEG II. Annexes and regulations. Comment; EEG II. Anlagen und Verordnungen. Kommentar

Energy Technology Data Exchange (ETDEWEB)

Frenz, Walter (ed.) [Rheinisch-Westfaelische Technische Hochschule Aachen (Germany). Berg-, Umwelt- und Europarecht

2016-11-01

Berlin commentary EEG II: safe through the paraphernalia Like hardly any other law, the Renewable Energies Act (EEG) is subject to constant changes. With the 2014 amendment, the EEG was fundamentally redesigned. This makes the application of the complex rules a challenge even for experts. In addition, the sub-rules contain important statements in the form of numerous annexes and regulations - with the EEG amendment 2014, this has become even more detailed. In it, many calculations are only defined in detail and the legal provisions of the EEG are made more definite and supplemented. The Berlin commentary EEG II accompanies you expertly through this complex matter. Experts explain the widely divergent rules in practice. If necessary for a better understanding, the provisions of the EEG 2014 are also explained. Consistently designed for your practice As a buyer of the work, you also benefit from access to an extensive, regularly updated database. This contains important legal energy regulations of the EU, the federal government and the countries. Even earlier legal positions remain searchable and can be conveniently compared with current versions. So you can see at a glance what has changed. [German] Berliner Kommentar EEG II: sicher durch den Paragrafengeflecht Wie kaum ein anderes Gesetz ist das Erneuerbare-Energien-Gesetz (EEG) staendigen Aenderungen unterworfen. Mit der Novelle 2014 wurde das EEG grundlegend umgestaltet. Dies macht die Anwendung der komplexen Regeln selbst fuer Experten zu einer Herausforderung. Zudem enthaelt auch das untergesetzliche Regelwerk wichtige Aussagen in Form zahlreicher Anlagen und Verordnungen - mit der EEG-Novelle 2014 ist dieses noch ausfuehrlicher geworden. In ihm werden viele Berechnungen erst naeher festgelegt und gesetzliche Bestimmungen des EEG entscheidend konkretisiert und ergaenzt. Der Berliner Kommentar EEG II begleitet Sie fachkundig durch diese komplexe Materie. Experten erlaeutern Ihnen praxisorientiert die

Human EEG responses to controlled alterations of the Earth's magnetic field.

Science.gov (United States)

Sastre, Antonio; Graham, Charles; Cook, Mary R; Gerkovich, Mary M; Gailey, Paul

2002-09-01

Examine the effects of controlled changes in the Earth's magnetic field on electroencephalogram (EEG) and subjective report. Fifty volunteers were exposed double-blind to changes in field magnitude, angle of inclination, and angle of deviation. Volunteers were also exposed to magnetic field conditions found near the North and South Pole. EEG recorded over temporal and occipital sites was compared across 4s baseline, field exposure, and no-change control trials. No EEG spectral differences as a function of gender or recording site were found. Geomagnetic field alterations had no effect on total energy (0.5-42 Hz), energy within traditional EEG analysis bands, or on the 95% spectral edge. Most volunteers reported no sensations; others reported non-specific symptoms unrelated to type of field change. Three hypothesized field detection mechanisms were not supported: (1) mechanical reception through torque exerted on the ferromagnetic material magnetite; (2) movement-induced induction of an electric field in the body; and (3) enhanced sensitivity due to alterations in the rates of chemical reactions involving electron spin states. Humans have little ability to detect brief alterations in the geomagnetic field, even if these alteration are of a large magnitude.

Physiological artifacts in scalp EEG and ear-EEG.

Science.gov (United States)

Kappel, Simon L; Looney, David; Mandic, Danilo P; Kidmose, Preben

2017-08-11

A problem inherent to recording EEG is the interference arising from noise and artifacts. While in a laboratory environment, artifacts and interference can, to a large extent, be avoided or controlled, in real-life scenarios this is a challenge. Ear-EEG is a concept where EEG is acquired from electrodes in the ear. We present a characterization of physiological artifacts generated in a controlled environment for nine subjects. The influence of the artifacts was quantified in terms of the signal-to-noise ratio (SNR) deterioration of the auditory steady-state response. Alpha band modulation was also studied in an open/closed eyes paradigm. Artifacts related to jaw muscle contractions were present all over the scalp and in the ear, with the highest SNR deteriorations in the gamma band. The SNR deterioration for jaw artifacts were in general higher in the ear compared to the scalp. Whereas eye-blinking did not influence the SNR in the ear, it was significant for all groups of scalps electrodes in the delta and theta bands. Eye movements resulted in statistical significant SNR deterioration in both frontal, temporal and ear electrodes. Recordings of alpha band modulation showed increased power and coherence of the EEG for ear and scalp electrodes in the closed-eyes periods. Ear-EEG is a method developed for unobtrusive and discreet recording over long periods of time and in real-life environments. This study investigated the influence of the most important types of physiological artifacts, and demonstrated that spontaneous activity, in terms of alpha band oscillations, could be recorded from the ear-EEG platform. In its present form ear-EEG was more prone to jaw related artifacts and less prone to eye-blinking artifacts compared to state-of-the-art scalp based systems.

No association of cortical amyloid load and EEG connectivity in older people with subjective memory complaints

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Stefan Teipel

2018-01-01

Full Text Available Changes in functional connectivity of cortical networks have been observed in resting-state EEG studies in healthy aging as well as preclinical and clinical stages of AD. Little information, however, exists on associations between EEG connectivity and cortical amyloid load in people with subjective memory complaints. Here, we determined the association of global cortical amyloid load, as measured by florbetapir-PET, with functional connectivity based on the phase-lag index of resting state EEG data for alpha and beta frequency bands in 318 cognitively normal individuals aged 70–85 years with subjective memory complaints from the INSIGHT-preAD cohort. Within the entire group we did not find any significant associations between global amyloid load and phase-lag index in any frequency band. Assessing exclusively the subgroup of amyloid-positive participants, we found enhancement of functional connectivity with higher global amyloid load in the alpha and a reduction in the beta frequency bands. In the amyloid-negative participants, higher amyloid load was associated with lower connectivity in the low alpha band. However, these correlations failed to reach significance after controlling for multiple comparisons. The absence of a strong amyloid effect on functional connectivity may represent a selection effect, where individuals remain in the cognitively normal group only if amyloid accumulation does not impair cortical functional connectivity.

Identification of Anisomerous Motor Imagery EEG Signals Based on Complex Algorithms.

Science.gov (United States)

Liu, Rensong; Zhang, Zhiwen; Duan, Feng; Zhou, Xin; Meng, Zixuan

2017-01-01

Motor imagery (MI) electroencephalograph (EEG) signals are widely applied in brain-computer interface (BCI). However, classified MI states are limited, and their classification accuracy rates are low because of the characteristics of nonlinearity and nonstationarity. This study proposes a novel MI pattern recognition system that is based on complex algorithms for classifying MI EEG signals. In electrooculogram (EOG) artifact preprocessing, band-pass filtering is performed to obtain the frequency band of MI-related signals, and then, canonical correlation analysis (CCA) combined with wavelet threshold denoising (WTD) is used for EOG artifact preprocessing. We propose a regularized common spatial pattern (R-CSP) algorithm for EEG feature extraction by incorporating the principle of generic learning. A new classifier combining the K -nearest neighbor (KNN) and support vector machine (SVM) approaches is used to classify four anisomerous states, namely, imaginary movements with the left hand, right foot, and right shoulder and the resting state. The highest classification accuracy rate is 92.5%, and the average classification accuracy rate is 87%. The proposed complex algorithm identification method can significantly improve the identification rate of the minority samples and the overall classification performance.

Identification of Anisomerous Motor Imagery EEG Signals Based on Complex Algorithms

Science.gov (United States)

Zhang, Zhiwen; Duan, Feng; Zhou, Xin; Meng, Zixuan

2017-01-01

Motor imagery (MI) electroencephalograph (EEG) signals are widely applied in brain-computer interface (BCI). However, classified MI states are limited, and their classification accuracy rates are low because of the characteristics of nonlinearity and nonstationarity. This study proposes a novel MI pattern recognition system that is based on complex algorithms for classifying MI EEG signals. In electrooculogram (EOG) artifact preprocessing, band-pass filtering is performed to obtain the frequency band of MI-related signals, and then, canonical correlation analysis (CCA) combined with wavelet threshold denoising (WTD) is used for EOG artifact preprocessing. We propose a regularized common spatial pattern (R-CSP) algorithm for EEG feature extraction by incorporating the principle of generic learning. A new classifier combining the K-nearest neighbor (KNN) and support vector machine (SVM) approaches is used to classify four anisomerous states, namely, imaginary movements with the left hand, right foot, and right shoulder and the resting state. The highest classification accuracy rate is 92.5%, and the average classification accuracy rate is 87%. The proposed complex algorithm identification method can significantly improve the identification rate of the minority samples and the overall classification performance. PMID:28874909

Schizophrenia and the efficacy of qEEG-guided neurofeedback treatment: a clinical case series.

Science.gov (United States)

Surmeli, Tanju; Ertem, Ayben; Eralp, Emin; Kos, Ismet H

2012-04-01

Inventory (MMPI) and the Test of Variables of Attention (TOVA), both at baseline and following treatment. Each participant was prescribed an NF treatment protocol based on the results of their qEEG neurometric analysis. Each session was 60 minutes in duration, with 1 to 2 sessions per day. When 2 sessions were administered during a single day, a 30-minute rest was given between the sessions. Changes in the PANSS, MMPI, and TOVA were analyzed to evaluate the effectiveness of NF treatment. The mean number of sessions completed by the participants was 58.5 sessions within 24 to 91 days. Three dropped out of treatment between 30 and 40 sessions of NF, and one did not show any response. Of the remaining 48 participants 47 showed clinical improvement after NF treatment, based on changes in their PANSS scores. The participants who were able to take the MMPI and the TOVA showed significant improvements in these measures as well. Forty were followed up for more than 22 months, 2 for 1 year, 1 for 9 months, and 3 for between 1 and 3 months after completion of NF. Overall NF was shown to be effective. This study provides the first evidence for positive effects of NF in schizophrenia.

EEG and Coma.

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Ardeshna, Nikesh I

2016-03-01

Coma is defined as a state of extreme unresponsiveness, in which a person exhibits no voluntary movement or behavior even to painful stimuli. The utilization of EEG for patients in coma has increased dramatically over the last few years. In fact, many institutions have set protocols for continuous EEG (cEEG) monitoring for patients in coma due to potential causes such as subarachnoid hemorrhage or cardiac arrest. Consequently, EEG plays an important role in diagnosis, managenent, and in some cases even prognosis of coma patients.

Structure and Topology Dynamics of Hyper-Frequency Networks during Rest and Auditory Oddball Performance.

Science.gov (United States)

Müller, Viktor; Perdikis, Dionysios; von Oertzen, Timo; Sleimen-Malkoun, Rita; Jirsa, Viktor; Lindenberger, Ulman

2016-01-01

Resting-state and task-related recordings are characterized by oscillatory brain activity and widely distributed networks of synchronized oscillatory circuits. Electroencephalographic recordings (EEG) were used to assess network structure and network dynamics during resting state with eyes open and closed, and auditory oddball performance through phase synchronization between EEG channels. For this assessment, we constructed a hyper-frequency network (HFN) based on within- and cross-frequency coupling (WFC and CFC, respectively) at 10 oscillation frequencies ranging between 2 and 20 Hz. We found that CFC generally differentiates between task conditions better than WFC. CFC was the highest during resting state with eyes open. Using a graph-theoretical approach (GTA), we found that HFNs possess small-world network (SWN) topology with a slight tendency to random network characteristics. Moreover, analysis of the temporal fluctuations of HFNs revealed specific network topology dynamics (NTD), i.e., temporal changes of different graph-theoretical measures such as strength, clustering coefficient, characteristic path length (CPL), local, and global efficiency determined for HFNs at different time windows. The different topology metrics showed significant differences between conditions in the mean and standard deviation of these metrics both across time and nodes. In addition, using an artificial neural network approach, we found stimulus-related dynamics that varied across the different network topology metrics. We conclude that functional connectivity dynamics (FCD), or NTD, which was found using the HFN approach during rest and stimulus processing, reflects temporal and topological changes in the functional organization and reorganization of neuronal cell assemblies.

Increased theta band EEG power in sickle cell disease patients

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Case M

2017-12-01

Full Text Available Michelle Case,1 Sina Shirinpour,1 Huishi Zhang,1 Yvonne H Datta,2 Stephen C Nelson,3 Karim T Sadak,4 Kalpna Gupta,2 Bin He1,5 1Department of Biomedical Engineering, 2Department of Medicine, University of Minnesota, 3Pediatric Hematology-Oncology, Children’s Hospitals and Clinics of Minnesota, 4Pediatric Hematology-Oncology, University of Minnesota Masonic Children’s Hospital, 5Institute for Engineering in Medicine, University of Minnesota, Minneapolis, MN, USA Objective: Pain is a major issue in the care of patients with sickle cell disease (SCD. The mechanisms behind pain and the best way to treat it are not well understood. We studied how electroencephalography (EEG is altered in SCD patients. Methods: We recruited 20 SCD patients and compared their resting state EEG to that of 14 healthy controls. EEG power was found across frequency bands using Welch’s method. Electrophysiological source imaging was assessed for each frequency band using the eLORETA algorithm. Results: SCD patients had increased theta power and decreased beta2 power compared to controls. Source localization revealed that areas of greater theta band activity were in areas related to pain processing. Imaging parameters were significantly correlated to emergency department visits, which indicate disease severity and chronic pain intensity. Conclusion: The present results support the pain mechanism referred to as thalamocortical dysrhythmia. This mechanism causes increased theta power in patients. Significance: Our findings show that EEG can be used to quantitatively evaluate differences between controls and SCD patients. Our results show the potential of EEG to differentiate between different levels of pain in an unbiased setting, where specific frequency bands could be used as biomarkers for chronic pain. Keywords: sickle cell disease, electroencephalography, chronic pain, electrophysiological source imaging, thalamocortical dysrhythmia

Mobile Phone Chips Reduce Increases in EEG Brain Activity Induced by Mobile Phone-Emitted Electromagnetic Fields

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Henz, Diana; Schöllhorn, Wolfgang I.; Poeggeler, Burkhard

2018-01-01

Recent neurophysiological studies indicate that exposure to electromagnetic fields (EMFs) generated by mobile phone radiation can exert effects on brain activity. One technical solution to reduce effects of EMFs in mobile phone use is provided in mobile phone chips that are applied to mobile phones or attached to their surfaces. To date, there are no systematical studies on the effects of mobile phone chip application on brain activity and the underlying neural mechanisms. The present study investigated whether mobile phone chips that are applied to mobile phones reduce effects of EMFs emitted by mobile phone radiation on electroencephalographic (EEG) brain activity in a laboratory study. Thirty participants volunteered in the present study. Experimental conditions (mobile phone chip, placebo chip, no chip) were set up in a randomized within-subjects design. Spontaneous EEG was recorded before and after mobile phone exposure for two 2-min sequences at resting conditions. During mobile phone exposure, spontaneous EEG was recorded for 30 min during resting conditions, and 5 min during performance of an attention test (d2-R). Results showed increased activity in the theta, alpha, beta and gamma bands during EMF exposure in the placebo and no chip conditions. Application of the mobile phone chip reduced effects of EMFs on EEG brain activity and attentional performance significantly. Attentional performance level was maintained regarding number of edited characters. Further, a dipole analysis revealed different underlying activation patterns in the chip condition compared to the placebo chip and no chip conditions. Finally, a correlational analysis for the EEG frequency bands and electromagnetic high-frequency (HF) emission showed significant correlations in the placebo chip and no chip condition for the theta, alpha, beta, and gamma bands. In the chip condition, a significant correlation of HF with the theta and alpha bands, but not with the beta and gamma bands was

Mobile Phone Chips Reduce Increases in EEG Brain Activity Induced by Mobile Phone-Emitted Electromagnetic Fields.

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Henz, Diana; Schöllhorn, Wolfgang I; Poeggeler, Burkhard

2018-01-01

Recent neurophysiological studies indicate that exposure to electromagnetic fields (EMFs) generated by mobile phone radiation can exert effects on brain activity. One technical solution to reduce effects of EMFs in mobile phone use is provided in mobile phone chips that are applied to mobile phones or attached to their surfaces. To date, there are no systematical studies on the effects of mobile phone chip application on brain activity and the underlying neural mechanisms. The present study investigated whether mobile phone chips that are applied to mobile phones reduce effects of EMFs emitted by mobile phone radiation on electroencephalographic (EEG) brain activity in a laboratory study. Thirty participants volunteered in the present study. Experimental conditions (mobile phone chip, placebo chip, no chip) were set up in a randomized within-subjects design. Spontaneous EEG was recorded before and after mobile phone exposure for two 2-min sequences at resting conditions. During mobile phone exposure, spontaneous EEG was recorded for 30 min during resting conditions, and 5 min during performance of an attention test (d2-R). Results showed increased activity in the theta, alpha, beta and gamma bands during EMF exposure in the placebo and no chip conditions. Application of the mobile phone chip reduced effects of EMFs on EEG brain activity and attentional performance significantly. Attentional performance level was maintained regarding number of edited characters. Further, a dipole analysis revealed different underlying activation patterns in the chip condition compared to the placebo chip and no chip conditions. Finally, a correlational analysis for the EEG frequency bands and electromagnetic high-frequency (HF) emission showed significant correlations in the placebo chip and no chip condition for the theta, alpha, beta, and gamma bands. In the chip condition, a significant correlation of HF with the theta and alpha bands, but not with the beta and gamma bands was

Interictal Epileptiform Discharges (IEDs) classification in EEG data of epilepsy patients

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Puspita, J. W.; Soemarno, G.; Jaya, A. I.; Soewono, E.

2017-12-01

Interictal Epileptiform Dischargers (IEDs), which consists of spike waves and sharp waves, in human electroencephalogram (EEG) are characteristic signatures of epilepsy. Spike waves are characterized by a pointed peak with a duration of 20-70 ms, while sharp waves has a duration of 70-200 ms. The purpose of the study was to classify spike wave and sharp wave of EEG data of epilepsy patients using Backpropagation Neural Network. The proposed method consists of two main stages: feature extraction stage and classification stage. In the feature extraction stage, we use frequency, amplitude and statistical feature, such as mean, standard deviation, and median, of each wave. The frequency values of the IEDs are very sensitive to the selection of the wave baseline. The selected baseline must contain all data of rising and falling slopes of the IEDs. Thus, we have a feature that is able to represent the type of IEDs, appropriately. The results show that the proposed method achieves the best classification results with the recognition rate of 93.75 % for binary sigmoid activation function and learning rate of 0.1.

EEG entropy measures in anesthesia

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Liang, Zhenhu; Wang, Yinghua; Sun, Xue; Li, Duan; Voss, Logan J.; Sleigh, Jamie W.; Hagihira, Satoshi; Li, Xiaoli

2015-01-01

Highlights: ► Twelve entropy indices were systematically compared in monitoring depth of anesthesia and detecting burst suppression.► Renyi permutation entropy performed best in tracking EEG changes associated with different anesthesia states.► Approximate Entropy and Sample Entropy performed best in detecting burst suppression. Objective: Entropy algorithms have been widely used in analyzing EEG signals during anesthesia. However, a systematic comparison of these entropy algorithms in assessing anesthesia drugs' effect is lacking. In this study, we compare the capability of 12 entropy indices for monitoring depth of anesthesia (DoA) and detecting the burst suppression pattern (BSP), in anesthesia induced by GABAergic agents. Methods: Twelve indices were investigated, namely Response Entropy (RE) and State entropy (SE), three wavelet entropy (WE) measures [Shannon WE (SWE), Tsallis WE (TWE), and Renyi WE (RWE)], Hilbert-Huang spectral entropy (HHSE), approximate entropy (ApEn), sample entropy (SampEn), Fuzzy entropy, and three permutation entropy (PE) measures [Shannon PE (SPE), Tsallis PE (TPE) and Renyi PE (RPE)]. Two EEG data sets from sevoflurane-induced and isoflurane-induced anesthesia respectively were selected to assess the capability of each entropy index in DoA monitoring and BSP detection. To validate the effectiveness of these entropy algorithms, pharmacokinetic/pharmacodynamic (PK/PD) modeling and prediction probability (Pk) analysis were applied. The multifractal detrended fluctuation analysis (MDFA) as a non-entropy measure was compared. Results: All the entropy and MDFA indices could track the changes in EEG pattern during different anesthesia states. Three PE measures outperformed the other entropy indices, with less baseline variability, higher coefficient of determination (R2) and prediction probability, and RPE performed best; ApEn and SampEn discriminated BSP best. Additionally, these entropy measures showed an advantage in computation

The Implicit Function as Squashing Time Model: A Novel Parallel Nonlinear EEG Analysis Technique Distinguishing Mild Cognitive Impairment and Alzheimer's Disease Subjects with High Degree of Accuracy

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Massimo Buscema

2007-01-01

(2007, this protocol includes a new type of artificial organism, named TWIST. The working hypothesis was that compared to the results presented by the workgroup (2007; the new artificial organism TWIST could produce a better classification between AD and MCI. Material and methods. Resting eyes-closed EEG data were recorded in 180 AD patients and in 115 MCI subjects. The data inputs for the classification, instead of being the EEG data, were the weights of the connections within a nonlinear autoassociative ANN trained to generate the recorded data. The most relevant features were selected and coincidently the datasets were split in the two halves for the final binary classification (training and testing performed by a supervised ANN. Results. The best results distinguishing between AD and MCI were equal to 94.10% and they are considerable better than the ones reported in our previous study (∼92% (2007. Conclusion. The results confirm the working hypothesis that a correct automatic classification of MCI and AD subjects can be obtained by extracting spatial information content of the resting EEG voltage by ANNs and represent the basis for research aimed at integrating spatial and temporal information content of the EEG.

Automated EEG entropy measurements in coma, vegetative state/unresponsive wakefulness syndrome and minimally conscious state

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Gosseries, Olivia; Schnakers, Caroline; Ledoux, Didier; Vanhaudenhuyse, Audrey; Bruno, Marie-Aurélie; Demertzi, Athéna; Noirhomme, Quentin; Lehembre, Rémy; Damas, Pierre; Goldman, Serge; Peeters, Erika; Moonen, Gustave; Laureys, Steven

Summary Monitoring the level of consciousness in brain-injured patients with disorders of consciousness is crucial as it provides diagnostic and prognostic information. Behavioral assessment remains the gold standard for assessing consciousness but previous studies have shown a high rate of misdiagnosis. This study aimed to investigate the usefulness of electroencephalography (EEG) entropy measurements in differentiating unconscious (coma or vegetative) from minimally conscious patients. Left fronto-temporal EEG recordings (10-minute resting state epochs) were prospectively obtained in 56 patients and 16 age-matched healthy volunteers. Patients were assessed in the acute (≤1 month post-injury; n=29) or chronic (>1 month post-injury; n=27) stage. The etiology was traumatic in 23 patients. Automated online EEG entropy calculations (providing an arbitrary value ranging from 0 to 91) were compared with behavioral assessments (Coma Recovery Scale-Revised) and outcome. EEG entropy correlated with Coma Recovery Scale total scores (r=0.49). Mean EEG entropy values were higher in minimally conscious (73±19; mean and standard deviation) than in vegetative/unresponsive wakefulness syndrome patients (45±28). Receiver operating characteristic analysis revealed an entropy cut-off value of 52 differentiating acute unconscious from minimally conscious patients (sensitivity 89% and specificity 90%). In chronic patients, entropy measurements offered no reliable diagnostic information. EEG entropy measurements did not allow prediction of outcome. User-independent time-frequency balanced spectral EEG entropy measurements seem to constitute an interesting diagnostic – albeit not prognostic – tool for assessing neural network complexity in disorders of consciousness in the acute setting. Future studies are needed before using this tool in routine clinical practice, and these should seek to improve automated EEG quantification paradigms in order to reduce the remaining false

Assessing quantitative EEG spectrograms to identify non-epileptic events.

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Goenka, Ajay; Boro, Alexis; Yozawitz, Elissa

2017-09-01

To evaluate the sensitivity and specificity of quantitative EEG (QEEG) spectrograms in order to distinguish epileptic from non-epileptic events. Seventeen patients with paroxysmal non-epileptic events, captured during EEG monitoring, were retrospectively assessed using QEEG spectrograms. These patients were compared to a control group of 13 consecutive patients (ages 25-60 years) with epileptic seizures of similar semiology. Assessment of raw EEG was employed as the gold standard against which epileptic and non-epileptic events were validated. QEEG spectrograms, available using Persyst 12 EEG system integration software, were each assessed with respect to their usefulness to distinguish epileptic from non-epileptic seizures. The given spectrogram was interpreted as indicating a seizure if, at the time of the clinically identified event, it showed a visually significant change from baseline. Eighty-two clinically identified paroxysmal events were analysed (46 non-epileptic and 36 epileptic). The "seizure detector trend analysis" spectrogram correctly classified 33/46 (71%) non-epileptic events (no seizure indicated during a clinically identified event) vs. 29/36 (81%) epileptic seizures (seizure indicated during a clinically identified event) (p=0.013). Similarly, "rhythmicity spectrogram", FFT spectrogram, "asymmetry relative spectrogram", and integrated-amplitude EEG spectrogram detected 28/46 (61%), 30/46 (65%), 22/46 (48%) and 27/46 (59%) non-epileptic events vs. 27/36 (75%), 25/36 (69%), 25/36 (69%) and 27/36 (75%) epileptic events, respectively. High sensitivities and specificities for QEEG seizure detection analyses suggest that QEEG may have a role at the bedside to facilitate early differentiation between epileptic seizures and non-epileptic events in order to avoid unnecessary administration of antiepileptic drugs and possible iatrogenic consequences.

Major Depression Detection from EEG Signals Using Kernel Eigen-Filter-Bank Common Spatial Patterns.

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Liao, Shih-Cheng; Wu, Chien-Te; Huang, Hao-Chuan; Cheng, Wei-Teng; Liu, Yi-Hung

2017-06-14

Major depressive disorder (MDD) has become a leading contributor to the global burden of disease; however, there are currently no reliable biological markers or physiological measurements for efficiently and effectively dissecting the heterogeneity of MDD. Here we propose a novel method based on scalp electroencephalography (EEG) signals and a robust spectral-spatial EEG feature extractor called kernel eigen-filter-bank common spatial pattern (KEFB-CSP). The KEFB-CSP first filters the multi-channel raw EEG signals into a set of frequency sub-bands covering the range from theta to gamma bands, then spatially transforms the EEG signals of each sub-band from the original sensor space to a new space where the new signals (i.e., CSPs) are optimal for the classification between MDD and healthy controls, and finally applies the kernel principal component analysis (kernel PCA) to transform the vector containing the CSPs from all frequency sub-bands to a lower-dimensional feature vector called KEFB-CSP. Twelve patients with MDD and twelve healthy controls participated in this study, and from each participant we collected 54 resting-state EEGs of 6 s length (5 min and 24 s in total). Our results show that the proposed KEFB-CSP outperforms other EEG features including the powers of EEG frequency bands, and fractal dimension, which had been widely applied in previous EEG-based depression detection studies. The results also reveal that the 8 electrodes from the temporal areas gave higher accuracies than other scalp areas. The KEFB-CSP was able to achieve an average EEG classification accuracy of 81.23% in single-trial analysis when only the 8-electrode EEGs of the temporal area and a support vector machine (SVM) classifier were used. We also designed a voting-based leave-one-participant-out procedure to test the participant-independent individual classification accuracy. The voting-based results show that the mean classification accuracy of about 80% can be achieved by the KEFP

A Removal of Eye Movement and Blink Artifacts from EEG Data Using Morphological Component Analysis

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Balbir Singh

2017-01-01

Full Text Available EEG signals contain a large amount of ocular artifacts with different time-frequency properties mixing together in EEGs of interest. The artifact removal has been substantially dealt with by existing decomposition methods known as PCA and ICA based on the orthogonality of signal vectors or statistical independence of signal components. We focused on the signal morphology and proposed a systematic decomposition method to identify the type of signal components on the basis of sparsity in the time-frequency domain based on Morphological Component Analysis (MCA, which provides a way of reconstruction that guarantees accuracy in reconstruction by using multiple bases in accordance with the concept of “dictionary.” MCA was applied to decompose the real EEG signal and clarified the best combination of dictionaries for this purpose. In our proposed semirealistic biological signal analysis with iEEGs recorded from the brain intracranially, those signals were successfully decomposed into original types by a linear expansion of waveforms, such as redundant transforms: UDWT, DCT, LDCT, DST, and DIRAC. Our result demonstrated that the most suitable combination for EEG data analysis was UDWT, DST, and DIRAC to represent the baseline envelope, multifrequency wave-forms, and spiking activities individually as representative types of EEG morphologies.

A Removal of Eye Movement and Blink Artifacts from EEG Data Using Morphological Component Analysis

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Wagatsuma, Hiroaki

2017-01-01

EEG signals contain a large amount of ocular artifacts with different time-frequency properties mixing together in EEGs of interest. The artifact removal has been substantially dealt with by existing decomposition methods known as PCA and ICA based on the orthogonality of signal vectors or statistical independence of signal components. We focused on the signal morphology and proposed a systematic decomposition method to identify the type of signal components on the basis of sparsity in the time-frequency domain based on Morphological Component Analysis (MCA), which provides a way of reconstruction that guarantees accuracy in reconstruction by using multiple bases in accordance with the concept of “dictionary.” MCA was applied to decompose the real EEG signal and clarified the best combination of dictionaries for this purpose. In our proposed semirealistic biological signal analysis with iEEGs recorded from the brain intracranially, those signals were successfully decomposed into original types by a linear expansion of waveforms, such as redundant transforms: UDWT, DCT, LDCT, DST, and DIRAC. Our result demonstrated that the most suitable combination for EEG data analysis was UDWT, DST, and DIRAC to represent the baseline envelope, multifrequency wave-forms, and spiking activities individually as representative types of EEG morphologies. PMID:28194221

Abnormal Baseline Brain Activity in Patients with Pulsatile Tinnitus: A Resting-State fMRI Study

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Lv Han

2014-01-01

Full Text Available Numerous investigations studying the brain functional activity of the tinnitus patients have indicated that neurological changes are important findings of this kind of disease. However, the pulsatile tinnitus (PT patients were excluded in previous studies because of the totally different mechanisms of the two subtype tinnitus. The aim of this study is to investigate whether altered baseline brain activity presents in patients with PT using resting-state functional magnetic resonance imaging (rs-fMRI technique. The present study used unilateral PT patients (n=42 and age-, sex-, and education-matched normal control subjects (n=42 to investigate the changes in structural and amplitude of low-frequency (ALFF of the brain. Also, we analyzed the relationships between these changes with clinical data of the PT patients. Compared with normal controls, PT patients did not show any structural changes. PT patients showed significant increased ALFF in the bilateral precuneus, and bilateral inferior frontal gyrus (IFG and decreased ALFF in multiple occipital areas. Moreover, the increased THI score and PT duration was correlated with increased ALFF in precuneus and bilateral IFG. The abnormalities of spontaneous brain activity reflected by ALFF measurements in the absence of structural changes may provide insights into the neural reorganization in PT patients.

EEG Controlled Wheelchair

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Swee Sim Kok

2016-01-01

Full Text Available This paper describes the development of a brainwave controlled wheelchair. The main objective of this project is to construct a wheelchair which can be directly controlled by the brain without requires any physical feedback as controlling input from the user. The method employed in this project is the Brain-computer Interface (BCI, which enables direct communication between the brain and the electrical wheelchair. The best method for recording the brain’s activity is electroencephalogram (EEG. EEG signal is also known as brainwaves signal. The device that used for capturing the EEG signal is the Emotiv EPOC headset. This headset is able to transmit the EEG signal wirelessly via Bluetooth to the PC (personal computer. By using the PC software, the EEG signals are processed and converted into mental command. According to the mental command (e.g. forward, left... obtained, the output electrical signal is sent out to the electrical wheelchair to perform the desired movement. Thus, in this project, a computer software is developed for translating the EEG signal into mental commands and transmitting out the controlling signal wirelessly to the electrical wheelchair.

Incorporating priors for EEG source imaging and connectivity analysis

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Xu eLei

2015-08-01

Full Text Available Electroencephalography source imaging (ESI is a useful technique to localize the generators from a given scalp electric measurement and to investigate the temporal dynamics of the large-scale neural circuits. By introducing reasonable priors from other modalities, ESI reveals the most probable sources and communication structures at every moment in time. Here, we review the available priors from such techniques as magnetic resonance imaging (MRI, functional MRI (fMRI, and positron emission tomography (PET. The modality's specific contribution is analyzed from the perspective of source reconstruction. For spatial priors, such as EEG-correlated fMRI, temporally coherent networks and resting-state fMRI are systematically introduced in the ESI. Moreover, the fiber tracking (diffusion tensor imaging, DTI and neuro-stimulation techniques (transcranial magnetic stimulation, TMS are also introduced as the potential priors, which can help to draw inferences about the neuroelectric connectivity in the source space. We conclude that combining EEG source imaging with other complementary modalities is a promising approach towards the study of brain networks in cognitive and clinical neurosciences.

OCCIPITAL SOURCES OF RESTING STATE ALPHA RHYTHMS ARE RELATED TO LOCAL GRAY MATTER DENSITY IN SUBJECTS WITH AMNESIC MILD COGNITIVE IMPAIRMENT AND ALZHEIMER’S DISEASE

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Claudio, Babiloni; Claudio, Del Percio; Marina, Boccardi; Roberta, Lizio; Susanna, Lopez; Filippo, Carducci; Nicola, Marzano; Andrea, Soricelli; Raffaele, Ferri; Ivano, Triggiani Antonio; Annapaola, Prestia; Serenella, Salinari; Rasser Paul, E; Erol, Basar; Francesco, Famà; Flavio, Nobili; Görsev, Yener; Durusu, Emek-Savaş Derya; Gesualdo, Loreto; Ciro, Mundi; Thompson Paul, M; Rossini Paolo, M.; Frisoni Giovanni, B

2014-01-01

Occipital sources of resting state electroencephalographic (EEG) alpha rhythms are abnormal, at the group level, in patients with amnesic mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Here we evaluated the hypothesis that amplitude of these occipital sources is related to neurodegeneration in occipital lobe as measured by magnetic resonance imaging (MRI). Resting-state eyes-closed EEG rhythms were recorded in 45 healthy elderly (Nold), 100 MCI, and 90 AD subjects. Neurodegeneration of occipital lobe was indexed by weighted averages of gray matter density (GMD), estimated from structural MRIs. EEG rhythms of interest were alpha 1 (8–10.5 Hz) and alpha 2 (10.5–13 Hz). EEG cortical sources were estimated by low resolution brain electromagnetic tomography (LORETA). Results showed a positive correlation between occipital GMD and amplitude of occipital alpha 1 sources in Nold, MCI and AD subjects as a whole group (r=0.3, p=0.000004, N=235). Furthermore, there was a positive correlation between amplitude of occipital alpha 1 sources and cognitive status as revealed by Mini Mental State Evaluation (MMSE) score across all subjects (r=0.38, p=0.000001, N=235). Finally, amplitude of occipital alpha 1 sources allowed a moderate classification of individual Nold and AD subjects (sensitivity: 87.8%; specificity: 66.7%; area under the Receiver Operating Characteristic (ROC) curve: 0.81). These results suggest that the amplitude of occipital sources of resting state alpha rhythms is related to AD neurodegeneration in occipital lobe along pathological aging. PMID:25442118

EEG spectral analysis of attention in ADHD: implications for neurofeedback training?

