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Sample records for resting eeg parameters

  1. Resting state EEG correlates of memory consolidation.

    Brokaw, Kate; Tishler, Ward; Manceor, Stephanie; Hamilton, Kelly; Gaulden, Andrew; Parr, Elaine; Wamsley, Erin J

    2016-04-01

    Numerous studies demonstrate that post-training sleep benefits human memory. At the same time, emerging data suggest that other resting states may similarly facilitate consolidation. In order to identify the conditions under which non-sleep resting states benefit memory, we conducted an EEG (electroencephalographic) study of verbal memory retention across 15min of eyes-closed rest. Participants (n=26) listened to a short story and then either rested with their eyes closed, or else completed a distractor task for 15min. A delayed recall test was administered immediately following the rest period. We found, first, that quiet rest enhanced memory for the short story. Improved memory was associated with a particular EEG signature of increased slow oscillatory activity (rest can facilitate memory, and that this may occur via an active process of consolidation supported by slow oscillatory EEG activity and characterized by decreased attention to the external environment. Slow oscillatory EEG rhythms are proposed to facilitate memory consolidation during sleep by promoting hippocampal-cortical communication. Our findings suggest that EEG slow oscillations could play a significant role in memory consolidation during other resting states as well. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. Discovering EEG resting state alterations of semantic dementia.

    Grieder, Matthias; Koenig, Thomas; Kinoshita, Toshihiko; Utsunomiya, Keita; Wahlund, Lars-Olof; Dierks, Thomas; Nishida, Keiichiro

    2016-05-01

    Diagnosis of semantic dementia relies on cost-intensive MRI or PET, although resting EEG markers of other dementias have been reported. Yet the view still holds that resting EEG in patients with semantic dementia is normal. However, studies using increasingly sophisticated EEG analysis methods have demonstrated that slightest alterations of functional brain states can be detected. We analyzed the common four resting EEG microstates (A, B, C, and D) of 8 patients with semantic dementia in comparison with 8 healthy controls and 8 patients with Alzheimer's disease. Topographical differences between the groups were found in microstate classes B and C, while microstate classes A and D were comparable. The data showed that the semantic dementia group had a peculiar microstate E, but the commonly found microstate C was lacking. Furthermore, the presence of microstate E was significantly correlated with lower MMSE and language scores. Alterations in resting EEG can be found in semantic dementia. Topographical shifts in microstate C might be related to semantic memory deficits. This is the first study that discovered resting state EEG abnormality in semantic dementia. The notion that resting EEG in this dementia subtype is normal has to be revised. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  3. Resting EEG deficits in accused murderers with schizophrenia.

    Schug, Robert A; Yang, Yaling; Raine, Adrian; Han, Chenbo; Liu, Jianghong; Li, Liejia

    2011-10-31

    Empirical evidence continues to suggest a biologically distinct violent subtype of schizophrenia. The present study examined whether murderers with schizophrenia would demonstrate resting EEG deficits distinguishing them from both non-violent schizophrenia patients and murderers without schizophrenia. Resting EEG data were collected from five diagnostic groups (normal controls, non-murderers with schizophrenia, murderers with schizophrenia, murderers without schizophrenia, and murderers with psychiatric conditions other than schizophrenia) at a brain hospital in Nanjing, China. Murderers with schizophrenia were characterized by increased left-hemispheric fast-wave EEG activity relative to non-violent schizophrenia patients, while non-violent schizophrenia patients instead demonstrated increased diffuse slow-wave activity compared to all other groups. Results are discussed within the framework of a proposed left-hemispheric over-processing hypothesis specific to violent individuals with schizophrenia, involving left hemispheric hyperarousal deficits, which may lead to a homicidally violent schizophrenia outcome. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  4. Exploring resting-state EEG brain oscillatory activity in relation to cognitive functioning in multiple sclerosis.

    Keune, Philipp M; Hansen, Sascha; Weber, Emily; Zapf, Franziska; Habich, Juliane; Muenssinger, Jana; Wolf, Sebastian; Schönenberg, Michael; Oschmann, Patrick

    2017-09-01

    Neurophysiologic monitoring parameters related to cognition in Multiple Sclerosis (MS) are sparse. Previous work reported an association between magnetoencephalographic (MEG) alpha-1 activity and information processing speed. While this remains to be replicated by more available electroencephalographic (EEG) methods, also other established EEG markers, e.g. the slow-wave/fast-wave ratio (theta/beta ratio), remain to be explored in this context. Performance on standard tests addressing information processing speed and attention (Symbol-Digit Modalities Test, SDMT; Test of Attention Performance, TAP) was examined in relation to resting-state EEG alpha-1 and alpha-2 activity and the theta/beta ratio in 25MS patients. Increased global alpha-1 and alpha-2 activity and an increased frontal theta/beta ratio (pronounced slow-wave relative to fast-wave activity) were associated with lower SDMT processing speed. In an exploratory analysis, clinically impaired attention was associated with a significantly increased frontal theta/beta ratio whereas alpha power did not show sensitivity to clinical impairment. EEG global alpha power and the frontal theta/beta ratio were both associated with attention. The theta/beta ratio involved potential clinical sensitivity. Resting-state EEG recordings can be obtained during the routine clinical process. The examined resting-state measures may represent feasible monitoring parameters in MS. This notion should be explored in future intervention studies. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

  5. Correlation of BOLD Signal with Linear and Nonlinear Patterns of EEG in Resting State EEG-Informed fMRI

    Galina V. Portnova

    2018-01-01

    Full Text Available Concurrent EEG and fMRI acquisitions in resting state showed a correlation between EEG power in various bands and spontaneous BOLD fluctuations. However, there is a lack of data on how changes in the complexity of brain dynamics derived from EEG reflect variations in the BOLD signal. The purpose of our study was to correlate both spectral patterns, as linear features of EEG rhythms, and nonlinear EEG dynamic complexity with neuronal activity obtained by fMRI. We examined the relationships between EEG patterns and brain activation obtained by simultaneous EEG-fMRI during the resting state condition in 25 healthy right-handed adult volunteers. Using EEG-derived regressors, we demonstrated a substantial correlation of BOLD signal changes with linear and nonlinear features of EEG. We found the most significant positive correlation of fMRI signal with delta spectral power. Beta and alpha spectral features had no reliable effect on BOLD fluctuation. However, dynamic changes of alpha peak frequency exhibited a significant association with BOLD signal increase in right-hemisphere areas. Additionally, EEG dynamic complexity as measured by the HFD of the 2–20 Hz EEG frequency range significantly correlated with the activation of cortical and subcortical limbic system areas. Our results indicate that both spectral features of EEG frequency bands and nonlinear dynamic properties of spontaneous EEG are strongly associated with fluctuations of the BOLD signal during the resting state condition.

  6. Resting-state EEG, impulsiveness, and personality in daily and nondaily smokers.

    Rass, Olga; Ahn, Woo-Young; O'Donnell, Brian F

    2016-01-01

    Resting EEG is sensitive to transient, acute effects of nicotine administration and abstinence, but the chronic effects of smoking on EEG are poorly characterized. This study measures the resting EEG profile of chronic smokers in a non-deprived, non-peak state to test whether differences in smoking behavior and personality traits affect pharmaco-EEG response. Resting EEG, impulsiveness, and personality measures were collected from daily smokers (n=22), nondaily smokers (n=31), and non-smokers (n=30). Daily smokers had reduced resting delta and alpha EEG power and higher impulsiveness (Barratt Impulsiveness Scale) compared to nondaily smokers and non-smokers. Both daily and nondaily smokers discounted delayed rewards more steeply, reported lower conscientiousness (NEO-FFI), and reported greater disinhibition and experience seeking (Sensation Seeking Scale) than non-smokers. Nondaily smokers reported greater sensory hedonia than nonsmokers. Altered resting EEG power in daily smokers demonstrates differences in neural signaling that correlated with greater smoking behavior and dependence. Although nondaily smokers share some characteristics with daily smokers that may predict smoking initiation and maintenance, they differ on measures of impulsiveness and resting EEG power. Resting EEG in non-deprived chronic smokers provides a standard for comparison to peak and trough nicotine states and may serve as a biomarker for nicotine dependence, relapse risk, and recovery. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  7. Resting-state EEG, Impulsiveness, and Personality in Daily and Nondaily Smokers†

    Rass, Olga; Ahn, Woo-Young; O’Donnell, Brian F.

    2015-01-01

    Objectives Resting EEG is sensitive to transient, acute effects of nicotine administration and abstinence, but the chronic effects smoking on EEG are poorly characterized. This study measures the resting EEG profile of chronic smokers in a non-deprived, non-peak state to test whether differences in smoking behavior and personality traits affect pharmaco-EEG response. Methods Resting EEG, impulsiveness, and personality measures were collected from daily smokers (n=22), nondaily smokers (n=31), and non-smokers (n=30). Results Daily smokers had reduced resting delta and alpha EEG power and higher impulsiveness (Barratt Impulsiveness Scale) compared to nondaily smokers and non-smokers. Both daily and nondaily smokers discounted delayed rewards more steeply, reported lower conscientiousness (NEO-FFI) and reported greater disinhibition and experience seeking (Sensation Seeking Scale) than non-smokers. Nondaily smokers reported greater sensory hedonia than nonsmokers. Conclusions Altered resting EEG power in daily smokers demonstrates differences in neural signaling that correlated with greater smoking behavior and dependence. Although nondaily smokers share some characteristics with daily smokers that may predict smoking initiation and maintenance, they differ on measures of impulsiveness and resting EEG power. Significance Resting EEG in non-deprived chronic smokers provides a standard for comparison to peak and trough nicotine states and may serve as a biomarker for nicotine dependence, relapse risk, and recovery. PMID:26051750

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

    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

  9. MATLAB Toolboxes for Reference Electrode Standardization Technique (REST) of Scalp EEG.

    Dong, Li; Li, Fali; Liu, Qiang; Wen, Xin; Lai, Yongxiu; Xu, Peng; Yao, Dezhong

    2017-01-01

    Reference electrode standardization technique (REST) has been increasingly acknowledged and applied as a re-reference technique to transform an actual multi-channels recordings to approximately zero reference ones in electroencephalography/event-related potentials (EEG/ERPs) community around the world in recent years. However, a more easy-to-use toolbox for re-referencing scalp EEG data to zero reference is still lacking. Here, we have therefore developed two open-source MATLAB toolboxes for REST of scalp EEG. One version of REST is closely integrated into EEGLAB, which is a popular MATLAB toolbox for processing the EEG data; and another is a batch version to make it more convenient and efficient for experienced users. Both of them are designed to provide an easy-to-use for novice researchers and flexibility for experienced researchers. All versions of the REST toolboxes can be freely downloaded at http://www.neuro.uestc.edu.cn/rest/Down.html, and the detailed information including publications, comments and documents on REST can also be found from this website. An example of usage is given with comparative results of REST and average reference. We hope these user-friendly REST toolboxes could make the relatively novel technique of REST easier to study, especially for applications in various EEG studies.

  10. Recognizing mild cognitive impairment based on network connectivity analysis of resting EEG with zero reference

    Xu, Peng; Xiong, Xiu Chun; Tian, Yin; Zhang, Rui; Li, Pei Yang; Yao, De Zhong; Xue, Qing; Wang, Yu Ping; Peng, Yueheng

    2014-01-01

    The diagnosis of mild cognitive impairment (MCI) is very helpful for early therapeutic interventions of Alzheimer's disease (AD). MCI has been proven to be correlated with disorders in multiple brain areas. In this paper, we used information from resting brain networks at different EEG frequency bands to reliably recognize MCI. Because EEG network analysis is influenced by the reference that is used, we also evaluate the effect of the reference choices on the resting scalp EEG network-based MCI differentiation. The conducted study reveals two aspects: (1) the network-based MCI differentiation is superior to the previously reported classification that uses coherence in the EEG; and (2) the used EEG reference influences the differentiation performance, and the zero approximation technique (reference electrode standardization technique, REST) can construct a more accurate scalp EEG network, which results in a higher differentiation accuracy for MCI. This study indicates that the resting scalp EEG-based network analysis could be valuable for MCI recognition in the future. (paper)

  11. Resting-state qEEG predicts rate of second language learning in adults.

    Prat, Chantel S; Yamasaki, Brianna L; Kluender, Reina A; Stocco, Andrea

    2016-01-01

    Understanding the neurobiological basis of individual differences in second language acquisition (SLA) is important for research on bilingualism, learning, and neural plasticity. The current study used quantitative electroencephalography (qEEG) to predict SLA in college-aged individuals. Baseline, eyes-closed resting-state qEEG was used to predict language learning rate during eight weeks of French exposure using an immersive, virtual scenario software. Individual qEEG indices predicted up to 60% of the variability in SLA, whereas behavioral indices of fluid intelligence, executive functioning, and working-memory capacity were not correlated with learning rate. Specifically, power in beta and low-gamma frequency ranges over right temporoparietal regions were strongly positively correlated with SLA. These results highlight the utility of resting-state EEG for studying the neurobiological basis of SLA in a relatively construct-free, paradigm-independent manner. Published by Elsevier Inc.

  12. "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

    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

  13. Spatiotemporal dynamics of the brain at rest--exploring EEG microstates as electrophysiological signatures of BOLD resting state networks.

    Yuan, Han; Zotev, Vadim; Phillips, Raquel; Drevets, Wayne C; Bodurka, Jerzy

    2012-05-01

    Neuroimaging research suggests that the resting cerebral physiology is characterized by complex patterns of neuronal activity in widely distributed functional networks. As studied using functional magnetic resonance imaging (fMRI) of the blood-oxygenation-level dependent (BOLD) signal, the resting brain activity is associated with slowly fluctuating hemodynamic signals (~10s). More recently, multimodal functional imaging studies involving simultaneous acquisition of BOLD-fMRI and electroencephalography (EEG) data have suggested that the relatively slow hemodynamic fluctuations of some resting state networks (RSNs) evinced in the BOLD data are related to much faster (~100 ms) transient brain states reflected in EEG signals, that are referred to as "microstates". To further elucidate the relationship between microstates and RSNs, we developed a fully data-driven approach that combines information from simultaneously recorded, high-density EEG and BOLD-fMRI data. Using independent component analysis (ICA) of the combined EEG and fMRI data, we identified thirteen microstates and ten RSNs that are organized independently in their temporal and spatial characteristics, respectively. We hypothesized that the intrinsic brain networks that are active at rest would be reflected in both the EEG data and the fMRI data. To test this hypothesis, the rapid fluctuations associated with each microstate were correlated with the BOLD-fMRI signal associated with each RSN. We found that each RSN was characterized further by a specific electrophysiological signature involving from one to a combination of several microstates. Moreover, by comparing the time course of EEG microstates to that of the whole-brain BOLD signal, on a multi-subject group level, we unraveled for the first time a set of microstate-associated networks that correspond to a range of previously described RSNs, including visual, sensorimotor, auditory, attention, frontal, visceromotor and default mode networks. These

  14. Resting State EEG-based biometrics for individual identification using convolutional neural networks.

    Lan Ma; Minett, James W; Blu, Thierry; Wang, William S-Y

    2015-08-01

    Biometrics is a growing field, which permits identification of individuals by means of unique physical features. Electroencephalography (EEG)-based biometrics utilizes the small intra-personal differences and large inter-personal differences between individuals' brainwave patterns. In the past, such methods have used features derived from manually-designed procedures for this purpose. Another possibility is to use convolutional neural networks (CNN) to automatically extract an individual's best and most unique neural features and conduct classification, using EEG data derived from both Resting State with Open Eyes (REO) and Resting State with Closed Eyes (REC). Results indicate that this CNN-based joint-optimized EEG-based Biometric System yields a high degree of accuracy of identification (88%) for 10-class classification. Furthermore, rich inter-personal difference can be found using a very low frequency band (0-2Hz). Additionally, results suggest that the temporal portions over which subjects can be individualized is less than 200 ms.

  15. Gender differences in association between serotonin transporter gene polymorphism and resting-state EEG activity.

    Volf, N V; Belousova, L V; Knyazev, G G; Kulikov, A V

    2015-01-22

    Human brain oscillations represent important features of information processing and are highly heritable. Gender has been observed to affect association between the 5-HTTLPR (serotonin-transporter-linked polymorphic region) polymorphism and various endophenotypes. This study aimed to investigate the effects of 5-HTTLPR on the spontaneous electroencephalography (EEG) activity in healthy male and female subjects. DNA samples extracted from buccal swabs and resting EEG recorded at 60 standard leads were collected from 210 (101 men and 109 women) volunteers. Spectral EEG power estimates and cortical sources of EEG activity were investigated. It was shown that effects of 5-HTTLPR polymorphism on electrical activity of the brain vary as a function of gender. Women with the S/L genotype had greater global EEG power compared to men with the same genotype. In men, current source density was markedly different among genotype groups in only alpha 2 and alpha 3 frequency ranges: S/S allele carriers had higher current source density estimates in the left inferior parietal lobule in comparison with the L/L group. In women, genotype difference in global power asymmetry was found in the central-temporal region. Contrasting L/L and S/L genotype carriers also yielded significant effects in the right hemisphere inferior parietal lobule and the right postcentral gyrus with L/L genotype carriers showing lower current source density estimates than S/L genotype carriers in all but gamma bands. So, in women, the effects of 5-HTTLPR polymorphism were associated with modulation of the EEG activity in a wide range of EEG frequencies. The significance of the results lies in the demonstration of gene by sex interaction with resting EEG that has implications for understanding sex-related differences in affective states, emotion and cognition. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

  16. Plastic modulation of PTSD resting-state networks by EEG neurofeedback

    Kluetsch, Rosemarie C.; Ros, Tomas; Théberge, Jean; Frewen, Paul A.; Calhoun, Vince D.; Schmahl, Christian; Jetly, Rakesh; Lanius, Ruth A.

    2015-01-01

    Objective Electroencephalographic (EEG) neurofeedback training has been shown to produce plastic modulations in salience network and default mode network functional connectivity in healthy individuals. In this study, we investigated whether a single session of neurofeedback training aimed at the voluntary reduction of alpha rhythm (8–12 Hz) amplitude would be related to differences in EEG network oscillations, functional MRI (fMRI) connectivity, and subjective measures of state anxiety and arousal in a group of individuals with PTSD. Method 21 individuals with PTSD related to childhood abuse underwent 30 minutes of EEG neurofeedback training preceded and followed by a resting-state fMRI scan. Results Alpha desynchronizing neurofeedback was associated with decreased alpha amplitude during training, followed by a significant increase (‘rebound’) in resting-state alpha synchronization. This rebound was linked to increased calmness, greater salience network connectivity with the right insula, and enhanced default mode network connectivity with bilateral posterior cingulate, right middle frontal gyrus, and left medial prefrontal cortex. Conclusion Our study represents a first step in elucidating the potential neurobehavioral mechanisms mediating the effects of neurofeedback treatment on regulatory systems in PTSD. Moreover, it documents for the first time a spontaneous EEG ‘rebound’ after neurofeedback, pointing to homeostatic/compensatory mechanisms operating in the brain. PMID:24266644

  17. Plastic modulation of PTSD resting-state networks and subjective wellbeing by EEG neurofeedback.

    Kluetsch, R C; Ros, T; Théberge, J; Frewen, P A; Calhoun, V D; Schmahl, C; Jetly, R; Lanius, R A

    2014-08-01

    Electroencephalographic (EEG) neurofeedback training has been shown to produce plastic modulations in salience network and default mode network functional connectivity in healthy individuals. In this study, we investigated whether a single session of neurofeedback training aimed at the voluntary reduction of alpha rhythm (8-12 Hz) amplitude would be related to differences in EEG network oscillations, functional MRI (fMRI) connectivity, and subjective measures of state anxiety and arousal in a group of individuals with post-traumatic stress disorder (PTSD). Twenty-one individuals with PTSD related to childhood abuse underwent 30 min of EEG neurofeedback training preceded and followed by a resting-state fMRI scan. Alpha desynchronizing neurofeedback was associated with decreased alpha amplitude during training, followed by a significant increase ('rebound') in resting-state alpha synchronization. This rebound was linked to increased calmness, greater salience network connectivity with the right insula, and enhanced default mode network connectivity with bilateral posterior cingulate, right middle frontal gyrus, and left medial prefrontal cortex. Our study represents a first step in elucidating the potential neurobehavioural mechanisms mediating the effects of neurofeedback treatment on regulatory systems in PTSD. Moreover, it documents for the first time a spontaneous EEG 'rebound' after neurofeedback, pointing to homeostatic/compensatory mechanisms operating in the brain. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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

    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.

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

    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

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

    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

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

    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.

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

    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.

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

    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.

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

    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

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

    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.

  6. Aberrant EEG functional connectivity and EEG power spectra in resting state post-traumatic stress disorder: a sLORETA study.

    Imperatori, Claudio; Farina, Benedetto; Quintiliani, Maria Isabella; Onofri, Antonio; Castelli Gattinara, Paola; Lepore, Marta; Gnoni, Valentina; Mazzucchi, Edoardo; Contardi, Anna; Della Marca, Giacomo

    2014-10-01

    The aim of the present study was to explore the modifications of EEG power spectra and EEG connectivity of resting state (RS) condition in patients with post-traumatic stress disorder (PTSD). Seventeen patients and seventeen healthy subjects matched for age and gender were enrolled. EEG was recorded during 5min of RS. EEG analysis was conducted by means of the standardized Low Resolution Electric Tomography software (sLORETA). In power spectra analysis PTSD patients showed a widespread increase of theta activity (4.5-7.5Hz) in parietal lobes (Brodmann Area, BA 7, 4, 5, 40) and in frontal lobes (BA 6). In the connectivity analysis PTSD patients also showed increase of alpha connectivity (8-12.5Hz) between the cortical areas explored by Pz-P4 electrode. Our results could reflect the alteration of memory systems and emotional processing consistently altered in PTSD patients. Copyright © 2014 Elsevier B.V. All rights reserved.

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

    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.

  8. Preliteracy signatures of poor-reading abilities in resting-state EEG

    Giuseppina eSchiavone

    2014-09-01

    Full Text Available The hereditary character of dyslexia suggests the presence of putative underlying neural anomalies already in preliterate age. Here, we investigated whether early neurophysiological correlates of future reading difficulties—a hallmark of dyslexia—could be identified in the resting-state EEG of preliterate children. The children in this study were recruited at birth and classified on the basis of parents’ performance on reading tests to be at-risk of becoming poor readers (n = 48 or not (n = 14. Eyes-open rest EEG was measured at the age of 3 years, and the at-risk children were divided into fluent readers (n = 24 and non-fluent readers (n = 24 after reading assessment at their third grade of school. We found that fluent readers and non-fluent readers differed in normalized spectral amplitude. Non-fluent readers were characterized by lower amplitude in the delta-1 frequency band (0.5–2 Hz and higher amplitude in the alpha-1 band (6–8 Hz in multiple scalp regions compared to control and at-risk fluent readers. Interestingly, across groups these EEG biomarkers correlated with several behavioral test scores measured in the third grade. Specifically, the performance on reading fluency, phonological and orthographic tasks and rapid automatized naming task correlated positively with delta-1 and negatively with alpha-1. Together, our results suggest that combining family-risk status, neurophysiological testing and behavioral test scores in a longitudinal setting may help uncover physiological mechanisms implicated with neurodevelopmental disorders such as the predisposition to reading disabilities.

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

    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.

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

    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

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

    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

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

    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.

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

    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.

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

    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.

  15. Resting state glutamate predicts elevated pre-stimulus alpha during self-relatedness: A combined EEG-MRS study on "rest-self overlap".

    Bai, Yu; Nakao, Takashi; Xu, Jiameng; Qin, Pengmin; Chaves, Pedro; Heinzel, Alexander; Duncan, Niall; Lane, Timothy; Yen, Nai-Shing; Tsai, Shang-Yueh; Northoff, Georg

    2016-01-01

    Recent studies have demonstrated neural overlap between resting state activity and self-referential processing. This "rest-self" overlap occurs especially in anterior cortical midline structures like the perigenual anterior cingulate cortex (PACC). However, the exact neurotemporal and biochemical mechanisms remain to be identified. Therefore, we conducted a combined electroencephalography (EEG)-magnetic resonance spectroscopy (MRS) study. EEG focused on pre-stimulus (e.g., prior to stimulus presentation or perception) power changes to assess the degree to which those changes can predict subjects' perception (and judgment) of subsequent stimuli as high or low self-related. MRS measured resting state concentration of glutamate, focusing on PACC. High pre-stimulus (e.g., prior to stimulus presentation or perception) alpha power significantly correlated with both perception of stimuli judged to be highly self-related and with resting state glutamate concentrations in the PACC. In sum, our results show (i) pre-stimulus (e.g., prior to stimulus presentation or perception) alpha power and resting state glutamate concentration to mediate rest-self overlap that (ii) dispose or incline subjects to assign high degrees of self-relatedness to perceptual stimuli.

  16. Reliability of fully automated versus visually controlled pre- and post-processing of resting-state EEG.

    Hatz, F; Hardmeier, M; Bousleiman, H; Rüegg, S; Schindler, C; Fuhr, P

    2015-02-01

    To compare the reliability of a newly developed Matlab® toolbox for the fully automated, pre- and post-processing of resting state EEG (automated analysis, AA) with the reliability of analysis involving visually controlled pre- and post-processing (VA). 34 healthy volunteers (age: median 38.2 (20-49), 82% female) had three consecutive 256-channel resting-state EEG at one year intervals. Results of frequency analysis of AA and VA were compared with Pearson correlation coefficients, and reliability over time was assessed with intraclass correlation coefficients (ICC). Mean correlation coefficient between AA and VA was 0.94±0.07, mean ICC for AA 0.83±0.05 and for VA 0.84±0.07. AA and VA yield very similar results for spectral EEG analysis and are equally reliable. AA is less time-consuming, completely standardized, and independent of raters and their training. Automated processing of EEG facilitates workflow in quantitative EEG analysis. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

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

    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.

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

    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

  19. Cortical sources of resting state EEG rhythms are related to brain hypometabolism in subjects with Alzheimer's disease: an EEG-PET study.

    Babiloni, Claudio; Del Percio, Claudio; Caroli, Anna; Salvatore, Elena; Nicolai, Emanuele; Marzano, Nicola; Lizio, Roberta; Cavedo, Enrica; Landau, Susan; Chen, Kewei; Jagust, William; Reiman, Eric; Tedeschi, Gioacchino; Montella, Patrizia; De Stefano, Manuela; Gesualdo, Loreto; Frisoni, Giovanni B; Soricelli, Andrea

    2016-12-01

    Cortical sources of resting state electroencephalographic (EEG) delta (2-4 Hz) and low-frequency alpha (8-10.5 Hz) rhythms show abnormal activity (i.e., current density) in patients with dementia due to Alzheimer's disease (AD). Here, we hypothesized that abnormality of this activity is related to relevant disease processes as revealed by cortical hypometabolism typically observed in AD patients by fluorodeoxyglucose positron emission tomography. Resting state eyes-closed EEG data were recorded in 19 AD patients with dementia and 40 healthy elderly (Nold) subjects. EEG frequency bands of interest were delta and low-frequency alpha. EEG sources were estimated in these bands by low-resolution brain electromagnetic tomography (LORETA). Fluorodeoxyglucose positron emission tomography images were recorded only in the AD patients, and cortical hypometabolism was indexed by the so-called Alzheimer's discrimination analysis tool (PALZ) in the frontal association, ventromedial frontal, temporoparietal association, posterior cingulate, and precuneus areas. Results showed that compared with the Nold group, the AD group pointed to higher activity of delta sources and lower activity of low-frequency alpha sources in a cortical region of interest formed by all cortical areas of the PALZ score. In the AD patients, there was a positive correlation between the PALZ score and the activity of delta sources in the cortical region of interest (p < 0.05). These results suggest a relationship between resting state cortical hypometabolism and synchronization of cortical neurons at delta rhythms in AD patients with dementia. Copyright © 2016 Elsevier Inc. All rights reserved.

