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

OpenAIRE

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

2011-01-01

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

Beamformer source analysis and connectivity on concurrent EEG and MEG data during voluntary movements.

Directory of Open Access Journals (Sweden)

Muthuraman Muthuraman

Full Text Available Electroencephalography (EEG and magnetoencephalography (MEG are the two modalities for measuring neuronal dynamics at a millisecond temporal resolution. Different source analysis methods, to locate the dipoles in the brain from which these dynamics originate, have been readily applied to both modalities alone. However, direct comparisons and possible advantages of combining both modalities have rarely been assessed during voluntary movements using coherent source analysis. In the present study, the cortical and sub-cortical network of coherent sources at the finger tapping task frequency (2-4 Hz and the modes of interaction within this network were analysed in 15 healthy subjects using a beamformer approach called the dynamic imaging of coherent sources (DICS with subsequent source signal reconstruction and renormalized partial directed coherence analysis (RPDC. MEG and EEG data were recorded simultaneously allowing the comparison of each of the modalities separately to that of the combined approach. We found the identified network of coherent sources for the finger tapping task as described in earlier studies when using only the MEG or combined MEG+EEG whereas the EEG data alone failed to detect single sub-cortical sources. The signal-to-noise ratio (SNR level of the coherent rhythmic activity at the tapping frequency in MEG and combined MEG+EEG data was significantly higher than EEG alone. The functional connectivity analysis revealed that the combined approach had more active connections compared to either of the modalities during the finger tapping (FT task. These results indicate that MEG is superior in the detection of deep coherent sources and that the SNR seems to be more vital than the sensitivity to theoretical dipole orientation and the volume conduction effect in the case of EEG.

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

Science.gov (United States)

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

2017-12-01

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

Algorithmic procedures for Bayesian MEG/EEG source reconstruction in SPM☆

Science.gov (United States)

López, J.D.; Litvak, V.; Espinosa, J.J.; Friston, K.; Barnes, G.R.

2014-01-01

The MEG/EEG inverse problem is ill-posed, giving different source reconstructions depending on the initial assumption sets. Parametric Empirical Bayes allows one to implement most popular MEG/EEG inversion schemes (Minimum Norm, LORETA, etc.) within the same generic Bayesian framework. It also provides a cost-function in terms of the variational Free energy—an approximation to the marginal likelihood or evidence of the solution. In this manuscript, we revisit the algorithm for MEG/EEG source reconstruction with a view to providing a didactic and practical guide. The aim is to promote and help standardise the development and consolidation of other schemes within the same framework. We describe the implementation in the Statistical Parametric Mapping (SPM) software package, carefully explaining each of its stages with the help of a simple simulated data example. We focus on the Multiple Sparse Priors (MSP) model, which we compare with the well-known Minimum Norm and LORETA models, using the negative variational Free energy for model comparison. The manuscript is accompanied by Matlab scripts to allow the reader to test and explore the underlying algorithm. PMID:24041874

Using EEG/MEG Data of Cognitive Processes in Brain-Computer Interfaces

International Nuclear Information System (INIS)

Gutierrez, David

2008-01-01

Brain-computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using electroencephalographic (EEG) and, more recently, magnetoencephalographic (MEG) measurements of the brain function. Most of the current implementations of BCIs rely on EEG/MEG data of motor activities as such neural processes are well characterized, while the use of data related to cognitive activities has been neglected due to its intrinsic complexity. However, cognitive data usually has larger amplitude, lasts longer and, in some cases, cognitive brain signals are easier to control at will than motor signals. This paper briefy reviews the use of EEG/MEG data of cognitive processes in the implementation of BCIs. Specifically, this paper reviews some of the neuromechanisms, signal features, and processing methods involved. This paper also refers to some of the author's work in the area of detection and classifcation of cognitive signals for BCIs using variability enhancement, parametric modeling, and spatial fltering, as well as recent developments in BCI performance evaluation

Algorithmic procedures for Bayesian MEG/EEG source reconstruction in SPM.

Science.gov (United States)

López, J D; Litvak, V; Espinosa, J J; Friston, K; Barnes, G R

2014-01-01

The MEG/EEG inverse problem is ill-posed, giving different source reconstructions depending on the initial assumption sets. Parametric Empirical Bayes allows one to implement most popular MEG/EEG inversion schemes (Minimum Norm, LORETA, etc.) within the same generic Bayesian framework. It also provides a cost-function in terms of the variational Free energy-an approximation to the marginal likelihood or evidence of the solution. In this manuscript, we revisit the algorithm for MEG/EEG source reconstruction with a view to providing a didactic and practical guide. The aim is to promote and help standardise the development and consolidation of other schemes within the same framework. We describe the implementation in the Statistical Parametric Mapping (SPM) software package, carefully explaining each of its stages with the help of a simple simulated data example. We focus on the Multiple Sparse Priors (MSP) model, which we compare with the well-known Minimum Norm and LORETA models, using the negative variational Free energy for model comparison. The manuscript is accompanied by Matlab scripts to allow the reader to test and explore the underlying algorithm. © 2013. Published by Elsevier Inc. All rights reserved.

Ring and peg electrodes for minimally-Invasive and long-term sub-scalp EEG recordings.

Science.gov (United States)

Benovitski, Y B; Lai, A; McGowan, C C; Burns, O; Maxim, V; Nayagam, D A X; Millard, R; Rathbone, G D; le Chevoir, M A; Williams, R A; Grayden, D B; May, C N; Murphy, M; D'Souza, W J; Cook, M J; Williams, C E

2017-09-01

Minimally-invasive approaches are needed for long-term reliable Electroencephalography (EEG) recordings to assist with epilepsy diagnosis, investigation and more naturalistic monitoring. This study compared three methods for long-term implantation of sub-scalp EEG electrodes. Three types of electrodes (disk, ring, and peg) were fabricated from biocompatible materials and implanted under the scalp in five ambulatory ewes for 3months. Disk electrodes were inserted into sub-pericranial pockets. Ring electrodes were tunneled under the scalp. Peg electrodes were inserted into the skull, close to the dura. EEG was continuously monitored wirelessly. High resolution CT imaging, histopathology, and impedance measurements were used to assess the status of the electrodes at the end of the study. EEG amplitude was larger in the peg compared with the disk and ring electrodes (pEEG, mechanical stability, and lower chewing artifact. Whereas, ring electrode arrays tunneled under the scalp enable minimal surgical techniques to be used for implantation and removal. Copyright © 2017 Elsevier B.V. All rights reserved.

Safety of Simultaneous Scalp or Intracranial EEG during MRI: A Review

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Hassan B. Hawsawi

2017-10-01

Full Text Available Understanding the brain and its activity is one of the great challenges of modern science. Normal brain activity (cognitive processes, etc. has been extensively studied using electroencephalography (EEG since the 1930's, in the form of spontaneous fluctuations in rhythms, and patterns, and in a more experimentally-driven approach in the form of event-related potentials (ERPs allowing us to relate scalp voltage waveforms to brain states and behavior. The use of EEG recorded during functional magnetic resonance imaging (EEG-fMRI is a more recent development that has become an important tool in clinical neuroscience, for example for the study of epileptic activity. The purpose of this review is to explore the magnetic resonance imaging safety aspects specifically associated with the use of scalp EEG and other brain-implanted electrodes such as intracranial EEG electrodes when they are subjected to the MRI environment. We provide a theoretical overview of the mechanisms at play specifically associated with the presence of EEG equipment connected to the subject in the MR environment, and of the resulting health hazards. This is followed by a survey of the literature on the safety of scalp or invasive EEG-fMRI data acquisitions across field strengths, with emphasis on the practical implications for the safe application of the techniques; in particular, we attempt to summarize the findings in terms of acquisition protocols when possible.

Sparse EEG/MEG source estimation via a group lasso.

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Michael Lim

Full Text Available Non-invasive recordings of human brain activity through electroencephalography (EEG or magnetoencelphalography (MEG are of value for both basic science and clinical applications in sensory, cognitive, and affective neuroscience. Here we introduce a new approach to estimating the intra-cranial sources of EEG/MEG activity measured from extra-cranial sensors. The approach is based on the group lasso, a sparse-prior inverse that has been adapted to take advantage of functionally-defined regions of interest for the definition of physiologically meaningful groups within a functionally-based common space. Detailed simulations using realistic source-geometries and data from a human Visual Evoked Potential experiment demonstrate that the group-lasso method has improved performance over traditional ℓ2 minimum-norm methods. In addition, we show that pooling source estimates across subjects over functionally defined regions of interest results in improvements in the accuracy of source estimates for both the group-lasso and minimum-norm approaches.

Anatomically constrained dipole adjustment (ANACONDA) for accurate MEG/EEG focal source localizations

Science.gov (United States)

Im, Chang-Hwan; Jung, Hyun-Kyo; Fujimaki, Norio

2005-10-01

This paper proposes an alternative approach to enhance localization accuracy of MEG and EEG focal sources. The proposed approach assumes anatomically constrained spatio-temporal dipoles, initial positions of which are estimated from local peak positions of distributed sources obtained from a pre-execution of distributed source reconstruction. The positions of the dipoles are then adjusted on the cortical surface using a novel updating scheme named cortical surface scanning. The proposed approach has many advantages over the conventional ones: (1) as the cortical surface scanning algorithm uses spatio-temporal dipoles, it is robust with respect to noise; (2) it requires no a priori information on the numbers and initial locations of the activations; (3) as the locations of dipoles are restricted only on a tessellated cortical surface, it is physiologically more plausible than the conventional ECD model. To verify the proposed approach, it was applied to several realistic MEG/EEG simulations and practical experiments. From the several case studies, it is concluded that the anatomically constrained dipole adjustment (ANACONDA) approach will be a very promising technique to enhance accuracy of focal source localization which is essential in many clinical and neurological applications of MEG and EEG.

Anatomically constrained dipole adjustment (ANACONDA) for accurate MEG/EEG focal source localizations

International Nuclear Information System (INIS)

Im, Chang-Hwan; Jung, Hyun-Kyo; Fujimaki, Norio

2005-01-01

This paper proposes an alternative approach to enhance localization accuracy of MEG and EEG focal sources. The proposed approach assumes anatomically constrained spatio-temporal dipoles, initial positions of which are estimated from local peak positions of distributed sources obtained from a pre-execution of distributed source reconstruction. The positions of the dipoles are then adjusted on the cortical surface using a novel updating scheme named cortical surface scanning. The proposed approach has many advantages over the conventional ones: (1) as the cortical surface scanning algorithm uses spatio-temporal dipoles, it is robust with respect to noise; (2) it requires no a priori information on the numbers and initial locations of the activations; (3) as the locations of dipoles are restricted only on a tessellated cortical surface, it is physiologically more plausible than the conventional ECD model. To verify the proposed approach, it was applied to several realistic MEG/EEG simulations and practical experiments. From the several case studies, it is concluded that the anatomically constrained dipole adjustment (ANACONDA) approach will be a very promising technique to enhance accuracy of focal source localization which is essential in many clinical and neurological applications of MEG and EEG

A three domain covariance framework for EEG/MEG data

NARCIS (Netherlands)

Ros, B.P.; Bijma, F.; de Gunst, M.C.M.; de Munck, J.C.

2015-01-01

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

On the use of EEG or MEG brain imaging tools in neuromarketing research.

Science.gov (United States)

Vecchiato, Giovanni; Astolfi, Laura; De Vico Fallani, Fabrizio; Toppi, Jlenia; Aloise, Fabio; Bez, Francesco; Wei, Daming; Kong, Wanzeng; Dai, Jounging; Cincotti, Febo; Mattia, Donatella; Babiloni, Fabio

2011-01-01

Here we present an overview of some published papers of interest for the marketing research employing electroencephalogram (EEG) and magnetoencephalogram (MEG) methods. The interest for these methodologies relies in their high-temporal resolution as opposed to the investigation of such problem with the functional Magnetic Resonance Imaging (fMRI) methodology, also largely used in the marketing research. In addition, EEG and MEG technologies have greatly improved their spatial resolution in the last decades with the introduction of advanced signal processing methodologies. By presenting data gathered through MEG and high resolution EEG we will show which kind of information it is possible to gather with these methodologies while the persons are watching marketing relevant stimuli. Such information will be related to the memorization and pleasantness related to such stimuli. We noted that temporal and frequency patterns of brain signals are able to provide possible descriptors conveying information about the cognitive and emotional processes in subjects observing commercial advertisements. These information could be unobtainable through common tools used in standard marketing research. We also show an example of how an EEG methodology could be used to analyze cultural differences between fruition of video commercials of carbonated beverages in Western and Eastern countries.

On the Use of EEG or MEG Brain Imaging Tools in Neuromarketing Research

Directory of Open Access Journals (Sweden)

Giovanni Vecchiato

2011-01-01

Full Text Available Here we present an overview of some published papers of interest for the marketing research employing electroencephalogram (EEG and magnetoencephalogram (MEG methods. The interest for these methodologies relies in their high-temporal resolution as opposed to the investigation of such problem with the functional Magnetic Resonance Imaging (fMRI methodology, also largely used in the marketing research. In addition, EEG and MEG technologies have greatly improved their spatial resolution in the last decades with the introduction of advanced signal processing methodologies. By presenting data gathered through MEG and high resolution EEG we will show which kind of information it is possible to gather with these methodologies while the persons are watching marketing relevant stimuli. Such information will be related to the memorization and pleasantness related to such stimuli. We noted that temporal and frequency patterns of brain signals are able to provide possible descriptors conveying information about the cognitive and emotional processes in subjects observing commercial advertisements. These information could be unobtainable through common tools used in standard marketing research. We also show an example of how an EEG methodology could be used to analyze cultural differences between fruition of video commercials of carbonated beverages in Western and Eastern countries.

Multivariate matching pursuit in optimal Gabor dictionaries: theory and software with interface for EEG/MEG via Svarog

Science.gov (United States)

2013-01-01

Background Matching pursuit algorithm (MP), especially with recent multivariate extensions, offers unique advantages in analysis of EEG and MEG. Methods We propose a novel construction of an optimal Gabor dictionary, based upon the metrics introduced in this paper. We implement this construction in a freely available software for MP decomposition of multivariate time series, with a user friendly interface via the Svarog package (Signal Viewer, Analyzer and Recorder On GPL, http://braintech.pl/svarog), and provide a hands-on introduction to its application to EEG. Finally, we describe numerical and mathematical optimizations used in this implementation. Results Optimal Gabor dictionaries, based on the metric introduced in this paper, for the first time allowed for a priori assessment of maximum one-step error of the MP algorithm. Variants of multivariate MP, implemented in the accompanying software, are organized according to the mathematical properties of the algorithms, relevant in the light of EEG/MEG analysis. Some of these variants have been successfully applied to both multichannel and multitrial EEG and MEG in previous studies, improving preprocessing for EEG/MEG inverse solutions and parameterization of evoked potentials in single trials; we mention also ongoing work and possible novel applications. Conclusions Mathematical results presented in this paper improve our understanding of the basics of the MP algorithm. Simple introduction of its properties and advantages, together with the accompanying stable and user-friendly Open Source software package, pave the way for a widespread and reproducible analysis of multivariate EEG and MEG time series and novel applications, while retaining a high degree of compatibility with the traditional, visual analysis of EEG. PMID:24059247

Truncated RAP-MUSIC (TRAP-MUSIC) for MEG and EEG source localization.

Science.gov (United States)

Mäkelä, Niko; Stenroos, Matti; Sarvas, Jukka; Ilmoniemi, Risto J

2018-02-15

Electrically active brain regions can be located applying MUltiple SIgnal Classification (MUSIC) on magneto- or electroencephalographic (MEG; EEG) data. We introduce a new MUSIC method, called truncated recursively-applied-and-projected MUSIC (TRAP-MUSIC). It corrects a hidden deficiency of the conventional RAP-MUSIC algorithm, which prevents estimation of the true number of brain-signal sources accurately. The correction is done by applying a sequential dimension reduction to the signal-subspace projection. We show that TRAP-MUSIC significantly improves the performance of MUSIC-type localization; in particular, it successfully and robustly locates active brain regions and estimates their number. We compare TRAP-MUSIC and RAP-MUSIC in simulations with varying key parameters, e.g., signal-to-noise ratio, correlation between source time-courses, and initial estimate for the dimension of the signal space. In addition, we validate TRAP-MUSIC with measured MEG data. We suggest that with the proposed TRAP-MUSIC method, MUSIC-type localization could become more reliable and suitable for various online and offline MEG and EEG applications. Copyright © 2017 Elsevier Inc. All rights reserved.

EEG/MEG Source Reconstruction with Spatial-Temporal Two-Way Regularized Regression

KAUST Repository

Tian, Tian Siva; Huang, Jianhua Z.; Shen, Haipeng; Li, Zhimin

2013-01-01

In this work, we propose a spatial-temporal two-way regularized regression method for reconstructing neural source signals from EEG/MEG time course measurements. The proposed method estimates the dipole locations and amplitudes simultaneously

Guiding transcranial brain stimulation by EEG/MEG to interact with ongoing brain activity and associated functions

DEFF Research Database (Denmark)

Thut, Gregor; Bergmann, Til Ole; Fröhlich, Flavio

2017-01-01

of NTBS with respect to the ongoing brain activity. Temporal patterns of ongoing neuronal activity, in particular brain oscillations and their fluctuations, can be traced with electro- or magnetoencephalography (EEG/MEG), to guide the timing as well as the stimulation settings of NTBS. These novel, online...... and offline EEG/MEG-guided NTBS-approaches are tailored to specifically interact with the underlying brain activity. Online EEG/MEG has been used to guide the timing of NTBS (i.e., when to stimulate): by taking into account instantaneous phase or power of oscillatory brain activity, NTBS can be aligned......Non-invasive transcranial brain stimulation (NTBS) techniques have a wide range of applications but also suffer from a number of limitations mainly related to poor specificity of intervention and variable effect size. These limitations motivated recent efforts to focus on the temporal dimension...

SCOPE-mTL: A non-invasive tool for identifying and lateralizing mesial temporal lobe seizures prior to scalp EEG ictal onset.

Science.gov (United States)

Lam, Alice D; Maus, Douglas; Zafar, Sahar F; Cole, Andrew J; Cash, Sydney S

2017-09-01

In mesial temporal lobe (mTL) epilepsy, seizure onset can precede the appearance of a scalp EEG ictal pattern by many seconds. The ability to identify this early, occult mTL seizure activity could improve lateralization and localization of mTL seizures on scalp EEG. Using scalp EEG spectral features and machine learning approaches on a dataset of combined scalp EEG and foramen ovale electrode recordings in patients with mTL epilepsy, we developed an algorithm, SCOPE-mTL, to detect and lateralize early, occult mTL seizure activity, prior to the appearance of a scalp EEG ictal pattern. Using SCOPE-mTL, 73% of seizures with occult mTL onset were identified as such, and no seizures that lacked an occult mTL onset were identified as having one. Predicted mTL seizure onset times were highly correlated with actual mTL seizure onset times (r=0.69). 50% of seizures with early mTL onset were lateralizable prior to scalp ictal onset, with 94% accuracy. SCOPE-mTL can identify and lateralize mTL seizures prior to scalp EEG ictal onset, with high sensitivity, specificity, and accuracy. Quantitative analysis of scalp EEG can provide important information about mTL seizures, even in the absence of a visible scalp EEG ictal correlate. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Variance stabilization for computing and comparing grand mean waveforms in MEG and EEG.

Science.gov (United States)

Matysiak, Artur; Kordecki, Wojciech; Sielużycki, Cezary; Zacharias, Norman; Heil, Peter; König, Reinhard

2013-07-01

Grand means of time-varying signals (waveforms) across subjects in magnetoencephalography (MEG) and electroencephalography (EEG) are commonly computed as arithmetic averages and compared between conditions, for example, by subtraction. However, the prerequisite for these operations, homogeneity of the variance of the waveforms in time, and for most common parametric statistical tests also between conditions, is rarely met. We suggest that the heteroscedasticity observed instead results because waveforms may differ by factors and additive terms and follow a mixed model. We propose to apply the asinh-transformation to stabilize the variance in such cases. We demonstrate the homogeneous variance and the normal distributions of data achieved by this transformation using simulated waveforms, and we apply it to real MEG data and show its benefits. The asinh-transformation is thus an essential and useful processing step prior to computing and comparing grand mean waveforms in MEG and EEG. Copyright © 2013 Society for Psychophysiological Research.

Negligible motion artifacts in scalp electroencephalography (EEG during treadmill walking

Directory of Open Access Journals (Sweden)

Kevin eNathan

2016-01-01

Full Text Available Recent Mobile Brain/Body Imaging (MoBI techniques based on active electrode scalp electroencephalogram (EEG allow the acquisition and real-time analysis of brain dynamics during active unrestrained motor behavior involving whole body movements such as treadmill walking, over-ground walking and other locomotive and non-locomotive tasks. Unfortunately, MoBI protocols are prone to physiological and non-physiological artifacts, including motion artifacts that may contaminate the EEG recordings. A few attempts have been made to quantify these artifacts during locomotion tasks but with inconclusive results due in part to methodological pitfalls. In this paper, we investigate the potential contributions of motion artifacts in scalp EEG during treadmill walking at three different speeds (1.5, 3.0, and 4.5 km/h using a wireless 64 channel active EEG system and a wireless inertial sensor attached to the subject’s head. The experimental setup was designed according to good measurement practices using state-of-the-art commercially-available instruments, and the measurements were analyzed using Fourier analysis and wavelet coherence approaches. Contrary to prior claims, the subjects’ motion did not significantly affect their EEG during treadmill walking although precaution should be taken when gait speeds approach 4.5 km/h. Overall, these findings suggest how MoBI methods may be safely deployed in neural, cognitive, and rehabilitation engineering applications.

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

Science.gov (United States)

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.

Effect of Skull Resistivity on the Relative Sensitivity Distributions of EEG and MEG Measurements

National Research Council Canada - National Science Library

Malmivuo, J

2001-01-01

The authors have previously published calculations that show that, despite the high resistivity of the skull, the spatial sensitivity of magnetoencephalography, MEG, is no better than that of electroencephalography, EEG...

Combined MEG-EEG source localisation in patients with sub-acute sclerosing pan-encephalitis.

Science.gov (United States)

Velmurugan, J; Sinha, Sanjib; Nagappa, Madhu; Mariyappa, N; Bindu, P S; Ravi, G S; Hazra, Nandita; Thennarasu, K; Ravi, V; Taly, A B; Satishchandra, P

2016-08-01

To study the genesis and propagation patterns of periodic complexes (PCs) associated with myoclonic jerks in sub-acute sclerosing pan-encephalitis (SSPE) using magnetoencephalography (MEG) and electroencephalography (EEG). Simultaneous recording of MEG (306 channels) and EEG (64 channels) in five patients of SSPE (M:F = 3:2; age 10.8 ± 3.2 years; symptom-duration 6.2 ± 10 months) was carried out using Elekta Neuromag(®) TRIUX™ system. Qualitative analysis of 80-160 PCs per patient was performed. Ten isomorphic classical PCs with significant field topography per patient were analysed at the 'onset' and at 'earliest significant peak' of the burst using discrete and distributed source imaging methods. MEG background was asymmetrical in 2 and slow in 3 patients. Complexes were periodic (3) or quasi-periodic (2), occurring every 4-16 s and varied in morphology among patients. Mean source localization at onset of bursts using discrete and distributed source imaging in magnetic source imaging (MSI) was in thalami and or insula (50 and 50 %, respectively) and in electric source imaging (ESI) was also in thalami and or insula (38 and 46 %, respectively). Mean source localization at the earliest rising phase of peak in MSI was in peri-central gyrus (49 and 42 %) and in ESI it was in frontal cortex (52 and 56 %). Further analysis revealed that PCs were generated in thalami and or insula and thereafter propagated to anterolateral surface of the cortices (viz. sensori-motor cortex and frontal cortex) to same side as that of the onset. This novel MEG-EEG based case series of PCs provides newer insights for understanding the plausible generators of myoclonus in SSPE and patterns of their propagation.

Methods for artifact detection and removal from scalp EEG: A review.

Science.gov (United States)

Islam, Md Kafiul; Rastegarnia, Amir; Yang, Zhi

2016-11-01

Electroencephalography (EEG) is the most popular brain activity recording technique used in wide range of applications. One of the commonly faced problems in EEG recordings is the presence of artifacts that come from sources other than brain and contaminate the acquired signals significantly. Therefore, much research over the past 15 years has focused on identifying ways for handling such artifacts in the preprocessing stage. However, this is still an active area of research as no single existing artifact detection/removal method is complete or universal. This article presents an extensive review of the existing state-of-the-art artifact detection and removal methods from scalp EEG for all potential EEG-based applications and analyses the pros and cons of each method. First, a general overview of the different artifact types that are found in scalp EEG and their effect on particular applications are presented. In addition, the methods are compared based on their ability to remove certain types of artifacts and their suitability in relevant applications (only functional comparison is provided not performance evaluation of methods). Finally, the future direction and expected challenges of current research is discussed. Therefore, this review is expected to be helpful for interested researchers who will develop and/or apply artifact handling algorithm/technique in future for their applications as well as for those willing to improve the existing algorithms or propose a new solution in this particular area of research. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Algorithm to find high density EEG scalp coordinates and analysis of their correspondence to structural and functional regions of the brain.

Science.gov (United States)

Giacometti, Paolo; Perdue, Katherine L; Diamond, Solomon G

2014-05-30

Interpretation and analysis of electroencephalography (EEG) measurements relies on the correspondence of electrode scalp coordinates to structural and functional regions of the brain. An algorithm is introduced for automatic calculation of the International 10-20, 10-10, and 10-5 scalp coordinates of EEG electrodes on a boundary element mesh of a human head. The EEG electrode positions are then used to generate parcellation regions of the cerebral cortex based on proximity to the EEG electrodes. The scalp electrode calculation method presented in this study effectively and efficiently identifies EEG locations without prior digitization of coordinates. The average of electrode proximity parcellations of the cortex were tabulated with respect to structural and functional regions of the brain in a population of 20 adult subjects. Parcellations based on electrode proximity and EEG sensitivity were compared. The parcellation regions based on sensitivity and proximity were found to have 44.0 ± 11.3% agreement when demarcated by the International 10-20, 32.4 ± 12.6% by the 10-10, and 24.7 ± 16.3% by the 10-5 electrode positioning system. The EEG positioning algorithm is a fast and easy method of locating EEG scalp coordinates without the need for digitized electrode positions. The parcellation method presented summarizes the EEG scalp locations with respect to brain regions without computation of a full EEG forward model solution. The reference table of electrode proximity versus cortical regions may be used by experimenters to select electrodes that correspond to anatomical and functional regions of interest. Copyright © 2014 Elsevier B.V. All rights reserved.

Physiological Ripples (± 100 Hz) in Spike-Free Scalp EEGs of Children With and Without Epilepsy.

Science.gov (United States)

Mooij, Anne H; Raijmann, Renee C M A; Jansen, Floor E; Braun, Kees P J; Zijlmans, Maeike

2017-11-01

Pathological high frequency oscillations (HFOs, >80 Hz) are considered new biomarkers for epilepsy. They have mostly been recorded invasively, but pathological ripples (80-250 Hz) can also be found in scalp EEGs with frequent epileptiform spikes. Physiological HFOs also exist. They have been recorded invasively in hippocampus and neocortex. There are no reports of spontaneously occurring physiological HFOs recorded with scalp EEG. We aimed to study ripples in spike-free scalp EEGs. We included 23 children (6 with, 17 without epilepsy) who had an EEG without interictal epileptiform spikes recorded during sleep. We differentiated true ripples from spurious ripples such as filtering effects of sharp artifacts and high frequency components of muscle artifacts by viewing ripples simultaneously in bipolar and average montage and double-checking the unfiltered signal. We calculated mean frequency, duration and root mean square amplitude of the ripples, and studied their shape and distribution. We found ripples in EEGs of 20 out of 23 children (4 with, 16 without epilepsy). Ripples had a regular shape and occurred mostly on central and midline channels. Mean frequency was 102 Hz, mean duration 70 ms, mean root mean square amplitude 0.95 µV. Ripples occurring in normal EEGs of children without epilepsy were considered physiological; the similarity in appearance suggested that the ripples occurring in normal EEGs of children with epilepsy were also physiological. The finding that it is possible to study physiological neocortical ripples in scalp EEG paves the way for investigating their occurrence during brain development and their relation with cognitive functioning.

Probing interval timing with scalp-recorded electroencephalography (EEG).

Science.gov (United States)

Ng, Kwun Kei; Penney, Trevor B

2014-01-01

Humans, and other animals, are able to easily learn the durations of events and the temporal relationships among them in spite of the absence of a dedicated sensory organ for time. This chapter summarizes the investigation of timing and time perception using scalp-recorded electroencephalography (EEG), a non-invasive technique that measures brain electrical potentials on a millisecond time scale. Over the past several decades, much has been learned about interval timing through the examination of the characteristic features of averaged EEG signals (i.e., event-related potentials, ERPs) elicited in timing paradigms. For example, the mismatch negativity (MMN) and omission potential (OP) have been used to study implicit and explicit timing, respectively, the P300 has been used to investigate temporal memory updating, and the contingent negative variation (CNV) has been used as an index of temporal decision making. In sum, EEG measures provide biomarkers of temporal processing that allow researchers to probe the cognitive and neural substrates underlying time perception.

Raviart–Thomas-type sources adapted to applied EEG and MEG: implementation and results

International Nuclear Information System (INIS)

Pursiainen, S

2012-01-01

This paper studies numerically electroencephalography and magnetoencephalography (EEG and MEG), two non-invasive imaging modalities in which external measurements of the electric potential and the magnetic field are, respectively, utilized to reconstruct the primary current density (neuronal activity) of the human brain. The focus is on adapting a Raviart–Thomas-type source model to meet the needs of EEG and MEG applications. The goal is to construct a model that provides an accurate approximation of dipole source currents and can be flexibly applied to different reconstruction strategies as well as to realistic computation geometries. The finite element method is applied in the simulation of the data. Least-squares fit interpolation is used to establish Cartesian source directions, which guarantee that the recovered current field is minimally dependent on the underlying finite element mesh. Implementation is explained in detail and made accessible, e.g., by using quadrature-free formulae and the Gaussian one-point rule in numerical integration. Numerical results are presented concerning, for example, the iterative alternating sequential inverse algorithm as well as resolution, smoothness and local refinement of the finite element mesh. Both spherical and pseudo-realistic head models, as well as real MEG data, are utilized in the numerical experiments. (paper)

Concordance and discordance between PET images and foci of scalp EEG

International Nuclear Information System (INIS)

Iinuma, Kazuie; Haginoya, Kazuhiro; Yanai, Kazuhiko; Hatazawa, Jun; Ito, Masatoshi.

1989-01-01

Epileptic foci were determined by scalp EEG and positron emission tomography (PET) with fluorine 18 in 22 children with partial epilepsy (PE, n=13) and Lennoxy-Gastaut syndrome (LGS, n=9). The patients ranged in age from 6 to 18 years. The pattern of hypometabolism was classified into the following 4 categories: non-focal, localized, hemispheric, and diffuse. In the group of PE patients, 11 showed a relative agreement between the EEG foci and region of a low cerebral metabolic rate for glucose (CMRglc) determined by PET. A decreased CMRglc was matched with the EEG foci in 4 patients with LGS. A tendency of a higher relationship between the EEG foci and PET images was significant in PE than LGS. (N.K.)

A Parametric Empirical Bayesian framework for the EEG/MEG inverse problem: generative models for multisubject and multimodal integration

Directory of Open Access Journals (Sweden)

Richard N Henson

2011-08-01

Full Text Available We review recent methodological developments within a Parametric Empirical Bayesian (PEB framework for reconstructing intracranial sources of extracranial electroencephalographic (EEG and magnetoencephalographic (MEG data under linear Gaussian assumptions. The PEB framework offers a natural way to integrate multiple constraints (spatial priors on this inverse problem, such as those derived from different modalities (e.g., from functional magnetic resonance imaging, fMRI or from multiple replications (e.g., subjects. Using variations of the same basic generative model, we illustrate the application of PEB to three cases: 1 symmetric integration (fusion of MEG and EEG; 2 asymmetric integration of MEG or EEG with fMRI, and 3 group-optimisation of spatial priors across subjects. We evaluate these applications on multimodal data acquired from 18 subjects, focusing on energy induced by face perception within a time-frequency window of 100-220ms, 8-18Hz. We show the benefits of multi-modal, multi-subject integration in terms of the model evidence and the reproducibility (over subjects of cortical responses to faces.

Neural network classifications and correlation analysis of EEG and MEG activity accompanying spontaneous reversals of the Necker cube.

Science.gov (United States)

Gaetz, M; Weinberg, H; Rzempoluck, E; Jantzen, K J

1998-04-01

It has recently been suggested that reentrant connections are essential in systems that process complex information [A. Damasio, H. Damasio, Cortical systems for the retrieval of concrete knowledge: the convergence zone framework, in: C. Koch, J.L. Davis (Eds.), Large Scale Neuronal Theories of the Brain, The MIT Press, Cambridge, 1995, pp. 61-74; G. Edelman, The Remembered Present, Basic Books, New York, 1989; M.I. Posner, M. Rothbart, Constructing neuronal theories of mind, in: C. Koch, J.L. Davis (Eds.), Large Scale Neuronal Theories of the Brain, The MIT Press, Cambridge, 1995, pp. 183-199; C. von der Malsburg, W. Schneider, A neuronal cocktail party processor, Biol. Cybem., 54 (1986) 29-40]. Reentry is not feedback, but parallel signalling in the time domain between spatially distributed maps, similar to a process of correlation between distributed systems. Accordingly, it was expected that during spontaneous reversals of the Necker cube, complex patterns of correlations between distributed systems would be present in the cortex. The present study included EEG (n=4) and MEG recordings (n=5). Two experimental questions were posed: (1) Can distributed cortical patterns present during perceptual reversals be classified differently using a generalised regression neural network (GRNN) compared to processing of a two-dimensional figure? (2) Does correlated cortical activity increase significantly during perception of a Necker cube reversal? One-second duration single trials of EEG and MEG data were analysed using the GRNN. Electrode/sensor pairings based on cortico-cortical connections were selected to assess correlated activity in each condition. The GRNN significantly classified single trials recorded during Necker cube reversals as different from single trials recorded during perception of a two-dimensional figure for both EEG and MEG. In addition, correlated cortical activity increased significantly in the Necker cube reversal condition for EEG and MEG compared

The adjoint method for general EEG and MEG sensor-based lead field equations

International Nuclear Information System (INIS)

Vallaghe, Sylvain; Papadopoulo, Theodore; Clerc, Maureen

2009-01-01

Most of the methods for the inverse source problem in electroencephalography (EEG) and magnetoencephalography (MEG) use a lead field as an input. The lead field is the function which relates any source in the brain to its measurements at the sensors. For complex geometries, there is no analytical formula of the lead field. The common approach is to numerically compute the value of the lead field for a finite number of point sources (dipoles). There are several drawbacks: the model of the source space is fixed (a set of dipoles), and the computation can be expensive for as much as 10 000 dipoles. The common idea to bypass these problems is to compute the lead field from a sensor point of view. In this paper, we use the adjoint method to derive general EEG and MEG sensor-based lead field equations. Within a simple framework, we provide a complete review of the explicit lead field equations, and we are able to extend these equations to non-pointlike sensors.

FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data

NARCIS (Netherlands)

Oostenveld, R.; Fries, P.; Maris, E.G.G.; Schoffelen, J.M.

2011-01-01

This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow

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

Science.gov (United States)

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

2018-04-01

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

TopoToolbox: using sensor topography to calculate psychologically meaningful measures from event-related EEG/MEG.

Science.gov (United States)

Tian, Xing; Poeppel, David; Huber, David E

2011-01-01

The open-source toolbox "TopoToolbox" is a suite of functions that use sensor topography to calculate psychologically meaningful measures (similarity, magnitude, and timing) from multisensor event-related EEG and MEG data. Using a GUI and data visualization, TopoToolbox can be used to calculate and test the topographic similarity between different conditions (Tian and Huber, 2008). This topographic similarity indicates whether different conditions involve a different distribution of underlying neural sources. Furthermore, this similarity calculation can be applied at different time points to discover when a response pattern emerges (Tian and Poeppel, 2010). Because the topographic patterns are obtained separately for each individual, these patterns are used to produce reliable measures of response magnitude that can be compared across individuals using conventional statistics (Davelaar et al. Submitted and Huber et al., 2008). TopoToolbox can be freely downloaded. It runs under MATLAB (The MathWorks, Inc.) and supports user-defined data structure as well as standard EEG/MEG data import using EEGLAB (Delorme and Makeig, 2004).

Millivolt-scale DC shifts in the human scalp EEG: evidence for a nonneuronal generator.