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Hartmut eHeinrich

2014-08-01

Full Text Available Objective: In children with attention-deficit/hyperactivity disorder (ADHD, an increased theta/beta ratio in the resting EEG typically serves as a rationale to conduct theta/beta neurofeedback training. However, this finding is increasingly challenged. As neurofeedback may rather target an active than a passive state, we studied the EEG in a condition that requires attention.Methods: In children with ADHD of the DSM-IV combined type (ADHD-C; N=15 and of the predominantly inattentive type (ADHD-I; N=9 and in typically developing children (N=19, EEG spectral analysis was conducted for segments during the attention network test without processing of stimuli and overt behavior. Frontal (F3, Fz, F4, central (C3, Cz, C4 and parietal (P3, Pz, P4 electrodes were included in the statistical analysis. To investigate if EEG spectral parameters are related to performance measures, correlation coefficients were calculated.Results: Particularly in the ADHD-C group, higher theta and alpha activity was found with the most prominent effect in the upper-theta/lower-alpha (5.5-10.5 Hz range. In the ADHD-I group, a significantly higher theta/beta ratio was observed at single electrodes (F3, Fz and a tendency for a higher theta/beta ratio when considering all electrodes (large effect size. Higher 5.5-10.5 Hz activity was associated with higher reaction time variability with the effect most prominent in the ADHD-C group. A higher theta/beta ratio was associated with higher reaction times, particularly in the ADHD-I group.Conclusions: 1. In an attention demanding period, children with ADHD are characterized by an underactivated state in the EEG with subtype-specific differences. 2. The functional relevance of related EEG parameters is indicated by associations with performance (reaction time measures. 3. Findings provide a rationale for applying NF protocols targeting theta (and alpha activity and the theta/beta ratio in subgroups of children with ADHD.

Changes in EEG during graded exercise on a recumbent cycle ergometer.

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Bailey, Stephen P; Hall, Eric E; Folger, Stephen E; Miller, Paul C

2008-01-01

Previous studies have shown changes in brain activity as a result of exercise; however, few studies have examined changes during exercise. The purpose of this study was to examine brain activity during a graded exercise test. Twenty male participants performed a graded exercise test on a recumbent cycle ergometer. Exercise intensity was set initially at 50W and was increased by 50W every 2 minutes until volitional fatigue was reached. Electroencephalography (EEG) was measured prior to the onset of exercise, during the last minute of each stage of exercise, immediately post-exercise, and 10 minutes into recovery. EEG was recorded from 8 scalp sites leading to analysis of alpha 1, alpha 2, beta 1, beta 2, and theta activities. Expired air was collected and analyzed for ventilation rate (VE), VO2, % of peak VO2, and Respiratory Exchange Ratio (RER). No differences were seen in EEG between the hemispheres of the brain. There was, however, a significant increase in brain activity across the spectrum occurring at 200 W through immediately post-exercise. Brain activity returned to pre- exercise levels by 10 minutes post. VO2, % of peak VO2 and RER increased linearly with exercise intensity. VE increased linearly through 200 W; however, a disproportionate increase was seen in VE from 200 W to peak exercise. The results of this investigation demonstrate that brain activity may be related to exercise intensity. Future research will want to examine how these changes in brain activity influence affective, perceptual and cognitive changes often associated with exercise. Efforts will also need to be made to determine if changes in brain activity during exercise are mediated by central (within the brain) or peripheral mechanisms. Key pointsEEG can be recorded during exercise.Brain EEG activity increases during exercise and may be related to exercise intensity.Brain EEG activity returns to resting levels quickly after the cessation of exercise.

Regional reductions in sleep electroencephalography power in obstructive sleep apnea: a high-density EEG study.

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Jones, Stephanie G; Riedner, Brady A; Smith, Richard F; Ferrarelli, Fabio; Tononi, Giulio; Davidson, Richard J; Benca, Ruth M

2014-02-01

Obstructive sleep apnea (OSA) is associated with significant alterations in neuronal integrity resulting from either hypoxemia and/or sleep loss. A large body of imaging research supports reductions in gray matter volume, alterations in white matter integrity and resting state activity, and functional abnormalities in response to cognitive challenge in various brain regions in patients with OSA. In this study, we used high-density electroencephalography (hdEEG), a functional imaging tool that could potentially be used during routine clinical care, to examine the regional distribution of neural activity in a non-clinical sample of untreated men and women with moderate/severe OSA. Sleep was recorded with 256-channel EEG in relatively healthy subjects with apnea-hypopnea index (AHI) > 10, as well as age-, sex-, and body mass index-matched controls selected from a research population initially recruited for a study on sleep and meditation. Sleep laboratory. Nine subjects with AHI > 10 and nine matched controls. N/A. Topographic analysis of hdEEG data revealed a broadband reduction in EEG power in a circumscribed region overlying the parietal cortex in OSA subjects. This parietal reduction in neural activity was present, to some extent, across all frequency bands in all stages and episodes of nonrapid eye movement sleep. This investigation suggests that regional deficits in electroencephalography (EEG) power generation may be a useful clinical marker for neural disruption in obstructive sleep apnea, and that high-density EEG may have the sensitivity to detect pathological cortical changes early in the disease process.

Source-Modeling Auditory Processes of EEG Data Using EEGLAB and Brainstorm

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Maren Stropahl

2018-05-01

Full Text Available Electroencephalography (EEG source localization approaches are often used to disentangle the spatial patterns mixed up in scalp EEG recordings. However, approaches differ substantially between experiments, may be strongly parameter-dependent, and results are not necessarily meaningful. In this paper we provide a pipeline for EEG source estimation, from raw EEG data pre-processing using EEGLAB functions up to source-level analysis as implemented in Brainstorm. The pipeline is tested using a data set of 10 individuals performing an auditory attention task. The analysis approach estimates sources of 64-channel EEG data without the prerequisite of individual anatomies or individually digitized sensor positions. First, we show advanced EEG pre-processing using EEGLAB, which includes artifact attenuation using independent component analysis (ICA. ICA is a linear decomposition technique that aims to reveal the underlying statistical sources of mixed signals and is further a powerful tool to attenuate stereotypical artifacts (e.g., eye movements or heartbeat. Data submitted to ICA are pre-processed to facilitate good-quality decompositions. Aiming toward an objective approach on component identification, the semi-automatic CORRMAP algorithm is applied for the identification of components representing prominent and stereotypic artifacts. Second, we present a step-wise approach to estimate active sources of auditory cortex event-related processing, on a single subject level. The presented approach assumes that no individual anatomy is available and therefore the default anatomy ICBM152, as implemented in Brainstorm, is used for all individuals. Individual noise modeling in this dataset is based on the pre-stimulus baseline period. For EEG source modeling we use the OpenMEEG algorithm as the underlying forward model based on the symmetric Boundary Element Method (BEM. We then apply the method of dynamical statistical parametric mapping (dSPM to obtain

Meditation and the EEG

OpenAIRE

West, Michael

1980-01-01

Previous research on meditation and the EEG is described, and findings relating to EEG patterns during meditation are discussed. Comparisons of meditation with other altered states are reviewed and it is concluded that, on the basis of existing EEG evidence, there is some reason for differentiating between meditation and drowsing. Research on alpha-blocking and habituation of the blocking response during meditation is reviewed, and the effects of meditation on EEG patterns outside of meditati...

Mobile EEG in epilepsy

NARCIS (Netherlands)

Askamp, Jessica; van Putten, Michel Johannes Antonius Maria

2014-01-01

The sensitivity of routine EEG recordings for interictal epileptiform discharges in epilepsy is limited. In some patients, inpatient video-EEG may be performed to increase the likelihood of finding abnormalities. Although many agree that home EEG recordings may provide a cost-effective alternative

Prediction of rhythmic and periodic EEG patterns and seizures on continuous EEG with early epileptiform discharges.

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Koren, J; Herta, J; Draschtak, S; Pötzl, G; Pirker, S; Fürbass, F; Hartmann, M; Kluge, T; Baumgartner, C

2015-08-01

Continuous EEG (cEEG) is necessary to document nonconvulsive seizures (NCS), nonconvulsive status epilepticus (NCSE), as well as rhythmic and periodic EEG patterns of 'ictal-interictal uncertainty' (RPPIIU) including periodic discharges, rhythmic delta activity, and spike-and-wave complexes in neurological intensive care patients. However, cEEG is associated with significant recording and analysis efforts. Therefore, predictors from short-term routine EEG with a reasonably high yield are urgently needed in order to select patients for evaluation with cEEG. The aim of this study was to assess the prognostic significance of early epileptiform discharges (i.e., within the first 30 min of EEG recording) on the following: (1) incidence of ictal EEG patterns and RPPIIU on subsequent cEEG, (2) occurrence of acute convulsive seizures during the ICU stay, and (3) functional outcome after 6 months of follow-up. We conducted a separate analysis of the first 30 min and the remaining segments of prospective cEEG recordings according to the ACNS Standardized Critical Care EEG Terminology as well as NCS criteria and review of clinical data of 32 neurological critical care patients. In 17 patients with epileptiform discharges within the first 30 min of EEG (group 1), electrographic seizures were observed in 23.5% (n = 4), rhythmic or periodic EEG patterns of 'ictal-interictal uncertainty' in 64.7% (n = 11), and neither electrographic seizures nor RPPIIU in 11.8% (n = 2). In 15 patients with no epileptiform discharges in the first 30 min of EEG (group 2), no electrographic seizures were recorded on subsequent cEEG, RPPIIU were seen in 26.7% (n = 4), and neither electrographic seizures nor RPPIIU in 73.3% (n = 11). The incidence of EEG patterns on cEEG was significantly different between the two groups (p = 0.008). Patients with early epileptiform discharges developed acute seizures more frequently than patients without early epileptiform discharges (p = 0.009). Finally, functional

Your brain on bikes: P3, MMN/N2b, and baseline noise while pedaling a stationary bike.

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Scanlon, Joanna E M; Sieben, Alex J; Holyk, Kevin R; Mathewson, Kyle E

2017-06-01

Increasingly, there is a trend to measure brain activity in more ecologically realistic scenarios. Normally, the confines of the laboratory and sedentary tasks mitigate sources of electrical noise on EEG measurement. Moving EEG outside of the lab requires understanding of the impact of complex movements and activities on traditional EEG and ERP measures. Here, we recorded EEG with active electrodes while participants were either riding or sitting on a stationary bike in an electrical and sound-attenuated chamber in the lab. Participants performed an auditory oddball task, pressing a button when they detected rare target tones in a series of standard frequent tones. We quantified both the levels of spectral, single-trial baseline, and ERP baseline noise, as well as classic MMN/N2b and P3 ERP components measured during both biking and sitting still. We observed slight increases in posterior high frequency noise in the spectra, and increased noise in the baseline period during biking. However, morphologically and topographically similar MMN/N2b and P3 components were measured reliably while both biking and sitting. A quantification of the power to reliably measure ERPs as a function of the number of trials revealed slight increases in the number of trials needed during biking to achieve the same level of power. Taken in sum, our results confirm that classic ERPs can be measured reliably during biking activities in the lab. Future directions will employ these techniques outside the lab in ecologically valid situations. © 2017 Society for Psychophysiological Research.

Alcohol affects the brain's resting-state network in social drinkers.

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Chrysa Lithari

Full Text Available Acute alcohol intake is known to enhance inhibition through facilitation of GABA(A receptors, which are present in 40% of the synapses all over the brain. Evidence suggests that enhanced GABAergic transmission leads to increased large-scale brain connectivity. Our hypothesis is that acute alcohol intake would increase the functional connectivity of the human brain resting-state network (RSN. To test our hypothesis, electroencephalographic (EEG measurements were recorded from healthy social drinkers at rest, during eyes-open and eyes-closed sessions, after administering to them an alcoholic beverage or placebo respectively. Salivary alcohol and cortisol served to measure the inebriation and stress levels. By calculating Magnitude Square Coherence (MSC on standardized Low Resolution Electromagnetic Tomography (sLORETA solutions, we formed cortical networks over several frequency bands, which were then analyzed in the context of functional connectivity and graph theory. MSC was increased (p<0.05, corrected with False Discovery Rate, FDR corrected in alpha, beta (eyes-open and theta bands (eyes-closed following acute alcohol intake. Graph parameters were accordingly altered in these bands quantifying the effect of alcohol on the structure of brain networks; global efficiency and density were higher and path length was lower during alcohol (vs. placebo, p<0.05. Salivary alcohol concentration was positively correlated with the density of the network in beta band. The degree of specific nodes was elevated following alcohol (vs. placebo. Our findings support the hypothesis that short-term inebriation considerably increases large-scale connectivity in the RSN. The increased baseline functional connectivity can -at least partially- be attributed to the alcohol-induced disruption of the delicate balance between inhibitory and excitatory neurotransmission in favor of inhibitory influences. Thus, it is suggested that short-term inebriation is associated, as

Practice changes beta power at rest and its modulation during movement in healthy subjects but not in patients with Parkinson's disease.

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Moisello, Clara; Blanco, Daniella; Lin, Jing; Panday, Priya; Kelly, Simon P; Quartarone, Angelo; Di Rocco, Alessandro; Cirelli, Chiara; Tononi, Giulio; Ghilardi, M Felice

2015-10-01

PD (Parkinson's disease) is characterized by impairments in cortical plasticity, in beta frequency at rest and in beta power modulation during movement (i.e., event-related ERS [synchronization] and ERD [desynchronization]). Recent results with experimental protocols inducing long-term potentiation in healthy subjects suggest that cortical plasticity phenomena might be reflected by changes of beta power recorded with EEG during rest. Here, we determined whether motor practice produces changes in beta power at rest and during movements in both healthy subjects and patients with PD. We hypothesized that such changes would be reduced in PD. We thus recorded EEG in patients with PD and age-matched controls before, during and after a 40-minute reaching task. We determined posttask changes of beta power at rest and assessed the progressive changes of beta ERD and ERS during the task over frontal and sensorimotor regions. We found that beta ERS and ERD changed significantly with practice in controls but not in PD. In PD compared to controls, beta power at rest was greater over frontal sensors but posttask changes, like those during movements, were far less evident. In both groups, kinematic characteristics improved with practice; however, there was no correlation between such improvements and the changes in beta power. We conclude that prolonged practice in a motor task produces use-dependent modifications that are reflected in changes of beta power at rest and during movement. In PD, such changes are significantly reduced; such a reduction might represent, at least partially, impairment of cortical plasticity.

Sex Differences in the Sleep EEG of Young Adults : Visual Scoring and Spectral Analysis

NARCIS (Netherlands)

Dijk, Derk Jan; Beersma, Domien G.M.; Bloem, Gerda M.

1989-01-01

Baseline sleep of 13 men (mean age of 23.5 years) and 15 women (21.9 years) was analyzed. Visual scoring of the electroencephalograms (EEGs) revealed no significant differences between the sexes in the amounts of slow-wave sleep and rapid-eye-movement (REM) sleep. Spectral analysis, however,

Temporal Comparison Between NIRS and EEG Signals During a Mental Arithmetic Task Evaluated with Self-Organizing Maps.

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Oyama, Katsunori; Sakatani, Kaoru

2016-01-01

Simultaneous monitoring of brain activity with near-infrared spectroscopy and electroencephalography allows spatiotemporal reconstruction of the hemodynamic response regarding the concentration changes in oxyhemoglobin and deoxyhemoglobin that are associated with recorded brain activity such as cognitive functions. However, the accuracy of state estimation during mental arithmetic tasks is often different depending on the length of the segment for sampling of NIRS and EEG signals. This study compared the results of a self-organizing map and ANOVA, which were both used to assess the accuracy of state estimation. We conducted an experiment with a mental arithmetic task performed by 10 participants. The lengths of the segment in each time frame for observation of NIRS and EEG signals were compared with the 30-s, 1-min, and 2-min segment lengths. The optimal segment lengths were different for NIRS and EEG signals in the case of classification of feature vectors into the states of performing a mental arithmetic task and being at rest.

Major Depression Detection from EEG Signals Using Kernel Eigen-Filter-Bank Common Spatial Patterns

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Shih-Cheng Liao

2017-06-01

Full Text Available Major depressive disorder (MDD has become a leading contributor to the global burden of disease; however, there are currently no reliable biological markers or physiological measurements for efficiently and effectively dissecting the heterogeneity of MDD. Here we propose a novel method based on scalp electroencephalography (EEG signals and a robust spectral-spatial EEG feature extractor called kernel eigen-filter-bank common spatial pattern (KEFB-CSP. The KEFB-CSP first filters the multi-channel raw EEG signals into a set of frequency sub-bands covering the range from theta to gamma bands, then spatially transforms the EEG signals of each sub-band from the original sensor space to a new space where the new signals (i.e., CSPs are optimal for the classification between MDD and healthy controls, and finally applies the kernel principal component analysis (kernel PCA to transform the vector containing the CSPs from all frequency sub-bands to a lower-dimensional feature vector called KEFB-CSP. Twelve patients with MDD and twelve healthy controls participated in this study, and from each participant we collected 54 resting-state EEGs of 6 s length (5 min and 24 s in total. Our results show that the proposed KEFB-CSP outperforms other EEG features including the powers of EEG frequency bands, and fractal dimension, which had been widely applied in previous EEG-based depression detection studies. The results also reveal that the 8 electrodes from the temporal areas gave higher accuracies than other scalp areas. The KEFB-CSP was able to achieve an average EEG classification accuracy of 81.23% in single-trial analysis when only the 8-electrode EEGs of the temporal area and a support vector machine (SVM classifier were used. We also designed a voting-based leave-one-participant-out procedure to test the participant-independent individual classification accuracy. The voting-based results show that the mean classification accuracy of about 80% can be

EEG entropy measures in anesthesia

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Zhenhu eLiang

2015-02-01

Full Text Available Objective: Entropy algorithms have been widely used in analyzing EEG signals during anesthesia. However, a systematic comparison of these entropy algorithms in assessing anesthesia drugs’ effect is lacking. In this study, we compare the capability of twelve entropy indices for monitoring depth of anesthesia (DoA and detecting the burst suppression pattern (BSP, in anesthesia induced by GA-BAergic agents.Methods: Twelve indices were investigated, namely Response Entropy (RE and State entropy (SE, three wavelet entropy (WE measures (Shannon WE (SWE, Tsallis WE (TWE and Renyi WE (RWE, Hilbert-Huang spectral entropy (HHSE, approximate entropy (ApEn, sample entropy (SampEn, Fuzzy entropy, and three permutation entropy (PE measures (Shannon PE (SPE, Tsallis PE (TPE and Renyi PE (RPE. Two EEG data sets from sevoflurane-induced and isoflu-rane-induced anesthesia respectively were selected to assess the capability of each entropy index in DoA monitoring and BSP detection. To validate the effectiveness of these entropy algorithms, phar-macokinetic / pharmacodynamic (PK/PD modeling and prediction probability analysis were applied. The multifractal detrended fluctuation analysis (MDFA as a non-entropy measure was compared.Results: All the entropy and MDFA indices could track the changes in EEG pattern during different anesthesia states. Three PE measures outperformed the other entropy indices, with less baseline vari-ability, higher coefficient of determination and prediction probability, and RPE performed best; ApEn and SampEn discriminated BSP best. Additionally, these entropy measures showed an ad-vantage in computation efficiency compared with MDFA.Conclusion: Each entropy index has its advantages and disadvantages in estimating DoA. Overall, it is suggested that the RPE index was a superior measure.Significance: Investigating the advantages and disadvantages of these entropy indices could help improve current clinical indices for monitoring DoA.

EEG oscillatory power dissociates between distress- and depression-related psychopathology in subjective tinnitus.

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Meyer, Martin; Neff, Patrick; Grest, Angelina; Hemsley, Colette; Weidt, Steffi; Kleinjung, Tobias

2017-05-15

Recent research has used source estimation approaches to identify spatially distinct neural configurations in individuals with chronic, subjective tinnitus (TI). The results of these studies are often heterogeneous, a fact which may be partly explained by an inherent heterogeneity in the TI population and partly by the applied EEG data analysis procedure and EEG hardware. Hence this study was performed to re-enact a formerly published study (Joos et al., 2012) to better understand the reason for differences and overlap between studies from different labs. We re-investigated the relationship between neural oscillations and behavioral measurements of affective states in TI, namely depression and tinnitus-related distress by recruiting 45 TI who underwent resting-state EEG. Comprehensive psychopathological (depression and tinnitus-related distress scores) and psychometric data (including other tinnitus characteristics) were gathered. A principal component analysis (PCA) was performed to unveil independent factors that predict distinct aspects of tinnitus-related pathology. Furthermore, we correlated EEG power changes in the standard frequency bands with the behavioral scores for both the whole-brain level and, as a post hoc approach, for selected regions of interest (ROI) based on sLORETA. Behavioral data revealed significant relationships between measurements of depression and tinnitus-related distress. Notably, no significant results were observed for the depressive scores and modulations of the EEG signal. However, akin to the former study we evidenced a significant relationship between a power increase in the β-bands and tinnitus-related distress. In conclusion, it has emerged that depression and tinnitus-related distress, even though they are assumed not to be completely independent, manifest in distinct neural configurations. Copyright © 2017 Elsevier B.V. All rights reserved.

Statistical feature extraction for artifact removal from concurrent fMRI-EEG recordings.

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Liu, Zhongming; de Zwart, Jacco A; van Gelderen, Peter; Kuo, Li-Wei; Duyn, Jeff H

2012-02-01

We propose a set of algorithms for sequentially removing artifacts related to MRI gradient switching and cardiac pulsations from electroencephalography (EEG) data recorded during functional magnetic resonance imaging (fMRI). Special emphasis is directed upon the use of statistical metrics and methods for the extraction and selection of features that characterize gradient and pulse artifacts. To remove gradient artifacts, we use channel-wise filtering based on singular value decomposition (SVD). To remove pulse artifacts, we first decompose data into temporally independent components and then select a compact cluster of components that possess sustained high mutual information with the electrocardiogram (ECG). After the removal of these components, the time courses of remaining components are filtered by SVD to remove the temporal patterns phase-locked to the cardiac timing markers derived from the ECG. The filtered component time courses are then inversely transformed into multi-channel EEG time series free of pulse artifacts. Evaluation based on a large set of simultaneous EEG-fMRI data obtained during a variety of behavioral tasks, sensory stimulations and resting conditions showed excellent data quality and robust performance attainable with the proposed methods. These algorithms have been implemented as a Matlab-based toolbox made freely available for public access and research use. Published by Elsevier Inc.

Disentangling Tinnitus Distress and Tinnitus Presence by Means of EEG Power Analysis

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Martin Meyer

2014-01-01

Full Text Available The present study investigated 24 individuals suffering from chronic tinnitus (TI and 24 nonaffected controls (CO. We recorded resting-state EEG and collected psychometric data to obtain information about how chronic tinnitus experience affects the cognitive and emotional state of TI. The study was meant to disentangle TI with high distress from those who suffer less from persistent tinnitus based on both neurophysiological and behavioral data. A principal component analysis of psychometric data uncovers two distinct independent dimensions characterizing the individual tinnitus experience. These independent states are distress and presence, the latter is described as the perceived intensity of sound experience that increases with tinnitus duration devoid of any considerable emotional burden. Neuroplastic changes correlate with the two independent components. TI with high distress display increased EEG activity in the oscillatory range around 25 Hz (upper β-band that agglomerates over frontal recording sites. TI with high presence show enhanced EEG signal strength in the δ-, α-, and lower γ-bands (30–40 Hz over bilateral temporal and left perisylvian electrodes. Based on these differential patterns we suggest that the two dimensions, namely, distress and presence, should be considered as independent dimensions of chronic subjective tinnitus.

Decreased resting functional connectivity after traumatic brain injury in the rat.

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Asht Mangal Mishra

Full Text Available Traumatic brain injury (TBI contributes to about 10% of acquired epilepsy. Even though the mechanisms of post-traumatic epileptogenesis are poorly known, a disruption of neuronal networks predisposing to altered neuronal synchrony remains a viable candidate mechanism. We tested a hypothesis that resting state BOLD-fMRI functional connectivity can reveal network abnormalities in brain regions that are connected to the lesioned cortex, and that these changes associate with functional impairment, particularly epileptogenesis. TBI was induced using lateral fluid-percussion injury in seven adult male Sprague-Dawley rats followed by functional imaging at 9.4T 4 months later. As controls we used six sham-operated animals that underwent all surgical operations but were not injured. Electroencephalogram (EEG-functional magnetic resonance imaging (fMRI was performed to measure resting functional connectivity. A week after functional imaging, rats were implanted with bipolar skull electrodes. After recovery, rats underwent pentyleneterazol (PTZ seizure-susceptibility test under EEG. For image analysis, four pairs of regions of interests were analyzed in each hemisphere: ipsilateral and contralateral frontal and parietal cortex, hippocampus, and thalamus. High-pass and low-pass filters were applied to functional imaging data. Group statistics comparing injured and sham-operated rats and correlations over time between each region were calculated. In the end, rats were perfused for histology. None of the rats had epileptiform discharges during functional imaging. PTZ-test, however revealed increased seizure susceptibility in injured rats as compared to controls. Group statistics revealed decreased connectivity between the ipsilateral and contralateral parietal cortex and between the parietal cortex and hippocampus on the side of injury as compared to sham-operated animals. Injured animals also had abnormal negative connectivity between the ipsilateral and

EEG in connection with coma.

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Wilson, John A; Nordal, Helge J

2013-01-08

Coma is a dynamic condition that may have various causes. Important changes may take place rapidly, often with consequences for treatment. The purpose of this article is to provide a brief overview of EEG patterns in comas with various causes, and indicate how EEG contributes in an assessment of the prognosis for coma patients. The article is based on many years of clinical and research-based experience of EEG used for patients in coma. A self-built reference database was supplemented by searches for relevant articles in PubMed. EEG reveals immediate changes in coma, and can provide early information on cause and prognosis. It is the only diagnostic tool for detecting a non-convulsive epileptic status. Locked-in- syndrome may be overseen without EEG. Repeated EEG scans increase diagnostic certainty and make it possible to monitor the development of coma. EEG reflects brain function continuously and therefore holds a key place in the assessment and treatment of coma.

Video-EEG epilepsian diagnostiikassa - milloin ja miksi?

OpenAIRE

Mervaala, Esa; Mäkinen, Riikka; Peltola, Jukka; Eriksson, Kai; Jutila, Leena; Immonen, Arto

2009-01-01

Aivosähkötoimintaa mittaava EEG on epilepsian spesifinen tutkimus. Video-EEG:llä (V-EEG) tarkoitetaan EEG:n ja videokuvan samanaikaista tallennusta. Valtaosa epilepsiapotilaista joudutaan diagnosoimaan ilman V-EEG:tä, varsinkin jos kohtauksia on esiintynyt vain muutama. Kohtausten toistuessa tavoite on päästä kohtauksenaikaiseen V-EEG-rekisteröintiin. V-EEG:n käyttöaiheista tärkein on epilepsian diagnostiikka ja erotusdiagnostiikka. V-EEG:llä pystytään erottamaan epileptiset kohtaukset esimer...

Clinical utility of early amplitude integrated EEG in monitoring term newborns at risk of neurological injury

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Paulina A. Toso

2014-04-01

Full Text Available OBJECTIVE: to test the clinical utility of an early amplitude-integrated electroencephalography (aEEG to predict short-term neurological outcome in term newborns at risk of neurology injury. METHODS: this was a prospective, descriptive study. The inclusion criteria were neonatal encephalopathy, neurologic disturbances, and severe respiratory distress syndrome. Sensitivity, specificity, positive and negative predictive values, and likelihood ratio (LR were calculated. Clinical and demographic data were analyzed. Neurological outcome was defined as the sum of clinical, electroimaging, and neuroimaging findings. RESULTS: ten of the 21 monitored infants (48% presented altered short-term neurologic outcome. The aEEG had 90% sensitivity, 82% specificity, 82% positive predictive value, and 90% negative predictive value. The positive LR was 4.95, and the negative LR was 0.12. In three of 12 (25% encephalopathic infants, the aEEG allowed for a better definition of the severity of their condition. Seizures were detected in eight infants (38%, all subclinical at baseline, and none had a normal aEEG background pattern. The status of three infants (43% evolved and required two or more drugs for treatment. CONCLUSIONS: in infants with encephalopathy or other severe illness, aEEG disturbances occur frequently. aEEG provided a better classification of the severity of encephalopathy, detected early subclinical seizures, and allowed for monitoring of the response to treatment. aEEG was a useful tool at the neonatal intensive care unit for predicting poor short-term neurological outcomes for all sick newborn.

Tele-transmission of EEG recordings.

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Lemesle, M; Kubis, N; Sauleau, P; N'Guyen The Tich, S; Touzery-de Villepin, A

2015-03-01

EEG recordings can be sent for remote interpretation. This article aims to define the tele-EEG procedures and technical guidelines. Tele-EEG is a complete medical act that needs to be carried out with the same quality requirements as a local one in terms of indications, formulation of the medical request and medical interpretation. It adheres to the same quality requirements for its human resources and materials. It must be part of a medical organization (technical and medical network) and follow all rules and guidelines of good medical practices. The financial model of this organization must include costs related to performing the EEG recording, operating and maintenance of the tele-EEG network and medical fees of the physician interpreting the EEG recording. Implementing this organization must be detailed in a convention between all parties involved: physicians, management of the healthcare structure, and the company providing the tele-EEG service. This convention will set rules for network operation and finance, and also the continuous training of all staff members. The tele-EEG system must respect all rules for safety and confidentiality, and ensure the traceability and storing of all requests and reports. Under these conditions, tele-EEG can optimize the use of human resources and competencies in its zone of utilization and enhance the organization of care management. Copyright © 2015. Published by Elsevier SAS.

Electroencephalogy (EEG) Feedback in Decision-Making

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2015-08-26

Electroencephalogy ( EEG ) Feedback In Decision- Making The goal of this project is to investigate whether Electroencephalogy ( EEG ) can provide useful...feedback when training rapid decision-making. More specifically, EEG will allow us to provide online feedback about the neural decision processes...Electroencephalogy ( EEG ) Feedback In Decision-Making Report Title The goal of this project is to investigate whether Electroencephalogy ( EEG ) can provide useful

Bilateral 5 Hz transcranial alternating current stimulation on fronto-temporal areas modulates resting-state EEG.

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D'Atri, Aurora; Romano, Claudia; Gorgoni, Maurizio; Scarpelli, Serena; Alfonsi, Valentina; Ferrara, Michele; Ferlazzo, Fabio; Rossini, Paolo Maria; De Gennaro, Luigi

2017-11-15

Rhythmic non-invasive brain stimulations are promising tools to modulate brain activity by entraining neural oscillations in specific cortical networks. The aim of the study was to assess the possibility to influence the neural circuits of the wake-sleep transition in awake subjects via a bilateral transcranial alternating current stimulation at 5 Hz (θ-tACS) on fronto-temporal areas. 25 healthy volunteers participated in two within-subject sessions (θ-tACS and sham), one week apart and in counterbalanced order. We assessed the stimulation effects on cortical EEG activity (28 derivations) and self-reported sleepiness (Karolinska Sleepiness Scale). θ-tACS induced significant increases of the theta activity in temporo-parieto-occipital areas and centro-frontal increases in the alpha activity compared to sham but failed to induce any online effect on sleepiness. Since the total energy delivered in the sham condition was much less than in the active θ-tACS, the current data are unable to isolate the specific effect of entrained theta oscillatory activity per se on sleepiness scores. On this basis, we concluded that θ-tACS modulated theta and alpha EEG activity with a topography consistent with high sleep pressure conditions. However, no causal relation can be traced on the basis of the current results between these rhythms and changes on sleepiness.

Idiopathic normal pressure hydrocephalus, quantitative EEG findings, and the cerebrospinal fluid tap test: a pilot study.

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Seo, Jong-Geun; Kang, Kyunghun; Jung, Ji-Young; Park, Sung-Pa; Lee, Maan-Gee; Lee, Ho-Won

2014-12-01

In this pilot study, we analyzed relationships between quantitative EEG measurements and clinical parameters in idiopathic normal pressure hydrocephalus patients, along with differences in these quantitative EEG markers between cerebrospinal fluid tap test responders and nonresponders. Twenty-six idiopathic normal pressure hydrocephalus patients (9 cerebrospinal fluid tap test responders and 17 cerebrospinal fluid tap test nonresponders) constituted the final group for analysis. The resting EEG was recorded and relative powers were computed for seven frequency bands. Cerebrospinal fluid tap test nonresponders, when compared with responders, showed a statistically significant increase in alpha2 band power at the right frontal and centrotemporal regions. Higher delta2 band powers in the frontal, central, parietal, and occipital regions and lower alpha1 band powers in the right temporal region significantly correlated with poorer cognitive performance. Higher theta1 band powers in the left parietal and occipital regions significantly correlated with gait dysfunction. And higher delta1 band powers in the right frontal regions significantly correlated with urinary disturbance. Our findings may encourage further research using quantitative EEG in patients with ventriculomegaly as a potential electrophysiological marker for predicting cerebrospinal fluid tap test responders. This study additionally suggests that the delta, theta, and alpha bands are statistically correlated with the severity of symptoms in idiopathic normal pressure hydrocephalus patients.

Fractionation of parietal function in bistable perception probed with concurrent TMS-EEG.

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Schauer, Georg; Chang, Acer; Schwartzman, David; Rae, Charlotte L; Iriye, Heather; Seth, Anil K; Kanai, Ryota

2016-08-16

When visual input has conflicting interpretations, conscious perception can alternate spontaneously between these possible interpretations. This is called bistable perception. Previous neuroimaging studies have indicated the involvement of two right parietal areas in resolving perceptual ambiguity (ant-SPLr and post-SPLr). Transcranial magnetic stimulation (TMS) studies that selectively interfered with the normal function of these regions suggest that they play opposing roles in this type of perceptual switch. In the present study, we investigated this fractionation of parietal function by use of combined TMS with electroencephalography (EEG). Specifically, while participants viewed either a bistable stimulus, a replay stimulus, or resting-state fixation, we applied single pulse TMS to either location independently while simultaneously recording EEG. Combined with participant's individual structural magnetic resonance imaging (MRI) scans, this dataset allows for complex analyses of the effect of TMS on neural time series data, which may further elucidate the causal role of the parietal cortex in ambiguous perception.

Analysing coupling architecture in the cortical EEG of a patient with unilateral cerebral palsy

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Kornilov, Maksim V.; Baas, C. Marjolein; van Rijn, Clementina M.; Sysoev, Ilya V.

2016-04-01

The detection of coupling presence and direction between cortical areas from the EEG is a popular approach in neuroscience. Granger causality method is promising for this task, since it allows to operate with short time series and to detect nonlinear coupling or coupling between nonlinear systems. In this study EEG multichannel data from adolescent children, suffering from unilateral cerebral palsy were investigated. Signals, obtained in rest and during motor activity of affected and less affected hand, were analysed. The changes in inter-hemispheric and intra-hemispheric interactions were studied over time with an interval of two months. The obtained results of coupling were tested for significance using surrogate times series. In the present proceeding paper we report the data of one patient. The modified nonlinear Granger causality is indeed able to reveal couplings within the human brain.

Index finger motor imagery EEG pattern recognition in BCI applications using dictionary cleaned sparse representation-based classification for healthy people

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Miao, Minmin; Zeng, Hong; Wang, Aimin; Zhao, Fengkui; Liu, Feixiang

2017-09-01

Electroencephalogram (EEG)-based motor imagery (MI) brain-computer interface (BCI) has shown its effectiveness for the control of rehabilitation devices designed for large body parts of the patients with neurologic impairments. In order to validate the feasibility of using EEG to decode the MI of a single index finger and constructing a BCI-enhanced finger rehabilitation system, we collected EEG data during right hand index finger MI and rest state for five healthy subjects and proposed a pattern recognition approach for classifying these two mental states. First, Fisher's linear discriminant criteria and power spectral density analysis were used to analyze the event-related desynchronization patterns. Second, both band power and approximate entropy were extracted as features. Third, aiming to eliminate the abnormal samples in the dictionary and improve the classification performance of the conventional sparse representation-based classification (SRC) method, we proposed a novel dictionary cleaned sparse representation-based classification (DCSRC) method for final classification. The experimental results show that the proposed DCSRC method gives better classification accuracies than SRC and an average classification accuracy of 81.32% is obtained for five subjects. Thus, it is demonstrated that single right hand index finger MI can be decoded from the sensorimotor rhythms, and the feature patterns of index finger MI and rest state can be well recognized for robotic exoskeleton initiation.