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

    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 ).

  1. EEG

    ... 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 ...

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

    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%.

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

    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.

  4. EEG

    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.

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

    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.

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

    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.

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

    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.

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

    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

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

    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.

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

    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.

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

    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.

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

    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.

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

    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

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

    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.

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

    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.

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

    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.

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

    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.

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

    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.

  19. Neurophysiological features of Internet gaming disorder and alcohol use disorder: a resting-state EEG study.

    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.

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

    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.

  1. 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

    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.

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

    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.

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

    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...

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

    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.

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

    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

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

    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.

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

    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.

  8. Feature selection and classifier parameters estimation for EEG signals peak detection using particle swarm optimization.

    Adam, Asrul; Shapiai, Mohd Ibrahim; Tumari, Mohd Zaidi Mohd; Mohamad, Mohd Saberi; Mubin, Marizan

    2014-01-01

    Electroencephalogram (EEG) signal peak detection is widely used in clinical applications. The peak point can be detected using several approaches, including time, frequency, time-frequency, and nonlinear domains depending on various peak features from several models. However, there is no study that provides the importance of every peak feature in contributing to a good and generalized model. In this study, feature selection and classifier parameters estimation based on particle swarm optimization (PSO) are proposed as a framework for peak detection on EEG signals in time domain analysis. Two versions of PSO are used in the study: (1) standard PSO and (2) random asynchronous particle swarm optimization (RA-PSO). The proposed framework tries to find the best combination of all the available features that offers good peak detection and a high classification rate from the results in the conducted experiments. The evaluation results indicate that the accuracy of the peak detection can be improved up to 99.90% and 98.59% for training and testing, respectively, as compared to the framework without feature selection adaptation. Additionally, the proposed framework based on RA-PSO offers a better and reliable classification rate as compared to standard PSO as it produces low variance model.

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

    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.

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

    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.

  11. The Influence of Age on Hemodynamic Parameters During Rest and Exercise in Healthy Individuals

    Wolsk, Emil; Bakkestrøm, Rine; Thomsen, Jacob H

    2017-01-01

    OBJECTIVES: The authors sought to obtain hemodynamic estimates across a wide age span and in both sexes for future reference and compare these estimates with current guideline diagnostic hemodynamic thresholds for abnormal filling pressure and pulmonary hypertension. BACKGROUND: At present....... METHODS: Sixty-two healthy participants, evenly distributed with respect to age (20 to 80 years) and sex (32 women/30 men), were prospectively enrolled in the study. Participants were all deemed healthy by medical history, echocardiography, exercise test, spirometry, blood tests, and electrocardiogram....... Participants had hemodynamic parameters measured using right heart catheterization during rest, passive leg raise, and incremental exercise. RESULTS: During rest, all hemodynamic parameters were similar between age groups, apart from blood pressure. During leg raise and incremental exercise...

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

    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.

  13. How attention influences perceptual decision making: Single-trial EEG correlates of drift-diffusion model parameters

    Nunez, Michael D.; Vandekerckhove, Joachim; Srinivasan, Ramesh

    2016-01-01

    Perceptual decision making can be accounted for by drift-diffusion models, a class of decision-making models that assume a stochastic accumulation of evidence on each trial. Fitting response time and accuracy to a drift-diffusion model produces evidence accumulation rate and non-decision time parameter estimates that reflect cognitive processes. Our goal is to elucidate the effect of attention on visual decision making. In this study, we show that measures of attention obtained from simultaneous EEG recordings can explain per-trial evidence accumulation rates and perceptual preprocessing times during a visual decision making task. Models assuming linear relationships between diffusion model parameters and EEG measures as external inputs were fit in a single step in a hierarchical Bayesian framework. The EEG measures were features of the evoked potential (EP) to the onset of a masking noise and the onset of a task-relevant signal stimulus. Single-trial evoked EEG responses, P200s to the onsets of visual noise and N200s to the onsets of visual signal, explain single-trial evidence accumulation and preprocessing times. Within-trial evidence accumulation variance was not found to be influenced by attention to the signal or noise. Single-trial measures of attention lead to better out-of-sample predictions of accuracy and correct reaction time distributions for individual subjects. PMID:28435173

  14. How attention influences perceptual decision making: Single-trial EEG correlates of drift-diffusion model parameters.

    Nunez, Michael D; Vandekerckhove, Joachim; Srinivasan, Ramesh

    2017-02-01

    Perceptual decision making can be accounted for by drift-diffusion models, a class of decision-making models that assume a stochastic accumulation of evidence on each trial. Fitting response time and accuracy to a drift-diffusion model produces evidence accumulation rate and non-decision time parameter estimates that reflect cognitive processes. Our goal is to elucidate the effect of attention on visual decision making. In this study, we show that measures of attention obtained from simultaneous EEG recordings can explain per-trial evidence accumulation rates and perceptual preprocessing times during a visual decision making task. Models assuming linear relationships between diffusion model parameters and EEG measures as external inputs were fit in a single step in a hierarchical Bayesian framework. The EEG measures were features of the evoked potential (EP) to the onset of a masking noise and the onset of a task-relevant signal stimulus. Single-trial evoked EEG responses, P200s to the onsets of visual noise and N200s to the onsets of visual signal, explain single-trial evidence accumulation and preprocessing times. Within-trial evidence accumulation variance was not found to be influenced by attention to the signal or noise. Single-trial measures of attention lead to better out-of-sample predictions of accuracy and correct reaction time distributions for individual subjects.

  15. Prospective Cohort Study Evaluating the Prognostic Value of Simple EEG Parameters in Postanoxic Coma.

    Azabou, Eric; Fischer, Catherine; Mauguiere, François; Vaugier, Isabelle; Annane, Djillali; Sharshar, Tarek; Lofaso, Fréderic

    2016-01-01

    We prospectively studied early bedside standard EEG characteristics in 61 acute postanoxic coma patients. Five simple EEG features, namely, isoelectric, discontinuous, nonreactive to intense auditory and nociceptive stimuli, dominant delta frequency, and occurrence of paroxysms were classified yes or no. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristic curve (AUC) of each of these variables for predicting an unfavorable outcome, defined as death, persistent vegetative state, minimally conscious state, or severe neurological disability, as assessed 1 year after coma onset were computed as well as Synek's score. The outcome was unfavorable in 56 (91.8%) patients. Sensitivity, specificity, PPV, NPV, and AUC of nonreactive EEG for predicting an unfavorable outcome were 84%, 80%, 98%, 31%, and 0.82, respectively; and were all very close to the ones of Synek score>3, which were 82%, 80%, 98%, 29%, and 0.81, respectively. Specificities for predicting an unfavorable outcome were 100% for isoelectric, discontinuous, or dominant delta activity EEG. These 3 last features were constantly associated to unfavorable outcome. Absent EEG reactivity strongly predicted an unfavorable outcome in postanoxic coma, and performed as accurate as a Synek score>3. Analyzing characteristics of some simple EEG features may easily help nonneurophysiologist physicians to investigate prognostic issue of postanoxic coma patient. In this study (a) discontinuous, isoelectric, or delta-dominant EEG were constantly associated with unfavorable outcome and (b) nonreactive EEG performed prognostic as accurate as a Synek score>3. © EEG and Clinical Neuroscience Society (ECNS) 2015.

  16. Long-Term Evolution Electromagnetic Fields Exposure Modulates the Resting State EEG on Alpha and Beta Bands.

    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.

  17. Item parameters dissociate between expectation formats: A regression analysis of time-frequency decomposed EEG data

    Irene Fernández Monsalve

    2014-08-01

    Full Text Available During language comprehension, semantic contextual information is used to generate expectations about upcoming items. This has been commonly studied through the N400 event-related potential (ERP, as a measure of facilitated lexical retrieval. However, the associative relationships in multi-word expressions (MWE may enable the generation of a categorical expectation, leading to lexical retrieval before target word onset. Processing of the target word would thus reflect a target-identification mechanism, possibly indexed by a P3 ERP component. However, given their time overlap (200-500 ms post-stimulus onset, differentiating between N400/P3 ERP responses (averaged over multiple linguistically variable trials is problematic. In the present study, we analyzed EEG data from a previous experiment, which compared ERP responses to highly expected words that were placed either in a MWE or a regular non-fixed compositional context, and to low predictability controls. We focused on oscillatory dynamics and regression analyses, in order to dissociate between the two contexts by modeling the electrophysiological response as a function of item-level parameters. A significant interaction between word position and condition was found in the regression model for power in a theta range (~7-9 Hz, providing evidence for the presence of qualitative differences between conditions. Power levels within this band were lower for MWE than compositional contexts then the target word appeared later on in the sentence, confirming that in the former lexical retrieval would have taken place before word onset. On the other hand, gamma-power (~50-70 Hz was also modulated by predictability of the item in all conditions, which is interpreted as an index of a similar `matching' sub-step for both types of contexts, binding an expected representation and the external input.

  18. 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

    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.

  19. Arbuscular mycorrhizal fungi associated with vegetation and soil parameters under rest grazing management in a desert steppe ecosystem.

    Bai, Gegenbaoleer; Bao, Yuying; Du, Guoxin; Qi, Yunlong

    2013-05-01

    The impact of rest grazing on arbuscular mycorrhizal fungi (AMF) and the interactions of AMF with vegetation and soil parameters under rest grazing condition were investigated between spring and late summer in a desert steppe ecosystem with different grazing managements (rest grazing with different lengths of resting period, banned or continuous grazing) in Inner Mongolia, China. AMF diversity and colonization, vegetation biomass, soil properties and soil phosphatase activity were examined. In rest grazing areas of 60 days, AMF spore number and diversity index at a 0-10 cm soil depth as well as vesicular and hyphal colonization rates were higher compared with other grazing treatments. In addition, soil organic matter and total N contents were highest and soil alkaline phosphatase was most active under 60-day rest grazing. In August and September, these areas also had the highest amount of aboveground vegetation. The results indicated that resting grazing for an appropriate period of time in spring has a positive effect on AMF sporulation, colonization and diversity, and that under rest grazing conditions, AMF parameters are positively correlated with some soil characteristics.

  20. Neuro-immune relationships at patients with chronic pyelonephrite and cholecystite. Communication 2. Correlations between parameters EEG, HRV and Phagocytosis

    Kul’chyns’kyi, Andriy B; Kovbasnyuk, Marta M; Korolyshyn, Tetyana A; Kyjenko, Valeriy M; Zukow, Walery; Popovych, Igor L

    2016-01-01

    Kul’chyns’kyi Andriy B, Kovbasnyuk Marta M, Korolyshyn Tetyana A, Kyjenko Valeriy M, Zukow Walery, Popovych Igor L. Neuro-immune relationships at patients with chronic pyelonephrite and cholecystite. Communication 2. Correlations between parameters EEG, HRV and Phagocytosis. Journal of Education, Health and Sport. 2016;6(10):377-401. eISSN 2391-8306. DOI http://dx.doi.org/10.5281/zenodo.163221 http://ojs.ukw.edu.pl/index.php/johs/article/view/3957 The journal h...

  1. Resting metabolic rate, pulmonary functions, and body composition parameters in children with attention deficit hyperactivity disorder.

    Alpaslan, Ahmet Hamdi; Ucok, Kagan; Coşkun, Kerem Şenol; Genc, Abdurrahman; Karabacak, Hatice; Guzel, Halil Ibrahim

    2017-03-01

    Several studies of school-aged children with attention deficit hyperactivity disorder (ADHD) have found a higher prevalence of overweight/obesity compared with the general population. However, the scientific literature contains insufficient evidence to establish clear conclusions on pulmonary functions, resting metabolic rate (RMR), and body composition in children with ADHD. This study therefore investigates the pulmonary functions tests (PFTs), RMR, and body composition parameters in children with ADHD and evaluates their quality of life. Forty children with ADHD and 40 healthy controls participated in the study. The children's parents completed Conners' parent rating scale (CPRS) and the pediatric quality of life (PedsQL), and their teachers completed Conners' Teacher rating scale (CTRS). The child participants also completed the PedsQL. RMR, PFTs, and body composition parameters were investigated. No significant differences in age, gender, and socioeconomic level were found. All CPRS subscales, except anxiety and psychosomatic conditions, were significantly different (p ADHD group. The results showed that the ADHD group's quality of life is worse than the control group. Body mass index, body composition parameters, RMR, and PFTs were not statistically different between the children with ADHD and the healthy controls. Further studies with complex designs are needed to confirm the results.

  2. [Motivation effect on EEG spectral power and heart rate parameters in students during examination stress].

    Dzhebrailova, T D; Korobeĭnikova, I I; Rudneva, L P

    2014-09-01

    EEG spectral power was calculated in 24 students (18-21 years) with different levels of motivation and anxiety (tested by Spielberger) in two experimental conditions: during the common educational process and the examination stress. Before examination tests, in subjects with high motivation and anxiety level the relative delta activity power increased in right frontal (F4) brain areas. In students with medium motivation immediately before an examination the relative beta2-activity power increased in right frontal (F4) brain areas. It is suggested that delta oscillati- ons reflect activity of the defensive motivational system, whereas beta2 oscillations may be associated with the achievement motivation.

  3. Neural signatures of economic parameters during decision-making: a functional MRI (FMRI), electroencephalography (EEG) and autonomic monitoring study.

    Minati, Ludovico; Grisoli, Marina; Franceschetti, Silvana; Epifani, Francesca; Granvillano, Alice; Medford, Nick; Harrison, Neil A; Piacentini, Sylvie; Critchley, Hugo D

    2012-01-01

    Adaptive behaviour requires an ability to obtain rewards by choosing between different risky options. Financial gambles can be used to study effective decision-making experimentally, and to distinguish processes involved in choice option evaluation from outcome feedback and other contextual factors. Here, we used a paradigm where participants evaluated 'mixed' gambles, each presenting a potential gain and a potential loss and an associated variable outcome probability. We recorded neural responses using autonomic monitoring, electroencephalography (EEG) and functional neuroimaging (fMRI), and used a univariate, parametric design to test for correlations with the eleven economic parameters that varied across gambles, including expected value (EV) and amount magnitude. Consistent with behavioural economic theory, participants were risk-averse. Gamble evaluation generated detectable autonomic responses, but only weak correlations with outcome uncertainty were found, suggesting that peripheral autonomic feedback does not play a major role in this task. Long-latency stimulus-evoked EEG potentials were sensitive to expected gain and expected value, while alpha-band power reflected expected loss and amount magnitude, suggesting parallel representations of distinct economic qualities in cortical activation and central arousal. Neural correlates of expected value representation were localized using fMRI to ventromedial prefrontal cortex, while the processing of other economic parameters was associated with distinct patterns across lateral prefrontal, cingulate, insula and occipital cortices including default-mode network and early visual areas. These multimodal data provide complementary evidence for distributed substrates of choice evaluation across multiple, predominantly cortical, brain systems wherein distinct regions are preferentially attuned to specific economic features. Our findings extend biologically-plausible models of risky decision-making while providing

  4. EEG biofeedback

    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

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

    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.

  6. Bending analysis of agglomerated carbon nanotube-reinforced beam resting on two parameters modified Vlasov model foundation

    Ghorbanpour Arani, A.; Zamani, M. H.

    2018-06-01

    The present work deals with bending behavior of nanocomposite beam resting on two parameters modified Vlasov model foundation (MVMF), with consideration of agglomeration and distribution of carbon nanotubes (CNTs) in beam matrix. Equivalent fiber based on Eshelby-Mori-Tanaka approach is employed to determine influence of CNTs aggregation on elastic properties of CNT-reinforced beam. The governing equations are deduced using the principle of minimum potential energy under assumption of the Euler-Bernoulli beam theory. The MVMF required the estimation of γ parameter; to this purpose, unique iterative technique based on variational principles is utilized to compute value of the γ and subsequently fourth-order differential equation is solved analytically. Eventually, the transverse displacements and bending stresses are obtained and compared for different agglomeration parameters, various boundary conditions simultaneously and variant elastic foundation without requirement to instate values for foundation parameters.

  7. Surveillance of Ocular Parameters and Visual Function in Bed Rest Subjects

    Cromwell, Ronita L.

    2011-01-01

    Recent visual changes in astronauts have raised concern about ocular health during long duration spaceflight. Seven cases have been documented in astronauts who spent 6 months aboard the International Space Station. These astronauts were male ranging in age from 45 to 55 years old. All astronauts exhibited pre- to post flight refractive changes. Decreased intraocular pressure (IOP) post flight was observed in 3 cases. Fundoscopic exams revealed post flight findings of choroidal folds in 4 cases, optic disc edema in 5 cases and the presence of cotton wool spots in 3 cases. Optical coherence tomography (OCT) confirmed findings of choroidal folds and disc edema, and also documented retinal nerve fiber layer thickening (5 cases). Findings from MRI examinations showed posterior globe flattening (5 cases), optic nerve sheath distention (6 cases) and torturous optic nerves (2 cases). Of the 7 cases, intracranial pressure was measured on 4 astronauts. These 4 showed elevated ICP post-flight that remained elevated for as long as 19 months in one case. While the etiology remains unknown, hypotheses speculate that venous insufficiency or hypertension in the brain caused by cephalad fluid shifts during spaceflight are possible mechanisms for ocular changes seen in astronauts. Head-down tilt bed rest is a spaceflight analog that induces cephalad fluid shifts. This study is designed to provide ocular monitoring of bed rest subjects and determine whether clinically relevant changes are found. Ocular Changes

  8. Relationship between Cardiometabolic Parameters and Elevated Resting and Effort Heart Rate in Schoolchildren.

    Silva, Cristiane Fernanda da; Burgos, Miria Suzana; Silva, Priscila Tatiana da; Burgos, Leandro Tibiriçá; Welser, Letícia; Sehn, Ana Paula; Horta, Jorge André; Mello, Elza Daniel de; Reuter, Cézane Priscila

    2017-09-01

    Little has been studied on heart rate and its relationship with metabolic disorders. To identify possible association between heart rate (HR) and metabolic disorders in children and adolescents. This cross-sectional study evaluated 2.098 subjects, aged between 7 and 17 years. The variables evaluated were: HR, systolic (SBP) and diastolic blood pressure (DBP), pulse pressure (PP), double-product (DP), myocardial oxygen consumption (mVO2), lipids, glucose and uric acid levels, body mass index (BMI) and waist circumference (WC). The values of HR at rest and effort were divided into quartiles. The association between continuous values of HR and cardiometabolic indicators was tested by linear regression. LDL cholesterol presented a significantly higher mean (p = 0.003) in schoolchildren with resting HR greater or equal to 91 bpm, compared to students with less than 75 bpm. Compared with the quartiles of effort HR, SBP, DBP, glucose and uric acid presented high values when HR was greater or equal than 185 bpm. SBP, glucose and HDL cholesterol demonstrated a significant association with resting HR. Uric acid was observed as a predictor of increased effort HR. Schoolchildren with a higher resting HR have higher mean of LDL cholesterol. For effort HR, there was an increase in blood pressure, glucose and uric acid levels. Uric acid has been shown to be a predictor of elevated effort HR. Pouco se tem estudado sobre frequência cardíaca e suas relações com alterações metabólicas. Verificar se existe associação entre frequência cardíaca e disfunções metabólicas em crianças e adolescentes. Estudo transversal com 2.098 escolares, com idade entre 7 e 17 anos. As variáveis avaliadas foram: frequência cardíaca (FC), pressão arterial sistólica (PAS), diastólica (PAD) e de pulso (PP), duplo-produto (DP), consumo de oxigênio pelo miocárdio (mVO2), perfil lipídico e glicêmico, níveis de ácido úrico, índice de massa corporal (IMC) e circunferência da cintura

  9. Ten minutes of 1 mA transcranial direct current stimulation was well tolerated by children and adolescents: Self-reports and resting state EEG analysis.

    Moliadze, Vera; Andreas, Saskia; Lyzhko, Ekaterina; Schmanke, Till; Gurashvili, Tea; Freitag, Christine M; Siniatchkin, Michael

    2015-10-01

    Transcranial direct current stimulation (tDCS) is a promising and well-tolerated method of non-invasive brain stimulation, by which cortical excitability can be modulated. However, the effects of tDCS on the developing brain are still unknown, and knowledge about its tolerability in children and adolescents is still lacking. Safety and tolerability of tDCS was assessed in children and adolescents by self-reports and spectral characteristics of electroencephalogram (EEG) recordings. Nineteen typically developing children and adolescents aged 11-16 years participated in the study. Anodal and cathodal tDCS as well as sham stimulation were applied for a duration of 10 min over the left primary motor cortex (M1), each with an intensity of 1 mA. Subjects were unable to identify whether they had received active or sham stimulation, and all participants tolerated the stimulation well with a low rate of adverse events in both groups and no serious adverse events. No pathological oscillations, in particular, no markers of epileptiform activity after 1mA tDCS were detected in any of the EEG analyses. In summary, our study demonstrates that tDCS with 1mA intensity over 10 min is well tolerated, and thus may be used as an experimental and treatment method in the pediatric population. Copyright © 2015 Elsevier Inc. All rights reserved.

  10. Geometrically nonlinear dynamic and static analysis of shallow spherical shell resting on two-parameters elastic foundations

    Civalek, Ö.

    2014-01-01

    In the present study nonlinear static and dynamic responses of shallow spherical shells resting on Winkler–Pasternak elastic foundations are carried out. The formulation of the shells is based on the Donnell theory. The nonlinear governing equations of motion of shallow shells are discretized in space and time domains using the discrete singular convolution and the differential quadrature methods, respectively. The validity of the present method is demonstrated by comparing the present results with those available in the open literature. The effects of the Winkler and Pasternak foundation parameters on nonlinear static and dynamic response of shells are investigated. Some results are also presented for circular plate as special case. Damping effect on nonlinear dynamic response of shells is studied. It is important to state that the increase in damping parameter causes decrease in the dynamic response of the shells. It is shown that the shear parameter of the foundation has a significant influence on the dynamic and static response of the shells. Also, the response of the shell is decreased with the increasing value of the shear parameter of the foundation. Parametric studies considering different geometric variables have also been investigated. -- Highlights: • Nonlinear responses of shallow spherical shells are presented. • The effects of foundation parameters are investigated. • Damping effect on nonlinear dynamic response of shells is also studied

  11. Three-dimensional components of selfhood in treatment-naive patients with major depressive disorder: A resting-state qEEG imaging study.

    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.

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

    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.

  13. An increase in alpha band frequency in resting state EEG after electrical stimulation of the ear in tinnitus patients - a pilot study

    Marzena Mielczarek

    2016-10-01

    Full Text Available In our clinic invasive transtympanal promontory positive DC stimulations were first used, with a success rate of 42%. However, non-invasive hydrotransmissive negative DC stimulations are now favoured, with improvement being obtained in 37.8% directly after the treatment, and 51.3% in a follow up one month after treatment. The further improvement after one month may be due to neuroplastic changes at central level as a result of altered peripheral input. The aim of the study was to determine how a single electrical stimulation of the ear influences cortical activity, and whether changes observed in tinnitus after electrical stimulation are associated with any changes in cortical activity recorded in EEG.The study included 12 tinnitus patients(F–6, M-6 divided into two groups. Group I comprised six patients with unilateral tinnitus - unilateral, ipsilateral ES was performed. Group II comprised six patients with bilateral tinnitus - bilateral ES was performed.Electrical stimulation was performed using a custom-made apparatus.The active, silver probe – was immersed inside the external ear canal filled with saline. The passive electrode was placed on the forehead. The stimulating frequency was 250Hz, the intensity ranged from 0.14 to 1.08 mA. The voltage was kept constant at 3V. The duration of stimulation was four minutes. The EEG recording (Deymed QEST 32 was performed before and after electrical stimulation. We assessed the intensity of tinnitus on the visual analogue scale (1-10. Results.In both groups an improvement in VAS was observed– in group I - in five ears (83.3%, in group II - in seven ears (58.3%. In Group I,a significant increase in the upper and lower limits of the alpha frequency range was observed in the left central temporal and left frontal regions following electrical stimulation. These changes, however, were not correlated with improvement in tinnitus. No significant changes were observed in the beta and theta bands and in

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

    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.

  15. Clusters of Insomnia Disorder: An Exploratory Cluster Analysis of Objective Sleep Parameters Reveals Differences in Neurocognitive Functioning, Quantitative EEG, and Heart Rate Variability

    Miller, Christopher B.; Bartlett, Delwyn J.; Mullins, Anna E.; Dodds, Kirsty L.; Gordon, Christopher J.; Kyle, Simon D.; Kim, Jong Won; D'Rozario, Angela L.; Lee, Rico S.C.; Comas, Maria; Marshall, Nathaniel S.; Yee, Brendon J.; Espie, Colin A.; Grunstein, Ronald R.

    2016-01-01

    Study Objectives: To empirically derive and evaluate potential clusters of Insomnia Disorder through cluster analysis from polysomnography (PSG). We hypothesized that clusters would differ on neurocognitive performance, sleep-onset measures of quantitative (q)-EEG and heart rate variability (HRV). Methods: Research volunteers with Insomnia Disorder (DSM-5) completed a neurocognitive assessment and overnight PSG measures of total sleep time (TST), wake time after sleep onset (WASO), and sleep onset latency (SOL) were used to determine clusters. Results: From 96 volunteers with Insomnia Disorder, cluster analysis derived at least two clusters from objective sleep parameters: Insomnia with normal objective sleep duration (I-NSD: n = 53) and Insomnia with short sleep duration (I-SSD: n = 43). At sleep onset, differences in HRV between I-NSD and I-SSD clusters suggest attenuated parasympathetic activity in I-SSD (P insomnia clusters derived from cluster analysis differ in sleep onset HRV. Preliminary data suggest evidence for three clusters in insomnia with differences for sustained attention and sleep-onset q-EEG. Clinical Trial Registration: Insomnia 100 sleep study: Australia New Zealand Clinical Trials Registry (ANZCTR) identification number 12612000049875. URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=347742. Citation: Miller CB, Bartlett DJ, Mullins AE, Dodds KL, Gordon CJ, Kyle SD, Kim JW, D'Rozario AL, Lee RS, Comas M, Marshall NS, Yee BJ, Espie CA, Grunstein RR. Clusters of Insomnia Disorder: an exploratory cluster analysis of objective sleep parameters reveals differences in neurocognitive functioning, quantitative EEG, and heart rate variability. SLEEP 2016;39(11):1993–2004. PMID:27568796

  16. Changes of Selected Hematological Parameters and Morning Rest Rate during Ten Days High Altitude Stay and Training

    Jiří Suchý

    2015-03-01

    Full Text Available Changes of Selected Hematological Parameters and Morning Rest Rate during Ten Days High Altitude Stay and Training This article describes the influence of a ten day stay and training in a high altitude area (1850 m ASL on selected blood count parameters and morning resting heart rate. Three tests were performed on a group of young cross country skiers (n = 10, age: 18.7 ± 4.8: two days before, two days after and ten days after the altitude training camp. Two day after the return, significant (p 0.05. The study in a group of young cross country skiers has shown positive effects of a tenday training camp in high altitude on blood count parameters and morning resting heart rate monitored in lowland two and ten days after the return from high altitude. Změny vybraných hematologických parametrů a ranní klidové srdeční frekvence v průběhu desetidenního tréninku a pobytu ve vyšší nadmořské výšce Článek popisuje vliv desetidenního tréninku a pobytu ve vyšší nadmořské výšce (1850 m n. m. na vybrané parametry krevního obrazu a ranní klidové srdeční frekvence. U skupiny mladých běžců na lyžích (n = 10, věk: 18,7 ± 4,8 byly realizovány celkem tři odběry krve: dva dny před soustředěním ve výšce, dva dny a deset dnů po návratu do nížiny. Dva dny po návratu byly signifikantně (p 0,05. Průměrné hodnoty ranní klidové srdeční frekvence byly během soustředění ve výšce vyšší než před odjezdem v nížině (p 0,05. Námi realizovaný výzkum u skupiny mladých běžců na lyžích prokázal pozitivní efekt desetidenního pobytu a tréninku ve vyšší nadmořské výšce (1850 m n. m. na sledované krevní parametry a ranní klidovou srdeční frekvenci v nížině po návratu.