Science.gov (United States)

Voipio, Juha; Tallgren, Pekka; Heinonen, Erkki; Vanhatalo, Sampsa; Kaila, Kai

2003-04-01

Slow shifts in the human scalp-recorded EEG, including those related to changes in brain CO(2) levels, have been generally assumed to result from changes in the level of tonic excitation of apical dendrites of cortical pyramidal neurons. We readdressed this issue using DC-EEG shifts elicited in healthy adult subjects by hypo- or hypercapnia. A 3-min period of hyperventilation resulted in a prompt negative shift with a rate of up to 10 microV/s at the vertex (Cz) and an extremely steep dependence (up to 100 microV/mmHg) on the end-tidal Pco(2). This shift had a maximum of up to -2 mV at Cz versus the temporal derivations (T3/T4). Hyperventilation-like breathing of 5% CO(2)-95% O(2), which does not lead to a significant hypocapnia, resulted in a near-complete block of the negative DC shift at Cz. Hypoventilation, or breathing 5% CO(2) in air at normal respiratory rate, induced a positive shift. The high amplitude of the voltage gradients on the scalp induced by hyperventilation is not consistent with a neuronal origin. Instead, the present data suggest that they are generated by extracortical volume currents driven by a Pco(2)-dependent potential difference across epithelia separating the cerebrospinal fluid and blood. Since changes in respiratory patterns and, hence, in the level of brain Pco(2), are likely to occur under a number of experimental conditions in which slow EEG responses have been reported (e.g., attention shifts, preparatory states, epileptic seizures, and hypoxic episodes), the present results call for a thorough reexamination of the mechanisms underlying scalp-recorded DC-EEG responses.

Matrix kernels for MEG and EEG source localization and imaging

International Nuclear Information System (INIS)

Mosher, J.C.; Lewis, P.S.; Leahy, R.M.

1994-01-01

The most widely used model for electroencephalography (EEG) and magnetoencephalography (MEG) assumes a quasi-static approximation of Maxwell's equations and a piecewise homogeneous conductor model. Both models contain an incremental field element that linearly relates an incremental source element (current dipole) to the field or voltage at a distant point. The explicit form of the field element is dependent on the head modeling assumptions and sensor configuration. Proper characterization of this incremental element is crucial to the inverse problem. The field element can be partitioned into the product of a vector dependent on sensor characteristics and a matrix kernel dependent only on head modeling assumptions. We present here the matrix kernels for the general boundary element model (BEM) and for MEG spherical models. We show how these kernels are easily interchanged in a linear algebraic framework that includes sensor specifics such as orientation and gradiometer configuration. We then describe how this kernel is easily applied to ''gain'' or ''transfer'' matrices used in multiple dipole and source imaging models

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Fast multipole acceleration of the MEG/EEG boundary element method

International Nuclear Information System (INIS)

Kybic, Jan; Clerc, Maureen; Faugeras, Olivier; Keriven, Renaud; Papadopoulo, Theo

2005-01-01

The accurate solution of the forward electrostatic problem is an essential first step before solving the inverse problem of magneto- and electroencephalography (MEG/EEG). The symmetric Galerkin boundary element method is accurate but cannot be used for very large problems because of its computational complexity and memory requirements. We describe a fast multipole-based acceleration for the symmetric boundary element method (BEM). It creates a hierarchical structure of the elements and approximates far interactions using spherical harmonics expansions. The accelerated method is shown to be as accurate as the direct method, yet for large problems it is both faster and more economical in terms of memory consumption

EEG/MEG Source Reconstruction with Spatial-Temporal Two-Way Regularized Regression

KAUST Repository

Tian, Tian Siva

2013-07-11

In this work, we propose a spatial-temporal two-way regularized regression method for reconstructing neural source signals from EEG/MEG time course measurements. The proposed method estimates the dipole locations and amplitudes simultaneously through minimizing a single penalized least squares criterion. The novelty of our methodology is the simultaneous consideration of three desirable properties of the reconstructed source signals, that is, spatial focality, spatial smoothness, and temporal smoothness. The desirable properties are achieved by using three separate penalty functions in the penalized regression framework. Specifically, we impose a roughness penalty in the temporal domain for temporal smoothness, and a sparsity-inducing penalty and a graph Laplacian penalty in the spatial domain for spatial focality and smoothness. We develop a computational efficient multilevel block coordinate descent algorithm to implement the method. Using a simulation study with several settings of different spatial complexity and two real MEG examples, we show that the proposed method outperforms existing methods that use only a subset of the three penalty functions. © 2013 Springer Science+Business Media New York.

Early prefrontal brain responses to the Hedonic quality of emotional words--a simultaneous EEG and MEG study.

Science.gov (United States)

Keuper, Kati; Zwitserlood, Pienie; Rehbein, Maimu A; Eden, Annuschka S; Laeger, Inga; Junghöfer, Markus; Zwanzger, Peter; Dobel, Christian

2013-01-01

The hedonic meaning of words affects word recognition, as shown by behavioral, functional imaging, and event-related potential (ERP) studies. However, the spatiotemporal dynamics and cognitive functions behind are elusive, partly due to methodological limitations of previous studies. Here, we account for these difficulties by computing combined electro-magnetoencephalographic (EEG/MEG) source localization techniques. Participants covertly read emotionally high-arousing positive and negative nouns, while EEG and MEG were recorded simultaneously. Combined EEG/MEG current-density reconstructions for the P1 (80-120 ms), P2 (150-190 ms) and EPN component (200-300 ms) were computed using realistic individual head models, with a cortical constraint. Relative to negative words, the P1 to positive words predominantly involved language-related structures (left middle temporal and inferior frontal regions), and posterior structures related to directed attention (occipital and parietal regions). Effects shifted to the right hemisphere in the P2 component. By contrast, negative words received more activation in the P1 time-range only, recruiting prefrontal regions, including the anterior cingulate cortex (ACC). Effects in the EPN were not statistically significant. These findings show that different neuronal networks are active when positive versus negative words are processed. We account for these effects in terms of an "emotional tagging" of word forms during language acquisition. These tags then give rise to different processing strategies, including enhanced lexical processing of positive words and a very fast language-independent alert response to negative words. The valence-specific recruitment of different networks might underlie fast adaptive responses to both approach- and withdrawal-related stimuli, be they acquired or biological.

A fast and reliable method for simultaneous waveform, amplitude and latency estimation of single-trial EEG/MEG data.

Directory of Open Access Journals (Sweden)

Wouter D Weeda

Full Text Available The amplitude and latency of single-trial EEG/MEG signals may provide valuable information concerning human brain functioning. In this article we propose a new method to reliably estimate single-trial amplitude and latency of EEG/MEG signals. The advantages of the method are fourfold. First, no a-priori specified template function is required. Second, the method allows for multiple signals that may vary independently in amplitude and/or latency. Third, the method is less sensitive to noise as it models data with a parsimonious set of basis functions. Finally, the method is very fast since it is based on an iterative linear least squares algorithm. A simulation study shows that the method yields reliable estimates under different levels of latency variation and signal-to-noise ratioÕs. Furthermore, it shows that the existence of multiple signals can be correctly determined. An application to empirical data from a choice reaction time study indicates that the method describes these data accurately.

Reducing Sensor Noise in MEG and EEG Recordings Using Oversampled Temporal Projection.

Science.gov (United States)

Larson, Eric; Taulu, Samu

2018-05-01

Here, we review the theory of suppression of spatially uncorrelated, sensor-specific noise in electro- and magentoencephalography (EEG and MEG) arrays, and introduce a novel method for suppression. Our method requires only that the signals of interest are spatially oversampled, which is a reasonable assumption for many EEG and MEG systems. Our method is based on a leave-one-out procedure using overlapping temporal windows in a mathematical framework to project spatially uncorrelated noise in the temporal domain. This method, termed "oversampled temporal projection" (OTP), has four advantages over existing methods. First, sparse channel-specific artifacts are suppressed while limiting mixing with other channels, whereas existing linear, time-invariant spatial operators can spread such artifacts to other channels with a spatial distribution which can be mistaken for one produced by an electrophysiological source. Second, OTP minimizes distortion of the spatial configuration of the data. During source localization (e.g., dipole fitting), many spatial methods require corresponding modification of the forward model to avoid bias, while OTP does not. Third, noise suppression factors at the sensor level are maintained during source localization, whereas bias compensation removes the denoising benefit for spatial methods that require such compensation. Fourth, OTP uses a time-window duration parameter to control the tradeoff between noise suppression and adaptation to time-varying sensor characteristics. OTP efficiently optimizes noise suppression performance while controlling for spatial bias of the signal of interest. This is important in applications where sensor noise significantly limits the signal-to-noise ratio, such as high-frequency brain oscillations.

Similarities and differences between on-scalp and conventional in-helmet magnetoencephalography recordings.

Directory of Open Access Journals (Sweden)

Lau M Andersen

Full Text Available The development of new magnetic sensor technologies that promise sensitivities approaching that of conventional MEG technology while operating at far lower operating temperatures has catalysed the growing field of on-scalp MEG. The feasibility of on-scalp MEG has been demonstrated via benchmarking of new sensor technologies performing neuromagnetic recordings in close proximity to the head surface against state-of-the-art in-helmet MEG sensor technology. However, earlier work has provided little information about how these two approaches compare, or about the reliability of observed differences. Herein, we present such a comparison, based on recordings of the N20m component of the somatosensory evoked field as elicited by electric median nerve stimulation. As expected from the proximity differences between the on-scalp and in-helmet sensors, the magnitude of the N20m activation as recorded with the on-scalp sensor was higher than that of the in-helmet sensors. The dipole pattern of the on-scalp recordings was also more spatially confined than that of the conventional recordings. Our results furthermore revealed unexpected temporal differences in the peak of the N20m component. An analysis protocol was therefore developed for assessing the reliability of this observed difference. We used this protocol to examine our findings in terms of differences in sensor sensitivity between the two types of MEG recordings. The measurements and subsequent analysis raised attention to the fact that great care has to be taken in measuring the field close to the zero-line crossing of the dipolar field, since it is heavily dependent on the orientation of sensors. Taken together, our findings provide reliable evidence that on-scalp and in-helmet sensors measure neural sources in mostly similar ways.

Early Prefrontal Brain Responses to the Hedonic Quality of Emotional Words – A Simultaneous EEG and MEG Study

Science.gov (United States)

Keuper, Kati; Zwitserlood, Pienie; Rehbein, Maimu A.; Eden, Annuschka S.; Laeger, Inga; Junghöfer, Markus; Zwanzger, Peter; Dobel, Christian

2013-01-01

The hedonic meaning of words affects word recognition, as shown by behavioral, functional imaging, and event-related potential (ERP) studies. However, the spatiotemporal dynamics and cognitive functions behind are elusive, partly due to methodological limitations of previous studies. Here, we account for these difficulties by computing combined electro-magnetoencephalographic (EEG/MEG) source localization techniques. Participants covertly read emotionally high-arousing positive and negative nouns, while EEG and MEG were recorded simultaneously. Combined EEG/MEG current-density reconstructions for the P1 (80–120 ms), P2 (150–190 ms) and EPN component (200–300 ms) were computed using realistic individual head models, with a cortical constraint. Relative to negative words, the P1 to positive words predominantly involved language-related structures (left middle temporal and inferior frontal regions), and posterior structures related to directed attention (occipital and parietal regions). Effects shifted to the right hemisphere in the P2 component. By contrast, negative words received more activation in the P1 time-range only, recruiting prefrontal regions, including the anterior cingulate cortex (ACC). Effects in the EPN were not statistically significant. These findings show that different neuronal networks are active when positive versus negative words are processed. We account for these effects in terms of an “emotional tagging” of word forms during language acquisition. These tags then give rise to different processing strategies, including enhanced lexical processing of positive words and a very fast language-independent alert response to negative words. The valence-specific recruitment of different networks might underlie fast adaptive responses to both approach- and withdrawal-related stimuli, be they acquired or biological. PMID:23940642

Comparing the Performance of Popular MEG/EEG Artifact Correction Methods in an Evoked-Response Study

DEFF Research Database (Denmark)

Haumann, Niels Trusbak; Parkkonen, Lauri; Kliuchko, Marina

2016-01-01

We here compared results achieved by applying popular methods for reducing artifacts in magnetoencephalography (MEG) and electroencephalography (EEG) recordings of the auditory evoked Mismatch Negativity (MMN) responses in healthy adult subjects. We compared the Signal Space Separation (SSS......) and temporal SSS (tSSS) methods for reducing noise from external and nearby sources. Our results showed that tSSS reduces the interference level more reliably than plain SSS, particularly for MEG gradiometers, also for healthy subjects not wearing strongly interfering magnetic material. Therefore, tSSS...... is recommended over SSS. Furthermore, we found that better artifact correction is achieved by applying Independent Component Analysis (ICA) in comparison to Signal Space Projection (SSP). Although SSP reduces the baseline noise level more than ICA, SSP also significantly reduces the signal—slightly more than...

Model-based analysis and optimization of the mapping of cortical sources in the spontaneous scalp EEG

NARCIS (Netherlands)

Sazonov, A.; Bergmans, J.W.M.; Cluitmans, P.J.M.; Griep, P.A.M.; Arends, J.B.A.M.; Boon, P.A.J.M.

2007-01-01

The mapping of brain sources into the scalp electroencephalogram (EEG) depends on volume conduction properties of the head and on an electrode montage involving a reference. Mathematically, this source mapping (SM) is fully determined by an observation function (OF) matrix. This paper analyses the

The Iterative Reweighted Mixed-Norm Estimate for Spatio-Temporal MEG/EEG Source Reconstruction.

Science.gov (United States)

Strohmeier, Daniel; Bekhti, Yousra; Haueisen, Jens; Gramfort, Alexandre

2016-10-01

Source imaging based on magnetoencephalography (MEG) and electroencephalography (EEG) allows for the non-invasive analysis of brain activity with high temporal and good spatial resolution. As the bioelectromagnetic inverse problem is ill-posed, constraints are required. For the analysis of evoked brain activity, spatial sparsity of the neuronal activation is a common assumption. It is often taken into account using convex constraints based on the l 1 -norm. The resulting source estimates are however biased in amplitude and often suboptimal in terms of source selection due to high correlations in the forward model. In this work, we demonstrate that an inverse solver based on a block-separable penalty with a Frobenius norm per block and a l 0.5 -quasinorm over blocks addresses both of these issues. For solving the resulting non-convex optimization problem, we propose the iterative reweighted Mixed Norm Estimate (irMxNE), an optimization scheme based on iterative reweighted convex surrogate optimization problems, which are solved efficiently using a block coordinate descent scheme and an active set strategy. We compare the proposed sparse imaging method to the dSPM and the RAP-MUSIC approach based on two MEG data sets. We provide empirical evidence based on simulations and analysis of MEG data that the proposed method improves on the standard Mixed Norm Estimate (MxNE) in terms of amplitude bias, support recovery, and stability.

ElectroMagnetoEncephalography software: overview and integration with other EEG/MEG toolboxes.

Science.gov (United States)

Peyk, Peter; De Cesarei, Andrea; Junghöfer, Markus

2011-01-01

EMEGS (electromagnetic encephalography software) is a MATLAB toolbox designed to provide novice as well as expert users in the field of neuroscience with a variety of functions to perform analysis of EEG and MEG data. The software consists of a set of graphical interfaces devoted to preprocessing, analysis, and visualization of electromagnetic data. Moreover, it can be extended using a plug-in interface. Here, an overview of the capabilities of the toolbox is provided, together with a simple tutorial for both a standard ERP analysis and a time-frequency analysis. Latest features and future directions of the software development are presented in the final section.

Is functional brain connectivity atypical in autism? A systematic review of EEG and MEG studies.

Directory of Open Access Journals (Sweden)

Christian O'Reilly

Full Text Available Although it is well recognized that autism is associated with altered patterns of over- and under-connectivity, specifics are still a matter of debate. Little has been done so far to synthesize available literature using whole-brain electroencephalography (EEG and magnetoencephalography (MEG recordings.1 To systematically review the literature on EEG/MEG functional and effective connectivity in autism spectrum disorder (ASD, 2 to synthesize and critically appraise findings related with the hypothesis that ASD is characterized by long-range underconnectivity and local overconnectivity, and 3 to provide, based on the literature, an analysis of tentative factors that are likely to mediate association between ASD and atypical connectivity (e.g., development, topography, lateralization.Literature reviews were done using PubMed and PsychInfo databases. Abstracts were screened, and only relevant articles were analyzed based on the objectives of this paper. Special attention was paid to the methodological characteristics that could have created variability in outcomes reported between studies.Our synthesis provides relatively strong support for long-range underconnectivity in ASD, whereas the status of local connectivity remains unclear. This observation was also mirrored by a similar relationship with lower frequencies being often associated with underconnectivity and higher frequencies being associated with both under- and over-connectivity. Putting together these observations, we propose that ASD is characterized by a general trend toward an under-expression of lower-band wide-spread integrative processes compensated by more focal, higher-frequency, locally specialized, and segregated processes. Further investigation is, however, needed to corroborate the conclusion and its generalizability across different tasks. Of note, abnormal lateralization in ASD, specifically an elevated left-over-right EEG and MEG functional connectivity ratio, has been also

EEG and MEG source localization using recursively applied (RAP) MUSIC

Energy Technology Data Exchange (ETDEWEB)

Mosher, J.C. [Los Alamos National Lab., NM (United States); Leahy, R.M. [University of Southern California, Los Angeles, CA (United States). Signal and Image Processing Inst.

1996-12-31

The multiple signal characterization (MUSIC) algorithm locates multiple asynchronous dipolar sources from electroencephalography (EEG) and magnetoencephalography (MEG) data. A signal subspace is estimated from the data, then the algorithm scans a single dipole model through a three-dimensional head volume and computes projections onto this subspace. To locate the sources, the user must search the head volume for local peaks in the projection metric. Here we describe a novel extension of this approach which we refer to as RAP (Recursively APplied) MUSIC. This new procedure automatically extracts the locations of the sources through a recursive use of subspace projections, which uses the metric of principal correlations as a multidimensional form of correlation analysis between the model subspace and the data subspace. The dipolar orientations, a form of `diverse polarization,` are easily extracted using the associated principal vectors.

Compressive sensing scalp EEG signals: implementations and practical performance.

Science.gov (United States)

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.

Physiological Ripples (± 100 Hz) in Spike-Free Scalp EEGs of Children With and Without Epilepsy

NARCIS (Netherlands)

Mooij, Anne H.; Raijmann, Renee C.M.A.; Jansen, Floor E.; Braun, Kees P.J.; Zijlmans, Maeike

2017-01-01

Pathological high frequency oscillations (HFOs, >80 Hz) are considered new biomarkers for epilepsy. They have mostly been recorded invasively, but pathological ripples (80-250 Hz) can also be found in scalp EEGs with frequent epileptiform spikes. Physiological HFOs also exist. They have been

High precision anatomy for MEG.

Science.gov (United States)

Troebinger, Luzia; López, José David; Lutti, Antoine; Bradbury, David; Bestmann, Sven; Barnes, Gareth

2014-02-01

Precise MEG estimates of neuronal current flow are undermined by uncertain knowledge of the head location with respect to the MEG sensors. This is either due to head movements within the scanning session or systematic errors in co-registration to anatomy. Here we show how such errors can be minimized using subject-specific head-casts produced using 3D printing technology. The casts fit the scalp of the subject internally and the inside of the MEG dewar externally, reducing within session and between session head movements. Systematic errors in matching to MRI coordinate system are also reduced through the use of MRI-visible fiducial markers placed on the same cast. Bootstrap estimates of absolute co-registration error were of the order of 1mm. Estimates of relative co-registration error were <1.5mm between sessions. We corroborated these scalp based estimates by looking at the MEG data recorded over a 6month period. We found that the between session sensor variability of the subject's evoked response was of the order of the within session noise, showing no appreciable noise due to between-session movement. Simulations suggest that the between-session sensor level amplitude SNR improved by a factor of 5 over conventional strategies. We show that at this level of coregistration accuracy there is strong evidence for anatomical models based on the individual rather than canonical anatomy; but that this advantage disappears for errors of greater than 5mm. This work paves the way for source reconstruction methods which can exploit very high SNR signals and accurate anatomical models; and also significantly increases the sensitivity of longitudinal studies with MEG. © 2013. Published by Elsevier Inc. All rights reserved.

The developmental trajectory of brain-scalp distance from birth through childhood: implications for functional neuroimaging.

Directory of Open Access Journals (Sweden)

Michael S Beauchamp

Full Text Available Measurements of human brain function in children are of increasing interest in cognitive neuroscience. Many techniques for brain mapping used in children, including functional near-infrared spectroscopy (fNIRS, electroencephalography (EEG, magnetoencephalography (MEG and transcranial magnetic stimulation (TMS, use probes placed on or near the scalp. The distance between the scalp and the brain is a key variable for these techniques because optical, electrical and magnetic signals are attenuated by distance. However, little is known about how scalp-brain distance differs between different cortical regions in children or how it changes with development. We investigated scalp-brain distance in 71 children, from newborn to age 12 years, using structural T1-weighted MRI scans of the whole head. Three-dimensional reconstructions were created from the scalp surface to allow for accurate calculation of brain-scalp distance. Nine brain landmarks in different cortical regions were manually selected in each subject based on the published fNIRS literature. Significant effects were found for age, cortical region and hemisphere. Brain-scalp distances were lowest in young children, and increased with age to up to double the newborn distance. There were also dramatic differences between brain regions, with up to 50% differences between landmarks. In frontal and temporal regions, scalp-brain distances were significantly greater in the right hemisphere than in the left hemisphere. The largest contributors to developmental changes in brain-scalp distance were increases in the corticospinal fluid (CSF and inner table of the cranium. These results have important implications for functional imaging studies of children: age and brain-region related differences in fNIRS signals could be due to the confounding factor of brain-scalp distance and not true differences in brain activity.

Identification of scalp EEG circadian variation using a novel correlation sum measure

Science.gov (United States)

Shahidi Zandi, Ali; Boudreau, Philippe; Boivin, Diane B.; Dumont, Guy A.

2015-10-01

Objective. In this paper, we propose a novel method to determine the circadian variation of scalp electroencephalogram (EEG) in both individual and group levels using a correlation sum measure, quantifying self-similarity of the EEG relative energy across waking epochs. Approach. We analysed EEG recordings from central-parietal and occipito-parietal montages in nine healthy subjects undergoing a 72 h ultradian sleep-wake cycle protocol. Each waking epoch (˜1 s) of every nap opportunity was decomposed using the wavelet packet transform, and the relative energy for that epoch was calculated in the desired frequency band using the corresponding wavelet coefficients. Then, the resulting set of energy values was resampled randomly to generate different subsets with equal number of elements. The correlation sum of each subset was then calculated over a range of distance thresholds, and the average over all subsets was computed. This average value was finally scaled for each nap opportunity and considered as a new circadian measure. Main results. According to the evaluation results, a clear circadian rhythm was identified in some EEG frequency ranges, particularly in 4-8 Hz and 10-12 Hz. The correlation sum measure not only was able to disclose the circadian rhythm on the group data but also revealed significant circadian variations in most individual cases, as opposed to previous studies only reporting the circadian rhythms on a population of subjects. Compared to a naive measure based on the EEG absolute energy in the frequency band of interest, the proposed measure showed a clear superiority using both individual and group data. Results also suggested that the acrophase (i.e., the peak) of the circadian rhythm in 10-12 Hz occurs close to the core body temperature minimum. Significance. These results confirm the potential usefulness of the proposed EEG-based measure as a non-invasive circadian marker.

Analyzing Electroencephalogram Signal Using EEG Lab

Directory of Open Access Journals (Sweden)

Mukesh BHARDWAJ

2009-01-01

Full Text Available The EEG is composed of electrical potentials arising from several sources. Each source (including separate neural clusters, blink artifact or pulse artifact forms a unique topography onto the scalp – ‘scalp map‘. Scalp map may be 2-D or 3-D.These maps are mixed according to the principle of linear superposition. Independent component analysis (ICA attempts to reverse the superposition by separating the EEG into mutually independent scalp maps, or components. MATLAB toolbox and graphic user interface, EEGLAB is used for processing EEG data of any number of channels. Wavelet toolbox has been used for 2-D signal analysis.

Information theoretic measures of network coordination in high-frequency scalp EEG reveal dynamic patterns associated with seizure termination.

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Stamoulis, Catherine; Schomer, Donald L; Chang, Bernard S

2013-08-01

How a seizure terminates is still under-studied and, despite its clinical importance, remains an obscure phase of seizure evolution. Recent studies of seizure-related scalp EEGs at frequencies >100 Hz suggest that neural activity, in the form of oscillations and/or neuronal network interactions, may play an important role in preictal/ictal seizure evolution (Andrade-Valenca et al., 2011; Stamoulis et al., 2012). However, the role of high-frequency activity in seizure termination, is unknown, if it exists at all. Using information theoretic measures of network coordination, this study investigated ictal and immediate postictal neurodynamic interactions encoded in scalp EEGs from a relatively small sample of 8 patients with focal epilepsy and multiple seizures originating in temporal and/or frontal brain regions, at frequencies ≤ 100 Hz and >100 Hz, respectively. Despite some heterogeneity in the dynamics of these interactions, consistent patterns were also estimated. Specifically, in several seizures, linear or non-linear increase in high-frequency neuronal coordination during ictal intervals, coincided with a corresponding decrease in coordination at frequencies interval, which continues during the postictal interval. This may be one of several possible mechanisms that facilitate seizure termination. In fact, inhibition of pairwise interactions between EEGs by other signals in their spatial neighborhood, quantified by negative interaction information, was estimated at frequencies ≤ 100 Hz, at least in some seizures. Copyright © 2013 Elsevier B.V. All rights reserved.

Adaptive autoregressive identification with spectral power decomposition for studying movement-related activity in scalp EEG signals and basal ganglia local field potentials

Science.gov (United States)

Foffani, Guglielmo; Bianchi, Anna M.; Priori, Alberto; Baselli, Giuseppe

2004-09-01

We propose a method that combines adaptive autoregressive (AAR) identification and spectral power decomposition for the study of movement-related spectral changes in scalp EEG signals and basal ganglia local field potentials (LFPs). This approach introduces the concept of movement-related poles, allowing one to study not only the classical event-related desynchronizations (ERD) and synchronizations (ERS), which correspond to modulations of power, but also event-related modulations of frequency. We applied the method to analyze movement-related EEG signals and LFPs contemporarily recorded from the sensorimotor cortex, the globus pallidus internus (GPi) and the subthalamic nucleus (STN) in a patient with Parkinson's disease who underwent stereotactic neurosurgery for the implant of deep brain stimulation (DBS) electrodes. In the AAR identification we compared the whale and the exponential forgetting factors, showing that the whale forgetting provides a better disturbance rejection and it is therefore more suitable to investigate movement-related brain activity. Movement-related power modulations were consistent with previous studies. In addition, movement-related frequency modulations were observed from both scalp EEG signals and basal ganglia LFPs. The method therefore represents an effective approach to the study of movement-related brain activity.

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

Directory of Open Access Journals (Sweden)

Federico Chella

2017-05-01

considering the effects of the reference choice in the interpretation and comparison of the results of bispectral analysis of scalp EEG.

MEG/EEG source reconstruction, statistical evaluation, and visualization with NUTMEG.

Science.gov (United States)

Dalal, Sarang S; Zumer, Johanna M; Guggisberg, Adrian G; Trumpis, Michael; Wong, Daniel D E; Sekihara, Kensuke; Nagarajan, Srikantan S

2011-01-01

NUTMEG is a source analysis toolbox geared towards cognitive neuroscience researchers using MEG and EEG, including intracranial recordings. Evoked and unaveraged data can be imported to the toolbox for source analysis in either the time or time-frequency domains. NUTMEG offers several variants of adaptive beamformers, probabilistic reconstruction algorithms, as well as minimum-norm techniques to generate functional maps of spatiotemporal neural source activity. Lead fields can be calculated from single and overlapping sphere head models or imported from other software. Group averages and statistics can be calculated as well. In addition to data analysis tools, NUTMEG provides a unique and intuitive graphical interface for visualization of results. Source analyses can be superimposed onto a structural MRI or headshape to provide a convenient visual correspondence to anatomy. These results can also be navigated interactively, with the spatial maps and source time series or spectrogram linked accordingly. Animations can be generated to view the evolution of neural activity over time. NUTMEG can also display brain renderings and perform spatial normalization of functional maps using SPM's engine. As a MATLAB package, the end user may easily link with other toolboxes or add customized functions.

Model-Based Analysis and Optimization of the Mapping of Cortical Sources in the Spontaneous Scalp EEG

Directory of Open Access Journals (Sweden)

Andrei V. Sazonov

2007-01-01

Full Text Available The mapping of brain sources into the scalp electroencephalogram (EEG depends on volume conduction properties of the head and on an electrode montage involving a reference. Mathematically, this source mapping (SM is fully determined by an observation function (OF matrix. This paper analyses the OF-matrix for a generation model for the desynchronized spontaneous EEG. The model involves a four-shell spherical volume conductor containing dipolar sources that are mutually uncorrelated so as to reflect the desynchronized EEG. The reference is optimized in order to minimize the impact in the SM of the sources located distant from the electrodes. The resulting reference is called the localized reference (LR. The OF-matrix is analyzed in terms of the relative power contribution of the sources and the cross-channel correlation coefficient for five existing references as well as for the LR. It is found that the Hjorth Laplacian reference is a fair approximation of the LR, and thus is close to optimum for practical intents and purposes. The other references have a significantly poorer performance. Furthermore, the OF-matrix is analyzed for limits to the spatial resolution for the EEG. These are estimated to be around 2 cm.

Localization of extended brain sources from EEG/MEG: the ExSo-MUSIC approach.

Science.gov (United States)

Birot, Gwénaël; Albera, Laurent; Wendling, Fabrice; Merlet, Isabelle

2011-05-01

We propose a new MUSIC-like method, called 2q-ExSo-MUSIC (q ≥ 1). This method is an extension of the 2q-MUSIC (q ≥ 1) approach for solving the EEG/MEG inverse problem, when spatially-extended neocortical sources ("ExSo") are considered. It introduces a novel ExSo-MUSIC principle. The novelty is two-fold: i) the parameterization of the spatial source distribution that leads to an appropriate metric in the context of distributed brain sources and ii) the introduction of an original, efficient and low-cost way of optimizing this metric. In 2q-ExSo-MUSIC, the possible use of higher order statistics (q ≥ 2) offers a better robustness with respect to Gaussian noise of unknown spatial coherence and modeling errors. As a result we reduced the penalizing effects of both the background cerebral activity that can be seen as a Gaussian and spatially correlated noise, and the modeling errors induced by the non-exact resolution of the forward problem. Computer results on simulated EEG signals obtained with physiologically-relevant models of both the sources and the volume conductor show a highly increased performance of our 2q-ExSo-MUSIC method as compared to the classical 2q-MUSIC algorithms. Copyright © 2011 Elsevier Inc. All rights reserved.

Spatiotemporal source analysis in scalp EEG vs. intracerebral EEG and SPECT: a case study in a 2-year-old child.

Science.gov (United States)

Aarabi, A; Grebe, R; Berquin, P; Bourel Ponchel, E; Jalin, C; Fohlen, M; Bulteau, C; Delalande, O; Gondry, C; Héberlé, C; Moullart, V; Wallois, F

2012-06-01

This case study aims to demonstrate that spatiotemporal spike discrimination and source analysis are effective to monitor the development of sources of epileptic activity in time and space. Therefore, they can provide clinically useful information allowing a better understanding of the pathophysiology of individual seizures with time- and space-resolved characteristics of successive epileptic states, including interictal, preictal, postictal, and ictal states. High spatial resolution scalp EEGs (HR-EEG) were acquired from a 2-year-old girl with refractory central epilepsy and single-focus seizures as confirmed by intracerebral EEG recordings and ictal single-photon emission computed tomography (SPECT). Evaluation of HR-EEG consists of the following three global steps: (1) creation of the initial head model, (2) automatic spike and seizure detection, and finally (3) source localization. During the source localization phase, epileptic states are determined to allow state-based spike detection and localization of underlying sources for each spike. In a final cluster analysis, localization results are integrated to determine the possible sources of epileptic activity. The results were compared with the cerebral locations identified by intracerebral EEG recordings and SPECT. The results obtained with this approach were concordant with those of MRI, SPECT and distribution of intracerebral potentials. Dipole cluster centres found for spikes in interictal, preictal, ictal and postictal states were situated an average of 6.3mm from the intracerebral contacts with the highest voltage. Both amplitude and shape of spikes change between states. Dispersion of the dipoles was higher in the preictal state than in the postictal state. Two clusters of spikes were identified. The centres of these clusters changed position periodically during the various epileptic states. High-resolution surface EEG evaluated by an advanced algorithmic approach can be used to investigate the

EEG, MRI, and SPECT in epilepsy. Relative contributions to preoperative evaluation

International Nuclear Information System (INIS)

Seki, Gaku; Hoshida, Tohru; Goda, Kazuo; Hashimoto, Hiroshi; Nakase, Hiroyuki; Hirabayashi, Hidehiro; Kawaguchi, Shoichiro; Morimoto, Tetsuya; Sakaki, Toshisuke

1998-01-01

We comparatively assessed detection of epileptogenic areas on preoperative evaluation in 33 patients with intractable partial epilepsy using scalp interictal and ictal electroencephalography (EEG), magnetic resonance imaging (MRI), and interictal single photon emission computed tomography (SPECT). There are 22 temporal and 11 extratemporal lobe epilepsies. All or almost of their seizures have stopped after resective surgery for more than 12 months follow-up period, averaged 43 months. MRI studies demonstrated 21 organic lesions, 11 mesial temporal sclerosis and one patient showed normal brain tissue. Scalp EEG could correctly identify the focus in 14 of 33 cases (42%), interictal SPECT in 18 of 26 (69%), MRI in 29 of 33 (88%), interictal scalp EEG-video monitoring in 17 of 24 (71%), and ictal scalp EEG-video monitoring in 15 of 22 (68%). Although neuroimaging studies, especially MRI, are useful to detect not only localization of epileptic lesions but also epileptogenic focus, for example, mesial temporal sclerosis, the exact localization of epileptogenic areas could be done by comprehensive evaluation including ictal scalp EEG-video monitoring. (author)

EEG, MRI, and SPECT in epilepsy. Relative contributions to preoperative evaluation

Energy Technology Data Exchange (ETDEWEB)

Seki, Gaku [Luoyang Medical Coll. Associated Hospital (China); Hoshida, Tohru; Goda, Kazuo; Hashimoto, Hiroshi; Nakase, Hiroyuki; Hirabayashi, Hidehiro; Kawaguchi, Shoichiro; Morimoto, Tetsuya; Sakaki, Toshisuke

1998-07-01

We comparatively assessed detection of epileptogenic areas on preoperative evaluation in 33 patients with intractable partial epilepsy using scalp interictal and ictal electroencephalography (EEG), magnetic resonance imaging (MRI), and interictal single photon emission computed tomography (SPECT). There are 22 temporal and 11 extratemporal lobe epilepsies. All or almost of their seizures have stopped after resective surgery for more than 12 months follow-up period, averaged 43 months. MRI studies demonstrated 21 organic lesions, 11 mesial temporal sclerosis and one patient showed normal brain tissue. Scalp EEG could correctly identify the focus in 14 of 33 cases (42%), interictal SPECT in 18 of 26 (69%), MRI in 29 of 33 (88%), interictal scalp EEG-video monitoring in 17 of 24 (71%), and ictal scalp EEG-video monitoring in 15 of 22 (68%). Although neuroimaging studies, especially MRI, are useful to detect not only localization of epileptic lesions but also epileptogenic focus, for example, mesial temporal sclerosis, the exact localization of epileptogenic areas could be done by comprehensive evaluation including ictal scalp EEG-video monitoring. (author)

EEG-distributed inverse solutions for a spherical head model

Science.gov (United States)

Riera, J. J.; Fuentes, M. E.; Valdés, P. A.; Ohárriz, Y.

1998-08-01

The theoretical study of the minimum norm solution to the MEG inverse problem has been carried out in previous papers for the particular case of spherical symmetry. However, a similar study for the EEG is remarkably more difficult due to the very complicated nature of the expression relating the voltage differences on the scalp to the primary current density (PCD) even for this simple symmetry. This paper introduces the use of the electric lead field (ELF) on the dyadic formalism in the spherical coordinate system to overcome such a drawback using an expansion of the ELF in terms of longitudinal and orthogonal vector fields. This approach allows us to represent EEG Fourier coefficients on a 2-sphere in terms of a current multipole expansion. The choice of a suitable basis for the Hilbert space of the PCDs on the brain region allows the current multipole moments to be related by spatial transfer functions to the PCD spectral coefficients. Properties of the most used distributed inverse solutions are explored on the basis of these results. Also, a part of the ELF null space is completely characterized and those spherical components of the PCD which are possible silent candidates are discussed.

FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data.

Science.gov (United States)

Oostenveld, Robert; Fries, Pascal; Maris, Eric; Schoffelen, Jan-Mathijs

2011-01-01

This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages.

Bayesian model selection of template forward models for EEG source reconstruction.