Low-Rank Linear Dynamical Systems for Motor Imagery EEG.

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Zhang, Wenchang; Sun, Fuchun; Tan, Chuanqi; Liu, Shaobo

2016-01-01

The common spatial pattern (CSP) and other spatiospectral feature extraction methods have become the most effective and successful approaches to solve the problem of motor imagery electroencephalography (MI-EEG) pattern recognition from multichannel neural activity in recent years. However, these methods need a lot of preprocessing and postprocessing such as filtering, demean, and spatiospectral feature fusion, which influence the classification accuracy easily. In this paper, we utilize linear dynamical systems (LDSs) for EEG signals feature extraction and classification. LDSs model has lots of advantages such as simultaneous spatial and temporal feature matrix generation, free of preprocessing or postprocessing, and low cost. Furthermore, a low-rank matrix decomposition approach is introduced to get rid of noise and resting state component in order to improve the robustness of the system. Then, we propose a low-rank LDSs algorithm to decompose feature subspace of LDSs on finite Grassmannian and obtain a better performance. Extensive experiments are carried out on public dataset from "BCI Competition III Dataset IVa" and "BCI Competition IV Database 2a." The results show that our proposed three methods yield higher accuracies compared with prevailing approaches such as CSP and CSSP.

Correlated alpha activity with the facial expression processing network in a simultaneous EEG-fMRI experiment.

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Simoes, Marco; Direito, Bruno; Lima, Joao; Castelhano, Joao; Ferreira, Carlos; Couceiro, Ricardo; Carvalho, Paulo; Castelo-Branco, Miguel

2017-07-01

The relationship between EEG and fMRI data is poorly covered in the literature. Extensive work has been conducted in resting-state and epileptic activity, highlighting a negative correlation between the alpha power band of the EEG and the BOLD activity in the default-mode-network. The identification of an appropriate task-specific relationship between fMRI and EEG data for predefined regions-of-interest, would allow the transfer of interventional paradigms (such as BOLD-based neurofeedback sessions) from fMRI to EEG, enhancing its application range by lowering its costs and improving its flexibility. In this study, we present an analysis of the correlation between task-specific alpha band fluctuations and BOLD activity in the facial expressions processing network. We characterized the network ROIs through a stringent localizer and identified two clusters on the scalp (one frontal, one parietal-occipital) with marked alpha fluctuations, related to the task. We then check whether such power variations throughout the time correlate with the BOLD activity in the network. Our results show statistically significant negative correlations between the alpha power in both clusters and for all the ROIs of the network. The correlation levels have still not met the requirements for transferring the protocol to an EEG setup, but they pave the way towards a better understand on how frontal and parietal-occipital alpha relates to the activity of the facial expressions processing network.

[Dextrals and sinistrals (right-handers and left-handers): specificity of interhemispheric brain asymmetry and EEG coherence parameters].

Science.gov (United States)

Zhavoronkova, L A

2007-01-01

Data of literature about morphological, functional and biochemical specificity of the brain interhemispheric asymmetry of healthy right-handers and left-handers and about peculiarity of dynamics of cerebral pathology in patients with different individual asymmetry profiles are presented at the present article. Results of our investigation by using coherence parameters of electroencephalogram (EEG) in healthy right-handers and left-handers in state of rest, during functional tests and sleeping and in patients with different forms of the brain organic damage were analyzed too. EEG coherence analysis revealed the reciprocal changing of alpha-beta and theta-delta spectral bands in right-handers whilein left-handers synchronous changing of all EEG spectral bands were observed. Data about regional-frequent specificity of EEG coherence, peculiarity of EEG asymmetry in right-handers and left-handers, aslo about specificity of EEG spectral band genesis and point of view about a role of the brain regulator systems in forming of interhemispheric asymmetry in different functional states allowed to propose the conception about principle of interhermispheric brain asymmetry formation in left-handers and left-handers. Following this conception in dextrals elements of concurrent (summary-reciprocal) cooperation are predominant at the character of interhemispheric and cortical-subcortical interaction while in sinistrals a principle of concordance (supplementary) is preferable. These peculiarities the brain organization determine, from the first side, the quicker revovery of functions damaged after cranio-cerebral trauma in left-handers in comparison right-handers and from the other side - they determine the forming of the more expressed pathology in the remote terms after exposure the low dose of radiation.

Resting-state theta-band connectivity and verbal memory in schizophrenia and in the high-risk state.

Science.gov (United States)

Andreou, Christina; Leicht, Gregor; Nolte, Guido; Polomac, Nenad; Moritz, Steffen; Karow, Anne; Hanganu-Opatz, Ileana L; Engel, Andreas K; Mulert, Christoph

2015-02-01

Disturbed functional connectivity is assumed to underlie neurocognitive deficits in patients with schizophrenia. As neurocognitive deficits are already present in the high-risk state, identification of the neural networks involved in this core feature of schizophrenia is essential to our understanding of the disorder. Resting-state studies enable such investigations, while at the same time avoiding the known confounder of impaired task performance in patients. The aim of the present study was to investigate EEG resting-state connectivity in high-risk individuals (HR) compared to first episode patients with schizophrenia (SZ) and to healthy controls (HC), and its association with cognitive deficits. 64-channel resting-state EEG recordings (eyes closed) were obtained for 28 HR, 19 stable SZ, and 23 HC, matched for age, education, and parental education. The imaginary coherence-based multivariate interaction measure (MIM) was used as a measure of connectivity across 80 cortical regions and six frequency bands. Mean connectivity at each region was compared across groups using the non-parametric randomization approach. Additionally, the network-based statistic was applied to identify affected networks in patients. SZ displayed increased theta-band resting-state MIM connectivity across midline, sensorimotor, orbitofrontal regions and the left temporoparietal junction. HR displayed intermediate theta-band connectivity patterns that did not differ from either SZ or HC. Mean theta-band connectivity within the above network partially mediated verbal memory deficits in SZ and HR. Aberrant theta-band connectivity may represent a trait characteristic of schizophrenia associated with neurocognitive deficits. As such, it might constitute a promising target for novel treatment applications. Copyright © 2014 Elsevier B.V. All rights reserved.

Educational simulation of the electroencephalogram (EEG)

NARCIS (Netherlands)

Beer, de N.A.M.; Meurs, van W.L.; Grit, M.B.M.; Good, M.L.; Gravenstein, D.

2001-01-01

We describe a model for simulating a spontaneous electroencephalogram (EEG) and for simulating the effects of anesthesia on the EEG, to allow anesthesiologists and EEG technicians to learn and practice intraoperative EEG monitoring. For this purpose, we developed a linear model to manipulate the

The use of EEG to measure cerebral changes during computer-based motion-sickness-inducing tasks

Science.gov (United States)

Strychacz, Christopher; Viirre, Erik; Wing, Shawn

2005-05-01

Motion sickness (MS) is a stressor commonly attributed with causing serious navigational and performance errors. The distinct nature of MS suggests this state may have distinct neural markers distinguishable from other states known to affect performance (e.g., stress, fatigue, sleep deprivation, high workload). This pilot study used new high-resolution electro-encephalograph (EEG) technologies to identify distinct neuronal activation changes that occur during MS. Brain EEG activity was monitored while subjects performed a ball-tracking task and viewed stimuli on a projection screen intended to induce motion sickness/spatial disorientation. Results show the presence of EEG spectral changes in all subjects who developed motion sickness when compared to baseline levels. These changes included: 1) low frequency (1 to 10 Hz) changes that may reflect oculomotor movements rather than intra-cerebral sources; 2) increased spectral power across all frequencies (attributable to increased scalp conductivity related to sweating), 3) local increases of power spectra in the 20-50 Hz range (likely attributable to external muscles on the skull) and; 4) a central posterior (occipital) independent component that shows suppression of a 20 Hz peak in the MS condition when compared to baseline. Further research is necessary to refine neural markers, characterize their origin and physiology, to distinguish between motion sickness and other states and to enable markers to be used for operator state monitoring and the designing of interventions for motion sickness.

Relative power and coherence of EEG series are related to amnestic mild cognitive impairment in diabetes

Directory of Open Access Journals (Sweden)

Zhijie eBian

2014-02-01

Full Text Available Objective: Diabetes is a risk factor for dementia and mild cognitive impairment. The aim of this study was to investigate whether some features of resting-state EEG (rsEEG could be applied as a biomarker to distinguish the subjects with amnestic mild cognitive impairment (aMCI from normal cognitive function in type 2 diabetes. Materials and Methods: In this study, 28 patients with type 2 diabetes (16 aMCI patients and 12 controls were investigated. Recording of the rsEEG series and neuropsychological assessments were performed. The rsEEG signal was first decomposed into delta, theta, alpha, beta, gamma frequency bands. The relative power of each given band/sum of power and the coherence of waves from different brain areas were calculated. The extracted features from rsEEG and neuropsychological assessments were analyzed as well. Results: The main findings of this study were that: 1 compared with the control group, the ratios of power in theta band (P(theta versus power in alpha band (P(alpha (P(theta/P(alpha in the frontal region and left temporal region were significantly higher for aMCI, and 2 for aMCI, the alpha coherences in posterior, fronto-right temporal, fronto-posterior, right temporo-posterior were decreased; the theta coherences in left central-right central (LC-RC and left posterior-right posterior (LP-RP regions were also decreased; but the delta coherences in left temporal-right temporal (LT-RT region were increased. Conclusion: The proposed indexes from rsEEG recordings could be employed to track cognitive function of diabetic patients and also to help in the diagnosis of those who develop aMCI.

Multifractal Detrended Fluctuation Analysis of alpha and theta EEG rhythms with musical stimuli

International Nuclear Information System (INIS)

Maity, Akash Kumar; Pratihar, Ruchira; Mitra, Anubrato; Dey, Subham; Agrawal, Vishal; Sanyal, Shankha; Banerjee, Archi; Sengupta, Ranjan; Ghosh, Dipak

2015-01-01

Highlights: • EEG was done to record the brain electrical activity of 10 subjects in response to simple acoustical tanpura stimuli. • Empirical Mode Decomposition (EMD) technique used to make the EEG signal free from blink and other muscular artifacts. • Multifractal Detrended Fluctuation Analysis (MFDFA) performed to assess the complexity of extracted alpha and theta brain rhythms. • The findings show spectral width i.e. complexity of alpha and theta rhythms increase in all the seven frontal locations studied, under the effect of musical stimuli. - Abstract: Electroencephalography (EEG) was performed on 10 participants using a simple acoustical stimuli i.e. a tanpura drone. The tanpura drone is free from any semantic content and is used with a hypothesis that it provides a specific resting environment for the listeners. The EEG data was extracted for all the frontal electrodes viz. F3, F4, F7, F8, Fp1, Fp2 and Fz. Empirical Mode Decomposition (EMD) was applied on the acquired raw EEG signal to make it free from blink as well as other muscular artifacts. Wavelet Transform (WT) technique was used to segregate alpha and theta waves from the denoised EEG signal. Non-linear analysis in the form of Multifractal Detrended Fluctuation Analysis (MFDFA) was carried out on the extracted alpha and theta time series data to study the variation of their complexity. It was found that in all the frontal electrodes alpha as well as theta complexity increases as is evident from the increase of multifractal spectral width. This study is entirely new and gives interesting data regarding neural activation of the alpha and theta brain rhythms while listening to simple acoustical stimuli. The importance of this study lies in the context of emotion quantification using multifractal spectral width as a parameter as well as in the field of cognitive music therapy. The results are discussed in detail.

Effects of 2G and 3G mobile phones on human alpha rhythms: Resting EEG in adolescents, young adults, and the elderly.

Science.gov (United States)

Croft, R J; Leung, S; McKenzie, R J; Loughran, S P; Iskra, S; Hamblin, D L; Cooper, N R

2010-09-01

The present study was conducted to determine whether adolescents and/or the elderly are more sensitive to mobile phone (MP)-related bioeffects than young adults, and to determine this for both 2nd generation (2G) GSM, and 3rd generation (3G) W-CDMA exposures. To test this, resting alpha activity (8-12 Hz band of the electroencephalogram) was assessed because numerous studies have now reported it to be enhanced by MP exposure. Forty-one 13-15 year olds, forty-two 19-40 year olds, and twenty 55-70 year olds were tested using a double-blind crossover design, where each participant received Sham, 2G and 3G exposures, separated by at least 4 days. Alpha activity, during exposure relative to baseline, was recorded and compared between conditions. Consistent with previous research, the young adults' alpha was greater in the 2G compared to Sham condition, however, no effect was seen in the adolescent or the elderly groups, and no effect of 3G exposures was found in any group. The results provide further support for an effect of 2G exposures on resting alpha activity in young adults, but fail to support a similar enhancement in adolescents or the elderly, or in any age group as a function of 3G exposure. 2010 Wiley-Liss, Inc.

Diagnosis of autism through EEG processed by advanced computational algorithms: A pilot study.

Science.gov (United States)

Grossi, Enzo; Olivieri, Chiara; Buscema, Massimo

2017-04-01

Multi-Scale Ranked Organizing Map coupled with Implicit Function as Squashing Time algorithm(MS-ROM/I-FAST) is a new, complex system based on Artificial Neural networks (ANNs) able to extract features of interest in computerized EEG through the analysis of few minutes of their EEG without any preliminary pre-processing. A proof of concept study previously published showed accuracy values ranging from 94%-98% in discerning subjects with Mild Cognitive Impairment and/or Alzheimer's Disease from healthy elderly people. The presence of deviant patterns in simple resting state EEG recordings in autism, consistent with the atypical organization of the cerebral cortex present, prompted us in applying this potent analytical systems in search of a EEG signature of the disease. The aim of the study is to assess how effectively this methodology distinguishes subjects with autism from typically developing ones. Fifteen definite ASD subjects (13 males; 2 females; age range 7-14; mean value = 10.4) and ten typically developing subjects (4 males; 6 females; age range 7-12; mean value 9.2) were included in the study. Patients received Autism diagnoses according to DSM-V criteria, subsequently confirmed by the ADOS scale. A segment of artefact-free EEG lasting 60 seconds was used to compute input values for subsequent analyses. MS-ROM/I-FAST coupled with a well-documented evolutionary system able to select predictive features (TWIST) created an invariant features vector input of EEG on which supervised machine learning systems acted as blind classifiers. The overall predictive capability of machine learning system in sorting out autistic cases from normal control amounted consistently to 100% with all kind of systems employed using training-testing protocol and to 84% - 92.8% using Leave One Out protocol. The similarities among the ANN weight matrixes measured with apposite algorithms were not affected by the age of the subjects. This suggests that the ANNs do not read age

Complexity analysis of EEG in patients with schizophrenia using fractal dimension

International Nuclear Information System (INIS)

Raghavendra, B S; Dutt, D Narayana; Halahalli, Harsha N; John, John P

2009-01-01

We computed Higuchi's fractal dimension (FD) of resting, eyes closed EEG recorded from 30 scalp locations in 18 male neuroleptic-naïve, recent-onset schizophrenia (NRS) subjects and 15 male healthy control (HC) subjects, who were group-matched for age. Schizophrenia patients showed a diffuse reduction of FD except in the bilateral temporal and occipital regions, with the reduction being most prominent bifrontally. The positive symptom (PS) schizophrenia subjects showed FD values similar to or even higher than HC in the bilateral temporo-occipital regions, along with a co-existent bifrontal FD reduction as noted in the overall sample of NRS. In contrast, this increase in FD values in the bilateral temporo-occipital region was absent in the negative symptom (NS) subgroup. The regional differences in complexity suggested by these findings may reflect the aberrant brain dynamics underlying the pathophysiology of schizophrenia and its symptom dimensions. Higuchi's method of measuring FD directly in the time domain provides an alternative for the more computationally intensive nonlinear methods of estimating EEG complexity

PyEEG: An Open Source Python Module for EEG/MEG Feature Extraction

OpenAIRE

Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

2011-01-01

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting ...

EEG use in a tertiary referral centre.

LENUS (Irish Health Repository)

O'Toole, O

2011-11-15

The aim of this study was to retrospectively audit all electroencephalograms (EEGs) done over a 2-month period in 2009 by the Neurophysiology Department at Cork University Hospital. There were 316 EEGs performed in total, of which 176\\/316 (56%) were done within 24 hours of request. Out of 316 EEGs, 208 (66%) were considered \\'appropriate\\' by SIGN and NICE guidelines; 79\\/208 (38%) had abnormal EEGs and 28 of these abnormal EEGs had epileptiform features. There were 108\\/316 (34%) \\'inappropriate\\' requests for EEG; of these 15\\/108 (14%) were abnormal. Of the 67\\/316 (21%) patients who had EEGs requested based on a history of syncope\\/funny turns: none of these patients had epileptiform abnormalities on their EEGs. Our audit demonstrates that EEGs are inappropriately over-requested in our institution in particular for cases with reported \\'funny turns\\' and syncope. The yield from EEGs in this cohort of patients was low as would be expected.

EEG alpha power as an intermediate measure between brain-derived neurotrophic factor Val66Met and depression severity in patients with major depressive disorder.

Science.gov (United States)

Zoon, Harriët F A; Veth, C P M; Arns, Martijn; Drinkenburg, W H I M; Talloen, Willem; Peeters, Pieter J; Kenemans, J L

2013-06-01

Major depressive disorder has a large impact on patients and society and is projected to be the second greatest global burden of disease by 2020. The brain-derived neurotrophic factor (BDNF) gene is considered to be one of the important factors in the etiology of major depressive disorder. In a recent study, alpha power was found to mediate between BDNF Met and subclinical depressed mood. The current study looked at a population of patients with major depressive disorder (N = 107) to examine the association between the BDNF Val66Met polymorphism, resting state EEG alpha power, and depression severity. For this purpose, repeated-measures analysis of variance, partial correlation, and multiple linear models were used. Results indicated a negative association between parietal-occipital alpha power in the eyes open resting state and depression severity. In addition, Met/Met patients showed lower global absolute alpha power in the eyes closed condition compared with Val-carriers. These findings are in accordance with the previously uncovered pathway between BDNF Val66Met, resting state EEG alpha power, and depression severity. Additional research is needed for the clarification of this tentative pathway and its implication in personalized treatment of major depressive disorder.

Resting-state functional connectivity remains unaffected by preceding exposure to aversive visual stimuli.

Science.gov (United States)

Geissmann, Léonie; Gschwind, Leo; Schicktanz, Nathalie; Deuring, Gunnar; Rosburg, Timm; Schwegler, Kyrill; Gerhards, Christiane; Milnik, Annette; Pflueger, Marlon O; Mager, Ralph; de Quervain, Dominique J F; Coynel, David

2018-02-15

While much is known about immediate brain activity changes induced by the confrontation with emotional stimuli, the subsequent temporal unfolding of emotions has yet to be explored. To investigate whether exposure to emotionally aversive pictures affects subsequent resting-state networks differently from exposure to neutral pictures, a resting-state fMRI study implementing a two-group repeated-measures design in healthy young adults (N = 34) was conducted. We focused on investigating (i) patterns of amygdala whole-brain and hippocampus connectivity in both a seed-to-voxel and seed-to-seed approach, (ii) whole-brain resting-state networks with an independent component analysis coupled with dual regression, and (iii) the amygdala's fractional amplitude of low frequency fluctuations, all while EEG recording potential fluctuations in vigilance. In spite of the successful emotion induction, as demonstrated by stimuli rating and a memory-facilitating effect of negative emotionality, none of the resting-state measures was differentially affected by picture valence. In conclusion, resting-state networks connectivity as well as the amygdala's low frequency oscillations appear to be unaffected by preceding exposure to widely used emotionally aversive visual stimuli in healthy young adults. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Objective Audiometry using Ear-EEG

DEFF Research Database (Denmark)

Christensen, Christian Bech; Kidmose, Preben

Recently, a novel electroencephalographic (EEG) method called ear-EEG [1], that enable recording of auditory evoked potentials (AEPs) from a personalized earpiece was introduced. Initial investigations show that well established AEPs, such as ASSR and P1-N1-P2 complex can be observed from ear-EEG...

Bed Rest and Hypoxic Exposure Affect Sleep Architecture and Breathing Stability

Directory of Open Access Journals (Sweden)

Shawnda A. Morrison

2017-06-01

Full Text Available Objective: Despite over 50 years of research on the physiological effects of sustained bed rest, data characterizing its effects on sleep macrostructure and breathing stability in humans are scarce. This study was conducted to determine the effects of continuous exposure to hypoxia and sustained best rest, both individually and combined, on nocturnal sleep and breathing stability.Methods: Eleven participants completed three randomized, counter-balanced, 21-days trials of: (1 normoxic bed rest (NBR, PIO2 = 133.1 ± 0.3, (2 hypoxic ambulatory confinement (HAMB, PIO2 = 90.0 ± 0.4 and (3 hypoxic bed rest (HBR, PIO2 = 90.0 ± 0.4; ~4,000 m equivalent altitude. Full objective polysomnography was performed at baseline, on Night 1 and Night 21 in each condition.Results: In NBR Night 1, more time was spent in light sleep (10 ± 2% compared to baseline (8 ± 2%; p = 0.028; Slow-wave sleep (SWS was reduced from baseline in the hypoxic-only trial by 18% (HAMB Night 21, p = 0.028 and further reduced by 33% (HBR Night 1, p = 0.010, and 36% (HBR Night 21, p = 0.008 when combined with bed rest. The apnea-hypopnea index doubled from Night 1 to Night 21 in HBR (32–62 events·h−1 and HAMB (31–59 events·h−1; p = 0.002. Those who experienced greatest breathing instability from Night 1 to Night 21 (NBR were correlated to unchanged or higher (+1% night SpO2 concentrations (R2 = 0.471, p = 0.020.Conclusion: Bed rest negatively affects sleep macrostructure, increases the apnea-hypopnea index, and worsens breathing stability, each independently exacerbated by continuous exposure to hypoxia.

Bed Rest and Hypoxic Exposure Affect Sleep Architecture and Breathing Stability

Science.gov (United States)

Morrison, Shawnda A.; Mirnik, Dani; Korsic, Spela; Eiken, Ola; Mekjavic, Igor B.; Dolenc-Groselj, Leja

2017-01-01

Objective: Despite over 50 years of research on the physiological effects of sustained bed rest, data characterizing its effects on sleep macrostructure and breathing stability in humans are scarce. This study was conducted to determine the effects of continuous exposure to hypoxia and sustained best rest, both individually and combined, on nocturnal sleep and breathing stability. Methods: Eleven participants completed three randomized, counter-balanced, 21-days trials of: (1) normoxic bed rest (NBR, PIO2 = 133.1 ± 0.3), (2) hypoxic ambulatory confinement (HAMB, PIO2 = 90.0 ± 0.4) and (3) hypoxic bed rest (HBR, PIO2 = 90.0 ± 0.4; ~4,000 m equivalent altitude). Full objective polysomnography was performed at baseline, on Night 1 and Night 21 in each condition. Results: In NBR Night 1, more time was spent in light sleep (10 ± 2%) compared to baseline (8 ± 2%; p = 0.028); Slow-wave sleep (SWS) was reduced from baseline in the hypoxic-only trial by 18% (HAMB Night 21, p = 0.028) and further reduced by 33% (HBR Night 1, p = 0.010), and 36% (HBR Night 21, p = 0.008) when combined with bed rest. The apnea-hypopnea index doubled from Night 1 to Night 21 in HBR (32–62 events·h−1) and HAMB (31–59 events·h−1; p = 0.002). Those who experienced greatest breathing instability from Night 1 to Night 21 (NBR) were correlated to unchanged or higher (+1%) night SpO2 concentrations (R2 = 0.471, p = 0.020). Conclusion: Bed rest negatively affects sleep macrostructure, increases the apnea-hypopnea index, and worsens breathing stability, each independently exacerbated by continuous exposure to hypoxia. PMID:28676764

Ear-EEG detects ictal and interictal abnormalities in focal and generalized epilepsy - A comparison with scalp EEG monitoring.

Science.gov (United States)

Zibrandtsen, I C; Kidmose, P; Christensen, C B; Kjaer, T W

2017-12-01

Ear-EEG is recording of electroencephalography from a small device in the ear. This is the first study to compare ictal and interictal abnormalities recorded with ear-EEG and simultaneous scalp-EEG in an epilepsy monitoring unit. We recorded and compared simultaneous ear-EEG and scalp-EEG from 15 patients with suspected temporal lobe epilepsy. EEGs were compared visually by independent neurophysiologists. Correlation and time-frequency analysis was used to quantify the similarity between ear and scalp electrodes. Spike-averages were used to assess similarity of interictal spikes. There were no differences in sensitivity or specificity for seizure detection. Mean correlation coefficient between ear-EEG and nearest scalp electrode was above 0.6 with a statistically significant decreasing trend with increasing distance away from the ear. Ictal morphology and frequency dynamics can be observed from visual inspection and time-frequency analysis. Spike averages derived from ear-EEG electrodes yield a recognizable spike appearance. Our results suggest that ear-EEG can reliably detect electroencephalographic patterns associated with focal temporal lobe seizures. Interictal spike morphology from sufficiently large temporal spike sources can be sampled using ear-EEG. Ear-EEG is likely to become an important tool in clinical epilepsy monitoring and diagnosis. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Aspartame exacerbates EEG spike-wave discharge in children with generalized absence epilepsy: a double-blind controlled study.

Science.gov (United States)

Camfield, P R; Camfield, C S; Dooley, J M; Gordon, K; Jollymore, S; Weaver, D F

1992-05-01

There are anecdotal reports of increased seizures in humans after ingestion of aspartame. We studied 10 children with newly diagnosed but untreated generalized absence seizures. Ambulatory cassette recording of EEG allowed quantification of numbers and length of spike-wave discharges in a double-blind study on two consecutive days. On one day the children received 40 mg/kg aspartame and on the other day, a sucrose-sweetened drink. Baseline EEG was the same before aspartame and sucrose. Following aspartame compared with sucrose, the number of spike-wave discharges per hour and mean length of spike-wave discharges increased but not to a statistically significant degree. However, the total duration of spike-wave discharge per hour was significantly increased after aspartame (p = 0.028), with a 40% +/- 17% (SEM) increase in the number of seconds per hour of EEG recording that the children spent in spike-wave discharge. Aspartame appears to exacerbate the amount of EEG spike wave in children with absence seizures. Further studies are needed to establish if this effect occurs at lower doses and in other seizure types.

Dysconnection topography in schizophrenia revealed with state-space analysis of EEG.

Science.gov (United States)

Jalili, Mahdi; Lavoie, Suzie; Deppen, Patricia; Meuli, Reto; Do, Kim Q; Cuénod, Michel; Hasler, Martin; De Feo, Oscar; Knyazeva, Maria G

2007-10-24

The dysconnection hypothesis has been proposed to account for pathophysiological mechanisms underlying schizophrenia. Widespread structural changes suggesting abnormal connectivity in schizophrenia have been imaged. A functional counterpart of the structural maps would be the EEG synchronization maps. However, due to the limits of currently used bivariate methods, functional correlates of dysconnection are limited to the isolated measurements of synchronization between preselected pairs of EEG signals. To reveal a whole-head synchronization topography in schizophrenia, we applied a new method of multivariate synchronization analysis called S-estimator to the resting dense-array (128 channels) EEG obtained from 14 patients and 14 controls. This method determines synchronization from the embedding dimension in a state-space domain based on the theoretical consequence of the cooperative behavior of simultaneous time series-the shrinking of the state-space embedding dimension. The S-estimator imaging revealed a specific synchronization landscape in schizophrenia patients. Its main features included bilaterally increased synchronization over temporal brain regions and decreased synchronization over the postcentral/parietal region neighboring the midline. The synchronization topography was stable over the course of several months and correlated with the severity of schizophrenia symptoms. In particular, direct correlations linked positive, negative, and general psychopathological symptoms to the hyper-synchronized temporal clusters over both hemispheres. Along with these correlations, general psychopathological symptoms inversely correlated within the hypo-synchronized postcentral midline region. While being similar to the structural maps of cortical changes in schizophrenia, the S-maps go beyond the topography limits, demonstrating a novel aspect of the abnormalities of functional cooperation: namely, regionally reduced or enhanced connectivity. The new method of

Dysconnection topography in schizophrenia revealed with state-space analysis of EEG.

Directory of Open Access Journals (Sweden)

Mahdi Jalili

2007-10-01

Full Text Available The dysconnection hypothesis has been proposed to account for pathophysiological mechanisms underlying schizophrenia. Widespread structural changes suggesting abnormal connectivity in schizophrenia have been imaged. A functional counterpart of the structural maps would be the EEG synchronization maps. However, due to the limits of currently used bivariate methods, functional correlates of dysconnection are limited to the isolated measurements of synchronization between preselected pairs of EEG signals.To reveal a whole-head synchronization topography in schizophrenia, we applied a new method of multivariate synchronization analysis called S-estimator to the resting dense-array (128 channels EEG obtained from 14 patients and 14 controls. This method determines synchronization from the embedding dimension in a state-space domain based on the theoretical consequence of the cooperative behavior of simultaneous time series-the shrinking of the state-space embedding dimension. The S-estimator imaging revealed a specific synchronization landscape in schizophrenia patients. Its main features included bilaterally increased synchronization over temporal brain regions and decreased synchronization over the postcentral/parietal region neighboring the midline. The synchronization topography was stable over the course of several months and correlated with the severity of schizophrenia symptoms. In particular, direct correlations linked positive, negative, and general psychopathological symptoms to the hyper-synchronized temporal clusters over both hemispheres. Along with these correlations, general psychopathological symptoms inversely correlated within the hypo-synchronized postcentral midline region. While being similar to the structural maps of cortical changes in schizophrenia, the S-maps go beyond the topography limits, demonstrating a novel aspect of the abnormalities of functional cooperation: namely, regionally reduced or enhanced connectivity.The new

Automatic EEG-assisted retrospective motion correction for fMRI (aE-REMCOR).

Science.gov (United States)

Wong, Chung-Ki; Zotev, Vadim; Misaki, Masaya; Phillips, Raquel; Luo, Qingfei; Bodurka, Jerzy

2016-04-01

correction efficiency over the 305 fMRI scans is 18% and the largest achieved efficiency is 71%. The utility of aE-REMCOR on the resting state fMRI connectivity of the default mode network is also examined. The motion-induced position-dependent error in the DMN connectivity analysis is shown to be reduced when aE-REMCOR is utilized. These results demonstrate that aE-REMCOR can be conveniently and efficiently used to improve fMRI motion correction in large clinical EEG-fMRI studies. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Hypnagogic imagery and EEG activity.

Science.gov (United States)

Hayashi, M; Katoh, K; Hori, T

1999-04-01

The relationships between hypnagogic imagery and EEG activity were studied. 7 subjects (4 women and 3 men) reported the content of hypnagogic imagery every minute and the hypnagogic EEGs were classified into 5 stages according to Hori's modified criteria. The content of the hypnagogic imagery changed as a function of the hypnagogic EEG stages.

EEG applications for sport and performance.

Science.gov (United States)

Thompson, Trevor; Steffert, Tony; Ros, Tomas; Leach, Joseph; Gruzelier, John

2008-08-01

One approach to understanding processes that underlie skilled performing has been to study electrical brain activity using electroencephalography (EEG). A notorious problem with EEG is that genuine cerebral data is often contaminated by artifacts of non-cerebral origin. Unfortunately, such artifacts tend to be exacerbated when the subject is in motion, meaning that obtaining reliable data during exercise is inherently problematic. These problems may explain the limited number of studies using EEG as a methodological tool in the sports sciences. This paper discusses how empirical studies have generally tackled the problem of movement artifact by adopting alternative paradigms which avoid recording during actual physical exertion. Moreover, the specific challenges that motion presents to obtaining reliable EEG data are discussed along with practical and computational techniques to confront these challenges. Finally, as EEG recording in sports is often underpinned by a desire to optimise performance, a brief review of EEG-biofeedback and peak performance studies is also presented. A knowledge of practical aspects of EEG recording along with the advent of new technology and increasingly sophisticated processing models offer a promising approach to minimising, if perhaps not entirely circumventing, the problem of obtaining reliable EEG data during motion.

Neural Mechanisms of Cognitive Dissonance (Revised): An EEG Study.

Science.gov (United States)

Colosio, Marco; Shestakova, Anna; Nikulin, Vadim V; Blagovechtchenski, Evgeny; Klucharev, Vasily

2017-05-17

Cognitive dissonance theory suggests that our preferences are modulated by the mere act of choosing. A choice between two similarly valued alternatives creates psychological tension (cognitive dissonance) that is reduced by a postdecisional reevaluation of the alternatives. We measured EEG of human subjects during rest and free-choice paradigm. Our study demonstrates that choices associated with stronger cognitive dissonance trigger a larger negative frontocentral evoked response similar to error-related negativity, which has in turn been implicated in general performance monitoring. Furthermore, the amplitude of the evoked response is correlated with the reevaluation of the alternatives. We also found a link between individual neural dynamics (long-range temporal correlations) of the frontocentral cortices during rest and follow-up neural and behavioral effects of cognitive dissonance. Individuals with stronger resting-state long-range temporal correlations demonstrated a greater postdecisional reevaluation of the alternatives and larger evoked brain responses associated with stronger cognitive dissonance. Thus, our results suggest that cognitive dissonance is reflected in both resting-state and choice-related activity of the prefrontal cortex as part of the general performance-monitoring circuitry. SIGNIFICANCE STATEMENT Contrary to traditional decision theory, behavioral studies repeatedly demonstrate that our preferences are modulated by the mere act of choosing. Difficult choices generate psychological (cognitive) dissonance, which is reduced by the postdecisional devaluation of unchosen options. We found that decisions associated with a higher level of cognitive dissonance elicited a stronger negative frontocentral deflection that peaked ∼60 ms after the response. This activity shares similar spatial and temporal features as error-related negativity, the electrophysiological correlate of performance monitoring. Furthermore, the frontocentral resting

Preterm EEG: a multimodal neurophysiological protocol.

Science.gov (United States)

Stjerna, Susanna; Voipio, Juha; Metsäranta, Marjo; Kaila, Kai; Vanhatalo, Sampsa

2012-02-18

Since its introduction in early 1950s, electroencephalography (EEG) has been widely used in the neonatal intensive care units (NICU) for assessment and monitoring of brain function in preterm and term babies. Most common indications are the diagnosis of epileptic seizures, assessment of brain maturity, and recovery from hypoxic-ischemic events. EEG recording techniques and the understanding of neonatal EEG signals have dramatically improved, but these advances have been slow to penetrate through the clinical traditions. The aim of this presentation is to bring theory and practice of advanced EEG recording available for neonatal units. In the theoretical part, we will present animations to illustrate how a preterm brain gives rise to spontaneous and evoked EEG activities, both of which are unique to this developmental phase, as well as crucial for a proper brain maturation. Recent animal work has shown that the structural brain development is clearly reflected in early EEG activity. Most important structures in this regard are the growing long range connections and the transient cortical structure, subplate. Sensory stimuli in a preterm baby will generate responses that are seen at a single trial level, and they have underpinnings in the subplate-cortex interaction. This brings neonatal EEG readily into a multimodal study, where EEG is not only recording cortical function, but it also tests subplate function via different sensory modalities. Finally, introduction of clinically suitable dense array EEG caps, as well as amplifiers capable of recording low frequencies, have disclosed multitude of brain activities that have as yet been overlooked. In the practical part of this video, we show how a multimodal, dense array EEG study is performed in neonatal intensive care unit from a preterm baby in the incubator. The video demonstrates preparation of the baby and incubator, application of the EEG cap, and performance of the sensory stimulations.