  17. Clusters of Insomnia Disorder: An Exploratory Cluster Analysis of Objective Sleep Parameters Reveals Differences in Neurocognitive Functioning, Quantitative EEG, and Heart Rate Variability.

    Miller, Christopher B; Bartlett, Delwyn J; Mullins, Anna E; Dodds, Kirsty L; Gordon, Christopher J; Kyle, Simon D; Kim, Jong Won; D'Rozario, Angela L; Lee, Rico S C; Comas, Maria; Marshall, Nathaniel S; Yee, Brendon J; Espie, Colin A; Grunstein, Ronald R

    2016-11-01

    To empirically derive and evaluate potential clusters of Insomnia Disorder through cluster analysis from polysomnography (PSG). We hypothesized that clusters would differ on neurocognitive performance, sleep-onset measures of quantitative ( q )-EEG and heart rate variability (HRV). Research volunteers with Insomnia Disorder (DSM-5) completed a neurocognitive assessment and overnight PSG measures of total sleep time (TST), wake time after sleep onset (WASO), and sleep onset latency (SOL) were used to determine clusters. From 96 volunteers with Insomnia Disorder, cluster analysis derived at least two clusters from objective sleep parameters: Insomnia with normal objective sleep duration (I-NSD: n = 53) and Insomnia with short sleep duration (I-SSD: n = 43). At sleep onset, differences in HRV between I-NSD and I-SSD clusters suggest attenuated parasympathetic activity in I-SSD (P insomnia clusters derived from cluster analysis differ in sleep onset HRV. Preliminary data suggest evidence for three clusters in insomnia with differences for sustained attention and sleep-onset q -EEG. Insomnia 100 sleep study: Australia New Zealand Clinical Trials Registry (ANZCTR) identification number 12612000049875. URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=347742. © 2016 Associated Professional Sleep Societies, LLC.

  18. Regional Reproducibility of BOLD Calibration Parameter M, OEF and Resting-State CMRO2 Measurements with QUO2 MRI.

    Isabelle Lajoie

    Full Text Available The current generation of calibrated MRI methods goes beyond simple localization of task-related responses to allow the mapping of resting-state cerebral metabolic rate of oxygen (CMRO2 in micromolar units and estimation of oxygen extraction fraction (OEF. Prior to the adoption of such techniques in neuroscience research applications, knowledge about the precision and accuracy of absolute estimates of CMRO2 and OEF is crucial and remains unexplored to this day. In this study, we addressed the question of methodological precision by assessing the regional inter-subject variance and intra-subject reproducibility of the BOLD calibration parameter M, OEF, O2 delivery and absolute CMRO2 estimates derived from a state-of-the-art calibrated BOLD technique, the QUantitative O2 (QUO2 approach. We acquired simultaneous measurements of CBF and R2* at rest and during periods of hypercapnia (HC and hyperoxia (HO on two separate scan sessions within 24 hours using a clinical 3 T MRI scanner. Maps of M, OEF, oxygen delivery and CMRO2, were estimated from the measured end-tidal O2, CBF0, CBFHC/HO and R2*HC/HO. Variability was assessed by computing the between-subject coefficients of variation (bwCV and within-subject CV (wsCV in seven ROIs. All tests GM-averaged values of CBF0, M, OEF, O2 delivery and CMRO2 were: 49.5 ± 6.4 mL/100 g/min, 4.69 ± 0.91%, 0.37 ± 0.06, 377 ± 51 μmol/100 g/min and 143 ± 34 μmol/100 g/min respectively. The variability of parameter estimates was found to be the lowest when averaged throughout all GM, with general trends toward higher CVs when averaged over smaller regions. Among the MRI measurements, the most reproducible across scans was R2*0 (wsCVGM = 0.33% along with CBF0 (wsCVGM = 3.88% and R2*HC (wsCVGM = 6.7%. CBFHC and R2*HO were found to have a higher intra-subject variability (wsCVGM = 22.4% and wsCVGM = 16% respectively, which is likely due to propagation of random measurement errors, especially for CBFHC due to the

  19. The value of radionuclide phase analysis and parameters of cardial function for diagnosis CAD at rest and during exercise

    Huang Gang

    1990-01-01

    27 patients and 5 normal were studied with ECG-gated cardial blood pool images and radionuclide phase analysis at rest and during exercise. The results showed that the sensitivity of LVEF in CAD at rest and during exercise were 57% and 71% respectively, and the sensitivity of the ventricular phase in CAD were 79% at rest and 90% during exercise, and the sensitivity of phase angle in CAD were higher than of LVEF. This suggested that the ventricular phase angle was important for diagnosing early CAD. In addition, regional EF, phase image and ventricular wall motion were useful to detect the lesion of ischemia in CAD

  20. EEG (Electroencephalogram)

    ... 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 ...

  1. Test-retest reliability of cognitive EEG

    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.

  2. EEG frequency PCA in EEG-ERP dynamics.

    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.

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

    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.

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

    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.

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

    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

  6. [Influence Additional Cognitive Tasks on EEG Beta Rhythm Parameters during Forming and Testing Set to Perception of the Facial Expression].

    Yakovenko, I A; Cheremushkin, E A; Kozlov, M K

    2015-01-01

    The research of changes of a beta rhythm parameters on condition of working memory loading by extension of a interstimuli interval between the target and triggering stimuli to 16 sec is investigated on 70 healthy adults in two series of experiments with set to a facial expression. In the second series at the middle of this interval for strengthening of the load was entered the additional cognitive task in the form of conditioning stimuli like Go/NoGo--circles of blue or green color. Data analysis of the research was carried out by means of continuous wavelet-transformation on the basis of "mather" complex Morlet-wavelet in the range of 1-35 Hz. Beta rhythm power was characterized by the mean level, maxima of wavelet-transformation coefficient (WLC) and latent periods of maxima. Introduction of additional cognitive task to pause between the target and triggering stimuli led to essential increase in absolute values of the mean level of beta rhythm WLC and relative sizes of maxima of beta rhythm WLC. In the series of experiments without conditioning stimulus subjects with large number of mistakes (from 6 to 40), i.e. rigid set, in comparison with subjects with small number of mistakes (to 5), i.e. plastic set, at the forming stage were characterized by higher values of the mean level of beta rhythm WLC. Introduction of the conditioning stimuli led to smoothing of intergroup distinctions throughout the experiment.

  7. Radiotelemetry recording of electroencephalogram in piglets during rest.

    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.

  8. Increased theta band EEG power in sickle cell disease patients

    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

  9. Improving the Specificity of EEG for Diagnosing Alzheimer's Disease

    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.

  10. Analysis of Small Muscle Movement Effects on EEG Signals

    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

  11. Reproducibility of heart rate variability parameters measured in healthy subjects at rest and after a postural change maneuver

    E.M. Dantas

    2010-10-01

    Full Text Available Heart rate variability (HRV provides important information about cardiac autonomic modulation. Since it is a noninvasive and inexpensive method, HRV has been used to evaluate several parameters of cardiovascular health. However, the internal reproducibility of this method has been challenged in some studies. Our aim was to determine the intra-individual reproducibility of HRV parameters in short-term recordings obtained in supine and orthostatic positions. Electrocardiographic (ECG recordings were obtained from 30 healthy subjects (20-49 years, 14 men using a digital apparatus (sampling ratio = 250 Hz. ECG was recorded for 10 min in the supine position and for 10 min in the orthostatic position. The procedure was repeated 2-3 h later. Time and frequency domain analyses were performed. Frequency domain included low (LF, 0.04-0.15 Hz and high frequency (HF, 0.15-0.4 Hz bands. Power spectral analysis was performed by the autoregressive method and model order was set at 16. Intra-subject agreement was assessed by linear regression analysis, test of difference in variances and limits of agreement. Most HRV measures (pNN50, RMSSD, LF, HF, and LF/HF ratio were reproducible independent of body position. Better correlation indexes (r > 0.6 were obtained in the orthostatic position. Bland-Altman plots revealed that most values were inside the agreement limits, indicating concordance between measures. Only SDNN and NNv in the supine position were not reproducible. Our results showed reproducibility of HRV parameters when recorded in the same individual with a short time between two exams. The increased sympathetic activity occurring in the orthostatic position probably facilitates reproducibility of the HRV indexes.

  12. EEG data during open heart surgery. Their automatic analysis related to anesthetic parameters and its use in peroperative monitoring of cerebral function

    Simons, A.J.R.; Pronk, R.A.F.

    1982-01-01

    It is generally agreed upon by experts that EEG monitoring of brain function during open heart surgery is of the utmost importance in preventing postoperative neurological and psychopathological consequences. Up to now, however, this monitoring has not been performed on a large scale: (1) it is a

  13. Response of the oxygen uptake efficiency slope to orthotopic heart transplantation: lack of correlation with changes in central hemodynamic parameters and resting lung function.

    Van Laethem, Christophe; Goethals, Marc; Verstreken, Sofie; Walravens, Maarten; Wellens, Francis; De Proft, Margot; Bartunek, Jozef; Vanderheyden, Marc

    2007-09-01

    Recently, a new linear measure of ventilatory response to exercise, the oxygen uptake efficiency slope (OUES), was proposed in the evaluation of heart failure patients. No data are available on the response of the OUES after orthotopic heart transplantation (HTx). Thirty patients who underwent HTx between 1999 and 2003 were included in the study. Data from maximal cardiopulmonary exercise test, resting pulmonary function and hemodynamic assessment were collected before the transplant at time of screening and 1 year after HTx. During the first year after HTx, OUES and normalized OUES for body weight (OUES/kg) increased significantly from 15.6 +/- 4.9 to 19.7 +/- 4.8 (p volumes or capacities and measures of central hemodynamic function after HTx. OUES improved significantly after HTx, but, similar to other exercise parameters, remained considerably impaired. The changes in OUES were highly correlated with the improvements in other exercise variables, but did not correlate with marked improvements in central hemodynamics or resting lung function.

  14. RESTful NET

    Flanders, Jon

    2008-01-01

    RESTful .NET is the first book that teaches Windows developers to build RESTful web services using the latest Microsoft tools. Written by Windows Communication Foundation (WFC) expert Jon Flanders, this hands-on tutorial demonstrates how you can use WCF and other components of the .NET 3.5 Framework to build, deploy and use REST-based web services in a variety of application scenarios. RESTful architecture offers a simpler approach to building web services than SOAP, SOA, and the cumbersome WS- stack. And WCF has proven to be a flexible technology for building distributed systems not necessa

  15. Quality parameters for a multimodal EEG/EMG/kinematic brain-computer interface (BCI aiming to suppress neurological tremor in upper limbs [v2; ref status: indexed, http://f1000r.es/3aq

    Giuliana Grimaldi

    2014-04-01

    Full Text Available Tremor is the most common movement disorder encountered during daily neurological practice. Tremor in the upper limbs causes functional disability and social inconvenience, impairing daily life activities. The response of tremor to pharmacotherapy is variable. Therefore, a combination of drugs is often required. Surgery is considered when the response to medications is not sufficient. However, about one third of patients are refractory to current treatments. New bioengineering therapies are emerging as possible alternatives. Our study was carried out in the framework of the European project “Tremor” (ICT-2007-224051. The main purpose of this challenging project was to develop and validate a new treatment for upper limb tremor based on the combination of functional electrical stimulation (FES; which has been shown to reduce upper limb tremor with a brain-computer interface (BCI. A BCI-driven detection of voluntary movement is used to trigger FES in a closed-loop approach. Neurological tremor is detected using a matrix of EMG electrodes and inertial sensors embedded in a wearable textile. The identification of the intentionality of movement is a critical aspect to optimize this complex system. We propose a multimodal detection of the intentionality of movement by fusing signals from EEG, EMG and kinematic sensors (gyroscopes and accelerometry. Parameters of prediction of movement are extracted in order to provide global prediction plots and trigger FES properly. In particular, quality parameters (QPs for the EEG signals, corticomuscular coherence and event-related desynchronization/synchronization (ERD/ERS parameters are combined in an original algorithm which takes into account the refractoriness/responsiveness of tremor. A simulation study of the relationship between the threshold of ERD/ERS of artificial EEG traces and the QPs is also provided. Very interestingly, values of QPs were much greater than those obtained for the corticomuscular

  16. Memories of attachment hamper EEG cortical connectivity in dissociative patients.

    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.

  17. A new chronobiological approach to discriminate between acute and chronic depression using peripheral temperature, rest-activity, and light exposure parameters.

    Ávila Moraes, Cláudia; Cambras, Trinitat; Diez-Noguera, Antoni; Schimitt, Regina; Dantas, Giovana; Levandovski, Rosa; Hidalgo, Maria Paz

    2013-03-09

    Circadian theories for major depressive disorder have suggested that the rhythm of the circadian pacemaker is misaligned. Stable phase relationships between internal rhythms, such as temperature and rest/activity, and the external day-night cycle, are considered to be crucial for adapting to life in the external environmental. Therefore, the relationship and possible alterations among (i) light exposure, (ii) activity rhythm, and (iii) temperature rhythm could be important factors in clinical depression. This study aimed to investigate the rhythmic alterations in depression and evaluate the ability of chronobiological parameters to discriminate between healthy subjects and depressed patients. Thirty female subjects, including healthy subjects, depressed patients in the first episode, and major recurrent depression patients. Symptoms were assessed using Hamilton Depression Scale, Beck Depression Inventory and Montgomery-Äsberg Scale. Motor activity, temperature, and light values were determined for 7 days by actigraph, and circadian rhythms were calculated. Depressed groups showed a lower amplitude in the circadian rhythm of activity and light exposure, but a higher amplitude in the rhythm of peripheral temperature. The correlation between temperature and activity values was different in the day and night among the control and depressed groups. For the same level of activity, depressed patients had lowest temperature values during the day. The amplitudes of temperature and activity were the highest discriminant parameters. These results indicate that the study of rhythms is useful for diagnosis and therapy for depressive mood disorders.

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

    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.

  19. Meditation and the EEG

    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...

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

    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…

  1. Mobile EEG in epilepsy

    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

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

    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.

  3. The effect of multi-directional nanocomposite materials on the vibrational response of thick shell panels with finite length and rested on two-parameter elastic foundations

    Tahouneh, Vahid; Naei, Mohammad Hasan

    2016-03-01

    The main purpose of this paper is to investigate the effect of bidirectional continuously graded nanocomposite materials on free vibration of thick shell panels rested on elastic foundations. The elastic foundation is considered as a Pasternak model after adding a shear layer to the Winkler model. The panels reinforced by randomly oriented straight single-walled carbon nanotubes are considered. The volume fractions of SWCNTs are assumed to be graded not only in the radial direction, but also in axial direction of the curved panel. This study presents a 2-D six-parameter power-law distribution for CNTs volume fraction of 2-D continuously graded nanocomposite that gives designers a powerful tool for flexible designing of structures under multi-functional requirements. The benefit of using generalized power-law distribution is to illustrate and present useful results arising from symmetric, asymmetric and classic profiles. The material properties are determined in terms of local volume fractions and material properties by Mori-Tanaka scheme. The 2-D differential quadrature method as an efficient numerical tool is used to discretize governing equations and to implement boundary conditions. The fast rate of convergence of the method is shown and results are compared against existing results in literature. Some new results for natural frequencies of the shell are prepared, which include the effects of elastic coefficients of foundation, boundary conditions, material and geometrical parameters. The interesting results indicate that a graded nanocomposite volume fraction in two directions has a higher capability to reduce the natural frequency than conventional 1-D functionally graded nanocomposite materials.

  4. Atypical Laterality of Resting Gamma Oscillations in Autism Spectrum Disorders

    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…

  5. The Mozart Effect: A quantitative EEG study.

    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.

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

    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...

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

    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.

  8. Information-Theoretical Analysis of EEG Microstate Sequences in Python

    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.

  9. EEG and Coma.

    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.

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

    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.

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

    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…

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

    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

  13. EEG activity during estral cycle in the rat.

    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.

  14. EEG: Origin and measurement

    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

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

    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

  16. Infraslow Electroencephalographic and Dynamic Resting State Network Activity.

    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.

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

    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.

  18. EEG source imaging during two Qigong meditations.

    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.

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

    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

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

    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.

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

    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.

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

    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.

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

    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

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

    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.

  5. EEG Controlled Wheelchair

    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.

  6. Comparison of a parent-rated DSM-IV measure of attention-deficit/hyperactivity disorder and quantitative EEG parameters in an outpatient sample of children.

    Coolidge, Frederick L; Starkey, Michael T; Cahill, Brian S

    2007-08-01

    Attention-deficit/hyperactivity disorder (ADHD) was investigated using the parent-as-respondent, 200-item, Coolidge Personality and Neuropsychology Inventory (CPNI) and a quantitative electroencephalograph (QEEG). Parents of 183 children (mean age = 12.2 years) brought to an outpatient private clinic for behavioral and/or emotional problems completed the CPNI including the 18-item DSM-IV-based ADHD scale and their children were also evaluated by QEEG. The correlation between the CPNI ADHD scale T score and the categorical QEEG parameter (based on the beta-theta power ratio) for the identification of ADHD was r = -0.15. Using a dichotomous ADHD CPNI measure (positive/negative) and the QEEG beta-theta power ratio resulted in an r value of -0.09. The sensitivity of the QEEG ADHD parameter and the CPNI ADHD scale was 50% and the specificity was 36%. The results stand in contrast to those of who found 90% sensitivity and 94% specificity between behavioral measures of ADHD and the QEEG scanning procedure. The lack of correspondence between the two measures is discussed.

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

    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.

  8. Pharmaco-EEG Studies in Animals: A History-Based Introduction to Contemporary Translational Applications.

    Drinkenburg, Wilhelmus H I M; Ahnaou, Abdallah; Ruigt, Gé S F

    2015-01-01

    Current research on the effects of pharmacological agents on human neurophysiology finds its roots in animal research, which is also reflected in contemporary animal pharmaco-electroencephalography (p-EEG) applications. The contributions, present value and translational appreciation of animal p-EEG-based applications are strongly interlinked with progress in recording and neuroscience analysis methodology. After the pioneering years in the late 19th and early 20th century, animal p-EEG research flourished in the pharmaceutical industry in the early 1980s. However, around the turn of the millennium the emergence of structurally and functionally revealing imaging techniques and the increasing application of molecular biology caused a temporary reduction in the use of EEG as a window into the brain for the prediction of drug efficacy. Today, animal p-EEG is applied again for its biomarker potential - extensive databases of p-EEG and polysomnography studies in rats and mice hold EEG signatures of a broad collection of psychoactive reference and test compounds. A multitude of functional EEG measures has been investigated, ranging from simple spectral power and sleep-wake parameters to advanced neuronal connectivity and plasticity parameters. Compared to clinical p-EEG studies, where the level of vigilance can be well controlled, changes in sleep-waking behaviour are generally a prominent confounding variable in animal p-EEG studies and need to be dealt with. Contributions of rodent pharmaco-sleep EEG research are outlined to illustrate the value and limitations of such preclinical p-EEG data for pharmacodynamic and chronopharmacological drug profiling. Contemporary applications of p-EEG and pharmaco-sleep EEG recordings in animals provide a common and relatively inexpensive window into the functional brain early in the preclinical and clinical development of psychoactive drugs in comparison to other brain imaging techniques. They provide information on the impact of

  9. Predictive value of EEG in postanoxic encephalopathy: A quantitative model-based approach.

    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.

  10. Hypnagogic imagery and EEG activity.

    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.

  11. Analysis and correction of ballistocardiogram contamination of EEG recordings in MR

    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.)

  12. Torsional Post-Buckling of a Simply Supported Thin-Walled Open-Section Beam Resting on a Two-Parameter Foundation

    Rao, Ch. K.; Rao, L. B.

    2018-01-01

    The problem of the post-buckling response of a simply supported thin-walled beam subjected to an axial compressive load and supported by the Winkler-Pasternak foundation is studied in this paper. The strains are assumed to be small and elastic. The shear deformations and the in-plane cross-sectional deformations are assumed to be negligible. The post-buckling paths of the simply supported beam are determined for different values of the Winkler and Pasternak stiffness parameters. Bifurcation points are found.

  13. THE HYPERFINE STRUCTURE OF THE ROTATIONAL SPECTRUM OF HDO AND ITS EXTENSION TO THE THz REGION: ACCURATE REST FREQUENCIES AND SPECTROSCOPIC PARAMETERS FOR ASTROPHYSICAL OBSERVATIONS

    Cazzoli, Gabriele; Lattanzi, Valerio; Puzzarini, Cristina [Dipartimento di Chimica “Giacomo Ciamician”, Università di Bologna, Via Selmi 2, I-40126 Bologna (Italy); Alonso, José Luis [Grupo de Espectroscopía Molecular (GEM), Unidad Asociada CSIC, Edificio Quifima, Laboratorios de Espectroscopia y Bioespectroscopia, Parque Científico UVa, Universidad de Valladolid, E-47005 Valladolid (Spain); Gauss, Jürgen, E-mail: cristina.puzzarini@unibo.it [Institut für Physikalische Chemie, Universität Mainz, D-55099 Mainz (Germany)

    2015-06-10

    The rotational spectrum of the mono-deuterated isotopologue of water, HD{sup 16}O, has been investigated in the millimeter- and submillimeter-wave frequency regions, up to 1.6 THz. The Lamb-dip technique has been exploited to obtain sub-Doppler resolution and to resolve the hyperfine (hf) structure due to the deuterium and hydrogen nuclei, thus enabling the accurate determination of the corresponding hf parameters. Their experimental determination has been supported by high-level quantum-chemical calculations. The Lamb-dip measurements have been supplemented by Doppler-limited measurements (weak high-J and high-frequency transitions) in order to extend the predictive capability of the available spectroscopic constants. The possibility of resolving hf splittings in astronomical spectra has been discussed.

  14. REST based mobile applications

    Rambow, Mark; Preuss, Thomas; Berdux, Jörg; Conrad, Marc

    2008-02-01

    Simplicity is the major advantage of REST based webservices. Whereas SOAP is widespread in complex, security sensitive business-to-business aplications, REST is widely used for mashups and end-user centric applicatons. In that context we give an overview of REST and compare it to SOAP. Furthermore we apply the GeoDrawing application as an example for REST based mobile applications and emphasize on pros and cons for the use of REST in mobile application scenarios.

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

    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.

  16. Illumination influences working memory: an EEG study.

    Park, Jin Young; Min, Byoung-Kyong; Jung, Young-Chul; Pak, Hyensou; Jeong, Yeon-Hong; Kim, Eosu

    2013-09-05

    Illumination conditions appear to influence working efficacy in everyday life. In the present study, we obtained electroencephalogram (EEG) correlates of working-memory load, and investigated how these waveforms are modulated by illumination conditions. We hypothesized that illumination conditions may affect cognitive performance. We designed an EEG study to monitor and record participants' EEG during the Sternberg working memory task under four different illumination conditions. Illumination conditions were generated with a factorial design of two color-temperatures (3000 and 7100 K) by two illuminance levels (150 and 700 lx). During a working memory task, we observed that high illuminance led to significantly lower frontal EEG theta activity than did low illuminance. These differences persisted despite no significant difference in task performance between illumination conditions. We found that the latency of an early event-related potential component, such as N1, was significantly modulated by the illumination condition. The fact that the illumination condition affects brain activity but not behavioral performance suggests that the lighting conditions used in the present study did not influence the performance stage of behavioral processing. Nevertheless, our findings provide objective evidence that illumination conditions modulate brain activity. Further studies are necessary to refine the optimal lighting parameters for facilitating working memory. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

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

    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.

  18. [EEG-markers of vertical postural organization in healthy persons].

    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.

  19. Do resting brain dynamics predict oddball evoked-potential?

    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.

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

    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...

  1. EEG-based characterization of flicker perception

    Lazo, M.; Tsoneva, T.; Garcia Molina, G.

    2013-01-01

    Steady-State Visual Evoked Potential (SSVEP) is an oscillatory electrical response appearing in the electroencephalogram (EEG) in response to flicker stimulation. The SSVEP manifests more prominently in electrodes located near the visual cortex and has oscillatory components at the stimulation frequency and/or harmonics. The phase and amplitude of the SSVEP are sensitive to stimulus parameters such as frequency, modu-lation depth, and spatial frequency. Research related to SSVEP and the human...

  2. Diagnostic Accuracy of microEEG: A Miniature, Wireless EEG Device

    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. ...

  3. EEG analyses with SOBI.

    Glickman, Matthew R.; Tang, Akaysha (University of New Mexico, Albuquerque, NM)

    2009-02-01

    The motivating vision behind Sandia's MENTOR/PAL LDRD project has been that of systems which use real-time psychophysiological data to support and enhance human performance, both individually and of groups. Relevant and significant psychophysiological data being a necessary prerequisite to such systems, this LDRD has focused on identifying and refining such signals. The project has focused in particular on EEG (electroencephalogram) data as a promising candidate signal because it (potentially) provides a broad window on brain activity with relatively low cost and logistical constraints. We report here on two analyses performed on EEG data collected in this project using the SOBI (Second Order Blind Identification) algorithm to identify two independent sources of brain activity: one in the frontal lobe and one in the occipital. The first study looks at directional influences between the two components, while the second study looks at inferring gender based upon the frontal component.

  4. Automated approach to detecting behavioral states using EEG-DABS

    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.

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

    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

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

    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

  7. Quantitative change of EEG and respiration signals during mindfulness meditation

    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

  8. Rett syndrome: EEG presentation.

    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.

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

    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.

  10. Categorisation of Mobile EEG: A Researcher’s Perspective

    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.

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

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

    2016-04-01

    Head motions during functional magnetic resonance imaging (fMRI) impair fMRI data quality and introduce systematic artifacts that can affect interpretation of fMRI results. Electroencephalography (EEG) recordings performed simultaneously with fMRI provide high-temporal-resolution information about ongoing brain activity as well as head movements. Recently, an EEG-assisted retrospective motion correction (E-REMCOR) method was introduced. E-REMCOR utilizes EEG motion artifacts to correct the effects of head movements in simultaneously acquired fMRI data on a slice-by-slice basis. While E-REMCOR is an efficient motion correction approach, it involves an independent component analysis (ICA) of the EEG data and identification of motion-related ICs. Here we report an automated implementation of E-REMCOR, referred to as aE-REMCOR, which we developed to facilitate the application of E-REMCOR in large-scale EEG-fMRI studies. The aE-REMCOR algorithm, implemented in MATLAB, enables an automated preprocessing of the EEG data, an ICA decomposition, and, importantly, an automatic identification of motion-related ICs. aE-REMCOR has been used to perform retrospective motion correction for 305 fMRI datasets from 16 subjects, who participated in EEG-fMRI experiments conducted on a 3T MRI scanner. Performance of aE-REMCOR has been evaluated based on improvement in temporal signal-to-noise ratio (TSNR) of the fMRI data, as well as correction efficiency defined in terms of spike reduction in fMRI motion parameters. The results show that aE-REMCOR is capable of substantially reducing head motion artifacts in fMRI data. In particular, when there are significant rapid head movements during the scan, a large TSNR improvement and high correction efficiency can be achieved. Depending on a subject's motion, an average TSNR improvement over the brain upon the application of aE-REMCOR can be as high as 27%, with top ten percent of the TSNR improvement values exceeding 55%. The average

  12. Alternative REST Splicing Underappreciated

    Chen, Guo-Lin; Miller, Gregory

    2017-01-01

    As a major orchestrator of the cellular epigenome, the repressor element-1 silencing transcription factor (REST) can either repress or activate thousands of genes depending on cellular context, suggesting a highly context-dependent REST function tuned by environmental cues. While REST shows cell-type non-selective active transcription, an N-terminal REST4 isoform caused by alternative splicing - inclusion of an extra exon (N3c) which introduces a pre-mature stop codon - has been implicated in...