Science.gov (United States)

Strobbe, Gregor; van Mierlo, Pieter; De Vos, Maarten; Mijović, Bogdan; Hallez, Hans; Van Huffel, Sabine; López, José David; Vandenberghe, Stefaan

2014-06-01

Several EEG source reconstruction techniques have been proposed to identify the generating neuronal sources of electrical activity measured on the scalp. The solution of these techniques depends directly on the accuracy of the forward model that is inverted. Recently, a parametric empirical Bayesian (PEB) framework for distributed source reconstruction in EEG/MEG was introduced and implemented in the Statistical Parametric Mapping (SPM) software. The framework allows us to compare different forward modeling approaches, using real data, instead of using more traditional simulated data from an assumed true forward model. In the absence of a subject specific MR image, a 3-layered boundary element method (BEM) template head model is currently used including a scalp, skull and brain compartment. In this study, we introduced volumetric template head models based on the finite difference method (FDM). We constructed a FDM head model equivalent to the BEM model and an extended FDM model including CSF. These models were compared within the context of three different types of source priors related to the type of inversion used in the PEB framework: independent and identically distributed (IID) sources, equivalent to classical minimum norm approaches, coherence (COH) priors similar to methods such as LORETA, and multiple sparse priors (MSP). The resulting models were compared based on ERP data of 20 subjects using Bayesian model selection for group studies. The reconstructed activity was also compared with the findings of previous studies using functional magnetic resonance imaging. We found very strong evidence in favor of the extended FDM head model with CSF and assuming MSP. These results suggest that the use of realistic volumetric forward models can improve PEB EEG source reconstruction. Copyright © 2014 Elsevier Inc. All rights reserved.

Genetic influence demonstrated for MEG-recorded somatosensory evoked responses

NARCIS (Netherlands)

van 't Ent, D.; van Soelen, I.L.C.; Stam, K.J.; de Geus, E.J.C.; Boomsma, D.I.

2010-01-01

We tested for a genetic influence on magnetoencephalogram (MEG)-recorded somatosensory evoked fields (SEFs) in 20 monozygotic (MZ) and 14 dizygotic (DZ) twin pairs. Previous electroencephalogram (EEG) studies that demonstrated a genetic contribution to evoked responses generally focused on

Plethysmogram and EEG: Effects of Music and Voice Sound

Science.gov (United States)

Miao, Tiejun; Oyama-Higa, Mayumi; Sato, Sadaka; Kojima, Junji; Lin, Juan; Reika, Sato

2011-06-01

We studied a relation of chaotic dynamics of finger plethysmogram to complexity of high cerebral center in both theoretical and experimental approaches. We proposed a mathematical model to describe emergence of chaos in finger tip pulse wave, which gave a theoretical prediction indicating increased chaoticity in higher cerebral center leading to an increase of chaos dynamics in plethysmograms. We designed an experiment to observe scalp-EEG and finger plethysmogram using two mental tasks to validate the relationship. We found that scalp-EEG showed an increase of the largest Lyapunov exponents (LLE) during speaking certain voices. Topographical scalp map of LLE showed enhanced arise around occipital and right cerebral area. Whereas there was decreasing tendency during listening music, where LLE scalp map revealed a drop around center cerebral area. The same tendency was found for LLE obtained from finger plethysmograms as ones of EEG under either speaking or listening tasks. The experiment gave results that agreed well with the theoretical relation derived from our proposed model.

The neural basis of sublexical speech and corresponding nonspeech processing: a combined EEG-MEG study.

Science.gov (United States)

Kuuluvainen, Soila; Nevalainen, Päivi; Sorokin, Alexander; Mittag, Maria; Partanen, Eino; Putkinen, Vesa; Seppänen, Miia; Kähkönen, Seppo; Kujala, Teija

2014-03-01

We addressed the neural organization of speech versus nonspeech sound processing by investigating preattentive cortical auditory processing of changes in five features of a consonant-vowel syllable (consonant, vowel, sound duration, frequency, and intensity) and their acoustically matched nonspeech counterparts in a simultaneous EEG-MEG recording of mismatch negativity (MMN/MMNm). Overall, speech-sound processing was enhanced compared to nonspeech sound processing. This effect was strongest for changes which affect word meaning (consonant, vowel, and vowel duration) in the left and for the vowel identity change in the right hemisphere also. Furthermore, in the right hemisphere, speech-sound frequency and intensity changes were processed faster than their nonspeech counterparts, and there was a trend for speech-enhancement in frequency processing. In summary, the results support the proposed existence of long-term memory traces for speech sounds in the auditory cortices, and indicate at least partly distinct neural substrates for speech and nonspeech sound processing. Copyright © 2014 Elsevier Inc. All rights reserved.

EEG: Origin and measurement

NARCIS (Netherlands)

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

2010-01-01

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

Ear-EEG detects ictal and interictal abnormalities in focal and generalized epilepsy

DEFF Research Database (Denmark)

Zibrandtsen, I. C.; Kidmose, P.; Christensen, C. B.

2017-01-01

-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...... 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. Conclusions 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. Significance Ear-EEG is likely to become an important tool in clinical epilepsy monitoring and diagnosis....

Bioelectromagnetic forward problem: isolated source approach revis(it)ed.

Science.gov (United States)

Stenroos, M; Sarvas, J

2012-06-07

Electro- and magnetoencephalography (EEG and MEG) are non-invasive modalities for studying the electrical activity of the brain by measuring voltages on the scalp and magnetic fields outside the head. In the forward problem of EEG and MEG, the relationship between the neural sources and resulting signals is characterized using electromagnetic field theory. This forward problem is commonly solved with the boundary-element method (BEM). The EEG forward problem is numerically challenging due to the low relative conductivity of the skull. In this work, we revise the isolated source approach (ISA) that enables the accurate, computationally efficient BEM solution of this problem. The ISA is formulated for generic basis and weight functions that enable the use of Galerkin weighting. The implementation of the ISA-formulated linear Galerkin BEM (LGISA) is first verified in spherical geometry. Then, the LGISA is compared with conventional Galerkin and symmetric BEM approaches in a realistic 3-shell EEG/MEG model. The results show that the LGISA is a state-of-the-art method for EEG/MEG forward modeling: the ISA formulation increases the accuracy and decreases the computational load. Contrary to some earlier studies, the results show that the ISA increases the accuracy also in the computation of magnetic fields.

Computerized spectral analyses of EEG in chronic schizophrenic patients

International Nuclear Information System (INIS)

Fujita, Haruhiro

1985-01-01

This study was aimed at clarifying the EEG difference between chronic schizophrenic patients and normal controls by using the EEG method of spectral analyses. Twelve comparatively homogenous chronic schizophrenic patients and the 10 healthy controls were subjected to EEG investigations. 1) The EEG of schizophrenic patients had a slowing tendency of the frequency in the frontal pole, anterior temporal and central regions of the scalp compared with control subjects. 2) There was a decrease of mutual relation among the five electrodes' peak frequency in the schizophrenic patients. 3) The EEG of schizophrenic patients had more fast waves of β 1 and β 2 band than that of control subjects. 4) A slowing tendency of the frequency in the first half regions of the scalp was not found in 3 chronic schizophrenic patients which showed defective functions in the frontal area by positron emission tomography. 5) When mental arithmetic was given, the schizophrenic patients showed an increase of fast wave in the central, posterior temporal and occipital regions of the scalp. 6) When they opened their eyes, attenuation in the α band was not so marked in the schizophrenic patients. (author)

Effect of Brain-to-Skull Conductivity Ratio on EEG Source Localization Accuracy

OpenAIRE

Gang Wang; Doutian Ren

2013-01-01

The goal of this study was to investigate the influence of the brain-to-skull conductivity ratio (BSCR) on EEG source localization accuracy. In this study, we evaluated four BSCRs: 15, 20, 25, and 80, which were mainly discussed according to the literature. The scalp EEG signals were generated by BSCR-related forward computation for each cortical dipole source. Then, for each scalp EEG measurement, the source reconstruction was performed to identify the estimated dipole sources by the actual ...

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

International Nuclear Information System (INIS)

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)

Simultaneous head tissue conductivity and EEG source location estimation.

Science.gov (United States)

Akalin Acar, Zeynep; Acar, Can E; Makeig, Scott

2016-01-01

Accurate electroencephalographic (EEG) source localization requires an electrical head model incorporating accurate geometries and conductivity values for the major head tissues. While consistent conductivity values have been reported for scalp, brain, and cerebrospinal fluid, measured brain-to-skull conductivity ratio (BSCR) estimates have varied between 8 and 80, likely reflecting both inter-subject and measurement method differences. In simulations, mis-estimation of skull conductivity can produce source localization errors as large as 3cm. Here, we describe an iterative gradient-based approach to Simultaneous tissue Conductivity And source Location Estimation (SCALE). The scalp projection maps used by SCALE are obtained from near-dipolar effective EEG sources found by adequate independent component analysis (ICA) decomposition of sufficient high-density EEG data. We applied SCALE to simulated scalp projections of 15cm(2)-scale cortical patch sources in an MR image-based electrical head model with simulated BSCR of 30. Initialized either with a BSCR of 80 or 20, SCALE estimated BSCR as 32.6. In Adaptive Mixture ICA (AMICA) decompositions of (45-min, 128-channel) EEG data from two young adults we identified sets of 13 independent components having near-dipolar scalp maps compatible with a single cortical source patch. Again initialized with either BSCR 80 or 25, SCALE gave BSCR estimates of 34 and 54 for the two subjects respectively. The ability to accurately estimate skull conductivity non-invasively from any well-recorded EEG data in combination with a stable and non-invasively acquired MR imaging-derived electrical head model could remove a critical barrier to using EEG as a sub-cm(2)-scale accurate 3-D functional cortical imaging modality. Copyright © 2015 Elsevier Inc. All rights reserved.

Correlation between intra- and extracranial background EEG

DEFF Research Database (Denmark)

Duun-Henriksen, Jonas; Kjaer, Troels W.; Madsen, Rasmus E.

2012-01-01

Scalp EEG is the most widely used modality to record the electrical signals of the brain. It is well known that the volume conduction of these brain waves through the brain, cerebrospinal fluid, skull and scalp reduces the spatial resolution and the signal amplitude. So far the volume conduction...... has primarily been investigated by realistic head models or interictal spike analysis. We have set up a novel and more realistic experiment that made it possible to compare the information in the intra- and extracranial EEG. We found that intracranial EEG channels contained correlated patterns when...... placed less than 30 mm apart, that intra- and extracranial channels were partly correlated when placed less than 40 mm apart, and that extracranial channels probably were correlated over larger distances. The underlying cortical area that influences the extracranial EEG is found to be up to 45 cm2...

Independent EEG sources are dipolar.

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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.

Automatic seizure detection: going from sEEG to iEEG

DEFF Research Database (Denmark)

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

2010-01-01

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

Source-space ICA for MEG source imaging.

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Jonmohamadi, Yaqub; Jones, Richard D

2016-02-01

One of the most widely used approaches in electroencephalography/magnetoencephalography (MEG) source imaging is application of an inverse technique (such as dipole modelling or sLORETA) on the component extracted by independent component analysis (ICA) (sensor-space ICA + inverse technique). The advantage of this approach over an inverse technique alone is that it can identify and localize multiple concurrent sources. Among inverse techniques, the minimum-variance beamformers offer a high spatial resolution. However, in order to have both high spatial resolution of beamformer and be able to take on multiple concurrent sources, sensor-space ICA + beamformer is not an ideal combination. We propose source-space ICA for MEG as a powerful alternative approach which can provide the high spatial resolution of the beamformer and handle multiple concurrent sources. The concept of source-space ICA for MEG is to apply the beamformer first and then singular value decomposition + ICA. In this paper we have compared source-space ICA with sensor-space ICA both in simulation and real MEG. The simulations included two challenging scenarios of correlated/concurrent cluster sources. Source-space ICA provided superior performance in spatial reconstruction of source maps, even though both techniques performed equally from a temporal perspective. Real MEG from two healthy subjects with visual stimuli were also used to compare performance of sensor-space ICA and source-space ICA. We have also proposed a new variant of minimum-variance beamformer called weight-normalized linearly-constrained minimum-variance with orthonormal lead-field. As sensor-space ICA-based source reconstruction is popular in EEG and MEG imaging, and given that source-space ICA has superior spatial performance, it is expected that source-space ICA will supersede its predecessor in many applications.

Automatic detection and visualisation of MEG ripple oscillations in epilepsy

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Nicole van Klink

2017-01-01

Full Text Available High frequency oscillations (HFOs, 80–500 Hz in invasive EEG are a biomarker for the epileptic focus. Ripples (80–250 Hz have also been identified in non-invasive MEG, yet detection is impeded by noise, their low occurrence rates, and the workload of visual analysis. We propose a method that identifies ripples in MEG through noise reduction, beamforming and automatic detection with minimal user effort. We analysed 15 min of presurgical resting-state interictal MEG data of 25 patients with epilepsy. The MEG signal-to-noise was improved by using a cross-validation signal space separation method, and by calculating ~2400 beamformer-based virtual sensors in the grey matter. Ripples in these sensors were automatically detected by an algorithm optimized for MEG. A small subset of the identified ripples was visually checked. Ripple locations were compared with MEG spike dipole locations and the resection area if available. Running the automatic detection algorithm resulted in on average 905 ripples per patient, of which on average 148 ripples were visually reviewed. Reviewing took approximately 5 min per patient, and identified ripples in 16 out of 25 patients. In 14 patients the ripple locations showed good or moderate concordance with the MEG spikes. For six out of eight patients who had surgery, the ripple locations showed concordance with the resection area: 4/5 with good outcome and 2/3 with poor outcome. Automatic ripple detection in beamformer-based virtual sensors is a feasible non-invasive tool for the identification of ripples in MEG. Our method requires minimal user effort and is easily applicable in a clinical setting.

Application of modern tests for stationarity to single-trial MEG data: transferring powerful statistical tools from econometrics to neuroscience.

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Kipiński, Lech; König, Reinhard; Sielużycki, Cezary; Kordecki, Wojciech

2011-10-01

Stationarity is a crucial yet rarely questioned assumption in the analysis of time series of magneto- (MEG) or electroencephalography (EEG). One key drawback of the commonly used tests for stationarity of encephalographic time series is the fact that conclusions on stationarity are only indirectly inferred either from the Gaussianity (e.g. the Shapiro-Wilk test or Kolmogorov-Smirnov test) or the randomness of the time series and the absence of trend using very simple time-series models (e.g. the sign and trend tests by Bendat and Piersol). We present a novel approach to the analysis of the stationarity of MEG and EEG time series by applying modern statistical methods which were specifically developed in econometrics to verify the hypothesis that a time series is stationary. We report our findings of the application of three different tests of stationarity--the Kwiatkowski-Phillips-Schmidt-Schin (KPSS) test for trend or mean stationarity, the Phillips-Perron (PP) test for the presence of a unit root and the White test for homoscedasticity--on an illustrative set of MEG data. For five stimulation sessions, we found already for short epochs of duration of 250 and 500 ms that, although the majority of the studied epochs of single MEG trials were usually mean-stationary (KPSS test and PP test), they were classified as nonstationary due to their heteroscedasticity (White test). We also observed that the presence of external auditory stimulation did not significantly affect the findings regarding the stationarity of the data. We conclude that the combination of these tests allows a refined analysis of the stationarity of MEG and EEG time series.

Investigating social cognition in infants and adults using dense array electroencephalography ((d)EEG).

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Akano, Adekemi J; Haley, David W; Dudek, Joanna

2011-06-27

Dense array electroencephalography ((d)EEG), which provides a non-invasive window for measuring brain activity and a temporal resolution unsurpassed by any other current brain imaging technology¹, ² is being used increasingly in the study of social cognitive functioning in infants and adults. While (d)EEG is enabling researchers to examine brain activity patterns with unprecedented levels of sensitivity, conventional EEG recording systems continue to face certain limitations, including 1) poor spatial resolution and source localization³,⁴2) the physical discomfort for test subjects of enduring the individual application of numerous electrodes to the surface of the scalp, and 3) the complexity for researchers of learning to use multiple software packages to collect and process data. Here we present an overview of an established methodology that represents a significant improvement on conventional methodologies for studying EEG in infants and adults. Although several analytical software techniques can be used to establish indirect indices of source localization to improve the spatial resolution of (d)EEG, the HydroCel Geodesic Sensor Net (HCGSN) by Electrical Geodesics, Inc. (EGI), a dense sensory array that maintains equal distances among adjacent recording electrodes on all surfaces of the scalp, further enhances spatial resolution⁴,⁵(,)⁶ compared to standard (d)EEG systems. The sponge-based HCGSN can be applied rapidly and without scalp abrasion, making it ideal for use with adults⁷,⁸ children⁹,¹⁰, ¹¹,¹² and infants¹², in both research and clinical ⁴,⁵,⁶,¹³,¹⁴,¹⁵settings. This feature allows for considerable cost and time savings by decreasing the average net application time compared to other (d)EEG systems. Moreover, the HCGSN includes unified, seamless software applications for all phases of data, greatly simplifying the collection, processing, and analysis of (d)EEG data. The HCGSN features a low-profile electrode

Processing of complex distracting sounds in school-aged children and adults: Evidence from EEG and MEG data

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Philipp eRuhnau

2013-10-01

Full Text Available When a perceiver performs a task, rarely occurring sounds often have a distracting effect on task performance. The neural mismatch responses in event-related potentials to such distracting stimuli depend on age. Adults commonly show a negative response, whereas in children a positive as well as a negative mismatch response has been reported. Using electro- and magnetoencephalography (EEG/MEG, here we investigated the developmental changes of distraction processing in school-aged children (9–10 years and adults. Participants took part in an auditory-visual distraction paradigm comprising a visuo-spatial primary task and task-irrelevant environmental sounds distracting from this task. Behaviorally, distractors delayed reaction times in the primary task in both age groups, and this delay was of similar magnitude in both groups. The neurophysiological data revealed an early as well as a late mismatch response elicited by distracting stimuli in both age groups. Together with previous research, this indicates that deviance detection is accomplished in a hierarchical manner in the auditory system. Both mismatch responses were localized to auditory cortex areas. All mismatch responses were generally delayed in children, suggesting that not all neurophysiological aspects of deviance processing are mature in school-aged children. Furthermore, the P3a, reflecting involuntary attention capture, was present in both age groups in the EEG with comparable amplitudes and at similar latencies, but with a different topographical distribution. This suggests that involuntary attention shifts towards complex distractors operate comparably in school-aged children and adults, yet undergoing generator maturation.

Selection of Mother Wavelet Functions for Multi-Channel EEG Signal Analysis during a Working Memory Task

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Noor Kamal Al-Qazzaz

2015-11-01

Full Text Available We performed a comparative study to select the efficient mother wavelet (MWT basis functions that optimally represent the signal characteristics of the electrical activity of the human brain during a working memory (WM task recorded through electro-encephalography (EEG. Nineteen EEG electrodes were placed on the scalp following the 10–20 system. These electrodes were then grouped into five recording regions corresponding to the scalp area of the cerebral cortex. Sixty-second WM task data were recorded from ten control subjects. Forty-five MWT basis functions from orthogonal families were investigated. These functions included Daubechies (db1–db20, Symlets (sym1–sym20, and Coiflets (coif1–coif5. Using ANOVA, we determined the MWT basis functions with the most significant differences in the ability of the five scalp regions to maximize their cross-correlation with the EEG signals. The best results were obtained using “sym9” across the five scalp regions. Therefore, the most compatible MWT with the EEG signals should be selected to achieve wavelet denoising, decomposition, reconstruction, and sub-band feature extraction. This study provides a reference of the selection of efficient MWT basis functions.

Lexical mediation of phonotactic frequency effects on spoken word recognition: A Granger causality analysis of MRI-constrained MEG/EEG data.

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Gow, David W; Olson, Bruna B

2015-07-01

Phonotactic frequency effects play a crucial role in a number of debates over language processing and representation. It is unclear however, whether these effects reflect prelexical sensitivity to phonotactic frequency, or lexical "gang effects" in speech perception. In this paper, we use Granger causality analysis of MR-constrained MEG/EEG data to understand how phonotactic frequency influences neural processing dynamics during auditory lexical decision. Effective connectivity analysis showed weaker feedforward influence from brain regions involved in acoustic-phonetic processing (superior temporal gyrus) to lexical areas (supramarginal gyrus) for high phonotactic frequency words, but stronger top-down lexical influence for the same items. Low entropy nonwords (nonwords judged to closely resemble real words) showed a similar pattern of interactions between brain regions involved in lexical and acoustic-phonetic processing. These results contradict the predictions of a feedforward model of phonotactic frequency facilitation, but support the predictions of a lexically mediated account.

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

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Bleichner, Martin G.; Debener, Stefan

2017-01-01

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

Single-channel in-ear-EEG detects the focus of auditory attention to concurrent tone streams and mixed speech

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Fiedler, Lorenz; Wöstmann, Malte; Graversen, Carina; Brandmeyer, Alex; Lunner, Thomas; Obleser, Jonas

2017-06-01

Objective. Conventional, multi-channel scalp electroencephalography (EEG) allows the identification of the attended speaker in concurrent-listening (‘cocktail party’) scenarios. This implies that EEG might provide valuable information to complement hearing aids with some form of EEG and to install a level of neuro-feedback. Approach. To investigate whether a listener’s attentional focus can be detected from single-channel hearing-aid-compatible EEG configurations, we recorded EEG from three electrodes inside the ear canal (‘in-Ear-EEG’) and additionally from 64 electrodes on the scalp. In two different, concurrent listening tasks, participants (n  =  7) were fitted with individualized in-Ear-EEG pieces and were either asked to attend to one of two dichotically-presented, concurrent tone streams or to one of two diotically-presented, concurrent audiobooks. A forward encoding model was trained to predict the EEG response at single EEG channels. Main results. Each individual participants’ attentional focus could be detected from single-channel EEG response recorded from short-distance configurations consisting only of a single in-Ear-EEG electrode and an adjacent scalp-EEG electrode. The differences in neural responses to attended and ignored stimuli were consistent in morphology (i.e. polarity and latency of components) across subjects. Significance. In sum, our findings show that the EEG response from a single-channel, hearing-aid-compatible configuration provides valuable information to identify a listener’s focus of attention.

Two channel EEG thought pattern classifier.

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

2006-01-01

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

Blind Source Separation of Event-Related EEG/MEG.

Science.gov (United States)

Metsomaa, Johanna; Sarvas, Jukka; Ilmoniemi, Risto Juhani

2017-09-01

Blind source separation (BSS) can be used to decompose complex electroencephalography (EEG) or magnetoencephalography data into simpler components based on statistical assumptions without using a physical model. Applications include brain-computer interfaces, artifact removal, and identifying parallel neural processes. We wish to address the issue of applying BSS to event-related responses, which is challenging because of nonstationary data. We introduce a new BSS approach called momentary-uncorrelated component analysis (MUCA), which is tailored for event-related multitrial data. The method is based on approximate joint diagonalization of multiple covariance matrices estimated from the data at separate latencies. We further show how to extend the methodology for autocovariance matrices and how to apply BSS methods suitable for piecewise stationary data to event-related responses. We compared several BSS approaches by using simulated EEG as well as measured somatosensory and transcranial magnetic stimulation (TMS) evoked EEG. Among the compared methods, MUCA was the most tolerant one to noise, TMS artifacts, and other challenges in the data. With measured somatosensory data, over half of the estimated components were found to be similar by MUCA and independent component analysis. MUCA was also stable when tested with several input datasets. MUCA is based on simple assumptions, and the results suggest that MUCA is robust with nonideal data. Event-related responses and BSS are valuable and popular tools in neuroscience. Correctly designed BSS is an efficient way of identifying artifactual and neural processes from nonstationary event-related data.

MEG and fMRI fusion for nonlinear estimation of neural and BOLD signal changes

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Sergey M Plis

2010-11-01

Full Text Available The combined analysis of MEG/EEG and functional MRI measurements can lead to improvement in the description of the dynamical and spatial properties of brain activity. In this paper we empirically demonstrate this improvement using simulated and recorded task related MEG and fMRI activity. Neural activity estimates were derived using a dynamic Bayesian network with continuous real valued parameters by means of a sequential Monte Carlo technique. In synthetic data, we show that MEG and fMRI fusion improves estimation of the indirectly observed neural activity and smooths tracking of the BOLD response. In recordings of task related neural activity the combination of MEG and fMRI produces a result with greater SNR, that confirms the expectation arising from the nature of the experiment. The highly nonlinear model of the BOLD response poses a difficult inference problem for neural activity estimation; computational requirements are also high due to the time and space complexity. We show that joint analysis of the data improves the system's behavior by stabilizing the differential equations system and by requiring fewer computational resources.

Zoomed MRI Guided by Combined EEG/MEG Source Analysis: A Multimodal Approach for Optimizing Presurgical Epilepsy Work-up and its Application in a Multi-focal Epilepsy Patient Case Study.

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Aydin, Ü; Rampp, S; Wollbrink, A; Kugel, H; Cho, J -H; Knösche, T R; Grova, C; Wellmer, J; Wolters, C H

2017-07-01

In recent years, the use of source analysis based on electroencephalography (EEG) and magnetoencephalography (MEG) has gained considerable attention in presurgical epilepsy diagnosis. However, in many cases the source analysis alone is not used to tailor surgery unless the findings are confirmed by lesions, such as, e.g., cortical malformations in MRI. For many patients, the histology of tissue resected from MRI negative epilepsy shows small lesions, which indicates the need for more sensitive MR sequences. In this paper, we describe a technique to maximize the synergy between combined EEG/MEG (EMEG) source analysis and high resolution MRI. The procedure has three main steps: (1) construction of a detailed and calibrated finite element head model that considers the variation of individual skull conductivities and white matter anisotropy, (2) EMEG source analysis performed on averaged interictal epileptic discharges (IED), (3) high resolution (0.5 mm) zoomed MR imaging, limited to small areas centered at the EMEG source locations. The proposed new diagnosis procedure was then applied in a particularly challenging case of an epilepsy patient: EMEG analysis at the peak of the IED coincided with a right frontal focal cortical dysplasia (FCD), which had been detected at standard 1 mm resolution MRI. Of higher interest, zoomed MR imaging (applying parallel transmission, 'ZOOMit') guided by EMEG at the spike onset revealed a second, fairly subtle, FCD in the left fronto-central region. The evaluation revealed that this second FCD, which had not been detectable with standard 1 mm resolution, was the trigger of the seizures.

Spatio-temporal reconstruction of brain dynamics from EEG with a Markov prior

DEFF Research Database (Denmark)

Hansen, Sofie Therese; Hansen, Lars Kai

2016-01-01

the functional dynamics of the brain. Solving the inverse problem of EEG is however highly ill-posed as there are many more potential locations of the EEG generators than EEG measurement points. Several well-known properties of brain dynamics can be exploited to alleviate this problem. More short ranging......Electroencephalography (EEG) can capture brain dynamics in high temporal resolution. By projecting the scalp EEG signal back to its origin in the brain also high spatial resolution can be achieved. Source localized EEG therefore has potential to be a very powerful tool for understanding...

Deep Learning Approach for Automatic Classification of Ocular and Cardiac Artifacts in MEG Data

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Ahmad Hasasneh

2018-01-01

Full Text Available We propose an artifact classification scheme based on a combined deep and convolutional neural network (DCNN model, to automatically identify cardiac and ocular artifacts from neuromagnetic data, without the need for additional electrocardiogram (ECG and electrooculogram (EOG recordings. From independent components, the model uses both the spatial and temporal information of the decomposed magnetoencephalography (MEG data. In total, 7122 samples were used after data augmentation, in which task and nontask related MEG recordings from 48 subjects served as the database for this study. Artifact rejection was applied using the combined model, which achieved a sensitivity and specificity of 91.8% and 97.4%, respectively. The overall accuracy of the model was validated using a cross-validation test and revealed a median accuracy of 94.4%, indicating high reliability of the DCNN-based artifact removal in task and nontask related MEG experiments. The major advantages of the proposed method are as follows: (1 it is a fully automated and user independent workflow of artifact classification in MEG data; (2 once the model is trained there is no need for auxiliary signal recordings; (3 the flexibility in the model design and training allows for various modalities (MEG/EEG and various sensor types.

Self-Adhesive and Capacitive Carbon Nanotube-Based Electrode to Record Electroencephalograph Signals From the Hairy Scalp.

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Lee, Seung Min; Kim, Jeong Hun; Park, Cheolsoo; Hwang, Ji-Young; Hong, Joung Sook; Lee, Kwang Ho; Lee, Sang Hoon

2016-01-01

We fabricated a carbon nanotube (CNT)/adhesive polydimethylsiloxane (aPDMS) composite-based dry electroencephalograph (EEG) electrode for capacitive measuring of EEG signals. As research related to brain-computer interface applications has advanced, the presence of hairs on a patient's scalp has continued to present an obstacle to recorder EEG signals using dry electrodes. The CNT/aPDMS electrode developed here is elastic, highly conductive, self-adhesive, and capable of making conformal contact with and attaching to a hairy scalp. Onto the conductive disk, hundreds of conductive pillars coated with Parylene C insulation layer were fabricated. A CNT/aPDMS layer was attached on the disk to transmit biosignals to the pillar. The top of disk was designed to be solderable, which enables the electrode to connect with a variety of commercial EEG acquisition systems. The mechanical and electrical characteristics of the electrode were tested, and the performances of the electrodes were evaluated by recording EEGs, including alpha rhythms, auditory-evoked potentials, and steady-state visually-evoked potentials. The results revealed that the electrode provided a high signal-to-noise ratio with good tolerance for motion. Almost no leakage current was observed. Although preamplifiers with ultrahigh input impedance have been essential for previous capacitive electrodes, the EEGs were recorded here by directly connecting a commercially available EEG acquisition system to the electrode to yield high-quality signals comparable to those obtained using conventional wet electrodes.

EEG Based Inference of Spatio-Temporal Brain Dynamics

DEFF Research Database (Denmark)

Hansen, Sofie Therese

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

A statistically robust EEG re-referencing procedure to mitigate reference effect

OpenAIRE

Lepage, Kyle Q.; Kramer, Mark A.; Chu, Catherine J.

2014-01-01

Background: The electroencephalogram (EEG) remains the primary tool for diagnosis of abnormal brain activity in clinical neurology and for in vivo recordings of human neurophysiology in neuroscience research. In EEG data acquisition, voltage is measured at positions on the scalp with respect to a reference electrode. When this reference electrode responds to electrical activity or artifact all electrodes are affected. Successful analysis of EEG data often involves re-referencing procedures th...

EEG, PET, SPET and MRI in intractable childhood epilepsies: possible surgical correlations.

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Fois, A; Farnetani, M A; Balestri, P; Buoni, S; Di Cosmo, G; Vattimo, A; Guazzelli, M; Guzzardi, R; Salvadori, P A

1995-12-01

Magnetic resonance imaging (MRI), single photon emission tomography (SPET), and positron emission tomography (PET) using [18F]fluorodeoxyglucose were used in combination with scalp and scalp-video EEGs in a group of 30 pediatric patients with drug resistant epilepsy (DRE) in order to identify patients who could benefit from neurosurgical approach. Seizures were classified according to the consensus criteria of The International League Against Epilepsy. In three patients infantile spasms (IS) were diagnosed; 13 subjects were affected by different types of generalized seizures, associated with complex partial seizures (CPS) in three. In the other 14 patients partial seizures, either simple (SPS) or complex, were present. A localized abnormality was demonstrated in one patient with IS and in three patients with generalized seizures. Of the group of 14 subjects with CPS, MRI and CT were normal in 7, but SPET or PET indicated focal hypoperfusion or hypometabolism concordant with the localization of the EEG abnormalities. In 5 of the other 7 patients anatomical and functional imaging and EEG findings were concordant for a localized abnormality. It can be concluded that functional imaging combined with scalp EEGs appears to be superior to the use of only CT and MRI for selecting children with epilepsy in whom a surgical approach can be considered, in particular when CPS resistant to therapy are present.

Study on non-linear bistable dynamics model based EEG signal discrimination analysis method.

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Ying, Xiaoguo; Lin, Han; Hui, Guohua

2015-01-01

Electroencephalogram (EEG) is the recording of electrical activity along the scalp. EEG measures voltage fluctuations generating from ionic current flows within the neurons of the brain. EEG signal is looked as one of the most important factors that will be focused in the next 20 years. In this paper, EEG signal discrimination based on non-linear bistable dynamical model was proposed. EEG signals were processed by non-linear bistable dynamical model, and features of EEG signals were characterized by coherence index. Experimental results showed that the proposed method could properly extract the features of different EEG signals.

Extended seizure detection algorithm for intracranial EEG recordings

DEFF Research Database (Denmark)

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

2010-01-01

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

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

Directory of Open Access Journals (Sweden)

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.

The standardized EEG electrode array of the IFCN.

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Seeck, Margitta; Koessler, Laurent; Bast, Thomas; Leijten, Frans; Michel, Christoph; Baumgartner, Christoph; He, Bin; Beniczky, Sándor

2017-10-01

Standardized EEG electrode positions are essential for both clinical applications and research. The aim of this guideline is to update and expand the unifying nomenclature and standardized positioning for EEG scalp electrodes. Electrode positions were based on 20% and 10% of standardized measurements from anatomical landmarks on the skull. However, standard recordings do not cover the anterior and basal temporal lobes, which is the most frequent source of epileptogenic activity. Here, we propose a basic array of 25 electrodes including the inferior temporal chain, which should be used for all standard clinical recordings. The nomenclature in the basic array is consistent with the 10-10-system. High-density scalp EEG arrays (64-256 electrodes) allow source imaging with even sub-lobar precision. This supplementary exam should be requested whenever necessary, e.g. search for epileptogenic activity in negative standard EEG or for presurgical evaluation. In the near future, nomenclature for high density electrodes arrays beyond the 10-10 system needs to be defined, to allow comparison and standardized recordings across centers. Contrary to the established belief that smaller heads needs less electrodes, in young children at least as many electrodes as in adults should be applied due to smaller skull thickness and the risk of spatial aliasing. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

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

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

2017-09-01

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

Sparse Source EEG Imaging with the Variational Garrote

DEFF Research Database (Denmark)

Hansen, Sofie Therese; Stahlhut, Carsten; Hansen, Lars Kai

2013-01-01

EEG imaging, the estimation of the cortical source distribution from scalp electrode measurements, poses an extremely ill-posed inverse problem. Recent work by Delorme et al. (2012) supports the hypothesis that distributed source solutions are sparse. We show that direct search for sparse solutions...

Linking EEG signals, brain functions and mental operations: Advantages of the Laplacian transformation.

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Vidal, Franck; Burle, Boris; Spieser, Laure; Carbonnell, Laurence; Meckler, Cédric; Casini, Laurence; Hasbroucq, Thierry

2015-09-01

Electroencephalography (EEG) is a very popular technique for investigating brain functions and/or mental processes. To this aim, EEG activities must be interpreted in terms of brain and/or mental processes. EEG signals being a direct manifestation of neuronal activity it is often assumed that such interpretations are quite obvious or, at least, straightforward. However, they often rely on (explicit or even implicit) assumptions regarding the structures supposed to generate the EEG activities of interest. For these assumptions to be used appropriately, reliable links between EEG activities and the underlying brain structures must be established. Because of volume conduction effects and the mixture of activities they induce, these links are difficult to establish with scalp potential recordings. We present different examples showing how the Laplacian transformation, acting as an efficient source separation method, allowed to establish more reliable links between EEG activities and brain generators and, ultimately, with mental operations. The nature of those links depends on the depth of inferences that can vary from weak to strong. Along this continuum, we show that 1) while the effects of experimental manipulation can appear widely distributed with scalp potentials, Laplacian transformation allows to reveal several generators contributing (in different manners) to these modulations, 2) amplitude variations within the same set of generators can generate spurious differences in scalp potential topographies, often interpreted as reflecting different source configurations. In such a case, Laplacian transformation provides much more similar topographies, evidencing the same generator(s) set, and 3) using the LRP as an index of response activation most often produces ambiguous results, Laplacian-transformed response-locked ERPs obtained over motor areas allow resolving these ambiguities. Copyright © 2015 Elsevier B.V. All rights reserved.

Probabilistic M/EEG source imaging from sparse spatio-temporal event structure

DEFF Research Database (Denmark)

Stahlhut, Carsten; Attias, Hagai T.; Wipf, David

While MEG and EEG source imaging methods have to tackle a severely ill-posed problem their success can be stated as their ability to constrain the solutions using appropriate priors. In this paper we propose a hierarchical Bayesian model facilitating spatio-temporal patterns through the use of bo...