Homeostatic and Circadian Contribution to EEG and Molecular State Variables of Sleep Regulation

Science.gov (United States)

Curie, Thomas; Mongrain, Valérie; Dorsaz, Stéphane; Mang, Géraldine M.; Emmenegger, Yann; Franken, Paul

2013-01-01

Study Objectives: Besides their well-established role in circadian rhythms, our findings that the forebrain expression of the clock-genes Per2 and Dbp increases and decreases, respectively, in relation to time spent awake suggest they also play a role in the homeostatic aspect of sleep regulation. Here, we determined whether time of day modulates the effects of elevated sleep pressure on clock-gene expression. Time of day effects were assessed also for recognized electrophysiological (EEG delta power) and molecular (Homer1a) markers of sleep homeostasis. Design: EEG and qPCR data were obtained for baseline and recovery from 6-h sleep deprivation starting at ZT0, -6, -12, or -18. Setting: Mouse sleep laboratory. Participants: Male mice. Interventions: Sleep deprivation. Results: The sleep-deprivation induced changes in Per2 and Dbp expression importantly varied with time of day, such that Per2 could even decrease during sleep deprivations occurring at the decreasing phase in baseline. Dbp showed similar, albeit opposite dynamics. These unexpected results could be reliably predicted assuming that these transcripts behave according to a driven damped harmonic oscillator. As expected, the sleep-wake distribution accounted for a large degree of the changes in EEG delta power and Homer1a. Nevertheless, the sleep deprivation-induced increase in delta power varied also with time of day with higher than expected levels when recovery sleep started at dark onset. Conclusions: Per2 and delta power are widely used as exclusive state variables of the circadian and homeostatic process, respectively. Our findings demonstrate a considerable cross-talk between these two processes. As Per2 in the brain responds to both sleep loss and time of day, this molecule is well positioned to keep track of and to anticipate homeostatic sleep need. Citation: Curie T; Mongrain V; Dorsaz S; Mang GM; Emmenegger Y; Franken P. Homeostatic and circadian contribution to EEG and molecular state

Homeostatic and circadian contribution to EEG and molecular state variables of sleep regulation.

Science.gov (United States)

Curie, Thomas; Mongrain, Valérie; Dorsaz, Stéphane; Mang, Géraldine M; Emmenegger, Yann; Franken, Paul

2013-03-01

Besides their well-established role in circadian rhythms, our findings that the forebrain expression of the clock-genes Per2 and Dbp increases and decreases, respectively, in relation to time spent awake suggest they also play a role in the homeostatic aspect of sleep regulation. Here, we determined whether time of day modulates the effects of elevated sleep pressure on clock-gene expression. Time of day effects were assessed also for recognized electrophysiological (EEG delta power) and molecular (Homer1a) markers of sleep homeostasis. EEG and qPCR data were obtained for baseline and recovery from 6-h sleep deprivation starting at ZT0, -6, -12, or -18. Mouse sleep laboratory. Male mice. Sleep deprivation. The sleep-deprivation induced changes in Per2 and Dbp expression importantly varied with time of day, such that Per2 could even decrease during sleep deprivations occurring at the decreasing phase in baseline. Dbp showed similar, albeit opposite dynamics. These unexpected results could be reliably predicted assuming that these transcripts behave according to a driven damped harmonic oscillator. As expected, the sleep-wake distribution accounted for a large degree of the changes in EEG delta power and Homer1a. Nevertheless, the sleep deprivation-induced increase in delta power varied also with time of day with higher than expected levels when recovery sleep started at dark onset. Per2 and delta power are widely used as exclusive state variables of the circadian and homeostatic process, respectively. Our findings demonstrate a considerable cross-talk between these two processes. As Per2 in the brain responds to both sleep loss and time of day, this molecule is well positioned to keep track of and to anticipate homeostatic sleep need. Curie T; Mongrain V; Dorsaz S; Mang GM; Emmenegger Y; Franken P. Homeostatic and circadian contribution to EEG and molecular state variables of sleep regulation. SLEEP 2013;36(3):311-323.

Effects of Different Types of 3D Rest Frames on Reducing Cybersickness in a Virtual Environment

Directory of Open Access Journals (Sweden)

KyungHun Han

2011-10-01

Full Text Available A virtual environment (VE presents several kinds of sensory stimuli for creating a virtual reality. Some sensory stimuli presented in the VE have been reported to provoke cybersickness, which is caused by conflicts between sensory stimuli, especially conflicts between visual and vestibular sensations. Application of a rest frame has been known to be effective on reducing cybersickness by alleviating sensory conflict. The form and the way rest frames are presented in 3D VEs have different effects on reducing cybersickness. In this study, two different types of 3D rest frames were created. For verifying the rest frames' effects in reducing cybersickness, twenty subjects were exposed to two different rest frame conditions and a non-rest frame condition after an interval of three days in 3D VE. We observed the characteristic changes in the physiology of cybersickness in terms of autonomic regulation. Psychophysiological signals including EEG, EGG, and HRV were recorded and a simulator sickness questionnaire (SSQ was used for measuring the intensity of the sickness before and after the exposure to the different conditions. In the results, the SSQ was reduced significantly in the rest frame conditions. Psychophysiological responses changed significantly in the rest frame conditions compared to the non-rest frame condition. The results suggest that the rest frame conditions have condition-specific effects on reducing cybersickness by differentially alleviating aspects of visual and vestibular sensory conflicts in 3D VE.

Online Reduction of Artifacts in EEG of Simultaneous EEG-fMRI Using Reference Layer Adaptive Filtering (RLAF).

Science.gov (United States)

Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R

2018-01-01

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) allow us to study the active human brain from two perspectives concurrently. Signal processing based artifact reduction techniques are mandatory for this, however, to obtain reasonable EEG quality in simultaneous EEG-fMRI. Current artifact reduction techniques like average artifact subtraction (AAS), typically become less effective when artifact reduction has to be performed on-the-fly. We thus present and evaluate a new technique to improve EEG quality online. This technique adds up with online AAS and combines a prototype EEG-cap for reference recordings of artifacts, with online adaptive filtering and is named reference layer adaptive filtering (RLAF). We found online AAS + RLAF to be highly effective in improving EEG quality. Online AAS + RLAF outperformed online AAS and did so in particular online in terms of the chosen performance metrics, these being specifically alpha rhythm amplitude ratio between closed and opened eyes (3-45% improvement), signal-to-noise-ratio of visual evoked potentials (VEP) (25-63% improvement), and VEPs variability (16-44% improvement). Further, we found that EEG quality after online AAS + RLAF is occasionally even comparable with the offline variant of AAS at a 3T MRI scanner. In conclusion RLAF is a very effective add-on tool to enable high quality EEG in simultaneous EEG-fMRI experiments, even when online artifact reduction is necessary.

Serial EEG findings in anti-NMDA receptor encephalitis: correlation between clinical course and EEG.

Science.gov (United States)

Ueda, Jun; Kawamoto, Michi; Hikiami, Ryota; Ishii, Junko; Yoshimura, Hajime; Matsumoto, Riki; Kohara, Nobuo

2017-12-01

Anti-NMDA receptor encephalitis is a paraneoplastic encephalitis characterised by psychiatric features, involuntary movement, and autonomic instability. Various EEG findings in patients with anti-NMDA receptor encephalitis have been reported, however, the correlation between the EEG findings and clinical course of anti-NMDA receptor encephalitis remains unclear. We describe a patient with anti-NMDA receptor encephalitis with a focus on EEG findings, which included: status epilepticus, generalised rhythmic delta activity, excess beta activity, extreme delta brush, and paroxysmal alpha activity upon arousal from sleep, which we term"arousal alpha pattern". Initially, status epilepticus was observed on the EEG when the patient was comatose with conjugate deviation. The EEG then indicated excess beta activity, followed by the emergence of continuous slow activity, including generalised rhythmic delta activity and extreme delta brush, in the most severe phase. Slow activity gradually faded in parallel with clinical amelioration. Excess beta activity persisted, even after the patient became almost independent in daily activities, and finally disappeared with full recovery. In summary, our patient with anti-NMDA receptor encephalitis demonstrated slow activity on the EEG, including extreme delta brush during the most severe phase, which gradually faded in parallel with clinical amelioration, with excess beta activity persisting into the recovery phase.

Wireless recording systems: from noninvasive EEG-NIRS to invasive EEG devices.

Science.gov (United States)

Sawan, Mohamad; Salam, Muhammad T; Le Lan, Jérôme; Kassab, Amal; Gelinas, Sébastien; Vannasing, Phetsamone; Lesage, Frédéric; Lassonde, Maryse; Nguyen, Dang K

2013-04-01

In this paper, we present the design and implementation of a wireless wearable electronic system dedicated to remote data recording for brain monitoring. The reported wireless recording system is used for a) simultaneous near-infrared spectrometry (NIRS) and scalp electro-encephalography (EEG) for noninvasive monitoring and b) intracerebral EEG (icEEG) for invasive monitoring. Bluetooth and dual radio links were introduced for these recordings. The Bluetooth-based device was embedded in a noninvasive multichannel EEG-NIRS system for easy portability and long-term monitoring. On the other hand, the 32-channel implantable recording device offers 24-bit resolution, tunable features, and a sampling frequency up to 2 kHz per channel. The analog front-end preamplifier presents low input-referred noise of 5 μ VRMS and a signal-to-noise ratio of 112 dB. The communication link is implemented using a dual-band radio frequency transceiver offering a half-duplex 800 kb/s data rate, 16.5 mW power consumption and less than 10(-10) post-correction Bit-Error Rate (BER). The designed system can be accessed and controlled by a computer with a user-friendly graphical interface. The proposed wireless implantable recording device was tested in vitro using real icEEG signals from two patients with refractory epilepsy. The wirelessly recorded signals were compared to the original signals recorded using wired-connection, and measured normalized root-mean square deviation was under 2%.

[Voluntary alpha-power increasing training impact on the heart rate variability].

Science.gov (United States)

Bazanova, O M; Balioz, N V; Muravleva, K B; Skoraia, M V

2013-01-01

In order to study the effect of the alpha EEG power increasing training at heart rate variability (HRV) as the index of the autonomic regulation of cognitive functions there were follow tasks: (1) to figure out the impact of biofeedback in the voluntary increasing the power in the individual high-frequency alpha-band effect on heart rate variability and related characteristics of cognitive and emotional spheres, (2) to determine the nature of the relationship between alpha activity indices and heart rate variability, depending on the alpha-frequency EEG pattern at rest (3) to examine how the individual alpha frequency EEG pattern is reflected in changes HRV as a result of biofeedback training. Psychometric indicators of cognitive performance, the characteristics of the alpha-EEG activity and heart rate variability (HRV) as LF/HF and pNN50 were recorded in 27 healthy men aged 18-34 years, before, during, and after 10 sessions of training of voluntary increase in alpha power in the individual high-frequency alpha band with eyes closed. To determine the biofeedback effect on the alpha power increasing training, data subjects are compared in 2 groups: experimental (14) with the real and the control group (13 people)--with mock biofeedback. The follow up effect of trainings was studied through month over the 10 training sessions. Results showed that alpha biofeedback training enhanced the fluency and accuracy in cognitive performance, decreased anxiety and frontal EMG, increased resting frequency, width and power in individual upper alpha range only in participants with low baseline alpha frequency. While mock biofeedback increased resting alpha power only in participants with high baseline resting alpha frequency and did change neither cognitive performance, nor HRV indices. Biofeedback training eliminated the alpha power decrease in response to arithmetic task in both with high and low alpha frequency participants and this effect was followed up over the month. Mock

EEG. Renewables Act. Comment. 4. new rev. and enl. ed.; EEG. Erneuerbare-Energien-Gesetz. Kommentar

Energy Technology Data Exchange (ETDEWEB)

Frenz, Walter [RWTH Aachen Univ. (Germany). Lehr- und Forschungsgebiet Berg-, Umwelt- und Europarecht; Mueggenborg, Hans-Juergen [Technische Hochschule Aachen (Germany); Kassel Univ. (Germany); Cosack, Tilman [Hochschule Trier, Umwelt-Campus Birkenfeld (Germany). IREK - Inst. fuer das Recht der Erneuerbaren Energien, Energieeffizienzrecht und Klimaschutzrecht; Ekardt, Felix (ed.) [Forschungsstelle Nachhaltigkeit und Klimapolitik, Leipzig (Germany)

2015-07-01

Unlike any other Act, the Renewable Energy Sources Act (EEG) changes continuously. Recently it has been fundamentally transformed with the amendment 2014. Comprehensive, readable and practice-oriented. The proven Berliner comment EEG is your reliable companion through the new regulatory regime. All provisions of the EEG 2014 thorough and easy to understand commented by experts of the matter. 2. The EEG Amending Act of 29.6.2015 has already been considered. A detailed introduction and contributions to the relevant European law and the antitrust aspects of the renewable energy sources to guarantee you a broad understanding of the rules. Valuable background information you provide, the digressions of the most important renewable energy technologies, will explain the pictures thanks to numerous the scientific and technical foundations. Moreover you the construction law aspects in the construction of photovoltaic and wind turbines are explained clearly. [German] Wie kaum ein anderes Gesetz veraendert sich das Erneuerbare-Energien-Gesetz (EEG) laufend. Zuletzt wurde es mit der Novelle 2014 grundlegend umgestaltet. Umfassend, verstaendlich und praxisgerecht Der bewaehrte Berliner Kommentar EEG ist Ihr verlaesslicher Begleiter durch das neue Regelungsregime. Alle Vorschriften des EEG 2014 werden gruendlich und leicht verstaendlich von Kennern der Materie kommentiert. Das 2. EEG-Aenderungsgesetz vom 29.06.2015 ist bereits beruecksichtigt. Eine ausfuehrliche Einleitung sowie Beitraege zum einschlaegigen europaeischen Recht und zu den kartellrechtlichen Aspekten der erneuerbaren Energien verhelfen Ihnen zu einem breiten Verstaendnis der Vorschriften. Wertvolles Hintergrundwissen liefern Ihnen auch die Exkurse zu den wichtigsten Erneuerbare-Energien-Technologien, die Ihnen dank zahlreicher Abbildungen die naturwissenschaftlich-technischen Grundlagen erlaeutern. Zudem werden Ihnen die baurechtlichen Aspekte bei der Errichtung von Photovoltaik- und Windenergieanlagen

Simultaneous recording of EEG and electromyographic polygraphy increases the diagnostic yield of video-EEG monitoring.

Science.gov (United States)

Hill, Aron T; Briggs, Belinda A; Seneviratne, Udaya

2014-06-01

To investigate the usefulness of adjunctive electromyographic (EMG) polygraphy in the diagnosis of clinical events captured during long-term video-EEG monitoring. A total of 40 patients (21 women, 19 men) aged between 19 and 72 years (mean 43) investigated using video-EEG monitoring were studied. Electromyographic activity was simultaneously recorded with EEG in four patients selected on clinical grounds. In these patients, surface EMG electrodes were placed over muscles suspected to be activated during a typical clinical event. Of the 40 patients investigated, 24 (60%) were given a diagnosis, whereas 16 (40%) remained undiagnosed. All four patients receiving adjunctive EMG polygraphy obtained a diagnosis, with three of these diagnoses being exclusively reliant on the EMG recordings. Specifically, one patient was diagnosed with propriospinal myoclonus, another patient was diagnosed with facio-mandibular myoclonus, and a third patient was found to have bruxism and periodic leg movements of sleep. The information obtained from surface EMG recordings aided the diagnosis of clinical events captured during video-EEG monitoring in 7.5% of the total cohort. This study suggests that EEG-EMG polygraphy may be used as a technique of improving the diagnostic yield of video-EEG monitoring in selected cases.

Physiological and psychological individual differences influence resting brain function measured by ASL perfusion.

Science.gov (United States)

Kano, M; Coen, S J; Farmer, A D; Aziz, Q; Williams, S C R; Alsop, D C; Fukudo, S; O'Gorman, R L

2014-09-01

Effects of physiological and/or psychological inter-individual differences on the resting brain state have not been fully established. The present study investigated the effects of individual differences in basal autonomic tone and positive and negative personality dimensions on resting brain activity. Whole-brain resting cerebral perfusion images were acquired from 32 healthy subjects (16 males) using arterial spin labeling perfusion MRI. Neuroticism and extraversion were assessed with the Eysenck Personality Questionnaire-Revised. Resting autonomic activity was assessed using a validated measure of baseline cardiac vagal tone (CVT) in each individual. Potential associations between the perfusion data and individual CVT (27 subjects) and personality score (28 subjects) were tested at the level of voxel clusters by fitting a multiple regression model at each intracerebral voxel. Greater baseline perfusion in the dorsal anterior cingulate cortex (ACC) and cerebellum was associated with lower CVT. At a corrected significance threshold of p individual autonomic tone and psychological variability influence resting brain activity in brain regions, previously shown to be associated with autonomic arousal (dorsal ACC) and personality traits (amygdala, caudate, etc.) during active task processing. The resting brain state may therefore need to be taken into account when interpreting the neurobiology of individual differences in structural and functional brain activity.

Relationship of genetically transmitted alpha EEG traits to anxiety disorders and alcoholism

Energy Technology Data Exchange (ETDEWEB)

Enoch, M.A.; Rohrbaugh, W.; Harris, C.R. [Washington School of Medicine, St. Louis, MO (United States)] [and others

1995-10-09

We tested the hypothesis that a heritable EEG trait, the low voltage alpha (LV), is associated with psychiatric disorders. Modest to moderate evidence for genetic linkage of both panic disorder and the low voltage alpha trait to the same region of chromosome 20q has recently been reported, raising the issue of whether there is a phenotypic correlation between these traits. A total of 124 subjects including 50 unrelated index subjects and 74 relatives were studied. Alpha EEG power was measured and EEG phenotypes were impressionistically classified. Subjects were psychiatrically interviewed using the SADS-L and blind-rated by RDC criteria. Alcoholics were four times more likely to be LV (including so-called borderline low voltage alpha) than were nonalcoholic, nonanxious subjects. Alcoholics with anxiety disorder are 10 times more likely to be LV. However, alcoholics without anxiety disorder were similar to nonalcoholics in alpha power. An anxiety disorder (panic disorder, phobia, or generalized anxiety) was found in 14/17 LV subjects as compared to 34/101 of the rest of the sample (P < 0.01). Support for these observations was found in the unrelated index subjects in whom no traits would be shared by familial clustering. Lower alpha power in anxiety disorders was not state-dependent, as indicated by the Spielberger Anxiety Scale. Familial covariance of alpha power was 0.25 (P < 0.01). These findings indicate there may be a shared factor underlying the transmissible low voltage alpha EEG variant and vulnerability to anxiety disorders with associated alcoholism. This factor is apparently not rare, because LV was found in approximately 10% of unrelated index subjects and 5% of subjects free of alcoholism and anxiety disorders. 43 refs., 1 fig., 3 tabs.

Investigating long-range correlation properties in EEG during complex cognitive tasks

International Nuclear Information System (INIS)

Karkare, Siddharth; Saha, Goutam; Bhattacharya, Joydeep

2009-01-01

Previous work shows the presence of scale invariance and long-range correlations in ongoing and spontaneous activity of large scale brain responses (i.e. EEG), and such scaling behavior can also be modulated by simple sensory stimulus. However, little is known whether such alteration but not destruction in scaling properties also occurs during complex cognitive processing and if neuroplasticity plays any role in mediating such changes. In this study, we addressed these issues by investigating scaling properties of multivariate EEG signals obtained from two broad groups - artists and non-artists - while they performed complex tasks of perception and mental imagery of visual art objects. We found that brain regions showing increased correlation properties from rest were similar for both tasks, suggesting that brain networks responsible for visual perception are reactivated for mental imagery. Further, we observed that the two groups could be differentiated by scaling exponents and an artificial neural network based classifier achieved a classification efficiency of over 80%. These results altogether suggest that specific complex cognitive task demands and task-specific expertise can modify the temporal scale-free dynamics of brain responses.

Investigating long-range correlation properties in EEG during complex cognitive tasks

Energy Technology Data Exchange (ETDEWEB)

Karkare, Siddharth [Department of Electrical Engineering, Indian Institute of Technology, Kharagpur 721302 (India); Saha, Goutam [Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology, Kharagpur 721302 (India); Bhattacharya, Joydeep [Department of Psychology, Goldsmiths College, University of London, New Cross, London SE14 6NW (United Kingdom); Commission for Scientific Visualization, Austrian Academy of Sciences, Vienna A1220 (Austria)], E-mail: j.bhattacharya@gold.ac.uk

2009-11-30

Previous work shows the presence of scale invariance and long-range correlations in ongoing and spontaneous activity of large scale brain responses (i.e. EEG), and such scaling behavior can also be modulated by simple sensory stimulus. However, little is known whether such alteration but not destruction in scaling properties also occurs during complex cognitive processing and if neuroplasticity plays any role in mediating such changes. In this study, we addressed these issues by investigating scaling properties of multivariate EEG signals obtained from two broad groups - artists and non-artists - while they performed complex tasks of perception and mental imagery of visual art objects. We found that brain regions showing increased correlation properties from rest were similar for both tasks, suggesting that brain networks responsible for visual perception are reactivated for mental imagery. Further, we observed that the two groups could be differentiated by scaling exponents and an artificial neural network based classifier achieved a classification efficiency of over 80%. These results altogether suggest that specific complex cognitive task demands and task-specific expertise can modify the temporal scale-free dynamics of brain responses.

EEG Based Inference of Spatio-Temporal Brain Dynamics

DEFF Research Database (Denmark)

Hansen, Sofie Therese

Electroencephalography (EEG) provides a measure of brain activity and has improved our understanding of the brain immensely. However, there is still much to be learned and the full potential of EEG is yet to be realized. In this thesis we suggest to improve the information gain of EEG using three...... different approaches; 1) by recovery of the EEG sources, 2) by representing and inferring the propagation path of EEG sources, and 3) by combining EEG with functional magnetic resonance imaging (fMRI). The common goal of the methods, and thus of this thesis, is to improve the spatial dimension of EEG...... recovery ability. The forward problem describes the propagation of neuronal activity in the brain to the EEG electrodes on the scalp. The geometry and conductivity of the head layers are normally required to model this path. We propose a framework for inferring forward models which is based on the EEG...

Long-term and within-day variability of working memory performance and EEG in individuals.

Science.gov (United States)

Gevins, Alan; McEvoy, Linda K; Smith, Michael E; Chan, Cynthia S; Sam-Vargas, Lita; Baum, Cliff; Ilan, Aaron B

2012-07-01

Assess individual-subject long-term and within-day variability of a combined behavioral and EEG test of working memory. EEGs were recorded from 16 adults performing n-back working memory tasks, with 10 tested in morning and afternoon sessions over several years. Participants were also tested after ingesting non-prescription medications or recreational substances. Performance and EEG measures were analyzed to derive an Overall score and three constituent sub-scores characterizing changes in performance, cortical activation, and alertness from each individual's baseline. Long-term and within-day variability were determined for each score; medication effects were assessed by reference to each individual's normal day-to-day variability. Over the several year period, the mean Overall score and sub-scores were approximately zero with standard deviations less than one. Overall scores were lower and their variability higher in afternoon relative to morning sessions. At the group level, alcohol, diphenhydramine and marijuana produced significant effects, but there were large individual differences. Objective working memory measures incorporating performance and EEG are stable over time and sensitive at the level of individual subjects to interventions that affect neurocognitive function. With further research these measures may be suitable for use in individualized medical care by providing a sensitive assessment of incipient illness and response to treatment. Published by Elsevier Ireland Ltd.

Continuous EEG-fMRI in Pre-Surgical Evaluation of a Patient with Symptomatic Seizures: Bold Activation Linked to Interictal Epileptic Discharges Caused by Cavernoma.

Science.gov (United States)

Avesani, M; Formaggio, E; Milanese, F; Baraldo, A; Gasparini, A; Cerini, R; Bongiovanni, L G; Pozzi Mucelli, R; Fiaschi, A; Manganotti, P

2008-04-07

We used continuous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) to identify the linkage between the "epileptogenic" and the "irritative" area in a patient with symptomatic epilepsy (cavernoma, previously diagnosed and surgically treated), i.e. a patient with a well known "epileptogenic area", and to increase the possibility of a non invasive pre-surgical evaluation of drug-resistant epilepsies. A compatible MRI system was used (EEG with 29 scalp electrodes and two electrodes for ECG and EMG) and signals were recorded with a 1.5 Tesla MRI scanner. After the recording session and MRI artifact removal, EEG data were analyzed offline and used as paradigms in fMRI study. Activation (EEG sequences with interictal slow-spiked-wave activity) and rest (sequences of normal EEG) conditions were compared to identify the potential resulting focal increase in BOLD signal and to consider if this is spatially linked to the interictal focus used as a paradigm and to the lesion. We noted an increase in the BOLD signal in the left neocortical temporal region, laterally and posteriorly to the poro-encephalic cavity (residual of cavernoma previously removed), that is around the "epileptogenic area". In our study "epileptogenic" and "irritative" areas were connected with each other. Combined EEG-fMRI may become routine in clinical practice for a better identification of an irritative and lesional focus in patients with symptomatic drug-resistant epilepsy.

Functional connectivity analysis of the brain network using resting-state fMRI

International Nuclear Information System (INIS)

Hayashi, Toshihiro

2011-01-01

Spatial patterns of spontaneous fluctuations in blood oxygenation level-dependent (BOLD) signals reflect the underlying neural architecture. The study of the brain network based on these self-organized patterns is termed resting-state functional MRI (fMRI). This review article aims at briefly reviewing a basic concept of this technology and discussing its implications for neuropsychological studies. First, the technical aspects of resting-state fMRI, including signal sources, physiological artifacts, image acquisition, and analytical methods such as seed-based correlation analysis and independent component analysis, are explained, followed by a discussion on the major resting-state networks, including the default mode network. In addition, the structure-function correlation studied using diffuse tensor imaging and resting-state fMRI is briefly discussed. Second, I have discussed the reservations and potential pitfalls of 2 major imaging methods: voxel-based lesion-symptom mapping and task fMRI. Problems encountered with voxel-based lesion-symptom mapping can be overcome by using resting-state fMRI and evaluating undamaged brain networks in patients. Regarding task fMRI in patients, I have also emphasized the importance of evaluating the baseline brain activity because the amplitude of activation in BOLD fMRI is hard to interpret as the same baseline cannot be assumed for both patient and normal groups. (author)

Short analysis of the increase of the EEG apportionment 2013; Kurzanalyse des Anstiegs der EEG-Umlage 2013

Energy Technology Data Exchange (ETDEWEB)

Loreck, Charlotte; Matthes, Felix C.; Hermann, Hauke; Jung, Frederieke; Emele, Lukas

2012-10-15

At 15th October, 2012 the transmission system operators had published the EEG apportionment (EEG - Energy Economy Law). For the year 2013. This apportionment amounts 5,277 ct/kWh for non-privileged consumers in comparison to 3,59 ct/kWh for the year 2012. The ongoing enhancement of the renewable energies increases the EEG apportionment by an amount of 0.74 ct/kWh. With 0.26 ct/kWh the photovoltaics has the largest proportion in comparison to photovoltaics. The power generation from biomass as well as from wind energy at onshore sites contribute with 0.21 ct/kWh to the EEG apportionment. The greatest item of 0.48 ct/kWh is the debit balancing of the EEG account. The liquidity reserve for the year 2013 will be enhanced to 10% of the budget deficit. The expansion of the privileged status of the power consumption increases the EEG apportionment by 0.12 ct/kWh.

EEG Clearing Office strengthened by EEG 2012. Alternative dispute resolution in the renewable energies industry; Aufwertung der Clearingstelle EEG durch das EEG 2012. Alternative Dispute Resolution im Bereich der Erneuerbaren Energien

Energy Technology Data Exchange (ETDEWEB)

Chatzinerantzis, Alexandros; Fach, Martin [Linklaters LLP, Frankfurt am Main (Germany). Praxisgruppe Litigation and Arbitration

2012-11-14

The EEG Clearing Office is a special arbitration forum for the purpose of facilitating quick and inexpensive out-of-court dispute resolutions and resolving cases of legal uncertainty in connection with the regulations of the EEG (Renewable Energy Law). The Clearing Office has developed dynamically over the past years, as the numbers of newly registered potential and ongoing procedures impressively show. In the 2012 amendment to the EEG the legislature has fundamentally revised and substantially widened the legal basis for the work of the Clearing Office. This provides the motivation for presenting the Clearing Office and its procedural rules in the following article.

Prediction of microsleeps using pairwise joint entropy and mutual information between EEG channels.

Science.gov (United States)

Baseer, Abdul; Weddell, Stephen J; Jones, Richard D

2017-07-01

Microsleeps are involuntary and brief instances of complete loss of responsiveness, typically of 0.5-15 s duration. They adversely affect performance in extended attention-driven jobs and can be fatal. Our aim was to predict microsleeps from 16 channel EEG signals. Two information theoretic concepts - pairwise joint entropy and mutual information - were independently used to continuously extract features from EEG signals. k-nearest neighbor (kNN) with k = 3 was used to calculate both joint entropy and mutual information. Highly correlated features were discarded and the rest were ranked using Fisher score followed by an average of 3-fold cross-validation area under the curve of the receiver operating characteristic (AUC ROC ). Leave-one-out method (LOOM) was performed to test the performance of microsleep prediction system on independent data. The best prediction for 0.25 s ahead was AUCROC, sensitivity, precision, geometric mean (GM), and φ of 0.93, 0.68, 0.33, 0.75, and 0.38 respectively with joint entropy using single linear discriminant analysis (LDA) classifier.

A Single Session of rTMS Enhances Small-Worldness in Writer’s Cramp: Evidence from Simultaneous EEG-fMRI Multi-Modal Brain Graph

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Rose D. Bharath

2017-09-01

Full Text Available Background and Purpose: Repetitive transcranial magnetic stimulation (rTMS induces widespread changes in brain connectivity. As the network topology differences induced by a single session of rTMS are less known we undertook this study to ascertain whether the network alterations had a small-world morphology using multi-modal graph theory analysis of simultaneous EEG-fMRI.Method: Simultaneous EEG-fMRI was acquired in duplicate before (R1 and after (R2 a single session of rTMS in 14 patients with Writer’s Cramp (WC. Whole brain neuronal and hemodynamic network connectivity were explored using the graph theory measures and clustering coefficient, path length and small-world index were calculated for EEG and resting state fMRI (rsfMRI. Multi-modal graph theory analysis was used to evaluate the correlation of EEG and fMRI clustering coefficients.Result: A single session of rTMS was found to increase the clustering coefficient and small-worldness significantly in both EEG and fMRI (p < 0.05. Multi-modal graph theory analysis revealed significant modulations in the fronto-parietal regions immediately after rTMS. The rsfMRI revealed additional modulations in several deep brain regions including cerebellum, insula and medial frontal lobe.Conclusion: Multi-modal graph theory analysis of simultaneous EEG-fMRI can supplement motor physiology methods in understanding the neurobiology of rTMS in vivo. Coinciding evidence from EEG and rsfMRI reports small-world morphology for the acute phase network hyper-connectivity indicating changes ensuing low-frequency rTMS is probably not “noise”.

Transcranial Direct Current Stimulation and Power Spectral Parameters: a tDCS/EEG co-registration study

Directory of Open Access Journals (Sweden)

Anna Lisa Mangia

2014-08-01

Full Text Available Transcranial direct current stimulation (tDCS delivers low electric currents to the brain through the scalp. Constant electric currents induce shifts in neuronal membrane excitability, resulting in secondary changes in cortical activity. Concomitant electroencephalography (EEG monitoring during tDCS can provide valuable information on the tDCS mechanisms of action. This study examined the effects of anodal tDCS on spontaneous cortical activity in a resting brain to disclose possible modulation of spontaneous oscillatory brain activity. EEG activity was measured in ten healthy subjects during and after a session of anodal stimulation of the postero-parietal cortex to detect the tDCS-induced alterations. Changes in the theta, alpha, beta and gamma power bands were investigated. Three main findings emerged: 1 an increase in theta band activity during the first minutes of stimulation; 2 an increase in alpha and beta power during and after stimulation; 3 a widespread activation in several brain regions.

The Effect of Lamotrigine and Levetiracetam on TMS-Evoked EEG Responses Depends on Stimulation Intensity

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Isabella Premoli

2017-10-01

Full Text Available The combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG has uncovered underlying mechanisms of two anti-epileptic medications: levetiracetam and lamotrigine. Despite their different mechanism of action, both drugs modulated TMS-evoked EEG potentials (TEPs in a similar way. Since both medications increase resting motor threshold (RMT, the current aim was to examine the similarities and differences in post-drug TEPs, depending on whether stimulation intensity was adjusted to take account of post-drug RMT increase. The experiment followed a placebo controlled, double blind, crossover design, involving a single dose of either lamotrigine or levetiracetam. When a drug-induced increase of RMT occurred, post-drug measurements involved two blocks of stimulations, using unadjusted and adjusted stimulation intensity. A cluster based permutation analysis of differences in TEP amplitude between adjusted and unadjusted stimulation intensity showed that lamotrigine induced a stronger modulation of the N45 TEP component compared to levetiracetam. Results highlight the impact of adjusting stimulation intensity.

EEG

Science.gov (United States)

... brain dead. EEG cannot be used to measure intelligence. Normal Results Brain electrical activity has a certain ... 2018, A.D.A.M., Inc. Duplication for commercial use must be authorized in writing by ADAM ...

Comparative sensitivity of quantitative EEG (QEEG) spectrograms for detecting seizure subtypes.

Science.gov (United States)

Goenka, Ajay; Boro, Alexis; Yozawitz, Elissa

2018-02-01

To assess the sensitivity of Persyst version 12 QEEG spectrograms to detect focal, focal with secondarily generalized, and generalized onset seizures. A cohort of 562 seizures from 58 patients was analyzed. Successive recordings with 2 or more seizures during continuous EEG monitoring for clinical indications in the ICU or EMU between July 2016 and January 2017 were included. Patient ages ranged from 5 to 64 years (mean = 36 years). There were 125 focal seizures, 187 secondarily generalized and 250 generalized seizures from 58 patients analyzed. Seizures were identified and classified independently by two epileptologists. A correlate to the seizure pattern in the raw EEG was sought in the QEEG spectrograms in 4-6 h EEG epochs surrounding the identified seizures. A given spectrogram was interpreted as indicating a seizure, if at the time of a seizure it showed a visually significant departure from the pre-event baseline. Sensitivities for seizure detection using each spectrogram were determined for each seizure subtype. Overall sensitivities of the QEEG spectrograms for detecting seizures ranged from 43% to 72%, with highest sensitivity (402/562,72%) by the seizure detection trend. The asymmetry spectrogram had the highest sensitivity for detecting focal seizures (117/125,94%). The FFT spectrogram was most sensitive for detecting secondarily generalized seizures (158/187, 84%). The seizure detection trend was the most sensitive for generalized onset seizures (197/250,79%). Our study suggests that different seizure types have specific patterns in the Persyst QEEG spectrograms. Identifying these patterns in the EEG can significantly increase the sensitivity for seizure identification. Copyright © 2018 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

The quest for EEG power band correlation with ICA derived fMRI resting state networks

NARCIS (Netherlands)

Meyer, M.C.; Janssen, R.J.; van Oort, E.S.B.; Beckmann, Christian; Barth, M.

2013-01-01

The neuronal underpinnings of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) resting state networks (RSNs) are still unclear. To investigate the underlying mechanisms, specifically the relation to the electrophysiological signal, we used simultaneous recordings of

Causality within the Epileptic Network: An EEG-fMRI Study Validated by Intracranial EEG.