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

    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

  14. Analysis of correlation between white matter changes and functional responses in thalamic stroke: a DTI & EEG study.

    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

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

    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

  16. Functional neural network analysis in frontotemporal dementia and Alzheimer's disease using EEG and graph theory

    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.

  17. EEG dynamical correlates of focal and diffuse causes of coma.

    Kafashan, MohammadMehdi; Ryu, Shoko; Hargis, Mitchell J; Laurido-Soto, Osvaldo; Roberts, Debra E; Thontakudi, Akshay; Eisenman, Lawrence; Kummer, Terrance T; Ching, ShiNung

    2017-11-15

    Rapidly determining the causes of a depressed level of consciousness (DLOC) including coma is a common clinical challenge. Quantitative analysis of the electroencephalogram (EEG) has the potential to improve DLOC assessment by providing readily deployable, temporally detailed characterization of brain activity in such patients. While used commonly for seizure detection, EEG-based assessment of DLOC etiology is less well-established. As a first step towards etiological diagnosis, we sought to distinguish focal and diffuse causes of DLOC through assessment of temporal dynamics within EEG signals. We retrospectively analyzed EEG recordings from 40 patients with DLOC with consensus focal or diffuse culprit pathology. For each recording, we performed a suite of time-series analyses, then used a statistical framework to identify which analyses (features) could be used to distinguish between focal and diffuse cases. Using cross-validation approaches, we identified several spectral and non-spectral EEG features that were significantly different between DLOC patients with focal vs. diffuse etiologies, enabling EEG-based classification with an accuracy of 76%. Our findings suggest that DLOC due to focal vs. diffuse injuries differ along several electrophysiological parameters. These results may form the basis of future classification strategies for DLOC and coma that are more etiologically-specific and therefore therapeutically-relevant.

  18. A three domain covariance framework for EEG/MEG data.

    Roś, Beata P; Bijma, Fetsje; de Gunst, Mathisca C M; de Munck, Jan C

    2015-10-01

    In this paper we introduce a covariance framework for the analysis of single subject EEG and MEG data that takes into account observed temporal stationarity on small time scales and trial-to-trial variations. We formulate a model for the covariance matrix, which is a Kronecker product of three components that correspond to space, time and epochs/trials, and consider maximum likelihood estimation of the unknown parameter values. An iterative algorithm that finds approximations of the maximum likelihood estimates is proposed. Our covariance model is applicable in a variety of cases where spontaneous EEG or MEG acts as source of noise and realistic noise covariance estimates are needed, such as in evoked activity studies, or where the properties of spontaneous EEG or MEG are themselves the topic of interest, like in combined EEG-fMRI experiments in which the correlation between EEG and fMRI signals is investigated. We use a simulation study to assess the performance of the estimator and investigate the influence of different assumptions about the covariance factors on the estimated covariance matrix and on its components. We apply our method to real EEG and MEG data sets. Copyright © 2015 Elsevier Inc. All rights reserved.

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

    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.

  20. INTELLIGENT EEG ANALYSIS

    M. Murugesan

    2011-04-01

    Full Text Available Brain is the wonderful organ of human body. It is the agent of information collection and transformation. The neural activity of the human brain starts between the 17th and 23rd week of prenatal development. It is believed that from this early stage and throughout life electrical signals are generated by the brain function but also the status of the whole body. Understanding of neuronal functions and neurophysiologic properties of the brain function together with the mechanisms underlying the generation of signals and their recording is, however, vital for those who deal with these signals for detection, diagnosis, and treatment of brain disorders and the related diseases. This research paper concentrated only on brain tumor detection. Using minimum electrode location the brain tumor possibility is detected. This paper is separated into two parts: the First part deals with electrode location on the scalp and the second part deals with how the fuzzy logic rule based algorithm is applied for estimation of brain tumor from EEG. Basically 8 locations are identified. After acquiring the pure EEG signal Fuzzy Logic Rule is applied to predict the possibility of brain tumor.

  1. The effect of hypobaric hypoxia on multichannel EEG signal complexity.

    Papadelis, Christos; Kourtidou-Papadeli, Chrysoula; Bamidis, Panagiotis D; Maglaveras, Nikos; Pappas, Konstantinos

    2007-01-01

    The objective of this study was the development and evaluation of nonlinear electroencephalography parameters which assess hypoxia-induced EEG alterations, and describe the temporal characteristics of different hypoxic levels' residual effect upon the brain electrical activity. Multichannel EEG, pO2, pCO2, ECG, and respiration measurements were recorded from 10 subjects exposed to three experimental conditions (100% oxygen, hypoxia, recovery) at three-levels of reduced barometric pressure. The mean spectral power of EEG under each session and altitude were estimated for the standard bands. Approximate Entropy (ApEn) of EEG segments was calculated, and the ApEn's time-courses were smoothed by a moving average filter. On the smoothed diagrams, parameters were defined. A significant increase in total power and power of theta and alpha bands was observed during hypoxia. Visual interpretation of ApEn time-courses revealed a characteristic pattern (decreasing during hypoxia and recovering after oxygen re-administration). The introduced qEEG parameters S1 and K1 distinguished successfully the three hypoxic conditions. The introduced parameters based on ApEn time-courses are assessing reliably and effectively the different hypoxic levels. ApEn decrease may be explained by neurons' functional isolation due to hypoxia since decreased complexity corresponds to greater autonomy of components, although this interpretation should be further supported by electrocorticographic animal studies. The introduced qEEG parameters seem to be appropriate for assessing the hypoxia-related neurophysiological state of patients in the hyperbaric chambers in the treatment of decompression sickness, carbon dioxide poisoning, and mountaineering.

  2. EEG correlates of a mental arithmetic task in patients with first episode schizophrenia and schizoaffective disorder.

    Garakh, Zhanna; Zaytseva, Yuliya; Kapranova, Alexandra; Fiala, Ondrej; Horacek, Jiri; Shmukler, Alexander; Gurovich, Isaac Ya; Strelets, Valeria B

    2015-11-01

    To evaluate the spectral power of the cortical bands in patients with first episode schizophrenia and schizoaffective disorder at rest and during the performance of a mental arithmetic task. We analyzed EEG spectral power (SP) in the resting state and subsequently while counting down from 200 in steps of 7, in 32 first episode schizophrenia patients (SZ), 32 patients with first episode schizoaffective disorder (SA) and healthy controls (HC, n=40). Behavioral parameters such as accuracy and counting speed were also evaluated. Both SZ and SA patients were slower in counting than HC, no difference was obtained in the accuracy and counting speed in the patient groups. In the resting state patients showed elevated midline theta power, off-midline anterior beta 2 power and decreased central/posterior alpha power. The SA group occupied an intermediate position between the schizophrenia patients and controls. In task performance patients lacked a typical increase of midline theta, left anterior beta 2, and anterior gamma power; however, schizoaffective patients demonstrated a growing trend of power in the gamma band in left anterior off-midline sites similar to HC. Moreover, alpha power was less inhibited in schizoaffective patients and more pronounced in schizophrenia patients indicating distinct inhibitory mechanisms in these psychotic disorders. Patients with SA demonstrate less alteration in the spectral power of bands at rest than SZ, and present spectral power changes during cognitive task performance close to the controls. Our study contributes to the present evidence on the neurophysiological distinction between schizophrenia and schizoaffective disorder. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  3. Educational simulation of the electroencephalogram (EEG)

    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

  4. EEG in connection with coma.

    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.

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

    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.

  6. Electroencephalogy (EEG) Feedback in Decision-Making

    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

  7. Reproducible localization of interictal epileptiform discharges using EEG-triggered fMRI

    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)

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

    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

  9. RESTful Web Services Cookbook

    Allamaraju, Subbu

    2010-01-01

    While the REST design philosophy has captured the imagination of web and enterprise developers alike, using this approach to develop real web services is no picnic. This cookbook includes more than 100 recipes to help you take advantage of REST, HTTP, and the infrastructure of the Web. You'll learn ways to design RESTful web services for client and server applications that meet performance, scalability, reliability, and security goals, no matter what programming language and development framework you use. Each recipe includes one or two problem statements, with easy-to-follow, step-by-step i

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

    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.

  11. Physiological artifacts in scalp EEG and ear-EEG.

    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.

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

    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

  13. EEG controls for detecting the recurrence of supratentorial gliomas

    Leblhuber, F.; Olschowski, A.; Deisenhammer, E.; Hammer, B.; Knauer, W.

    1984-01-01

    The purpose of this study was to find out the value of postoperative EEG controls in the early detection of recurrence of supratentorial gliomas (the majority being astrocytomas, stage II to IV). 29 cases with verified tumour recurrence were examined and in all but one the EEG showed a reactivation of the focus in accordance with the development of the glioma. At least one of the following parameters had to be established: 1. a further spreading of the focal changes, 2. a reduction in frequency, 3. an increase in amplitudes and 4. focal depression and amplitudes. At least 3 postoperative EEG controls were made in each case. The duration of tumour treatment was 3 to 59 months. In 3 cases temporary focus activation was found without evidence of tumour recurrence; in one of these cases the activation was preceded by an epileptic seizure. Epileptic seizures, thus, seem to have a focus activating effect. Focus activation as a result of radiotherapy or cytostatic treatment was not observed. On the basis of our findings it appears that regularly conducted postoperative EEG controls seem to be highly suited as a non-invasive and economical method for the early detection of recurrence of this type of tumour. In the case of malignant types of gliomas involving rapid growth EEG controls should be made monthly. (Author)

  14. Analysis of tractable distortion metrics for EEG compression applications

    Bazán-Prieto, Carlos; Blanco-Velasco, Manuel; Cruz-Roldán, Fernando; Cárdenas-Barrera, Julián

    2012-01-01

    Coding distortion in lossy electroencephalographic (EEG) signal compression methods is evaluated through tractable objective criteria. The percentage root-mean-square difference, which is a global and relative indicator of the quality held by reconstructed waveforms, is the most widely used criterion. However, this parameter does not ensure compliance with clinical standard guidelines that specify limits to allowable noise in EEG recordings. As a result, expert clinicians may have difficulties interpreting the resulting distortion of the EEG for a given value of this parameter. Conversely, the root-mean-square error is an alternative criterion that quantifies distortion in understandable units. In this paper, we demonstrate that the root-mean-square error is better suited to control and to assess the distortion introduced by compression methods. The experiments conducted in this paper show that the use of the root-mean-square error as target parameter in EEG compression allows both clinicians and scientists to infer whether coding error is clinically acceptable or not at no cost for the compression ratio. (paper)

  15. Joint optimization of algorithmic suites for EEG analysis.

    Santana, Eder; Brockmeier, Austin J; Principe, Jose C

    2014-01-01

    Electroencephalogram (EEG) data analysis algorithms consist of multiple processing steps each with a number of free parameters. A joint optimization methodology can be used as a wrapper to fine-tune these parameters for the patient or application. This approach is inspired by deep learning neural network models, but differs because the processing layers for EEG are heterogeneous with different approaches used for processing space and time. Nonetheless, we treat the processing stages as a neural network and apply backpropagation to jointly optimize the parameters. This approach outperforms previous results on the BCI Competition II - dataset IV; additionally, it outperforms the common spatial patterns (CSP) algorithm on the BCI Competition III dataset IV. In addition, the optimized parameters in the architecture are still interpretable.

  16. Improving Generalization Based on l1-Norm Regularization for EEG-Based Motor Imagery Classification

    Yuwei Zhao

    2018-05-01

    Full Text Available Multichannel electroencephalography (EEG is widely used in typical brain-computer interface (BCI systems. In general, a number of parameters are essential for a EEG classification algorithm due to redundant features involved in EEG signals. However, the generalization of the EEG method is often adversely affected by the model complexity, considerably coherent with its number of undetermined parameters, further leading to heavy overfitting. To decrease the complexity and improve the generalization of EEG method, we present a novel l1-norm-based approach to combine the decision value obtained from each EEG channel directly. By extracting the information from different channels on independent frequency bands (FB with l1-norm regularization, the method proposed fits the training data with much less parameters compared to common spatial pattern (CSP methods in order to reduce overfitting. Moreover, an effective and efficient solution to minimize the optimization object is proposed. The experimental results on dataset IVa of BCI competition III and dataset I of BCI competition IV show that, the proposed method contributes to high classification accuracy and increases generalization performance for the classification of MI EEG. As the training set ratio decreases from 80 to 20%, the average classification accuracy on the two datasets changes from 85.86 and 86.13% to 84.81 and 76.59%, respectively. The classification performance and generalization of the proposed method contribute to the practical application of MI based BCI systems.

  17. Lifespan Differences in Nonlinear Dynamics during Rest and Auditory Oddball Performance

    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…

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

    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.

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

    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.

  20. Resting-state beta and gamma activity in Internet addiction.

    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.

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

    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.

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

    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

  3. Engagement Assessment Using EEG Signals

    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.

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

    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

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

    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

  6. Objective Audiometry using Ear-EEG

    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...

  7. Hypnagogic EEG stages and polysomnogram

    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,...

  8. Psychogenic non-epileptic seizures: our video-EEG experience.

    Nežádal, Tomáš; Hovorka, Jiří; Herman, Erik; Němcová, Iveta; Bajaček, Michal; Stichová, Eva

    2011-09-01

    The aim of our study was to assess the number of psychogenic non-epileptic seizures (PNES) in our patients with a refractory seizure disorder, to determine the 'typical' PNES semiology using video-EEG monitoring and describe other PNES parameters. We evaluated prospectively 596 patients with pharmacoresistant seizures. All these patients underwent continuous video-EEG monitoring. In consenting patients, we used suggestive seizure provocation. We assessed seizure semiology, interictal EEG, brain MRI, psychiatric co-morbidities, personality profiles, and seizure outcome. In the sample of 596 monitored patients, we detected 111 (19.3%) patients with PNES. Of the 111 patients with PNES, 86.5% had spontaneous and 76.5% had provoked seizures. The five most typical symptoms were: initially closed eyelids (67.6%), rapid tremor (47.7%), asynchronous limb movement (37.8%), preictal pseudosleep (33.3%), and side-to-side head movement (32.4%). Interictal EEG was rated as abnormal in 46.2% and with epileptiform abnormality in 9%. Brain MRI was abnormal in 32 (28.8%) patients. Personality disorders (46.8%), anxiety (39.6%), and depression (12.6%) were the most frequent additional psychiatric co-morbidities. PNES outcome after at least 2 years is reported; 22.5% patients was seizure-free; one-third had markedly reduced seizure frequency. We have not seen any negative impact of the provocative testing on the seizure outcome. Video-EEG monitoring with suggestive seizure provocation supported by clinical psychiatric and psychological evaluation significantly contributes to the correct PNES diagnosis, while interictal EEG and brain MRI are frequently abnormal. Symptoms typical for PNES, as opposed to epileptic seizures, could be distinguished.

  9. The effect of epoch length on estimated EEG functional connectivity and brain network organisation

    Fraschini, Matteo; Demuru, Matteo; Crobe, Alessandra; Marrosu, Francesco; Stam, Cornelis J.; Hillebrand, Arjan

    2016-06-01

    Objective. Graph theory and network science tools have revealed fundamental mechanisms of functional brain organization in resting-state M/EEG analysis. Nevertheless, it is still not clearly understood how several methodological aspects may bias the topology of the reconstructed functional networks. In this context, the literature shows inconsistency in the chosen length of the selected epochs, impeding a meaningful comparison between results from different studies. Approach. The aim of this study was to provide a network approach insensitive to the effects that epoch length has on functional connectivity and network reconstruction. Two different measures, the phase lag index (PLI) and the amplitude envelope correlation (AEC) were applied to EEG resting-state recordings for a group of 18 healthy volunteers using non-overlapping epochs with variable length (1, 2, 4, 6, 8, 10, 12, 14 and 16 s). Weighted clustering coefficient (CCw), weighted characteristic path length (L w) and minimum spanning tree (MST) parameters were computed to evaluate the network topology. The analysis was performed on both scalp and source-space data. Main results. Results from scalp analysis show a decrease in both mean PLI and AEC values with an increase in epoch length, with a tendency to stabilize at a length of 12 s for PLI and 6 s for AEC. Moreover, CCw and L w show very similar behaviour, with metrics based on AEC more reliable in terms of stability. In general, MST parameters stabilize at short epoch lengths, particularly for MSTs based on PLI (1-6 s versus 4-8 s for AEC). At the source-level the results were even more reliable, with stability already at 1 s duration for PLI-based MSTs. Significance. The present work suggests that both PLI and AEC depend on epoch length and that this has an impact on the reconstructed network topology, particularly at the scalp-level. Source-level MST topology is less sensitive to differences in epoch length, therefore enabling the comparison of brain

  10. A Pervasive Approach to EEG-Based Depression Detection

    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.

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

    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

  12. REST based service composition

    Grönvall, Erik; Ingstrup, Mads; Pløger, Morten

    2011-01-01

    This paper presents an ongoing work developing and testing a Service Composition framework based upon the REST architecture named SECREST. A minimalistic approach have been favored instead of a creating a complete infrastructure. One focus has been on the system's interaction model. Indeed, an aim...

  13. The FNS-based analyzing the EEG to diagnose the bipolar affective disorder

    Panischev, Yu; Panischeva, S N; Demin, S A

    2015-01-01

    Here we demonstrate a capability of method based on the Flicker-Noise Spectroscopy (FNS) in analyzing the manifestation bipolar affective disorder (BAD) in EEG. Generally EEG from BAD patient does not show the visual differences from healthy EEG. Analyzing the behavior of FNS-parameters and the structure of 3D-cross correlators allows to discover the differential characteristics of BAD. The cerebral cortex electric activity of BAD patients have a specific collective dynamics and configuration of the FNS-characteristics in comparison with healthy subjects. (paper)

  14. Automatic EEG spike detection.

    Harner, Richard

    2009-10-01

    Since the 1970s advances in science and technology during each succeeding decade have renewed the expectation of efficient, reliable automatic epileptiform spike detection (AESD). But even when reinforced with better, faster tools, clinically reliable unsupervised spike detection remains beyond our reach. Expert-selected spike parameters were the first and still most widely used for AESD. Thresholds for amplitude, duration, sharpness, rise-time, fall-time, after-coming slow waves, background frequency, and more have been used. It is still unclear which of these wave parameters are essential, beyond peak-peak amplitude and duration. Wavelet parameters are very appropriate to AESD but need to be combined with other parameters to achieve desired levels of spike detection efficiency. Artificial Neural Network (ANN) and expert-system methods may have reached peak efficiency. Support Vector Machine (SVM) technology focuses on outliers rather than centroids of spike and nonspike data clusters and should improve AESD efficiency. An exemplary spike/nonspike database is suggested as a tool for assessing parameters and methods for AESD and is available in CSV or Matlab formats from the author at brainvue@gmail.com. Exploratory Data Analysis (EDA) is presented as a graphic method for finding better spike parameters and for the step-wise evaluation of the spike detection process.

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

    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.

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

    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.

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

    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.

  18. EEG Findings in Burnout Patients

    Luijtelaar, E.L.J.M. van; Verbraak, M.J.P.M.; Bunt, P.M. van den; Keijsers, G.P.J.; Arns, M.W.

    2010-01-01

    The concept of burnout remains enigmatic since it is only determined by behavioral characteristics. Moreover, the differential diagnosis with depression and chronic fatigue syndrome is difficult. EEG-related variables in 13 patients diagnosed with burnout syndrome were compared with 13 healthy

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

    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

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

    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.

  1. Automatic classification of background EEG activity in healthy and sick neonates

    Löfhede, Johan; Thordstein, Magnus; Löfgren, Nils; Flisberg, Anders; Rosa-Zurera, Manuel; Kjellmer, Ingemar; Lindecrantz, Kaj

    2010-02-01

    The overall aim of our research is to develop methods for a monitoring system to be used at neonatal intensive care units. When monitoring a baby, a range of different types of background activity needs to be considered. In this work, we have developed a scheme for automatic classification of background EEG activity in newborn babies. EEG from six full-term babies who were displaying a burst suppression pattern while suffering from the after-effects of asphyxia during birth was included along with EEG from 20 full-term healthy newborn babies. The signals from the healthy babies were divided into four behavioural states: active awake, quiet awake, active sleep and quiet sleep. By using a number of features extracted from the EEG together with Fisher's linear discriminant classifier we have managed to achieve 100% correct classification when separating burst suppression EEG from all four healthy EEG types and 93% true positive classification when separating quiet sleep from the other types. The other three sleep stages could not be classified. When the pathological burst suppression pattern was detected, the analysis was taken one step further and the signal was segmented into burst and suppression, allowing clinically relevant parameters such as suppression length and burst suppression ratio to be calculated. The segmentation of the burst suppression EEG works well, with a probability of error around 4%.

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

    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.

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

    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.

  4. EEG use in a tertiary referral centre.

    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.

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

    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.

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

    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

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

    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.

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

    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.

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

    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.

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

    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.

  11. Independent EEG sources are dipolar.

    Arnaud Delorme

    Full Text Available Independent component analysis (ICA and blind source separation (BSS methods are increasingly used to separate individual brain and non-brain source signals mixed by volume conduction in electroencephalographic (EEG and other electrophysiological recordings. We compared results of decomposing thirteen 71-channel human scalp EEG datasets by 22 ICA and BSS algorithms, assessing the pairwise mutual information (PMI in scalp channel pairs, the remaining PMI in component pairs, the overall mutual information reduction (MIR effected by each decomposition, and decomposition 'dipolarity' defined as the number of component scalp maps matching the projection of a single equivalent dipole with less than a given residual variance. The least well-performing algorithm was principal component analysis (PCA; best performing were AMICA and other likelihood/mutual information based ICA methods. Though these and other commonly-used decomposition methods returned many similar components, across 18 ICA/BSS algorithms mean dipolarity varied linearly with both MIR and with PMI remaining between the resulting component time courses, a result compatible with an interpretation of many maximally independent EEG components as being volume-conducted projections of partially-synchronous local cortical field activity within single compact cortical domains. To encourage further method comparisons, the data and software used to prepare the results have been made available (http://sccn.ucsd.edu/wiki/BSSComparison.

  12. EEG correlates of virtual reality hypnosis.

    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.

  13. Juvenile myoclonic epilepsy: clinical and EEG features

    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....

  14. Juvenile myoclonic epilepsy: clinical and EEG features

    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....

  15. Optimizing detection and analysis of slow waves in sleep EEG.

    Mensen, Armand; Riedner, Brady; Tononi, Giulio

    2016-12-01

    Analysis of individual slow waves in EEG recording during sleep provides both greater sensitivity and specificity compared to spectral power measures. However, parameters for detection and analysis have not been widely explored and validated. We present a new, open-source, Matlab based, toolbox for the automatic detection and analysis of slow waves; with adjustable parameter settings, as well as manual correction and exploration of the results using a multi-faceted visualization tool. We explore a large search space of parameter settings for slow wave detection and measure their effects on a selection of outcome parameters. Every choice of parameter setting had some effect on at least one outcome parameter. In general, the largest effect sizes were found when choosing the EEG reference, type of canonical waveform, and amplitude thresholding. Previously published methods accurately detect large, global waves but are conservative and miss the detection of smaller amplitude, local slow waves. The toolbox has additional benefits in terms of speed, user-interface, and visualization options to compare and contrast slow waves. The exploration of parameter settings in the toolbox highlights the importance of careful selection of detection METHODS: The sensitivity and specificity of the automated detection can be improved by manually adding or deleting entire waves and or specific channels using the toolbox visualization functions. The toolbox standardizes the detection procedure, sets the stage for reliable results and comparisons and is easy to use without previous programming experience. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. Tele-transmission of EEG recordings.

    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.

  17. [Compressive-spectral analysis of EEG in patients with panic attacks in the context of different psychiatric diseases].

    Tuter, N V; Gnezditskiĭ, V V

    2008-01-01

    Panic disorders (PD) which develop in the context of different psychiatric diseases (neurotic, personality disorder and schizotypal disorders) have their own clinical and neurophysiological features. The results of compressive-spectral analysis of EEG (CSA EEG) in patients with panic attack were different depending on the specifics of initial psychiatric status. EEG parameters in patients differed from those in controls. The common feature for all PD patients was the lower spectral density of theta-, alpha- and beta-bands as well as total spectral density without any alterations of region distribution. The decrease of electrical activity of activation systems was found in the groups with neurotic and schizotypal disorders and that of inhibition systems - in the group with schizotypal disorders. The EEG results did not suggest any depression of activation systems in patients with specific personality disorders. The data obtained with CSA EEG mirror the integrative brain activity which determinad of the appearance of PA as well as of nosology of psychiatre disease.

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

    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.

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

    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.

  20. Myocardial oxygen consumption at rest and during submaximal ...

    olayemitoyin

    2008-11-26

    Nov 26, 2008 ... ratio were the most important independent parameters in prediction of RPP. The study shows that ... study of various medical, surgical, and physical interventions on .... increase in myocardial activity and thus the MVO2 at rest.

  1. Dipoles at rest

    Griffiths, D.J.

    1992-01-01

    In a world populated by magnetic monopoles (as well as ordinary electric charges), there are two kinds of electric dipoles: those due to separated electric charges, and those due to current loops of magnetic charge. Similarly, there are two kinds of magnetic dipoles: those due to separated magnetic monopoles, and those due to electric current loops. This paper derives the potentials and fields of each of the four dipole species, and calculates the force, torque, energy, momentum, and angular momentum of each type, when placed (at rest) in a static external field (which may itself be produced by electric charges and currents, magnetic charges and currents, or all of these). Some implications and applications of the various results are discussed

  2. Video-EEG epilepsian diagnostiikassa - milloin ja miksi?

    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...

  3. Preterm EEG: a multimodal neurophysiological protocol.

    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.

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

    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

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

    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

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

    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

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

    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

  8. Automatic seizure detection: going from sEEG to iEEG

    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...

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

    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.

  10. EEG entropy measures in anesthesia

    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.

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

    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

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

    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.

  13. EEG entropy measures in anesthesia

    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

  14. EEG applications for sport and performance.

    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.

  15. Effects of oral amines on the EEG.

    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.

  16. Source localization of rhythmic ictal EEG activity

    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....

  17. Analysis of EEG Related Saccadic Eye Movement

    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.

  18. Changes of hypnagogic imagery and EEG stages

    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 (

  19. Continuous EEG Monitoring in Aneurysmal Subarachnoid Hemorrhage

    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...

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

    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

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

    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

  2. Classification of Motor Imagery EEG Signals with Support Vector Machines and Particle Swarm Optimization

    Ma, Yuliang; Ding, Xiaohui; She, Qingshan; Luo, Zhizeng; Potter, Thomas; Zhang, Yingchun

    2016-01-01

    Support vector machines are powerful tools used to solve the small sample and nonlinear classification problems, but their ultimate classification performance depends heavily upon the selection of appropriate kernel and penalty parameters. In this study, we propose using a particle swarm optimization algorithm to optimize the selection of both the kernel and penalty parameters in order to improve the classification performance of support vector machines. The performance of the optimized classifier was evaluated with motor imagery EEG signals in terms of both classification and prediction. Results show that the optimized classifier can significantly improve the classification accuracy of motor imagery EEG signals. PMID:27313656

  3. EEG correlates of task engagement and mental workload in vigilance, learning, and memory tasks.

    Berka, Chris; Levendowski, Daniel J; Lumicao, Michelle N; Yau, Alan; Davis, Gene; Zivkovic, Vladimir T; Olmstead, Richard E; Tremoulet, Patrice D; Craven, Patrick L

    2007-05-01

    The ability to continuously and unobtrusively monitor levels of task engagement and mental workload in an operational environment could be useful in identifying more accurate and efficient methods for humans to interact with technology. This information could also be used to optimize the design of safer, more efficient work environments that increase motivation and productivity. The present study explored the feasibility of monitoring electroencephalo-graphic (EEG) indices of engagement and workload acquired unobtrusively and quantified during performance of cognitive tests. EEG was acquired from 80 healthy participants with a wireless sensor headset (F3-F4,C3-C4,Cz-POz,F3-Cz,Fz-C3,Fz-POz) during tasks including: multi-level forward/backward-digit-span, grid-recall, trails, mental-addition, 20-min 3-Choice Vigilance, and image-learning and memory tests. EEG metrics for engagement and workload were calculated for each 1 -s of EEG. Across participants, engagement but not workload decreased over the 20-min vigilance test. Engagement and workload were significantly increased during the encoding period of verbal and image-learning and memory tests when compared with the recognition/ recall period. Workload but not engagement increased linearly as level of difficulty increased in forward and backward-digit-span, grid-recall, and mental-addition tests. EEG measures correlated with both subjective and objective performance metrics. These data in combination with previous studies suggest that EEG engagement reflects information-gathering, visual processing, and allocation of attention. EEG workload increases with increasing working memory load and during problem solving, integration of information, analytical reasoning, and may be more reflective of executive functions. Inspection of EEG on a second-by-second timescale revealed associations between workload and engagement levels when aligned with specific task events providing preliminary evidence that second

  4. Low-Rank Linear Dynamical Systems for Motor Imagery EEG.

    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.