Generator localization by current source density (CSD): Implications of volume conduction and field closure at intracranial and scalp resolutions

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Tenke, Craig E.; Kayser, Jürgen

2012-01-01

The topographic ambiguity and reference-dependency that has plagued EEG/ERP research throughout its history are largely attributable to volume conduction, which may be concisely described by a vector form of Ohm’s Law. This biophysical relationship is common to popular algorithms that infer neuronal generators via inverse solutions. It may be further simplified as Poisson’s source equation, which identifies underlying current generators from estimates of the second spatial derivative of the field potential (Laplacian transformation). Intracranial current source density (CSD) studies have dissected the “cortical dipole” into intracortical sources and sinks, corresponding to physiologically-meaningful patterns of neuronal activity at a sublaminar resolution, much of which is locally cancelled (i.e., closed field). By virtue of the macroscopic scale of the scalp-recorded EEG, a surface Laplacian reflects the radial projections of these underlying currents, representing a unique, unambiguous measure of neuronal activity at scalp. Although the surface Laplacian requires minimal assumptions compared to complex, model-sensitive inverses, the resulting waveform topographies faithfully summarize and simplify essential constraints that must be placed on putative generators of a scalp potential topography, even if they arise from deep or partially-closed fields. CSD methods thereby provide a global empirical and biophysical context for generator localization, spanning scales from intracortical to scalp recordings. PMID:22796039

Crisis del lóbulo temporal registrada mediante magnetoencefalografía: caso clínico Temporal lobe seizure recorded by magnetoencephalography: case report

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Carlos Amo

2004-09-01

Full Text Available La localización del inicio de las crisis es un factor importante para la evaluación prequirúrgica de la epilepsia. En este trabajo se describe la localización del inicio de una crisis registrada mediante magnetoencefalografía (MEG en un niño de 12 años que presenta crisis parciales complejas farmacorresistentes. La RM muestra una lesión de 20mm de diámetro en el hipocampo izquierdo. EEG de superficie con ondas theta temporales izquierdas. Registro MEG interictal con punta-onda aislada posterior e inferior a la lesión de la RM. Registro MEG ictal con punta-onda (2 Hz. La localización de los dipolos indica el inicio de la crisis en la circunvolución temporal inferior en la misma localización que la actividad interictal MEG. Esta actividad ictal se propaga bilateralmente a áreas frontales. El registro corticográfico intraquirúrgico confirma los resultados de la localización interictal mediante MEG.Ictal onset localization is a important factor in presurgical evaluation of epilepsy. This paper describes the localization of a seizure onset recorded by magnetoencephalography (MEG from a 12-year-old male patient who suffered from complex partial drug-resistant seizures. MRI revealed a 20mm diameter lesion located in left hippocampus. Scalp EEG showed left temporal theta waves. Interictal MEG registrations detected isolated spike-wave activity posterior and inferior to the MRI lesion. Ictal MEG showed continuous spike-wave activity (2 Hz. Dipole localization sited seizure onset in the inferior left temporal gyrus, the same localization of the interictal MEG activity. This ictal activity spreads bilaterally to frontal areas. Intrasurgical electrocorticography recording confirmed interictal MEG results.

Determination of head conductivity frequency response in vivo with optimized EIT-EEG.

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Dabek, Juhani; Kalogianni, Konstantina; Rotgans, Edwin; van der Helm, Frans C T; Kwakkel, Gert; van Wegen, Erwin E H; Daffertshofer, Andreas; de Munck, Jan C

2016-02-15

Electroencephalography (EEG) benefits from accurate head models. Dipole source modelling errors can be reduced from over 1cm to a few millimetres by replacing generic head geometry and conductivity with tailored ones. When adequate head geometry is available, electrical impedance tomography (EIT) can be used to infer the conductivities of head tissues. In this study, the boundary element method (BEM) is applied with three-compartment (scalp, skull and brain) subject-specific head models. The optimal injection of small currents to the head with a modular EIT current injector, and voltage measurement by an EEG amplifier is first sought by simulations. The measurement with a 64-electrode EEG layout is studied with respect to three noise sources affecting EIT: background EEG, deviations from the fitting assumption of equal scalp and brain conductivities, and smooth model geometry deviations from the true head geometry. The noise source effects were investigated depending on the positioning of the injection and extraction electrode and the number of their combinations used sequentially. The deviation from equal scalp and brain conductivities produces rather deterministic errors in the three conductivities irrespective of the current injection locations. With a realistic measurement of around 2 min and around 8 distant distinct current injection pairs, the error from the other noise sources is reduced to around 10% or less in the skull conductivity. The analysis of subsequent real measurements, however, suggests that there could be subject-specific local thinnings in the skull, which could amplify the conductivity fitting errors. With proper analysis of multiplexed sinusoidal EIT current injections, the measurements on average yielded conductivities of 340 mS/m (scalp and brain) and 6.6 mS/m (skull) at 2 Hz. From 11 to 127 Hz, the conductivities increased by 1.6% (scalp and brain) and 6.7% (skull) on the average. The proper analysis was ensured by using recombination of

Topographical characteristics and principal component structure of the hypnagogic EEG.

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Tanaka, H; Hayashi, M; Hori, T

1997-07-01

The purpose of the present study was to identify the dominant topographic components of electroencephalographs (EEG) and their behavior during the waking-sleeping transition period. Somnography of nocturnal sleep was recorded on 10 male subjects. Each recording, from "lights-off" to 5 minutes after the appearance of the first sleep spindle, was analyzed. The typical EEG patterns during hypnagogic period were classified into nine EEG stages. Topographic maps demonstrated that the dominant areas of alpha-band activity moved from the posterior areas to anterior areas along the midline of the scalp. In delta-, theta-, and sigma-band activities, the differences of EEG amplitude between the focus areas (the dominant areas) and the surrounding areas increased as a function of EEG stage. To identify the dominant topographic components, a principal component analysis was carried out on a 12-channel EEG data set for each of six frequency bands. The dominant areas of alpha 2- (9.6-11.4 Hz) and alpha 3- (11.6-13.4 Hz) band activities moved from the posterior to anterior areas, respectively. The distribution of alpha 2-band activity on the scalp clearly changed just after EEG stage 3 (alpha intermittent, < 50%). On the other hand, alpha 3-band activity became dominant in anterior areas after the appearance of vertex sharp-wave bursts (EEG stage 7). For the sigma band, the amplitude of extensive areas from the frontal pole to the parietal showed a rapid rise after the onset of stage 7 (the appearance of vertex sharp-wave bursts). Based on the results, sleep onset process probably started before the onset of sleep stage 1 in standard criteria. On the other hand, the basic sleep process may start before the onset of sleep stage 2 or the manually scored spindles.

MEG and EEG data analysis with MNE-Python

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Alexandre eGramfort

2013-12-01

Full Text Available Magnetoencephalography and electroencephalography (M/EEG measure the weakelectromagnetic signals generated by neuronal activity in the brain. Using thesesignals to characterize and locate neural activation in the brain is achallenge that requires expertise in physics, signalprocessing, statistics, and numerical methods. As part of the MNE softwaresuite, MNE-Python is an open-sourcesoftware package that addresses this challenge by providingstate-of-the-art algorithms implemented in Python that cover multiple methods of data preprocessing, source localization, statistical analysis, and estimation offunctional connectivity between distributed brain regions.All algorithms and utility functions are implemented in a consistent manner with well-documented interfaces, enabling users to create M/EEG data analysispipelines by writing Python scripts.Moreover, MNE-Python is tightly integrated with the core Python libraries for scientificcomptutation (Numpy, Scipy and visualization (matplotlib and Mayavi, as wellas the greater neuroimaging ecosystem in Python via the Nibabel package. The code is provided under the new BSD licenseallowing code reuse, even in commercial products. Although MNE-Python has onlybeen under heavy development for a couple of years, it has rapidly evolved withexpanded analysis capabilities and pedagogical tutorials because multiple labs have collaborated during code development to help share best practices.MNE-Python also gives easy access to preprocessed datasets,helping users to get started quickly and facilitating reproducibility ofmethods by other researchers. Full documentation, including dozens ofexamples, is available at http://martinos.org/mne.

Frontal midline theta rhythm and gamma power changes during focused attention on mental calculation: an MEG beamformer analysis

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Ryouhei eIshii

2014-06-01

Full Text Available Frontal midline theta rhythm (Fmθ appears widely distributed over medial prefrontal areas in EEG recordings, indicating focused attention. Although mental calculation is often used as an attention-demanding task, little has been reported on calculation-related activation in Fmθ experiments. In this study we used spatially filtered MEG and permutation analysis to precisely localize cortical generators of the magnetic counterpart of Fmθ, as well as other sources of oscillatory activity associated with mental calculation processing (i.e., arithmetic subtraction. Our results confirmed and extended earlier EEG/MEG studies indicating that Fmθ during mental calculation is generated in the dorsal anterior cingulate and adjacent medial prefrontal cortex. Mental subtraction was also associated with gamma event-related synchronization, as an index of activation, in right parietal regions subserving basic numerical processing and number-based spatial attention. Gamma event-related desynchronization appeared in the right lateral prefrontal cortex, likely representing a mechanism to interrupt neural activity that can interfere with the ongoing cognitive task.

[MEG]PLS: A pipeline for MEG data analysis and partial least squares statistics.

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Cheung, Michael J; Kovačević, Natasa; Fatima, Zainab; Mišić, Bratislav; McIntosh, Anthony R

2016-01-01

The emphasis of modern neurobiological theories has recently shifted from the independent function of brain areas to their interactions in the context of whole-brain networks. As a result, neuroimaging methods and analyses have also increasingly focused on network discovery. Magnetoencephalography (MEG) is a neuroimaging modality that captures neural activity with a high degree of temporal specificity, providing detailed, time varying maps of neural activity. Partial least squares (PLS) analysis is a multivariate framework that can be used to isolate distributed spatiotemporal patterns of neural activity that differentiate groups or cognitive tasks, to relate neural activity to behavior, and to capture large-scale network interactions. Here we introduce [MEG]PLS, a MATLAB-based platform that streamlines MEG data preprocessing, source reconstruction and PLS analysis in a single unified framework. [MEG]PLS facilitates MRI preprocessing, including segmentation and coregistration, MEG preprocessing, including filtering, epoching, and artifact correction, MEG sensor analysis, in both time and frequency domains, MEG source analysis, including multiple head models and beamforming algorithms, and combines these with a suite of PLS analyses. The pipeline is open-source and modular, utilizing functions from FieldTrip (Donders, NL), AFNI (NIMH, USA), SPM8 (UCL, UK) and PLScmd (Baycrest, CAN), which are extensively supported and continually developed by their respective communities. [MEG]PLS is flexible, providing both a graphical user interface and command-line options, depending on the needs of the user. A visualization suite allows multiple types of data and analyses to be displayed and includes 4-D montage functionality. [MEG]PLS is freely available under the GNU public license (http://meg-pls.weebly.com). Copyright © 2015 Elsevier Inc. All rights reserved.

MEG and EEG data analysis with MNE-Python.

Science.gov (United States)

Gramfort, Alexandre; Luessi, Martin; Larson, Eric; Engemann, Denis A; Strohmeier, Daniel; Brodbeck, Christian; Goj, Roman; Jas, Mainak; Brooks, Teon; Parkkonen, Lauri; Hämäläinen, Matti

2013-12-26

Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals generated by neuronal activity in the brain. Using these signals to characterize and locate neural activation in the brain is a challenge that requires expertise in physics, signal processing, statistics, and numerical methods. As part of the MNE software suite, MNE-Python is an open-source software package that addresses this challenge by providing state-of-the-art algorithms implemented in Python that cover multiple methods of data preprocessing, source localization, statistical analysis, and estimation of functional connectivity between distributed brain regions. All algorithms and utility functions are implemented in a consistent manner with well-documented interfaces, enabling users to create M/EEG data analysis pipelines by writing Python scripts. Moreover, MNE-Python is tightly integrated with the core Python libraries for scientific comptutation (NumPy, SciPy) and visualization (matplotlib and Mayavi), as well as the greater neuroimaging ecosystem in Python via the Nibabel package. The code is provided under the new BSD license allowing code reuse, even in commercial products. Although MNE-Python has only been under heavy development for a couple of years, it has rapidly evolved with expanded analysis capabilities and pedagogical tutorials because multiple labs have collaborated during code development to help share best practices. MNE-Python also gives easy access to preprocessed datasets, helping users to get started quickly and facilitating reproducibility of methods by other researchers. Full documentation, including dozens of examples, is available at http://martinos.org/mne.

Ethanol modulates cortical activity: direct evidence with combined TMS and EEG.

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Kähkönen, S; Kesäniemi, M; Nikouline, V V; Karhu, J; Ollikainen, M; Holi, M; Ilmoniemi, R J

2001-08-01

The motor cortex of 10 healthy subjects was stimulated by transcranial magnetic stimulation (TMS) before and after ethanol challenge (0.8 g/kg resulting in blood concentration of 0.77 +/- 0.14 ml/liter). The electrical brain activity resulting from the brief electromagnetic pulse was recorded with high-resolution electroencephalography (EEG) and located using inversion algorithms. Focal magnetic pulses to the left motor cortex were delivered with a figure-of-eight coil at the random interstimulus interval of 1.5-2.5 s. The stimulation intensity was adjusted to the motor threshold of abductor digiti minimi. Two conditions before and after ethanol ingestion (30 min) were applied: (1) real TMS, with the coil pressed against the scalp; and (2) control condition, with the coil separated from the scalp by a 2-cm-thick piece of plastic. A separate EMG control recording of one subject during TMS was made with two bipolar platinum needle electrodes inserted to the left temporal muscle. In each condition, 120 pulses were delivered. The EEG was recorded from 60 scalp electrodes. A peak in the EEG signals was observed at 43 ms after the TMS pulse in the real-TMS condition but not in the control condition or in the control scalp EMG. Potential maps before and after ethanol ingestion were significantly different from each other (P = 0.01), but no differences were found in the control condition. Ethanol changed the TMS-evoked potentials over right frontal and left parietal areas, the underlying effect appearing to be largest in the right prefrontal area. Our findings suggest that ethanol may have changed the functional connectivity between prefrontal and motor cortices. This new noninvasive method provides direct evidence about the modulation of cortical connectivity after ethanol challenge. Copyright 2001 Academic Press.

Solving the forward problem in EEG source analysis by spherical and fdm head modeling: a comparative analysis - biomed 2009

NARCIS (Netherlands)

Vatta, F.; Meneghini, F.; Esposito, F.; Mininel, S.; Di Salle, F.

2009-01-01

Neural source localization techniques based on electroencephalography (EEG) use scalp potential data to infer the location of underlying neural activity. This procedure entails modeling the sources of EEG activity and modeling the head volume conduction process to link the modeled sources to the

Only low frequency event-related EEG activity is compromised in multiple sclerosis: insights from an independent component clustering analysis.

Directory of Open Access Journals (Sweden)

Hanni Kiiski

Full Text Available Cognitive impairment (CI, often examined with neuropsychological tests such as the Paced Auditory Serial Addition Test (PASAT, affects approximately 65% of multiple sclerosis (MS patients. The P3b event-related potential (ERP, evoked when an infrequent target stimulus is presented, indexes cognitive function and is typically compared across subjects' scalp electroencephalography (EEG data. However, the clustering of independent components (ICs is superior to scalp-based EEG methods because it can accommodate the spatiotemporal overlap inherent in scalp EEG data. Event-related spectral perturbations (ERSPs; event-related mean power spectral changes and inter-trial coherence (ITCs; event-related consistency of spectral phase reveal a more comprehensive overview of EEG activity. Ninety-five subjects (56 MS patients, 39 controls completed visual and auditory two-stimulus P3b event-related potential tasks and the PASAT. MS patients were also divided into CI and non-CI groups (n = 18 in each based on PASAT scores. Data were recorded from 128-scalp EEG channels and 4 IC clusters in the visual, and 5 IC clusters in the auditory, modality were identified. In general, MS patients had significantly reduced ERSP theta power versus controls, and a similar pattern was observed for CI vs. non-CI MS patients. The ITC measures were also significantly different in the theta band for some clusters. The finding that MS patients had reduced P3b task-related theta power in both modalities is a reflection of compromised connectivity, likely due to demyelination, that may have disrupted early processes essential to P3b generation, such as orientating and signal detection. However, for posterior sources, MS patients had a greater decrease in alpha power, normally associated with enhanced cognitive function, which may reflect a compensatory mechanism in response to the compromised early cognitive processing.

Changes in the MEG background activity in patients with positive symptoms of schizophrenia: spectral analysis and impact of age

International Nuclear Information System (INIS)

Escudero, Javier; Ifeachor, Emmanuel; Fernández, Alberto; López-Ibor, Juan José; Hornero, Roberto

2013-01-01

The frequency spectrum of the magnetoencephalogram (MEG) background activity was analysed in 15 schizophrenia (SCH) patients with predominant positive symptoms and 17 age-matched healthy control subjects using the following variables: median frequency (MF), spectral entropy (SpecEn) and relative power in delta (RPδ), theta (RPθ), lower alpha (RPα1), upper alpha (RPα2), beta (RPβ) and gamma (RPγ) bands. We found significant differences between the two subject groups in the average level of MF and RPγ in some regions of the scalp. Additionally, the MF, SpecEn, RPβ and RPγ values of SCH patients with positive symptoms had a different dependence on age as compared with the results of control subjects, suggesting that SCH affects the way in which the brain activity evolves with age. Moreover, we also classified the MEG signals by means of a cross-validated feature selection process followed by a logistic regression. The subjects were classified with 71.3% accuracy and an area under the ROC curve of 0.741. Thus, the spectral and classification analysis of the MEG in SCH may provide insights into how this condition affects the brain activity and may help in its early detection. (paper)

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

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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%.

Cognitive inhibition of number/length interference in a Piaget-like task: evidence by combining ERP and MEG.

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Joliot, Marc; Leroux, Gaëlle; Dubal, Stéphanie; Tzourio-Mazoyer, Nathalie; Houdé, Olivier; Mazoyer, Bernard; Petit, Laurent

2009-08-01

We combined event-related potential (ERP) and magnetoencephalography (MEG) acquisition and analysis to investigate the electrophysiological markers of the inhibitory processes involved in the number/length interference in a Piaget-like numerical task. Eleven healthy subjects performed four gradually interfering conditions with the heuristic "length equals number" to be inhibited. Low resolution tomography reconstruction was performed on the combined grand averaged electromagnetic data at the early (N1, P1) and late (P2, N2, P3(early) and P3(late)) latencies. Every condition was analyzed at both scalp and regional brain levels. The inhibitory processes were visible on the late components of the electromagnetic brain activity. A right P2-related frontal orbital activation reflected the change of strategy in the inhibitory processes. N2-related SMA/cingulate activation revealed the first occurrence of the stimuli processing to be inhibited. Both P3 components revealed the working memory processes operating in a medial temporal complex and the mental imagery processes subtended by the precuneus. Simultaneous ERP and MEG signal acquisition and analysis allowed to describe the spatiotemporal patterns of neural networks involved in the inhibition of the "length equals number" interference. Combining ERP and MEG ensured a sensitivity which could be reached previously only through invasive intracortical recordings.

MEG-compatible pneumatic stimulator to elicit passive finger and toe movements.

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Piitulainen, Harri; Bourguignon, Mathieu; Hari, Riitta; Jousmäki, Veikko

2015-05-15

Magnetoencephalographic (MEG) signals recorded from the primary sensorimotor (SM1) cortex are coherent with kinematics of both active and passive finger movements. The coherence mainly reflects movement-related proprioceptive afference to the cortex. Here we describe a novel MEG-compatible stimulator to generate computer-controlled passive finger and toe movements that can be used as stimuli in functional brain-imaging experiments. The movements are produced by pneumatic artificial muscle (PAM), elastic actuator that shortens with increasing air pressure. To test the applicability of the stimulator to functional brain-imaging, 4-min trains of passive repetitive 5-mm flexion-extension movements of the right and left index finger and the right hallux were produced at 3Hz while the subject's brain activity was measured with whole-scalp MEG and finger or toe kinematics with an accelerometer. In all ten subjects studied, statistically significant coherence (up to 0.78) occurred between the accelerometer and MEG signals at the movement frequency or its first harmonic. Sources of coherent activity were in the contralateral hand or foot SM1 cortices. Movement-evoked fields elicited with intermittent movements of the right index finger (once every 3.2-4.0s; mean±SD peak response latency 88±25ms) were co-located with the respective coherent sources. We further moved the right index finger at 3, 6, and 12Hz (movement ranges 5, 3, and 2mm, respectively), and analyzed the first 1, 2, and 4-min epochs of data. One minute of data was sufficient to locate the left hand area of the SM1 cortex at all movement frequencies. Sound-induced spurious coherence was reliably ruled out in a control experiment. Our novel movement stimulator thus provides a robust and reliable tool to track proprioceptive afference to the cortex and to locate the SM1 cortex. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

A semi-automated method for rapid detection of ripple events on interictal voltage discharges in the scalp electroencephalogram.

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Chu, Catherine J; Chan, Arthur; Song, Dan; Staley, Kevin J; Stufflebeam, Steven M; Kramer, Mark A

2017-02-01

High frequency oscillations are emerging as a clinically important indicator of epileptic networks. However, manual detection of these high frequency oscillations is difficult, time consuming, and subjective, especially in the scalp EEG, thus hindering further clinical exploration and application. Semi-automated detection methods augment manual detection by reducing inspection to a subset of time intervals. We propose a new method to detect high frequency oscillations that co-occur with interictal epileptiform discharges. The new method proceeds in two steps. The first step identifies candidate time intervals during which high frequency activity is increased. The second step computes a set of seven features for each candidate interval. These features require that the candidate event contain a high frequency oscillation approximately sinusoidal in shape, with at least three cycles, that co-occurs with a large amplitude discharge. Candidate events that satisfy these features are stored for validation through visual analysis. We evaluate the detector performance in simulation and on ten examples of scalp EEG data, and show that the proposed method successfully detects spike-ripple events, with high positive predictive value, low false positive rate, and high intra-rater reliability. The proposed method is less sensitive than the existing method of visual inspection, but much faster and much more reliable. Accurate and rapid detection of high frequency activity increases the clinical viability of this rhythmic biomarker of epilepsy. The proposed spike-ripple detector rapidly identifies candidate spike-ripple events, thus making clinical analysis of prolonged, multielectrode scalp EEG recordings tractable. Copyright © 2016 Elsevier B.V. All rights reserved.

The diagnostic value of clinical EEG in detecting abnormal synchronicity in panic disorder.

Science.gov (United States)

Adamaszek, Michael; Olbrich, Sebastian; Gallinat, Jürgen

2011-07-01

Electroencephalographic (EEG) findings repeatedly reported abnormal synchronous or even epileptiform discharges in panic disorder. Although less frequently occurring in patients with panic disorder, these deviant EEG features during panic attacks were also observed in intracranial EEG. For this purpose, our article reviews the consideration of abnormal synchronous neuronal activity in different neurocircuits, particularly limbic, as a suggested condition of panic attacks. Therapeutic approaches of anticonvulsants have shown reductions of symptoms and frequency of attacks in numerous patients suffering from panic disorder, supporting the presumption of underlying abnormal synchronous neuronal activity. Thus, scalp EEG recordings are still recommended for discovering indications of abnormal synchronous neuronal activity in panic patients.

Epileptogenic zone localization using magnetoencephalography predicts seizure freedom in epilepsy surgery

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Englot, Dario J.; Nagarajan, Srikantan S.; Imber, Brandon S.; Raygor, Kunal P.; Honma, Susanne M.; Mizuiri, Danielle; Mantle, Mary; Knowlton, Robert C.; Kirsch, Heidi E.; Chang, Edward F.

2015-01-01

Objective The efficacy of epilepsy surgery depends critically upon successful localization of the epileptogenic zone. Magnetoencephalography (MEG) enables non-invasive detection of interictal spike activity in epilepsy, which can then be localized in three dimensions using magnetic source imaging (MSI) techniques. However, the clinical value of MEG in the pre-surgical epilepsy evaluation is not fully understood, as studies to date are limited by either a lack of long-term seizure outcomes or small sample size. Methods We performed a retrospective cohort study of focal epilepsy patients who received MEG for interictal spike mapping followed by surgical resection at our institution. Results We studied 132 surgical patients, with mean post-operative follow-up of 3.6 years (minimum 1 year). Dipole source modelling was successful in 103 (78%) patients, while no interictal spikes were seen in others. Among patients with successful dipole modelling, MEG findings were concordant with and specific to: i) the region of resection in 66% of patients, ii) invasive electrocorticography (ECoG) findings in 67% of individuals, and iii) the MRI abnormality in 74% of cases. MEG showed discordant lateralization in ~5% of cases. After surgery, 70% of all patients achieved seizure-freedom (Engel class I outcome). Whereas 85% of patients with concordant and specific MEG findings became seizure-free, this outcome was achieved by only 37% of individuals with MEG findings that were non-specific or discordant with the region of resection (χ2 = 26.4, p < 0.001). MEG reliability was comparable in patients with or without localized scalp EEG, and overall, localizing MEG findings predicted seizure freedom with an odds ratio of 5.11 (2.23–11.8, 95% CI). Significance MEG is a valuable tool for non-invasive interictal spike mapping in epilepsy surgery, including patients with non-localized findings on long-term EEG monitoring, and localization of the epileptogenic zone using MEG is associated

Convolutional neural networks for seizure prediction using intracranial and scalp electroencephalogram.

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Truong, Nhan Duy; Nguyen, Anh Duy; Kuhlmann, Levin; Bonyadi, Mohammad Reza; Yang, Jiawei; Ippolito, Samuel; Kavehei, Omid

2018-05-07

Seizure prediction has attracted growing attention as one of the most challenging predictive data analysis efforts to improve the life of patients with drug-resistant epilepsy and tonic seizures. Many outstanding studies have reported great results in providing sensible indirect (warning systems) or direct (interactive neural stimulation) control over refractory seizures, some of which achieved high performance. However, to achieve high sensitivity and a low false prediction rate, many of these studies relied on handcraft feature extraction and/or tailored feature extraction, which is performed for each patient independently. This approach, however, is not generalizable, and requires significant modifications for each new patient within a new dataset. In this article, we apply convolutional neural networks to different intracranial and scalp electroencephalogram (EEG) datasets and propose a generalized retrospective and patient-specific seizure prediction method. We use the short-time Fourier transform on 30-s EEG windows to extract information in both the frequency domain and the time domain. The algorithm automatically generates optimized features for each patient to best classify preictal and interictal segments. The method can be applied to any other patient from any dataset without the need for manual feature extraction. The proposed approach achieves sensitivity of 81.4%, 81.2%, and 75% and a false prediction rate of 0.06/h, 0.16/h, and 0.21/h on the Freiburg Hospital intracranial EEG dataset, the Boston Children's Hospital-MIT scalp EEG dataset, and the American Epilepsy Society Seizure Prediction Challenge dataset, respectively. Our prediction method is also statistically better than an unspecific random predictor for most of the patients in all three datasets. Copyright © 2018 Elsevier Ltd. All rights reserved.

ReliefF-Based EEG Sensor Selection Methods for Emotion Recognition.

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Zhang, Jianhai; Chen, Ming; Zhao, Shaokai; Hu, Sanqing; Shi, Zhiguo; Cao, Yu

2016-09-22

Electroencephalogram (EEG) signals recorded from sensor electrodes on the scalp can directly detect the brain dynamics in response to different emotional states. Emotion recognition from EEG signals has attracted broad attention, partly due to the rapid development of wearable computing and the needs of a more immersive human-computer interface (HCI) environment. To improve the recognition performance, multi-channel EEG signals are usually used. A large set of EEG sensor channels will add to the computational complexity and cause users inconvenience. ReliefF-based channel selection methods were systematically investigated for EEG-based emotion recognition on a database for emotion analysis using physiological signals (DEAP). Three strategies were employed to select the best channels in classifying four emotional states (joy, fear, sadness and relaxation). Furthermore, support vector machine (SVM) was used as a classifier to validate the performance of the channel selection results. The experimental results showed the effectiveness of our methods and the comparison with the similar strategies, based on the F-score, was given. Strategies to evaluate a channel as a unity gave better performance in channel reduction with an acceptable loss of accuracy. In the third strategy, after adjusting channels' weights according to their contribution to the classification accuracy, the number of channels was reduced to eight with a slight loss of accuracy (58.51% ± 10.05% versus the best classification accuracy 59.13% ± 11.00% using 19 channels). In addition, the study of selecting subject-independent channels, related to emotion processing, was also implemented. The sensors, selected subject-independently from frontal, parietal lobes, have been identified to provide more discriminative information associated with emotion processing, and are distributed symmetrically over the scalp, which is consistent with the existing literature. The results will make a contribution to the

ReliefF-Based EEG Sensor Selection Methods for Emotion Recognition

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Jianhai Zhang

2016-09-01

Full Text Available Electroencephalogram (EEG signals recorded from sensor electrodes on the scalp can directly detect the brain dynamics in response to different emotional states. Emotion recognition from EEG signals has attracted broad attention, partly due to the rapid development of wearable computing and the needs of a more immersive human-computer interface (HCI environment. To improve the recognition performance, multi-channel EEG signals are usually used. A large set of EEG sensor channels will add to the computational complexity and cause users inconvenience. ReliefF-based channel selection methods were systematically investigated for EEG-based emotion recognition on a database for emotion analysis using physiological signals (DEAP. Three strategies were employed to select the best channels in classifying four emotional states (joy, fear, sadness and relaxation. Furthermore, support vector machine (SVM was used as a classifier to validate the performance of the channel selection results. The experimental results showed the effectiveness of our methods and the comparison with the similar strategies, based on the F-score, was given. Strategies to evaluate a channel as a unity gave better performance in channel reduction with an acceptable loss of accuracy. In the third strategy, after adjusting channels’ weights according to their contribution to the classification accuracy, the number of channels was reduced to eight with a slight loss of accuracy (58.51% ± 10.05% versus the best classification accuracy 59.13% ± 11.00% using 19 channels. In addition, the study of selecting subject-independent channels, related to emotion processing, was also implemented. The sensors, selected subject-independently from frontal, parietal lobes, have been identified to provide more discriminative information associated with emotion processing, and are distributed symmetrically over the scalp, which is consistent with the existing literature. The results will make a

Interval analysis of interictal EEG: pathology of the alpha rhythm in focal epilepsy

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Pyrzowski, Jan; Siemiński, Mariusz; Sarnowska, Anna; Jedrzejczak, Joanna; Nyka, Walenty M.

2015-11-01

The contemporary use of interictal scalp electroencephalography (EEG) in the context of focal epilepsy workup relies on the visual identification of interictal epileptiform discharges. The high-specificity performance of this marker comes, however, at a cost of only moderate sensitivity. Zero-crossing interval analysis is an alternative to Fourier analysis for the assessment of the rhythmic component of EEG signals. We applied this method to standard EEG recordings of 78 patients divided into 4 subgroups: temporal lobe epilepsy (TLE), frontal lobe epilepsy (FLE), psychogenic nonepileptic seizures (PNES) and nonepileptic patients with headache. Interval-analysis based markers were capable of effectively discriminating patients with epilepsy from those in control subgroups (AUC~0.8) with diagnostic sensitivity potentially exceeding that of visual analysis. The identified putative epilepsy-specific markers were sensitive to the properties of the alpha rhythm and displayed weak or non-significant dependences on the number of antiepileptic drugs (AEDs) taken by the patients. Significant AED-related effects were concentrated in the theta interval range and an associated marker allowed for identification of patients on AED polytherapy (AUC~0.9). Interval analysis may thus, in perspective, increase the diagnostic yield of interictal scalp EEG. Our findings point to the possible existence of alpha rhythm abnormalities in patients with epilepsy.

Performance evaluation of the Champagne source reconstruction algorithm on simulated and real M/EEG data.

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Owen, Julia P; Wipf, David P; Attias, Hagai T; Sekihara, Kensuke; Nagarajan, Srikantan S

2012-03-01

In this paper, we present an extensive performance evaluation of a novel source localization algorithm, Champagne. It is derived in an empirical Bayesian framework that yields sparse solutions to the inverse problem. It is robust to correlated sources and learns the statistics of non-stimulus-evoked activity to suppress the effect of noise and interfering brain activity. We tested Champagne on both simulated and real M/EEG data. The source locations used for the simulated data were chosen to test the performance on challenging source configurations. In simulations, we found that Champagne outperforms the benchmark algorithms in terms of both the accuracy of the source localizations and the correct estimation of source time courses. We also demonstrate that Champagne is more robust to correlated brain activity present in real MEG data and is able to resolve many distinct and functionally relevant brain areas with real MEG and EEG data. Copyright © 2011 Elsevier Inc. All rights reserved.

Preictal dynamics of EEG complexity in intracranially recorded epileptic seizure: a case report.

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Bob, Petr; Roman, Robert; Svetlak, Miroslav; Kukleta, Miloslav; Chladek, Jan; Brazdil, Milan

2014-11-01

Recent findings suggest that neural complexity reflecting a number of independent processes in the brain may characterize typical changes during epileptic seizures and may enable to describe preictal dynamics. With respect to previously reported findings suggesting specific changes in neural complexity during preictal period, we have used measure of pointwise correlation dimension (PD2) as a sensitive indicator of nonstationary changes in complexity of the electroencephalogram (EEG) signal. Although this measure of complexity in epileptic patients was previously reported by Feucht et al (Applications of correlation dimension and pointwise dimension for non-linear topographical analysis of focal onset seizures. Med Biol Comput. 1999;37:208-217), it was not used to study changes in preictal dynamics. With this aim to study preictal changes of EEG complexity, we have examined signals from 11 multicontact depth (intracerebral) EEG electrodes located in 108 cortical and subcortical brain sites, and from 3 scalp EEG electrodes in a patient with intractable epilepsy, who underwent preoperative evaluation before epilepsy surgery. From those 108 EEG contacts, records related to 44 electrode contacts implanted into lesional structures and white matter were not included into the experimental analysis.The results show that in comparison to interictal period (at about 8-6 minutes before seizure onset), there was a statistically significant decrease in PD2 complexity in the preictal period at about 2 minutes before seizure onset in all 64 intracranial channels localized in various brain sites that were included into the analysis and in 3 scalp EEG channels as well. Presented results suggest that using PD2 in EEG analysis may have significant implications for research of preictal dynamics and prediction of epileptic seizures.

Near-lossless multichannel EEG compression based on matrix and tensor decompositions.

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Dauwels, Justin; Srinivasan, K; Reddy, M Ramasubba; Cichocki, Andrzej

2013-05-01

A novel near-lossless compression algorithm for multichannel electroencephalogram (MC-EEG) is proposed based on matrix/tensor decomposition models. MC-EEG is represented in suitable multiway (multidimensional) forms to efficiently exploit temporal and spatial correlations simultaneously. Several matrix/tensor decomposition models are analyzed in view of efficient decorrelation of the multiway forms of MC-EEG. A compression algorithm is built based on the principle of “lossy plus residual coding,” consisting of a matrix/tensor decomposition-based coder in the lossy layer followed by arithmetic coding in the residual layer. This approach guarantees a specifiable maximum absolute error between original and reconstructed signals. The compression algorithm is applied to three different scalp EEG datasets and an intracranial EEG dataset, each with different sampling rate and resolution. The proposed algorithm achieves attractive compression ratios compared to compressing individual channels separately. For similar compression ratios, the proposed algorithm achieves nearly fivefold lower average error compared to a similar wavelet-based volumetric MC-EEG compression algorithm.

Offline identification of imagined speed of wrist movements in paralyzed ALS patients from single-trial EEG

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Ying Gu

2009-08-01

Full Text Available The study investigated the possibility of identifying the speed of an imagined movement from EEG recordings in amyotrophic lateral sclerosis (ALS patients. EEG signals were acquired from four ALS patients during imagination of wrist extensions at two speeds (fast and slow, each repeated up to 100 times in random order. The movement-related cortical potentials (MRCPs and averaged sensorimotor rhythm associated with the two tasks were obtained from the EEG recordings. Moreover, offline single-trial EEG classification was performed with discrete wavelet transform for feature extraction and support vector machine for classification. The speed of the task was encoded in the time delay of peak negativity in the MRCPs, which was shorter for faster than for slower movements. The average single-trial misclassification rate between speeds was 30.4 ± 3.5 % when the best scalp location and time interval were selected for each individual. The scalp location and time interval leading to the lowest misclassification rate varied among patients. The results indicate that the imagination of movements at different speeds is a viable strategy for controlling a brain-computer interface system by ALS patients.

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

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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.

EEGNET: An Open Source Tool for Analyzing and Visualizing M/EEG Connectome.

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Hassan, Mahmoud; Shamas, Mohamad; Khalil, Mohamad; El Falou, Wassim; Wendling, Fabrice

2015-01-01

The brain is a large-scale complex network often referred to as the "connectome". Exploring the dynamic behavior of the connectome is a challenging issue as both excellent time and space resolution is required. In this context Magneto/Electroencephalography (M/EEG) are effective neuroimaging techniques allowing for analysis of the dynamics of functional brain networks at scalp level and/or at reconstructed sources. However, a tool that can cover all the processing steps of identifying brain networks from M/EEG data is still missing. In this paper, we report a novel software package, called EEGNET, running under MATLAB (Math works, inc), and allowing for analysis and visualization of functional brain networks from M/EEG recordings. EEGNET is developed to analyze networks either at the level of scalp electrodes or at the level of reconstructed cortical sources. It includes i) Basic steps in preprocessing M/EEG signals, ii) the solution of the inverse problem to localize / reconstruct the cortical sources, iii) the computation of functional connectivity among signals collected at surface electrodes or/and time courses of reconstructed sources and iv) the computation of the network measures based on graph theory analysis. EEGNET is the unique tool that combines the M/EEG functional connectivity analysis and the computation of network measures derived from the graph theory. The first version of EEGNET is easy to use, flexible and user friendly. EEGNET is an open source tool and can be freely downloaded from this webpage: https://sites.google.com/site/eegnetworks/.

Differences between magnetoencephalographic (MEG) spectral profiles of drugs acting on GABA at synaptic and extrasynaptic sites: a study in healthy volunteers.