Science.gov (United States)

Vaudano, Anna Elisabetta; Avanzini, Pietro; Tassi, Laura; Ruggieri, Andrea; Cantalupo, Gaetano; Benuzzi, Francesca; Nichelli, Paolo; Lemieux, Louis; Meletti, Stefano

2013-01-01

Accurate localization of the Seizure Onset Zone (SOZ) is crucial in patients with drug-resistance focal epilepsy. EEG with fMRI recording (EEG-fMRI) has been proposed as a complementary non-invasive tool, which can give useful additional information in the pre-surgical work-up. However, fMRI maps related to interictal epileptiform activities (IED) often show multiple regions of signal change, or "networks," rather than highly focal ones. Effective connectivity approaches like Dynamic Causal Modeling (DCM) applied to fMRI data potentially offers a framework to address which brain regions drives the generation of seizures and IED within an epileptic network. Here, we present a first attempt to validate DCM on EEG-fMRI data in one patient affected by frontal lobe epilepsy. Pre-surgical EEG-fMRI demonstrated two distinct clusters of blood oxygenation level dependent (BOLD) signal increases linked to IED, one located in the left frontal pole and the other in the ipsilateral dorso-lateral frontal cortex. DCM of the IED-related BOLD signal favored a model corresponding to the left dorso-lateral frontal cortex as driver of changes in the fronto-polar region. The validity of DCM was supported by: (a) the results of two different non-invasive analysis obtained on the same dataset: EEG source imaging (ESI), and "psycho-physiological interaction" analysis; (b) the failure of a first surgical intervention limited to the fronto-polar region; (c) the results of the intracranial EEG monitoring performed after the first surgical intervention confirming a SOZ located over the dorso-lateral frontal cortex. These results add evidence that EEG-fMRI together with advanced methods of BOLD signal analysis is a promising tool that can give relevant information within the epilepsy surgery diagnostic work-up.

Causality within the epileptic network: an EEG-fMRI study validated by intracranial EEG.

Directory of Open Access Journals (Sweden)

Anna Elisabetta eVaudano

2013-11-01

Full Text Available Accurate localization of the Seizure Onset Zone (SOZ is crucial in patients with drug-resistance focal epilepsy. EEG with fMRI recording (EEG-fMRI has been proposed as a complementary non-invasive tool, which can give useful additional information in the pre-surgical workup. However, fMRI maps related to interictal epileptiform activities (IED often show multiple regions of signal change, or networks, rather than highly focal ones. Effective connectivity approaches like Dynamic Causal Modelling (DCM applied to fMRI data potentially offers a framework to address which brain regions drives the generation of seizures and IED within an epileptic network. Here we present a first attempt to validate DCM on EEG-fMRI data in one patient affected by frontal lobe epilepsy. Pre-surgical EEG-fMRI demonstrated two distinct clusters of BOLD signal increases linked to IED, one located in the left frontal pole and the other in the ipsilateral dorso-lateral frontal cortex. DCM of the IED-related BOLD signal favoured a model corresponding to the left dorsolateral frontal cortex as driver of changes in the fronto-polar region. The validity of DCM was supported by: (a the results of two different non-invasive analysis obtained on the same dataset: EEG source imaging (ESI, and psychophysiological interaction analysis (PPI; (b the failure of a first surgical intervention limited to the fronto-polar region; (c the results of the intracranial EEG monitoring performed after the first surgical intervention confirming a SOZ located over the dorso-lateral frontal cortex. These results add evidence that EEG-fMRI together with advanced methods of BOLD signal analysis is a promising tool that can give relevant information within the epilepsy surgery diagnostic work-up.

The EEG 2017 in the overview

International Nuclear Information System (INIS)

Altrock, Martin; Vollprecht, Jens

2016-01-01

On 08.07.2016, the German Bundestag, the German Renewable Energies Act (EEG) in 2017 passed together with the wind-at-sea law. At the same time, the legislature changed 22 other energy legislation, inter alia, also the EnWG. Here, the law de facto a law amending the EEG 2014 is: The EEG is thus not total re-promulgated. Rather essentially part 3 (''Payment of market premium and feed in rate'') of the EEG 2014 renewed, notably Section 3 supplemented by regulations on the newly introduced procurements. But beyond the framework of support is further developed in various details, like the definition of a plant, the promotion of storage facilities and of course, in the again very ambitious and complicated transitional arrangements. Other notable individual changes concern the introduction of regional evidence of directly marketed electricity from renewable sources, the increase of liability for balancing group deviations in paragraph 60 para. 1 EEG 2017 or readjustments in the special equalization scheme, paragraph 64 para. 2 no. 2 EEG. [de

Neural correlates of verbal creativity: Differences in resting-state functional connectivity associated with expertise in creative writing

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Martin eLotze

2014-07-01

Full Text Available Neural characteristics of verbal creativity as assessed by word generation tasks have been recently identified, but differences in resting-state functional connectivity (rFC between experts and non-experts in creative writing have not been reported yet. Previous electroencephalography (EEG coherence measures during rest demonstrated a decreased cooperation between brain areas in association with creative thinking ability. Here, we used resting-state functional magnetic resonance imaging to compare 20 experts in creative writing and 23 age-matched non-experts with respect to rFC strengths within a brain network previously found to be associated with creative writing. Decreased rFC for experts was found between areas 44 of both hemispheres. Increased rFC for experts was observed between right hemispheric caudate and intraparietal sulcus. Correlation analysis of verbal creativity indices with rFC values in the expert group revealed predominantly negative associations, particularly of rFC between left area 44 and left temporal pole. Overall, our data support previous findings on reduced connectivity between interhemispheric areas and increased right-hemispheric connectivity during rest in highly verbally creative individuals.

Is Rest Really Rest? Resting State Functional Connectivity during Rest and Motor Task Paradigms.

Science.gov (United States)

Jurkiewicz, Michael T; Crawley, Adrian P; Mikulis, David J

2018-04-18

Numerous studies have identified the default mode network (DMN) within the brain of healthy individuals, which has been attributed to the ongoing mental activity of the brain during the wakeful resting-state. While engaged during specific resting-state fMRI paradigms, it remains unclear as to whether traditional block-design simple movement fMRI experiments significantly influence the default mode network or other areas. Using blood-oxygen level dependent (BOLD) fMRI we characterized the pattern of functional connectivity in healthy subjects during a resting-state paradigm and compared this to the same resting-state analysis performed on motor task data residual time courses after regressing out the task paradigm. Using seed-voxel analysis to define the DMN, the executive control network (ECN), and sensorimotor, auditory and visual networks, the resting-state analysis of the residual time courses demonstrated reduced functional connectivity in the motor network and reduced connectivity between the insula and the ECN compared to the standard resting-state datasets. Overall, performance of simple self-directed motor tasks does little to change the resting-state functional connectivity across the brain, especially in non-motor areas. This would suggest that previously acquired fMRI studies incorporating simple block-design motor tasks could be mined retrospectively for assessment of the resting-state connectivity.

Affective attitudes to face images associated with intracerebral EEG source location before face viewing.

Science.gov (United States)

Pizzagalli, D; Koenig, T; Regard, M; Lehmann, D

1999-01-01

We investigated whether different, personality-related affective attitudes are associated with different brain electric field (EEG) sources before any emotional challenge (stimulus exposure). A 27-channel EEG was recorded in 15 subjects during eyes-closed resting. After recording, subjects rated 32 images of human faces for affective appeal. The subjects in the first (i.e., most negative) and fourth (i.e., most positive) quartile of general affective attitude were further analyzed. The EEG data (mean=25+/-4. 8 s/subject) were subjected to frequency-domain model dipole source analysis (FFT-Dipole-Approximation), resulting in 3-dimensional intracerebral source locations and strengths for the delta-theta, alpha, and beta EEG frequency band, and for the full range (1.5-30 Hz) band. Subjects with negative attitude (compared to those with positive attitude) showed the following source locations: more inferior for all frequency bands, more anterior for the delta-theta band, more posterior and more right for the alpha, beta and 1.5-30 Hz bands. One year later, the subjects were asked to rate the face images again. The rating scores for the same face images were highly correlated for all subjects, and original and retest affective mean attitude was highly correlated across subjects. The present results show that subjects with different affective attitudes to face images had different active, cerebral, neural populations in a task-free condition prior to viewing the images. We conclude that the brain functional state which implements affective attitude towards face images as a personality feature exists without elicitors, as a continuously present, dynamic feature of brain functioning. Copyright 1999 Elsevier Science B.V.

Electroencephalogram (EEG spectral features discriminate between Alzheimer’s (AD and Vascular dementia (VaD

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Emanuel eNeto

2015-02-01

Full Text Available Alzheimer’s disease (AD and vascular dementia (VaD present with similar clinical symptoms of cognitive decline, but the underlying pathophysiological mechanisms differ. To determine whether clinical electroencephalography (EEG can provide information relevant to discriminate between these diagnoses, we used quantitative EEG analysis to compare the spectra between non-medicated patients with AD (n=77 and VaD (n=77 and healthy elderly normal controls (NC (n=77. We use curve-fitting with a combination of a power loss and Gaussian function to model the averaged resting-state spectra of each EEG channel extracting six parameters. We assessed the performance of our model and tested the extracted parameters for group differentiation. We performed regression analysis in a MANCOVA with group, age, gender, and number of epochs as predictors and further explored the topographical group differences with pair-wise contrasts. Significant topographical differences between the groups were found in several of the extracted features. Both AD and VaD groups showed increased delta power when compared to NC, whereas the AD patients showed a decrease in alpha power for occipital and temporal regions when compared with NC. The VaD patients had higher alpha power than NC and AD. The AD and VaD groups showed slowing of the alpha rhythm. Variability of the alpha frequency was wider for both AD and VaD groups. There was a general decrease in beta power for both AD and VaD. The proposed model is a useful to parameterize spectra which allowed extracting relevant clinical EEG key features that move towards simple and interpretable diagnostic criteria.

Resting state electroencephalographic correlates with red cell long-chain fatty acids, memory performance and age in adolescent boys with attention deficit hyperactivity disorder.

Science.gov (United States)

Sumich, Alexander; Matsudaira, Toshiko; Gow, Rachel V; Ibrahimovic, Almira; Ghebremeskel, Kebreab; Crawford, Michael; Taylor, Eric

2009-12-01

Abnormal fatty acid status has been implicated in the aetiology of attention deficit hyperactivity disorder (ADHD). Delayed maturation in ADHD may result in raised frontal low frequency (theta) electroencephalographic activity (EEG) and a reduction in posterior high frequency (beta, alpha) activity. The current study used sequential linear regression to investigate the association between age, resting-state EEG and levels of long-chain polyunsaturated omega-3 and omega-6 fatty acids in red blood cells in 46 adolescent boys with ADHD symptoms. Docosahexaenoic acid (DHA) levels were positively associated with fast frequency activity: alpha during eyes-open and beta during eyes-closed conditions. Frontal theta activity during both eyes-open and eyes-closed conditions was inversely associated with age and positively associated with eicosapentaenoic acid (EPA) levels. Alpha activity correlated positively with performance on fluency for categories (semantic memory). Theta activity correlated inversely with performance on delayed (25 min) verbal memory (recall + recognition/2). No associations were observed between long-chain omega-6 and EEG measures. Results support differential associations for DHA and EPA with fast and slow EEG activity respectively. Results support EEG activity as an objective biomarker of neural function associated with long-chain omega-3 fatty acids in ADHD.

Biogas plants in EEG. 4. new rev. and enl. ed.; Biogasanlagen im EEG

Energy Technology Data Exchange (ETDEWEB)

Loibl, Helmut; Maslaton, Martin; Bredow, Hartwig von; Walter, Rene (eds.)

2016-08-01

With the EEG 2014, the legislature has created a complete revision of all the RES plants. Specifically for biogas plants fundamental changes have been made with the maximum rated power or a new landscape conservation concept. For new biogas plants the legislator arranges not only a much lower remuneration, but also the direct marketing as a rule, which entails fundamental changes in the overall compensation system by itself. The new edition of this highly regarded standard work revives the extensive practical experience to EEG 2009, 2012 and 2014 in detail and in particular and takes into account the large number of newly issued clearinghouses decisions and judgments. All current legal issues and challenges of biogas plants can be found comprehensively presented here. [German] Mit dem EEG 2014 hat der Gesetzgeber eine komplette Neuregelung fuer alle EEG-Anlagen geschaffen. Speziell fuer Biogasanlagen wurden mit der Hoechstbemessungsleistung oder einem neuen Landschaftspflegebegriff grundlegende Aenderungen vorgenommen. Fuer neue Biogasanlagen ordnet der Gesetzgeber nicht nur eine deutlich geringere Verguetung, sondern zudem die Direktvermarktung als Regelfall an, was grundlegende Veraenderungen des gesamten Verguetungssystems nach sich zieht. Die Neuauflage dieses vielbeachteten Standardwerks greift die umfangreichen Praxiserfahrungen zum EEG 2009, 2012 und 2014 detailliert auf und beruecksichtigt insbesondere auch die Vielzahl der neu ergangenen Clearingstellenentscheidungen und Urteile. Alle aktuellen rechtlichen Themen und Herausforderungen bei Biogasanlagen finden Sie hier umfassend dargestellt.

EEG: Origin and measurement

NARCIS (Netherlands)

Lopes da Silva, F.; Mulert, C.; Lemieux, L.

2010-01-01

The existence of the electrical activity of the brain (i.e. the electroencephalogram or EEG) was discovered more than a century ago by Caton. After the demonstration that the EEG could be recorded from the human scalp by Berger in the 1920s, it made a slow start before it became accepted as a method

Analysis of EEG Related Saccadic Eye Movement

Science.gov (United States)

Funase, Arao; Kuno, Yoshiaki; Okuma, Shigeru; Yagi, Tohru

Our final goal is to establish the model for saccadic eye movement that connects the saccade and the electroencephalogram(EEG). As the first step toward this goal, we recorded and analyzed the saccade-related EEG. In the study recorded in this paper, we tried detecting a certain EEG that is peculiar to the eye movement. In these experiments, each subject was instructed to point their eyes toward visual targets (LEDs) or the direction of the sound sources (buzzers). In the control cases, the EEG was recorded in the case of no eye movemens. As results, in the visual experiments, we found that the potential of EEG changed sharply on the occipital lobe just before eye movement. Furthermore, in the case of the auditory experiments, similar results were observed. In the case of the visual experiments and auditory experiments without eye movement, we could not observed the EEG changed sharply. Moreover, when the subject moved his/her eyes toward a right-side target, a change in EEG potential was found on the right occipital lobe. On the contrary, when the subject moved his/her eyes toward a left-side target, a sharp change in EEG potential was found on the left occipital lobe.

Sleep and alertness during alternating monophasic and polyphasic rest-activity cycles.

Science.gov (United States)

Porcú, S; Casagrande, M; Ferrara, M; Bellatreccia, A

1998-07-01

People involved in shift work often have to face altered patterns of sleep and wakefulness. This is particularly true for schedules involving night shifts and/or fragmentation of duty periods throughout the 24-hr day. In such conditions, it can be difficult to obtain satisfactory periods of sleep, and sleepiness on duty is a frequent and dangerous occurrence. The aim of this study was to evaluate sleep and wakefulness periods of subjects whose work schedule was characterized by an alternation of 2 hours of activity and 4 hours of rest (sleep allowed), repeated 4 times throughout the 24-hr day. This schedule was alternated with 24 hours off duty. Nine healthy male volunteers were monitored by means of ambulatory polysomnography while attending their 24-hr rest-activity schedule. Sleep periods were visually scored according to standard criteria. Wake periods were visually scored using both 30 s and 5 s epochs in order to reveal episodes of drowsiness and/or microsleep. Results showed that total sleep time was substantially reduced as compared to the usual 7-8 hour monophasic nocturnal sleep. Subjects did not sleep during the first rest period (11.00-15.00). Time in sleep linearly increased in the course of the 3 remaining rest periods. Normal sleep stage distribution was substantially spared only in the last rest period (3.00-7.00 a.m.). With regard to duty periods, only a few microsleeps were detected and their number did not significantly vary across the four 2-hr activity periods. In conclusion, this rest-activity schedule, despite the considerable sleep reduction, allowed maintaining good levels of vigilance as shown by the virtual absence of EEG microsleeps. Whether future research will prove that this regimen does not cause an impairment of performance, it should be a suitable strategy for the management of continuous operations.

Standardized computer-based organized reporting of EEG

DEFF Research Database (Denmark)

Beniczky, Sándor; Aurlien, Harald; Brøgger, Jan C.

2017-01-01

Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted in the se......Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted...... in the second, revised version of SCORE (Standardized Computer-based Organized Reporting of EEG), which is presented in this paper. The revised terminology was implemented in a software package (SCORE EEG), which was tested in clinical practice on 12,160 EEG recordings. Standardized terms implemented in SCORE....... In the end, the diagnostic significance is scored, using a standardized list of terms. SCORE has specific modules for scoring seizures (including seizure semiology and ictal EEG patterns), neonatal recordings (including features specific for this age group), and for Critical Care EEG Terminology. SCORE...

Extended seizure detection algorithm for intracranial EEG recordings

DEFF Research Database (Denmark)

Kjaer, T. W.; Remvig, L. S.; Henriksen, J.

2010-01-01

Objective: We implemented and tested an existing seizure detection algorithm for scalp EEG (sEEG) with the purpose of improving it to intracranial EEG (iEEG) recordings. Method: iEEG was obtained from 16 patients with focal epilepsy undergoing work up for resective epilepsy surgery. Each patient...... had 4 or 5 recorded seizures and 24 hours of non-ictal data were used for evaluation. Data from three electrodes placed at the ictal focus were used for the analysis. A wavelet based feature extraction algorithm delivered input to a support vector machine (SVM) classifier for distinction between ictal...... and non-ictal iEEG. We compare our results to a method published by Shoeb in 2004. While the original method on sEEG was optimal with the use of only four subbands in the wavelet analysis, we found that better seizure detection could be made if all subbands were used for iEEG. Results: When using...

Alzheimer's disease: The state of the art in resting-state magnetoencephalography.

Science.gov (United States)

Engels, M M A; van der Flier, W M; Stam, C J; Hillebrand, A; Scheltens, Ph; van Straaten, E C W

2017-08-01

Alzheimer's disease (AD) is accompanied by functional brain changes that can be detected in imaging studies, including electromagnetic activity recorded with magnetoencephalography (MEG). Here, we systematically review the studies that have examined resting-state MEG changes in AD and identify areas that lack scientific or clinical progress. Three levels of MEG analysis will be covered: (i) single-channel signal analysis, (ii) pairwise analyses over time series, which includes the study of interdependencies between two time series and (iii) global network analyses. We discuss the findings in the light of other functional modalities, such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Overall, single-channel MEG results show consistent changes in AD that are in line with EEG studies, but the full potential of the high spatial resolution of MEG and advanced functional connectivity and network analysis has yet to be fully exploited. Adding these features to the current knowledge will potentially aid in uncovering organizational patterns of brain function in AD and thereby aid the understanding of neuronal mechanisms leading to cognitive deficits. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

EEG classification of emotions using emotion-specific brain functional network.

Science.gov (United States)

Gonuguntla, V; Shafiq, G; Wang, Y; Veluvolu, K C

2015-08-01

The brain functional network perspective forms the basis to relate mechanisms of brain functions. This work analyzes the network mechanisms related to human emotion based on synchronization measure - phase-locking value in EEG to formulate the emotion specific brain functional network. Based on network dissimilarities between emotion and rest tasks, most reactive channel pairs and the reactive band corresponding to emotions are identified. With the identified most reactive pairs, the subject-specific functional network is formed. The identified subject-specific and emotion-specific dynamic network pattern show significant synchrony variation in line with the experiment protocol. The same network pattern are then employed for classification of emotions. With the study conducted on the 4 subjects, an average classification accuracy of 62 % was obtained with the proposed technique.

Childhood trauma and dissociative symptoms predict frontal EEG asymmetry in borderline personality disorder.

Science.gov (United States)

Popkirov, Stoyan; Flasbeck, Vera; Schlegel, Uwe; Juckel, Georg; Brüne, Martin

2018-03-15

Frontal EEG asymmetry (FEA) has been studied as both state and trait parameter in emotion regulation and affective disorders. Its significance in borderline personality disorder (BPD) remains largely unknown. Twenty-six BPD patients and 26 healthy controls underwent EEG before and after mood induction using aversive images. A slight but significant shift from left- to right-sided asymmetry over prefrontal electrodes occurred across all subjects. In BPD baseline FEA over F7 and F8 correlated significantly with childhood trauma and functional neurological "conversion" symptoms as assessed by respective questionnaires. Regression analysis revealed a predictive role of both childhood trauma and dissociative neurological symptoms. FEA offers a relatively stable electrophysiological correlate of BPD psychopathology that responds only minimally to acute mood changes. Future studies should address whether this psychophysiological association is universal for trauma- and dissociation-related disorders, and whether it is responsive to psychotherapy.

Effects and after-effects of chewing gum on vigilance, heart rate, EEG and mood.

Science.gov (United States)

Allen, Andrew P; Jacob, Tim J C; Smith, Andrew P

2014-06-22

Research has shown that chewing gum improves attention, although the mechanism for this effect remains unclear. This study investigated the effects and after-effects of chewing gum on vigilance, mood, heart rate and EEG. Participants completed a vigilance task four times; at baseline, with or without chewing gum, and twice post-chewing. EEG alpha and beta power at left frontal and temporal lobes, subjective mood and heart rate were assessed. Chewing gum shortened reaction time and increased the rate of hits, although hits fell during the second post-chewing task. Chewing gum heightened heart rate, but only during chewing. Gum also increased beta power at F7 and T3 immediately post-chewing, but not following the post-chewing tasks. The findings show that chewing gum affects several different indicators of alertness. Copyright © 2014 Elsevier Inc. All rights reserved.

EEG

African Journals Online (AJOL)

2017-09-03

Sep 3, 2017 ... However, very few studies have examined the use of EEG in developing countries, including Ni- ... of evoked potentials from brain neurons, referred to as .... Percentage. Gender. Male. 89. 62.7. Female. 53. 37.3. Age. 0-10. 59.

Baseline Neurocognitive Test Results In Non-concussed Athletes: Does Sleep Matter?

OpenAIRE

McClure, D. Jake; Zuckerman, Scott L.; Kutscher, Scott J.; Gregory, Andrew; Solomon, Gary S.

2013-01-01

Objectives: When managing sport-related concussions (SRC), sports medicine physicians utilize serial neurocognitive assessments and self-reported symptom inventories when evaluating athlete recovery and safety for returning to play (RTP). Since post-concussive RTP goals include symptom resolution and return to neurocognitive baseline, clinical decisions rest on an understanding of modifiers of baseline performance. Several studies have reported the influence of age, gender and sport on baseli...

Contribution of EEG in transient neurological deficits.

Science.gov (United States)

Lozeron, Pierre; Tcheumeni, Nadine Carole; Turki, Sahar; Amiel, Hélène; Meppiel, Elodie; Masmoudi, Sana; Roos, Caroline; Crassard, Isabelle; Plaisance, Patrick; Benbetka, Houria; Guichard, Jean-Pierre; Houdart, Emmanuel; Baudoin, Hélène; Kubis, Nathalie

2018-01-01

Identification of stroke mimics and 'chameleons' among transient neurological deficits (TND) is critical. Diagnostic workup consists of a brain imaging study, for a vascular disease or a brain tumour and EEG, for epileptiform discharges. The precise role of EEG in this diagnostic workup has, however, never been clearly delineated. However, this could be crucial in cases of atypical or incomplete presentation with consequences on disease management and treatment. We analysed the EEG patterns on 95 consecutive patients referred for an EEG within 7 days of a TND with diagnostic uncertainty. Patients were classified at the discharge or the 3-month follow-up visit as: 'ischemic origin', 'migraine aura', 'focal seizure', and 'other'. All patients had a brain imaging study. EEG characteristics were correlated to the TND symptoms, imaging study, and final diagnosis. Sixty four (67%) were of acute onset. Median symptom duration was 45 min. Thirty two % were 'ischemic', 14% 'migraine aura', 19% 'focal seizure', and 36% 'other' cause. EEGs were recorded with a median delay of 1.6 day after symptoms onset. Forty EEGs (42%) were abnormal. Focal slow waves were the most common finding (43%), also in the ischemic group (43%), whether patients had a typical presentation or not. Epileptiform discharges were found in three patients, one with focal seizure and two with migraine aura. Non-specific EEG focal slowing is commonly found in TND, and may last several days. We found no difference in EEG presentation between stroke mimics and stroke chameleons, and between other diagnoses.

Resting-state brain networks revealed by granger causal connectivity in frogs.

Science.gov (United States)

Xue, Fei; Fang, Guangzhan; Yue, Xizi; Zhao, Ermi; Brauth, Steven E; Tang, Yezhong

2016-10-15

Resting-state networks (RSNs) refer to the spontaneous brain activity generated under resting conditions, which maintain the dynamic connectivity of functional brain networks for automatic perception or higher order cognitive functions. Here, Granger causal connectivity analysis (GCCA) was used to explore brain RSNs in the music frog (Babina daunchina) during different behavioral activity phases. The results reveal that a causal network in the frog brain can be identified during the resting state which reflects both brain lateralization and sexual dimorphism. Specifically (1) ascending causal connections from the left mesencephalon to both sides of the telencephalon are significantly higher than those from the right mesencephalon, while the right telencephalon gives rise to the strongest efferent projections among all brain regions; (2) causal connections from the left mesencephalon in females are significantly higher than those in males and (3) these connections are similar during both the high and low behavioral activity phases in this species although almost all electroencephalograph (EEG) spectral bands showed higher power in the high activity phase for all nodes. The functional features of this network match important characteristics of auditory perception in this species. Thus we propose that this causal network maintains auditory perception during the resting state for unexpected auditory inputs as resting-state networks do in other species. These results are also consistent with the idea that females are more sensitive to auditory stimuli than males during the reproductive season. In addition, these results imply that even when not behaviorally active, the frogs remain vigilant for detecting external stimuli. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

EEG-informed fMRI analysis during a hand grip task: estimating the relationship between EEG rhythms and the BOLD signal

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Roberta eSclocco

2014-04-01

Full Text Available In the last decade, an increasing interest has arisen in investigating the relationship between the electrophysiological and hemodynamic measurements of brain activity, such as EEG and (BOLD fMRI. In particular, changes in BOLD have been shown to be associated with changes in the spectral profile of neural activity, rather than with absolute power. Concurrently, recent findings showed that different EEG rhythms are independently related to changes in the BOLD signal: therefore, it would be important to distinguish between the contributions of the different EEG rhythms to BOLD fluctuations when modeling the relationship between the two signals. Here we propose a method to perform EEG-informed fMRI analysis, in which the EEG regressors take into account both the changes in the spectral profile and the rhythms distinction. We applied it to EEG-fMRI data during a hand grip task in healthy subjects, and compared the results with those obtained by two existing models found in literature. Our results showed that the proposed method better captures the correlations between BOLD signal and EEG rhythms modulations, identifying task-related, well localized activated volumes. Furthermore, we showed that including among the regressors also EEG rhythms not primarily involved in the task enhances the performance of the analysis, even when only correlations with BOLD signal and specific EEG rhythms are explored.

The added value of simultaneous EEG and amplitude-integrated EEG recordings in three newborn infants

NARCIS (Netherlands)

de Vries, Nathalie K. S.; ter Horst, Hendrik J.; Bos, Arend F.

2007-01-01

Amplitude-integrated electroencephalograms (aEEGs) recorded by cerebral function monitors (CFMs) are used increasingly to monitor the cerebral activity of newborn infants with encephalopathy. Recently, new CFM devices became available which also reveal the original EEG signals from the same leads.

Two channel EEG thought pattern classifier.

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Craig, D A; Nguyen, H T; Burchey, H A

2006-01-01

This paper presents a real-time electro-encephalogram (EEG) identification system with the goal of achieving hands free control. With two EEG electrodes placed on the scalp of the user, EEG signals are amplified and digitised directly using a ProComp+ encoder and transferred to the host computer through the RS232 interface. Using a real-time multilayer neural network, the actual classification for the control of a powered wheelchair has a very fast response. It can detect changes in the user's thought pattern in 1 second. Using only two EEG electrodes at positions O(1) and C(4) the system can classify three mental commands (forward, left and right) with an accuracy of more than 79 %

A Resting-State Brain Functional Network Study in MDD Based on Minimum Spanning Tree Analysis and the Hierarchical Clustering

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Xiaowei Li

2017-01-01

Full Text Available A large number of studies demonstrated that major depressive disorder (MDD is characterized by the alterations in brain functional connections which is also identifiable during the brain’s “resting-state.” But, in the present study, the approach of constructing functional connectivity is often biased by the choice of the threshold. Besides, more attention was paid to the number and length of links in brain networks, and the clustering partitioning of nodes was unclear. Therefore, minimum spanning tree (MST analysis and the hierarchical clustering were first used for the depression disease in this study. Resting-state electroencephalogram (EEG sources were assessed from 15 healthy and 23 major depressive subjects. Then the coherence, MST, and the hierarchical clustering were obtained. In the theta band, coherence analysis showed that the EEG coherence of the MDD patients was significantly higher than that of the healthy controls especially in the left temporal region. The MST results indicated the higher leaf fraction in the depressed group. Compared with the normal group, the major depressive patients lost clustering in frontal regions. Our findings suggested that there was a stronger brain interaction in the MDD group and a left-right functional imbalance in the frontal regions for MDD controls.

Evidence for a Resting State Network Abnormality in Adults Who Stutter

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Amir H. Ghaderi

2018-04-01

Full Text Available Neural network-based investigations of stuttering have begun to provide a possible integrative account for the large number of brain-based anomalies associated with stuttering. Here we used resting-state EEG to investigate functional brain networks in adults who stutter (AWS. Participants were 19 AWS and 52 age-, and gender-matched normally fluent speakers. EEGs were recorded and connectivity matrices were generated by LORETA in the theta (4–8 Hz, alpha (8–12 Hz, beta1 (12–20 Hz, and beta2 (20–30 Hz bands. Small-world propensity (SWP, shortest path, and clustering coefficients were computed for weighted graphs. Minimum spanning tree analysis was also performed and measures were compared by non-parametric permutation test. The results show that small-world topology was evident in the functional networks of all participants. Three graph indices (diameter, clustering coefficient, and shortest path exhibited significant differences between groups in the theta band and one [maximum betweenness centrality (BC] measure was significantly different between groups in the beta2 band. AWS show higher BC than control in right temporal and inferior frontal areas and lower BC in the right primary motor cortex. Abnormal functional networks during rest state suggest an anomaly of DMN activity in AWS. Furthermore, functional segregation/integration deficits in the theta network are evident in AWS. These deficits reinforce the hypothesis that there is a neural basis for abnormal executive function in AWS. Increased beta2 BC in the right speech–motor related areas confirms previous evidence that right audio–speech areas are over-activated in AWS. Decreased beta2 BC in the right primary motor cortex is discussed in relation to abnormal neural mechanisms associated with time perception in AWS.

Changes in dynamic resting state network connectivity following aphasia therapy.

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Duncan, E Susan; Small, Steven L

2017-10-24

Resting state magnetic resonance imaging (rsfMRI) permits observation of intrinsic neural networks produced by task-independent correlations in low frequency brain activity. Various resting state networks have been described, with each thought to reflect common engagement in some shared function. There has been limited investigation of the plasticity in these network relationships after stroke or induced by therapy. Twelve individuals with language disorders after stroke (aphasia) were imaged at multiple time points before (baseline) and after an imitation-based aphasia therapy. Language assessment using a narrative production task was performed at the same time points. Group independent component analysis (ICA) was performed on the rsfMRI data to identify resting state networks. A sliding window approach was then applied to assess the dynamic nature of the correlations among these networks. Network correlations during each 30-second window were used to cluster the data into ten states for each window at each time point for each subject. Correlation was performed between changes in time spent in each state and therapeutic gains on the narrative task. The amount of time spent in a single one of the (ten overall) dynamic states was positively associated with behavioral improvement on the narrative task at the 6-week post-therapy maintenance interval, when compared with either baseline or assessment immediately following therapy. This particular state was characterized by minimal correlation among the task-independent resting state networks. Increased functional independence and segregation of resting state networks underlies improvement on a narrative production task following imitation-based aphasia treatment. This has important clinical implications for the targeting of noninvasive brain stimulation in post-stroke remediation.

Executive function on the 16-day of bed rest in young healthy men

Science.gov (United States)

Ishizaki, Yuko; Fukuoka, Hideoki; Tanaka, Hidetaka; Ishizaki, Tatsuro; Fujii, Yuri; Hattori-Uchida, Yuko; Nakamura, Minako; Ohkawa, Kaoru; Kobayashi, Hodaka; Taniuchi, Shoichiro; Kaneko, Kazunari

2009-05-01

Microgravity due to prolonged bed rest may cause changes in cerebral circulation, which is related to brain function. We evaluate the effect of simulated microgravity due to a 6° head-down tilt bed rest experiment on executive function among 12 healthy young men. Four kinds of psychoneurological tests—the table tapping test, the trail making test, the pointing test and losing at rock-paper-scissors—were performed on the baseline and on day 16 of the experiment. There was no significant difference in the results between the baseline and day 16 on all tests, which indicated that executive function was not impaired by the 16-day 6° head-down tilting bed rest. However, we cannot conclude that microgravity did not affect executive function because of the possible contribution of the following factors: (1) the timing of tests, (2) the learning effect, or (3) changes in psychophysiology that were too small to affect higher brain function.

Anti-deception: reliable EEG-based biometrics with real-time capability from the neural response of face rapid serial visual presentation.

Science.gov (United States)

Wu, Qunjian; Yan, Bin; Zeng, Ying; Zhang, Chi; Tong, Li

2018-05-03

The electroencephalogram (EEG) signal represents a subject's specific brain activity patterns and is considered as an ideal biometric given its superior invisibility, non-clonality, and non-coercion. In order to enhance its applicability in identity authentication, a novel EEG-based identity authentication method is proposed based on self- or non-self-face rapid serial visual presentation. In contrast to previous studies that extracted EEG features from rest state or motor imagery, the designed paradigm could obtain a distinct and stable biometric trait with a lower time cost. Channel selection was applied to select specific channels for each user to enhance system portability and improve discriminability between users and imposters. Two different imposter scenarios were designed to test system security, which demonstrate the capability of anti-deception. Fifteen users and thirty imposters participated in the experiment. The mean authentication accuracy values for the two scenarios were 91.31 and 91.61%, with 6 s time cost, which illustrated the precision and real-time capability of the system. Furthermore, in order to estimate the repeatability and stability of our paradigm, another data acquisition session is conducted for each user. Using the classification models generated from the previous sessions, a mean false rejected rate of 7.27% has been achieved, which demonstrates the robustness of our paradigm. Experimental results reveal that the proposed paradigm and methods are effective for EEG-based identity authentication.

Is Love Right? Prefrontal Resting Brain Asymmetry is Related to the Affiliation Motive

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Markus eQuirin

2013-12-01

Full Text Available Previous research on relationships between affective-motivational traits and hemispheric asymmetries in resting frontal alpha band power as measured by electroencephalography (EEG has focused on individual differences in motivational direction (approach vs. withdrawal or behavioral activation. The present study investigated resting frontal alpha asymmetries in 72 participants as a function of individual differences in the implicit affiliation motive as measured with the operant motive test (OMT and explored the brain source thereof. As predicted, relative right frontal activity as indexed by increased alpha band suppression was related to the implicit affiliation motive. No relationships were found for explicit personality measures. Intracranial current density distributions of alpha based on Variable Resolution Electromagnetic Tomography (VARETA source estimations suggests that the source of cortical alpha distribution is located within the right ventromedial prefrontal cortex (PFC. The present results are discussed with respect to differential roles of the two hemispheres in social motivation.