  5. Incorporating priors for EEG source imaging and connectivity analysis

    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.

  6. DIRAC RESTful API

    Casajus Ramo, A; Graciani Diaz, R; Tsaregorodtsev, A

    2012-01-01

    The DIRAC framework for distributed computing has been designed as a flexible and modular solution that can be adapted to the requirements of any community. Users interact with DIRAC via command line, using the web portal or accessing resources via the DIRAC python API. The current DIRAC API requires users to use a python version valid for DIRAC. Some communities have developed their own software solutions for handling their specific workload, and would like to use DIRAC as their back-end to access distributed computing resources easily. Many of these solutions are not coded in python or depend on a specific python version. To solve this gap DIRAC provides a new language agnostic API that any software solution can use. This new API has been designed following the RESTful principles. Any language with libraries to issue standard HTTP queries may use it. GSI proxies can still be used to authenticate against the API services. However GSI proxies are not a widely adopted standard. The new DIRAC API also allows clients to use OAuth for delegating the user credentials to a third party solution. These delegated credentials allow the third party software to query to DIRAC on behalf of the users. This new API will further expand the possibilities communities have to integrate DIRAC into their distributed computing models.

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

    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.

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

    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.

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

    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.

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

    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.

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

    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.

  12. Classification of different reaching movements from the same limb using EEG

    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

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

    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

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

    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

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

    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.

  16. A Game Player Expertise Level Classification System Using Electroencephalography (EEG

    Syed Muhammad Anwar

    2017-12-01

    Full Text Available The success and wider adaptability of smart phones has given a new dimension to the gaming industry. Due to the wide spectrum of video games, the success of a particular game depends on how efficiently it is able to capture the end users’ attention. This leads to the need to analyse the cognitive aspects of the end user, that is the game player, during game play. A direct window to see how an end user responds to a stimuli is to look at their brain activity. In this study, electroencephalography (EEG is used to record human brain activity during game play. A commercially available EEG headset is used for this purpose giving fourteen channels of recorded EEG brain activity. The aim is to classify a player as expert or novice using the brain activity as the player indulges in the game play. Three different machine learning classifiers have been used to train and test the system. Among the classifiers, naive Bayes has outperformed others with an accuracy of 88 % , when data from all fourteen EEG channels are used. Furthermore, the activity observed on electrodes is statistically analysed and mapped for brain visualizations. The analysis has shown that out of the available fourteen channels, only four channels in the frontal and occipital brain regions show significant activity. Features of these four channels are then used, and the performance parameters of the four-channel classification are compared to the results of the fourteen-channel classification. It has been observed that support vector machine and the naive Bayes give good classification accuracy and processing time, well suited for real-time applications.

  17. Physiology Of Prolonged Bed Rest

    Greenleaf, John E.

    1991-01-01

    Report describes physiological effects of prolonged bed rest. Rest for periods of 24 hours or longer deconditions body to some extent; healing proceeds simultaneously with deconditioning. Report provides details on shifts in fluid electrolytes and loss of lean body mass, which comprises everything in body besides fat - that is, water, muscle, and bone. Based on published research.

  18. Quantitative topographic differentiation of the neonatal EEG.

    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.

  19. Contribution of EEG in transient neurological deficits.

    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.

  20. Signal Quality Evaluation of Emerging EEG Devices

    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.

  1. Assessment of preconscious sucrose perception using EEG

    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...

  2. Analyzing Electroencephalogram Signal Using EEG Lab

    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.

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

    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

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

    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.

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

    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.

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

    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.

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

    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.

  8. Combining Cryptography with EEG Biometrics.

    Damaševičius, Robertas; Maskeliūnas, Rytis; Kazanavičius, Egidijus; Woźniak, Marcin

    2018-01-01

    Cryptographic frameworks depend on key sharing for ensuring security of data. While the keys in cryptographic frameworks must be correctly reproducible and not unequivocally connected to the identity of a user, in biometric frameworks this is different. Joining cryptography techniques with biometrics can solve these issues. We present a biometric authentication method based on the discrete logarithm problem and Bose-Chaudhuri-Hocquenghem (BCH) codes, perform its security analysis, and demonstrate its security characteristics. We evaluate a biometric cryptosystem using our own dataset of electroencephalography (EEG) data collected from 42 subjects. The experimental results show that the described biometric user authentication system is effective, achieving an Equal Error Rate (ERR) of 0.024.

  9. Applying Improved Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG

    Ming-ai Li

    2017-01-01

    Full Text Available Electroencephalography (EEG is considered the output of a brain and it is a bioelectrical signal with multiscale and nonlinear properties. Motor Imagery EEG (MI-EEG not only has a close correlation with the human imagination and movement intention but also contains a large amount of physiological or disease information. As a result, it has been fully studied in the field of rehabilitation. To correctly interpret and accurately extract the features of MI-EEG signals, many nonlinear dynamic methods based on entropy, such as Approximate Entropy (ApEn, Sample Entropy (SampEn, Fuzzy Entropy (FE, and Permutation Entropy (PE, have been proposed and exploited continuously in recent years. However, these entropy-based methods can only measure the complexity of MI-EEG based on a single scale and therefore fail to account for the multiscale property inherent in MI-EEG. To solve this problem, Multiscale Sample Entropy (MSE, Multiscale Permutation Entropy (MPE, and Multiscale Fuzzy Entropy (MFE are developed by introducing scale factor. However, MFE has not been widely used in analysis of MI-EEG, and the same parameter values are employed when the MFE method is used to calculate the fuzzy entropy values on multiple scales. Actually, each coarse-grained MI-EEG carries the characteristic information of the original signal on different scale factors. It is necessary to optimize MFE parameters to discover more feature information. In this paper, the parameters of MFE are optimized independently for each scale factor, and the improved MFE (IMFE is applied to the feature extraction of MI-EEG. Based on the event-related desynchronization (ERD/event-related synchronization (ERS phenomenon, IMFE features from multi channels are fused organically to construct the feature vector. Experiments are conducted on a public dataset by using Support Vector Machine (SVM as a classifier. The experiment results of 10-fold cross-validation show that the proposed method yields

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

    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 ...

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

    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.

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

    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

  13. EMF-REST: Generation of RESTful APIs from Models

    Hamza , Ed-Douibi; Cánovas Izquierdo , Javier Luis; Gómez , Abel; Tisi , Massimo; Cabot , Jordi

    2016-01-01

    In the last years, RESTful Web services have become more and more popular as a lightweight solution to connect remote systems in distributed and Cloud-based architectures. However, being an architectural style rather than a specification or standard, the proper design of RESTful Web services is not trivial since developers have to deal with a plethora of recommendations and best practices. Model-Driven Engineering (MDE) emphasizes the use of models and model transformations to raise the level...

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

    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.

  15. ORIGINAL ARTICLE EEG changes and neuroimaging abnormalities ...

    salah

    Clinical Genetics Department, Human Genetics & Genome Research Division, ... neuroimaging changes of the brain and EEG abnormalities in correlation to the ... level and by developmental changes2. .... for IQ as a confounding factor.30.

  16. Two channel EEG thought pattern classifier.

    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 %

  17. Correlation between intra- and extracranial background EEG

    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...

  18. Amplitude-Integrated EEG in the Newborn

    J Gordon Millichap

    2008-11-01

    Full Text Available Th value of amplitude-integrated electroencephalography (aEEG in the newborn is explored by researchers at Washington University, St Louis; Wilhelmina Children’s Hospital, Utrecht, Netherlands; and Uppsala University Hospital, Sweden.

  19. Predictive Values of Electroencephalography (EEG) in Epilepsy ...

    Predictive Values of Electroencephalography (EEG) in Epilepsy Patients with Abnormal Behavioural Symptoms. OR Obiako, SO Adeyemi, TL Sheikh, LF Owolabi, MA Majebi, MO Gomina, F Adebayo, EU Iwuozo ...

  20. EEG analysis in a telemedical virtual world

    Jovanov, E.; Starcevic, D.; Samardzic, A.; Marsh, A.; Obrenovic, Z.

    1999-01-01

    Telemedicine creates virtual medical collaborative environments. We propose here a novel concept of virtual medical devices (VMD) for telemedical applications. VMDs provide different views on biomedical recordings and efficient signal analysis. In this paper we present a telemedical EEG analysis

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

    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

  2. Connectivity Measures in EEG Microstructural Sleep Elements.

    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

  3. EEG hippocampique de l'homme, du chien et du chat (Communication préliminaire)

    Arnolds, D.E.A.T.; Aitink, J.W.; Boeyinga, P.; Lopes Da Silva, F.H.

    1979-01-01

    A comparative neurophysiological study of the reactivity of hippocampal EEG in dog, cat and human (an epileptic patient with chronically indwelling electrodes) was carried out. In all 3 species the same type of qualitative changes in hippocampal spectral parameters in the theta frequency band (peak

  4. A Fast EEG Forecasting Algorithm for Phase-Locked Transcranial Electrical Stimulation of the Human Brain

    Farrokh Mansouri

    2017-07-01

    Full Text Available A growing body of research suggests that non-invasive electrical brain stimulation can more effectively modulate neural activity when phase-locked to the underlying brain rhythms. Transcranial alternating current stimulation (tACS can potentially stimulate the brain in-phase to its natural oscillations as recorded by electroencephalography (EEG, but matching these oscillations is a challenging problem due to the complex and time-varying nature of the EEG signals. Here we address this challenge by developing and testing a novel approach intended to deliver tACS phase-locked to the activity of the underlying brain region in real-time. This novel approach extracts phase and frequency from a segment of EEG, then forecasts the signal to control the stimulation. A careful tuning of the EEG segment length and prediction horizon is required and has been investigated here for different EEG frequency bands. The algorithm was tested on EEG data from 5 healthy volunteers. Algorithm performance was quantified in terms of phase-locking values across a variety of EEG frequency bands. Phase-locking performance was found to be consistent across individuals and recording locations. With current parameters, the algorithm performs best when tracking oscillations in the alpha band (8–13 Hz, with a phase-locking value of 0.77 ± 0.08. Performance was maximized when the frequency band of interest had a dominant frequency that was stable over time. The algorithm performs faster, and provides better phase-locked stimulation, compared to other recently published algorithms devised for this purpose. The algorithm is suitable for use in future studies of phase-locked tACS in preclinical and clinical applications.

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

    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.

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

    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.

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

    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.

  8. The EEG 2017 in the overview

    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

  9. Sleep EEG of Microcephaly in Zika Outbreak.

    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.

  10. Review on solving the forward problem in EEG source analysis

    Vergult Anneleen

    2007-11-01

    Full Text Available Abstract Background The aim of electroencephalogram (EEG source localization is to find the brain areas responsible for EEG waves of interest. It consists of solving forward and inverse problems. The forward problem is solved by starting from a given electrical source and calculating the potentials at the electrodes. These evaluations are necessary to solve the inverse problem which is defined as finding brain sources which are responsible for the measured potentials at the EEG electrodes. Methods While other reviews give an extensive summary of the both forward and inverse problem, this review article focuses on different aspects of solving the forward problem and it is intended for newcomers in this research field. Results It starts with focusing on the generators of the EEG: the post-synaptic potentials in the apical dendrites of pyramidal neurons. These cells generate an extracellular current which can be modeled by Poisson's differential equation, and Neumann and Dirichlet boundary conditions. The compartments in which these currents flow can be anisotropic (e.g. skull and white matter. In a three-shell spherical head model an analytical expression exists to solve the forward problem. During the last two decades researchers have tried to solve Poisson's equation in a realistically shaped head model obtained from 3D medical images, which requires numerical methods. The following methods are compared with each other: the boundary element method (BEM, the finite element method (FEM and the finite difference method (FDM. In the last two methods anisotropic conducting compartments can conveniently be introduced. Then the focus will be set on the use of reciprocity in EEG source localization. It is introduced to speed up the forward calculations which are here performed for each electrode position rather than for each dipole position. Solving Poisson's equation utilizing FEM and FDM corresponds to solving a large sparse linear system. Iterative

  11. EEG Based Inference of Spatio-Temporal Brain Dynamics

    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...

  12. Clinical physiology of bed rest

    Greenleaf, John E.

    1993-01-01

    Maintenance of optimal health in humans requires the proper balance between exercise, rest, and sleep as well as time in the upright position. About one-third of a lifetime is spent sleeping; and it is no coincidence that sleeping is performed in the horizontal position, the position in which gravitational influence on the body is minimal. Although enforced bed rest is necessary for the treatment of some ailments, in some cases it has probably been used unwisely. In addition to the lower hydrostatic pressure with the normally dependent regions of the cardiovascular system, body fuid compartments during bed rest in the horizontal body position, and virtual elimination of compression on the long bones of the skeletal system during bed rest (hypogravia), there is often reduction in energy metabolism due to the relative confinement (hypodynamia) and alteration of ambulatory circadian variations in metabolism, body temperature, and many hormonal systems. If patients are also moved to unfamiliar surroundings, they probably experience some feelings of anxiety and some sociopsychological problems. Adaptive physiological responses during bed rest are normal for that environment. They are attempts by the body to reduce unnecessary energy expenditure, to optimize its function, and to enhance its survival potential. Many of the deconditioning responses begin within the first day or two of bed rest; these early responses have prompted physicians to insist upon early resumption of the upright posture and ambulation of bedridden patients.

  13. Clustering of resting state networks.

    Megan H Lee

    Full Text Available The goal of the study was to demonstrate a hierarchical structure of resting state activity in the healthy brain using a data-driven clustering algorithm.The fuzzy-c-means clustering algorithm was applied to resting state fMRI data in cortical and subcortical gray matter from two groups acquired separately, one of 17 healthy individuals and the second of 21 healthy individuals. Different numbers of clusters and different starting conditions were used. A cluster dispersion measure determined the optimal numbers of clusters. An inner product metric provided a measure of similarity between different clusters. The two cluster result found the task-negative and task-positive systems. The cluster dispersion measure was minimized with seven and eleven clusters. Each of the clusters in the seven and eleven cluster result was associated with either the task-negative or task-positive system. Applying the algorithm to find seven clusters recovered previously described resting state networks, including the default mode network, frontoparietal control network, ventral and dorsal attention networks, somatomotor, visual, and language networks. The language and ventral attention networks had significant subcortical involvement. This parcellation was consistently found in a large majority of algorithm runs under different conditions and was robust to different methods of initialization.The clustering of resting state activity using different optimal numbers of clusters identified resting state networks comparable to previously obtained results. This work reinforces the observation that resting state networks are hierarchically organized.

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

    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.

  15. Network Analysis of Resting State EEG in the Developing Young Brain: Structure Comes With Maturation

    Boersma, M.; Smit, D.J.A.; de Bie, H.M.A.; van Baal, G.C.M.; Boomsma, D.I.; de Geus, E.J.C.; Delemarre-van de Waal, H.A.; Stam, C.J.

    2011-01-01

    During childhood, brain structure and function changes substantially. Recently, graph theory has been introduced to model connectivity in the brain. Small-world networks, such as the brain, combine optimal properties of both ordered and random networks, i.e., high clustering and short path lengths.

  16. A cortical source localization analysis of resting EEG data after remifentanil infusion

    Khodayari-Rostamabad, Ahmad; Graversen, Carina; Malver, Lasse P

    2015-01-01

    in several brain areas including inferior frontal gyrus and insula at frontal lobe oscillated more strongly after remifentanil infusion compared to placebo. Furthermore, the source activity at delta band was correlated with continuous reaction time index. CONCLUSIONS: These results indicate that alterations...... in brain oscillations during remifentanil are mostly localized to frontal, fronto-temporal and fronto-central lobes and related to cognitive function. SIGNIFICANCE: The approach offers the potential to be used for understanding the underlying mechanism of action of remifentanil on brain activity....

  17. An EEG-Based Biometric System Using Eigenvector Centrality in Resting State Brain Networks

    Fraschini, M.; Hillebrand, A.; Demuru, M.; Didaci, L.; Marcialis, G.L.

    2015-01-01

    Recently, there has been a growing interest in the use of brain activity for biometric systems. However, so far these studies have focused mainly on basic features of the Electroencephalography. In this study we propose an approach based on phase synchronization, to investigate personal distinctive

  18. Optimal use of EEG recordings to target active brain areas with transcranial electrical stimulation.

    Dmochowski, Jacek P; Koessler, Laurent; Norcia, Anthony M; Bikson, Marom; Parra, Lucas C

    2017-08-15

    To demonstrate causal relationships between brain and behavior, investigators would like to guide brain stimulation using measurements of neural activity. Particularly promising in this context are electroencephalography (EEG) and transcranial electrical stimulation (TES), as they are linked by a reciprocity principle which, despite being known for decades, has not led to a formalism for relating EEG recordings to optimal stimulation parameters. Here we derive a closed-form expression for the TES configuration that optimally stimulates (i.e., targets) the sources of recorded EEG, without making assumptions about source location or distribution. We also derive a duality between TES targeting and EEG source localization, and demonstrate that in cases where source localization fails, so does the proposed targeting. Numerical simulations with multiple head models confirm these theoretical predictions and quantify the achieved stimulation in terms of focality and intensity. We show that constraining the stimulation currents automatically selects optimal montages that involve only a few (4-7) electrodes, with only incremental loss in performance when targeting focal activations. The proposed technique allows brain scientists and clinicians to rationally target the sources of observed EEG and thus overcomes a major obstacle to the realization of individualized or closed-loop brain stimulation. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  19. Overcoming Inter-Subject Variability in BCI Using EEG-Based Identification

    J. Stastny

    2014-04-01

    Full Text Available The high dependency of the Brain Computer Interface (BCI system performance on the BCI user is a well-known issue of many BCI devices. This contribution presents a new way to overcome this problem using a synergy between a BCI device and an EEG-based biometric algorithm. Using the biometric algorithm, the BCI device automatically identifies its current user and adapts parameters of the classification process and of the BCI protocol to maximize the BCI performance. In addition to this we present an algorithm for EEG-based identification designed to be resistant to variations in EEG recordings between sessions, which is also demonstrated by an experiment with an EEG database containing two sessions recorded one year apart. Further, our algorithm is designed to be compatible with our movement-related BCI device and the evaluation of the algorithm performance took place under conditions of a standard BCI experiment. Estimation of the mu rhythm fundamental frequency using the Frequency Zooming AR modeling is used for EEG feature extraction followed by a classifier based on the regularized Mahalanobis distance. An average subject identification score of 96 % is achieved.

  20. Classification of Hand Grasp Kinetics and Types Using Movement-Related Cortical Potentials and EEG Rhythms

    Mads Jochumsen

    2017-01-01

    Full Text Available Detection of single-trial movement intentions from EEG is paramount for brain-computer interfacing in neurorehabilitation. These movement intentions contain task-related information and if this is decoded, the neurorehabilitation could potentially be optimized. The aim of this study was to classify single-trial movement intentions associated with two levels of force and speed and three different grasp types using EEG rhythms and components of the movement-related cortical potential (MRCP as features. The feature importance was used to estimate encoding of discriminative information. Two data sets were used. 29 healthy subjects executed and imagined different hand movements, while EEG was recorded over the contralateral sensorimotor cortex. The following features were extracted: delta, theta, mu/alpha, beta, and gamma rhythms, readiness potential, negative slope, and motor potential of the MRCP. Sequential forward selection was performed, and classification was performed using linear discriminant analysis and support vector machines. Limited classification accuracies were obtained from the EEG rhythms and MRCP-components: 0.48±0.05 (grasp types, 0.41±0.07 (kinetic profiles, motor execution, and 0.39±0.08 (kinetic profiles, motor imagination. Delta activity contributed the most but all features provided discriminative information. These findings suggest that information from the entire EEG spectrum is needed to discriminate between task-related parameters from single-trial movement intentions.

  1. Classifier models and architectures for EEG-based neonatal seizure detection

    Greene, B R; Marnane, W P; Lightbody, G; Reilly, R B; Boylan, G B

    2008-01-01

    Neonatal seizures are the most common neurological emergency in the neonatal period and are associated with a poor long-term outcome. Early detection and treatment may improve prognosis. This paper aims to develop an optimal set of parameters and a comprehensive scheme for patient-independent multi-channel EEG-based neonatal seizure detection. We employed a dataset containing 411 neonatal seizures. The dataset consists of multi-channel EEG recordings with a mean duration of 14.8 h from 17 neonatal patients. Early-integration and late-integration classifier architectures were considered for the combination of information across EEG channels. Three classifier models based on linear discriminants, quadratic discriminants and regularized discriminants were employed. Furthermore, the effect of electrode montage was considered. The best performing seizure detection system was found to be an early integration configuration employing a regularized discriminant classifier model. A referential EEG montage was found to outperform the more standard bipolar electrode montage for automated neonatal seizure detection. A cross-fold validation estimate of the classifier performance for the best performing system yielded 81.03% of seizures correctly detected with a false detection rate of 3.82%. With post-processing, the false detection rate was reduced to 1.30% with 59.49% of seizures correctly detected. These results represent a comprehensive illustration that robust reliable patient-independent neonatal seizure detection is possible using multi-channel EEG

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

    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.

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

    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.

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

    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.

  5. EEG markers of cognitive impairments in patients with coronary artery disease

    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.

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

    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

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

    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.

  8. Analysis of absence seizure generation using EEG spatial-temporal regularity measures.

    Mammone, Nadia; Labate, Domenico; Lay-Ekuakille, Aime; Morabito, Francesco C

    2012-12-01

    Epileptic seizures are thought to be generated and to evolve through an underlying anomaly of synchronization in the activity of groups of neuronal populations. The related dynamic scenario of state transitions is revealed by detecting changes in the dynamical properties of Electroencephalography (EEG) signals. The recruitment procedure ending with the crisis can be explored through a spatial-temporal plot from which to extract suitable descriptors that are able to monitor and quantify the evolving synchronization level from the EEG tracings. In this paper, a spatial-temporal analysis of EEG recordings based on the concept of permutation entropy (PE) is proposed. The performance of PE are tested on a database of 24 patients affected by absence (generalized) seizures. The results achieved are compared to the dynamical behavior of the EEG of 40 healthy subjects. Being PE a feature which is dependent on two parameters, an extensive study of the sensitivity of the performance of PE with respect to the parameters' setting was carried out on scalp EEG. Once the optimal PE configuration was determined, its ability to detect the different brain states was evaluated. According to the results here presented, it seems that the widely accepted model of "jump" transition to absence seizure should be in some cases coupled (or substituted) by a gradual transition model characteristic of self-organizing networks. Indeed, it appears that the transition to the epileptic status is heralded before the preictal state, ever since the interictal stages. As a matter of fact, within the limits of the analyzed database, the frontal-temporal scalp areas appear constantly associated to PE levels higher compared to the remaining electrodes, whereas the parieto-occipital areas appear associated to lower PE values. The EEG of healthy subjects neither shows any similar dynamic behavior nor exhibits any recurrent portrait in PE topography.

  9. EEG indices correlate with sustained attention performance in patients affected by diffuse axonal injury.

    Coelli, Stefania; Barbieri, Riccardo; Reni, Gianluigi; Zucca, Claudio; Bianchi, Anna Maria

    2018-06-01

    The aim of this study is to assess the ability of EEG-based indices in providing relevant information about cognitive engagement level during the execution of a clinical sustained attention (SA) test in healthy volunteers and DAI (diffused axonal injury)-affected patients. We computed three continuous power-based engagement indices (P β /P α , 1/P α , and P β / (P α + P θ )) from EEG recordings in a control group (n = 7) and seven DAI-affected patients executing a 10-min Conners' "not-X" continuous performance test (CPT). A correlation analysis was performed in order to investigate the existence of relations between the EEG metrics and behavioral parameters in both the populations. P β /P α and 1/P α indices were found to be correlated with reaction times in both groups while P β / (P α + P θ ) and P β /P α also correlated with the errors rate for DAI patients. In line with previous studies, time course fluctuations revealed a first strong decrease of attention after 2 min from the beginning of the test and a final fading at the end. Our results provide evidence that EEG-derived indices extraction and evaluation during SA tasks are helpful in the assessment of attention level in healthy subjects and DAI patients, offering motivations for including EEG monitoring in cognitive rehabilitation practice. Graphical abstract Three EEG-derived indices were computed from four electrodes montages in a population of seven healthy volunteers and a group of seven DAI-affected patients. Results show a significant correlation between the time course of the indices and behavioral parameters, thus demonstrating their usefulness in monitoring mental engagement level during a sustained attention task.

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

    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.

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

    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.

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

    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

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

    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

  14. Acute single channel EEG predictors of cognitive function after stroke.

    Anna Aminov

    Full Text Available Early and accurate identification of factors that predict post-stroke cognitive outcome is important to set realistic targets for rehabilitation and to guide patients and their families accordingly. However, behavioral measures of cognition are difficult to obtain in the acute phase of recovery due to clinical factors (e.g. fatigue and functional barriers (e.g. language deficits. The aim of the current study was to test whether single channel wireless EEG data obtained acutely following stroke could predict longer-term cognitive function.Resting state Relative Power (RP of delta, theta, alpha, beta, delta/alpha ratio (DAR, and delta/theta ratio (DTR were obtained from a single electrode over FP1 in 24 participants within 72 hours of a first-ever stroke. The Montreal Cognitive Assessment (MoCA was administered at 90-days post-stroke. Correlation and regression analyses were completed to identify relationships between 90-day cognitive function and electrophysiological data, neurological status, and demographic characteristics at admission.Four acute qEEG indices demonstrated moderate to high correlations with 90-day MoCA scores: DTR (r = -0.57, p = 0.01, RP theta (r = 0.50, p = 0.01, RP delta (r = -0.47, p = 0.02, and DAR (r = -0.45, p = 0.03. Acute DTR (b = -0.36, p < 0.05 and stroke severity on admission (b = -0.63, p < 0.01 were the best linear combination of predictors of MoCA scores 90-days post-stroke, accounting for 75% of variance.Data generated by a single pre-frontal electrode support the prognostic value of acute DAR, and identify DTR as a potential marker of post-stroke cognitive outcome. Use of single channel recording in an acute clinical setting may provide an efficient and valid predictor of cognitive function after stroke.

  15. EEG Correlates of Ten Positive Emotions.

    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.

  16. Highly Efficient Compression Algorithms for Multichannel EEG.

    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.

  17. RESTful Java web services security

    Enríquez, René

    2014-01-01

    A sequential and easy-to-follow guide which allows you to understand the concepts related to securing web apps/services quickly and efficiently, since each topic is explained and described with the help of an example and in a step-by-step manner, helping you to easily implement the examples in your own projects. This book is intended for web application developers who use RESTful web services to power their websites. Prior knowledge of RESTful is not mandatory, but would be advisable.