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Nutt, David; Wilson, Sue; Lingford-Hughes, Anne; Myers, Jim; Papadopoulos, Andreas; Muthukumaraswamy, Suresh

2015-01-01

A range of medications target different aspects of the GABA system; understanding their effects is important to inform further drug development. Effects on the waking EEG comparing these mechanisms have not been reported; in this study we compare the effects on resting MEG spectra of the benzodiazepine receptor agonist zolpidem, the delta sub-unit selective agonist gaboxadol (also known as THIP) and the GABA reuptake inhibitor tiagabine. These were two randomised, single-blind, placebo-controlled, crossover studies in healthy volunteers, one using zolpidem 10 mg, gaboxadol 15 mg and placebo, and the other tiagabine 15 mg and placebo. Whole head MEG recordings and individual MEG spectra were divided into frequency bands. Baseline spectra were subtracted from each post-intervention spectra and then differences between intervention and placebo compared. After zolpidem there were significant increases in beta frequencies and reduction in alpha frequency power; after gaboxadol and tiagabine there were significant increases in power at all frequencies up to beta. Enhancement of tonic inhibition via extrasynaptic receptors by gaboxadol gives rise to a very different MEG signature from the synaptic action of zolpidem. Tiagabine theoretically can affect both types of receptor; from these MEG results it is likely that the latter is the more prominent effect here. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

An MEG signature corresponding to an axiomatic model of reward prediction error.

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Talmi, Deborah; Fuentemilla, Lluis; Litvak, Vladimir; Duzel, Emrah; Dolan, Raymond J

2012-01-02

Optimal decision-making is guided by evaluating the outcomes of previous decisions. Prediction errors are theoretical teaching signals which integrate two features of an outcome: its inherent value and prior expectation of its occurrence. To uncover the magnetic signature of prediction errors in the human brain we acquired magnetoencephalographic (MEG) data while participants performed a gambling task. Our primary objective was to use formal criteria, based upon an axiomatic model (Caplin and Dean, 2008a), to determine the presence and timing profile of MEG signals that express prediction errors. We report analyses at the sensor level, implemented in SPM8, time locked to outcome onset. We identified, for the first time, a MEG signature of prediction error, which emerged approximately 320 ms after an outcome and expressed as an interaction between outcome valence and probability. This signal followed earlier, separate signals for outcome valence and probability, which emerged approximately 200 ms after an outcome. Strikingly, the time course of the prediction error signal, as well as the early valence signal, resembled the Feedback-Related Negativity (FRN). In simultaneously acquired EEG data we obtained a robust FRN, but the win and loss signals that comprised this difference wave did not comply with the axiomatic model. Our findings motivate an explicit examination of the critical issue of timing embodied in computational models of prediction errors as seen in human electrophysiological data. Copyright © 2011 Elsevier Inc. All rights reserved.

Spectral-Spatial Differentiation of Brain Activity During Mental Imagery of Improvisational Music Performance Using MEG.

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Boasen, Jared; Takeshita, Yuya; Kuriki, Shinya; Yokosawa, Koichi

2018-01-01

Group musical improvisation is thought to be akin to conversation, and therapeutically has been shown to be effective at improving communicativeness, sociability, creative expression, and overall psychological health. To understand these therapeutic effects, clarifying the nature of brain activity during improvisational cognition is important. Some insight regarding brain activity during improvisational music cognition has been gained via functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). However, we have found no reports based on magnetoencephalography (MEG). With the present study, we aimed to demonstrate the feasibility of improvisational music performance experimentation in MEG. We designed a novel MEG-compatible keyboard, and used it with experienced musicians ( N = 13) in a music performance paradigm to spectral-spatially differentiate spontaneous brain activity during mental imagery of improvisational music performance. Analyses of source activity revealed that mental imagery of improvisational music performance induced greater theta (5-7 Hz) activity in left temporal areas associated with rhythm production and communication, greater alpha (8-12 Hz) activity in left premotor and parietal areas associated with sensorimotor integration, and less beta (15-29 Hz) activity in right frontal areas associated with inhibition control. These findings support the notion that musical improvisation is conversational, and suggest that creation of novel auditory content is facilitated by a more internally-directed, disinhibited cognitive state.

Fetal scalp pH testing

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Fetal scalp blood; Scalp pH testing; Fetal blood testing - scalp; Fetal distress - fetal scalp testing; Labor - fetal scalp testing ... a baby. In these cases, testing the scalp pH can help the doctor decide whether the fetus ...

An Internet-Based Real-Time Audiovisual Link for Dual MEG Recordings.

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Andrey Zhdanov

Full Text Available Most neuroimaging studies of human social cognition have focused on brain activity of single subjects. More recently, "two-person neuroimaging" has been introduced, with simultaneous recordings of brain signals from two subjects involved in social interaction. These simultaneous "hyperscanning" recordings have already been carried out with a spectrum of neuroimaging modalities, such as functional magnetic resonance imaging (fMRI, electroencephalography (EEG, and functional near-infrared spectroscopy (fNIRS.We have recently developed a setup for simultaneous magnetoencephalographic (MEG recordings of two subjects that communicate in real time over an audio link between two geographically separated MEG laboratories. Here we present an extended version of the setup, where we have added a video connection and replaced the telephone-landline-based link with an Internet connection. Our setup enabled transmission of video and audio streams between the sites with a one-way communication latency of about 130 ms. Our software that allows reproducing the setup is publicly available.We demonstrate that the audiovisual Internet-based link can mediate real-time interaction between two subjects who try to mirror each others' hand movements that they can see via the video link. All the nine pairs were able to synchronize their behavior. In addition to the video, we captured the subjects' movements with accelerometers attached to their index fingers; we determined from these signals that the average synchronization accuracy was 215 ms. In one subject pair we demonstrate inter-subject coherence patterns of the MEG signals that peak over the sensorimotor areas contralateral to the hand used in the task.

Resistor mesh model of a spherical head: part 1: applications to scalp potential interpolation.

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Chauveau, N; Morucci, J P; Franceries, X; Celsis, P; Rigaud, B

2005-11-01

A resistor mesh model (RMM) has been implemented to describe the electrical properties of the head and the configuration of the intracerebral current sources by simulation of forward and inverse problems in electroencephalogram/event related potential (EEG/ERP) studies. For this study, the RMM representing the three basic tissues of the human head (brain, skull and scalp) was superimposed on a spherical volume mimicking the head volume: it included 43 102 resistances and 14 123 nodes. The validation was performed with reference to the analytical model by consideration of a set of four dipoles close to the cortex. Using the RMM and the chosen dipoles, four distinct families of interpolation technique (nearest neighbour, polynomial, splines and lead fields) were tested and compared so that the scalp potentials could be recovered from the electrode potentials. The 3D spline interpolation and the inverse forward technique (IFT) gave the best results. The IFT is very easy to use when the lead-field matrix between scalp electrodes and cortex nodes has been calculated. By simple application of the Moore-Penrose pseudo inverse matrix to the electrode cap potentials, a set of current sources on the cortex is obtained. Then, the forward problem using these cortex sources renders all the scalp potentials.

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

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

2014-08-01

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

New perspectives in EEG/MEG brain mapping and PET/fMRI neuroimaging of human pain.

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Chen, A C

2001-10-01

With the maturation of EEG/MEG brain mapping and PET/fMRI neuroimaging in the 1990s, greater understanding of pain processing in the brain now elucidates and may even challenge the classical theory of pain mechanisms. This review scans across the cultural diversity of pain expression and modulation in man. It outlines the difficulties in defining and studying human pain. It then focuses on methods of studying the brain in experimental and clinical pain, the cohesive results of brain mapping and neuroimaging of noxious perception, the implication of pain research in understanding human consciousness and the relevance to clinical care as well as to the basic science of human psychophysiology. Non-invasive brain studies in man start to unveil the age-old puzzles of pain-illusion, hypnosis and placebo in pain modulation. The neurophysiological and neurohemodynamic brain measures of experimental pain can now largely satisfy the psychophysiologist's dream, unimaginable only a few years ago, of modelling the body-brain, brain-mind, mind-matter duality in an inter-linking 3-P triad: physics (stimulus energy); physiology (brain activities); and psyche (perception). For neuropsychophysiology greater challenges lie ahead: (a) how to integrate a cohesive theory of human pain in the brain; (b) what levels of analyses are necessary and sufficient; (c) what constitutes the structural organisation of the pain matrix; (d) what are the modes of processing among and across the sites of these structures; and (e) how can neural computation of these processes in the brain be carried out? We may envision that modular identification and delineation of the arousal-attention, emotion-motivation and perception-cognition neural networks of pain processing in the brain will also lead to deeper understanding of the human mind. Two foreseeable impacts on clinical sciences and basic theories from brain mapping/neuroimaging are the plausible central origin in persistent pain and integration of

Saccadic spike potentials in gamma-band EEG: characterization, detection and suppression.

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Keren, Alon S; Yuval-Greenberg, Shlomit; Deouell, Leon Y

2010-02-01

Analysis of high-frequency (gamma-band) neural activity by means of non-invasive EEG is gaining increasing interest. However, we have recently shown that a saccade-related spike potential (SP) seriously confounds the analysis of EEG induced gamma-band responses (iGBR), as the SP eludes traditional EEG artifact rejection methods. Here we provide a comprehensive profile of the SP and evaluate methods for its detection and suppression, aiming to unveil true cerebral gamma-band activity. The SP appears consistently as a sharp biphasic deflection of about 22 ms starting at the saccade onset, with a frequency band of approximately 20-90 Hz. On the average, larger saccades elicit higher SP amplitudes. The SP amplitude gradually changes from the extra-ocular channels towards posterior sites with the steepest gradients around the eyes, indicating its ocular source. Although the amplitude and the sign of the SP depend on the choice of reference channel, the potential gradients remain the same and non-zero for all references. The scalp topography is modulated almost exclusively by the direction of saccades, with steeper gradients ipsilateral to the saccade target. We discuss how the above characteristics impede attempts to remove these SPs from the EEG by common temporal filtering, choice of different references, or rejection of contaminated trials. We examine the extent to which SPs can be reliably detected without an eye tracker, assess the degree to which scalp current density derivation attenuates the effect of the SP, and propose a tailored ICA procedure for minimizing the effect of the SP. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Nonlinear CER Anticipation of Epileptic Seizures is More Effective in Intracranial EEG than in Scalp/Sphenoidal EEG

Czech Academy of Sciences Publication Activity Database

Komárek, V.; Hrnčíř, Z.; Paluš, Milan; Procházka, T.; Jiruška, P.; Marusic, P.

2003-01-01

Roč. 44, Suppl. 8 (2003), s. 178 ISSN 0013-9580. [International Epilepsy Congress /25./. 12.10.2003-16.10.2003, Lisbon] Institutional research plan: CEZ:AV0Z1030915; MSM 111300003; MSM 111300004 Keywords : brain dynamic * long term EEG analysis Subject RIV: ED - Physiology

The Scalp Time-Varying Networks of N170: Reference, Latency, and Information Flow

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Yin Tian

2018-04-01

Full Text Available Using the scalp time-varying network method, the present study is the first to investigate the temporal influence of the reference on N170, a negative event-related potential component (ERP appeared about 170 ms that is elicited by facial recognition, in the network levels. Two kinds of scalp electroencephalogram (EEG references, namely, AR (average of all recording channels and reference electrode standardization technique (REST, were comparatively investigated via the time-varying processing of N170. Results showed that the latency and amplitude of N170 were significantly different between REST and AR, with the former being earlier and smaller. In particular, the information flow from right temporal-parietal P8 to left P7 in the time-varying network was earlier in REST than that in AR, and this phenomenon was reproduced by simulation, in which the performance of REST was closer to the true case at source level. These findings indicate that reference plays a crucial role in ERP data interpretation, and importantly, the newly developed approximate zero-reference REST would be a superior choice for precise evaluation of the scalp spatio-temporal changes relating to various cognitive events.

Methodological aspects of EEG and Body dynamics measurements during motion.

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Pedro eReis

2014-03-01

Full Text Available EEG involves recording, analysis, and interpretation of voltages recorded on the human scalp originating from brain grey matter. EEG is one of the favorite methods to study and understand processes that underlie behavior. This is so, because EEG is relatively cheap, easy to wear, light weight and has high temporal resolution. In terms of behavior, this encompasses actions, such as movements, that are performed in response to the environment. However, there are methodological difficulties when recording EEG during movement such as movement artifacts. Thus, most studies about the human brain have examined activations during static conditions. This article attempts to compile and describe relevant methodological solutions that emerged in order to measure body and brain dynamics during motion. These descriptions cover suggestions of how to avoid and reduce motion artifacts, hardware, software and techniques for synchronously recording EEG, EMG, kinematics, kinetics and eye movements during motion. Additionally, we present various recording systems, EEG electrodes, caps and methods for determination of real/custom electrode positions. In the end we will conclude that it is possible to record and analyze synchronized brain and body dynamics related to movement or exercise tasks.

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

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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.

Comparison of different spatial transformations applied to EEG data: A case study of error processing

NARCIS (Netherlands)

Cohen, M.X.

2015-01-01

The purpose of this paper is to compare the effects of different spatial transformations applied to the same scalp-recorded EEG data. The spatial transformations applied are two referencing schemes (average and linked earlobes), the surface Laplacian, and beamforming (a distributed source

Independent component analysis of gait-related movement artifact recorded using EEG electrodes during treadmill walking.

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Kristine Lynne Snyder

2015-12-01

Full Text Available There has been a recent surge in the use of electroencephalography (EEG as a tool for mobile brain imaging due to its portability and fine time resolution. When EEG is combined with independent component analysis (ICA and source localization techniques, it can model electrocortical activity as arising from temporally independent signals located in spatially distinct cortical areas. However, for mobile tasks, it is not clear how movement artifacts influence ICA and source localization. We devised a novel method to collect pure movement artifact data (devoid of any electrophysiological signals with a 256-channel EEG system. We first blocked true electrocortical activity using a silicone swim cap. Over the silicone layer, we placed a simulated scalp with electrical properties similar to real human scalp. We collected EEG movement artifact signals from ten healthy, young subjects wearing this setup as they walked on a treadmill at speeds from 0.4-1.6 m/s. We performed ICA and dipole fitting on the EEG movement artifact data to quantify how accurately these methods would identify the artifact signals as non-neural. ICA and dipole fitting accurately localized 99% of the independent components in non-neural locations or lacked dipolar characteristics. The remaining 1% of sources had locations within the brain volume and low residual variances, but had topographical maps, power spectra, time courses, and event related spectral perturbations typical of non-neural sources. Caution should be exercised when interpreting ICA for data that includes semi-periodic artifacts including artifact arising from human walking. Alternative methods are needed for the identification and separation of movement artifact in mobile EEG signals, especially methods that can be performed in real time. Separating true brain signals from motion artifact could clear the way for EEG brain computer interfaces for assistance during mobile activities, such as walking.

Generalized Information Equilibrium Approaches to EEG Sleep Stage Discrimination

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Todd Zorick

2016-01-01

Full Text Available Recent advances in neuroscience have raised the hypothesis that the underlying pattern of neuronal activation which results in electroencephalography (EEG signals is via power-law distributed neuronal avalanches, while EEG signals are nonstationary. Therefore, spectral analysis of EEG may miss many properties inherent in such signals. A complete understanding of such dynamical systems requires knowledge of the underlying nonequilibrium thermodynamics. In recent work by Fielitz and Borchardt (2011, 2014, the concept of information equilibrium (IE in information transfer processes has successfully characterized many different systems far from thermodynamic equilibrium. We utilized a publicly available database of polysomnogram EEG data from fourteen subjects with eight different one-minute tracings of sleep stage 2 and waking and an overlapping set of eleven subjects with eight different one-minute tracings of sleep stage 3. We applied principles of IE to model EEG as a system that transfers (equilibrates information from the time domain to scalp-recorded voltages. We find that waking consciousness is readily distinguished from sleep stages 2 and 3 by several differences in mean information transfer constants. Principles of IE applied to EEG may therefore prove to be useful in the study of changes in brain function more generally.

Spectral-Spatial Differentiation of Brain Activity During Mental Imagery of Improvisational Music Performance Using MEG

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Boasen, Jared; Takeshita, Yuya; Kuriki, Shinya; Yokosawa, Koichi

2018-01-01

Group musical improvisation is thought to be akin to conversation, and therapeutically has been shown to be effective at improving communicativeness, sociability, creative expression, and overall psychological health. To understand these therapeutic effects, clarifying the nature of brain activity during improvisational cognition is important. Some insight regarding brain activity during improvisational music cognition has been gained via functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). However, we have found no reports based on magnetoencephalography (MEG). With the present study, we aimed to demonstrate the feasibility of improvisational music performance experimentation in MEG. We designed a novel MEG-compatible keyboard, and used it with experienced musicians (N = 13) in a music performance paradigm to spectral-spatially differentiate spontaneous brain activity during mental imagery of improvisational music performance. Analyses of source activity revealed that mental imagery of improvisational music performance induced greater theta (5–7 Hz) activity in left temporal areas associated with rhythm production and communication, greater alpha (8–12 Hz) activity in left premotor and parietal areas associated with sensorimotor integration, and less beta (15–29 Hz) activity in right frontal areas associated with inhibition control. These findings support the notion that musical improvisation is conversational, and suggest that creation of novel auditory content is facilitated by a more internally-directed, disinhibited cognitive state. PMID:29740300

Spectral-Spatial Differentiation of Brain Activity During Mental Imagery of Improvisational Music Performance Using MEG

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Jared Boasen

2018-04-01

Full Text Available Group musical improvisation is thought to be akin to conversation, and therapeutically has been shown to be effective at improving communicativeness, sociability, creative expression, and overall psychological health. To understand these therapeutic effects, clarifying the nature of brain activity during improvisational cognition is important. Some insight regarding brain activity during improvisational music cognition has been gained via functional magnetic resonance imaging (fMRI and electroencephalography (EEG. However, we have found no reports based on magnetoencephalography (MEG. With the present study, we aimed to demonstrate the feasibility of improvisational music performance experimentation in MEG. We designed a novel MEG-compatible keyboard, and used it with experienced musicians (N = 13 in a music performance paradigm to spectral-spatially differentiate spontaneous brain activity during mental imagery of improvisational music performance. Analyses of source activity revealed that mental imagery of improvisational music performance induced greater theta (5–7 Hz activity in left temporal areas associated with rhythm production and communication, greater alpha (8–12 Hz activity in left premotor and parietal areas associated with sensorimotor integration, and less beta (15–29 Hz activity in right frontal areas associated with inhibition control. These findings support the notion that musical improvisation is conversational, and suggest that creation of novel auditory content is facilitated by a more internally-directed, disinhibited cognitive state.

Decoding human mental states by whole-head EEG+fNIRS during category fluency task performance

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Omurtag, Ahmet; Aghajani, Haleh; Onur Keles, Hasan

2017-12-01

Objective. Concurrent scalp electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), which we refer to as EEG+fNIRS, promises greater accuracy than the individual modalities while remaining nearly as convenient as EEG. We sought to quantify the hybrid system’s ability to decode mental states and compare it with its unimodal components. Approach. We recorded from healthy volunteers taking the category fluency test and applied machine learning techniques to the data. Main results. EEG+fNIRS’s decoding accuracy was greater than that of its subsystems, partly due to the new type of neurovascular features made available by hybrid data. Significance. Availability of an accurate and practical decoding method has potential implications for medical diagnosis, brain-computer interface design, and neuroergonomics.

Decoding English Alphabet Letters Using EEG Phase Information

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YiYan Wang

2018-02-01

Full Text Available Increasing evidence indicates that the phase pattern and power of the low frequency oscillations of brain electroencephalograms (EEG contain significant information during the human cognition of sensory signals such as auditory and visual stimuli. Here, we investigate whether and how the letters of the alphabet can be directly decoded from EEG phase and power data. In addition, we investigate how different band oscillations contribute to the classification and determine the critical time periods. An English letter recognition task was assigned, and statistical analyses were conducted to decode the EEG signal corresponding to each letter visualized on a computer screen. We applied support vector machine (SVM with gradient descent method to learn the potential features for classification. It was observed that the EEG phase signals have a higher decoding accuracy than the oscillation power information. Low-frequency theta and alpha oscillations have phase information with higher accuracy than do other bands. The decoding performance was best when the analysis period began from 180 to 380 ms after stimulus presentation, especially in the lateral occipital and posterior temporal scalp regions (PO7 and PO8. These results may provide a new approach for brain-computer interface techniques (BCI and may deepen our understanding of EEG oscillations in cognition.

A method for detecting nonlinear determinism in normal and epileptic brain EEG signals.

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Meghdadi, Amir H; Fazel-Rezai, Reza; Aghakhani, Yahya

2007-01-01

A robust method of detecting determinism for short time series is proposed and applied to both healthy and epileptic EEG signals. The method provides a robust measure of determinism through characterizing the trajectories of the signal components which are obtained through singular value decomposition. Robustness of the method is shown by calculating proposed index of determinism at different levels of white and colored noise added to a simulated chaotic signal. The method is shown to be able to detect determinism at considerably high levels of additive noise. The method is then applied to both intracranial and scalp EEG recordings collected in different data sets for healthy and epileptic brain signals. The results show that for all of the studied EEG data sets there is enough evidence of determinism. The determinism is more significant for intracranial EEG recordings particularly during seizure activity.

Bayesian Inference for Neural Electromagnetic Source Localization: Analysis of MEG Visual Evoked Activity

International Nuclear Information System (INIS)

George, J.S.; Schmidt, D.M.; Wood, C.C.

1999-01-01

We have developed a Bayesian approach to the analysis of neural electromagnetic (MEG/EEG) data that can incorporate or fuse information from other imaging modalities and addresses the ill-posed inverse problem by sarnpliig the many different solutions which could have produced the given data. From these samples one can draw probabilistic inferences about regions of activation. Our source model assumes a variable number of variable size cortical regions of stimulus-correlated activity. An active region consists of locations on the cortical surf ace, within a sphere centered on some location in cortex. The number and radi of active regions can vary to defined maximum values. The goal of the analysis is to determine the posterior probability distribution for the set of parameters that govern the number, location, and extent of active regions. Markov Chain Monte Carlo is used to generate a large sample of sets of parameters distributed according to the posterior distribution. This sample is representative of the many different source distributions that could account for given data, and allows identification of probable (i.e. consistent) features across solutions. Examples of the use of this analysis technique with both simulated and empirical MEG data are presented

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

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

2017-06-14

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

pH and electric conductivity study of H{sub 2}O/MEG/salt systems on monoethyleneglycol (MEG) reclamation units in gas processing; Estudo de pH e condutividade eletrica em sistemas H{sub 2}O/MEG/sal, em unidades de recuperacao de monoetilenoglicol (MEG), no processamento de gas natural

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Senna, Camila; Carrijo, Darley; Nascimento, Jailton; Grava, Wilson [PETROBRAS, Rio de Janeiro, RJ (Brazil). Centro de Pesquisas (CENPES); Lemos, Alessandro A.; Andrade, Wander V.; Chiavone-Filho, Osvaldo; Amorim, Josinira Antunes de [Universidade Federal do Rio Grande do Norte (UFRN), Natal, RN (Brazil). Dept. de Engenharia Quimica

2008-07-01

The monoethylene glycol (MEG) is injected in natural gas production wells in order to combine with the free water, altering the thermodynamic conditions for the formation of hydrates. The presence of MEG in aqueous solutions containing salts provokes the decrease of the solubility of the same ones. Information of properties as the pH and the conductivity are important for the control of the process. Before this, the present work has as objective determines the behavior of the aqueous solutions with MEG and NaCl in pH and conductivity terms, in different temperatures, with views to the stage of recovery of MEG and the salt precipitation beginning. The experimental methodology consisted of the elaboration of synthetic solutions of the mixtures in study, covering every MEG concentration range and temperature between 5 and 90 deg C. The conductivity results for the system H{sub 2}O+MEG showed that the conductivity decreases with the concentration of MEG and it increases with the temperature. A conductivity increase was observed for diluted concentrations of MEG, due to the most pronounced effect of protonation of MEG. For pH measures, it was necessary to develop a calibration procedure due to the fact that this property varies with the solvent media. The pH values decrease as it increases the concentration of MEG, reaching a value practically constant around 40%. (author)

INTELLIGENT EEG ANALYSIS

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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.

Information-Theoretical Analysis of EEG Microstate Sequences in Python

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Frederic von Wegner

2018-06-01

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

3D Printed Dry EEG Electrodes.

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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.

3D Printed Dry EEG Electrodes

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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.

Scalp Wound Closure with K wires: An alternative easier method to scalp wound closure.

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Ramesh, S; Ajik, S

2012-12-01

Scalp defects and lacerations present a reconstructive challenge to plastic surgeons. Many methods have been described from the use of skin grafting to rotation flaps. Here we present a method of closure of a contaminated scalp wound with the use of Kirschner wires. In our case, closure of scalp laceration was made possible with the use of 1.4 Kirschner wires and cable tie/ zip tie fasteners. The duration to closure of wound was 10 days. In reconstructing the scalp defect, this method was found to adhere to principles of scalp reconstruction. There were no post operative complications found from the procedure. On initial application on the edge of the wound, tension applied caused the K wires to cut through the wound edge. On replacement of K wires 1cm away from wound edge the procedure was not plagued by any further complication. In conclusion we find scalp closure with Kirschner wires are a simple and effective method for scalp wound closure.

Connectivity Measures in EEG Microstructural Sleep Elements.

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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

Corrected Four-Sphere Head Model for EEG Signals.

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Næss, Solveig; Chintaluri, Chaitanya; Ness, Torbjørn V; Dale, Anders M; Einevoll, Gaute T; Wójcik, Daniel K

2017-01-01

The EEG signal is generated by electrical brain cell activity, often described in terms of current dipoles. By applying EEG forward models we can compute the contribution from such dipoles to the electrical potential recorded by EEG electrodes. Forward models are key both for generating understanding and intuition about the neural origin of EEG signals as well as inverse modeling, i.e., the estimation of the underlying dipole sources from recorded EEG signals. Different models of varying complexity and biological detail are used in the field. One such analytical model is the four-sphere model which assumes a four-layered spherical head where the layers represent brain tissue, cerebrospinal fluid (CSF), skull, and scalp, respectively. While conceptually clear, the mathematical expression for the electric potentials in the four-sphere model is cumbersome, and we observed that the formulas presented in the literature contain errors. Here, we derive and present the correct analytical formulas with a detailed derivation. A useful application of the analytical four-sphere model is that it can serve as ground truth to test the accuracy of numerical schemes such as the Finite Element Method (FEM). We performed FEM simulations of the four-sphere head model and showed that they were consistent with the corrected analytical formulas. For future reference we provide scripts for computing EEG potentials with the four-sphere model, both by means of the correct analytical formulas and numerical FEM simulations.

Corrected Four-Sphere Head Model for EEG Signals

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Solveig Næss

2017-10-01

Full Text Available The EEG signal is generated by electrical brain cell activity, often described in terms of current dipoles. By applying EEG forward models we can compute the contribution from such dipoles to the electrical potential recorded by EEG electrodes. Forward models are key both for generating understanding and intuition about the neural origin of EEG signals as well as inverse modeling, i.e., the estimation of the underlying dipole sources from recorded EEG signals. Different models of varying complexity and biological detail are used in the field. One such analytical model is the four-sphere model which assumes a four-layered spherical head where the layers represent brain tissue, cerebrospinal fluid (CSF, skull, and scalp, respectively. While conceptually clear, the mathematical expression for the electric potentials in the four-sphere model is cumbersome, and we observed that the formulas presented in the literature contain errors. Here, we derive and present the correct analytical formulas with a detailed derivation. A useful application of the analytical four-sphere model is that it can serve as ground truth to test the accuracy of numerical schemes such as the Finite Element Method (FEM. We performed FEM simulations of the four-sphere head model and showed that they were consistent with the corrected analytical formulas. For future reference we provide scripts for computing EEG potentials with the four-sphere model, both by means of the correct analytical formulas and numerical FEM simulations.

A portable, differential amplifier for recording high frequency EEG signals and evoked potentials

International Nuclear Information System (INIS)

Donos, Cristian; Giurgiu, Liviu; Popescu, Aurel; Mocanu, Marian

2010-01-01

In a clinical context, EEG refers to recording the brain's spontaneous electric activity, using small electrodes placed on the scalp. The signals collected are electric 'potentials' measured between two electrodes. Usually, for a healthy adult, these signals have small voltage (10 μV to 100 μV) and frequencies in the 0-40 Hz range. In the scientific literature, there are mentioned EEG signals and evoked potentials that have higher frequencies (up to 600 Hz) and amplitudes lower than 500 ηV. For this reason, building an amplifier capable of recording EEG signals in the ηV range and with frequencies up to couple of kHz is necessary to continue research beyond 600 Hz. We designed a very low noise amplifier that is able to measure/record EEG signals in the ηV range over a very large frequency bandwidth (0.09 Hz -385 kHz).(Author)

The influence of methylphenidate on the power spectrum of ADHD children – an MEG study

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Bauer Susanne

2005-07-01

Full Text Available Abstract Background The present study was dedicated to investigate the influence of Methylphenidate (MPH on cortical processing of children who were diagnosed with different subtypes of Attention Deficit Hyperactivity Disorder (ADHD. As all of the previous studies investigating power differences in different frequency bands have been using EEG, mostly with a relatively small number of electrodes our aim was to obtain new aspects using high density magnetoencephalography (MEG. Methods 35 children (6 female, 29 male participated in this study. Mean age was 11.7 years (± 1.92 years. 17 children were diagnosed of having an Attention-Deficit/Hyperactivity Disorder of the combined type (ADHDcom, DSM IV code 314.01; the other 18 were diagnosed for ADHD of the predominantly inattentive type (ADHDin, DSM IV code 314.0. We measured the MEG during a 5 minute resting period with a 148-channel magnetometer system (MAGNES™ 2500 WH, 4D Neuroimaging, San Diego, USA. Power values were averaged for 5 bands: Delta (D, 1.5–3.5 Hz, Theta (T, 3.5–7.5 Hz, Alpha (A, 7.5–12.5 Hz, Beta (B, 12.5–25 Hz and Global (GL, 1.5–25 Hz.. Additionally, attention was measured behaviourally using the D2 test of attention with and without medication. Results The global power of the frequency band from 1.5 to 25 Hz increased with MPH. Relative Theta was found to be higher in the left hemisphere after administration of MPH than before. A positive correlation was found between D2 test improvement and MPH-induced power changes in the Theta band over the left frontal region. A linear regression was computed and confirmed that the larger the improvement in D2 test performance, the larger the increase in Theta after MPH application. Conclusion Main effects induced by medication were found in frontal regions. Theta band activity increased over the left hemisphere after MPH application. This finding contradicts EEG results of several groups who found lower levels of Theta power

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

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

2015-01-01

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

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

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Shih-Cheng Liao

2017-06-01

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

Post-movement beta rebound abnormality as indicator of mirror neuron system dysfunction in autistic spectrum disorder: an MEG study.

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Honaga, Eiko; Ishii, Ryouhei; Kurimoto, Ryu; Canuet, Leonides; Ikezawa, Koji; Takahashi, Hidetoshi; Nakahachi, Takayuki; Iwase, Masao; Mizuta, Ichiro; Yoshimine, Toshiki; Takeda, Masatoshi

2010-07-12

The mu rhythm is regarded as a physiological indicator of the human mirror neuron system (MNS). The dysfunctional MNS hypothesis in patients with autistic spectrum disorder (ASD) has often been tested using EEG and MEG, targeting mu rhythm suppression during action observation/execution, although with controversial results. We explored neural activity related to the MNS in patients with ASD, focusing on power increase in the beta frequency band after observation and execution of movements, known as post-movement beta rebound (PMBR). Multiple source beamformer (MSBF) and BrainVoyager QX were used for MEG source imaging and statistical group analysis, respectively. Seven patients with ASD and ten normal subjects participated in this study. During the MEG recordings, the subjects were asked to observe and later execute object-related hand actions performed by an experimenter. We found that both groups exhibited pronounced PMBR exceeding 20% when observing and executing actions with a similar topographic distribution of maximal activity. However, significantly reduced PMBR was found only during the observation condition in the patients relative to controls in cortical regions within the MNS, namely the sensorimotor area, premotor cortex and superior temporal gyrus. Reduced PMBR during the observation condition was also found in the medial prefrontal cortex. These results support the notion of a dysfunctional execution/observation matching system related to MNS impairment in patients with ASD, and the feasibility of using MEG to detect neural activity, in particular PMBR abnormalities, as an index of MNS dysfunction during performance of motor or cognitive tasks. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

Epileptogenic developmental venous anomaly: insights from simultaneous EEG/fMRI.

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Scheidegger, Olivier; Wiest, Roland; Jann, Kay; König, Thomas; Meyer, Klaus; Hauf, Martinus

2013-04-01

Developmental venous anomalies (DVAs) are associated with epileptic seizures; however, the role of DVA in the epileptogenesis is still not established. Simultaneous interictal electroencephalogram/functional magnetic resonance imaging (EEG/fMRI) recordings provide supplementary information to electroclinical data about the epileptic generators, and thus aid in the differentiation of clinically equivocal epilepsy syndromes. The main objective of our study was to characterize the epileptic network in a patient with DVA and epilepsy by simultaneous EEG/fMRI recordings. A 17-year-old woman with recently emerging generalized tonic-clonic seizures, and atypical generalized discharges, was investigated using simultaneous EEG/fMRI at the university hospital. Previous high-resolution MRI showed no structural abnormalities, except a DVA in the right frontal operculum. Interictal EEG recordings showed atypical generalized discharges, corresponding to positive focal blood oxygen level dependent (BOLD) correlates in the right frontal operculum, a region drained by the DVA. Additionally, widespread cortical bilateral negative BOLD correlates in the frontal and parietal lobes were delineated, resembling a generalized epileptic network. The EEG/fMRI recordings support a right frontal lobe epilepsy, originating in the vicinity of the DVA, propagating rapidly to both frontal and parietal lobes, as expressed on the scalp EEG by secondary bilateral synchrony. The DVA may be causative of focal epilepsies in cases where no concomitant epileptogenic lesions can be detected. Advanced imaging techniques, such as simultaneous EEG/fMRI, may thus aid in the differentiation of clinically equivocal epilepsy syndromes.

FFT transformed quantitative EEG analysis of short term memory load.

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Singh, Yogesh; Singh, Jayvardhan; Sharma, Ratna; Talwar, Anjana

2015-07-01

The EEG is considered as building block of functional signaling in the brain. The role of EEG oscillations in human information processing has been intensively investigated. To study the quantitative EEG correlates of short term memory load as assessed through Sternberg memory test. The study was conducted on 34 healthy male student volunteers. The intervention consisted of Sternberg memory test, which runs on a version of the Sternberg memory scanning paradigm software on a computer. Electroencephalography (EEG) was recorded from 19 scalp locations according to 10-20 international system of electrode placement. EEG signals were analyzed offline. To overcome the problems of fixed band system, individual alpha frequency (IAF) based frequency band selection method was adopted. The outcome measures were FFT transformed absolute powers in the six bands at 19 electrode positions. Sternberg memory test served as model of short term memory load. Correlation analysis of EEG during memory task was reflected as decreased absolute power in Upper alpha band in nearly all the electrode positions; increased power in Theta band at Fronto-Temporal region and Lower 1 alpha band at Fronto-Central region. Lower 2 alpha, Beta and Gamma band power remained unchanged. Short term memory load has distinct electroencephalographic correlates resembling the mentally stressed state. This is evident from decreased power in Upper alpha band (corresponding to Alpha band of traditional EEG system) which is representative band of relaxed mental state. Fronto-temporal Theta power changes may reflect the encoding and execution of memory task.

Co-localization between the BOLD response and epileptiform discharges recorded by simultaneous intracranial EEG-fMRI at 3 T

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Yahya Aghakhani

2015-01-01

Conclusions: iEEG-fMRI is a feasible and low-risk method for assessment of hemodynamic changes of very focal IEDs that may not be recorded by scalp EEG. A high concordance rate between the location of the BOLD response and IEDs was seen for mesial temporal (6/7 IEDs. Significant BOLD activation was also seen in areas distant from the active electrode and these sites exhibited maximal BOLD activation in the majority of cases. This implies that iEEG-fMRI may further describe the areas involved in the generation of IEDs beyond the vicinity of the electrode(s.

EEG evaluation of humaneness of asphyxia and decapitation euthanasia of the laboratory rat.

Science.gov (United States)

Mikeska, J A; Klemm, W R

1975-04-01

The relative humaneness of asphyxia and decapitation was objectively evaluated in rats by EEG monitoring. EEG activation (low voltage, fast activity) was considered to indicate discomfort, pain, and affective responses to euthansia. Such activation was present 37.3 plus or minus 7.5 sec after asphyxia and 13.6 plus or minus 4,6 sec after decapitation. Decapitation was also characterized by an immediate large, and relatively long-lasting, ultra-slow voltage, detected by non-polarizable scalp electrodes. Isoelectric activity (death) occurred 69.4 plus or minus 9.9 sec after onset of asphyxia and 27.2 plus or minus 4.4 sec after decapitation.

Long-lasting cerebral functional changes following moderate dose x-radiation treatment to the scalp in childhood: an electroencephalographic power spectral study

International Nuclear Information System (INIS)

Yaar, I.; Ron, E.; Modan, B.; Rinott, Y.; Yaar, M.; Modan, M.