EEG. Renewables Act. Comment. 3. new rev. and enl. ed.; EEG. Erneuerbare-Energien-Gesetz. Kommentar

Energy Technology Data Exchange (ETDEWEB)

Frenz, Walter [Rheinisch-Westfaelische Technische Hochschule (RWTH), Aachen (Germany). Lehr- und Forschungsgebiet Berg-, Umwelt- und Europarecht; Mueggenborg, Hans-Juergen (eds.) [Kassel Univ. (Germany)

2013-05-01

Like hardly any other law, the Renewable Energy Sources Law (EEG) is a subject to continuing modifications. This makes the application of the already complicated regulations even for experts to a special challenge. With the proven Berliner comment EEG, now a reliable companion through the bureaucratic jungle is available. All regulations of the EEG are commented precisely and easily to understand by profound experts. An extensive selection of terminology enables a rapid orientation within this book. In addition to the excursions to renewable energy technologies, this book also describes the structural aspects in the establishment of a photovoltaic system.

Standardized Computer-based Organized Reporting of EEG: SCORE

Science.gov (United States)

Beniczky, Sándor; Aurlien, Harald; Brøgger, Jan C; Fuglsang-Frederiksen, Anders; Martins-da-Silva, António; Trinka, Eugen; Visser, Gerhard; Rubboli, Guido; Hjalgrim, Helle; Stefan, Hermann; Rosén, Ingmar; Zarubova, Jana; Dobesberger, Judith; Alving, Jørgen; Andersen, Kjeld V; Fabricius, Martin; Atkins, Mary D; Neufeld, Miri; Plouin, Perrine; Marusic, Petr; Pressler, Ronit; Mameniskiene, Ruta; Hopfengärtner, Rüdiger; Emde Boas, Walter; Wolf, Peter

2013-01-01

The electroencephalography (EEG) signal has a high complexity, and the process of extracting clinically relevant features is achieved by visual analysis of the recordings. The interobserver agreement in EEG interpretation is only moderate. This is partly due to the method of reporting the findings in free-text format. The purpose of our endeavor was to create a computer-based system for EEG assessment and reporting, where the physicians would construct the reports by choosing from predefined elements for each relevant EEG feature, as well as the clinical phenomena (for video-EEG recordings). A working group of EEG experts took part in consensus workshops in Dianalund, Denmark, in 2010 and 2011. The faculty was approved by the Commission on European Affairs of the International League Against Epilepsy (ILAE). The working group produced a consensus proposal that went through a pan-European review process, organized by the European Chapter of the International Federation of Clinical Neurophysiology. The Standardised Computer-based Organised Reporting of EEG (SCORE) software was constructed based on the terms and features of the consensus statement and it was tested in the clinical practice. The main elements of SCORE are the following: personal data of the patient, referral data, recording conditions, modulators, background activity, drowsiness and sleep, interictal findings, “episodes” (clinical or subclinical events), physiologic patterns, patterns of uncertain significance, artifacts, polygraphic channels, and diagnostic significance. The following specific aspects of the neonatal EEGs are scored: alertness, temporal organization, and spatial organization. For each EEG finding, relevant features are scored using predefined terms. Definitions are provided for all EEG terms and features. SCORE can potentially improve the quality of EEG assessment and reporting; it will help incorporate the results of computer-assisted analysis into the report, it will make

Pharmaco-EEG: A Study of Individualized Medicine in Clinical Practice.

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Swatzyna, Ronald J; Kozlowski, Gerald P; Tarnow, Jay D

2015-07-01

Pharmaco-electroencephalography (Pharmaco-EEG) studies using clinical EEG and quantitative EEG (qEEG) technologies have existed for more than 4 decades. This is a promising area that could improve psychotropic intervention using neurological data. One of the objectives in our clinical practice has been to collect EEG and quantitative EEG (qEEG) data. In the past 5 years, we have identified a subset of refractory cases (n = 386) found to contain commonalities of a small number of electrophysiological features in the following diagnostic categories: mood, anxiety, autistic spectrum, and attention deficit disorders, Four abnormalities were noted in the majority of medication failure cases and these abnormalities did not appear to significantly align with their diagnoses. Those were the following: encephalopathy, focal slowing, beta spindles, and transient discharges. To analyze the relationship noted, they were tested for association with the assigned diagnoses. Fisher's exact test and binary logistics regression found very little (6%) association between particular EEG/qEEG abnormalities and diagnoses. Findings from studies of this type suggest that EEG/qEEG provides individualized understanding of pharmacotherapy failures and has the potential to improve medication selection. © EEG and Clinical Neuroscience Society (ECNS) 2014.

Abnormal pain processing in chronic tension-type headache: a high-density EEG brain mapping study

DEFF Research Database (Denmark)

Buchgreitz, L.; Egsgaard, L.L.; Jensen, R.

2008-01-01

Central sensitization caused by prolonged nociceptive input from muscles is considered to play an important role for chronification of tension-type headache. In the present study we used a new high-density EEG brain mapping technique to investigate spatiotemporal aspects of brain activity...... in response to muscle pain in 19 patients with chronic tension-type headache (CTTH) and 19 healthy, age- and sex-matched controls. Intramuscular electrical stimuli (single and train of five pulses delivered at 2 Hz) were applied to the trapezius muscle and somatosensory evoked potentials were recorded...... with 128-channel EEG both in- and outside a condition with induced tonic neck/shoulder muscle pain (glutamate injection into the trapezius muscle). Significant reduction in magnitude during and after induced tonic muscle pain was found in controls at the P200 dipole in response to both the first (baseline...

EEG activity during estral cycle in the rat.

Science.gov (United States)

Corsi-Cabrera, M; Juárez, J; Ponce-de-León, M; Ramos, J; Velázquez, P N

1992-10-01

EEG activity was recorded from right and left parietal cortex in adult female rats daily during 6 days. Immediately after EEG recording vaginal smears were taken and were microscopically analyzed to determine the estral stage. Absolute and relative powers and interhemispheric correlation of EEG activity were calculated and compared between estral stages. Interhemispheric correlation was significantly lower during diestrous as compared to proestrous and estrous. Absolute and relative powers did not show significant differences between estral stages. Absolute powers of alpha1, alpha2, beta1 and beta2 bands were significantly higher at the right parietal cortex. Comparisons of the same EEG records with estral stages randomly grouped showed no significant differences for any of the EEG parameters. EEG activity is a sensitive tool to study functional changes related to the estral cycle.

Signal Quality Evaluation of Emerging EEG Devices

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Thea Radüntz

2018-02-01

Full Text Available Electroencephalogram (EEG registration as a direct measure of brain activity has unique potentials. It is one of the most reliable and predicative indicators when studying human cognition, evaluating a subject's health condition, or monitoring their mental state. Unfortunately, standard signal acquisition procedures limit the usability of EEG devices and narrow their application outside the lab. Emerging sensor technology allows gel-free EEG registration and wireless signal transmission. Thus, it enables quick and easy application of EEG devices by users themselves. Although a main requirement for the interpretation of an EEG is good signal quality, there is a lack of research on this topic in relation to new devices. In our work, we compared the signal quality of six very different EEG devices. On six consecutive days, 24 subjects wore each device for 60 min and completed tasks and games on the computer. The registered signals were evaluated in the time and frequency domains. In the time domain, we examined the percentage of artifact-contaminated EEG segments and the signal-to-noise ratios. In the frequency domain, we focused on the band power variation in relation to task demands. The results indicated that the signal quality of a mobile, gel-based EEG system could not be surpassed by that of a gel-free system. However, some of the mobile dry-electrode devices offered signals that were almost comparable and were very promising. This study provided a differentiated view of the signal quality of emerging mobile and gel-free EEG recording technology and allowed an assessment of the functionality of the new devices. Hence, it provided a crucial prerequisite for their general application, while simultaneously supporting their further development.

Standardized computer-based organized reporting of EEG

DEFF Research Database (Denmark)

Beniczky, Sándor; Aurlien, Harald; Brøgger, Jan C.

2017-01-01

Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted in the se......Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted...... in the second, revised version of SCORE (Standardized Computer-based Organized Reporting of EEG), which is presented in this paper. The revised terminology was implemented in a software package (SCORE EEG), which was tested in clinical practice on 12,160 EEG recordings. Standardized terms implemented in SCORE...... are used to report the features of clinical relevance, extracted while assessing the EEGs. Selection of the terms is context sensitive: initial choices determine the subsequently presented sets of additional choices. This process automatically generates a report and feeds these features into a database...

Screening EEG in Aircrew Selection: Clinical Aerospace Neurology Perspective

Science.gov (United States)

Clark, Jonathan B.; Riley, Terrence

2001-01-01

As clinical aerospace neurologists we do not favor using screening EEG in pilot selection on unselected and otherwise asymptomatic individuals. The role of EEG in aviation screening should be as an adjunct to diagnosis, and the decision to disqualify a pilot should never be based solely on the EEG. Although a policy of using a screening EEG in an unselected population might detect an individual with a potentially increased relative risk, it would needlessly exclude many applicants who would probably never have a seizure. A diagnostic test performed on an asymptomatic individual without clinical indications, in a population with a low prevalence of disease (seizure) may be of limited or possibly detrimental value. We feel that rather than do EEGs on all candidates, a better approach would be to perform an EEG for a specific indication, such as family history of seizure, single convulsion (seizure) , history of unexplained loss of consciousness or head injury. Routine screening EEGs in unselected aviation applications are not done without clinical indication in the U.S. Air Force, Navy, or NASA. The USAF discontinued routine screening EEGs for selection in 1978, the U.S. Navy discontinued it in 1981 , and NASA discontinued it in 1995. EEG as an aeromedical screening tool in the US Navy dates back to 1939. The US Navy routinely used EEGs to screen all aeromedical personnel from 1961 to 1981. The incidence of epileptiform activity on EEG in asymptomatic flight candidates ranges from 0.11 to 2.5%. In 3 studies of asymptomatic flight candidates with epileptiform activity on EEG followed for 2 to 15 years, 1 of 31 (3.2%), 1 of 30 (3.3%), and 0 of 14 (0%) developed a seizure, for a cumulative risk of an individual with an epileptiform EEG developing a seizure of 2.67% (2 in 75). Of 28,658 student naval aviation personnel screened 31 had spikes and/or slow waves on EEG, and only 1 later developed a seizure. Of the 28,627 who had a normal EEG, 4 later developed seizures, or

Brain order disorder 2nd group report of f-EEG

Science.gov (United States)

Lalonde, Francois; Gogtay, Nitin; Giedd, Jay; Vydelingum, Nadarajen; Brown, David; Tran, Binh Q.; Hsu, Charles; Hsu, Ming-Kai; Cha, Jae; Jenkins, Jeffrey; Ma, Lien; Willey, Jefferson; Wu, Jerry; Oh, Kenneth; Landa, Joseph; Lin, C. T.; Jung, T. P.; Makeig, Scott; Morabito, Carlo Francesco; Moon, Qyu; Yamakawa, Takeshi; Lee, Soo-Young; Lee, Jong-Hwan; Szu, Harold H.; Kaur, Balvinder; Byrd, Kenneth; Dang, Karen; Krzywicki, Alan; Familoni, Babajide O.; Larson, Louis; Harkrider, Susan; Krapels, Keith A.; Dai, Liyi

2014-05-01

responses, which is what we seek. The averaged traditional EEG measurements and are further improved by BSS decomposition into finer stimulus-response source mixing matrix [A] having finer & faster spatial grids with rapid temporal updates. Then, the functional EEG is the second order co-variance matrix defined as the electrode-pair fluctuation correlation function C(s~, s~') of independent thermodynamic source components. (1) We define a 1-D Space filling curve as a spiral curve without origin. This pattern is historically known as the Peano-Hilbert arc length a. By taking the most significant bits of the Cartesian product a≡ O(x * y * z), it represents the arc length in the numerical size with values that map the 3-D neighborhood proximity into a 1-D neighborhood arc length representation. (2) 1-D Fourier coefficients spectrum have no spurious high frequency contents, which typically arise in lexicographical (zig-zag scanning) discontinuity [Hsu & Szu, "Peano-Hilbert curve," SPIE 2014]. A simple Fourier spectrum histogram fits nicely with the Compressive Sensing CRDT Mathematics. (3) Stationary power spectral density is a reasonable approximation of EEG responses in striate layers in resonance feedback loops capable of producing a 100, 000 neuronal collective Impulse Response Function (IRF). The striate brain layer architecture represents an ensemble functional-EEG: After taking the 1-D space-filling curve, we compute the ensemble averaged 1-D Power Spectral Density (PSD) and then make use of the inverse FFT to generate f-EEG. (ii) Goal#2 individual wellness baseline (IWB): We need novel change detection, so we derive the ubiquitous fat-tail distributions for healthy brains PSD in outdoor environments (Signal=310°C Noise=27°C: SNR=310/300; 300°K=(1/40)eV). The departure from IWB might imply stress, fever, a sports injury, an unexpected fall, or numerous midnight excursions which may signal an onset of dementia in Home Alone Senior (HAS), discovered by telemedicine

Correlations of CT and EEG findings in brain affections

International Nuclear Information System (INIS)

Roth, B.; Nevsimalova, S.; Kvicala, V.

1984-01-01

The results were compared of electroencephalography (EEG) and computerized tomography (CT) examinations of 250 patients with different brain affections. In intracranial expansive processes the pre-operative CT findings were positive in 100% cases, the EEG findings in 89.7% of cases. In severe traumatic affections the EEG and CT findings were positive in all cases, in mild injuries and post-traumatic conditions the EEG findings were more frequently positive than the CT. In focal and diffuse vascular affections the EEG and CT findings were consistent, in transitory ischemic conditions the EEG findings were more frequently positive. In inflammatory cerebral affections and in paroxymal diseases the EEG findings were positive more frequently than the CT. The same applies for demyelinating and degenerative affections. Findings of other authors were confirmed to the effect that CT very reliably reveals morphological changes in cerebral tissue while EEG records the functional state of the central nervous system and its changes. The two methods are complementary. (author)

Identifying the effects of microsaccades in tripolar EEG signals.

Science.gov (United States)

Bellisle, Rachel; Steele, Preston; Bartels, Rachel; Lei Ding; Sunderam, Sridhar; Besio, Walter

2017-07-01

Microsaccades are tiny, involuntary eye movements that occur during fixation, and they are necessary to human sight to maintain a sharp image and correct the effects of other fixational movements. Researchers have theorized and studied the effects of microsaccades on electroencephalography (EEG) signals to understand and eliminate the unwanted artifacts from EEG. The tripolar concentric ring electrode (TCRE) sensors are used to acquire TCRE EEG (tEEG). The tEEG detects extremely focal signals from directly below the TCRE sensor. We have noticed a slow wave frequency found in some tEEG recordings. Therefore, we conducted the current work to determine if there was a correlation between the slow wave in the tEEG and the microsaccades. This was done by analyzing the coherence of the frequency spectrums of both tEEG and eye movement in recordings where microsaccades are present. Our preliminary findings show that there is a correlation between the two.

Clinical utility of early amplitude integrated EEG in monitoring term newborns at risk of neurological injury

Directory of Open Access Journals (Sweden)

Paulina A. Toso

2014-03-01

Full Text Available Objective: to test the clinical utility of an early amplitude-integrated electroencephalography (aEEG to predict short-term neurological outcome in term newborns at risk of neurology injury. Methods: this was a prospective, descriptive study. The inclusion criteria were neonatal encephalopathy, neurologic disturbances, and severe respiratory distress syndrome. Sensitivity, specificity, positive and negative predictive values, and likelihood ratio (LR were calculated. Clinical and demographic data were analyzed. Neurological outcome was defined as the sum of clinical, electroimaging, and neuroimaging findings. Results: ten of the 21 monitored infants (48% presented altered short-term neurologic outcome. The aEEG had 90% sensitivity, 82% specificity, 82% positive predictive value, and 90% negative predictive value. The positive LR was 4.95, and the negative LR was 0.12. In three of 12 (25% encephalopathic infants, the aEEG allowed for a better definition of the severity of their condition. Seizures were detected in eight infants (38%, all subclinical at baseline, and none had a normal aEEG background pattern. The status of three infants (43% evolved and required two or more drugs for treatment. Conclusions: in infants with encephalopathy or other severe illness, aEEG disturbances occur frequently. aEEG provided a better classification of the severity of encephalopathy, detected early subclinical seizures, and allowed for monitoring of the response to treatment. aEEG was a useful tool at the neonatal intensive care unit for predicting poor short-term neurological outcomes for all sick newborn. Resumo: Objetivo: testar a utilidade clínica do aEEG precoce em recém-nascidos a termo com risco de lesão neurológica, para prever resultados neurológicos de curto prazo. Métodos: estudo prospectivo e descritivo. Os critérios de inclusão foram encefalopatia neonatal, distúrbios neurológicos e bebês com SARA grave. Sensibilidade, especificidade

Combined process automation for large-scale EEG analysis.

Science.gov (United States)

Sfondouris, John L; Quebedeaux, Tabitha M; Holdgraf, Chris; Musto, Alberto E

2012-01-01

Epileptogenesis is a dynamic process producing increased seizure susceptibility. Electroencephalography (EEG) data provides information critical in understanding the evolution of epileptiform changes throughout epileptic foci. We designed an algorithm to facilitate efficient large-scale EEG analysis via linked automation of multiple data processing steps. Using EEG recordings obtained from electrical stimulation studies, the following steps of EEG analysis were automated: (1) alignment and isolation of pre- and post-stimulation intervals, (2) generation of user-defined band frequency waveforms, (3) spike-sorting, (4) quantification of spike and burst data and (5) power spectral density analysis. This algorithm allows for quicker, more efficient EEG analysis. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Spiking Neural Network Methodology and System for Learning and Comparative Analysis of EEG Data From Healthy Versus Addiction Treated Versus Addiction Not Treated Subjects.

Science.gov (United States)

Doborjeh, Maryam Gholami; Wang, Grace Y; Kasabov, Nikola K; Kydd, Robert; Russell, Bruce

2016-09-01

This paper introduces a method utilizing spiking neural networks (SNN) for learning, classification, and comparative analysis of brain data. As a case study, the method was applied to electroencephalography (EEG) data collected during a GO/NOGO cognitive task performed by untreated opiate addicts, those undergoing methadone maintenance treatment (MMT) for opiate dependence and a healthy control group. the method is based on an SNN architecture called NeuCube, trained on spatiotemporal EEG data. NeuCube was used to classify EEG data across subject groups and across GO versus NOGO trials, but also facilitated a deeper comparative analysis of the dynamic brain processes. This analysis results in a better understanding of human brain functioning across subject groups when performing a cognitive task. In terms of the EEG data classification, a NeuCube model obtained better results (the maximum obtained accuracy: 90.91%) when compared with traditional statistical and artificial intelligence methods (the maximum obtained accuracy: 50.55%). more importantly, new information about the effects of MMT on cognitive brain functions is revealed through the analysis of the SNN model connectivity and its dynamics. this paper presented a new method for EEG data modeling and revealed new knowledge on brain functions associated with mental activity which is different from the brain activity observed in a resting state of the same subjects.

Development of brain synchronisation within school-age--individual analysis of resting (α) coherence in a longitudinal data set.

Science.gov (United States)

Gmehlin, Dennis; Thomas, Christine; Weisbrod, Matthias; Walther, Stephan; Resch, Franz; Oelkers-Ax, Rieke

2011-10-01

Given evidence that synchronisation of neuronal activity may be a correlate of cognition, we examined EEG coherence as function of age and inter-electrode distance in healthy children and adolescents in order to elucidate basic information for a better understanding of developmental disorders associated with deficits in cognitive functions. Based on a 64-channel eyes closed resting EEG we combined local and global coherence measures in order to reduce volume conduction and reference effects. We used a two point longitudinal design in order to analyze intraindividual change during school-age (n=40; 6-18 years). Coherence was analyzed within individually adjusted frequency bands and around iPF (= individual alpha peak frequency). Both local and global resting coherence was largest in the alpha range and particularly around iPF. Local synchronisation was larger in the left compared with the right hemisphere. Controlling for increases in iPF, synchronisation increased with age, with global changes being most pronounced in the alpha range. Moreover age-related changes suggest an earlier development in girls. Our data provides evidence that both local and global functional integration increases during normal development within school-age. This general pattern - combined with more specific effects of sex and frequency - may help to specify deviations in developmental disorders. Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Mapping (and modeling) physiological movements during EEG-fMRI recordings: the added value of the video acquired simultaneously.

Science.gov (United States)

Ruggieri, Andrea; Vaudano, Anna Elisabetta; Benuzzi, Francesca; Serafini, Marco; Gessaroli, Giuliana; Farinelli, Valentina; Nichelli, Paolo Frigio; Meletti, Stefano

2015-01-15

During resting-state EEG-fMRI studies in epilepsy, patients' spontaneous head-face movements occur frequently. We tested the usefulness of synchronous video recording to identify and model the fMRI changes associated with non-epileptic movements to improve sensitivity and specificity of fMRI maps related to interictal epileptiform discharges (IED). Categorization of different facial/cranial movements during EEG-fMRI was obtained for 38 patients [with benign epilepsy with centro-temporal spikes (BECTS, n=16); with idiopathic generalized epilepsy (IGE, n=17); focal symptomatic/cryptogenic epilepsy (n=5)]. We compared at single subject- and at group-level the IED-related fMRI maps obtained with and without additional regressors related to spontaneous movements. As secondary aim, we considered facial movements as events of interest to test the usefulness of video information to obtain fMRI maps of the following face movements: swallowing, mouth-tongue movements, and blinking. Video information substantially improved the identification and classification of the artifacts with respect to the EEG observation alone (mean gain of 28 events per exam). Inclusion of physiological activities as additional regressors in the GLM model demonstrated an increased Z-score and number of voxels of the global maxima and/or new BOLD clusters in around three quarters of the patients. Video-related fMRI maps for swallowing, mouth-tongue movements, and blinking were comparable to the ones obtained in previous task-based fMRI studies. Video acquisition during EEG-fMRI is a useful source of information. Modeling physiological movements in EEG-fMRI studies for epilepsy will lead to more informative IED-related fMRI maps in different epileptic conditions. Copyright © 2014 Elsevier B.V. All rights reserved.

The role of the standard EEG in clinical psychiatry.

LENUS (Irish Health Repository)

O'Sullivan, S S

2012-02-03

BACKGROUND: The EEG is a commonly requested test on patients attending psychiatric services, predominantly to investigate for a possible organic brain syndrome causing behavioural changes. AIMS: To assess referrals for EEG from psychiatric services in comparison with those from other sources. We determine which clinical factors were associated with an abnormal EEG in patients referred from psychiatric sources. METHODS: A retrospective review of EEG requests in a 1-year period was performed. Analysis of referral reasons for psychiatric patients was undertaken, and outcome of patients referred from psychiatric services post-EEG was reviewed. RESULTS: One thousand four hundred and seventy EEGs were reviewed, of which 91 (6.2%) were referred from psychiatry. Neurology service referrals had detection rates of abnormal EEGs of 27%, with psychiatric referrals having the lowest abnormality detection rate of 17.6% (p < 0.1). In psychiatric-referred patients the only significant predictors found of an abnormal EEG were a known history of epilepsy (p < 0.001), being on clozapine (p < 0.05), and a possible convulsive seizure (RR = 6.51). Follow-up data of 53 patients did not reveal a significant clinical impact of EEG results on patient management. CONCLUSIONS: Many patients are referred for EEG from psychiatric sources despite a relatively low index of suspicion of an organic brain disorders, based on reasons for referral documented, with an unsurprising low clinical yield.

The colorful brain: Visualization of EEG background patterns

NARCIS (Netherlands)

van Putten, Michel Johannes Antonius Maria

2008-01-01

This article presents a method to transform routine clinical EEG recordings to an alternative visual domain. The method is intended to support the classic visual interpretation of the EEG background pattern and to facilitate communication about relevant EEG characteristics. In addition, it provides

[EEG changes in symptomatic headache caused by bruxism].

Science.gov (United States)

Wieselmann, G; Grabmair, W; Logar, C; Permann, R; Moser, F

1987-02-20

EEG recordings were carried out on 36 patients with the verified diagnosis of bruxism and unilateral headache. Occlusal splints were applied in the long-term management of these patients. Initial EEG recordings showed pathological changes in 56% of the patients. The EEG recordings were repeated two and six weeks later in these patients and following improvement in the clinical symptomatology pathological EEG patterns were detected in only 22% of all cases. This decrease is of statistical significance.

Juvenile myoclonic epilepsy: clinical and EEG features

DEFF Research Database (Denmark)

Pedersen, S B; Petersen, K A

1998-01-01

We aimed to characterize the clinical profile and EEG features of 43 patients with juvenile myoclonic epilepsy. In a retrospective design we studied the records of, and re-interviewed, 43 patients diagnosed with JME from the epilepsy clinic data base. Furthermore, available EEGs were re...... were sleep deprivation (84%), stress (70%), and alcohol consumption (51%). EEG findings included rapid spike-wave and polyspike-wave....

Juvenile myoclonic epilepsy: clinical and EEG features

DEFF Research Database (Denmark)

Pedersen, S B; Petersen, K A

1998-01-01

We aimed to characterize the clinical profile and EEG features of 43 patients with juvenile myoclonic epilepsy. In a retrospective design we studied the records of, and re-interviewed, 43 patients diagnosed with JME from the epilepsy clinic data base. Furthermore, available EEGs were re-evaluated...... were sleep deprivation (84%), stress (70%), and alcohol consumption (51%). EEG findings included rapid spike-wave and polyspike-wave....

EEG Correlates of Ten Positive Emotions.

Science.gov (United States)

Hu, Xin; Yu, Jianwen; Song, Mengdi; Yu, Chun; Wang, Fei; Sun, Pei; Wang, Daifa; Zhang, Dan

2017-01-01

Compared with the well documented neurophysiological findings on negative emotions, much less is known about positive emotions. In the present study, we explored the EEG correlates of ten different positive emotions (joy, gratitude, serenity, interest, hope, pride, amusement, inspiration, awe, and love). A group of 20 participants were invited to watch 30 short film clips with their EEGs simultaneously recorded. Distinct topographical patterns for different positive emotions were found for the correlation coefficients between the subjective ratings on the ten positive emotions per film clip and the corresponding EEG spectral powers in different frequency bands. Based on the similarities of the participants' ratings on the ten positive emotions, these emotions were further clustered into three representative clusters, as 'encouragement' for awe, gratitude, hope, inspiration, pride, 'playfulness' for amusement, joy, interest, and 'harmony' for love, serenity. Using the EEG spectral powers as features, both the binary classification on the higher and lower ratings on these positive emotions and the binary classification between the three positive emotion clusters, achieved accuracies of approximately 80% and above. To our knowledge, our study provides the first piece of evidence on the EEG correlates of different positive emotions.

EEG patterns from acute to chronic stroke phases in focal cerebral ischemic rats: correlations with functional recovery.

Science.gov (United States)

Zhang, Shao-jie; Ke, Zheng; Li, Le; Yip, Shea-ping; Tong, Kai-yu

2013-04-01

Monitoring the neural activities from the ischemic penumbra provides critical information on neurological recovery after stroke. The purpose of this study is to evaluate the temporal alterations of neural activities using electroencephalography (EEG) from the acute phase to the chronic phase, and to compare EEG with the degree of post-stroke motor function recovery in a rat model of focal ischemic stroke. Male Sprague-Dawley rats were subjected to 90 min transient middle cerebral artery occlusion surgery followed by reperfusion for seven days (n = 58). The EEG signals were recorded at the pre-stroke phase (0 h), acute phase (3, 6 h), subacute phase (12, 24, 48, 72 h) and chronic phase (96, 120, 144, 168 h) (n = 8). This study analyzed post-stroke seizures and polymorphic delta activities (PDAs) and calculated quantitative EEG parameters such as the alpha-to-delta ratio (ADR). The ADR represented the ratio between alpha power and delta power, which indicated how fast the EEG activities were. Forelimb and hindlimb motor functions were measured by De Ryck's test and the beam walking test, respectively. In the acute phase, delta power increased fourfold with the occurrence of PDAs, and the histological staining showed that the infarct was limited to the striatum and secondary sensory cortex. In the subacute phase, the alpha power reduced to 50% of the baseline, and the infarct progressed to the forelimb cortical region. ADRs reduced from 0.23 ± 0.09 to 0.04 ± 0.01 at 3 h in the acute phase and gradually recovered to 0.22 ± 0.08 at 168 h in the chronic phase. In the comparison of correlations between the EEG parameters and the limb motor function from the acute phase to the chronic phase, ADRs were found to have the highest correlation coefficients with the beam walking test (r = 0.9524, p test (r = 0.8077, p < 0.05). This study measured EEG activities after focal cerebral ischemia and showed that functional recovery was closely correlated with the neural

EEG patterns from acute to chronic stroke phases in focal cerebral ischemic rats: correlations with functional recovery

International Nuclear Information System (INIS)

Zhang, Shao-jie; Ke, Zheng; Tong, Kai-yu; Li, Le; Yip, Shea-ping

2013-01-01

Monitoring the neural activities from the ischemic penumbra provides critical information on neurological recovery after stroke. The purpose of this study is to evaluate the temporal alterations of neural activities using electroencephalography (EEG) from the acute phase to the chronic phase, and to compare EEG with the degree of post-stroke motor function recovery in a rat model of focal ischemic stroke. Male Sprague–Dawley rats were subjected to 90 min transient middle cerebral artery occlusion surgery followed by reperfusion for seven days (n = 58). The EEG signals were recorded at the pre-stroke phase (0 h), acute phase (3, 6 h), subacute phase (12, 24, 48, 72 h) and chronic phase (96, 120, 144, 168 h) (n = 8). This study analyzed post-stroke seizures and polymorphic delta activities (PDAs) and calculated quantitative EEG parameters such as the alpha-to-delta ratio (ADR). The ADR represented the ratio between alpha power and delta power, which indicated how fast the EEG activities were. Forelimb and hindlimb motor functions were measured by De Ryck's test and the beam walking test, respectively. In the acute phase, delta power increased fourfold with the occurrence of PDAs, and the histological staining showed that the infarct was limited to the striatum and secondary sensory cortex. In the subacute phase, the alpha power reduced to 50% of the baseline, and the infarct progressed to the forelimb cortical region. ADRs reduced from 0.23 ± 0.09 to 0.04 ± 0.01 at 3 h in the acute phase and gradually recovered to 0.22 ± 0.08 at 168 h in the chronic phase. In the comparison of correlations between the EEG parameters and the limb motor function from the acute phase to the chronic phase, ADRs were found to have the highest correlation coefficients with the beam walking test (r = 0.9524, p < 0.05) and De Ryck's test (r = 0.8077, p < 0.05). This study measured EEG activities after focal cerebral ischemia and showed that functional recovery was closely

EEG (Electroencephalogram)

Science.gov (United States)

... in diagnosing brain disorders, especially epilepsy or another seizure disorder. An EEG might also be helpful for diagnosing ... Sometimes seizures are intentionally triggered in people with epilepsy during the test, but appropriate medical care is ...

Quantitative topographic differentiation of the neonatal EEG.

Science.gov (United States)

Paul, Karel; Krajca, Vladimír; Roth, Zdenek; Melichar, Jan; Petránek, Svojmil

2006-09-01

To test the discriminatory topographic potential of a new method of the automatic EEG analysis in neonates. A quantitative description of the neonatal EEG can contribute to the objective assessment of the functional state of the brain, and may improve the precision of diagnosing cerebral dysfunctions manifested by 'disorganization', 'dysrhythmia' or 'dysmaturity'. 21 healthy, full-term newborns were examined polygraphically during sleep (EEG-8 referential derivations, respiration, ECG, EOG, EMG). From each EEG record, two 5-min samples (one from the middle of quiet sleep, the other from the middle of active sleep) were subject to subsequent automatic analysis and were described by 13 variables: spectral features and features describing shape and variability of the signal. The data from individual infants were averaged and the number of variables was reduced by factor analysis. All factors identified by factor analysis were statistically significantly influenced by the location of derivation. A large number of statistically significant differences were also established when comparing the effects of individual derivations on each of the 13 measured variables. Both spectral features and features describing shape and variability of the signal are largely accountable for the topographic differentiation of the neonatal EEG. The presented method of the automatic EEG analysis is capable to assess the topographic characteristics of the neonatal EEG, and it is adequately sensitive and describes the neonatal electroencephalogram with sufficient precision. The discriminatory capability of the used method represents a promise for their application in the clinical practice.

Connectivity Measures in EEG Microstructural Sleep Elements.

Science.gov (United States)

Sakellariou, Dimitris; Koupparis, Andreas M; Kokkinos, Vasileios; Koutroumanidis, Michalis; Kostopoulos, George K

2016-01-01

During Non-Rapid Eye Movement sleep (NREM) the brain is relatively disconnected from the environment, while connectedness between brain areas is also decreased. Evidence indicates, that these dynamic connectivity changes are delivered by microstructural elements of sleep: short periods of environmental stimuli evaluation followed by sleep promoting procedures. The connectivity patterns of the latter, among other aspects of sleep microstructure, are still to be fully elucidated. We suggest here a methodology for the assessment and investigation of the connectivity patterns of EEG microstructural elements, such as sleep spindles. The methodology combines techniques in the preprocessing, estimation, error assessing and visualization of results levels in order to allow the detailed examination of the connectivity aspects (levels and directionality of information flow) over frequency and time with notable resolution, while dealing with the volume conduction and EEG reference assessment. The high temporal and frequency resolution of the methodology will allow the association between the microelements and the dynamically forming networks that characterize them, and consequently possibly reveal aspects of the EEG microstructure. The proposed methodology is initially tested on artificially generated signals for proof of concept and subsequently applied to real EEG recordings via a custom built MATLAB-based tool developed for such studies. Preliminary results from 843 fast sleep spindles recorded in whole night sleep of 5 healthy volunteers indicate a prevailing pattern of interactions between centroparietal and frontal regions. We demonstrate hereby, an opening to our knowledge attempt to estimate the scalp EEG connectivity that characterizes fast sleep spindles via an "EEG-element connectivity" methodology we propose. The application of the latter, via a computational tool we developed suggests it is able to investigate the connectivity patterns related to the occurrence

[Daytime tiredness correlated with nocturnal respiratory and arousal variables in patients with sleep apnea: polysomnographic and EEG mapping studies].

Science.gov (United States)

Saletu, M; Hauer, C; Anderer, P; Saletu-Zyhlarz, G; Gruber, G; Oberndorfer, S; Mandl, M; Popovic, R; Saletu, B

2000-03-24

There is evidence that daytime tiredness is caused by apnea/hypopnea with oxygen desaturation and/or by sleep fragmentation due to arousals. The aim of this study was to investigate objective and subjective sleep and awakening quality and daytime vigilance--objectified by midmorning mapping of vigilance-controlled EEG (V-EEG)--in sleep apnea patients (N: 18), as compared with age- and sex-matched normal controls (N: 18) as well as to correlate nocturnal respiratory distress and arousals to daytime brain function. Statistical analyses demonstrated a deterioration in subjective and objective sleep and awakening quality in apnea patients. Midmorning V-EEG mapping in apnea patients exhibited less total power, more delta and theta, less alpha and beta activity, as well as a slower dominant frequency and centroid of the total activity compared to controls, which suggests a vigilance decrement. The Spearman rank correlation between 6 polysomnographically registered respiratory variables and 36 diurnal quantitative EEG measures demonstrated the following: the higher the apnea, apnea-hypopnea, snoring and desaturation indices and the lower the minimum and average low oxygen saturation, the more pronounced was diurnal tiredness. Eleven arousal measures based on ASDA criteria showed the following significant correlations: the higher the nocturnal arousal index and the more arousals due to hypopneas, the greater was daytime tiredness. On the other hand, the greater the average frequency change during arousals and the more spontaneous arousals, the better was daytime vigilance. Our findings show that, in contrast to the lengthy Multiple Sleep Latency (MSLT) and Maintenance of Wakefulness (MWT) tests which evaluate sleep pressure under resting conditions conducive to sleep, V-EEG mapping provides a brief objective measure of a sleep apnea patient's daytime tiredness under conditions of wakefulness more appropriate to reflect the patient's everyday life.