  18. Investigating reading comprehension through EEG

    Luciane Baretta

    2012-12-01

    Full Text Available http://dx.doi.org/10.5007/2175-8026.2012n63p69   Experimental studies point that different factors can influence reading comprehension, such as the topic, text type, reading task, and others. The advances in technologies for the past decades have provided researchers with several possibilities to investigate what goes on in one’s brain since their eyes meet the page until comprehension is achieved. Since the mid-80’s, numerous studies have been conducted with the use of the electroencephalogram (EEG to investigate the process of reading, through the analysis of different components – n400, n100 or n1, P2, among others. These components reveal, for example, how the brain integrates the meaning of a specific word in the semantic context of a given sentence.  based on previous studies, which demonstrate that different types of words affect cognitive load, this paper aims at investigating how the brain processes function and content words inserted in expository and narrative texts with suitable / unsuitable conclusions. results showed that the type of text and word influence the cognitive load in different scalp areas (midline, right and left hemispheres. The  n1s were more pronounced to the content words inserted in narrative texts and to the function words inserted in the expository type of texts, corroborating former studies.

  19. Identifying the effects of microsaccades in tripolar EEG signals.

    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.

  20. Removal of ocular artifacts from the REM sleep EEG

    Waterman, D.; Woestenburg, J.C.; Elton, M.; Hofman, W.; Kok, A.

    1992-01-01

    The present report concerns the first study in which electrooculographic (EOG) contamination of electroencephalographic (EEG) recordings in rapid eye movement (REM) sleep is systematically investigated. Contamination of REM sleep EEG recordings in six subjects was evaluated in the frequency domain.

  1. Extended seizure detection algorithm for intracranial EEG recordings

    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...

  2. Changes in EEG indices and serotonin concentrations in depression and anxiety disorders

    I. V. Kichuk

    2016-01-01

    Full Text Available Electroencephalogram (EEG is an important tool to study brain function. EEG can evaluate the current functional state of the brain with high temporal resolution and identify metabolic and ion disorders that cannot be detected by magnetic resonance imaging.Objective: to analyze the relationship between some neurophysiological and biochemical parameters with a Neuro-KM hardware-software complex for the topographic mapping of brain electrical activity.Patients and methods. 75 patients with depression, 101 with anxiety disorders (AD, and 86 control individuals were examined. EEG spectrum and coherence changes were estimated in the depression and AD groups versus the control group. Correlation analysis of EEG indices and blood serotonin concentrations was carried out.Results and discussion. The patients with depression and those with AD as compared to the controls were observed to have similar EEG spectral changes in the beta band. Coherence analysis in the beta-band showed that both disease groups versus the control group had oppositely directed changes: a reduction in intra- and interhemispheric coherence for depression and its increase for AD (p < 0.001. That in the theta and alpha bands revealed that both disease groups had unidirectional interhemispheric coherence changes: a decrease in integration in the alpha band and its increase in the theta and delta bands in the depression and AD groups (p < 0.05 and multidirectional changes in intrahemispheric coherence: its reduction in the depression group and an increase in the AD group (p < 0.05. Correlation analysis of EEG parameters and platelet serotonin concentrations showed opposite correlations of serotonin concentrations and EEG percentage power in the theta and beta bands. When there were higher serotonin concentrations in the patients with depression, EEG demonstrated a preponderance of a synchronization pattern; when these were in the patients with AD, there was a predominance

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

    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.

  4. [EEG changes in symptomatic headache caused by bruxism].

    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.

  5. EEG-guided meditation: A personalized approach.

    Fingelkurts, Andrew A; Fingelkurts, Alexander A; Kallio-Tamminen, Tarja

    2015-12-01

    The therapeutic potential of meditation for physical and mental well-being is well documented, however the possibility of adverse effects warrants further discussion of the suitability of any particular meditation practice for every given participant. This concern highlights the need for a personalized approach in the meditation practice adjusted for a concrete individual. This can be done by using an objective screening procedure that detects the weak and strong cognitive skills in brain function, thus helping design a tailored meditation training protocol. Quantitative electroencephalogram (qEEG) is a suitable tool that allows identification of individual neurophysiological types. Using qEEG screening can aid developing a meditation training program that maximizes results and minimizes risk of potential negative effects. This brief theoretical-conceptual review provides a discussion of the problem and presents some illustrative results on the usage of qEEG screening for the guidance of mediation personalization. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

    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.

  7. Widespread EEG changes precede focal seizures.

    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.

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

    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.

  9. Quantum neural network-based EEG filtering for a brain-computer interface.

    Gandhi, Vaibhav; Prasad, Girijesh; Coyle, Damien; Behera, Laxmidhar; McGinnity, Thomas Martin

    2014-02-01

    A novel neural information processing architecture inspired by quantum mechanics and incorporating the well-known Schrodinger wave equation is proposed in this paper. The proposed architecture referred to as recurrent quantum neural network (RQNN) can characterize a nonstationary stochastic signal as time-varying wave packets. A robust unsupervised learning algorithm enables the RQNN to effectively capture the statistical behavior of the input signal and facilitates the estimation of signal embedded in noise with unknown characteristics. The results from a number of benchmark tests show that simple signals such as dc, staircase dc, and sinusoidal signals embedded within high noise can be accurately filtered and particle swarm optimization can be employed to select model parameters. The RQNN filtering procedure is applied in a two-class motor imagery-based brain-computer interface where the objective was to filter electroencephalogram (EEG) signals before feature extraction and classification to increase signal separability. A two-step inner-outer fivefold cross-validation approach is utilized to select the algorithm parameters subject-specifically for nine subjects. It is shown that the subject-specific RQNN EEG filtering significantly improves brain-computer interface performance compared to using only the raw EEG or Savitzky-Golay filtered EEG across multiple sessions.

  10. Relationship between speed and EEG activity during imagined and executed hand movements

    Yuan, Han; Perdoni, Christopher; He, Bin

    2010-04-01

    The relationship between primary motor cortex and movement kinematics has been shown in nonhuman primate studies of hand reaching or drawing tasks. Studies have demonstrated that the neural activities accompanying or immediately preceding the movement encode the direction, speed and other information. Here we investigated the relationship between the kinematics of imagined and actual hand movement, i.e. the clenching speed, and the EEG activity in ten human subjects. Study participants were asked to perform and imagine clenching of the left hand and right hand at various speeds. The EEG activity in the alpha (8-12 Hz) and beta (18-28 Hz) frequency bands were found to be linearly correlated with the speed of imagery clenching. Similar parametric modulation was also found during the execution of hand movements. A single equation relating the EEG activity to the speed and the hand (left versus right) was developed. This equation, which contained a linear independent combination of the two parameters, described the time-varying neural activity during the tasks. Based on the model, a regression approach was developed to decode the two parameters from the multiple-channel EEG signals. We demonstrated the continuous decoding of dynamic hand and speed information of the imagined clenching. In particular, the time-varying clenching speed was reconstructed in a bell-shaped profile. Our findings suggest an application to providing continuous and complex control of noninvasive brain-computer interface for movement-impaired paralytics.

  11. Simultaneous Channel and Feature Selection of Fused EEG Features Based on Sparse Group Lasso

    Jin-Jia Wang

    2015-01-01

    Full Text Available Feature extraction and classification of EEG signals are core parts of brain computer interfaces (BCIs. Due to the high dimension of the EEG feature vector, an effective feature selection algorithm has become an integral part of research studies. In this paper, we present a new method based on a wrapped Sparse Group Lasso for channel and feature selection of fused EEG signals. The high-dimensional fused features are firstly obtained, which include the power spectrum, time-domain statistics, AR model, and the wavelet coefficient features extracted from the preprocessed EEG signals. The wrapped channel and feature selection method is then applied, which uses the logistical regression model with Sparse Group Lasso penalized function. The model is fitted on the training data, and parameter estimation is obtained by modified blockwise coordinate descent and coordinate gradient descent method. The best parameters and feature subset are selected by using a 10-fold cross-validation. Finally, the test data is classified using the trained model. Compared with existing channel and feature selection methods, results show that the proposed method is more suitable, more stable, and faster for high-dimensional feature fusion. It can simultaneously achieve channel and feature selection with a lower error rate. The test accuracy on the data used from international BCI Competition IV reached 84.72%.

  12. Geotechnical Parameters from Seismic Measurements: Two Field Examples from Egypt and Saudi Arabia

    Khalil, Mohamed H.; Hanafy, Sherif M.

    2016-01-01

    © 2016 EEGS. Geotechnical parameters were used to determine subsurface rock quality for construction purposes. We summarize the mathematical relationships used to calculate the geotechnical parameters from P- and S-wave velocities and density values

  13. The colorful brain: Visualization of EEG background patterns

    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

  14. A comparison of EEG spectral entropy with conventional quantitative ...

    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 ...

  15. Analysis of routine EEG usage in a general adult ICU.

    McHugh, J C

    2009-09-01

    Non-convulsive seizures and status epilepticus are common in brain-injured patients in intensive care units. Continuous electroencephalography (cEEG) monitoring is the most sensitive means of their detection. In centres where cEEG is unavailable, routine EEG is often utilized for diagnosis although its sensitivity is lower.

  16. Automatic epileptic seizure detection in EEGs using MF-DFA, SVM based on cloud computing.

    Zhang, Zhongnan; Wen, Tingxi; Huang, Wei; Wang, Meihong; Li, Chunfeng

    2017-01-01

    Epilepsy is a chronic disease with transient brain dysfunction that results from the sudden abnormal discharge of neurons in the brain. Since electroencephalogram (EEG) is a harmless and noninvasive detection method, it plays an important role in the detection of neurological diseases. However, the process of analyzing EEG to detect neurological diseases is often difficult because the brain electrical signals are random, non-stationary and nonlinear. In order to overcome such difficulty, this study aims to develop a new computer-aided scheme for automatic epileptic seizure detection in EEGs based on multi-fractal detrended fluctuation analysis (MF-DFA) and support vector machine (SVM). New scheme first extracts features from EEG by MF-DFA during the first stage. Then, the scheme applies a genetic algorithm (GA) to calculate parameters used in SVM and classify the training data according to the selected features using SVM. Finally, the trained SVM classifier is exploited to detect neurological diseases. The algorithm utilizes MLlib from library of SPARK and runs on cloud platform. Applying to a public dataset for experiment, the study results show that the new feature extraction method and scheme can detect signals with less features and the accuracy of the classification reached up to 99%. MF-DFA is a promising approach to extract features for analyzing EEG, because of its simple algorithm procedure and less parameters. The features obtained by MF-DFA can represent samples as well as traditional wavelet transform and Lyapunov exponents. GA can always find useful parameters for SVM with enough execution time. The results illustrate that the classification model can achieve comparable accuracy, which means that it is effective in epileptic seizure detection.

  17. The NASA Bed Rest Project

    Rhodes, Bradley; Meck, Janice

    2005-01-01

    NASA s National Vision for Space Exploration includes human travel beyond low earth orbit and the ultimate safe return of the crews. Crucial to fulfilling the vision is the successful and timely development of countermeasures for the adverse physiological effects on human systems caused by long term exposure to the microgravity environment. Limited access to in-flight resources for the foreseeable future increases NASA s reliance on ground-based analogs to simulate these effects of microgravity. The primary analog for human based research will be head-down bed rest. By this approach NASA will be able to evaluate countermeasures in large sample sizes, perform preliminary evaluations of proposed in-flight protocols and assess the utility of individual or combined strategies before flight resources are requested. In response to this critical need, NASA has created the Bed Rest Project at the Johnson Space Center. The Project establishes the infrastructure and processes to provide a long term capability for standardized domestic bed rest studies and countermeasure development. The Bed Rest Project design takes a comprehensive, interdisciplinary, integrated approach that reduces the resource overhead of one investigator for one campaign. In addition to integrating studies operationally relevant for exploration, the Project addresses other new Vision objectives, namely: 1) interagency cooperation with the NIH allows for Clinical Research Center (CRC) facility sharing to the benefit of both agencies, 2) collaboration with our International Partners expands countermeasure development opportunities for foreign and domestic investigators as well as promotes consistency in approach and results, 3) to the greatest degree possible, the Project also advances research by clinicians and academia alike to encourage return to earth benefits. This paper will describe the Project s top level goals, organization and relationship to other Exploration Vision Projects, implementation

  18. AgNOR Count in Resting Cells (Resting NOR Is a New Prognostic Marker in Invasive Bladder Tumor

    Mitsuro Tomobe

    2001-01-01

    Full Text Available Purpose: We have previously demonstrated that the AgNOR count in proliferating cells is a predictor of tumor recurrence in superficial bladder tumor (J. Urol. 162 (1999, 63–68. In the present study, we evaluate the type of AgNOR associated with cell cycles as a prognostic factor in invasive bladder tumor using a double staining technique employing both AgNOR and MIB-1 labelling. Materials and methods: Forty-four paraffin sections of invasive bladder tumors were stained simultaneously with AgNOR and MIB-1. The number of AgNORs in proliferating (MIB-1 positive or resting (MIB-1 negative cells were counted from a total of 100 nuclei. Correlations between MIB-1 associated AgNOR count and clinicopathological parameters were statistically analyzed. Results: The AgNOR count in proliferating cells (proliferating NOR was significantly higher than that in resting cells (resting NOR (p < 0.01. The resting NOR in tumors with distant metastases was significantly higher than that in tumors without metastases (p < 0.05. Patients with a low resting NOR tumor had a better prognosis than those with a high resting NOR tumor, whereas the proliferating NOR was not associated with survival. Survival analysis revealed that the resting NOR was the most powerful prognostic marker in patients with invasive bladder tumor (p < 0.05. Conclusions: Resting NOR had a predictive value in the prognosis of patients with invasive bladder tumor. Keywords: Transitional cell carcinoma, invasive, resting cell, AgNORs, MIB-1

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

    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.

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

    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

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

    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.

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

    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.

  3. Aesthetic preference recognition of 3D shapes using EEG.

    Chew, Lin Hou; Teo, Jason; Mountstephens, James

    2016-04-01

    Recognition and identification of aesthetic preference is indispensable in industrial design. Humans tend to pursue products with aesthetic values and make buying decisions based on their aesthetic preferences. The existence of neuromarketing is to understand consumer responses toward marketing stimuli by using imaging techniques and recognition of physiological parameters. Numerous studies have been done to understand the relationship between human, art and aesthetics. In this paper, we present a novel preference-based measurement of user aesthetics using electroencephalogram (EEG) signals for virtual 3D shapes with motion. The 3D shapes are designed to appear like bracelets, which is generated by using the Gielis superformula. EEG signals were collected by using a medical grade device, the B-Alert X10 from advance brain monitoring, with a sampling frequency of 256 Hz and resolution of 16 bits. The signals obtained when viewing 3D bracelet shapes were decomposed into alpha, beta, theta, gamma and delta rhythm by using time-frequency analysis, then classified into two classes, namely like and dislike by using support vector machines and K-nearest neighbors (KNN) classifiers respectively. Classification accuracy of up to 80 % was obtained by using KNN with the alpha, theta and delta rhythms as the features extracted from frontal channels, Fz, F3 and F4 to classify two classes, like and dislike.

  4. Compressive sensing scalp EEG signals: implementations and practical performance.

    Abdulghani, Amir M; Casson, Alexander J; Rodriguez-Villegas, Esther

    2012-11-01

    Highly miniaturised, wearable computing and communication systems allow unobtrusive, convenient and long term monitoring of a range of physiological parameters. For long term operation from the physically smallest batteries, the average power consumption of a wearable device must be very low. It is well known that the overall power consumption of these devices can be reduced by the inclusion of low power consumption, real-time compression of the raw physiological data in the wearable device itself. Compressive sensing is a new paradigm for providing data compression: it has shown significant promise in fields such as MRI; and is potentially suitable for use in wearable computing systems as the compression process required in the wearable device has a low computational complexity. However, the practical performance very much depends on the characteristics of the signal being sensed. As such the utility of the technique cannot be extrapolated from one application to another. Long term electroencephalography (EEG) is a fundamental tool for the investigation of neurological disorders and is increasingly used in many non-medical applications, such as brain-computer interfaces. This article investigates in detail the practical performance of different implementations of the compressive sensing theory when applied to scalp EEG signals.

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

    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.

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

    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

  7. Random matrix analysis of human EEG data

    Šeba, Petr

    2003-01-01

    Roč. 91, - (2003), s. 198104-1 - 198104-4 ISSN 0031-9007 R&D Projects: GA ČR GA202/02/0088 Institutional research plan: CEZ:AV0Z1010914 Keywords : random matrix theory * EEG signal Subject RIV: BE - Theoretical Physics Impact factor: 7.035, year: 2003

  8. Discriminant Multitaper Component Analysis of EEG

    Dyrholm, Mads; Sajda, Paul

    the method for predicting the handedness of a subject’s button press given multivariate EEG data. We show that our method learns multitapers sensitive to oscillatory activity in the 8–12 Hz range with spatial filters selective for lateralized motor cortex. This finding is consistent with the well-known mu...

  9. EEG-based characterization of flicker perception

    Lazo, M.; Tsoneva, T.; Garcia Molina, G.

    2013-01-01

    Steady-State Visual Evoked Potential (SSVEP) is an oscillatory electrical response appearing in the electroencephalogram (EEG) in response to flicker stimulation. The SSVEP manifests more prominently in electrodes located near the visual cortex and has oscillatory components at the stimulation

  10. 3D Printed Dry EEG Electrodes.

    Krachunov, Sammy; Casson, Alexander J

    2016-10-02

    Electroencephalography (EEG) is a procedure that records brain activity in a non-invasive manner. The cost and size of EEG devices has decreased in recent years, facilitating a growing interest in wearable EEG that can be used out-of-the-lab for a wide range of applications, from epilepsy diagnosis, to stroke rehabilitation, to Brain-Computer Interfaces (BCI). A major obstacle for these emerging applications is the wet electrodes, which are used as part of the EEG setup. These electrodes are attached to the human scalp using a conductive gel, which can be uncomfortable to the subject, causes skin irritation, and some gels have poor long-term stability. A solution to this problem is to use dry electrodes, which do not require conductive gel, but tend to have a higher noise floor. This paper presents a novel methodology for the design and manufacture of such dry electrodes. We manufacture the electrodes using low cost desktop 3D printers and off-the-shelf components for the first time. This allows quick and inexpensive electrode manufacturing and opens the possibility of creating electrodes that are customized for each individual user. Our 3D printed electrodes are compared against standard wet electrodes, and the performance of the proposed electrodes is suitable for BCI applications, despite the presence of additional noise.

  11. 3D Printed Dry EEG Electrodes

    Sammy Krachunov

    2016-10-01

    Full Text Available Electroencephalography (EEG is a procedure that records brain activity in a non-invasive manner. The cost and size of EEG devices has decreased in recent years, facilitating a growing interest in wearable EEG that can be used out-of-the-lab for a wide range of applications, from epilepsy diagnosis, to stroke rehabilitation, to Brain-Computer Interfaces (BCI. A major obstacle for these emerging applications is the wet electrodes, which are used as part of the EEG setup. These electrodes are attached to the human scalp using a conductive gel, which can be uncomfortable to the subject, causes skin irritation, and some gels have poor long-term stability. A solution to this problem is to use dry electrodes, which do not require conductive gel, but tend to have a higher noise floor. This paper presents a novel methodology for the design and manufacture of such dry electrodes. We manufacture the electrodes using low cost desktop 3D printers and off-the-shelf components for the first time. This allows quick and inexpensive electrode manufacturing and opens the possibility of creating electrodes that are customized for each individual user. Our 3D printed electrodes are compared against standard wet electrodes, and the performance of the proposed electrodes is suitable for BCI applications, despite the presence of additional noise.

  12. An overview of an amplitude integrated EEG

    Setyo Handryastuti

    2007-05-01

    for neurodevelopmental problem in conditions such as hypoxic-ischemic encephalopathy (HIE, prematurity, neonatal seizures, central nervous system infection, metabolic disorders, intraventricular or intracranial bleeding and brain malformation. This article gives an overview about aEEG and its role in newborn.

  13. Microneedle array electrode for human EEG recording.

    Lüttge, Regina; van Nieuwkasteele-Bystrova, Svetlana Nikolajevna; van Putten, Michel Johannes Antonius Maria; Vander Sloten, Jos; Verdonck, Pascal; Nyssen, Marc; Haueisen, Jens

    2009-01-01

    Microneedle array electrodes for EEG significantly reduce the mounting time, particularly by circumvention of the need for skin preparation by scrubbing. We designed a new replication process for numerous types of microneedle arrays. Here, polymer microneedle array electrodes with 64 microneedles,

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

    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.

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

    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.

  16. Interrater variability of EEG interpretation in comatose cardiac arrest patients

    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...

  17. RESTful web services with Dropwizard

    Dallas, Alexandros

    2014-01-01

    A hands-on focused step-by-step tutorial to help you create Web Service applications using Dropwizard. If you are a software engineer or a web developer and want to learn more about building your own Web Service application, then this is the book for you. Basic knowledge of Java and RESTful Web Service concepts is assumed and familiarity with SQL/MySQL and command-line scripting would be helpful.

  18. Use Case Analysis: The Ambulatory EEG in Navy Medicine for Traumatic Brain Injuries

    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

  19. WEB-SERVICE. RESTFUL ARCHITECTURE

    M. Melnichuk

    2018-04-01

    Full Text Available Network technology for interaction between two applications via the HTTP protocol was considered in article.When client works with REST API - it means it works with "resources", and in SOAP work is performed with operations. To build REST web services, you must follow certain principles: explicit use of HTTP methods, access to resources by URI, stateless, HATEAOS, caching, transfer of objects in JSON or XML representation. But sometimes some principles are ignored to ensure a higher speed of work and to reduce development time.The pros and cons of using JSON and XML representations were considered, and it can be said that using the JSON format reduces the amount of data transfer, and with the use of XML, the readability of data increases.Also, two main ways of data transfer in REST web services were considered: converting the file to Base64 and transferring it as an object field or transferring the file using the usual HTTP multipart. The Base64 standard approach gives a higher speed for multiple files in a single request, because only one HTTP connection is created, but these files are stored in RAM during request processing, which increases chance of the application crashing.In the conclusion, the advantages of using web services and their wide use in other architectural approaches were considered, which increases the popularity of web services.

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

    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

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

    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

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

    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.

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

    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.

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

    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.

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

    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.

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

    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

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

    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.

  8. A New Approach to Eliminate High Amplitude Artifacts in EEG Signals

    Ana Rita Teixeira

    2016-09-01

    Full Text Available High amplitude artifacts represent a problem during EEG recordings in neuroscience research. Taking this into account, this paper proposes a method to identify high amplitude artifacts with no requirement for visual inspection, electrooscillogram (EOG reference channel or user assigned parameters. A potential solution to the high amplitude artifacts (HAA elimination is presented based on blind source separation methods. The assumption underlying the selection of components is that HAA are independent of the EEG signal and different HAA can be generated during the EEG recordings. Therefore, the number of components related to HAA is variable and depends on the processed signal, which means that the method is adaptable to the input signal. The results show, when removing the HAA artifacts, the delta band is distorted but all the other frequency bands are preserved. A case study with EEG signals recorded while participants performed on the Halstead Category Test (HCT is presented. After HAA removal, data analysis revealed, as expected, an error-related frontal ERP wave: the feedback-related negativity (FRN in response to feedback stimuli.

  9. Use of EEG workload indices for diagnostic monitoring of vigilance decrement.

    Kamzanova, Altyngul T; Kustubayeva, Almira M; Matthews, Gerald

    2014-09-01

    A study was run to test which of five electroencephalographic (EEG) indices was most diagnostic of loss of vigilance at two levels of workload. EEG indices of alertness include conventional spectral power measures as well as indices combining measures from multiple frequency bands, such as the Task Load Index (TLI) and the Engagement Index (El). However, it is unclear which indices are optimal for early detection of loss of vigilance. Ninety-two participants were assigned to one of two experimental conditions, cued (lower workload) and uncued (higher workload), and then performed a 40-min visual vigilance task. Performance on this task is believed to be limited by attentional resource availability. EEG was recorded continuously. Performance, subjective state, and workload were also assessed. The task showed a vigilance decrement in performance; cuing improved performance and reduced subjective workload. Lower-frequency alpha (8 to 10.9 Hz) and TLI were most sensitive to the task parameters. The magnitude of temporal change was larger for lower-frequency alpha. Surprisingly, higher TLI was associated with superior performance. Frontal theta and El were influenced by task workload only in the final period of work. Correlational data also suggested that the indices are distinct from one another. Lower-frequency alpha appears to be the optimal index for monitoring vigilance on the task used here, but further work is needed to test how diagnosticity of EEG indices varies with task demands. Lower-frequency alpha may be used to diagnose loss of operator alertness on tasks requiring vigilance.

  10. Rapid prototyping of an EEG-based brain-computer interface (BCI).

    Guger, C; Schlögl, A; Neuper, C; Walterspacher, D; Strein, T; Pfurtscheller, G

    2001-03-01

    The electroencephalogram (EEG) is modified by motor imagery and can be used by patients with severe motor impairments (e.g., late stage of amyotrophic lateral sclerosis) to communicate with their environment. Such a direct connection between the brain and the computer is known as an EEG-based brain-computer interface (BCI). This paper describes a new type of BCI system that uses rapid prototyping to enable a fast transition of various types of parameter estimation and classification algorithms to real-time implementation and testing. Rapid prototyping is possible by using Matlab, Simulink, and the Real-Time Workshop. It is shown how to automate real-time experiments and perform the interplay between on-line experiments and offline analysis. The system is able to process multiple EEG channels on-line and operates under Windows 95 in real-time on a standard PC without an additional digital signal processor (DSP) board. The BCI can be controlled over the Internet, LAN or modem. This BCI was tested on 3 subjects whose task it was to imagine either left or right hand movement. A classification accuracy between 70% and 95% could be achieved with two EEG channels after some sessions with feedback using an adaptive autoregressive (AAR) model and linear discriminant analysis (LDA).

  11. Rest requirements and rest management of personnel in shift work

    Hammell, B.D. [PDG Environmental, Melbourne, FL (United States); Scheuerle, A. [Univ. of Texas, Houston, TX (United States)

    1995-12-31

    A difficulty-weighted shift assignment scheme is proposed for use in prolonged and strenuous field operations such as emergency response, site testing, and short term hazardous waste remediation projects. The purpose of the work rotation plan is to increase productivity, safety, and moral of workers. Job weighting is accomplished by assigning adjustments to the mental and physical intensity of the task, the protective equipment worn, and the climatic conditions. The plan is based on medical studies of sleep deprivation, the effects of rest adjustments, and programs to reduce sleep deprivation and normalize shift schedules.

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

    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.

  13. Rest but busy: Aberrant resting-state functional connectivity of triple network model in insomnia.

    Dong, Xiaojuan; Qin, Haixia; Wu, Taoyu; Hu, Hua; Liao, Keren; Cheng, Fei; Gao, Dong; Lei, Xu

    2018-02-01

    One classical hypothesis among many models to explain the etiology and maintenance of insomnia disorder (ID) is hyperarousal. Aberrant functional connectivity among resting-state large-scale brain networks may be the underlying neurological mechanisms of this hypothesis. The aim of current study was to investigate the functional network connectivity (FNC) among large-scale brain networks in patients with insomnia disorder (ID) during resting state. In the present study, the resting-state fMRI was used to evaluate whether patients with ID showed aberrant FNC among dorsal attention network (DAN), frontoparietal control network (FPC), anterior default mode network (aDMN), and posterior default mode network (pDMN) compared with healthy good sleepers (HGSs). The Pearson's correlation analysis was employed to explore whether the abnormal FNC observed in patients with ID was associated with sleep parameters, cognitive and emotional scores, and behavioral performance assessed by questionnaires and tasks. Patients with ID had worse subjective thought control ability measured by Thought Control Ability Questionnaire (TCAQ) and more negative affect than HGSs. Intriguingly, relative to HGSs, patients with ID showed a significant increase in FNC between DAN and FPC, but a significant decrease in FNC between aDMN and pDMN. Exploratory analysis in patients with ID revealed a significantly positive correlation between the DAN-FPC FNC and reaction time (RT) of psychomotor vigilance task (PVT). The current study demonstrated that even during the resting state, the task-activated and task-deactivated large-scale brain networks in insomniacs may still maintain a hyperarousal state, looking quite similar to the pattern in a task condition with external stimuli. Those results support the hyperarousal model of insomnia.