1982-01-01

EEG tracings were compared in 44 young adults who received scalp x-radiation treatment for tinea capitis during childhood and 59 non-irradiated control subjects. The irradiated subjects were exposed, over 20 years previously, to a mean dose of 130 rads to the brain. Visual analysis of the EEG revealed an insignificant excess of abnormalities among the irradiated subjects compared to the controls. Power spectral density function analysis showed increased power values among the irradiated subjects, particularly in the beta wave frequencies. This finding provides further evidence for suspecting that x-irradiation during brain maturation may cause long-lasting damage to the brain tissue. (author)

Adaptive Neuro-Fuzzy Inference System for Classification of Background EEG Signals from ESES Patients and Controls

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Zhixian Yang

2014-01-01

Full Text Available Background electroencephalography (EEG, recorded with scalp electrodes, in children with electrical status epilepticus during slow-wave sleep (ESES syndrome and control subjects has been analyzed. We considered 10 ESES patients, all right-handed and aged 3–9 years. The 10 control individuals had the same characteristics of the ESES ones but presented a normal EEG. Recordings were undertaken in the awake and relaxed states with their eyes open. The complexity of background EEG was evaluated using the permutation entropy (PE and sample entropy (SampEn in combination with the ANOVA test. It can be seen that the entropy measures of EEG are significantly different between the ESES patients and normal control subjects. Then, a classification framework based on entropy measures and adaptive neuro-fuzzy inference system (ANFIS classifier is proposed to distinguish ESES and normal EEG signals. The results are promising and a classification accuracy of about 89% is achieved.

Multivariate spectral-analysis of movement-related EEG data

International Nuclear Information System (INIS)

Andrew, C. M.

1997-01-01

The univariate method of event-related desynchronization (ERD) analysis, which quantifies the temporal evolution of power within specific frequency bands from electroencephalographic (EEG) data recorded during a task or event, is extended to an event related multivariate spectral analysis method. With this method, time courses of cross-spectra, phase spectra, coherence spectra, band-averaged coherence values (event-related coherence, ERCoh), partial power spectra and partial coherence spectra are estimated from an ensemble of multivariate event-related EEG trials. This provides a means of investigating relationships between EEG signals recorded over different scalp areas during the performance of a task or the occurrence of an event. The multivariate spectral analysis method is applied to EEG data recorded during three different movement-related studies involving discrete right index finger movements. The first study investigates the impact of the EEG derivation type on the temporal evolution of interhemispheric coherence between activity recorded at electrodes overlying the left and right sensorimotor hand areas during cued finger movement. The question results whether changes in coherence necessarily reflect changes in functional coupling of the cortical structures underlying the recording electrodes. The method is applied to data recorded during voluntary finger movement and a hypothesis, based on an existing global/local model of neocortical dynamics, is formulated to explain the coherence results. The third study applies partial spectral analysis too, and investigates phase relationships of, movement-related data recorded from a full head montage, thereby providing further results strengthening the global/local hypothesis. (author)

A liquid hydrogen target for the calibration of the MEG and MEG II liquid xenon calorimeter

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Signorelli, G., E-mail: giovanni.signorelli@pi.infn.it [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Baldini, A.M. [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Bemporad, C.; Cei, F.; Nicolò, D. [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Università di Pisa, Dipartimento di Fisica, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Galli, L.; Gallucci, G.; Grassi, M. [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Papa, A. [Paul Scherrer Institut, 5232 Villigen (Switzerland); Sergiampietri, F. [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Venturini, M. [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126 Pisa (Italy)

2016-07-11

We designed, built and operated a liquid hydrogen target for the calibration of the liquid xenon calorimeter of the MEG experiment. The target was used throughout the entire data taking period, from 2008 to 2013 and it is being refurbished and partly re-designed to be integrated and used in the MEG-II experiment.

Magnetoencephalography signals are influenced by skull defects.

Science.gov (United States)

Lau, S; Flemming, L; Haueisen, J

2014-08-01

Magnetoencephalography (MEG) signals had previously been hypothesized to have negligible sensitivity to skull defects. The objective is to experimentally investigate the influence of conducting skull defects on MEG and EEG signals. A miniaturized electric dipole was implanted in vivo into rabbit brains. Simultaneous recording using 64-channel EEG and 16-channel MEG was conducted, first above the intact skull and then above a skull defect. Skull defects were filled with agar gels, which had been formulated to have tissue-like homogeneous conductivities. The dipole was moved beneath the skull defects, and measurements were taken at regularly spaced points. The EEG signal amplitude increased 2-10 times, whereas the MEG signal amplitude reduced by as much as 20%. The EEG signal amplitude deviated more when the source was under the edge of the defect, whereas the MEG signal amplitude deviated more when the source was central under the defect. The change in MEG field-map topography (relative difference measure, RDM(∗)=0.15) was geometrically related to the skull defect edge. MEG and EEG signals can be substantially affected by skull defects. MEG source modeling requires realistic volume conductor head models that incorporate skull defects. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Imaging DC MEG Fields Associated with Epileptic Onset

Science.gov (United States)

Weiland, B. J.; Bowyer, S. M.; Moran, J. E.; Jenrow, K.; Tepley, N.

2004-10-01

Magnetoencephalography (MEG) is a non-invasive brain imaging modality, with high spatial and temporal resolution, used to evaluate and quantify the magnetic fields associated with neuronal activity. Complex partial epileptic seizures are characterized by hypersynchronous neuronal activity believed to arise from a zone of epileptogenesis. This study investigated the characteristics of direct current (DC) MEG shifts arising at epileptic onset. MEG data were acquired with rats using a six-channel first order gradiometer system. Limbic status epilepticus was induced by IA (femoral) administration of kainic acid. DC-MEG shifts were observed at the onset of epileptic spike train activity and status epilepticus. Epilepsy is also being studied in patients undergoing presurgical mapping from the Comprehensive Epilepsy Center at Henry Ford Hospital using a whole head Neuromagnetometer. Preliminary data analysis shows that DC-MEG waveforms, qualitatively similar to those seen in the animal model, are evident prior to seizure activity in human subjects.

Neocortical dynamics at multiple scales: EEG standing waves, statistical mechanics, and physical analogs.

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Ingber, Lester; Nunez, Paul L

2011-02-01

The dynamic behavior of scalp potentials (EEG) is apparently due to some combination of global and local processes with important top-down and bottom-up interactions across spatial scales. In treating global mechanisms, we stress the importance of myelinated axon propagation delays and periodic boundary conditions in the cortical-white matter system, which is topologically close to a spherical shell. By contrast, the proposed local mechanisms are multiscale interactions between cortical columns via short-ranged non-myelinated fibers. A mechanical model consisting of a stretched string with attached nonlinear springs demonstrates the general idea. The string produces standing waves analogous to large-scale coherent EEG observed in some brain states. The attached springs are analogous to the smaller (mesoscopic) scale columnar dynamics. Generally, we expect string displacement and EEG at all scales to result from both global and local phenomena. A statistical mechanics of neocortical interactions (SMNI) calculates oscillatory behavior consistent with typical EEG, within columns, between neighboring columns via short-ranged non-myelinated fibers, across cortical regions via myelinated fibers, and also derives a string equation consistent with the global EEG model. Copyright © 2010 Elsevier Inc. All rights reserved.

Mutual information measures applied to EEG signals for sleepiness characterization.

Science.gov (United States)

Melia, Umberto; Guaita, Marc; Vallverdú, Montserrat; Embid, Cristina; Vilaseca, Isabel; Salamero, Manel; Santamaria, Joan

2015-03-01

Excessive daytime sleepiness (EDS) is one of the main symptoms of several sleep related disorders with a great impact on the patient lives. While many studies have been carried out in order to assess daytime sleepiness, the automatic EDS detection still remains an open problem. In this work, a novel approach to this issue based on non-linear dynamical analysis of EEG signal was proposed. Multichannel EEG signals were recorded during five maintenance of wakefulness (MWT) and multiple sleep latency (MSLT) tests alternated throughout the day from patients suffering from sleep disordered breathing. A group of 20 patients with excessive daytime sleepiness (EDS) was compared with a group of 20 patients without daytime sleepiness (WDS), by analyzing 60-s EEG windows in waking state. Measures obtained from cross-mutual information function (CMIF) and auto-mutual-information function (AMIF) were calculated in the EEG. These functions permitted a quantification of the complexity properties of the EEG signal and the non-linear couplings between different zones of the scalp. Statistical differences between EDS and WDS groups were found in β band during MSLT events (p-value CMIF measures yielded sensitivity and specificity above 80% and AUC of ROC above 0.85 in classifying EDS and WDS patients. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

LIMO EEG: a toolbox for hierarchical LInear MOdeling of ElectroEncephaloGraphic data.

Science.gov (United States)

Pernet, Cyril R; Chauveau, Nicolas; Gaspar, Carl; Rousselet, Guillaume A

2011-01-01

Magnetic- and electric-evoked brain responses have traditionally been analyzed by comparing the peaks or mean amplitudes of signals from selected channels and averaged across trials. More recently, tools have been developed to investigate single trial response variability (e.g., EEGLAB) and to test differences between averaged evoked responses over the entire scalp and time dimensions (e.g., SPM, Fieldtrip). LIMO EEG is a Matlab toolbox (EEGLAB compatible) to analyse evoked responses over all space and time dimensions, while accounting for single trial variability using a simple hierarchical linear modelling of the data. In addition, LIMO EEG provides robust parametric tests, therefore providing a new and complementary tool in the analysis of neural evoked responses.

The MEG positron spectrometer

International Nuclear Information System (INIS)

Nishiguchi, Hajime

2007-01-01

We have been developing an innovative spectrometer for the MEG experiment at the Paul Scherrer Institute (PSI) in Switzerland. This experiment searches for a lepton flavour violating decay μ + →e + γ with a sensitivity of 10 -13 in order to explore the region predicted by supersymmetric extensions of the standard model. The MEG positron spectrometer consists of a specially designed superconducting solenoidal magnet with a highly graded field, an ultimate low-mass drift chamber system, and a precise time measuring counter system. This innovative positron spectrometer is described here focusing on the drift chamber system

Effective Connectivity of Cortical Sensorimotor Networks During Finger Movement Tasks: A Simultaneous fNIRS, fMRI, EEG Study.

Science.gov (United States)

Anwar, A R; Muthalib, M; Perrey, S; Galka, A; Granert, O; Wolff, S; Heute, U; Deuschl, G; Raethjen, J; Muthuraman, Muthuraman

2016-09-01

Recently, interest has been growing to understand the underlying dynamic directional relationship between simultaneously activated regions of the brain during motor task performance. Such directionality analysis (or effective connectivity analysis), based on non-invasive electrophysiological (electroencephalography-EEG) and hemodynamic (functional near infrared spectroscopy-fNIRS; and functional magnetic resonance imaging-fMRI) neuroimaging modalities can provide an estimate of the motor task-related information flow from one brain region to another. Since EEG, fNIRS and fMRI modalities achieve different spatial and temporal resolutions of motor-task related activation in the brain, the aim of this study was to determine the effective connectivity of cortico-cortical sensorimotor networks during finger movement tasks measured by each neuroimaging modality. Nine healthy subjects performed right hand finger movement tasks of different complexity (simple finger tapping-FT, simple finger sequence-SFS, and complex finger sequence-CFS). We focused our observations on three cortical regions of interest (ROIs), namely the contralateral sensorimotor cortex (SMC), the contralateral premotor cortex (PMC) and the contralateral dorsolateral prefrontal cortex (DLPFC). We estimated the effective connectivity between these ROIs using conditional Granger causality (GC) analysis determined from the time series signals measured by fMRI (blood oxygenation level-dependent-BOLD), fNIRS (oxygenated-O2Hb and deoxygenated-HHb hemoglobin), and EEG (scalp and source level analysis) neuroimaging modalities. The effective connectivity analysis showed significant bi-directional information flow between the SMC, PMC, and DLPFC as determined by the EEG (scalp and source), fMRI (BOLD) and fNIRS (O2Hb and HHb) modalities for all three motor tasks. However the source level EEG GC values were significantly greater than the other modalities. In addition, only the source level EEG showed a

Head and neck tumors and impaired mental function following scalp irradiation

International Nuclear Information System (INIS)

Modan, B.; Ron, E.; Werner, A.; Yaar, I.

1977-01-01

This is a second report of a comprehensive case-control study of 11,000 individuals subjected to scalp x-irradiation in childhood between 1949 and 1960. Follow up was conducted through the following national records: Tumor, Registry, Central Population Registry, Mental Health Registry, Nationwide High School Aptitude Test, Police, Ministry of Welfare and the Army. In addition, a sample of the cases and of the controls was brought in for clinical examinations, psychological testing and computerized EEG. The mean dose delivered to the brain, as determined by dosimetric studies, was 140r and to the thyroid 6-9r. Specific topics to be presented and discussed are as follows: an increased risk of head and neck tumors and the presence of a dose response relationship. The implication of the marked increase in risk for thyroid tumors, in view of the low dose delivered to this organ. Radiation effect on brain function as evidenced by a lower educational achievement, a lower basic intelligence level, somewhat impaired mental ability, and an increased rate of admissions to mental hospitals among cases, as compared to each of the two control groups, as well as the presence of a hyperactivity pattern on EEG

Long-term EEG in children.

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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.

Brain-computer interfaces current trends and applications

CERN Document Server

Azar, Ahmad

2015-01-01

The success of a BCI system depends as much on the system itself as on the user’s ability to produce distinctive EEG activity. BCI systems can be divided into two groups according to the placement of the electrodes used to detect and measure neurons firing in the brain. These groups are: invasive systems, electrodes are inserted directly into the cortex are used for single cell or multi unit recording, and electrocorticography (EcoG), electrodes are placed on the surface of the cortex (or dura); noninvasive systems, they are placed on the scalp and use electroencephalography (EEG) or magnetoencephalography (MEG) to detect neuron activity. The book is basically divided into three parts. The first part of the book covers the basic concepts and overviews of Brain Computer Interface. The second part describes new theoretical developments of BCI systems. The third part covers views on real applications of BCI systems.

Dissociable Decoding of Spatial Attention and Working Memory from EEG Oscillations and Sustained Potentials.

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Bae, Gi-Yeul; Luck, Steven J

2018-01-10

In human scalp EEG recordings, both sustained potentials and alpha-band oscillations are present during the delay period of working memory tasks and may therefore reflect the representation of information in working memory. However, these signals may instead reflect support mechanisms rather than the actual contents of memory. In particular, alpha-band oscillations have been tightly tied to spatial attention and may not reflect location-independent memory representations per se. To determine how sustained and oscillating EEG signals are related to attention and working memory, we attempted to decode which of 16 orientations was being held in working memory by human observers (both women and men). We found that sustained EEG activity could be used to decode the remembered orientation of a stimulus, even when the orientation of the stimulus varied independently of its location. Alpha-band oscillations also carried clear information about the location of the stimulus, but they provided little or no information about orientation independently of location. Thus, sustained potentials contain information about the object properties being maintained in working memory, consistent with previous evidence of a tight link between these potentials and working memory capacity. In contrast, alpha-band oscillations primarily carry location information, consistent with their link to spatial attention. SIGNIFICANCE STATEMENT Working memory plays a key role in cognition, and working memory is impaired in several neurological and psychiatric disorders. Previous research has suggested that human scalp EEG recordings contain signals that reflect the neural representation of information in working memory. However, to conclude that a neural signal actually represents the object being remembered, it is necessary to show that the signal contains fine-grained information about that object. Here, we show that sustained voltages in human EEG recordings contain fine-grained information about the

Scales on the scalp

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Jamil A

2013-05-01

Full Text Available A five-year-old boy presented with a six-week history of scales, flaking and crusting of the scalp. He had mild pruritus but no pain. He did not have a history of atopy and there were no pets at home. Examination of the scalp showed thick, yellowish dry crusts on the vertex and parietal areas and the hair was adhered to the scalp in clumps. There was non-scarring alopecia and mild erythema (Figure 1 & 2. There was no cervical or occipital lymphadenopathy. The patient’s nails and skin in other parts of the body were normal.

Wavelet-Based Artifact Identification and Separation Technique for EEG Signals during Galvanic Vestibular Stimulation

Science.gov (United States)

Adib, Mani; Cretu, Edmond

2013-01-01

We present a new method for removing artifacts in electroencephalography (EEG) records during Galvanic Vestibular Stimulation (GVS). The main challenge in exploiting GVS is to understand how the stimulus acts as an input to brain. We used EEG to monitor the brain and elicit the GVS reflexes. However, GVS current distribution throughout the scalp generates an artifact on EEG signals. We need to eliminate this artifact to be able to analyze the EEG signals during GVS. We propose a novel method to estimate the contribution of the GVS current in the EEG signals at each electrode by combining time-series regression methods with wavelet decomposition methods. We use wavelet transform to project the recorded EEG signal into various frequency bands and then estimate the GVS current distribution in each frequency band. The proposed method was optimized using simulated signals, and its performance was compared to well-accepted artifact removal methods such as ICA-based methods and adaptive filters. The results show that the proposed method has better performance in removing GVS artifacts, compared to the others. Using the proposed method, a higher signal to artifact ratio of −1.625 dB was achieved, which outperformed other methods such as ICA-based methods, regression methods, and adaptive filters. PMID:23956786

Wavelet-Based Artifact Identification and Separation Technique for EEG Signals during Galvanic Vestibular Stimulation

Directory of Open Access Journals (Sweden)

Mani Adib

2013-01-01

Full Text Available We present a new method for removing artifacts in electroencephalography (EEG records during Galvanic Vestibular Stimulation (GVS. The main challenge in exploiting GVS is to understand how the stimulus acts as an input to brain. We used EEG to monitor the brain and elicit the GVS reflexes. However, GVS current distribution throughout the scalp generates an artifact on EEG signals. We need to eliminate this artifact to be able to analyze the EEG signals during GVS. We propose a novel method to estimate the contribution of the GVS current in the EEG signals at each electrode by combining time-series regression methods with wavelet decomposition methods. We use wavelet transform to project the recorded EEG signal into various frequency bands and then estimate the GVS current distribution in each frequency band. The proposed method was optimized using simulated signals, and its performance was compared to well-accepted artifact removal methods such as ICA-based methods and adaptive filters. The results show that the proposed method has better performance in removing GVS artifacts, compared to the others. Using the proposed method, a higher signal to artifact ratio of −1.625 dB was achieved, which outperformed other methods such as ICA-based methods, regression methods, and adaptive filters.

Results of scalp cooling during anthracycline containing chemotherapy depend on scalp skin temperature

NARCIS (Netherlands)

Komen, M.M.; Smorenburg, C.H.; Nortier, J.W.; Ploeg, T. van der; Hurk, C.J. van den; Hoeven, J.J. van der

2016-01-01

OBJECTIVES: The success of scalp cooling in preventing or reducing chemotherapy induced alopecia (CIA) is highly variable between patients undergoing similar chemotherapy regimens. A decrease of the scalp skin temperature seems to be an important factor, but data on the optimum temperature reached

Auto-correlation in the motor/imaginary human EEG signals: A vision about the FDFA fluctuations.

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Gilney Figueira Zebende

Full Text Available In this paper we analyzed, by the FDFA root mean square fluctuation (rms function, the motor/imaginary human activity produced by a 64-channel electroencephalography (EEG. We utilized the Physionet on-line databank, a publicly available database of human EEG signals, as a standardized reference database for this study. Herein, we report the use of detrended fluctuation analysis (DFA method for EEG analysis. We show that the complex time series of the EEG exhibits characteristic fluctuations depending on the analyzed channel in the scalp-recorded EEG. In order to demonstrate the effectiveness of the proposed technique, we analyzed four distinct channels represented here by F332, F637 (frontal region of the head and P349, P654 (parietal region of the head. We verified that the amplitude of the FDFA rms function is greater for the frontal channels than for the parietal. To tabulate this information in a better way, we define and calculate the difference between FDFA (in log scale for the channels, thus defining a new path for analysis of EEG signals. Finally, related to the studied EEG signals, we obtain the auto-correlation exponent, αDFA by DFA method, that reveals self-affinity at specific time scale. Our results shows that this strategy can be applied to study the human brain activity in EEG processing.

Automatic reference selection for quantitative EEG interpretation: identification of diffuse/localised activity and the active earlobe reference, iterative detection of the distribution of EEG rhythms.

Science.gov (United States)

Wang, Bei; Wang, Xingyu; Ikeda, Akio; Nagamine, Takashi; Shibasaki, Hiroshi; Nakamura, Masatoshi

2014-01-01

EEG (Electroencephalograph) interpretation is important for the diagnosis of neurological disorders. The proper adjustment of the montage can highlight the EEG rhythm of interest and avoid false interpretation. The aim of this study was to develop an automatic reference selection method to identify a suitable reference. The results may contribute to the accurate inspection of the distribution of EEG rhythms for quantitative EEG interpretation. The method includes two pre-judgements and one iterative detection module. The diffuse case is initially identified by pre-judgement 1 when intermittent rhythmic waveforms occur over large areas along the scalp. The earlobe reference or averaged reference is adopted for the diffuse case due to the effect of the earlobe reference depending on pre-judgement 2. An iterative detection algorithm is developed for the localised case when the signal is distributed in a small area of the brain. The suitable averaged reference is finally determined based on the detected focal and distributed electrodes. The presented technique was applied to the pathological EEG recordings of nine patients. One example of the diffuse case is introduced by illustrating the results of the pre-judgements. The diffusely intermittent rhythmic slow wave is identified. The effect of active earlobe reference is analysed. Two examples of the localised case are presented, indicating the results of the iterative detection module. The focal and distributed electrodes are detected automatically during the repeating algorithm. The identification of diffuse and localised activity was satisfactory compared with the visual inspection. The EEG rhythm of interest can be highlighted using a suitable selected reference. The implementation of an automatic reference selection method is helpful to detect the distribution of an EEG rhythm, which can improve the accuracy of EEG interpretation during both visual inspection and automatic interpretation. Copyright © 2013 IPEM

A systematic study of head tissue inhomogeneity and anisotropy on EEG forward problem computing

International Nuclear Information System (INIS)

Bashar, M.R.; Li, Y.; Wen, P.

2010-01-01

Full text: In this study, we propose a stochastic method to analyze the effects of inhomogeneous anisotropic tissue conductivity on electroencephalogram (EEG) in forward computation. We apply this method to an inhomogeneous and anisotropic spherical human head model. We apply stochastic finite element method based on Legendre polynomials, Karhunen-Loeve expansion and stochastic Galerkin methods. We apply Volume and Wang's constraints to restrict the anisotropic conductivities for both the white matter (WM) and the skull tissue compartments. The EEGs resulting from deterministic and stochastic FEMs are compared using statistical measurement techniques. Based on these comparisons, we find that EEGs generated by incorporating WM and skull inhomogeneous anisotropic tissue properties individually result in an average of 56.5 and 57.5% relative errors, respectively. Incorporating these tissue properties for both layers together generate 43.5% average relative error. Inhomogeneous scalp tissue causes 27% average relative error and a full inhomogeneous anisotropic model brings in an average of 45.5% relative error. The study results demonstrate that the effects of inhomogeneous anisotropic tissue conductivity are significant on EEG.

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

OpenAIRE

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 ...

Neocortical Dynamics at Multiple Scales: EEG Standing Waves, Statistical Mechanics, and Physical Analogs

OpenAIRE

Ingber, Lester; Nunez, Paul L.

2010-01-01

The dynamic behavior of scalp potentials (EEG) is apparently due to some combination of global and local processes with important top-down and bottom-up interactions across spatial scales. In treating global mechanisms, we stress the importance of myelinated axon propagation delays and periodic boundary conditions in the cortical-white matter system, which is topologically close to a spherical shell. By contrast, the proposed local mechanisms are multiscale interactions between cortical colum...

Enhancement of Neocortical-Medial Temporal EEG Correlations during Non-REM Sleep

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Nikolai Axmacher

2008-01-01

Full Text Available Interregional interactions of oscillatory activity are crucial for the integrated processing of multiple brain regions. However, while the EEG in virtually all brain structures passes through substantial modifications during sleep, it is still an open question whether interactions between neocortical and medial temporal EEG oscillations also depend on the state of alertness. Several previous studies in animals and humans suggest that hippocampal-neocortical interactions crucially depend on the state of alertness (i.e., waking state or sleep. Here, we analyzed scalp and intracranial EEG recordings during sleep and waking state in epilepsy patients undergoing presurgical evaluation. We found that the amplitudes of oscillations within the medial temporal lobe and the neocortex were more closely correlated during sleep, in particular during non-REM sleep, than during waking state. Possibly, the encoding of novel sensory inputs, which mainly occurs during waking state, requires that medial temporal dynamics are rather independent from neocortical dynamics, while the consolidation of memories during sleep may demand closer interactions between MTL and neocortex.

EEG entropy measures indicate decrease of cortical information processing in Disorders of Consciousness.

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Thul, Alexander; Lechinger, Julia; Donis, Johann; Michitsch, Gabriele; Pichler, Gerald; Kochs, Eberhard F; Jordan, Denis; Ilg, Rüdiger; Schabus, Manuel

2016-02-01

Clinical assessments that rely on behavioral responses to differentiate Disorders of Consciousness are at times inapt because of some patients' motor disabilities. To objectify patients' conditions of reduced consciousness the present study evaluated the use of electroencephalography to measure residual brain activity. We analyzed entropy values of 18 scalp EEG channels of 15 severely brain-damaged patients with clinically diagnosed Minimally-Conscious-State (MCS) or Unresponsive-Wakefulness-Syndrome (UWS) and compared the results to a sample of 24 control subjects. Permutation entropy (PeEn) and symbolic transfer entropy (STEn), reflecting information processes in the EEG, were calculated for all subjects. Participants were tested on a modified active own-name paradigm to identify correlates of active instruction following. PeEn showed reduced local information content in the EEG in patients, that was most pronounced in UWS. STEn analysis revealed altered directed information flow in the EEG of patients, indicating impaired feed-backward connectivity. Responses to auditory stimulation yielded differences in entropy measures, indicating reduced information processing in MCS and UWS. Local EEG information content and information flow are affected in Disorders of Consciousness. This suggests local cortical information capacity and feedback information transfer as neural correlates of consciousness. The utilized EEG entropy analyses were able to relate to patient groups with different Disorders of Consciousness. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Fetal scalp blood sampling during labor

DEFF Research Database (Denmark)

Chandraharan, Edwin; Wiberg, Nana

2014-01-01

Fetal cardiotocography is characterized by low specificity; therefore, in an attempt to ensure fetal well-being, fetal scalp blood sampling has been recommended by most obstetric societies in the case of a non-reassuring cardiotocography. The scientific agreement on the evidence for using fetal...... scalp blood sampling to decrease the rate of operative delivery for fetal distress is ambiguous. Based on the same studies, a Cochrane review states that fetal scalp blood sampling increases the rate of instrumental delivery while decreasing neonatal acidosis, whereas the National Institute of Health...... and Clinical Excellence guideline considers that fetal scalp blood sampling decreases instrumental delivery without differences in other outcome variables. The fetal scalp is supplied by vessels outside the skull below the level of the cranial vault, which is likely to be compressed during contractions...

A dry EEG-system for scientific research and brain-computer interfaces

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Thorsten Oliver Zander

2011-05-01

Full Text Available Although it ranks among the oldest tools in neuroscientific research, electroencephalography (EEG still forms the method of choice in a wide variety of clinical and research applications. In the context of Brain-Computer Interfacing (BCI, EEG recently has become a tool to enhance Human-Machine Interaction (HMI. EEG could be employed in a wider range of environments, especially for the use of BCI systems in a clinical context or at the homes of patients. However, the application of EEG in these contexts is impeded by the cumbersome preparation of the electrodes with conductive gel that is necessary to lower the impedance between electrodes and scalp. Dry electrodes could provide a solution to this barrier and allow for EEG applications outside the laboratory. In addition, dry electrodes may reduce the time needed for neurological exams in clinical practice. This study evaluates a prototype of a three-channel dry electrode EEG system, comparing it to state-of-the-art conventional EEG electrodes. Two experimental paradigms were used: first, Event-Related Potentials (ERP were investigated with a variant of the oddball paradigm. Second, features of the frequency domain were compared by a paradigm inducing occipital alpha. Furthermore, both paradigms were used to evaluate BCI classification accuracies of both EEG systems. Amplitude and temporal structure of ERPs as well as features in the frequency domain did not differ significantly between the EEG systems. BCI classification accuracies were equally high in both systems when the frequency domain was considered. With respect to the oddball classification accuracy, there were slight differences between the wet and dry electrode systems. We conclude that the tested dry electrodes were capable to detect EEG signals with good quality and that these signals can be used for research or BCI applications. Easy to handle electrodes may help to foster the use of EEG among a wider range of potential users.

[Teaching design of mastering scalp acupuncture fast].

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Li, Jie; Niu, Wenmin

2016-05-01

Scalp acupuncture is a method of treating whole-body diseases. The author takes the easy positioning of scalp acupuncture as starting point, covers the positioning of scalp acupuncture and needle insertion points, acupuncture manipulation and the selection of acupoints, so as to introduce the design of teaching the international standardized scalp acupuncture with texts and illustrations. The positions of scalp acupuncture are 4 lines in frontal area, 5 lines in parietal area, 2 lines in temporal area and 3 lines in occipital area. The needle insertion angle is 30° to the skin. Acupoints can be selected crossly and correspondingly in clinic.

Attentional Selection in a Cocktail Party Environment Can Be Decoded from Single-Trial EEG

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O'Sullivan, James A.; Power, Alan J.; Mesgarani, Nima; Rajaram, Siddharth; Foxe, John J.; Shinn-Cunningham, Barbara G.; Slaney, Malcolm; Shamma, Shihab A.; Lalor, Edmund C.

2015-01-01

How humans solve the cocktail party problem remains unknown. However, progress has been made recently thanks to the realization that cortical activity tracks the amplitude envelope of speech. This has led to the development of regression methods for studying the neurophysiology of continuous speech. One such method, known as stimulus-reconstruction, has been successfully utilized with cortical surface recordings and magnetoencephalography (MEG). However, the former is invasive and gives a relatively restricted view of processing along the auditory hierarchy, whereas the latter is expensive and rare. Thus it would be extremely useful for research in many populations if stimulus-reconstruction was effective using electroencephalography (EEG), a widely available and inexpensive technology. Here we show that single-trial (≈60 s) unaveraged EEG data can be decoded to determine attentional selection in a naturalistic multispeaker environment. Furthermore, we show a significant correlation between our EEG-based measure of attention and performance on a high-level attention task. In addition, by attempting to decode attention at individual latencies, we identify neural processing at ∼200 ms as being critical for solving the cocktail party problem. These findings open up new avenues for studying the ongoing dynamics of cognition using EEG and for developing effective and natural brain–computer interfaces. PMID:24429136

[Effectiveness of scalp cooling in chemotherapy].

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Poder, Thomas G; He, Jie; Lemieux, Renald

2011-10-01

The main objectives of this literature review are to determine if scalp cooling is efficient and safe, if there are side effects and if the patients' quality of life improves. In terms of effectiveness, scalp cooling seems to get good performance in its aim to prevent hair loss in patients receiving chemotherapy. The weighted average results of all identified studies indicate that this technology allows for 63.5% of patients to have a good preservation of their hair. In studies with a group of control, the weighted rates of good preservation of the hair are 50.6% with scalp cooling and 16.3% without. From the standpoint of safety technology, the main risk is that of scalp metastases. However, no study has successfully demonstrated a statistically significant difference between groups of patients receiving chemotherapy with or without scalp cooling.

Long noncoding RNA-MEG3 is involved in diabetes mellitus-related microvascular dysfunction

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Qiu, Gui-Zhen [Department of Health, Linyi People' s Hospital, Shandong University, Shandong (China); Tian, Wei [Department of Nursing, Linyi Oncosurgical Hospital, Shandong (China); Fu, Hai-Tao [Department of Ophthalmology, Linyi People' s Hospital, Shandong University, Shandong (China); Li, Chao-Peng, E-mail: lcpcn@163.com [Eye Institute of Xuzhou, Jiangsu (China); Liu, Ban, E-mail: liuban@126.com [Department of Cardiology, Shanghai Tenth People' s Hospital, Tongji University School of Medicine, Shanghai (China)

2016-02-26

Microvascular dysfunction is an important characteristic of diabetic retinopathy. Long non-coding RNAs (lncRNAs) play important roles in diverse biological processes. In this study, we investigated the role of lncRNA-MEG3 in diabetes-related microvascular dysfunction. We show that MEG3 expression level is significantly down-regulated in the retinas of STZ-induced diabetic mice, and endothelial cells upon high glucose and oxidative stress. MEG3 knockdown aggravates retinal vessel dysfunction in vivo, as shown by serious capillary degeneration, and increased microvascular leakage and inflammation. MEG3 knockdown also regulates retinal endothelial cell proliferation, migration, and tube formation in vitro. The role of MEG3 in endothelial cell function is mainly mediated by the activation of PI3k/Akt signaling. MEG3 up-regulation may serve as a therapeutic strategy for treating diabetes-related microvascular complications. - Highlights: • LncRNA-MEG3 level is down-regulated upon diabetic stress. • MEG3 knockdown aggravates retinal vascular dysfunction in vivo. • MEG3 regulates retinal endothelial cell function in vitro. • MEG3 regulates endothelial cell function through PI3k/Akt signaling.

Long noncoding RNA-MEG3 is involved in diabetes mellitus-related microvascular dysfunction

International Nuclear Information System (INIS)

Qiu, Gui-Zhen; Tian, Wei; Fu, Hai-Tao; Li, Chao-Peng; Liu, Ban

2016-01-01

Microvascular dysfunction is an important characteristic of diabetic retinopathy. Long non-coding RNAs (lncRNAs) play important roles in diverse biological processes. In this study, we investigated the role of lncRNA-MEG3 in diabetes-related microvascular dysfunction. We show that MEG3 expression level is significantly down-regulated in the retinas of STZ-induced diabetic mice, and endothelial cells upon high glucose and oxidative stress. MEG3 knockdown aggravates retinal vessel dysfunction in vivo, as shown by serious capillary degeneration, and increased microvascular leakage and inflammation. MEG3 knockdown also regulates retinal endothelial cell proliferation, migration, and tube formation in vitro. The role of MEG3 in endothelial cell function is mainly mediated by the activation of PI3k/Akt signaling. MEG3 up-regulation may serve as a therapeutic strategy for treating diabetes-related microvascular complications. - Highlights: • LncRNA-MEG3 level is down-regulated upon diabetic stress. • MEG3 knockdown aggravates retinal vascular dysfunction in vivo. • MEG3 regulates retinal endothelial cell function in vitro. • MEG3 regulates endothelial cell function through PI3k/Akt signaling.

Magnetoencephalography for the detection of intervention effects of a specific nutrient combination in patients with mild Alzheimer’s disease: Results from an exploratory double blind randomised controlled study

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Elisabeth Catharina Van Straaten

2016-10-01

Full Text Available Synaptic loss is an early pathological finding in Alzheimer’s disease (AD and correlates with memory impairment. Changes in macroscopic brain activity measured with electro- and magnetoencephalography (EEG and MEG in AD indicate synaptic changes and may therefore serve as markers of intervention effects in clinical trials. EEG peak frequency and functional networks have shown, in addition to improved memory performance, to be sensitive to detect an intervention effect in mild AD patients of the medical food Souvenaid containing the specific nutrient combination Fortasyn® Connect, which is designed to enhance synapse formation and function. Here, we explore the value of MEG, with higher spatial resolution than EEG, in identifying intervention effects of the nutrient combination by comparing MEG spectral measures, functional connectivity and – networks between an intervention and a control group. Quantitative markers describing spectral properties, functional connectivity and graph theoretical aspects of MEG from the exploratory 24-week, double blind, randomized controlled Souvenir II MEG sub-study (NTR1975, http://www.trialregister.nl in drug-naïve patients with mild AD were compared between a test group (n=27, receiving Souvenaid, and a control group (n=28, receiving an isocaloric control product. The groups were unbalanced at screening with respect to Mini-Mental State Examination (MMSE. Peak frequencies of MEG were compared to EEG peak frequencies, recorded in the same patients at similar time points, were compared with respect to sensitivity to intervention effects. No consistent statistically significant intervention effects were detected. In addition, we found no difference in sensitivity between MEG and EEG peak frequency. This exploratory study could not unequivocally establish the value of MEG in detecting interventional effects on brain activity, possibly due to small sample size and unbalanced study groups. We found no indication

Magnetoencephalography for the Detection of Intervention Effects of a Specific Nutrient Combination in Patients with Mild Alzheimer's Disease: Results from an Exploratory Double-Blind, Randomized, Controlled Study.

Science.gov (United States)

van Straaten, Elisabeth C W; de Waal, Hanneke; Lansbergen, Marieke M; Scheltens, Philip; Maestu, Fernando; Nowak, Rafal; Hillebrand, Arjan; Stam, Cornelis J

2016-01-01

Synaptic loss is an early pathological finding in Alzheimer's disease (AD) and correlates with memory impairment. Changes in macroscopic brain activity measured with electro- and magnetoencephalography (EEG and MEG) in AD indicate synaptic changes and may therefore serve as markers of intervention effects in clinical trials. EEG peak frequency and functional networks have shown, in addition to improved memory performance, to be sensitive to detect an intervention effect in mild AD patients of the medical food Souvenaid containing the specific nutrient combination Fortasyn ® Connect, which is designed to enhance synapse formation and function. Here, we explore the value of MEG, with higher spatial resolution than EEG, in identifying intervention effects of the nutrient combination by comparing MEG spectral measures, functional connectivity, and networks between an intervention and a control group. Quantitative markers describing spectral properties, functional connectivity, and graph theoretical aspects of MEG from the exploratory 24-week, double-blind, randomized, controlled Souvenir II MEG sub-study (NTR1975, http://www.trialregister.nl) in drug naïve patients with mild AD were compared between a test group ( n  = 27), receiving Souvenaid, and a control group ( n  = 28), receiving an isocaloric control product. The groups were unbalanced at screening with respect to Mini-Mental State Examination. Peak frequencies of MEG were compared with EEG peak frequencies, recorded in the same patients at similar time points, were compared with respect to sensitivity to intervention effects. No consistent statistically significant intervention effects were detected. In addition, we found no difference in sensitivity between MEG and EEG peak frequency. This exploratory study could not unequivocally establish the value of MEG in detecting interventional effects on brain activity, possibly due to small sample size and unbalanced study groups. We found no indication that

Magnetoencephalography for the Detection of Intervention Effects of a Specific Nutrient Combination in Patients with Mild Alzheimer’s Disease: Results from an Exploratory Double-Blind, Randomized, Controlled Study

Science.gov (United States)

van Straaten, Elisabeth C. W.; de Waal, Hanneke; Lansbergen, Marieke M.; Scheltens, Philip; Maestu, Fernando; Nowak, Rafal; Hillebrand, Arjan; Stam, Cornelis J.