Stimulus-dependent spiking relationships with the EEG

Science.gov (United States)

Snyder, Adam C.

2015-01-01

The development and refinement of noninvasive techniques for imaging neural activity is of paramount importance for human neuroscience. Currently, the most accessible and popular technique is electroencephalography (EEG). However, nearly all of what we know about the neural events that underlie EEG signals is based on inference, because of the dearth of studies that have simultaneously paired EEG recordings with direct recordings of single neurons. From the perspective of electrophysiologists there is growing interest in understanding how spiking activity coordinates with large-scale cortical networks. Evidence from recordings at both scales highlights that sensory neurons operate in very distinct states during spontaneous and visually evoked activity, which appear to form extremes in a continuum of coordination in neural networks. We hypothesized that individual neurons have idiosyncratic relationships to large-scale network activity indexed by EEG signals, owing to the neurons' distinct computational roles within the local circuitry. We tested this by recording neuronal populations in visual area V4 of rhesus macaques while we simultaneously recorded EEG. We found substantial heterogeneity in the timing and strength of spike-EEG relationships and that these relationships became more diverse during visual stimulation compared with the spontaneous state. The visual stimulus apparently shifts V4 neurons from a state in which they are relatively uniformly embedded in large-scale network activity to a state in which their distinct roles within the local population are more prominent, suggesting that the specific way in which individual neurons relate to EEG signals may hold clues regarding their computational roles. PMID:26108954

Quantitative EEG analysis using error reduction ratio-causality test; validation on simulated and real EEG data.

Science.gov (United States)

Sarrigiannis, Ptolemaios G; Zhao, Yifan; Wei, Hua-Liang; Billings, Stephen A; Fotheringham, Jayne; Hadjivassiliou, Marios

2014-01-01

To introduce a new method of quantitative EEG analysis in the time domain, the error reduction ratio (ERR)-causality test. To compare performance against cross-correlation and coherence with phase measures. A simulation example was used as a gold standard to assess the performance of ERR-causality, against cross-correlation and coherence. The methods were then applied to real EEG data. Analysis of both simulated and real EEG data demonstrates that ERR-causality successfully detects dynamically evolving changes between two signals, with very high time resolution, dependent on the sampling rate of the data. Our method can properly detect both linear and non-linear effects, encountered during analysis of focal and generalised seizures. We introduce a new quantitative EEG method of analysis. It detects real time levels of synchronisation in the linear and non-linear domains. It computes directionality of information flow with corresponding time lags. This novel dynamic real time EEG signal analysis unveils hidden neural network interactions with a very high time resolution. These interactions cannot be adequately resolved by the traditional methods of coherence and cross-correlation, which provide limited results in the presence of non-linear effects and lack fidelity for changes appearing over small periods of time. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

A technique to consider mismatches between fMRI and EEG/MEG sources for fMRI-constrained EEG/MEG source imaging: a preliminary simulation study

International Nuclear Information System (INIS)

Im, Chang-Hwan; Lee, Soo Yeol

2006-01-01

fMRI-constrained EEG/MEG source imaging can be a powerful tool in studying human brain functions with enhanced spatial and temporal resolutions. Recent studies on the combination of fMRI and EEG/MEG have suggested that fMRI prior information could be readily implemented by simply imposing different weighting factors to cortical sources overlapping with the fMRI activations. It has been also reported, however, that such a hard constraint may cause severe distortions or elimination of meaningful EEG/MEG sources when there are distinct mismatches between the fMRI activations and the EEG/MEG sources. If one wants to obtain the actual EEG/MEG source locations and uses the fMRI prior information as just an auxiliary tool to enhance focality of the distributed EEG/MEG sources, it is reasonable to weaken the strength of fMRI constraint when severe mismatches between fMRI and EEG/MEG sources are observed. The present study suggests an efficient technique to automatically adjust the strength of fMRI constraint according to the mismatch level. The use of the proposed technique rarely affects the results of conventional fMRI-constrained EEG/MEG source imaging if no major mismatch between the two modalities is detected; while the new results become similar to those of typical EEG/MEG source imaging without fMRI constraint if the mismatch level is significant. A preliminary simulation study using realistic EEG signals demonstrated that the proposed technique can be a promising tool to selectively apply fMRI prior information to EEG/MEG source imaging

Global Manufacturing Research: Experience Exchange Group (EEG) contributions

DEFF Research Database (Denmark)

Bruun, Peter

1998-01-01

of preliminary studies found interesting to set upan EEG composed of representatives from industry and a researcher. Inthe paper some general research methods pertinent to the areaindustrial management is discussed. The EEG concept is introduced andcharacterised in comparison with the other methods. EEG...... activities aredescribed and a tentative coupling to the phases in a research processis proposed. Following this is a discussion of methodological andquality requirements. It is considered how EEG activities couldpossible contribute to an industrial rooted research. The paper endsup looking at future research......The intention of this paper is to clarify if and how an ExperienceExchange Group (EEG) can be involved in a research process in the areaof industrial management. For exemplification of the topic an ongoingresearch in global manufacturing is referred to. In this research itwas after a series...

Standardized computer-based organized reporting of EEG:SCORE

DEFF Research Database (Denmark)

Beniczky, Sandor; H, Aurlien,; JC, Brøgger,

2013-01-01

process, organized by the European Chapter of the International Federation of Clinical Neurophysiology. The Standardised Computer-based Organised Reporting of EEG (SCORE) software was constructed based on the terms and features of the consensus statement and it was tested in the clinical practice...... in free-text format. The purpose of our endeavor was to create a computer-based system for EEG assessment and reporting, where the physicians would construct the reports by choosing from predefined elements for each relevant EEG feature, as well as the clinical phenomena (for video-EEG recordings....... SCORE can potentially improve the quality of EEG assessment and reporting; it will help incorporate the results of computer-assisted analysis into the report, it will make possible the build-up of a multinational database, and it will help in training young neurophysiologists....

Transfer function between EEG and BOLD signals of epileptic activity

Directory of Open Access Journals (Sweden)

Marco eLeite

2013-01-01

Full Text Available Simultaneous EEG-fMRI recordings have seen growing application in the evaluation of epilepsy, namely in the characterization of brain networks related to epileptic activity. In EEG-correlated fMRI studies, epileptic events are usually described as boxcar signals based on the timing information retrieved from the EEG, and subsequently convolved with a heamodynamic response function to model the associated BOLD changes. Although more flexible approaches may allow a higher degree of complexity for the haemodynamics, the issue of how to model these dynamics based on the EEG remains an open question. In this work, a new methodology for the integration of simultaneous EEG-fMRI data in epilepsy is proposed, which incorporates a transfer function from the EEG to the BOLD signal. Independent component analysis (ICA of the EEG is performed, and a number of metrics expressing different models of the EEG-BOLD transfer function are extracted from the resulting time courses. These metrics are then used to predict the fMRI data and to identify brain areas associated with the EEG epileptic activity. The methodology was tested on both ictal and interictal EEG-fMRI recordings from one patient with a hypothalamic hamartoma. When compared to the conventional analysis approach, plausible, consistent and more significant activations were obtained. Importantly, frequency-weighted EEG metrics yielded superior results than those weighted solely on the EEG power, which comes in agreement with previous literature. Reproducibility, specificity and sensitivity should be addressed in an extended group of patients in order to further validate the proposed methodology and generalize the presented proof of concept.

Automated approach to detecting behavioral states using EEG-DABS

Directory of Open Access Journals (Sweden)

Zachary B. Loris

2017-07-01

Full Text Available Electrocorticographic (ECoG signals represent cortical electrical dipoles generated by synchronous local field potentials that result from simultaneous firing of neurons at distinct frequencies (brain waves. Since different brain waves correlate to different behavioral states, ECoG signals presents a novel strategy to detect complex behaviors. We developed a program, EEG Detection Analysis for Behavioral States (EEG-DABS that advances Fast Fourier Transforms through ECoG signals time series, separating it into (user defined frequency bands and normalizes them to reduce variability. EEG-DABS determines events if segments of an experimental ECoG record have significantly different power bands than a selected control pattern of EEG. Events are identified at every epoch and frequency band and then are displayed as output graphs by the program. Certain patterns of events correspond to specific behaviors. Once a predetermined pattern was selected for a behavioral state, EEG-DABS correctly identified the desired behavioral event. The selection of frequency band combinations for detection of the behavior affects accuracy of the method. All instances of certain behaviors, such as freezing, were correctly identified from the event patterns generated with EEG-DABS. Detecting behaviors is typically achieved by visually discerning unique animal phenotypes, a process that is time consuming, unreliable, and subjective. EEG-DABS removes variability by using defined parameters of EEG/ECoG for a desired behavior over chronic recordings. EEG-DABS presents a simple and automated approach to quantify different behavioral states from ECoG signals.

Deep Neural Architectures for Mapping Scalp to Intracranial EEG.

Science.gov (United States)

Antoniades, Andreas; Spyrou, Loukianos; Martin-Lopez, David; Valentin, Antonio; Alarcon, Gonzalo; Sanei, Saeid; Took, Clive Cheong

2018-03-19

Data is often plagued by noise which encumbers machine learning of clinically useful biomarkers and electroencephalogram (EEG) data is no exemption. Intracranial EEG (iEEG) data enhances the training of deep learning models of the human brain, yet is often prohibitive due to the invasive recording process. A more convenient alternative is to record brain activity using scalp electrodes. However, the inherent noise associated with scalp EEG data often impedes the learning process of neural models, achieving substandard performance. Here, an ensemble deep learning architecture for nonlinearly mapping scalp to iEEG data is proposed. The proposed architecture exploits the information from a limited number of joint scalp-intracranial recording to establish a novel methodology for detecting the epileptic discharges from the sEEG of a general population of subjects. Statistical tests and qualitative analysis have revealed that the generated pseudo-intracranial data are highly correlated with the true intracranial data. This facilitated the detection of IEDs from the scalp recordings where such waveforms are not often visible. As a real-world clinical application, these pseudo-iEEGs are then used by a convolutional neural network for the automated classification of intracranial epileptic discharges (IEDs) and non-IED of trials in the context of epilepsy analysis. Although the aim of this work was to circumvent the unavailability of iEEG and the limitations of sEEG, we have achieved a classification accuracy of 68% an increase of 6% over the previously proposed linear regression mapping.

Data-driven forward model inference for EEG brain imaging

DEFF Research Database (Denmark)

Hansen, Sofie Therese; Hauberg, Søren; Hansen, Lars Kai

2016-01-01

Electroencephalography (EEG) is a flexible and accessible tool with excellent temporal resolution but with a spatial resolution hampered by volume conduction. Reconstruction of the cortical sources of measured EEG activity partly alleviates this problem and effectively turns EEG into a brain......-of-concept study, we show that, even when anatomical knowledge is unavailable, a suitable forward model can be estimated directly from the EEG. We propose a data-driven approach that provides a low-dimensional parametrization of head geometry and compartment conductivities, built using a corpus of forward models....... Combined with only a recorded EEG signal, we are able to estimate both the brain sources and a person-specific forward model by optimizing this parametrization. We thus not only solve an inverse problem, but also optimize over its specification. Our work demonstrates that personalized EEG brain imaging...

Thinner abuse alters peak of frequency of EEG spectra analyses El abuso de tíner altera el pico de frecuencia del análisis espectral del EEG

Directory of Open Access Journals (Sweden)

Adrián Poblano

2006-12-01

Full Text Available STUDY OBJECTIVE: The aim of the investigation was to use electroencephalography (EEG to study whether long-term thinner abuse may result in the slowing, disorganization and asymmetry of the EEG cortical rhythms. METHOD: Twenty-two patients attending with antecedent of thinner abuse only, and twenty two controls without alcohol, smoking, and drug abuse in the same age range and gender were studied. EEG recording were compared by means of the analyses of peak of frequency (POF, frequency of disorganization, and asymmetry of the background activity in patients and controls at rest eyes-closed condition in electrodes P3, P4, O1, and O2. RESULTS: Significant differences in POF among groups was observed in P3 and P4 location showing lower values in thinner abusers, but not in O1 and O2 locations. Frequencies of disorganization and asymmetry showed significantly higher proportions in thinner abusers. Bivariate correlations among POF at the four electrode location and time of thinner abuse showed significant values. However after partial correlation calculation correcting for age, significant values disappeared. CONCLUSION: Thus thinner abuse relates with slowing of POF in the EEG of patients with thinner abuse associated with disorganization, and asymmetry depending on time of abuse.OBJETIVO: Utilizar el electroencefalograma (EEG para estudiar si el abuso o intoxicación crónica por tíner produce lentificación, desorganización y asimetría de la actividad eléctrica cortical. MÉTODO: Se estudiaron 22 pacientes con antecedentes de intoxicación crónica por tíner y 22 sujetos sin antecedentes de abuso de tíner, alcohol, cigarro o drogas en el mismo rango de edad y en igual número de acuerdo al género. Se registro el EEG cuantitativo y se compararon: el promedio del pico de frecuencia (PoF, la frecuencia de desorganización de la actividad de fondo y la presencia de asimetría inter-hemisférica en la condición de reposo físico y mental entre

EEG-Informed fMRI: A Review of Data Analysis Methods

Science.gov (United States)

Abreu, Rodolfo; Leal, Alberto; Figueiredo, Patrícia

2018-01-01

The simultaneous acquisition of electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) is a very promising non-invasive technique for the study of human brain function. Despite continuous improvements, it remains a challenging technique, and a standard methodology for data analysis is yet to be established. Here we review the methodologies that are currently available to address the challenges at each step of the data analysis pipeline. We start by surveying methods for pre-processing both EEG and fMRI data. On the EEG side, we focus on the correction for several MR-induced artifacts, particularly the gradient and pulse artifacts, as well as other sources of EEG artifacts. On the fMRI side, we consider image artifacts induced by the presence of EEG hardware inside the MR scanner, and the contamination of the fMRI signal by physiological noise of non-neuronal origin, including a review of several approaches to model and remove it. We then provide an overview of the approaches specifically employed for the integration of EEG and fMRI when using EEG to predict the blood oxygenation level dependent (BOLD) fMRI signal, the so-called EEG-informed fMRI integration strategy, the most commonly used strategy in EEG-fMRI research. Finally, we systematically review methods used for the extraction of EEG features reflecting neuronal phenomena of interest. PMID:29467634

EEG-Informed fMRI: A Review of Data Analysis Methods

Directory of Open Access Journals (Sweden)

Rodolfo Abreu

2018-02-01

Full Text Available The simultaneous acquisition of electroencephalography (EEG with functional magnetic resonance imaging (fMRI is a very promising non-invasive technique for the study of human brain function. Despite continuous improvements, it remains a challenging technique, and a standard methodology for data analysis is yet to be established. Here we review the methodologies that are currently available to address the challenges at each step of the data analysis pipeline. We start by surveying methods for pre-processing both EEG and fMRI data. On the EEG side, we focus on the correction for several MR-induced artifacts, particularly the gradient and pulse artifacts, as well as other sources of EEG artifacts. On the fMRI side, we consider image artifacts induced by the presence of EEG hardware inside the MR scanner, and the contamination of the fMRI signal by physiological noise of non-neuronal origin, including a review of several approaches to model and remove it. We then provide an overview of the approaches specifically employed for the integration of EEG and fMRI when using EEG to predict the blood oxygenation level dependent (BOLD fMRI signal, the so-called EEG-informed fMRI integration strategy, the most commonly used strategy in EEG-fMRI research. Finally, we systematically review methods used for the extraction of EEG features reflecting neuronal phenomena of interest.

Caffeine reduces resting-state BOLD functional connectivity in the motor cortex.

Science.gov (United States)

Rack-Gomer, Anna Leigh; Liau, Joy; Liu, Thomas T

2009-05-15

In resting-state functional magnetic resonance imaging (fMRI), correlations between spontaneous low-frequency fluctuations in the blood oxygenation level dependent (BOLD) signal are used to assess functional connectivity between different brain regions. Changes in resting-state BOLD connectivity measures are typically interpreted as changes in coherent neural activity across spatially distinct brain regions. However, this interpretation can be complicated by the complex dependence of the BOLD signal on both neural and vascular factors. For example, prior studies have shown that vasoactive agents that alter baseline cerebral blood flow, such as caffeine and carbon dioxide, can significantly alter the amplitude and dynamics of the task-related BOLD response. In this study, we examined the effect of caffeine (200 mg dose) on resting-state BOLD connectivity in the motor cortex across a sample of healthy young subjects (N=9). We found that caffeine significantly (pcaffeine. These results suggest that caffeine usage should be carefully considered in the design and interpretation of resting-state BOLD fMRI studies.

Interrater variability of EEG interpretation in comatose cardiac arrest patients

DEFF Research Database (Denmark)

Westhall, Erik; Rosén, Ingmar; Rossetti, Andrea O

2015-01-01

OBJECTIVE: EEG is widely used to predict outcome in comatose cardiac arrest patients, but its value has been limited by lack of a uniform classification. We used the EEG terminology proposed by the American Clinical Neurophysiology Society (ACNS) to assess interrater variability in a cohort...... who were blinded for patient outcome. Percent agreement and kappa (κ) for the categories in the ACNS EEG terminology and for prespecified malignant EEG-patterns were calculated. RESULTS: There was substantial interrater agreement (κ 0.71) for highly malignant patterns and moderate agreement (κ 0.......42) for malignant patterns. Substantial agreement was found for malignant periodic or rhythmic patterns (κ 0.72) while agreement for identifying an unreactive EEG was fair (κ 0.26). CONCLUSIONS: The ACNS EEG terminology can be used to identify highly malignant EEG-patterns in post cardiac arrest patients...

Analyzing Electroencephalogram Signal Using EEG Lab

Directory of Open Access Journals (Sweden)

Mukesh BHARDWAJ

2009-01-01

Full Text Available The EEG is composed of electrical potentials arising from several sources. Each source (including separate neural clusters, blink artifact or pulse artifact forms a unique topography onto the scalp – ‘scalp map‘. Scalp map may be 2-D or 3-D.These maps are mixed according to the principle of linear superposition. Independent component analysis (ICA attempts to reverse the superposition by separating the EEG into mutually independent scalp maps, or components. MATLAB toolbox and graphic user interface, EEGLAB is used for processing EEG data of any number of channels. Wavelet toolbox has been used for 2-D signal analysis.

Resting state alpha frequency is associated with menstrual cycle phase, estradiol and use of oral contraceptives.

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Brötzner, Christina P; Klimesch, Wolfgang; Doppelmayr, Michael; Zauner, Andrea; Kerschbaum, Hubert H

2014-08-19

Ongoing intrinsic brain activity in resting, but awake humans is dominated by alpha oscillations. In human, individual alpha frequency (IAF) is associated with cognitive performance. Noticeable, performance in cognitive and emotional tasks in women is associated with menstrual cycle phase and sex hormone levels, respectively. In the present study, we correlated frequency of alpha oscillation in resting women with menstrual cycle phase, sex hormone level, or use of oral contraceptives. Electroencephalogram (EEG) was recorded from 57 women (aged 24.07 ± 3.67 years) having a natural menstrual cycle as well as from 57 women (aged 22.37 ± 2.20 years) using oral contraceptives while they sat in an armchair with eyes closed. Alpha frequency was related to the menstrual cycle phase. Luteal women showed highest and late follicular women showed lowest IAF or center frequency. Furthermore, IAF as well as center frequency correlated negatively with endogenous estradiol level, but did not reveal an association with endogenous progesterone. Women using oral contraceptives showed an alpha frequency similar to women in the early follicular phase. We suggest that endogenous estradiol modulate resting alpha frequency. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

A comparison of EEG spectral entropy with conventional quantitative ...

African Journals Online (AJOL)

A comparison of EEG spectral entropy with conventional quantitative EEG at varying depths of sevoflurane anaesthesia. PR Bartel, FJ Smith, PJ Becker. Abstract. Background and Aim: Recently an electroencephalographic (EEG) spectral entropy module (M-ENTROPY) for an anaesthetic monitor has become commercially ...

Neurophysiological features of Internet gaming disorder and alcohol use disorder: a resting-state EEG study.

Science.gov (United States)

Son, K-L; Choi, J-S; Lee, J; Park, S M; Lim, J-A; Lee, J Y; Kim, S N; Oh, S; Kim, D J; Kwon, J S

2015-09-01

Despite that Internet gaming disorder (IGD) shares clinical, neuropsychological and personality characteristics with alcohol use disorder (AUD), little is known about the resting-state quantitative electroencephalography (QEEG) patterns associated with IGD and AUD. Therefore, this study compared the QEEG patterns in patients with IGD with those in patients with AUD to identify unique neurophysiological characteristics that can be used as biomarkers of IGD. A total of 76 subjects (34 with IGD, 17 with AUD and 25 healthy controls) participated in this study. Resting-state, eyes-closed QEEGs were recorded, and the absolute and relative power of brains were analyzed. The generalized estimating equation showed that the IGD group had lower absolute beta power than AUD (estimate = 5.319, P < 0.01) and the healthy control group (estimate = 2.612, P = 0.01). The AUD group showed higher absolute delta power than IGD (estimate = 7.516, P < 0.01) and the healthy control group (estimate = 7.179, P < 0.01). We found no significant correlations between the severity of IGD and QEEG activities in patients with IGD. The current findings suggest that lower absolute beta power can be used as a potential trait marker of IGD. Higher absolute power in the delta band may be a susceptibility marker for AUD. This study clarifies the unique characteristics of IGD as a behavioral addiction, which is distinct from AUD, by providing neurophysiological evidence.

Predicting EEG complexity from sleep macro and microstructure

International Nuclear Information System (INIS)

Chouvarda, I; Maglaveras, N; Mendez, M O; Rosso, V; Parrino, L; Grassi, A; Terzano, M; Bianchi, A M; Cerutti, S

2011-01-01

This work investigates the relation between the complexity of electroencephalography (EEG) signal, as measured by fractal dimension (FD), and normal sleep structure in terms of its macrostructure and microstructure. Sleep features are defined, encoding sleep stage and cyclic alternating pattern (CAP) related information, both in short and long term. The relevance of each sleep feature to the EEG FD is investigated, and the most informative ones are depicted. In order to quantitatively assess the relation between sleep characteristics and EEG dynamics, a modeling approach is proposed which employs subsets of the sleep macrostructure and microstructure features as input variables and predicts EEG FD based on these features of sleep micro/macrostructure. Different sleep feature sets are investigated along with linear and nonlinear models. Findings suggest that the EEG FD time series is best predicted by a nonlinear support vector machine (SVM) model, employing both sleep stage/transitions and CAP features at different time scales depending on the EEG activation subtype. This combination of features suggests that short-term and long-term history of macro and micro sleep events interact in a complex manner toward generating the dynamics of sleep

Rett syndrome: EEG presentation.

Science.gov (United States)

Robertson, R; Langill, L; Wong, P K; Ho, H H

1988-11-01

Rett syndrome, a degenerative neurological disorder of girls, has a classical presentation and typical EEG findings. The electroencephalograms (EEGs) of 7 girls whose records have been followed from the onset of symptoms to the age of 5 or more are presented. These findings are tabulated with the Clinical Staging System of Hagberg and Witt-Engerström (1986). The records show a progressive deterioration in background rhythms in waking and sleep. The abnormalities of the background activity may only become evident at 4-5 years of age or during stage 2--the Rapid Destructive Stage. The marked contrast between waking and sleep background may not occur until stage 3--the Pseudostationary Stage. In essence EEG changes appear to lag behind clinical symptomatology by 1-3 years. An unexpected, but frequent, abnormality was central spikes seen in 5 of 7 girls. They appeared to be age related and could be evoked by tactile stimulation in 2 patients. We hypothesize that the prominent 'hand washing' mannerism may be self-stimulating and related to the appearance of central spike discharges.

EEG simulation by 2D interconnected chaotic oscillators

Energy Technology Data Exchange (ETDEWEB)

Kubany, Adam, E-mail: adamku@bgu.ac.i [Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, P.O. Box 653, Beer-Sheva 84105 (Israel); Mhabary, Ziv; Gontar, Vladimir [Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, P.O. Box 653, Beer-Sheva 84105 (Israel)

2011-01-15

Research highlights: ANN of 2D interconnected chaotic oscillators is explored for EEG simulation. An inverse problem solution (PRCGA) is proposed. Good matching between the simulated and experimental EEG signals has been achieved. - Abstract: An artificial neuronal network composed by 2D interconnected chaotic oscillators is explored for brain waves (EEG) simulation. For the inverse problem solution a parallel real-coded genetic algorithm (PRCGA) is proposed. In order to conduct thorough comparison between the simulated and target signal characteristics, a spectrum analysis of the signals is undertaken. A good matching between the theoretical and experimental EEG signals has been achieved. Numerical results of calculations are presented and discussed.

EEG simulation by 2D interconnected chaotic oscillators

International Nuclear Information System (INIS)

Kubany, Adam; Mhabary, Ziv; Gontar, Vladimir

2011-01-01

Research highlights: → ANN of 2D interconnected chaotic oscillators is explored for EEG simulation. → An inverse problem solution (PRCGA) is proposed. → Good matching between the simulated and experimental EEG signals has been achieved. - Abstract: An artificial neuronal network composed by 2D interconnected chaotic oscillators is explored for brain waves (EEG) simulation. For the inverse problem solution a parallel real-coded genetic algorithm (PRCGA) is proposed. In order to conduct thorough comparison between the simulated and target signal characteristics, a spectrum analysis of the signals is undertaken. A good matching between the theoretical and experimental EEG signals has been achieved. Numerical results of calculations are presented and discussed.

How Long Should Routine EEG Be Recorded to Get Relevant Information?

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Doudoux, Hannah; Skaare, Kristina; Geay, Thomas; Kahane, Philippe; Bosson, Jean L; Sabourdy, Cécile; Vercueil, Laurent

2017-03-01

The optimal duration of routine EEG (rEEG) has not been determined on a clinical basis. This study aims to determine the time required to obtain relevant information during rEEG with respect to the clinical request. All rEEGs performed over 3 months in unselected patients older than 14 years in an academic hospital were analyzed retrospectively. The latency required to obtain relevant information was determined for each rEEG by 2 independent readers blinded to the clinical data. EEG final diagnoses and latencies were analyzed with respect to the main clinical requests: subacute cognitive impairment, spells, transient focal neurologic manifestation or patients referred by epileptologists. From 430 rEEGs performed in the targeted period, 364 were analyzed: 92% of the pathological rEEGs were provided within the first 10 minutes of recording. Slowing background activity was diagnosed from the beginning, whereas interictal epileptiform discharges were recorded over time. Moreover, the time elapsed to demonstrate a pattern differed significantly in the clinical groups: in patients with subacute cognitive impairment, EEG abnormalities appeared within the first 10 minutes, whereas in the other groups, data could be provided over time. Patients with subacute cognitive impairment differed from those in the other groups significantly in the elapsed time required to obtain relevant information during rEEG, suggesting that 10-minute EEG recordings could be sufficient, arguing in favor of individualized rEEG. However, this conclusion does not apply to intensive care unit patients.

Sleep EEG of Microcephaly in Zika Outbreak.

Science.gov (United States)

Kanda, Paulo Afonso Medeiros; Aguiar, Aline de Almeida Xavier; Miranda, Jose Lucivan; Falcao, Alexandre Loverde; Andrade, Claudia Suenia; Reis, Luigi Neves Dos Santos; Almeida, Ellen White R Bacelar; Bello, Yanes Brum; Monfredinho, Arthur; Kanda, Rafael Guimaraes

2018-01-01

Microcephaly (MC), previously considered rare, is now a health emergency of international concern because of the devastating Zika virus pandemic outbreak of 2015. The authors describe the electroencephalogram (EEG) findings in sleep EEG of epileptic children who were born with microcephaly in areas of Brazil with active Zika virus transmission between 2014 and 2017. The authors reviewed EEGs from 23 children. Nine were females (39.2%), and the age distribution varied from 4 to 48 months. MC was associated with mother positive serology to toxoplasmosis (toxo), rubella (rub), herpes, and dengue (1 case); toxo (1 case); chikungunya virus (CHIKV) (1 case); syphilis (1 case); and Zika virus (ZIKV) (10 cases). In addition, 1 case was associated with perinatal hypoxia and causes of 9 cases remain unknown. The main background EEG abnormality was diffuse slowing (10 cases), followed by classic (3 cases) and modified (5 cases) hypsarrhythmia. A distinct EEG pattern was seen in ZIKV (5 cases), toxo (2 cases), and undetermined cause (1 case). It was characterized by runs of frontocentrotemporal 4.5-13 Hz activity (7 cases) or diffuse and bilateral runs of 18-24 Hz (1 case). In ZIKV, this rhythmic activity was associated with hypsarrhythmia or slow background. Further studies are necessary to determine if this association is suggestive of ZIKV infection. The authors believe that EEG should be included in the investigation of all newly diagnosed congenital MC, especially those occurring in areas of autochthonous transmission of ZIKV.

EEG-Annotate: Automated identification and labeling of events in continuous signals with applications to EEG.

Science.gov (United States)

Su, Kyung-Min; Hairston, W David; Robbins, Kay

2018-01-01

In controlled laboratory EEG experiments, researchers carefully mark events and analyze subject responses time-locked to these events. Unfortunately, such markers may not be available or may come with poor timing resolution for experiments conducted in less-controlled naturalistic environments. We present an integrated event-identification method for identifying particular responses that occur in unlabeled continuously recorded EEG signals based on information from recordings of other subjects potentially performing related tasks. We introduce the idea of timing slack and timing-tolerant performance measures to deal with jitter inherent in such non-time-locked systems. We have developed an implementation available as an open-source MATLAB toolbox (http://github.com/VisLab/EEG-Annotate) and have made test data available in a separate data note. We applied the method to identify visual presentation events (both target and non-target) in data from an unlabeled subject using labeled data from other subjects with good sensitivity and specificity. The method also identified actual visual presentation events in the data that were not previously marked in the experiment. Although the method uses traditional classifiers for initial stages, the problem of identifying events based on the presence of stereotypical EEG responses is the converse of the traditional stimulus-response paradigm and has not been addressed in its current form. In addition to identifying potential events in unlabeled or incompletely labeled EEG, these methods also allow researchers to investigate whether particular stereotypical neural responses are present in other circumstances. Timing-tolerance has the added benefit of accommodating inter- and intra- subject timing variations. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Highly Efficient Compression Algorithms for Multichannel EEG.

Science.gov (United States)

Shaw, Laxmi; Rahman, Daleef; Routray, Aurobinda

2018-05-01

The difficulty associated with processing and understanding the high dimensionality of electroencephalogram (EEG) data requires developing efficient and robust compression algorithms. In this paper, different lossless compression techniques of single and multichannel EEG data, including Huffman coding, arithmetic coding, Markov predictor, linear predictor, context-based error modeling, multivariate autoregression (MVAR), and a low complexity bivariate model have been examined and their performances have been compared. Furthermore, a high compression algorithm named general MVAR and a modified context-based error modeling for multichannel EEG have been proposed. The resulting compression algorithm produces a higher relative compression ratio of 70.64% on average compared with the existing methods, and in some cases, it goes up to 83.06%. The proposed methods are designed to compress a large amount of multichannel EEG data efficiently so that the data storage and transmission bandwidth can be effectively used. These methods have been validated using several experimental multichannel EEG recordings of different subjects and publicly available standard databases. The satisfactory parametric measures of these methods, namely percent-root-mean square distortion, peak signal-to-noise ratio, root-mean-square error, and cross correlation, show their superiority over the state-of-the-art compression methods.

Assessment of preconscious sucrose perception using EEG

DEFF Research Database (Denmark)

Rotvel, Camilla; Møller, Stine; Nielsen, Rene R

The objective of the current study is to develop a methodology for food ingredient screening based on Electro-Encephalo-Graphy (EEG). EEG measures electrical activity in the central nervous system, allowing assessment of activity in the ascending gustatory pathway from the taste buds on the tongue...... stimulus. The EEG was recorded using a 64 electrode setup, and gustatory evoked potentials (GEP) were estimated by coherent averaging across all 60 stimulations for each concentration. Cortical source localization based on the GEP was performed using a low resolution electromagnetic tomography (LORETA...

A Preliminary Study of Muscular Artifact Cancellation in Single-Channel EEG

OpenAIRE

Chen, Xun; Liu, Aiping; Peng, Hu; Ward, Rabab K.

2014-01-01

Electroencephalogram (EEG) recordings are often contaminated with muscular artifacts that strongly obscure the EEG signals and complicates their analysis. For the conventional case, where the EEG recordings are obtained simultaneously over many EEG channels, there exists a considerable range of methods for removing muscular artifacts. In recent years, there has been an increasing trend to use EEG information in ambulatory healthcare and related physiological signal monitoring systems. For pra...

Continuous EEG Monitoring in Aneurysmal Subarachnoid Hemorrhage

DEFF Research Database (Denmark)

Kondziella, Daniel; Friberg, Christian Kærsmose; Wellwood, Ian

2015-01-01

BACKGROUND: Continuous EEG (cEEG) may allow monitoring of patients with aneurysmal subarachnoid hemorrhage (SAH) for delayed cerebral ischemia (DCI) and seizures, including non-convulsive seizures (NCSz), and non-convulsive status epilepticus (NCSE). We aimed to evaluate: (a) the diagnostic...

A System for True and False Memory Prediction Based on 2D and 3D Educational Contents and EEG Brain Signals.

Science.gov (United States)

Bamatraf, Saeed; Hussain, Muhammad; Aboalsamh, Hatim; Qazi, Emad-Ul-Haq; Malik, Amir Saeed; Amin, Hafeez Ullah; Mathkour, Hassan; Muhammad, Ghulam; Imran, Hafiz Muhammad

2016-01-01

We studied the impact of 2D and 3D educational contents on learning and memory recall using electroencephalography (EEG) brain signals. For this purpose, we adopted a classification approach that predicts true and false memories in case of both short term memory (STM) and long term memory (LTM) and helps to decide whether there is a difference between the impact of 2D and 3D educational contents. In this approach, EEG brain signals are converted into topomaps and then discriminative features are extracted from them and finally support vector machine (SVM) which is employed to predict brain states. For data collection, half of sixty-eight healthy individuals watched the learning material in 2D format whereas the rest watched the same material in 3D format. After learning task, memory recall tasks were performed after 30 minutes (STM) and two months (LTM), and EEG signals were recorded. In case of STM, 97.5% prediction accuracy was achieved for 3D and 96.6% for 2D and, in case of LTM, it was 100% for both 2D and 3D. The statistical analysis of the results suggested that for learning and memory recall both 2D and 3D materials do not have much difference in case of STM and LTM.

Use Case Analysis: The Ambulatory EEG in Navy Medicine for Traumatic Brain Injuries

Science.gov (United States)

2016-12-01

science of binaural beats . Retrieved from http://binauralbrains.com/the-science-of- binaural - beats / Biosignal. (2016). MicroEEG. Retrieved from http...Cap. Source: Binaural Brains (n.d.). ....................................4  Figure 3.  EEG Machine. Source: Refine Medical Technology (n.d...EEG. Figures 2, 3, and 4 display images of a standard EEG cap, EEG machine, and an EEG recording. Figure 2. Standard EEG Cap. Source: Binaural Brains

Functional neural network analysis in frontotemporal dementia and Alzheimer's disease using EEG and graph theory

Directory of Open Access Journals (Sweden)

van der Flier Wiesje M

2009-08-01

Full Text Available Abstract Background Although a large body of knowledge about both brain structure and function has been gathered over the last decades, we still have a poor understanding of their exact relationship. Graph theory provides a method to study the relation between network structure and function, and its application to neuroscientific data is an emerging research field. We investigated topological changes in large-scale functional brain networks in patients with Alzheimer's disease (AD and frontotemporal lobar degeneration (FTLD by means of graph theoretical analysis of resting-state EEG recordings. EEGs of 20 patients with mild to moderate AD, 15 FTLD patients, and 23 non-demented individuals were recorded in an eyes-closed resting-state. The synchronization likelihood (SL, a measure of functional connectivity, was calculated for each sensor pair in 0.5–4 Hz, 4–8 Hz, 8–10 Hz, 10–13 Hz, 13–30 Hz and 30–45 Hz frequency bands. The resulting connectivity matrices were converted to unweighted graphs, whose structure was characterized with several measures: mean clustering coefficient (local connectivity, characteristic path length (global connectivity and degree correlation (network 'assortativity'. All results were normalized for network size and compared with random control networks. Results In AD, the clustering coefficient decreased in the lower alpha and beta bands (p Conclusion With decreasing local and global connectivity parameters, the large-scale functional brain network organization in AD deviates from the optimal 'small-world' network structure towards a more 'random' type. This is associated with less efficient information exchange between brain areas, supporting the disconnection hypothesis of AD. Surprisingly, FTLD patients show changes in the opposite direction, towards a (perhaps excessively more 'ordered' network structure, possibly reflecting a different underlying pathophysiological process.