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

    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.

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

    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.

  16. Screening EEG in Aircrew Selection: Clinical Aerospace Neurology Perspective

    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

  17. Sustainable Rest Area Design and Operations

    2017-10-01

    One way in which State Departments of Transportation (DOTs) can modernize their rest areas while reducing operations and maintenance costs is by incorporating sustainable practices into rest area design and operations. Sustainability practices that D...

  18. Analytic sensing for multi-layer spherical models with application to EEG source imaging

    Kandaswamy, Djano; Blu, Thierry; Van De Ville, Dimitri

    2013-01-01

    Source imaging maps back boundary measurements to underlying generators within the domain; e. g., retrieving the parameters of the generating dipoles from electrical potential measurements on the scalp such as in electroencephalography (EEG). Fitting such a parametric source model is non-linear in the positions of the sources and renewed interest in mathematical imaging has led to several promising approaches. One important step in these methods is the application of a sensing principle that ...

  19. The role of the standard EEG in clinical psychiatry.

    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.

  20. Restful API Architecture Based on Laravel Framework

    Chen, Xianjun; Ji, Zhoupeng; Fan, Yu; Zhan, Yongsong

    2017-10-01

    Web service has been an industry standard tech for message communication and integration between heterogeneous systems. RESTFUL API has become mainstream web service development paradigm after SOAP, how to effectively construct RESTFUL API remains a research hotspots. This paper presents a development model of RESTFUL API construction based on PHP language and LARAVEL framework. The key technical problems that need to be solved during the construction of RESTFUL API are discussed, and implementation details based on LARAVEL are given.

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

    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.

  2. EEG source space analysis of the supervised factor analytic approach for the classification of multi-directional arm movement

    Shenoy Handiru, Vikram; Vinod, A. P.; Guan, Cuntai

    2017-08-01

    Objective. In electroencephalography (EEG)-based brain-computer interface (BCI) systems for motor control tasks the conventional practice is to decode motor intentions by using scalp EEG. However, scalp EEG only reveals certain limited information about the complex tasks of movement with a higher degree of freedom. Therefore, our objective is to investigate the effectiveness of source-space EEG in extracting relevant features that discriminate arm movement in multiple directions. Approach. We have proposed a novel feature extraction algorithm based on supervised factor analysis that models the data from source-space EEG. To this end, we computed the features from the source dipoles confined to Brodmann areas of interest (BA4a, BA4p and BA6). Further, we embedded class-wise labels of multi-direction (multi-class) source-space EEG to an unsupervised factor analysis to make it into a supervised learning method. Main Results. Our approach provided an average decoding accuracy of 71% for the classification of hand movement in four orthogonal directions, that is significantly higher (>10%) than the classification accuracy obtained using state-of-the-art spatial pattern features in sensor space. Also, the group analysis on the spectral characteristics of source-space EEG indicates that the slow cortical potentials from a set of cortical source dipoles reveal discriminative information regarding the movement parameter, direction. Significance. This study presents evidence that low-frequency components in the source space play an important role in movement kinematics, and thus it may lead to new strategies for BCI-based neurorehabilitation.

  3. 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

    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.

  4. Mach's principle and the rest mass of the graviton

    Woodward, J.F.; Crowley, R.J.; Yourgrau, W.

    1975-01-01

    The question of the graviton rest mass is briefly discussed and then it is shown that the Sciama-Dicke formulation of Mach's principle admits, in the linear approximation, the calculation of the graviton rest mass. One finds that the value of the graviton rest mass depends on the cosmological model adopted, the mean matter density in the universe, the speed of light, and the constant of gravitation. The value obtained for an infinite, stationary universe is 7.6 times 10 -67 g. The value for evolutionary cosmological models is found to depend critically on the mass and ''radius'' of the universe, both null and non-null values occurring only for certain values of these parameters. Problems that arise as a consequence of the linear approximation are pointed out

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

    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.

  6. Classifying Drivers' Cognitive Load Using EEG Signals.

    Barua, Shaibal; Ahmed, Mobyen Uddin; Begum, Shahina

    2017-01-01

    A growing traffic safety issue is the effect of cognitive loading activities on traffic safety and driving performance. To monitor drivers' mental state, understanding cognitive load is important since while driving, performing cognitively loading secondary tasks, for example talking on the phone, can affect the performance in the primary task, i.e. driving. Electroencephalography (EEG) is one of the reliable measures of cognitive load that can detect the changes in instantaneous load and effect of cognitively loading secondary task. In this driving simulator study, 1-back task is carried out while the driver performs three different simulated driving scenarios. This paper presents an EEG based approach to classify a drivers' level of cognitive load using Case-Based Reasoning (CBR). The results show that for each individual scenario as well as using data combined from the different scenarios, CBR based system achieved approximately over 70% of classification accuracy.

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

    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.

  8. An EEG Data Investigation Using Only Artifacts

    2017-02-22

    hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and...some conditions, an automation feature was implemented to help the participants find the HVT. When the HVT was within the sensor footprint, a tone...EEG Data Investigation Using Only Artifacts 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 1 Chelsey

  9. Detection of EEG electrodes in brain volumes.

    Graffigna, Juan P; Gómez, M Eugenia; Bustos, José J

    2010-01-01

    This paper presents a method to detect 128 EEG electrodes in image study and to merge with the Nuclear Magnetic Resonance volume for better diagnosis. First we propose three hypotheses to define a specific acquisition protocol in order to recognize the electrodes and to avoid distortions in the image. In the second instance we describe a method for segmenting the electrodes. Finally, registration is performed between volume of the electrodes and NMR.

  10. Human brain networks in physiological aging: a graph theoretical analysis of cortical connectivity from EEG data.

    Vecchio, Fabrizio; Miraglia, Francesca; Bramanti, Placido; Rossini, Paolo Maria

    2014-01-01

    Modern analysis of electroencephalographic (EEG) rhythms provides information on dynamic brain connectivity. To test the hypothesis that aging processes modulate the brain connectivity network, EEG recording was conducted on 113 healthy volunteers. They were divided into three groups in accordance with their ages: 36 Young (15-45 years), 46 Adult (50-70 years), and 31 Elderly (>70 years). To evaluate the stability of the investigated parameters, a subgroup of 10 subjects underwent a second EEG recording two weeks later. Graph theory functions were applied to the undirected and weighted networks obtained by the lagged linear coherence evaluated by eLORETA on cortical sources. EEG frequency bands of interest were: delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), beta2 (20-30 Hz), and gamma (30-40 Hz). The spectral connectivity analysis of cortical sources showed that the normalized Characteristic Path Length (λ) presented the pattern Young > Adult>Elderly in the higher alpha band. Elderly also showed a greater increase in delta and theta bands than Young. The correlation between age and λ showed that higher ages corresponded to higher λ in delta and theta and lower in the alpha2 band; this pattern reflects the age-related modulation of higher (alpha) and decreased (delta) connectivity. The Normalized Clustering coefficient (γ) and small-world network modeling (σ) showed non-significant age-modulation. Evidence from the present study suggests that graph theory can aid in the analysis of connectivity patterns estimated from EEG and can facilitate the study of the physiological and pathological brain aging features of functional connectivity networks.

  11. Marked EEG worsening following Levetiracetam overdose: How a pharmacological issue can confound coma prognosis.

    Bouchier, Baptiste; Demarquay, Geneviève; Guérin, Claude; André-Obadia, Nathalie; Gobert, Florent

    2017-01-01

    Levetiracetam is an anti-epileptic drug commonly used in intensive care when seizure is suspected as a possible cause of coma. We propose to question the cofounding effect of Levetiracetam during the prognostication process in a case of anoxic coma. We report the story of a young woman presenting a comatose state following a hypoxic cardiac arrest. After a first EEG presenting an intermediate EEG pattern, a seizure suspicion led to prescribe Levetiracetam. The EEG showed then the appearance of burst suppression, which was compatible with a very severe pattern of post-anoxic coma. This aggravation was in fact related to an overdose of Levetiracetam (the only medication introduced recently) and was reversible after Levetiracetam cessation. The increased plasmatic dosages of Levetiracetam confirming this overdose could have been favoured by a moderate reduction of renal clearance, previously underestimated because of a low body-weight. This EEG dynamic was unexpected under Levetiracetam and could sign a functional instability after anoxia. Burst suppression is classically observed with high doses of anaesthetics, but is not expected after a minor anti-epileptic drug. This report proposes that Levetiracetam tolerance might not be straightforward after brain lesions and engages us to avoid confounding factors during the awakening prognostication, which is mainly based on the severity of the EEG. Hence, prognosis should not be decided on an isolated parameter, especially if the dynamic is atypical after a new prescription, even for well-known drugs. For any suspicion, the drug's dosage and replacement should be managed before any premature care's withdrawal. Copyright © 2016 Elsevier B.V. All rights reserved.

  12. Induction and separation of motion artifacts in EEG data using a mobile phantom head device.

    Oliveira, Anderson S; Schlink, Bryan R; Hairston, W David; König, Peter; Ferris, Daniel P

    2016-06-01

    Electroencephalography (EEG) can assess brain activity during whole-body motion in humans but head motion can induce artifacts that obfuscate electrocortical signals. Definitive solutions for removing motion artifact from EEG have yet to be found, so creating methods to assess signal processing routines for removing motion artifact are needed. We present a novel method for investigating the influence of head motion on EEG recordings as well as for assessing the efficacy of signal processing approaches intended to remove motion artifact. We used a phantom head device to mimic electrical properties of the human head with three controlled dipolar sources of electrical activity embedded in the phantom. We induced sinusoidal vertical motions on the phantom head using a custom-built platform and recorded EEG signals with three different acquisition systems while the head was both stationary and in varied motion conditions. Recordings showed up to 80% reductions in signal-to-noise ratio (SNR) and up to 3600% increases in the power spectrum as a function of motion amplitude and frequency. Independent component analysis (ICA) successfully isolated the three dipolar sources across all conditions and systems. There was a high correlation (r > 0.85) and marginal increase in the independent components' (ICs) power spectrum (∼15%) when comparing stationary and motion parameters. The SNR of the IC activation was 400%-700% higher in comparison to the channel data SNR, attenuating the effects of motion on SNR. Our results suggest that the phantom head and motion platform can be used to assess motion artifact removal algorithms and compare different EEG systems for motion artifact sensitivity. In addition, ICA is effective in isolating target electrocortical events and marginally improving SNR in relation to stationary recordings.

  13. 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.

    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.

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

    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”.

  15. Automated Detection of Driver Fatigue Based on AdaBoost Classifier with EEG Signals

    Jianfeng Hu

    2017-08-01

    Full Text Available Purpose: Driving fatigue has become one of the important causes of road accidents, there are many researches to analyze driver fatigue. EEG is becoming increasingly useful in the measuring fatigue state. Manual interpretation of EEG signals is impossible, so an effective method for automatic detection of EEG signals is crucial needed.Method: In order to evaluate the complex, unstable, and non-linear characteristics of EEG signals, four feature sets were computed from EEG signals, in which fuzzy entropy (FE, sample entropy (SE, approximate Entropy (AE, spectral entropy (PE, and combined entropies (FE + SE + AE + PE were included. All these feature sets were used as the input vectors of AdaBoost classifier, a boosting method which is fast and highly accurate. To assess our method, several experiments including parameter setting and classifier comparison were conducted on 28 subjects. For comparison, Decision Trees (DT, Support Vector Machine (SVM and Naive Bayes (NB classifiers are used.Results: The proposed method (combination of FE and AdaBoost yields superior performance than other schemes. Using FE feature extractor, AdaBoost achieves improved area (AUC under the receiver operating curve of 0.994, error rate (ERR of 0.024, Precision of 0.969, Recall of 0.984, F1 score of 0.976, and Matthews correlation coefficient (MCC of 0.952, compared to SVM (ERR at 0.035, Precision of 0.957, Recall of 0.974, F1 score of 0.966, and MCC of 0.930 with AUC of 0.990, DT (ERR at 0.142, Precision of 0.857, Recall of 0.859, F1 score of 0.966, and MCC of 0.716 with AUC of 0.916 and NB (ERR at 0.405, Precision of 0.646, Recall of 0.434, F1 score of 0.519, and MCC of 0.203 with AUC of 0.606. It shows that the FE feature set and combined feature set outperform other feature sets. AdaBoost seems to have better robustness against changes of ratio of test samples for all samples and number of subjects, which might therefore aid in the real-time detection of driver

  16. Wearable ear EEG for brain interfacing

    Schroeder, Eric D.; Walker, Nicholas; Danko, Amanda S.

    2017-02-01

    Brain-computer interfaces (BCIs) measuring electrical activity via electroencephalogram (EEG) have evolved beyond clinical applications to become wireless consumer products. Typically marketed for meditation and neu- rotherapy, these devices are limited in scope and currently too obtrusive to be a ubiquitous wearable. Stemming from recent advancements made in hearing aid technology, wearables have been shrinking to the point that the necessary sensors, circuitry, and batteries can be fit into a small in-ear wearable device. In this work, an ear-EEG device is created with a novel system for artifact removal and signal interpretation. The small, compact, cost-effective, and discreet device is demonstrated against existing consumer electronics in this space for its signal quality, comfort, and usability. A custom mobile application is developed to process raw EEG from each device and display interpreted data to the user. Artifact removal and signal classification is accomplished via a combination of support matrix machines (SMMs) and soft thresholding of relevant statistical properties.

  17. Robust power spectral estimation for EEG data.

    Melman, Tamar; Victor, Jonathan D

    2016-08-01

    Typical electroencephalogram (EEG) recordings often contain substantial artifact. These artifacts, often large and intermittent, can interfere with quantification of the EEG via its power spectrum. To reduce the impact of artifact, EEG records are typically cleaned by a preprocessing stage that removes individual segments or components of the recording. However, such preprocessing can introduce bias, discard available signal, and be labor-intensive. With this motivation, we present a method that uses robust statistics to reduce dependence on preprocessing by minimizing the effect of large intermittent outliers on the spectral estimates. Using the multitaper method (Thomson, 1982) as a starting point, we replaced the final step of the standard power spectrum calculation with a quantile-based estimator, and the Jackknife approach to confidence intervals with a Bayesian approach. The method is implemented in provided MATLAB modules, which extend the widely used Chronux toolbox. Using both simulated and human data, we show that in the presence of large intermittent outliers, the robust method produces improved estimates of the power spectrum, and that the Bayesian confidence intervals yield close-to-veridical coverage factors. The robust method, as compared to the standard method, is less affected by artifact: inclusion of outliers produces fewer changes in the shape of the power spectrum as well as in the coverage factor. In the presence of large intermittent outliers, the robust method can reduce dependence on data preprocessing as compared to standard methods of spectral estimation. Copyright © 2016 Elsevier B.V. All rights reserved.

  18. Rhythms of EEG and cognitive processes

    Novikova S.I.

    2015-06-01

    Full Text Available The study of cognitive processes is regarded to be more effective if it combines a psychological approach with a neurophysiological one. This approach makes it possible to come closer to understanding of the basic mechanisms of different cognitive processes, to describe the patterns of forming these mechanisms in ontogenesis, to investigate the origin of cognitive impairments, and to develop intervention techniques. The promising way of investigating the mechanisms of cognitive functions is the electroencephalography (EEG. This is a non-invasive, safe, and relatively cheap method of research of the functional condition of the brain. The characteristics of EEG rhythms, recorded with different cognitive loads, reflect the processes of functional modulation of neural network activity of the cortex, which serves the neurophysiologic basis for attention, memory and other cognitive processes. The article provides an overview of works containing the analysis of the alpha and theta rhythms’ dynamics in various states of wakefulness. It also introduces the substantiation of methodology of functional regulatory approach to the interpretation of behaviors of EEG rhythms.

  19. Data-driven forward model inference for EEG brain imaging

    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...

  20. Tactile exploration of virtual objects for blind and sighted people: the role of beta 1 EEG band in sensory substitution and supramodal mental mapping

    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...

  1. DCCA cross-correlation coefficients reveals the change of both synchronization and oscillation in EEG of Alzheimer disease patients

    Chen, Yingyuan; Cai, Lihui; Wang, Ruofan; Song, Zhenxi; Deng, Bin; Wang, Jiang; Yu, Haitao

    2018-01-01

    Alzheimer's disease (AD) is a degenerative disorder of neural system that affects mainly the older population. Recently, many researches show that the EEG of AD patients can be characterized by EEG slowing, enhanced complexity of the EEG signals, and EEG synchrony. In order to examine the neural synchrony at multi scales, and to find a biomarker that help detecting AD in diagnosis, detrended cross-correlation analysis (DCCA) of EEG signals is applied in this paper. Several parameters, namely DCCA coefficients in the whole brain, DCCA coefficients at a specific scale, maximum DCCA coefficient over the span of all time scales and the corresponding scale of such coefficients, were extracted to examine the synchronization, respectively. The results show that DCCA coefficients have a trend of increase as scale increases, and decreases as electrode distance increases. Comparing DCCA coefficients in AD patients with healthy controls, a decrease of synchronization in the whole brain, and a bigger scale corresponding to maximum correlation is discovered in AD patients. The change of max-correlation scale may relate to the slowing of oscillatory activities. Linear combination of max DCCA coefficient and max-correlation scale reaches a classification accuracy of 90%. From the above results, it is reasonable to conclude that DCCA coefficient reveals the change of both oscillation and synchrony in AD, and thus is a powerful tool to differentiate AD patients from healthy elderly individuals.

  2. Burst suppression in sleep in a routine outpatient EEG

    Ammar Kheder

    2014-01-01

    Full Text Available Burst suppression (BS is an electroencephalogram (EEG pattern that is characterized by brief bursts of spikes, sharp waves, or slow waves of relatively high amplitude alternating with periods of relatively flat EEG or isoelectric periods. The pattern is usually associated with coma, severe encephalopathy of various etiologies, or general anesthesia. We describe an unusual case of anoxic brain injury in which a BS pattern was seen during behaviorally defined sleep during a routine outpatient EEG study.

  3. Transfer function between EEG and BOLD signals of epileptic activity

    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.

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

    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.

  5. [Daytime tiredness correlated with nocturnal respiratory and arousal variables in patients with sleep apnea: polysomnographic and EEG mapping studies].

    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.

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

    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

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

    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

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

    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...

  9. EEG simulation by 2D interconnected chaotic oscillators

    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.

  10. EEG Signal Decomposition and Improved Spectral Analysis Using Wavelet Transform

    Bhatti, Muhammad

    2001-01-01

    EEG (Electroencephalograph), as a noninvasive testing method, plays a key role in the diagnosing diseases, and is useful for both physiological research and medical applications. Wavelet transform (WT...

  11. Synchronization of EEG activity in patients with bipolar disorder

    Panischev, O Yu; Demin, S A; Muhametshin, I G; Yu Demina, N

    2015-01-01

    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. (paper)

  12. Synchronization of EEG activity in patients with bipolar disorder

    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.

  13. Deep Neural Architectures for Mapping Scalp to Intracranial EEG.

    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.

  14. EEG simulation by 2D interconnected chaotic oscillators

    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.

  15. Intrasellar Symptomatic Salivary Gland Rest

    Chih-Hao Chen

    2007-05-01

    Full Text Available Ectopic salivary gland tissue in sellar turcica is frequently observed in microscopic examination at autopsy. This tissue is considered clinically silent. Only 2 symptomatic cases have been previously reported. Here we report a 28-year-old woman presenting with galactorrhea and hyperprolactinemia. Magnetic resonance imaging revealed a 6×5-mm nodule in the posterior aspect of the pituitary gland. This nodule showed isointensity on T1- and T2-weighted images and less enhancement on post-contrast T1-weighted images. Transsphenoidal exploration revealed a cystic lesion within the pituitary gland, which consisted of a grayish gelatinous content. The pathologic examination confirmed the diagnosis of salivary gland rest.

  16. Effect of Daytime Exercise on Sleep Eeg and Subjective Sleep

    Sasazawa, Y.; Kawada, T.; Kiryu, Y.

    1997-08-01

    This study was designed to assess the effects of daytime physical exercise on the quality of objective and subjective sleep by examining all-night sleep EEGs. The subjects were five male students, aged 19 to 20 years, who were in the habit of performing regular daytime exercise. The sleep polygraphic parameters in this study were sleep stage time as a percentage of total sleep time (%S1, %S2, %S(3+4), %SREM, %MT), time in bed (TIB), sleep time (ST), total sleep time (TST), sleep onset latency (SOL), waking from sleep, sleep efficiency, number of awakenings, number of stage shifts, number of spindles, and percentages of α and δ waves, all of which were determined by an automatic computer analysis system. The OSA questionnaire was used to investigate subjective sleep. The five scales of the OSA used were sleepiness, sleep maintenance, worry, integrated sleep feeling, and sleep initiation. Each sleep parameter was compared in the exercise and the non-exercise groups. Two-way analysis of variance was applied using subject factor and exercise factor. The main effect of the subject was significant in all parameters and the main effect of exercise in %S(3+4), SOL and sleep efficiency, among the objective sleep parameters. The main effects of the subject, except sleepiness, were significant, as was the main effect of exercise on sleep initiation, among the subjective sleep parameters. These findings suggest that daytime exercise shortened sleep latency and prolonged slow-wave sleep, and that the subjects fell asleep more easily on exercise days. There were also significant individual differences in both the objective and subjective sleep parameters.

  17. Peak and averaged bicoherence for different EEG patterns during general anaesthesia

    Myles Paul

    2010-11-01

    Full Text Available Abstract Background Changes in nonlinear neuronal mechanisms of EEG generation in the course of general anaesthesia have been extensively investigated in research literature. A number of EEG signal properties capable of tracking these changes have been reported and employed in anaesthetic depth monitors. The degree of phase coupling between different spectral components is a marker of nonlinear EEG generators and is claimed to be an important aspect of BIS. While bicoherence is the most direct measure of phase coupling, according to published research it is not directly used in the calculation of BIS, and only limited studies of its association with anaesthetic depth and level of consciousness have been published. This paper investigates bicoherence parameters across equal band and unequal band bifrequency regions, during different states of anaesthetic depth relating to routine clinical anaesthesia, as determined by visual inspection of EEG. Methods 41 subjects scheduled for day surgery under general anaesthesia were recruited into this study. EEG bicoherence was analysed using average and smoothed-peak estimates calculated over different regions on the bifrequency plane. Statistical analysis of associations between anaesthetic depth/state of consciousness and bicoherence estimates included linear regression using generalised linear mixed effects models (GLMs, ROC curves and prediction probability (Pk. Results Bicoherence estimates for the δ_θ region on the bifrequency plane were more sensitive to anaesthetic depth changes compared to other bifrequency regions. Smoothed-peak bicoherence displayed stronger associations than average bicoherence. Excluding burst suppression and large transients, the δ_θ peak bicoherence was significantly associated with level of anaesthetic depth (z = 25.74, p 2 = 0.191. Estimates of Pk for this parameter were 0.889(0.867-0.911 and 0.709(0.689-0.729 respectively for conscious states and anaesthetic depth

  18. A neural mass model of interconnected regions simulates rhythm propagation observed via TMS-EEG.

    Cona, F; Zavaglia, M; Massimini, M; Rosanova, M; Ursino, M

    2011-08-01

    Knowledge of cortical rhythms represents an important aspect of modern neuroscience, to understand how the brain realizes its functions. Recent data suggest that different regions in the brain may exhibit distinct electroencephalogram (EEG) rhythms when perturbed by Transcranial Magnetic Stimulation (TMS) and that these rhythms can change due to the connectivity among regions. In this context, in silico simulations may help the validation of these hypotheses that would be difficult to be verified in vivo. Neural mass models can be very useful to simulate specific aspects of electrical brain activity and, above all, to analyze and identify the overall frequency content of EEG in a cortical region of interest (ROI). In this work we implemented a model of connectivity among cortical regions to fit the impulse responses in three ROIs recorded during a series of TMS/EEG experiments performed in five subjects and using three different impulse intensities. In particular we investigated Brodmann Area (BA) 19 (occipital lobe), BA 7 (parietal lobe) and BA 6 (frontal lobe). Results show that the model can reproduce the natural rhythms of the three regions quite well, acting on a few internal parameters. Moreover, the model can explain most rhythm changes induced by stimulation of another region, and inter-subject variability, by estimating just a few long-range connectivity parameters among ROIs. Copyright © 2011 Elsevier Inc. All rights reserved.

  19. EEG Channel Selection Using Particle Swarm Optimization for the Classification of Auditory Event-Related Potentials

    Alejandro Gonzalez

    2014-01-01

    Full Text Available Brain-machine interfaces (BMI rely on the accurate classification of event-related potentials (ERPs and their performance greatly depends on the appropriate selection of classifier parameters and features from dense-array electroencephalography (EEG signals. Moreover, in order to achieve a portable and more compact BMI for practical applications, it is also desirable to use a system capable of accurate classification using information from as few EEG channels as possible. In the present work, we propose a method for classifying P300 ERPs using a combination of Fisher Discriminant Analysis (FDA and a multiobjective hybrid real-binary Particle Swarm Optimization (MHPSO algorithm. Specifically, the algorithm searches for the set of EEG channels and classifier parameters that simultaneously maximize the classification accuracy and minimize the number of used channels. The performance of the method is assessed through offline analyses on datasets of auditory ERPs from sound discrimination experiments. The proposed method achieved a higher classification accuracy than that achieved by traditional methods while also using fewer channels. It was also found that the number of channels used for classification can be significantly reduced without greatly compromising the classification accuracy.

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

    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.

  1. Transient Effect of the Noise of Passing Trucks on Sleep Eeg

    Suzuki, S.; Kawada, T.; Kiryu, Y.; Sasazawa, Y.; Tamura, Y.

    1997-08-01

    Twelve subjects were exposed to the noise of passing trucks at peak levels of 45, 50, 55 and 60 dB(A) for 15 min intervals throughout the night each for seven to 12 nights. Effects of the noise were observed by sleep electroencephalography (EEG). Three EEG parameters were affected by the noise event during stage 2. The number of spindles per epoch was depressed on average from 1·78 to 1·02 spindles per epoch or to 57% by the noise event of 60 dB(A), which lasted for only one minute. The threshold level for inducing the decrease was 32 dB(A), as assessed by a regression equation. Time % delta wave was depressed for six minutes, with a threshold level of 41 dB(A). The integral EMG increased in response to the noise event for one minute, and the threshold level for the integral EMG was 34 dB(A).

  2. Matching pursuit and source deflation for sparse EEG/MEG dipole moment estimation.

    Wu, Shun Chi; Swindlehurst, A Lee

    2013-08-01

    In this paper, we propose novel matching pursuit (MP)-based algorithms for EEG/MEG dipole source localization and parameter estimation for multiple measurement vectors with constant sparsity. The algorithms combine the ideas of MP for sparse signal recovery and source deflation, as employed in estimation via alternating projections. The source-deflated matching pursuit (SDMP) approach mitigates the problem of residual interference inherent in sequential MP-based methods or recursively applied (RAP)-MUSIC. Furthermore, unlike prior methods based on alternating projection, SDMP allows one to efficiently estimate the dipole orientation in addition to its location. Simulations show that the proposed algorithms outperform existing techniques under various conditions, including those with highly correlated sources. Results using real EEG data from auditory experiments are also presented to illustrate the performance of these algorithms.

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

    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.