2016-01-01

Synaptic loss is an early pathological finding in Alzheimer’s disease (AD) and correlates with memory impairment. Changes in macroscopic brain activity measured with electro- and magnetoencephalography (EEG and MEG) in AD indicate synaptic changes and may therefore serve as markers of intervention effects in clinical trials. EEG peak frequency and functional networks have shown, in addition to improved memory performance, to be sensitive to detect an intervention effect in mild AD patients of the medical food Souvenaid containing the specific nutrient combination Fortasyn® Connect, which is designed to enhance synapse formation and function. Here, we explore the value of MEG, with higher spatial resolution than EEG, in identifying intervention effects of the nutrient combination by comparing MEG spectral measures, functional connectivity, and networks between an intervention and a control group. Quantitative markers describing spectral properties, functional connectivity, and graph theoretical aspects of MEG from the exploratory 24-week, double-blind, randomized, controlled Souvenir II MEG sub-study (NTR1975, http://www.trialregister.nl) in drug naïve patients with mild AD were compared between a test group (n = 27), receiving Souvenaid, and a control group (n = 28), receiving an isocaloric control product. The groups were unbalanced at screening with respect to Mini-Mental State Examination. Peak frequencies of MEG were compared with EEG peak frequencies, recorded in the same patients at similar time points, were compared with respect to sensitivity to intervention effects. No consistent statistically significant intervention effects were detected. In addition, we found no difference in sensitivity between MEG and EEG peak frequency. This exploratory study could not unequivocally establish the value of MEG in detecting interventional effects on brain activity, possibly due to small sample size and unbalanced study groups. We found no indication that

A realistic multimodal modeling approach for the evaluation of distributed source analysis: application to sLORETA

Science.gov (United States)

Cosandier-Rimélé, D.; Ramantani, G.; Zentner, J.; Schulze-Bonhage, A.; Dümpelmann, M.

2017-10-01

Objective. Electrical source localization (ESL) deriving from scalp EEG and, in recent years, from intracranial EEG (iEEG), is an established method in epilepsy surgery workup. We aimed to validate the distributed ESL derived from scalp EEG and iEEG, particularly regarding the spatial extent of the source, using a realistic epileptic spike activity simulator. Approach. ESL was applied to the averaged scalp EEG and iEEG spikes of two patients with drug-resistant structural epilepsy. The ESL results for both patients were used to outline the location and extent of epileptic cortical patches, which served as the basis for designing a spatiotemporal source model. EEG signals for both modalities were then generated for different anatomic locations and spatial extents. ESL was subsequently performed on simulated signals with sLORETA, a commonly used distributed algorithm. ESL accuracy was quantitatively assessed for iEEG and scalp EEG. Main results. The source volume was overestimated by sLORETA at both EEG scales, with the error increasing with source size, particularly for iEEG. For larger sources, ESL accuracy drastically decreased, and reconstruction volumes shifted to the center of the head for iEEG, while remaining stable for scalp EEG. Overall, the mislocalization of the reconstructed source was more pronounced for iEEG. Significance. We present a novel multiscale framework for the evaluation of distributed ESL, based on realistic multiscale EEG simulations. Our findings support that reconstruction results for scalp EEG are often more accurate than for iEEG, owing to the superior 3D coverage of the head. Particularly the iEEG-derived reconstruction results for larger, widespread generators should be treated with caution.

A realistic multimodal modeling approach for the evaluation of distributed source analysis: application to sLORETA.

Science.gov (United States)

Cosandier-Rimélé, D; Ramantani, G; Zentner, J; Schulze-Bonhage, A; Dümpelmann, M

2017-10-01

Electrical source localization (ESL) deriving from scalp EEG and, in recent years, from intracranial EEG (iEEG), is an established method in epilepsy surgery workup. We aimed to validate the distributed ESL derived from scalp EEG and iEEG, particularly regarding the spatial extent of the source, using a realistic epileptic spike activity simulator. ESL was applied to the averaged scalp EEG and iEEG spikes of two patients with drug-resistant structural epilepsy. The ESL results for both patients were used to outline the location and extent of epileptic cortical patches, which served as the basis for designing a spatiotemporal source model. EEG signals for both modalities were then generated for different anatomic locations and spatial extents. ESL was subsequently performed on simulated signals with sLORETA, a commonly used distributed algorithm. ESL accuracy was quantitatively assessed for iEEG and scalp EEG. The source volume was overestimated by sLORETA at both EEG scales, with the error increasing with source size, particularly for iEEG. For larger sources, ESL accuracy drastically decreased, and reconstruction volumes shifted to the center of the head for iEEG, while remaining stable for scalp EEG. Overall, the mislocalization of the reconstructed source was more pronounced for iEEG. We present a novel multiscale framework for the evaluation of distributed ESL, based on realistic multiscale EEG simulations. Our findings support that reconstruction results for scalp EEG are often more accurate than for iEEG, owing to the superior 3D coverage of the head. Particularly the iEEG-derived reconstruction results for larger, widespread generators should be treated with caution.

Music and the brain - design of an MEG compatible piano.

Science.gov (United States)

Chacon-Castano, Julian; Rathbone, Daniel R; Hoffman, Rachel; Heng Yang; Pantazis, Dimitrios; Yang, Jason; Hornberger, Erik; Hanumara, Nevan C

2017-07-01

Magnetoencephalography (MEG) neuroimaging has been used to study subjects' responses when listening to music, but research into the effects of playing music has been limited by the lack of MEG compatible instruments that can operate in a magnetically shielded environment without creating electromagnetic interference. This paper describes the design and preliminary testing of an MEG compatible piano keyboard with 25 full size keys that employs a novel 3-state optical encoder design and electronics to provide realistic velocity-controlled volume modulation. This instrument will allow researchers to study musical performance on a finer timescale than fMRI and enable a range of MEG studies.

Issues and considerations for using the scalp surface Laplacian in EEG/ERP research: A tutorial review

Science.gov (United States)

Kayser, Jürgen; Tenke, Craig E.

2015-01-01

Despite the recognition that the surface Laplacian may counteract adverse effects of volume conduction and recording reference for surface potential data, electrophysiology as a discipline has been reluctant to embrace this approach for data analysis. The reasons for such hesitation are manifold but often involve unfamiliarity with the nature of the underlying transformation, as well as intimidation by a perceived mathematical complexity, and concerns of signal loss, dense electrode array requirements, or susceptibility to noise. We revisit the pitfalls arising from volume conduction and the mandated arbitrary choice of EEG reference, describe the basic principle of the surface Laplacian transform in an intuitive fashion, and exemplify the differences between common reference schemes (nose, linked mastoids, average) and the surface Laplacian for frequently-measured EEG spectra (theta, alpha) and standard event-related potential (ERP) components, such as N1 or P3. We specifically review common reservations against the universal use of the surface Laplacian, which can be effectively addressed by employing spherical spline interpolations with an appropriate selection of the spline flexibility parameter and regularization constant. We argue from a pragmatic perspective that not only are these reservations unfounded but that the continued predominant use of surface potentials poses a considerable impediment on the progress of EEG and ERP research. PMID:25920962

Effects of skull thickness, anisotropy, and inhomogeneity on forward EEG/ERP computations using a spherical three-dimensional resistor mesh model.

Science.gov (United States)

Chauveau, Nicolas; Franceries, Xavier; Doyon, Bernard; Rigaud, Bernard; Morucci, Jean Pierre; Celsis, Pierre

2004-02-01

Bone thickness, anisotropy, and inhomogeneity have been reported to induce important variations in electroencephalogram (EEG) scalp potentials. To study this effect, we used an original three-dimensional (3-D) resistor mesh model described in spherical coordinates, consisting of 67,464 elements and 22,105 nodes arranged in 36 different concentric layers. After validation of the model by comparison with the analytic solution, potential variations induced by geometric and electrical skull modifications were investigated at the surface in the dipole plane and along the dipole axis, for several eccentricities and bone thicknesses. The resistor mesh permits one to obtain various configurations, as local modifications are introduced very easily. This has allowed several head models to be designed to study the effects of skull properties (thickness, anisotropy, and heterogeneity) on scalp surface potentials. Results show a decrease of potentials in bone, depending on bone thickness, and a very small decrease through the scalp layer. Nevertheless, similar scalp potentials can be obtained using either a thick scalp layer and a thin skull layer, and vice versa. It is thus important to take into account skull and scalp thicknesses, because the drop of potential in bone depends on both. The use of three different layers for skull instead of one leads to small differences in potential values and patterns. In contrast, the introduction of a hole in the skull highly increases the maximum potential value (by a factor of 11.5 in our case), because of the absence of potential drop in the corresponding volume. The inverse solution without any a priori knowledge indicates that the model with the hole gives the largest errors in both position and dipolar moment. Our results indicate that the resistor mesh model can be used as a robust and user-friendly simulation tool in EEG or event-related potentials. It makes it possible to build up real head models directly from anatomic magnetic

Radiation therapy for angiosarcoma of the scalp: treatment outcomes of total scalp irradiation with X-rays and electrons.

Science.gov (United States)

Hata, Masaharu; Wada, Hidefumi; Ogino, Ichiro; Omura, Motoko; Koike, Izumi; Tayama, Yoshibumi; Odagiri, Kazumasa; Kasuya, Takeo; Inoue, Tomio

2014-10-01

Wide surgical excision is the standard treatment for angiosarcoma of the scalp, but many patients are inoperable. Therefore, we investigated the outcome of radiation therapy for angiosarcoma of the scalp. Seventeen patients with angiosarcoma of the scalp underwent radiation therapy with total scalp irradiation. Four patients had cervical lymph node metastases, but none had distant metastases. A median initial dose of 50 Gy in 25 fractions was delivered to the entire scalp. Subsequently, local radiation boost to the tumor sites achieved a median total dose of 70 Gy in 35 fractions. Fourteen of the 17 patients developed recurrences during the median follow-up period of 14 months after radiation therapy; 7 had recurrences in the scalp, including primary tumor progression in 2 patients and new disease in 5, and 12 patients developed distant metastases. The primary progression-free, scalp relapse-free, and distant metastasis-free rates were 86, 67, and 38 % at 1 year and 86, 38, and 16 % at 3 years, respectively. Thirteen patients died; the overall and cause-specific survival rates were both 73 % at 1 year and 23 and 44 % at 3 years, respectively. The median survival time was 16 months. There were no therapy-related toxicities ≥ grade 3. Total scalp irradiation is safe and effective for local tumor control, but a dose of ≤ 50 Gy in conventional fractions may be insufficient to eradicate microscopic tumors. For gross tumors, a total dose of 70 Gy, and > 70 Gy for tumors with deep invasion, is recommended.

MEG source localization of spatially extended generators of epileptic activity: comparing entropic and hierarchical bayesian approaches.

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Chowdhury, Rasheda Arman; Lina, Jean Marc; Kobayashi, Eliane; Grova, Christophe

2013-01-01

Localizing the generators of epileptic activity in the brain using Electro-EncephaloGraphy (EEG) or Magneto-EncephaloGraphy (MEG) signals is of particular interest during the pre-surgical investigation of epilepsy. Epileptic discharges can be detectable from background brain activity, provided they are associated with spatially extended generators. Using realistic simulations of epileptic activity, this study evaluates the ability of distributed source localization methods to accurately estimate the location of the generators and their sensitivity to the spatial extent of such generators when using MEG data. Source localization methods based on two types of realistic models have been investigated: (i) brain activity may be modeled using cortical parcels and (ii) brain activity is assumed to be locally smooth within each parcel. A Data Driven Parcellization (DDP) method was used to segment the cortical surface into non-overlapping parcels and diffusion-based spatial priors were used to model local spatial smoothness within parcels. These models were implemented within the Maximum Entropy on the Mean (MEM) and the Hierarchical Bayesian (HB) source localization frameworks. We proposed new methods in this context and compared them with other standard ones using Monte Carlo simulations of realistic MEG data involving sources of several spatial extents and depths. Detection accuracy of each method was quantified using Receiver Operating Characteristic (ROC) analysis and localization error metrics. Our results showed that methods implemented within the MEM framework were sensitive to all spatial extents of the sources ranging from 3 cm(2) to 30 cm(2), whatever were the number and size of the parcels defining the model. To reach a similar level of accuracy within the HB framework, a model using parcels larger than the size of the sources should be considered.

MEG source localization of spatially extended generators of epileptic activity: comparing entropic and hierarchical bayesian approaches.

Directory of Open Access Journals (Sweden)

Rasheda Arman Chowdhury

Full Text Available Localizing the generators of epileptic activity in the brain using Electro-EncephaloGraphy (EEG or Magneto-EncephaloGraphy (MEG signals is of particular interest during the pre-surgical investigation of epilepsy. Epileptic discharges can be detectable from background brain activity, provided they are associated with spatially extended generators. Using realistic simulations of epileptic activity, this study evaluates the ability of distributed source localization methods to accurately estimate the location of the generators and their sensitivity to the spatial extent of such generators when using MEG data. Source localization methods based on two types of realistic models have been investigated: (i brain activity may be modeled using cortical parcels and (ii brain activity is assumed to be locally smooth within each parcel. A Data Driven Parcellization (DDP method was used to segment the cortical surface into non-overlapping parcels and diffusion-based spatial priors were used to model local spatial smoothness within parcels. These models were implemented within the Maximum Entropy on the Mean (MEM and the Hierarchical Bayesian (HB source localization frameworks. We proposed new methods in this context and compared them with other standard ones using Monte Carlo simulations of realistic MEG data involving sources of several spatial extents and depths. Detection accuracy of each method was quantified using Receiver Operating Characteristic (ROC analysis and localization error metrics. Our results showed that methods implemented within the MEM framework were sensitive to all spatial extents of the sources ranging from 3 cm(2 to 30 cm(2, whatever were the number and size of the parcels defining the model. To reach a similar level of accuracy within the HB framework, a model using parcels larger than the size of the sources should be considered.

Treatment of multiple scalp cylindroma

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Radmilo Rončević

2016-07-01

Full Text Available Cylindroma is a rare, benign adnexal tumor of the skin. The most frequent tumor location is the head, especially the scalp, and neck area. This type of tumor can occur as solitary or multiple tumors. Tumor diagnosis is relatively easy and is based on clinical findings and biopsy. The therapy of choice is surgical excision with parts or entire scalp excision depending on whether it is solitary or multiple tumor. We presented a 65-year-old male patient with multiple scalp tumors of 0.5–6 cm in diameter. An entire scalp excision was performed and the postoperative wounds (i.e., the periosteum of the skull and the fascia galea were covered with free skin graft of partial thickness. In order to prevent profuse bleeding, we placed a tourniquet around his head and performed bilateral temporary ligature of temporal artery prior to surgery. During the nine-year follow-up, there were no new tumors or tumor recurrence reported.

Source-based neurofeedback methods using EEG recordings: training altered brain activity in a functional brain source derived from blind source separation

Science.gov (United States)

White, David J.; Congedo, Marco; Ciorciari, Joseph

2014-01-01

A developing literature explores the use of neurofeedback in the treatment of a range of clinical conditions, particularly ADHD and epilepsy, whilst neurofeedback also provides an experimental tool for studying the functional significance of endogenous brain activity. A critical component of any neurofeedback method is the underlying physiological signal which forms the basis for the feedback. While the past decade has seen the emergence of fMRI-based protocols training spatially confined BOLD activity, traditional neurofeedback has utilized a small number of electrode sites on the scalp. As scalp EEG at a given electrode site reflects a linear mixture of activity from multiple brain sources and artifacts, efforts to successfully acquire some level of control over the signal may be confounded by these extraneous sources. Further, in the event of successful training, these traditional neurofeedback methods are likely influencing multiple brain regions and processes. The present work describes the use of source-based signal processing methods in EEG neurofeedback. The feasibility and potential utility of such methods were explored in an experiment training increased theta oscillatory activity in a source derived from Blind Source Separation (BSS) of EEG data obtained during completion of a complex cognitive task (spatial navigation). Learned increases in theta activity were observed in two of the four participants to complete 20 sessions of neurofeedback targeting this individually defined functional brain source. Source-based EEG neurofeedback methods using BSS may offer important advantages over traditional neurofeedback, by targeting the desired physiological signal in a more functionally and spatially specific manner. Having provided preliminary evidence of the feasibility of these methods, future work may study a range of clinically and experimentally relevant brain processes where individual brain sources may be targeted by source-based EEG neurofeedback. PMID

Cerebral blood flow during paroxysmal EEG activation induced by sleep in patients with complex partial seizures

International Nuclear Information System (INIS)

Gozukirmizi, E.; Meyer, J.S.; Okabe, T.; Amano, T.; Mortel, K.; Karacan, I.

1982-01-01

Cerebral blood flow (CBF) measurements were combined with sleep polysomnography in nine patients with complex partial seizures. Two methods were used: the 133Xe method for measuring regional (rCBF) and the stable xenon CT method for local (LCBF). Compared to nonepileptic subjects, who show diffuse CBF decreases during stages I-II, non-REM sleep onset, patients with complex partial seizures show statistically significant increases in CBF which are maximal in regions where the EEG focus is localized and are predominantly seen in one temporal region but are also propagated to other cerebral areas. Both CBF methods gave comparable results, but greater statistical significance was achieved by stable xenon CT methodology. CBF increases are more diffuse than predicted by EEG paroxysmal activity recorded from scalp electrodes. An advantage of the 133Xe inhalation method was achievement of reliable data despite movement of the head. This was attributed to the use of a helmet which maintained the probes approximated to the scalp. Disadvantages were poor resolution (7 cm3) and two-dimensional information. The advantage of stable xenon CT method is excellent resolution (80 mm3) in three dimensions, but a disadvantage is that movement of the head in patients with seizure disorders may limit satisfactory measurements

Issues and considerations for using the scalp surface Laplacian in EEG/ERP research: A tutorial review.

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Kayser, Jürgen; Tenke, Craig E

2015-09-01

Despite the recognition that the surface Laplacian may counteract adverse effects of volume conduction and recording reference for surface potential data, electrophysiology as a discipline has been reluctant to embrace this approach for data analysis. The reasons for such hesitation are manifold but often involve unfamiliarity with the nature of the underlying transformation, as well as intimidation by a perceived mathematical complexity, and concerns of signal loss, dense electrode array requirements, or susceptibility to noise. We revisit the pitfalls arising from volume conduction and the mandated arbitrary choice of EEG reference, describe the basic principle of the surface Laplacian transform in an intuitive fashion, and exemplify the differences between common reference schemes (nose, linked mastoids, average) and the surface Laplacian for frequently-measured EEG spectra (theta, alpha) and standard event-related potential (ERP) components, such as N1 or P3. We specifically review common reservations against the universal use of the surface Laplacian, which can be effectively addressed by employing spherical spline interpolations with an appropriate selection of the spline flexibility parameter and regularization constant. We argue from a pragmatic perspective that not only are these reservations unfounded but that the continued predominant use of surface potentials poses a considerable impediment on the progress of EEG and ERP research. Copyright © 2015 Elsevier B.V. All rights reserved.

Scalp Psoriasis vs. Seborrheic Dermatitis: What's the Difference?

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... does a doctor tell the difference between scalp psoriasis and seborrheic dermatitis of the scalp? Answers from ... such as pitting. Compare signs and symptoms Scalp psoriasis Red skin covered with flakes and silvery scales ...

Multi-Class Motor Imagery EEG Decoding for Brain-Computer Interfaces

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Wang, Deng; Miao, Duoqian; Blohm, Gunnar

2012-01-01

Recent studies show that scalp electroencephalography (EEG) as a non-invasive interface has great potential for brain-computer interfaces (BCIs). However, one factor that has limited practical applications for EEG-based BCI so far is the difficulty to decode brain signals in a reliable and efficient way. This paper proposes a new robust processing framework for decoding of multi-class motor imagery (MI) that is based on five main processing steps. (i) Raw EEG segmentation without the need of visual artifact inspection. (ii) Considering that EEG recordings are often contaminated not just by electrooculography (EOG) but also other types of artifacts, we propose to first implement an automatic artifact correction method that combines regression analysis with independent component analysis for recovering the original source signals. (iii) The significant difference between frequency components based on event-related (de-) synchronization and sample entropy is then used to find non-contiguous discriminating rhythms. After spectral filtering using the discriminating rhythms, a channel selection algorithm is used to select only relevant channels. (iv) Feature vectors are extracted based on the inter-class diversity and time-varying dynamic characteristics of the signals. (v) Finally, a support vector machine is employed for four-class classification. We tested our proposed algorithm on experimental data that was obtained from dataset 2a of BCI competition IV (2008). The overall four-class kappa values (between 0.41 and 0.80) were comparable to other models but without requiring any artifact-contaminated trial removal. The performance showed that multi-class MI tasks can be reliably discriminated using artifact-contaminated EEG recordings from a few channels. This may be a promising avenue for online robust EEG-based BCI applications. PMID:23087607

Scalp Seborrheic Dermatitis and Dandruff Therapy Using a Herbal and Zinc Pyrithione-based Therapy of Shampoo and Scalp Lotion.

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Barak-Shinar, Deganit; Green, Lawrence J

2018-01-01

Objective: The aim of this study was to evaluate the safety and efficacy of an herbal and zinc pyrithione shampoo and a scalp lotion (Kamedis Derma-Scalp Dandruff Therapy, Kamedis Ltd., Tel Aviv, Israel) for the treatment of scalp seborrheic dermatitis and dandruff. Design: This was an interventional, open-label, safety and efficacy study. Setting: This open-label study was conducted at Consumer Product Testing Company Inc. in Fairfield, New Jersey. At the baseline visit (Day 0), an examination of the scalp was conducted by a board-certified dermatologist. The entire scalp was evaluated for evidence of seborrheic dermatitis using the Adherent Scalp Flaking Score with a 10-point scale. Only subjects with evidence of moderate-to-greater seborrheic dermatitis or moderate-to-greater dandruff were deemed qualified for inclusion in the study. Participants: Fifty subjects were recruited and included in the study. Measurements: Study subjects were evaluated by the same dermatologist for erythema and flaking at Days 0, 14, 28, and 42 using a five-point scale for each parameter. At each time point, a total severity score was calculated based on the findings of the evaluations. Following the scalp evaluation, each subject had a standardized digital photograph taken of his or her scalp. Each subject was also asked to answer a satisfaction questionnaire regarding the product treatment enhancement and characteristics. Results: A reduction in both parameters evaluated was seen at all time points. Statistical significance was achieved at each time point when compared with the baseline visit. In addition, the subjects expressed a high degree of satisfaction with the treatment. No adverse events were reported during this study. Conclusion: The study showed that the herbal zinc pyrithione shampoo and scalp lotion provided improvement in the main symptoms of seborrheic dermatitis.

Malignant nodular hidradenoma of scalp

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Tanmoy Maiti

2014-01-01

Full Text Available Malignant nodular hidradenoma (MNH is a rare tumor of sweat gland known by many names in the literature. Scalp is a known and yet uncommon site of occurrence. We describe two patients with scalp MNH with brain parenchymal invasion. Both tumors recurred in spite of total excision and radiotherapy.

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

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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.

Incorporating priors for EEG source imaging and connectivity analysis

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Xu eLei

2015-08-01

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

Sleep in the human hippocampus: a stereo-EEG study.

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Fabio Moroni

Full Text Available BACKGROUND: There is compelling evidence indicating that sleep plays a crucial role in the consolidation of new declarative, hippocampus-dependent memories. Given the increasing interest in the spatiotemporal relationships between cortical and hippocampal activity during sleep, this study aimed to shed more light on the basic features of human sleep in the hippocampus. METHODOLOGY/PRINCIPAL FINDINGS: We recorded intracerebral stereo-EEG directly from the hippocampus and neocortical sites in five epileptic patients undergoing presurgical evaluations. The time course of classical EEG frequency bands during the first three NREM-REM sleep cycles of the night was evaluated. We found that delta power shows, also in the hippocampus, the progressive decrease across sleep cycles, indicating that a form of homeostatic regulation of delta activity is present also in this subcortical structure. Hippocampal sleep was also characterized by: i a lower relative power in the slow oscillation range during NREM sleep compared to the scalp EEG; ii a flattening of the time course of the very low frequencies (up to 1 Hz across sleep cycles, with relatively high levels of power even during REM sleep; iii a decrease of power in the beta band during REM sleep, at odds with the typical increase of power in the cortical recordings. CONCLUSIONS/SIGNIFICANCE: Our data imply that cortical slow oscillation is attenuated in the hippocampal structures during NREM sleep. The most peculiar feature of hippocampal sleep is the increased synchronization of the EEG rhythms during REM periods. This state of resonance may have a supportive role for the processing/consolidation of memory.

Epileptic seizure detection from EEG signals with phase-amplitude cross-frequency coupling and support vector machine

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Liu, Yang; Wang, Jiang; Cai, Lihui; Chen, Yingyuan; Qin, Yingmei

2018-03-01

As a pattern of cross-frequency coupling (CFC), phase-amplitude coupling (PAC) depicts the interaction between the phase and amplitude of distinct frequency bands from the same signal, and has been proved to be closely related to the brain’s cognitive and memory activities. This work utilized PAC and support vector machine (SVM) classifier to identify the epileptic seizures from electroencephalogram (EEG) data. The entropy-based modulation index (MI) matrixes are used to express the strength of PAC, from which we extracted features as the input for classifier. Based on the Bonn database, which contains five datasets of EEG segments obtained from healthy volunteers and epileptic subjects, a 100% classification accuracy is achieved for identifying seizure ictal from healthy data, and an accuracy of 97.67% is reached in the classification of ictal EEG signals from inter-ictal EEGs. Based on the CHB-MIT database which is a group of continuously recorded epileptic EEGs by scalp electrodes, a 97.50% classification accuracy is obtained and a raising sign of MI value is found at 6s before seizure onset. The classification performance in this work is effective, and PAC can be considered as a useful tool for detecting and predicting the epileptic seizures and providing reference for clinical diagnosis.

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

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M.I. Tomescu

2018-06-01

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

Time-varying bispectral analysis of visually evoked multi-channel EEG

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Chandran, Vinod

2012-12-01

Theoretical foundations of higher order spectral analysis are revisited to examine the use of time-varying bicoherence on non-stationary signals using a classical short-time Fourier approach. A methodology is developed to apply this to evoked EEG responses where a stimulus-locked time reference is available. Short-time windowed ensembles of the response at the same offset from the reference are considered as ergodic cyclostationary processes within a non-stationary random process. Bicoherence can be estimated reliably with known levels at which it is significantly different from zero and can be tracked as a function of offset from the stimulus. When this methodology is applied to multi-channel EEG, it is possible to obtain information about phase synchronization at different regions of the brain as the neural response develops. The methodology is applied to analyze evoked EEG response to flash visual stimulii to the left and right eye separately. The EEG electrode array is segmented based on bicoherence evolution with time using the mean absolute difference as a measure of dissimilarity. Segment maps confirm the importance of the occipital region in visual processing and demonstrate a link between the frontal and occipital regions during the response. Maps are constructed using bicoherence at bifrequencies that include the alpha band frequency of 8Hz as well as 4 and 20Hz. Differences are observed between responses from the left eye and the right eye, and also between subjects. The methodology shows potential as a neurological functional imaging technique that can be further developed for diagnosis and monitoring using scalp EEG which is less invasive and less expensive than magnetic resonance imaging.

Brain Network Analysis from High-Resolution EEG Signals

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de Vico Fallani, Fabrizio; Babiloni, Fabio

Over the last decade, there has been a growing interest in the detection of the functional connectivity in the brain from different neuroelectromagnetic and hemodynamic signals recorded by several neuro-imaging devices such as the functional Magnetic Resonance Imaging (fMRI) scanner, electroencephalography (EEG) and magnetoencephalography (MEG) apparatus. Many methods have been proposed and discussed in the literature with the aim of estimating the functional relationships among different cerebral structures. However, the necessity of an objective comprehension of the network composed by the functional links of different brain regions is assuming an essential role in the Neuroscience. Consequently, there is a wide interest in the development and validation of mathematical tools that are appropriate to spot significant features that could describe concisely the structure of the estimated cerebral networks. The extraction of salient characteristics from brain connectivity patterns is an open challenging topic, since often the estimated cerebral networks have a relative large size and complex structure. Recently, it was realized that the functional connectivity networks estimated from actual brain-imaging technologies (MEG, fMRI and EEG) can be analyzed by means of the graph theory. Since a graph is a mathematical representation of a network, which is essentially reduced to nodes and connections between them, the use of a theoretical graph approach seems relevant and useful as firstly demonstrated on a set of anatomical brain networks. In those studies, the authors have employed two characteristic measures, the average shortest path L and the clustering index C, to extract respectively the global and local properties of the network structure. They have found that anatomical brain networks exhibit many local connections (i.e. a high C) and few random long distance connections (i.e. a low L). These values identify a particular model that interpolate between a regular

Feature analysis for correlation studies of simultaneous EEG-fMRI data: A proof of concept for neurofeedback approaches.

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Simoes, Simões; Lima, João; Direito, Bruno; Castelhano, João; Ferreira, Carlos; Carvalho, Paulo; Castelo-Branco, Miguel

2015-01-01

The identification and interpretation of facial expressions is an important feature of social cognition. This characteristic is often impaired in various neurodevelopmental disorders. Recent therapeutic approaches to intervene in social communication impairments include neurofeedback (NF). In this study, we present a NF real-time functional Magnetic Resonance Imaging (rt-fMRI), combined with electroencephalography (EEG) to train social communication skills. In this sense, we defined the right Superior Temporal Sulcus as our target region-of-interest. To analyze the correlation between the fMRI regions of interest and the EEG data, we transposed the sources located at the nearest cortical location to the target region. We extracted a set of 75 features from EEG segments and performed a correlation analysis with the brain activations extracted from rt-fMRI in the right pSTS region. The finding of significant correlations of simultaneously measured signals in distinct modalities (EEG and fMRI) is promising. Future studies should address whether the observed correlation levels between local brain activity and scalp measures are sufficient to implement NF approaches.

MRI in temporal lobe epilepsy. Correlation between EEG, SPECT and clinical features

International Nuclear Information System (INIS)

Uesugi, Hideji; Onuma, Teiichi; Matsuda, Hiroshi; Ishida, Shiro

1996-01-01

The relationship between MRI, SPECT, EEG and clinical features in temporal lobe epilepsy was investigated. Subjects were 162 patients (84 males, 78 females) whose average age was 38.1±12.1 years. SPECT was carried out in 45 patients. The results were as follows: abnormal MR images were obtained in 36% of the group without epileptic discharge, and in 42% of the group with temporal spikes. There was no correlation between epileptic discharge in EEG and MRI abnormality. The lateralities of epileptic discharge and MRI were in disagreement in 9 of 39 patients (23%), indicating that determining the epileptic focus from scalp EEG was difficult. There was no correlation between the basic activity in EEG and abnormality in MRI. The rate of abnormal SPECT (89%) was higher than that of abnormal MRI (40%). The rate of the group with ictal automatism (52%) was higher than that of the group without ictal automatism (35%). The rate of abnormal MR images was high in the group with encephalitis (73%). The rate was higher in the group with febrile convulsion (62%) than in the group without it (28%). The rate of the abnormal MR images was higher in the group with a seizure frequency of at least several mal/month (48%) than in the group with a seizure frequency of less than several mal/year (29%). (author)

Neuroglial heterotopia of the scalp.

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Attafi, S; Lahmar-Boufaroua, A; Rekik, W; Fraoua, F; Fadhel, C B; Bouraoui, S; Mzabi-Rgaya, S

2016-03-01

Heterotopic glial nodules of the scalp are non hereditary congenital malformations composed of mature brain tissue isolated from the cranial cavity. The majority of these lesions are found in the nasal region and occur rarely on the scalp. They are frequently diagnosed in newborn infants. However, they may rarely be found in adults. The pathogenesis of these lesions remains unknown. We describe the case of a temporal scalp nodule in a 50 year-old man. At the time of the excision, the mass was not associated with intracranial connection. Histological examination revealed neural tissue staining with S100-protein and the glial fibrillary acidic protein (GFAP). © Copyright Società Italiana di Anatomia Patologica e Citopatologia Diagnostica, Divisione Italiana della International Academy of Pathology.

From Structure to Circuits: The Contribution of MEG Connectivity Studies to Functional Neurosurgery.

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Pang, Elizabeth W; Snead Iii, O C

2016-01-01

New advances in structural neuroimaging have revealed the intricate and extensive connections within the brain, data which have informed a number of ambitious projects such as the mapping of the human connectome. Elucidation of the structural connections of the brain, at both the macro and micro levels, promises new perspectives on brain structure and function that could translate into improved outcomes in functional neurosurgery. The understanding of neuronal structural connectivity afforded by these data now offers a vista on the brain, in both healthy and diseased states, that could not be seen with traditional neuroimaging. Concurrent with these developments in structural imaging, a complementary modality called magnetoencephalography (MEG) has been garnering great attention because it too holds promise for being able to shed light on the intricacies of functional brain connectivity. MEG is based upon the elemental principle of physics that an electrical current generates a magnetic field. Hence, MEG uses highly sensitive biomagnetometers to measure extracranial magnetic fields produced by intracellular neuronal currents. Put simply then, MEG is a measure of neurophysiological activity, which captures the magnetic fields generated by synchronized intraneuronal electrical activity. As such, MEG recordings offer exquisite resolution in the time and oscillatory domain and, as well, when co-registered with magnetic resonance imaging (MRI), offer excellent resolution in the spatial domain. Recent advances in MEG computational and graph theoretical methods have led to studies of connectivity in the time-frequency domain. As such, MEG can elucidate a neurophysiological-based functional circuitry that may enhance what is seen with MRI connectivity studies. In particular, MEG may offer additional insight not possible by MRI when used to study complex eloquent function, where the precise timing and coordination of brain areas is critical. This article will review the

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

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Fran López-Caballero

2017-11-01

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

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

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López-Caballero, Fran; Escera, Carles

2017-01-01

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

Multimodal Approach to Testing the Acute Effects of Mild Traumatic Brain Injury (mTBI)

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2015-03-01

magnetoencephalography, MEG, MRI, blood biomarkers, actigraphy 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a...all participants in the study. B. EEG and MEG Recordings and Signal Preprocessing Subjects were asked to remain as still as possible during the...electrode EEG system (Wearable Sensing, San Diego, CA). The system includes 21 channels for EEG and two additional channels to record EOG and EKG activity

Management of scalp psoriasis: current perspectives

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Blakely K

2016-03-01

Full Text Available Kim Blakely,1 Melinda Gooderham2 1Faculty of Medicine, University of Toronto, Toronto, ON, Canada; 2Skin Centre for Dermatology, Peterborough, ON, Canada Abstract: Psoriasis is a chronic inflammatory condition. The age of onset, chronicity, physical, and psychosocial consequences of the disease cause psoriasis to have a significant impact on patient quality of life. Scalp psoriasis is no different, and effective treatment results in an improvement in quality of life. Successful management of scalp psoriasis includes topical therapies that are acceptable to the patient for mild-to-moderate disease, and systemic therapies for recalcitrant or moderate-to-severe disease. The most effective topical therapies are corticosteroid products, or combination products with calcipotriol and corticosteroid. Newer vehicle options provide more attractive and pleasing products for patients and may improve adherence. The current perspectives for management of scalp psoriasis are discussed including available data for systemic therapy of severe disease. Keywords: psoriasis, scalp psoriasis, topical therapies, systemic therapies, biologics

Mean-field thalamocortical modeling of longitudinal EEG acquired during intensive meditation training.