Increasing Performance of Professional Soccer Players and Elite Track and Field Athletes with Peak Performance Training and Biofeedback: A Pilot Study.

Science.gov (United States)

Rijken, Noortje H; Soer, Remko; de Maar, Ewold; Prins, Hilco; Teeuw, Wouter B; Peuscher, Jan; Oosterveld, Frits G J

2016-12-01

The aim of this pilot study was to investigate the effects of an intervention consisting of mental coaching combined with either electro encephalogram (EEG) alpha power feedback or heart rate variability (HRV) feedback on HRV, EEG outcomes and self-reported factors related to stress, performance, recovery and sleep quality in elite athletes. A prospective pilot study was performed with two distinct cohorts. Soccer players were provided with four sessions of mental coaching combined with daily HRV biofeedback (Group A); track and field athletes were provided with four sessions of mental coaching in combination with daily neurofeedback (Group B). Measurements were performed at baseline, post intervention and at 5 weeks follow-up. Objective measures: EEG and ECG. Subjective measures: Numeric Rating Scale for performance, Pittsburgh Sleep Quality Index, Rest and Stress Questionnaire and Sports Improvement-60. Group characteristics were too distinct to compare the interventions. Linear mixed models were used to analyze differences within groups over time. In Group A, significant changes over time were present in alpha power at 5 of 7 EEG locations (p HRV low frequency power and recovery scale of the REST-Q significantly increased (p = 0.02 and HRV or EEG alpha power feedback may increase HRV and alpha power and may lead to better performance-related outcomes and stress reduction. Further research is needed to elucidate the effects of either type of feedback and to compare effects with a control group.

Correlation between intra- and extracranial background EEG

DEFF Research Database (Denmark)

Duun-Henriksen, Jonas; Kjaer, Troels W.; Madsen, Rasmus E.

2012-01-01

Scalp EEG is the most widely used modality to record the electrical signals of the brain. It is well known that the volume conduction of these brain waves through the brain, cerebrospinal fluid, skull and scalp reduces the spatial resolution and the signal amplitude. So far the volume conduction...... has primarily been investigated by realistic head models or interictal spike analysis. We have set up a novel and more realistic experiment that made it possible to compare the information in the intra- and extracranial EEG. We found that intracranial EEG channels contained correlated patterns when...... placed less than 30 mm apart, that intra- and extracranial channels were partly correlated when placed less than 40 mm apart, and that extracranial channels probably were correlated over larger distances. The underlying cortical area that influences the extracranial EEG is found to be up to 45 cm2...

Brain dynamics of post-task resting state are influenced by expertise: Insights from baseball players.

Science.gov (United States)

Muraskin, Jordan; Dodhia, Sonam; Lieberman, Gregory; Garcia, Javier O; Verstynen, Timothy; Vettel, Jean M; Sherwin, Jason; Sajda, Paul

2016-12-01

Post-task resting state dynamics can be viewed as a task-driven state where behavioral performance is improved through endogenous, non-explicit learning. Tasks that have intrinsic value for individuals are hypothesized to produce post-task resting state dynamics that promote learning. We measured simultaneous fMRI/EEG and DTI in Division-1 collegiate baseball players and compared to a group of controls, examining differences in both functional and structural connectivity. Participants performed a surrogate baseball pitch Go/No-Go task before a resting state scan, and we compared post-task resting state connectivity using a seed-based analysis from the supplementary motor area (SMA), an area whose activity discriminated players and controls in our previous results using this task. Although both groups were equally trained on the task, the experts showed differential activity in their post-task resting state consistent with motor learning. Specifically, we found (1) differences in bilateral SMA-L Insula functional connectivity between experts and controls that may reflect group differences in motor learning, (2) differences in BOLD-alpha oscillation correlations between groups suggests variability in modulatory attention in the post-task state, and (3) group differences between BOLD-beta oscillations that may indicate cognitive processing of motor inhibition. Structural connectivity analysis identified group differences in portions of the functionally derived network, suggesting that functional differences may also partially arise from variability in the underlying white matter pathways. Generally, we find that brain dynamics in the post-task resting state differ as a function of subject expertise and potentially result from differences in both functional and structural connectivity. Hum Brain Mapp 37:4454-4471, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals

EEG datasets for motor imagery brain-computer interface.

Science.gov (United States)

Cho, Hohyun; Ahn, Minkyu; Ahn, Sangtae; Kwon, Moonyoung; Jun, Sung Chan

2017-07-01

Most investigators of brain-computer interface (BCI) research believe that BCI can be achieved through induced neuronal activity from the cortex, but not by evoked neuronal activity. Motor imagery (MI)-based BCI is one of the standard concepts of BCI, in that the user can generate induced activity by imagining motor movements. However, variations in performance over sessions and subjects are too severe to overcome easily; therefore, a basic understanding and investigation of BCI performance variation is necessary to find critical evidence of performance variation. Here we present not only EEG datasets for MI BCI from 52 subjects, but also the results of a psychological and physiological questionnaire, EMG datasets, the locations of 3D EEG electrodes, and EEGs for non-task-related states. We validated our EEG datasets by using the percentage of bad trials, event-related desynchronization/synchronization (ERD/ERS) analysis, and classification analysis. After conventional rejection of bad trials, we showed contralateral ERD and ipsilateral ERS in the somatosensory area, which are well-known patterns of MI. Finally, we showed that 73.08% of datasets (38 subjects) included reasonably discriminative information. Our EEG datasets included the information necessary to determine statistical significance; they consisted of well-discriminated datasets (38 subjects) and less-discriminative datasets. These may provide researchers with opportunities to investigate human factors related to MI BCI performance variation, and may also achieve subject-to-subject transfer by using metadata, including a questionnaire, EEG coordinates, and EEGs for non-task-related states. © The Authors 2017. Published by Oxford University Press.

Filtration of human EEG recordings from physiological artifacts with empirical mode method

Science.gov (United States)

Grubov, Vadim V.; Runnova, Anastasiya E.; Khramova, Marina V.

2017-03-01

In the paper we propose the new method for dealing with noise and physiological artifacts in experimental human EEG recordings. The method is based on analysis of EEG signals with empirical mode decomposition (Hilbert-Huang transform). We consider noises and physiological artifacts on EEG as specific oscillatory patterns that cause problems during EEG analysis and can be detected with additional signals recorded simultaneously with EEG (ECG, EMG, EOG, etc.) We introduce the algorithm of the method with following steps: empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing empirical modes with artifacts, reconstruction of the initial EEG signal. We test the method on filtration of experimental human EEG signals from eye-moving artifacts and show high efficiency of the method.

A STUDY ON EEG ABNORMALITIES IN CHILDREN WITH MIGRAINE

Directory of Open Access Journals (Sweden)

Subinay Mandal

2017-04-01

Full Text Available BACKGROUND Migraine is one of the common causes of headache in children. Migraine and epilepsy are both common episodic neurological disorders. The comorbidity of these two conditions is well known. Many researcher have pointed out that neuronal hyperexcitability is the initiating event for occurrence of migraine attack. The aim of the paper was to evaluate the EEG in children with migraine. MATERIALS AND METHODS We retrospectively analysed records of children who attended our paediatric outpatient department with diagnoses as suffering from migraine based on International Headache Society (IHS diagnostic criteria. Apart from detailed clinical history, EEG of every patient was collected and analysed. EEG was performed interictally at least 24 hours after the last episode of headache attack in all the cases. RESULTS 56 children (age range, 4-14 years constituted our study group. 64.3% children had migraine without aura (common type and in 23.2% cases had migraine with aura (classic type other were with migraine variants. Abnormal EEG was reported in 30.3% children. 17% of children with migraine without history of seizure had abnormal EEG. Sixty one percent of patients with aura had abnormal EEG. History of either febrile fits or afebrile fits was present in total 17.1% of cases. The type of paroxysmal discharges we came across was- a Sharp waves, b Spikes and c Spike and slow wave complexes. Abnormal paroxysmal sharp and spike-wave complexes (also called spike-and-slow-wave complexes were the most common EEG abnormality. CONCLUSION EEG abnormality was found in significant number of children with migraine both with and without history of seizure in our study. This indicates neuronal hyperexcitability during episodes of migraine. So, EEG should be considered in patients with clinical diagnoses of migraine to exclude association of any seizure activity.

[EEG-markers of vertical postural organization in healthy persons].

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Zhavoronkova, L A; Zharikova, A V; Kushnir, E M; Mikhalkova, A A

2012-01-01

In 10 healthy persons (22.8 +/- 0.67 years) spectral-coherence parameters of EEG were analyzed in different steps of verticalizations--from gorizontal position to seat and stand one. Maximal changes of all EEG parameters were observed in state with absence of visual control. We observed an increase of power for fast spectral bands of EEG (beta- and gamma-bands) in all conditions and additional increase of these EEG parameters was observed at situation of complication of conditions of vertical pose supporting. Results of EEG coherent analysis in conditions of human verticalization showed specific increase of coherence for the majority of rhythm ranges in the right hemisphere especially in the central-frontal and in occipital-parietal areas and for interhemispheric pairs for these leads. This fact can reflect participation of cortical as well as subcortical structures in these processes. In conditions of complicate conditions of vertical pose supporting the additional increase of EEG coherence in fast bands (beta-rhythm) was observed at the frontal areas. This fact can testify about increasing of executive functions in this conditions.

Long-Term Evolution Electromagnetic Fields Exposure Modulates the Resting State EEG on Alpha and Beta Bands.

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Yang, Lei; Chen, Qinghua; Lv, Bin; Wu, Tongning

2017-05-01

Long-term evolution (LTE) wireless telecommunication systems are widely used globally, which has raised a concern that exposure to electromagnetic fields (EMF) emitted from LTE devices can change human neural function. To date, few studies have been conducted on the effect of exposure to LTE EMF. Here, we evaluated the changes in electroencephalogram (EEG) due to LTE EMF exposure. An LTE EMF exposure system with a stable power emission, which was equivalent to the maximum emission from an LTE mobile phone, was used to radiate the subjects. Numerical simulations were conducted to ensure that the specific absorption rate in the subject's head was below the safety limits. Exposure to LTE EMF reduced the spectral power and the interhemispheric coherence in the alpha and beta bands of the frontal and temporal brain regions. No significant change was observed in the spectral power and the inter-hemispheric coherence in different timeslots during and after the exposure. These findings also corroborated those of our previous study using functional magnetic resonant imaging.

Effects of oral amines on the EEG.

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Scott, D F; Moffett, A M; Swash, M

1977-02-01

Oral tyramine activated pre-existing episodic EEG abnormalities--namely, sharp waves, spike and wave, and localised theta activity--in epileptic patients. Little change was found in the EEGs of migrainous subjects after chocolate or beta-phenylethylamine. The implications of the findings with tyramine are discussed.

Changes of hypnagogic imagery and EEG stages

OpenAIRE

Hayashi, Mitsuo; Katoh, Kohichi; Hori, Tadao

1998-01-01

The aim of this study is to investigate the relationships between hypnagogic imagery and EEG stages. According to Hori, et al. (1994), the hypnagogic EEGs was classified into 9 stages, those were 1) alpha wave train, 2) alpha wave intermittent (>50%), 3) alpha wave intermittent (

Standardized computer-based organized reporting of EEG SCORE - Second version

DEFF Research Database (Denmark)

Beniczky, Sándor; Aurlien, Harald; Brøgger, Jan C

2017-01-01

Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted in the se......Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted...... in the second, revised version of SCORE (Standardized Computer-based Organized Reporting of EEG), which is presented in this paper. The revised terminology was implemented in a software package (SCORE EEG), which was tested in clinical practice on 12,160 EEG recordings. Standardized terms implemented in SCORE....... In the end, the diagnostic significance is scored, using a standardized list of terms. SCORE has specific modules for scoring seizures (including seizure semiology and ictal EEG patterns), neonatal recordings (including features specific for this age group), and for Critical Care EEG Terminology. SCORE...

Application of a novel measure of EEG non-stationarity as 'Shannon- entropy of the peak frequency shifting' for detecting residual abnormalities in concussed individuals.

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Cao, Cheng; Slobounov, Semyon

2011-07-01

The aim of this report was to propose a novel measure of non-stationarity of EEG signals, named Shannon- entropy of the peak frequency shifting (SEPFS). The feasibility of this method was documented comparing this measure with traditional time domain assessment of non-stationarity and its application to EEG data sets obtained from student-athletes before and after suffering a single episode of mild traumatic brain injury (mTBI) with age-matched normal controls. Instead of assessing the power density distribution on the time-frequency plane, like previously proposed measures of signal non-stationarity, this new measure is based on the shift of the dominant frequency of the EEG signal over time. We applied SEPFS measure to assess the properties of EEG non-stationarity in subjects before and shortly after they suffered mTBI. Student-athletes at high risk for mTBI (n=265) were tested prior to concussive episodes as a baseline. From this subject pool, 30 athletes who suffered from mTBI were retested on day 30 post-injury. Additional subjects pool (student-athletes without history of concussion, n=30) were recruited and test-re-tested within the same 30 day interval. Thirty-two channels EEG signals were acquired in sitting eyes closed condition. The results showed that the SEPFS values significantly decreased in subjects suffering from mTBI. Specifically, reduced EEG non-stationarity was observed in occipital, temporal and central brain areas, indicating the possibility of residual brain dysfunctions in concussed individuals. A similar but less statistically significant trend was observed using traditional time domain analysis of EEG non-stationarity. The proposed measure has at least two merits of interest: (1) it is less affected by the limited resolution of time-frequency representation of the EEG signal; (2) it takes into account the neural characteristics of the EEG signal that have not been considered in previously proposed measures of non-stationarity. This new

Three-dimensional components of selfhood in treatment-naive patients with major depressive disorder: A resting-state qEEG imaging study.

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Fingelkurts, Andrew A; Fingelkurts, Alexander A

2017-05-01

Based on previous studies implicating increased functional connectivity within the self-referential brain network in major depressive disorder (MDD), and considering the functional roles of three distinct modules of such brain net (responsible for three-dimensional components of Selfhood) together with the documented abnormalities of self-related processing in MDD, we tested the hypothesis that patients with depression would exhibit increased connectivity within each module of the self-referential brain network and that the strength of these connections would correlate positively with depression severity. Applying the electroencephalogram (EEG) operational synchrony analysis to extract three modules of the self-referential brain network in 12 medication-free depressive outpatients and 10 control subjects we have found an increase in the strength of EEG synchrony within all three modules in depressive patients (though non-significant for the right module). Furthermore, multiple regression analysis that used 3 factors (values of synchrony strength for all three modules) as input indicated that combined increase in the strength of synchrony in all three modules was positively associated with severity of depression. Taken together the findings of this study suggest that depression is primarily associated with hypersynchrony in all three modules of the brain self-referential network (the anterior module been responsible for "witnessing observation and first-person perspective", the left posterior module been responsible for "reflective agency and narration" and the right posterior module been responsible for "bodily representational-emotional agency"), thus contributing to excessive self-focus, rumination, and body tension. Copyright © 2017 Elsevier Ltd. All rights reserved.

Diagnostic Role of ECG Recording Simultaneously With EEG Testing.

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Kendirli, Mustafa Tansel; Aparci, Mustafa; Kendirli, Nurten; Tekeli, Hakan; Karaoglan, Mustafa; Senol, Mehmet Guney; Togrol, Erdem

2015-07-01

Arrhythmia is not uncommon in the etiology of syncope which mimics epilepsy. Data about the epilepsy induced vagal tonus abnormalities have being increasingly reported. So we aimed to evaluate what a neurologist may gain by a simultaneous electrocardiogram (ECG) and electroencephalogram (EEG) recording in the patients who underwent EEG testing due to prediagnosis of epilepsy. We retrospectively evaluated and detected ECG abnormalities in 68 (18%) of 376 patients who underwent EEG testing. A minimum of 20 of minutes artifact-free recording were required for each patient. Standard 1-channel ECG was simultaneously recorded in conjunction with the EEG. In all, 28% of females and 14% of males had ECG abnormalities. Females (mean age 49 years, range 18-88 years) were older compared with the male group (mean age 28 years, range 16-83 years). Atrial fibrillation was more frequent in female group whereas bradycardia and respiratory sinus arrhythmia was higher in male group. One case had been detected a critical asystole indicating sick sinus syndrome in the female group and treated with a pacemaker implantation in the following period. Simultaneous ECG recording in conjunction with EEG testing is a clinical prerequisite to detect and to clarify the coexisting ECG and EEG abnormalities and their clinical relevance. Potentially rare lethal causes of syncope that mimic seizure or those that could cause resistance to antiepileptic therapy could effectively be distinguished by detecting ECG abnormalities coinciding with the signs and abnormalities during EEG recording. © EEG and Clinical Neuroscience Society (ECNS) 2014.

EEG feature selection method based on decision tree.

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Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

Temporal Courses in EEG Theta and Alpha Activity in the Dynamic Health Qigong Techniques Wu Qin Xi and Liu Zi Jue

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Diana Henz

2018-01-01

Full Text Available Health Qigong is a common technique of Traditional Chinese Medicine applied to strengthen mental and physical health. Several studies report increases in EEG theta and alpha activity after meditative Qigong techniques indicating a relaxed state of mind. To date, little is known on the effects of dynamic Health Qigong techniques that comprise bodily movements on brain activity. In the current study, we compared effects of two dynamic Health Qigong techniques on EEG brain activity. Subjects performed the techniques Wu Qin Xi (five animals play and Liu Zi Jue (six healing sounds in a within-subjects design. Eyes-open and eyes-closed resting EEG was recorded before and immediately after each 15-min practice block. Additionally, the Profile of Mood States (POMS questionnaire was administered at pretest, and after each 15-min practice block. Results show a decrease in alpha activity after 15 min, followed by an increase after 30 min in the Health Qigong technique Liu Zi Jue. Theta activity was decreased after 15 min, followed by an increase after 30 min in the technique Wu Qin Xi. Results of the POMS indicated an increased vigor-activity level with decreased fatigue and tension-anxiety levels in both techniques after 30 min of practice. Our results demonstrate different temporal dynamics in EEG theta and alpha activity for the Health Qigong techniques Wu Qin Xi and Liu Zi Jue. We hypothesize that the found brain activation patterns result from different attentional focusing styles and breathing techniques performed during the investigated Health Qigong techniques.

Effects of deep brain stimulation on rest tremor progression in early stage Parkinson disease.

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Hacker, Mallory L; DeLong, Mahlon R; Turchan, Maxim; Heusinkveld, Lauren E; Ostrem, Jill L; Molinari, Anna L; Currie, Amanda D; Konrad, Peter E; Davis, Thomas L; Phibbs, Fenna T; Hedera, Peter; Cannard, Kevin R; Drye, Lea T; Sternberg, Alice L; Shade, David M; Tonascia, James; Charles, David

2018-06-29

To evaluate whether the progression of individual motor features was influenced by early deep brain stimulation (DBS), a post hoc analysis of Unified Parkinson's Disease Rating Scale-III (UPDRS-III) score (after a 7-day washout) was conducted from the 2-year DBS in early Parkinson disease (PD) pilot trial dataset. The prospective pilot trial enrolled patients with PD aged 50-75 years, treated with PD medications for 6 months-4 years, and no history of dyskinesia or other motor fluctuations, who were randomized to receive optimal drug therapy (ODT) or DBS plus ODT (DBS + ODT). At baseline and 6, 12, 18, and 24 months, all patients stopped all PD therapy for 1 week (medication and stimulation, if applicable). UPDRS-III "off" item scores were compared between the ODT and DBS + ODT groups (n = 28); items with significant between-group differences were analyzed further. UPDRS-III "off" rest tremor score change from baseline to 24 months was worse in patients receiving ODT vs DBS + ODT ( p = 0.002). Rest tremor slopes from baseline to 24 months favored DBS + ODT both "off" and "on" therapy ( p will be tested in the Food and Drug Administration-approved, phase III, pivotal, multicenter clinical trial evaluating DBS in early PD. This study provides Class II evidence that for patients with early PD, DBS may slow the progression of rest tremor. © 2018 American Academy of Neurology.

Avoidance-related EEG asymmetry predicts circulating interleukin-6.

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Shields, Grant S; Moons, Wesley G

2016-03-01

Recent research has linked avoidance-oriented motivational states to elevated pro-inflammatory cytokine levels. According to one of many theories regarding the association between avoidance and cytokine levels, because the evolutionarily basic avoidance system may be activated when an organism is threatened or overwhelmed, an associated inflammatory response may be adaptive for dealing with potential injury in such threatening situations. To examine this hypothesis, we tested whether the neural correlate of avoidance motivation associates with baseline levels of the circulating pro-inflammatory cytokine interleukin-6 (IL-6). Controlling for covariates, greater resting neural activity in the right frontal cortex relative to the left frontal cortex-the neural correlate of avoidance motivation-was associated with baseline IL-6. These results thus support the hypothesis that the avoidance motivational system may be closely linked to systemic inflammatory activity. (c) 2016 APA, all rights reserved).

Acute effects of caffeine on threat-selective attention: moderation by anxiety and EEG theta/beta ratio.

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van Son, Dana; Schalbroeck, Rik; Angelidis, Angelos; van der Wee, Nic J A; van der Does, Willem; Putman, Peter

2018-05-21

Spontaneous EEG theta/beta ratio (TBR) probably marks prefrontal cortical (PFC) executive control, and its regulation of attentional threat-bias. Caffeine at moderate doses may strengthen executive control through increased PFC catecholamine action, dependent on basal PFC function. To test if caffeine affects threat-bias, moderated by baseline frontal TBR and trait-anxiety. A pictorial emotional Stroop task was used to assess threat-bias in forty female participants in a cross-over, double-blind study after placebo and 200 mg caffeine. At baseline and after placebo, comparable relations were observed for negative pictures: high TBR was related to low threat-bias in low trait-anxious people. Caffeine had opposite effects on threat-bias in low trait-anxious people with low and high TBR. This further supports TBR as a marker of executive control and highlights the importance of taking baseline executive function into consideration when studying effects of caffeine on executive functions. Copyright © 2018 Elsevier B.V. All rights reserved.

Synchronization of EEG activity in patients with bipolar disorder

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Panischev, O. Yu; Demin, S. A.; Muhametshin, I. G.; Demina, N. Yu

2015-12-01

In paper we apply the method based on the Flicker-Noise Spectroscopy (FNS) to determine the differences in frequency-phase synchronization of the cortical electroencephalographic (EEG) activities in patients with bipolar disorder (BD). We found that for healthy subjects the frequency-phase synchronization of EEGs from long-range electrodes was significantly better for BD patients. In BD patients a high synchronization of EEGs was observed only for short-range electrodes. Thus, the FNS is a simple graphical method for qualitative analysis can be applied to identify the synchronization effects in EEG activity and, probably, may be used for the diagnosis of this syndrome.

Analysis of correlation between white matter changes and functional responses in thalamic stroke: a DTI & EEG study.

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Duru, Adil Deniz; Duru, Dilek Göksel; Yumerhodzha, Sami; Bebek, Nerses

2016-06-01

Diffusion tensor imaging (DTI) allows in vivo structural brain mapping and detection of microstructural disruption of white matter (WM). One of the commonly used parameters for grading the anisotropic diffusivity in WM is fractional anisotropy (FA). FA value helps to quantify the directionality of the local tract bundle. Therefore, FA images are being used in voxelwise statistical analyses (VSA). The present study used Tract-Based Spatial Statistics (TBSS) of FA images across subjects, and computes the mean skeleton map to detect voxelwise knowledge of the tracts yielding to groupwise comparison. The skeleton image illustrates WM structure and shows any changes caused by brain damage. The microstructure of WM in thalamic stroke is investigated, and the VSA results of healthy control and thalamic stroke patients are reported. It has been shown that several skeleton regions were affected subject to the presence of thalamic stroke (FWE, p EEG (qEEG) scores and neurophysiological tests with the FA skeleton for the entire test group is also investigated. We compared measurements that are related to the same fibers across subjects, and discussed implications for VSA of WM in thalamic stroke cases, for the relationship between behavioral tests and FA skeletons, and for the correlation between the FA maps and qEEG scores.Results obtained through the regression analyses did not exceed the corrected statistical threshold values for multiple comparisons (uncorrected, p EEG, cingulum bundle and corpus callosum were found to be related. These areas are parts of the Default Mode Network (DMN) where DMN is known to be involved in resting state EEG theta activity. The relation between the EEG alpha band power values and FA values of the skeleton was found to support the cortico-thalamocortical cycles for both subject groups. Further, the neurophysiological tests including Benton Face Recognition (BFR), Digit Span test (DST), Warrington Topographic Memory test (WTMT

Safety and EEG data quality of concurrent high-density EEG and high-speed fMRI at 3 Tesla

DEFF Research Database (Denmark)

Foged, Mette Thrane; Lindberg, Ulrich; Vakamudi, Kishore

2017-01-01

) related heating, the effect of EEG on cortical signal-to-noise ratio (SNR) in fMRI, and assess EEG data quality. MATERIALS AND METHODS: The study compared EPI, multi-echo EPI, multi-band EPI and multi-slab echo-volumar imaging pulse sequences, using clinical 3 Tesla MR scanners from two different vendors...

Singular spectrum analysis of sleep EEG in insomnia.

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Aydın, Serap; Saraoǧlu, Hamdi Melih; Kara, Sadık

2011-08-01

In the present study, the Singular Spectrum Analysis (SSA) is applied to sleep EEG segments collected from healthy volunteers and patients diagnosed by either psycho physiological insomnia or paradoxical insomnia. Then, the resulting singular spectra computed for both C3 and C4 recordings are assigned as the features to the Artificial Neural Network (ANN) architectures for EEG classification in diagnose. In tests, singular spectrum of particular sleep stages such as awake, REM, stage1 and stage2, are considered. Three clinical groups are successfully classified by using one hidden layer ANN architecture with respect to their singular spectra. The results show that the SSA can be applied to sleep EEG series to support the clinical findings in insomnia if ten trials are available for the specific sleep stages. In conclusion, the SSA can detect the oscillatory variations on sleep EEG. Therefore, different sleep stages meet different singular spectra. In addition, different healthy conditions generate different singular spectra for each sleep stage. In summary, the SSA can be proposed for EEG discrimination to support the clinical findings for psycho-psychological disorders.

Tactile exploration of virtual objects for blind and sighted people: the role of beta 1 EEG band in sensory substitution and supramodal mental mapping

OpenAIRE

Campus, C.; Brayda, L.; De Carli, F.; Chellali, R.; Famà, F.; Bruzzo, C.; Lucagrossi, L.; Rodriguez, G.

2012-01-01

The neural correlates of exploration and cognitive mapping in blindness remain elusive. The role of visuo-spatial pathways in blind vs. sighted subjects is still under debate. In this preliminary study, we investigate, as a possible estimation of the activity in the visuo-spatial pathways, the EEG patterns of blind and blindfolded-sighted subjects during the active tactile construction of cognitive maps from virtual objects compared with rest and passive tactile stimulation. Ten blind and ten...

Higher-Order Spectrum in Understanding Nonlinearity in EEG Rhythms

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Cauchy Pradhan

2012-01-01

Full Text Available The fundamental nature of the brain's electrical activities recorded as electroencephalogram (EEG remains unknown. Linear stochastic models and spectral estimates are the most common methods for the analysis of EEG because of their robustness, simplicity of interpretation, and apparent association with rhythmic behavioral patterns in nature. In this paper, we extend the use of higher-order spectrum in order to indicate the hidden characteristics of EEG signals that simply do not arise from random processes. The higher-order spectrum is an extension Fourier spectrum that uses higher moments for spectral estimates. This essentially nullifies all Gaussian random effects, therefore, can reveal non-Gaussian and nonlinear characteristics in the complex patterns of EEG time series. The paper demonstrates the distinguishing features of bispectral analysis for chaotic systems, filtered noises, and normal background EEG activity. The bispectrum analysis detects nonlinear interactions; however, it does not quantify the coupling strength. The squared bicoherence in the nonredundant region has been estimated to demonstrate nonlinear coupling. The bicoherence values are minimal for white Gaussian noises (WGNs and filtered noises. Higher bicoherence values in chaotic time series and normal background EEG activities are indicative of nonlinear coupling in these systems. The paper shows utility of bispectral methods as an analytical tool in understanding neural process underlying human EEG patterns.

Categorisation of Mobile EEG: A Researcher’s Perspective

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Anthony D. Bateson

2017-01-01

Full Text Available Researchers are increasingly attempting to undertake electroencephalography (EEG recordings in novel environments and contexts outside of the traditional static laboratory setting. The term “mobile EEG,” although commonly used to describe many of these undertakings, is ambiguous, since it attempts to encompass a wide range of EEG device mobility, participant mobility, and system specifications used across investigations. To provide quantitative parameters for “mobile EEG,” we developed a Categorisation of Mobile EEG (CoME scheme based upon scoring of device mobility (D, from 0, off-body, to 5, head-mounted with no additional equipment, participant mobility (P, from 0, static, to 5, unconstrained running, system specification (S, from 4, lowest, to 20, highest, and number of channels (C used. The CoME scheme was applied to twenty-nine published mobile EEG studies. Device mobility scores ranged from 0D to 4D, participant mobility scores from 0P to 4P, and system specification scores from 6S to 17S. The format of the scores for the four parameters is given, for example, as (2D, 4P, 17S, 32C and readily enables comparisons across studies. Our CoME scheme enables researchers to quantify the degree of device mobility, participant mobility, and system specification used in their “mobile EEG” investigations in a standardised way.

Study on Brain Dynamics by Non Linear Analysis of Music Induced EEG Signals

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Banerjee, Archi; Sanyal, Shankha; Patranabis, Anirban; Banerjee, Kaushik; Guhathakurta, Tarit; Sengupta, Ranjan; Ghosh, Dipak; Ghose, Partha

2016-02-01

Music has been proven to be a valuable tool for the understanding of human cognition, human emotion, and their underlying brain mechanisms. The objective of this study is to analyze the effect of Hindustani music on brain activity during normal relaxing conditions using electroencephalography (EEG). Ten male healthy subjects without special musical education participated in the study. EEG signals were acquired at the frontal (F3/F4) lobes of the brain while listening to music at three experimental conditions (rest, with music and without music). Frequency analysis was done for the alpha, theta and gamma brain rhythms. The finding shows that arousal based activities were enhanced while listening to Hindustani music of contrasting emotions (romantic/sorrow) for all the subjects in case of alpha frequency bands while no significant changes were observed in gamma and theta frequency ranges. It has been observed that when the music stimulus is removed, arousal activities as evident from alpha brain rhythms remain for some time, showing residual arousal. This is analogous to the conventional 'Hysteresis' loop where the system retains some 'memory' of the former state. This is corroborated in the non linear analysis (Detrended Fluctuation Analysis) of the alpha rhythms as manifested in values of fractal dimension. After an input of music conveying contrast emotions, withdrawal of music shows more retention as evidenced by the values of fractal dimension.

A preliminary study of muscular artifact cancellation in single-channel EEG.

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Chen, Xun; Liu, Aiping; Peng, Hu; Ward, Rabab K

2014-10-01

Electroencephalogram (EEG) recordings are often contaminated with muscular artifacts that strongly obscure the EEG signals and complicates their analysis. For the conventional case, where the EEG recordings are obtained simultaneously over many EEG channels, there exists a considerable range of methods for removing muscular artifacts. In recent years, there has been an increasing trend to use EEG information in ambulatory healthcare and related physiological signal monitoring systems. For practical reasons, a single EEG channel system must be used in these situations. Unfortunately, there exist few studies for muscular artifact cancellation in single-channel EEG recordings. To address this issue, in this preliminary study, we propose a simple, yet effective, method to achieve the muscular artifact cancellation for the single-channel EEG case. This method is a combination of the ensemble empirical mode decomposition (EEMD) and the joint blind source separation (JBSS) techniques. We also conduct a study that compares and investigates all possible single-channel solutions and demonstrate the performance of these methods using numerical simulations and real-life applications. The proposed method is shown to significantly outperform all other methods. It can successfully remove muscular artifacts without altering the underlying EEG activity. It is thus a promising tool for use in ambulatory healthcare systems.

Predictive value of EEG in postanoxic encephalopathy: A quantitative model-based approach.

Science.gov (United States)

Efthymiou, Evdokia; Renzel, Roland; Baumann, Christian R; Poryazova, Rositsa; Imbach, Lukas L

2017-10-01

The majority of comatose patients after cardiac arrest do not regain consciousness due to severe postanoxic encephalopathy. Early and accurate outcome prediction is therefore essential in determining further therapeutic interventions. The electroencephalogram is a standardized and commonly available tool used to estimate prognosis in postanoxic patients. The identification of pathological EEG patterns with poor prognosis relies however primarily on visual EEG scoring by experts. We introduced a model-based approach of EEG analysis (state space model) that allows for an objective and quantitative description of spectral EEG variability. We retrospectively analyzed standard EEG recordings in 83 comatose patients after cardiac arrest between 2005 and 2013 in the intensive care unit of the University Hospital Zürich. Neurological outcome was assessed one month after cardiac arrest using the Cerebral Performance Category. For a dynamic and quantitative EEG analysis, we implemented a model-based approach (state space analysis) to quantify EEG background variability independent from visual scoring of EEG epochs. Spectral variability was compared between groups and correlated with clinical outcome parameters and visual EEG patterns. Quantitative assessment of spectral EEG variability (state space velocity) revealed significant differences between patients with poor and good outcome after cardiac arrest: Lower mean velocity in temporal electrodes (T4 and T5) was significantly associated with poor prognostic outcome (pEEG patterns such as generalized periodic discharges (pEEG analysis (state space analysis) provides a novel, complementary marker for prognosis in postanoxic encephalopathy. Copyright © 2017 Elsevier B.V. All rights reserved.

Hypnagogic EEG stages and polysomnogram

OpenAIRE

HAYASHI, Mitsuo; HIBINO, Kenji; HORI, Tadao

1999-01-01

The aim of this study is to show the polysomnogram of hypnagogic period. Sixteen subjects slept for two nights. Their EEGs (Fz, Cz, Pz, Oz), horizontal and vertical EOGs, submentalis EMG, thoracic and abdominal respiration were recorded. They pressed a button when pip tones (1000Hz, 50dB, max duration : 5s, ISI : 30-90s) were presented, and reported their psychological experiences, According to Hori et al. (1994), the hypnagogic EEGs just 5s before the pip tones were classified into 9 stages,...

Source localization of rhythmic ictal EEG activity

DEFF Research Database (Denmark)

Beniczky, Sándor; Lantz, Göran; Rosenzweig, Ivana

2013-01-01

Although precise identification of the seizure-onset zone is an essential element of presurgical evaluation, source localization of ictal electroencephalography (EEG) signals has received little attention. The aim of our study was to estimate the accuracy of source localization of rhythmic ictal...... EEG activity using a distributed source model....