  4. Comparison of different Kalman filter approaches in deriving time varying connectivity from EEG data.

    Ghumare, Eshwar; Schrooten, Maarten; Vandenberghe, Rik; Dupont, Patrick

    2015-08-01

    Kalman filter approaches are widely applied to derive time varying effective connectivity from electroencephalographic (EEG) data. For multi-trial data, a classical Kalman filter (CKF) designed for the estimation of single trial data, can be implemented by trial-averaging the data or by averaging single trial estimates. A general linear Kalman filter (GLKF) provides an extension for multi-trial data. In this work, we studied the performance of the different Kalman filtering approaches for different values of signal-to-noise ratio (SNR), number of trials and number of EEG channels. We used a simulated model from which we calculated scalp recordings. From these recordings, we estimated cortical sources. Multivariate autoregressive model parameters and partial directed coherence was calculated for these estimated sources and compared with the ground-truth. The results showed an overall superior performance of GLKF except for low levels of SNR and number of trials.

  5. Standardized Computer-based Organized Reporting of EEG: SCORE

    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

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

    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.

  7. Detecting interictal discharges in first seizure patients: ambulatory EEG or EEG after sleep deprivation?

    Geut, I.; Weenink, S.; Knottnerus, I.L.H.; van Putten, Michel J.A.M.

    2017-01-01

    Purpose Uncertainty about recurrence after a first unprovoked seizure is a significant psychological burden for patients, and motivates the need for diagnostic tools with high sensitivity and specificity to assess recurrence risk. As the sensitivity of a routine EEG after a first unprovoked seizure

  8. Hippocampal EEG and behaviour in dog. I. Hippocampal EEG correlates of gross motor behaviour

    Arnolds, D.E.A.T.; Lopes da Silva, F.H.; Aitink, J.W.; Kamp, A.

    It was shown that rewarding spectral shifts (i.e. increase in amplitude or peak frequency of the hippocampal EEG) causes a solitary dog to show increased motor behaviour. Rewarded spectral shifts concurred with a variety of behavioural transitions. It was found that statistically significant

  9. A simple system for detection of EEG artifacts in polysomnographic recordings.

    Durka, P J; Klekowicz, H; Blinowska, K J; Szelenberger, W; Niemcewicz, Sz

    2003-04-01

    We present an efficient parametric system for automatic detection of electroencephalogram (EEG) artifacts in polysomnographic recordings. For each of the selected types of artifacts, a relevant parameter was calculated for a given epoch. If any of these parameters exceeded a threshold, the epoch was marked as an artifact. Performance of the system, evaluated on 18 overnight polysomnographic recordings, revealed concordance with decisions of human experts close to the interexpert agreement and the repeatability of expert's decisions, assessed via a double-blind test. Complete software (Matlab source code) for the presented system is freely available from the Internet at http://brain.fuw.edu.pl/artifacts.

  10. Spatio Temporal EEG Source Imaging with the Hierarchical Bayesian Elastic Net and Elitist Lasso Models.

    Paz-Linares, Deirel; Vega-Hernández, Mayrim; Rojas-López, Pedro A; Valdés-Hernández, Pedro A; Martínez-Montes, Eduardo; Valdés-Sosa, Pedro A

    2017-01-01

    The estimation of EEG generating sources constitutes an Inverse Problem (IP) in Neuroscience. This is an ill-posed problem due to the non-uniqueness of the solution and regularization or prior information is needed to undertake Electrophysiology Source Imaging. Structured Sparsity priors can be attained through combinations of (L1 norm-based) and (L2 norm-based) constraints such as the Elastic Net (ENET) and Elitist Lasso (ELASSO) models. The former model is used to find solutions with a small number of smooth nonzero patches, while the latter imposes different degrees of sparsity simultaneously along different dimensions of the spatio-temporal matrix solutions. Both models have been addressed within the penalized regression approach, where the regularization parameters are selected heuristically, leading usually to non-optimal and computationally expensive solutions. The existing Bayesian formulation of ENET allows hyperparameter learning, but using the computationally intensive Monte Carlo/Expectation Maximization methods, which makes impractical its application to the EEG IP. While the ELASSO have not been considered before into the Bayesian context. In this work, we attempt to solve the EEG IP using a Bayesian framework for ENET and ELASSO models. We propose a Structured Sparse Bayesian Learning algorithm based on combining the Empirical Bayes and the iterative coordinate descent procedures to estimate both the parameters and hyperparameters. Using realistic simulations and avoiding the inverse crime we illustrate that our methods are able to recover complicated source setups more accurately and with a more robust estimation of the hyperparameters and behavior under different sparsity scenarios than classical LORETA, ENET and LASSO Fusion solutions. We also solve the EEG IP using data from a visual attention experiment, finding more interpretable neurophysiological patterns with our methods. The Matlab codes used in this work, including Simulations, Methods

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

    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.

  12. Brain dynamics of post-task resting state are influenced by expertise: Insights from baseball players.

    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

  13. EEG patterns from acute to chronic stroke phases in focal cerebral ischemic rats: correlations with functional recovery.

    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

  14. EEG patterns from acute to chronic stroke phases in focal cerebral ischemic rats: correlations with functional recovery

    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

  15. Long-term EEG in children.

    Montavont, A; Kaminska, A; Soufflet, C; Taussig, D

    2015-03-01

    Long-term video-EEG corresponds to a recording ranging from 1 to 24 h or even longer. It is indicated in the following situations: diagnosis of epileptic syndromes or unclassified epilepsy, pre-surgical evaluation for drug-resistant epilepsy, follow-up of epilepsy or in cases of paroxysmal symptoms whose etiology remains uncertain. There are some specificities related to paediatric care: a dedicated pediatric unit; continuous monitoring covering at least a full 24-hour period, especially in the context of pre-surgical evaluation; the requirement of presence by the parents, technician or nurse; and stronger attachment of electrodes (cup electrodes), the number of which is adapted to the age of the child. The chosen duration of the monitoring also depends on the frequency of seizures or paroxysmal events. The polygraphy must be adapted to the type and topography of movements. It is essential to have at least an electrocardiography (ECG) channel, respiratory sensor and electromyography (EMG) on both deltoids. There is no age limit for performing long-term video-EEG even in newborns and infants; nevertheless because of scalp fragility, strict surveillance of the baby's skin condition is required. In the specific context of pre-surgical evaluation, long-term video-EEG must record all types of seizures observed in the child. This monitoring is essential in order to develop hypotheses regarding the seizure onset zone, based on electroclinical correlations, which should be adapted to the child's age and the psychomotor development. Copyright © 2015. Published by Elsevier SAS.

  16. EEG-Annotate: Automated identification and labeling of events in continuous signals with applications to EEG.

    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.

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

    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%.

  18. Pro REST API development with nodejs

    Doglio, Fernando

    2015-01-01

    Pro REST API Development with Node.js is your guide to managing and understanding the full capabilities of successful REST development. API design is a hot topic in the programming world, but not many resources exist for developers to really understand how you can leverage the advantages. This book will provide a brief background on REST and the tools it provides (well known and not so well known). Understand how there is more to REST than just JSON and URLs. You will then cover and compare the maintained modules currently available in the npm community, including Express, Restify, Vatican,

  19. Relationship between brain function (aEEG) and brain structure (MRI) and their predictive value for neurodevelopmental outcome of preterm infants.

    Hüning, Britta; Storbeck, Tobias; Bruns, Nora; Dransfeld, Frauke; Hobrecht, Julia; Karpienski, Julia; Sirin, Selma; Schweiger, Bernd; Weiss, Christel; Felderhoff-Müser, Ursula; Müller, Hanna

    2018-05-22

    To improve the prediction of neurodevelopmental outcome in very preterm infants, this study used the combination of amplitude-integrated electroencephalography (aEEG) within the first 72 h of life and cranial magnetic resonance imaging (MRI) at term equivalent age. A single-center cohort of 38 infants born before 32 weeks of gestation was subjected to both investigations. Structural measurements were performed on MRI. Multiple regression analysis was used to identify independent factors including functional and structural brain measurements associated with outcome at a corrected age of 24 months. aEEG parameters significantly correlated with MRI measurements. Reduced deep gray matter volume was associated with low Burdjalov Score on day 3 (p neurodevelopmental outcome: intraventricular hemorrhage (p = 0.0060) and interhemispheric distance (p = 0.0052) for mental developmental index; Burdjalov Score day 1 (p = 0.0201) and interhemispheric distance (p = 0.0142) for psychomotor developmental index. Functional aEEG parameters were associated with altered brain maturation on MRI. The combination of aEEG and MRI contributes to the prediction of outcome at 24 months. What is Known: • Prematurity remains a risk factor for impaired neurodevelopment. • aEEG is used to measure brain activity in preterm infants and cranial MRI is performed to identify structural gray and white matter abnormalities with impact on neurodevelopmental outcome. What is New: • aEEG parameters observed within the first 72 h of life were associated with altered deep gray matter volumes, biparietal width, and transcerebellar diameter at term equivalent age. • The combination of aEEG and MRI contributes to the prediction of neurodevelopmental outcome at 2 years of corrected age in very preterm infants.

  20. Standardized EEG interpretation accurately predicts prognosis after cardiac arrest

    Westhall, Erik; Rossetti, Andrea O.; van Rootselaar, Anne-Fleur; Wesenberg Kjaer, Troels; Horn, Janneke; Ullén, Susann; Friberg, Hans; Nielsen, Niklas; Rosén, Ingmar; Åneman, Anders; Erlinge, David; Gasche, Yvan; Hassager, Christian; Hovdenes, Jan; Kjaergaard, Jesper; Kuiper, Michael; Pellis, Tommaso; Stammet, Pascal; Wanscher, Michael; Wetterslev, Jørn; Wise, Matt P.; Cronberg, Tobias; Saxena, Manoj; Miller, Jennene; Inskip, Deborah; Macken, Lewis; Finfer, Simon; Eatough, Noel; Hammond, Naomi; Bass, Frances; Yarad, Elizabeth; O'Connor, Anne; Bird, Simon; Jewell, Timothy; Davies, Gareth; Ng, Karl; Coward, Sharon; Stewart, Antony; Micallef, Sharon; Parker, Sharyn; Cortado, Dennis; Gould, Ann; Harward, Meg; Thompson, Kelly; Glass, Parisa; Myburgh, John; Smid, Ondrej; Belholavek, Jan; Juffermans, Nicole P.; Boerma, EC

    2016-01-01

    To identify reliable predictors of outcome in comatose patients after cardiac arrest using a single routine EEG and standardized interpretation according to the terminology proposed by the American Clinical Neurophysiology Society. In this cohort study, 4 EEG specialists, blinded to outcome,

  1. Convolutive ICA for Spatio-Temporal Analysis of EEG

    Dyrholm, Mads; Makeig, Scott; Hansen, Lars Kai

    2007-01-01

    in the convolutive model can be correctly detected using Bayesian model selection. We demonstrate a framework for deconvolving an EEG ICA subspace. Initial results suggest that in some cases convolutive mixing may be a more realistic model for EEG signals than the instantaneous ICA model....

  2. Using EEG to Study Cognitive Development: Issues and Practices

    Bell, Martha Ann; Cuevas, Kimberly

    2012-01-01

    Developmental research is enhanced by use of multiple methodologies for examining psychological processes. The electroencephalogram (EEG) is an efficient and relatively inexpensive method for the study of developmental changes in brain-behavior relations. In this review, we highlight some of the challenges for using EEG in cognitive development…

  3. Correlations of CT and EEG findings in brain affections

    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)

  4. EOG Artifacts Removal in EEG Measurements for Affective Interaction

    Qi, Wen

    2014-01-01

    A brain-computer interface (BCI) is a direct link between the brain and a computer. Multi-modal input with BCI forms a promising solution for creating rich gaming experience. Electroencephalography (EEG) measurement is the sole necessary component for a BCI system. EEG signals have the

  5. EEG Signal Classification With Super-Dirichlet Mixture Model

    Ma, Zhanyu; Tan, Zheng-Hua; Prasad, Swati

    2012-01-01

    Classification of the Electroencephalogram (EEG) signal is a challengeable task in the brain-computer interface systems. The marginalized discrete wavelet transform (mDWT) coefficients extracted from the EEG signals have been frequently used in researches since they reveal features related...

  6. Quantitative EEG Applying the Statistical Recognition Pattern Method

    Engedal, Knut; Snaedal, Jon; Hoegh, Peter

    2015-01-01

    BACKGROUND/AIM: The aim of this study was to examine the discriminatory power of quantitative EEG (qEEG) applying the statistical pattern recognition (SPR) method to separate Alzheimer's disease (AD) patients from elderly individuals without dementia and from other dementia patients. METHODS...

  7. A computerised EEG-analyzing system for small laboratory animals

    Kropveld, D.; Chamuleau, R. A.; Popken, R. J.; Smith, J.

    1983-01-01

    The experimental setup, including instrumentation and software packaging, is described for the use of a minicomputer as an on-line analyzing system of the EEG in rats. Complete fast Fourier transformation of the EEG sampled in 15 episodes of 10 s each is plotted out within 7 min after the start of

  8. Diagnostic Role of ECG Recording Simultaneously With EEG Testing.

    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.

  9. A comparison of EEG spectral entropy with conventional quantitative ...

    Adele

    and decrease with increasing depth of anaesthesia. Spectral en- tropy yields two scales: Response Entropy (RE), ranging between. 0 to100, is an amalgam of EEG and frontal muscle activity while. State Entropy (SE), consisting mainly of EEG activity in a lower frequency band, ranges from 0 to 91.2 Initial reports have pro-.

  10. Recording EEG In Young Children Without Sedation | Curuneaux ...

    Background Although it has been considered that sedation in children undergoing EEG tests is effective and safe and complications are infrequent, occasionally adverse sedation-related events are presented. Objective The aim of this work was to determine if it is possible to carry out EEG in children up to 4 years old ...

  11. The effect of CPAP treatment on EEG of OSAS patients.

    Zhang, Cheng; Lv, Jun; Zhou, Junhong; Su, Li; Feng, Liping; Ma, Jing; Wang, Guangfa; Zhang, Jue

    2015-12-01

    Continuous positive airway pressure (CPAP) is currently the most effective treatment method for obstructive sleep apnea syndrome (OSAS). The purpose of this study was to compare the sleep electroencephalogram (EEG) changes before and after the application of CPAP to OSAS patients. A retrospective study was conducted and 45 sequential patients who received both polysomnography (PSG) and CPAP titration were included. The raw data of sleep EEG were extracted and analyzed by engineers using two main factors: fractal dimension (FD) and the zero-crossing rate of detrended FD (zDFD). FD was an effective indicator reflecting the EEG complexity and zDFD was useful to reflect the variability of the EEG complexity. The FD and zDFD indexes of sleep EEG of 45 OSAS patients before and after CPAP titration were analyzed. The age of 45 OSAS patients was 52.7 ± 5.6 years old and the patients include 12 females and 33 males. After CPAP treatment, FD of EEG in non-rapid eye movement (NREM) sleep decreased significantly (P CPAP therapy (P CPAP therapy had a significant influence on sleep EEG in patients with OSAHS, which lead to a more stable EEG pattern. This may be one of the mechanisms that CPAP could improve sleep quality and brain function of OSAS patients.

  12. Association between uncoupling protein 2, adiponectin and resting energy expenditure in obese women with normal and low resting energy expenditure.

    Taghadomi Masoumi, Zahra; Eshraghian, Mohammad Reza; Hedayati, Mahdi; Pishva, Hamideh

    2018-02-01

    Obesity is recognized as the most prevalent metabolic disease worldwide. Decreases in energy expenditure may increase risk of obesity. One of the key regulators of energy balance is uncoupling protein2 (UCP2), a transporter protein presents in mitochondrial inner membrane. Moreover, adiponectin is the most abundant adipocytokine, it may play a role in energy metabolism and gene expression of UCP2. The aim of this study was to investigate potential associations between the level of uncoupling protein 2 and adiponectin and their relationship with REE (Resting Energy Expenditure) in obese women with normal and low resting energy expenditure. A total of 49 subjects (women, 25-50 years old), were included in current study, 16 subjects with BMI > 30 and low resting energy expenditure, 17 subjects with BMI > 30 and normal resting energy expenditure and 16 non-obese subjects as a control group. Anthropometric, body composition parameters and resting energy expenditure were measured. Plasma adiponectin, UCP2 protein and total protein in PBMC were determined. Measured resting energy expenditure in obese subjects with low REE was significantly lower than other groups. Plasma adiponectin in the obese subjects with low REE was significantly lower compared to normal weight group. There was a significant relationship between 'UCP2 protein/Total protein' ratio and plasma adiponectin in obese group with low REE and in three groups when we pooled. There was a significant association between REE and plasma adiponectin in three groups when we pooled. There was a significant association between plasma adiponectin and REE. Moreover, there was a significant relationship between UCP2 and REE.

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

    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.

  14. Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks.

    Smitha, K A; Akhil Raja, K; Arun, K M; Rajesh, P G; Thomas, Bejoy; Kapilamoorthy, T R; Kesavadas, Chandrasekharan

    2017-08-01

    The inquisitiveness about what happens in the brain has been there since the beginning of humankind. Functional magnetic resonance imaging is a prominent tool which helps in the non-invasive examination, localisation as well as lateralisation of brain functions such as language, memory, etc. In recent years, there is an apparent shift in the focus of neuroscience research to studies dealing with a brain at 'resting state'. Here the spotlight is on the intrinsic activity within the brain, in the absence of any sensory or cognitive stimulus. The analyses of functional brain connectivity in the state of rest have revealed different resting state networks, which depict specific functions and varied spatial topology. However, different statistical methods have been introduced to study resting state functional magnetic resonance imaging connectivity, yet producing consistent results. In this article, we introduce the concept of resting state functional magnetic resonance imaging in detail, then discuss three most widely used methods for analysis, describe a few of the resting state networks featuring the brain regions, associated cognitive functions and clinical applications of resting state functional magnetic resonance imaging. This review aims to highlight the utility and importance of studying resting state functional magnetic resonance imaging connectivity, underlining its complementary nature to the task-based functional magnetic resonance imaging.

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

    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

  16. Global Manufacturing Research: Experience Exchange Group (EEG) contributions

    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...

  17. Standardized computer-based organized reporting of EEG:SCORE

    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....

  18. EEG as an Indicator of Cerebral Functioning in Postanoxic Coma.

    Juan, Elsa; Kaplan, Peter W; Oddo, Mauro; Rossetti, Andrea O

    2015-12-01

    Postanoxic coma after cardiac arrest is one of the most serious acute cerebral conditions and a frequent cause of admission to critical care units. Given substantial improvement of outcome over the recent years, a reliable and timely assessment of clinical evolution and prognosis is essential in this context, but may be challenging. In addition to the classic neurologic examination, EEG is increasingly emerging as an important tool to assess cerebral functions noninvasively. Although targeted temperature management and related sedation may delay clinical assessment, EEG provides accurate prognostic information in the early phase of coma. Here, the most frequently encountered EEG patterns in postanoxic coma are summarized and their relations with outcome prediction are discussed. This article also addresses the influence of targeted temperature management on brain signals and the implication of the evolution of EEG patterns over time. Finally, the article ends with a view of the future prospects for EEG in postanoxic management and prognostication.

  19. EEG Suppression Associated with Apneic Episodes in a Neonate

    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.

  20. Frontal EEG asymmetry as a moderator and mediator of emotion.

    Coan, James A; Allen, John J B

    2004-10-01

    Frontal EEG asymmetry appears to serve as (1) an individual difference variable related to emotional responding and emotional disorders, and (2) a state-dependent concomitant of emotional responding. Such findings, highlighted in this review, suggest that frontal EEG asymmetry may serve as both a moderator and a mediator of emotion- and motivation-related constructs. Unequivocal evidence supporting frontal EEG asymmetry as a moderator and/or mediator of emotion is lacking, as insufficient attention has been given to analyzing the frontal EEG asymmetries in terms of moderators and mediators. The present report reviews the frontal EEG asymmetry literature from the framework of moderators and mediators, and overviews data analytic strategies that would support claims of moderation and mediation.

  1. Combined process automation for large-scale EEG analysis.

    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.

  2. Diagnostic Performance and Utility of Quantitative EEG Analyses in Delirium: Confirmatory Results From a Large Retrospective Case-Control Study.

    Fleischmann, Robert; Tränkner, Steffi; Bathe-Peters, Rouven; Rönnefarth, Maria; Schmidt, Sein; Schreiber, Stephan J; Brandt, Stephan A

    2018-03-01

    The lack of objective disease markers is a major cause of misdiagnosis and nonstandardized approaches in delirium. Recent studies conducted in well-selected patients and confined study environments suggest that quantitative electroencephalography (qEEG) can provide such markers. We hypothesize that qEEG helps remedy diagnostic uncertainty not only in well-defined study cohorts but also in a heterogeneous hospital population. In this retrospective case-control study, EEG power spectra of delirious patients and age-/gender-matched controls (n = 31 and n = 345, respectively) were fitted in a linear model to test their performance as binary classifiers. We subsequently evaluated the diagnostic performance of the best classifiers in control samples with normal EEGs (n = 534) and real-world samples including pathologic findings (n = 4294). Test reliability was estimated through split-half analyses. We found that the combination of spectral power at F3-P4 at 2 Hz (area under the curve [AUC] = .994) and C3-O1 at 19 Hz (AUC = .993) provided a sensitivity of 100% and a specificity of 99% to identify delirious patients among normal controls. These classifiers also yielded a false positive rate as low as 5% and increased the pretest probability of being delirious by 57% in an unselected real-world sample. Split-half reliabilities were .98 and .99, respectively. This retrospective study yielded preliminary evidence that qEEG provides excellent diagnostic performance to identify delirious patients even outside confined study environments. It furthermore revealed reduced beta power as a novel specific finding in delirium and that a normal EEG excludes delirium. Prospective studies including parameters of pretest probability and delirium severity are required to elaborate on these promising findings.

  3. Drug Treated Schizophrenia, Schizoaffective and Bipolar Disorder Patients Evaluated by qEEG Absolute Spectral Power and Mean Frequency Analysis.

    Wix-Ramos, Richard; Moreno, Xiomara; Capote, Eduardo; González, Gilbert; Uribe, Ezequiel; Eblen-Zajjur, Antonio

    2014-04-01

    Research of electroencephalograph (EEG) power spectrum and mean frequency has shown inconsistent results in patients with schizophrenic, schizoaffective and bipolar disorders during medication when compared to normal subjects thus; the characterization of these parameters is an important task. We applied quantitative EEG (qEEG) to investigate 38 control, 15 schizophrenic, 7 schizoaffective and 11 bipolar disorder subjects which remaine under the administration of psychotropic drugs (except control group). Absolute spectral power (ASP), mean frequency and hemispheric electrical asymmetry were measured by 19 derivation qEEG. Group mean values were compared with non parametrical Mann-Whitney test and spectral EEG maps with z-score method at p Schizoaffective patients received neuroleptic+benzodiazepine (71.4%) and for bipolar disorder patients neuroleptic+antiepileptic (81.8%). Schizophrenic (at all derivations except for Fp1, Fp2, F8 and T6) and schizoaffective (only at C3) show higher values of ASP (+57.7% and +86.1% respectively) compared to control group. ASP of bipolar disorder patients did not show differences against control group. The mean frequency was higher at Fp1 (+14.2%) and Fp2 (+17.4%) in bipolar disorder patients than control group, but no differences were found in frequencies between schizophrenic or schizoaffective patients against the control group. Majority of spectral differences were found at the left hemisphere in schizophrenic and schizoaffective but not in bipolar disorder subjects. The present report contributes to characterize quantitatively the qEEG in drug treated schizophrenic, schizoaffective or bipolar disorder patients.

  4. Automatic cardiac cycle determination directly from EEG-fMRI data by multi-scale peak detection method.

    Wong, Chung-Ki; Luo, Qingfei; Zotev, Vadim; Phillips, Raquel; Chan, Kam Wai Clifford; Bodurka, Jerzy

    2018-03-31

    In simultaneous EEG-fMRI, identification of the period of cardioballistic artifact (BCG) in EEG is required for the artifact removal. Recording the electrocardiogram (ECG) waveform during fMRI is difficult, often causing inaccurate period detection. Since the waveform of the BCG extracted by independent component analysis (ICA) is relatively invariable compared to the ECG waveform, we propose a multiple-scale peak-detection algorithm to determine the BCG cycle directly from the EEG data. The algorithm first extracts the high contrast BCG component from the EEG data by ICA. The BCG cycle is then estimated by band-pass filtering the component around the fundamental frequency identified from its energy spectral density, and the peak of BCG artifact occurrence is selected from each of the estimated cycle. The algorithm is shown to achieve a high accuracy on a large EEG-fMRI dataset. It is also adaptive to various heart rates without the needs of adjusting the threshold parameters. The cycle detection remains accurate with the scan duration reduced to half a minute. Additionally, the algorithm gives a figure of merit to evaluate the reliability of the detection accuracy. The algorithm is shown to give a higher detection accuracy than the commonly used cycle detection algorithm fmrib_qrsdetect implemented in EEGLAB. The achieved high cycle detection accuracy of our algorithm without using the ECG waveforms makes possible to create and automate pipelines for processing large EEG-fMRI datasets, and virtually eliminates the need for ECG recordings for BCG artifact removal. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

  5. Coherence of EEG frequency components during manual movements executed by the subdominant hand in women

    O. V. Korzhyk

    2017-02-01

    Full Text Available The academic community is paying more and more attention to the question of the individual characteristics of the brain processes which ensure the manual motor programming of movements performed not only by the leading, but also by the subdominant hand. Researchers do not exclude the existence of the particular parameters of the human brain correlating with manual motor activities. This study involved 136 women at the age of 19–21 years. The testees were divided into two groups according to high and low values of the EEG modal α-frequency determined individually and in a motionless state. We evaluated the coherence status of the EEG frequency components in the motionless state and during movements performed by fingers of the subdominant (left hand in response to rhythmic sound signals. The testing stages involved the sequential execution of motor tasks including clamping and unclamping performed by the fingers of the subdominant hand (such as grasping movements without effort. The testees also performed fingering (a manual response to each stimulus at in different times and not by all the fingers of the hand simultaneously, but separately, one by one, in a given sequence. Clamping and unclamping was executed by the fingers subject to power loading the (additional load on the fingers being 10H. Execution of manual movements by means of the subdominant hand in response to the sensory signals was accompanied by an increase in coherence in the EEG frequency components, especially in the frontal, temporal, and parietal cortexes of the central areas. Women with a low individual α-rate of such a regularity had significantly increased scores at the high (α3-, β- frequencies of the EEG spectrum. At the same time, women in both groups mainly showed a decrease in the coherence coefficients of θ-, α1- and α3-activity in the frontal cortex leads in terms of the execution of the sequential finger movements and movements under power loading. The

  6. Rest frame properties of the proton

    Strobel, G.L.

    1998-01-01

    The proton is modeled as three quarks of small current quark mass. The three-body Dirac equation is solved with spin-independent central diagonal linear confining potentials with an attractive Coulombic term in a relativistic three-quark model. Hyperspherical coordinates are used, and the bound state is found analytically. After integrating over the hyperangles, the Hamiltonian is an 8 by 8 matrix of coupled first-order differential equations in one variable, the hyperradius. These are analytically solved in hypercentral approximation. For the (1/2 + ) 3 ground-state configuration in the nonrelativistic large-quark-mass limit, there are no nodes in the wave function. However, in the extreme relativistic limit of small current quark masses of a few MeV, the expectation value of the number of nodes is about 1.30 when the potential parameters are chosen to reproduce the proton rms charge radius. The quarks are assumed to possess a Pauli anomalous magnetic moment, like that of the electron and muon of (α/2π)(e/m). Assuming all three quarks have equal mass, one can fit the rest energy, magnetic moment, rms charge radius, and axial charge of the proton with this relativistic three-body Dirac equation model. The solution found shows the necessity of including all components of the composite three-quark wave function, as the upper component contributes only 0.585 to the norm

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

    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.

  8. Complexity analysis of EEG in patients with schizophrenia using fractal dimension

    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

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

    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.

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

    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.