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Saggar, Manish; Zanesco, Anthony P; King, Brandon G; Bridwell, David A; MacLean, Katherine A; Aichele, Stephen R; Jacobs, Tonya L; Wallace, B Alan; Saron, Clifford D; Miikkulainen, Risto

2015-07-01

Meditation training has been shown to enhance attention and improve emotion regulation. However, the brain processes associated with such training are poorly understood and a computational modeling framework is lacking. Modeling approaches that can realistically simulate neurophysiological data while conforming to basic anatomical and physiological constraints can provide a unique opportunity to generate concrete and testable hypotheses about the mechanisms supporting complex cognitive tasks such as meditation. Here we applied the mean-field computational modeling approach using the scalp-recorded electroencephalogram (EEG) collected at three assessment points from meditating participants during two separate 3-month-long shamatha meditation retreats. We modeled cortical, corticothalamic, and intrathalamic interactions to generate a simulation of EEG signals recorded across the scalp. We also present two novel extensions to the mean-field approach that allow for: (a) non-parametric analysis of changes in model parameter values across all channels and assessments; and (b) examination of variation in modeled thalamic reticular nucleus (TRN) connectivity over the retreat period. After successfully fitting whole-brain EEG data across three assessment points within each retreat, two model parameters were found to replicably change across both meditation retreats. First, after training, we observed an increased temporal delay between modeled cortical and thalamic cells. This increase provides a putative neural mechanism for a previously observed reduction in individual alpha frequency in these same participants. Second, we found decreased inhibitory connection strength between the TRN and secondary relay nuclei (SRN) of the modeled thalamus after training. This reduction in inhibitory strength was found to be associated with increased dynamical stability of the model. Altogether, this paper presents the first computational approach, taking core aspects of physiology and

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

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Maren Stropahl

2018-05-01

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

Current clinical magnetoencephalography practice across Europe: Are we closer to use MEG as an established clinical tool?

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De Tiège, Xavier; Lundqvist, Daniel; Beniczky, Sándor; Seri, Stefano; Paetau, Ritva

2017-08-01

This comprehensive survey aims at characterizing the current clinical use of magnetoencephalography (MEG) across European MEG centres. Forty-four MEG centres across Europe were contacted in May 2015 via personalized e-mail to contribute to survey. The web-based survey was available on-line for 1 month and the MEG centres that did not respond were further contacted to maximize participation. Among the 57% of responders, 12 centres from 10 different countries reported to use MEG for clinical applications. A total of 524 MEG investigations were performed in 2014 for the pre-surgical evaluation of epilepsy, while in the same period 244 MEG investigations were performed for pre-surgical functional brain mapping. Seven MEG centres located in different European countries performed ≥50 MEG investigations for epilepsy mapping in 2014, both in children and adults. In those centres, time from patient preparation to MEG data reporting tends to be lower than those investigating a lower annual number of patients. This survey demonstrates that there is in Europe an increasing and widespread expertise in the field of clinical MEG. These findings should serve as a basis to harmonize clinical MEG procedures and promote the clinical added value of MEG across Europe. MEG should now be considered in Europe as a mature clinical neurophysiological technique that should be used routinely in two specific clinical indications, i.e, the pre-surgical evaluation of refractory focal epilepsy and functional brain mapping. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Review of Clinical Applications of Scalp Acupuncture for Paralysis: An Excerpt From Chinese Scalp Acupuncture

OpenAIRE

Hao, Jason Jishun; Hao, Linda Lingzhi

2012-01-01

Chinese scalp acupuncture is a contemporary acupuncture technique integrating traditional Chinese needling methods with Western medical knowledge of representative areas of the cerebral cortex. It has been proven to be a most effective technique for treating acute and chronic central nervous system disorders. Scalp acupuncture often produces remarkable results with just a few needles and usually brings about immediate improvement, sometimes taking only several seconds to a minute. Acupuncture...

Ictal and interictal SPECT imaging of 8 patients with symptomatic partial epilepsy

International Nuclear Information System (INIS)

Motooka, Hiromichi

1993-01-01

Although epileptic discharges such as spike, spike and wave complex, sharp wave, and sharp and wave complex can be recorded by interictal scalp electroencephalography (EEG) in many patients with epilepsy, recent studies have demonstrated that no epileptic discharges can be recorded by interictal and ictal scalp EEGs in some patients who clinically exhibit epileptic seizures. Accordingly scalp EEG is not always helpful for diagnosing epilepsy or identifying the epileptic foci in the brain in these patients. Recently, studies using single photon emission computed tomography (SPECT) have been performed for patients with epilepsy and evidence that epileptic foci can be identified by changes in the regional cerebral blood flow (rCBF) seen on SPECT scanning have been accumulated. In the present study, therefore, 8 patients with medically intractable partial seizures were simultaneously or independently investigated by the recordings of scalp EEG and SPECT scanning during the interictal and ictal period. N-isopropyl-p[ 123 I]-iodoamphetamine ( 123 I-IMP) was used for SPECT scanning for 7 patients and 99m Tc-d,l-hexamethyl-propyleneamineoxime ( 99m Tc-HMPAO) for 1 patient. An increase in rCBF (hyperperfusion) or decrease in rCBF (hypoperfusion) were found in 4 patients by interictal SPECT imaging and in all patients by ictal SPECT imaging although epileptic discharges were observed in 3 patients by interictal scalp EEG and 5 patients by ictal scalp EEG. The findings of the present study indicate that ictal SPECT scanning is more useful for diagnosing epilepsy and identifying the epileptic foci in the brain than ictal scalp EEG. (author)

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Removal of the ballistocardiographic artifact from EEG-fMRI data: a canonical correlation approach

International Nuclear Information System (INIS)

Assecondi, Sara; Hallez, Hans; Staelens, Steven; Lemahieu, Ignace; Bianchi, Anna M; Huiskamp, Geertjan M

2009-01-01

The simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) can give new insights into how the brain functions. However, the strong electromagnetic field of the MR scanner generates artifacts that obscure the EEG and diminish its readability. Among them, the ballistocardiographic artifact (BCGa) that appears on the EEG is believed to be related to blood flow in scalp arteries leading to electrode movements. Average artifact subtraction (AAS) techniques, used to remove the BCGa, assume a deterministic nature of the artifact. This assumption may be too strong, considering the blood flow related nature of the phenomenon. In this work we propose a new method, based on canonical correlation analysis (CCA) and blind source separation (BSS) techniques, to reduce the BCGa from simultaneously recorded EEG-fMRI. We optimized the method to reduce the user's interaction to a minimum. When tested on six subjects, recorded in 1.5 T or 3 T, the average artifact extracted with BSS-CCA and AAS did not show significant differences, proving the absence of systematic errors. On the other hand, when compared on the basis of intra-subject variability, we found significant differences and better performance of the proposed method with respect to AAS. We demonstrated that our method deals with the intrinsic subject variability specific to the artifact that may cause averaging techniques to fail.

Complexity analysis of EEG in patients with schizophrenia using fractal dimension

International Nuclear Information System (INIS)

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

2009-01-01

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

Design of EEG Signal Acquisition System Using Arduino MEGA1280 and EEGAnalyzer

Directory of Open Access Journals (Sweden)

Saptono Debyo

2016-01-01

Full Text Available This study integrates the hardware circuit design and software development to achieve a 16 channels Electroencephalogram (EEG system for Brain Computer Interface (BCI applications. Signals obtained should be strong enough amplitude that is usually expressed in units of millivolts and reasonably clean of noise that appears when the data acquisition process. The process of data acquisition consists of two stages are the acquisition of the original EEG signal can be done by the active electrode with an instrumentation amplifier or a preamplifier and processing the signal to get better signals with improved signal quality by removing noise using filters with IC OPAMP. The design of a preamplifier with high common-mode rejection ratio and high signal-to-noise ratio is very important. Moreover, the friction between the electrode pads and the skin as well as the design of dual power supply. Designs used single-power AC-coupled circuit, which effectively reduces the DC bias and improves the error caused by the effects of part errors. At the same time, the digital way is applied to design the adjustable amplification and filter function, which can design for different EEG frequency bands. The next step, those EEG signals received by the microcontroller through a port Analog to Digital Converter (ADC that integrated and converted into digital signals and stored in the RAM of microcontroller which simultaneously at 16 ports in accordance with the minimal number of points of data collection on the human scalp. Implementation results have shown the series of acquisitions to work properly so that it can be displayed EEG signals via software EEGAnalyzer.

Scalp squamous cell carcinoma in xeroderma pigmentosum.

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Awan, Basim A; Alzanbagi, Hanadi; Samargandi, Osama A; Ammar, Hossam

2014-02-01

Xeroderma pigmentosum is a rare autosomal-recessive disorder that appears in early childhood. Squamous cell carcinoma is not uncommon in patients with xeroderma pigmentosum and mostly involving the face, head, neck, and scalp. However, squamous cell carcinoma of the scalp may exhibit an aggressive course. Here, we present a huge squamous cell carcinoma of the scalp in a three-years-old child with xeroderma pigmentosum. In addition, we illustrate the challenges of a child with xeroderma pigmentosum who grows up in a sunny environment where the possibility of early onset of squamous cell carcinoma is extremely high in any suspected skin lesion. In xeroderma pigmentosum patients, squamous cell carcinoma of the scalp can present early and tends to be unusually aggressive. In sunny areas, proper education to the patient and their parents about ultra-violet light protection and early recognition of any suspicious lesion could be life-saving.

Interpretation of the MEG-MUSIC scan in biomagnetic source localization

Energy Technology Data Exchange (ETDEWEB)

Mosher, J.C.; Lewis, P.S. [Los Alamos National Lab., NM (United States); Leahy, R.M. [University of Southern California, Los Angeles, CA (United States). Signal and Image Processing Inst.

1993-09-01

MEG-Music is a new approach to MEG source localization. MEG-Music is based on a spatio-temporal source model in which the observed biomagnetic fields are generated by a small number of current dipole sources with fixed positions/orientations and varying strengths. From the spatial covariance matrix of the observed fields, a signal subspace can be identified. The rank of this subspace is equal to the number of elemental sources present. This signal sub-space is used in a projection metric that scans the three dimensional head volume. Given a perfect signal subspace estimate and a perfect forward model, the metric will peak at unity at each dipole location. In practice, the signal subspace estimate is contaminated by noise, which in turn yields MUSIC peaks which are less than unity. Previously we examined the lower bounds on localization error, independent of the choice of localization procedure. In this paper, we analyzed the effects of noise and temporal coherence on the signal subspace estimate and the resulting effects on the MEG-MUSIC peaks.

Long Non-Coding RNA MEG3 Inhibits Cell Proliferation and Induces Apoptosis in Prostate Cancer

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Gang Luo

2015-11-01

Full Text Available Background/Aims: Long non-coding RNAs (lncRNAs play important roles in diverse biological processes, such as cell growth, apoptosis and migration. Although downregulation of lncRNA maternally expressed gene 3 (MEG3 has been identified in several cancers, little is known about its role in prostate cancer progression. The aim of this study was to detect MEG3 expression in clinical prostate cancer tissues, investigate its biological functions in the development of prostate cancer and the underlying mechanism. Methods: MEG3 expression levels were detected by qRT-PCR in both tumor tissues and adjacent non-tumor tissues from 21 prostate cancer patients. The effects of MEG3 on PC3 and DU145 cells were assessed by MTT assay, colony formation assay, western blot and flow cytometry. Transfected PC3 cells were transplanted into nude mice, and the tumor growth curves were determined. Results: MEG3 decreased significantly in prostate cancer tissues relative to adjacent normal tissues. MEG3 inhibited intrinsic cell survival pathway in vitro and in vivo by reducing the protein expression of Bcl-2, enhancing Bax and activating caspase 3. We further demonstrated that MEG3 inhibited the expression of cell cycle regulatory protein Cyclin D1 and induced cell cycle arrest in G0/G1 phase. Conclusions: Our study presents an important role of MEG3 in the molecular etiology of prostate cancer and implicates the potential application of MEG3 in prostate cancer therapy.

Correntropy measures to detect daytime sleepiness from EEG signals

International Nuclear Information System (INIS)

Melia, Umberto; Vallverdú, Montserrat; Caminal, Pere; Guaita, Marc; Montserrat, Josep M; Vilaseca, Isabel; Salamero, Manel; Gaig, Carles; Santamaria, Joan

2014-01-01

Excessive daytime sleepiness (EDS) is one of the main symptoms of several sleep related disorders and has a great impact on patients’ lives. While many studies have been carried out in order to assess daytime sleepiness, automatic EDS detection still remains an open problem. In this work, a novel approach to this issue based on correntropy function analysis of EEG signals was proposed in order to detect patients suffering from EDS. Multichannel EEG signals were recorded during five Maintenance of Wakefulness Tests (MWT) and Multiple Sleep Latency Tests (MSLT) alternated throughout the day for patients suffering from sleep disordered breathing (SDB). A group of 20 patients with EDS was compared with a group of 20 patients without daytime sleepiness (WDS), by analyzing 60 s EEG windows in a waking state. Measures obtained from the cross-correntropy function (CCORR) and auto-correntropy function (ACORR) were calculated in the EEG frequency bands: δ, 0.1–4 Hz; θ, 4–8 Hz; α, 8–12 Hz; β, 12–30 Hz; total band TB, 0.1–45 Hz. These functions permitted the quantification of complex signal properties and the non-linear couplings between different areas of the scalp. Statistical differences between EDS and WDS groups were mainly found in the β band during MSLT events (p-value < 0.0001). The WDS group presented more complexity in the occipital zone than the EDS group, while a stronger nonlinear coupling between the occipital and frontal regions was detected in EDS patients than in the WDS group. At best, ACORR and CCORR measures yielded sensitivity and specificity above 80% and the area under ROC curve (AUC) was above 0.85 in classifying EDS and WDS patients. These performances represent an improvement with respect to classical EEG indices applied in the same database (sensitivity and specificity were never above 80% and AUC was under 0.75). (paper)

Photogrammetry-Based Head Digitization for Rapid and Accurate Localization of EEG Electrodes and MEG Fiducial Markers Using a Single Digital SLR Camera.

Science.gov (United States)

Clausner, Tommy; Dalal, Sarang S; Crespo-García, Maité

2017-01-01

The performance of EEG source reconstruction has benefited from the increasing use of advanced head modeling techniques that take advantage of MRI together with the precise positions of the recording electrodes. The prevailing technique for registering EEG electrode coordinates involves electromagnetic digitization. However, the procedure adds several minutes to experiment preparation and typical digitizers may not be accurate enough for optimal source reconstruction performance (Dalal et al., 2014). Here, we present a rapid, accurate, and cost-effective alternative method to register EEG electrode positions, using a single digital SLR camera, photogrammetry software, and computer vision techniques implemented in our open-source toolbox, janus3D . Our approach uses photogrammetry to construct 3D models from multiple photographs of the participant's head wearing the EEG electrode cap. Electrodes are detected automatically or semi-automatically using a template. The rigid facial features from these photo-based models are then surface-matched to MRI-based head reconstructions to facilitate coregistration to MRI space. This method yields a final electrode coregistration error of 0.8 mm, while a standard technique using an electromagnetic digitizer yielded an error of 6.1 mm. The technique furthermore reduces preparation time, and could be extended to a multi-camera array, which would make the procedure virtually instantaneous. In addition to EEG, the technique could likewise capture the position of the fiducial markers used in magnetoencephalography systems to register head position.

Review of Clinical Applications of Scalp Acupuncture for Paralysis: An Excerpt From Chinese Scalp Acupuncture

Science.gov (United States)

Hao, Linda Lingzhi

2012-01-01

Chinese scalp acupuncture is a contemporary acupuncture technique integrating traditional Chinese needling methods with Western medical knowledge of representative areas of the cerebral cortex. It has been proven to be a most effective technique for treating acute and chronic central nervous system disorders. Scalp acupuncture often produces remarkable results with just a few needles and usually brings about immediate improvement, sometimes taking only several seconds to a minute. Acupuncture, a therapeutic technique of Oriental Medicine, can be traced back more than 2500 years. Throughout its long history, acupuncture has evolved as its own unique traditional medicine. By embracing newly developed knowledge and technology, the profession continues to create additional methods of treatment. Techniques such as electrical and laser acupuncture and even new acupuncture points are currently being developed. We believe scalp acupuncture, which integrates Western medicine with Traditional Chinese Medicine, to be the most significant development that Chinese acupuncture has made in the past 60 years. PMID:24278807

Correlation between MEG and BOLD fMRI signals induced by visual flicker stimuli

Institute of Scientific and Technical Information of China (English)

Chu Renxin; Holroyd Tom; Duyn Jeff

2007-01-01

The goal of this work was to investigate how the MEG signal amplitude correlates with that of BOLD fMRI.To investigate the correlation between fMRI and macroscopic electrical activity, BOLD fMRI and MEG was performed on the same subjects (n =5). A visual flicker stimulus of varying temporal frequency was used to elicit neural responses in early visual areas. A strong similarity was observed in frequency tuning curves between both modalities.Although, averaged over subjects, the BOLD tuning curve was somewhat broader than MEG, both BOLD and MEG had maxima at a flicker frequency of 10 Hz. Also, we measured the first and second harmonic components as the stimuli frequency by MEG. In the low stimuli frequency (less than 6 Hz), the second harmonic has comparable amplitude with the first harmonic, which implies that neural frequency response is nonlinear and has more nonlinear components in low frequency than in high frequency.

Potential use of MEG to understand abnormalities in auditory function in clinical populations

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Eric eLarson

2014-03-01

Full Text Available Magnetoencephalography (MEG provides a direct, non-invasive view of neural activity with millisecond temporal precision. Recent developments in MEG analysis allow for improved source localization and mapping of connectivity between brain regions, expanding the possibilities for using MEG as a diagnostic tool. In this paper, we first describe inverse imaging methods (e.g., minimum-norm estimation and functional connectivity measures, and how they can provide insights into cortical processing. We then offer a perspective on how these techniques could be used to understand and evaluate auditory pathologies that often manifest during development. Here we focus specifically on how MEG inverse imaging, by providing anatomically-based interpretation of neural activity, may allow us to test which aspects of cortical processing play a role in (central auditory processing disorder ([C]APD. Appropriately combining auditory paradigms with MEG analysis could eventually prove useful for a hypothesis-driven understanding and diagnosis of (CAPD or other disorders, as well as the evaluation of the effectiveness of intervention strategies.

The cortical focus in childhood absence epilepsy; evidence from nonlinear analysis of scalp EEG recordings.

Science.gov (United States)

Sarrigiannis, Ptolemaios G; Zhao, Yifan; He, Fei; Billings, Stephen A; Baster, Kathleen; Rittey, Chris; Yianni, John; Zis, Panagiotis; Wei, Hualiang; Hadjivassiliou, Marios; Grünewald, Richard

2018-03-01

To determine the origin and dynamic characteristics of the generalised hyper-synchronous spike and wave (SW) discharges in childhood absence epilepsy (CAE). We applied nonlinear methods, the error reduction ratio (ERR) causality test and cross-frequency analysis, with a nonlinear autoregressive exogenous (NARX) model, to electroencephalograms (EEGs) from CAE, selected with stringent electro-clinical criteria (17 cases, 42 absences). We analysed the pre-ictal and ictal strength of association between homologous and heterologous EEG derivations and estimated the direction of synchronisation and corresponding time lags. A frontal/fronto-central onset of the absences is detected in 13 of the 17 cases with the highest ictal strength of association between homologous frontal followed by centro-temporal and fronto-central areas. Delays consistently in excess of 4 ms occur at the very onset between these regions, swiftly followed by the emergence of "isochronous" (0-2 ms) synchronisation but dynamic time lag changes occur during SW discharges. In absences an initial cortico-cortical spread leads to dynamic lag changes to include periods of isochronous interhemispheric synchronisation, which we hypothesize is mediated by the thalamus. Absences from CAE show ictal epileptic network dynamics remarkably similar to those observed in WAG/Rij rats which guided the formulation of the cortical focus theory. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Dynamic functional coupling of high resolution EEG potentials related to unilateral internally triggered one-digit movements.

Science.gov (United States)

Urbano, A; Babiloni, C; Onorati, P; Babiloni, F

1998-06-01

Between-electrode cross-covariances of delta (0-3 Hz)- and theta (4-7 Hz)-filtered high resolution EEG potentials related to preparation, initiation. and execution of human unilateral internally triggered one-digit movements were computed to investigate statistical dynamic coupling between these potentials. Significant (P planning, starting, and performance of unilateral movement. The involvement of these cortical areas is supported by the observation that averaged spatially enhanced delta- and theta-bandpassed potentials were computed from the scalp regions where task-related electrical activation of primary sensorimotor areas and supplementary motor area was roughly represented.

A two-way regularization method for MEG source reconstruction

KAUST Repository

Tian, Tian Siva; Huang, Jianhua Z.; Shen, Haipeng; Li, Zhimin

2012-01-01

The MEG inverse problem refers to the reconstruction of the neural activity of the brain from magnetoencephalography (MEG) measurements. We propose a two-way regularization (TWR) method to solve the MEG inverse problem under the assumptions that only a small number of locations in space are responsible for the measured signals (focality), and each source time course is smooth in time (smoothness). The focality and smoothness of the reconstructed signals are ensured respectively by imposing a sparsity-inducing penalty and a roughness penalty in the data fitting criterion. A two-stage algorithm is developed for fast computation, where a raw estimate of the source time course is obtained in the first stage and then refined in the second stage by the two-way regularization. The proposed method is shown to be effective on both synthetic and real-world examples. © Institute of Mathematical Statistics, 2012.

A two-way regularization method for MEG source reconstruction

KAUST Repository

Tian, Tian Siva

2012-09-01

The MEG inverse problem refers to the reconstruction of the neural activity of the brain from magnetoencephalography (MEG) measurements. We propose a two-way regularization (TWR) method to solve the MEG inverse problem under the assumptions that only a small number of locations in space are responsible for the measured signals (focality), and each source time course is smooth in time (smoothness). The focality and smoothness of the reconstructed signals are ensured respectively by imposing a sparsity-inducing penalty and a roughness penalty in the data fitting criterion. A two-stage algorithm is developed for fast computation, where a raw estimate of the source time course is obtained in the first stage and then refined in the second stage by the two-way regularization. The proposed method is shown to be effective on both synthetic and real-world examples. © Institute of Mathematical Statistics, 2012.

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

Science.gov (United States)

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

Maggots in the Brain: Sequelae of Ignored Scalp Wound.

Science.gov (United States)

Aggarwal, Ashish; Maskara, Prasant

2018-01-01

A 26-year-old male had suffered a burn injury to his scalp in childhood and ignored it. He presented with a complaint of something crawling on his head. Inspection of his scalp revealed multiple maggots on the brain surface with erosion of overlying bone and scalp. He was successfully managed by surgical debridement and regular dressing. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparing Features for Classification of MEG Responses to Motor Imagery.

Directory of Open Access Journals (Sweden)

Hanna-Leena Halme

Full Text Available Motor imagery (MI with real-time neurofeedback could be a viable approach, e.g., in rehabilitation of cerebral stroke. Magnetoencephalography (MEG noninvasively measures electric brain activity at high temporal resolution and is well-suited for recording oscillatory brain signals. MI is known to modulate 10- and 20-Hz oscillations in the somatomotor system. In order to provide accurate feedback to the subject, the most relevant MI-related features should be extracted from MEG data. In this study, we evaluated several MEG signal features for discriminating between left- and right-hand MI and between MI and rest.MEG was measured from nine healthy participants imagining either left- or right-hand finger tapping according to visual cues. Data preprocessing, feature extraction and classification were performed offline. The evaluated MI-related features were power spectral density (PSD, Morlet wavelets, short-time Fourier transform (STFT, common spatial patterns (CSP, filter-bank common spatial patterns (FBCSP, spatio-spectral decomposition (SSD, and combined SSD+CSP, CSP+PSD, CSP+Morlet, and CSP+STFT. We also compared four classifiers applied to single trials using 5-fold cross-validation for evaluating the classification accuracy and its possible dependence on the classification algorithm. In addition, we estimated the inter-session left-vs-right accuracy for each subject.The SSD+CSP combination yielded the best accuracy in both left-vs-right (mean 73.7% and MI-vs-rest (mean 81.3% classification. CSP+Morlet yielded the best mean accuracy in inter-session left-vs-right classification (mean 69.1%. There were large inter-subject differences in classification accuracy, and the level of the 20-Hz suppression correlated significantly with the subjective MI-vs-rest accuracy. Selection of the classification algorithm had only a minor effect on the results.We obtained good accuracy in sensor-level decoding of MI from single-trial MEG data. Feature extraction

EEG biofeedback

OpenAIRE

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

Mindfulness-induced selflessness: A MEG neurophenomenological study

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Yair eDor-Ziderman

2013-09-01

Full Text Available Contemporary philosophical and neurocognitive studies of the self have dissociated two distinct types of self-awareness: a 'narrative' self-awareness (NS weaving together episodic memory, future planning and self-evaluation into a coherent self-narrative and identity, and a 'minimal' self-awareness (MS focused on present momentary experience and closely tied to the sense of agency and ownership. Long-term Buddhist meditation practice aims at realization of a 'selfless' mode of awareness (SL, where identification with a static sense of self is replaced by identification with the phenomenon of experiencing itself. NS-mediating mechanisms have been explored by neuroimaging, mainly fMRI, implicating prefrontal midline structures, but MS processes are not well characterized and SL even less so. To this end we tested 12 long-term mindfulness meditators using a neurophenomenological study design, incorporating both magnetoencephalogram (MEG recordings and first person descriptions. We found that (1 NS attenuation involves extensive frontal, and medial prefrontal gamma band (60-80 Hz power decreases, consistent with fMRI and intracranial EEG findings; (2 MS attenuation is related to beta-band (13-25 Hz power decreases in a network that includes ventral medial prefrontal, medial posterior and lateral parietal regions; and (3 the experience of selflessness is linked to attenuation of beta-band activity in the right inferior parietal lobule. These results highlight the role of dissociable frequency-dependent networks in supporting different modes of self-processing, and the utility of combining phenomenology, mindfulness training and electrophysiological neuroimaging for characterizing self-awareness.

MEG3 is a prognostic factor for CRC and promotes chemosensitivity by enhancing oxaliplatin-induced cell apoptosis.

Science.gov (United States)

Li, Lixia; Shang, Jian; Zhang, Yupeng; Liu, Shi; Peng, Yanan; Zhou, Zhou; Pan, Huaqing; Wang, Xiaobing; Chen, Lipng; Zhao, Qiu

2017-09-01

A major reason for the failure of advanced colorectal cancer (CRC) treatment is the occurrence of chemoresistance to oxaliplatin-based chemotherapy. Recently, studies have shown that long non-coding RNAs (lncRNAs) play an important role in drug resistance. Using HiSeq sequencing methods, we identified that lncRNAs show differential expression levels in oxaliplatin-resistant (OxR) and non-resistant CRC patients. RT-qPCR was then performed in tissues and serum samples, and lncRNA MEG3 was verified to be downregulated in non-responding patients and to have considerable discriminating potential to identify responding patients from non-responding patients. Moreover, decreased serum MEG3 expression was associated with poor chemoresponse and low survival rate in CRC patients receiving oxaliplatin treatment. Subsequently, OxR cell lines were established, and MEG3 was significantly downregulated in HT29 OxR and SW480 OxR cells. In addition, overexpression of MEG3 with pMEG3 reversed oxaliplatin resistance in both CRC cell lines. Flow cytometric apoptosis analysis indicated that MEG3 promoted CRC cell apoptosis. More importantly, MEG3 enhanced oxaliplatin‑induced cell cytotoxicity in CRC. In conclusion, our integrated approach demonstrated that decreased expression of lncRNA MEG3 in CRC confers potent poor therapeutic efficacy, and that MEG3 promotes chemosensitivity by enhancing oxaliplatin-induced cell apoptosis. Thus, overexpression of MEG3 may be a future direction by which to develop a novel therapeutic strategy to overcome oxaliplatin resistance of CRC patients.

Delayed Diagnosis: Giant Basal Cell Carcinoma of Scalp

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Didem Didar Balcı,

2008-07-01

Full Text Available Although basal cell carcinoma (BCC is the most common form of skin cancer, the scalp lesions of BCC have been rarely reported. Giant BCC is defined as a tumor larger than 5 cm in diameter and only 0.5-1 % of all BCCs achieve this size. We report a case of giant BCC on the scalp that was treated with topical coticosteroids and antifungal shampoo for five years. BCC should be considered in the differential diagnosis in erythematous plaque type lesions resistant to therapy with long duration localized on the scalp.

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

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Samantha J Broyd

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

Scalp meningioma

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Singh Sunil

2008-01-01

Full Text Available Primary extracranial meningiomas occur very rarely. We present a rare case of extracranial meningioma of the transitional variant which was excised satisfactorily. There was no suggestion of any connection to the intracranial compartment or cranial nerves. The underlying galea was uninvolved, suggesting the true extracranial nature of this tumour. This rare diagnosis should nonetheless be kept in the differential diagnosis of scalp tumors.

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

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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.

A Long Short-Term Memory deep learning network for the prediction of epileptic seizures using EEG signals.

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Tsiouris, Κostas Μ; Pezoulas, Vasileios C; Zervakis, Michalis; Konitsiotis, Spiros; Koutsouris, Dimitrios D; Fotiadis, Dimitrios I

2018-05-17

The electroencephalogram (EEG) is the most prominent means to study epilepsy and capture changes in electrical brain activity that could declare an imminent seizure. In this work, Long Short-Term Memory (LSTM) networks are introduced in epileptic seizure prediction using EEG signals, expanding the use of deep learning algorithms with convolutional neural networks (CNN). A pre-analysis is initially performed to find the optimal architecture of the LSTM network by testing several modules and layers of memory units. Based on these results, a two-layer LSTM network is selected to evaluate seizure prediction performance using four different lengths of preictal windows, ranging from 15 min to 2 h. The LSTM model exploits a wide range of features extracted prior to classification, including time and frequency domain features, between EEG channels cross-correlation and graph theoretic features. The evaluation is performed using long-term EEG recordings from the open CHB-MIT Scalp EEG database, suggest that the proposed methodology is able to predict all 185 seizures, providing high rates of seizure prediction sensitivity and low false prediction rates (FPR) of 0.11-0.02 false alarms per hour, depending on the duration of the preictal window. The proposed LSTM-based methodology delivers a significant increase in seizure prediction performance compared to both traditional machine learning techniques and convolutional neural networks that have been previously evaluated in the literature. Copyright © 2018 Elsevier Ltd. All rights reserved.

Performance of the Helium Circulation System on a Commercialized MEG

International Nuclear Information System (INIS)

Takeda, T; Miyazaki, T; Okamoto, M; Katagiri, K

2012-01-01

We report the performance of a helium circulation system (HCS) mounted on a MEG (Magnetoencephalography) at Nagoya University, Japan. This instrument is the first commercialized version of an HCS. The HCS collects warm helium gas at approximately 300 K and then cools it to approximately 40 K. The gas is returned to the neck tube of a Dewar of the MEG to keep it cold. It also collects helium gas in the region just above the liquid helium surface while it is still cold, re-liquefies the gas and returns it to the Dewar. A special transfer tube (TT) of approximately 3 m length was developed to allow for dual helium streams. This tube separates the HCS using a MEG to reduce magnetic noise. A refiner was incorporated to effectively collect contaminating gases by freezing them. The refiner was equipped with an electric heater to remove the frozen contaminants as gases into the air. A gas flow controller was also developed, which automatically controlled the heater and electric valves to clean up contamination. The developed TT exhibited a very low heat inflow of less than 0.1 W/m to the liquid helium, ensuring efficient operation. The insert tube diameter, which was 1.5 in. was reduced to a standard 0.5 in. size. This dimensional change enabled the HCS to mount onto any commercialized MEG without any modifications to the MEG. The HCS can increase liquid helium in the Dewar by at least 3 liters/Day using two GM cryocoolers (SRDK-415D, Sumitomo Heavy Industries, Ltd.). The noise levels were virtually the same as before this installation.

Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals.

Science.gov (United States)

Kauppi, Jukka-Pekka; Kandemir, Melih; Saarinen, Veli-Matti; Hirvenkari, Lotta; Parkkonen, Lauri; Klami, Arto; Hari, Riitta; Kaski, Samuel

2015-05-15

We hypothesize that brain activity can be used to control future information retrieval systems. To this end, we conducted a feasibility study on predicting the relevance of visual objects from brain activity. We analyze both magnetoencephalographic (MEG) and gaze signals from nine subjects who were viewing image collages, a subset of which was relevant to a predetermined task. We report three findings: i) the relevance of an image a subject looks at can be decoded from MEG signals with performance significantly better than chance, ii) fusion of gaze-based and MEG-based classifiers significantly improves the prediction performance compared to using either signal alone, and iii) non-linear classification of the MEG signals using Gaussian process classifiers outperforms linear classification. These findings break new ground for building brain-activity-based interactive image retrieval systems, as well as for systems utilizing feedback both from brain activity and eye movements. Copyright © 2015 Elsevier Inc. All rights reserved.

Latest News from the MEG Experiment

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CERN. Geneva

2013-01-01

Within the Standard Model (SM), in spite of neutrino oscillations, the flavor of charged leptons is conserved in very good approximation, and therefore charged Lepton Flavor Violation (cLFV) is expected to be unobservable. On the other hand, most new physics models predict cLFV at a level within the experimental reach, and processes like the mu to e gamma decay became standard probes for physics beyond the SM. The MEG experiment, at the Paul Scherrer Institute (Switzerland), searches for the mu to e gamma decay, down to a Branching Ratio of about 5 10^-13, exploiting the most intense continuous muon beam in the word and innovative detectors. In this seminar, I will present the most recent results from MEG, and the plan for an upgrade of the experiment, aiming at an improvement of the sensitivity by one order of magnitude within this decade.

Scalp Dose Evaluation According Radiation Therapy Technique of Whole Brain Radiation Therapy

International Nuclear Information System (INIS)

Jang, Joon Yung; Park, Soo Yun; Kim, Jong Sik; Choi, Byeong Gi; Song, Gi Won

2011-01-01

Opposing portal irradiation with helmet field shape that has been given to a patient with brain metastasis can cause excess dose in patient's scalp, resulting in hair loss. For this reason, this study is to quantitatively analyze scalp dose for effective prevention of hair loss by comparing opposing portal irradiation with scalp-shielding shape and tomotherapy designed to protect patient's scalp with conventional radiation therapy. Scalp dose was measured by using three therapies (HELMET, MLC, TOMO) after five thermo-luminescence dosimeters were positioned along center line of frontal lobe by using RANDO Phantom. Scalp dose and change in dose distribution were compared and analyzed with DVH after radiation therapy plan was made by using Radiation Treatment Planning System (Pinnacle3, Philips Medical System, USA) and 6 MV X-ray (Clinac 6EX, VARIAN, USA). When surface dose of scalp by using thermo-luminescence dosimeters was measured, it was revealed that scalp dose decreased by average 87.44% at each point in MLC technique and that scalp dose decreased by average 88.03% at each point in TOMO compared with HELMET field therapy. In addition, when percentage of volume (V95%, V100%, V105% of prescribed dose) was calculated by using Dose Volume Histogram (DVH) in order to evaluate the existence or nonexistence of hotspot in scalp as to three therapies (HELMET, MLC, TOMO), it was revealed that MLC technique and TOMO plan had good dose coverage and did not have hot spot. Reducing hair loss of a patient who receives whole brain radiotherapy treatment can make a contribution to improve life quality of the patient. It is expected that making good use of opposing portal irradiation with scalp-shielding shape and tomotherapy to protect scalp of a patient based on this study will reduce hair loss of a patient.

Scalp Dose Evaluation According Radiation Therapy Technique of Whole Brain Radiation Therapy

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Jang, Joon Yung; Park, Soo Yun; Kim, Jong Sik; Choi, Byeong Gi; Song, Gi Won [Dept. of Radiation Oncology, Samsung Medical Center, Seoul (Korea, Republic of)

2011-09-15

Opposing portal irradiation with helmet field shape that has been given to a patient with brain metastasis can cause excess dose in patient's scalp, resulting in hair loss. For this reason, this study is to quantitatively analyze scalp dose for effective prevention of hair loss by comparing opposing portal irradiation with scalp-shielding shape and tomotherapy designed to protect patient's scalp with conventional radiation therapy. Scalp dose was measured by using three therapies (HELMET, MLC, TOMO) after five thermo-luminescence dosimeters were positioned along center line of frontal lobe by using RANDO Phantom. Scalp dose and change in dose distribution were compared and analyzed with DVH after radiation therapy plan was made by using Radiation Treatment Planning System (Pinnacle3, Philips Medical System, USA) and 6 MV X-ray (Clinac 6EX, VARIAN, USA). When surface dose of scalp by using thermo-luminescence dosimeters was measured, it was revealed that scalp dose decreased by average 87.44% at each point in MLC technique and that scalp dose decreased by average 88.03% at each point in TOMO compared with HELMET field therapy. In addition, when percentage of volume (V95%, V100%, V105% of prescribed dose) was calculated by using Dose Volume Histogram (DVH) in order to evaluate the existence or nonexistence of hotspot in scalp as to three therapies (HELMET, MLC, TOMO), it was revealed that MLC technique and TOMO plan had good dose coverage and did not have hot spot. Reducing hair loss of a patient who receives whole brain radiotherapy treatment can make a contribution to improve life quality of the patient. It is expected that making good use of opposing portal irradiation with scalp-shielding shape and tomotherapy to protect scalp of a patient based on this study will reduce hair loss of a patient.

Nonlinear analysis of EEGs of patients with major depression during different emotional states.

Science.gov (United States)

Akdemir Akar, Saime; Kara, Sadık; Agambayev, Sümeyra; Bilgiç, Vedat

2015-12-01

Although patients with major depressive disorder (MDD) have dysfunctions in cognitive behaviors and the regulation of emotions, the underlying brain dynamics of the pathophysiology are unclear. Therefore, nonlinear techniques can be used to understand the dynamic behavior of the EEG signals of MDD patients. To investigate and clarify the dynamics of MDD patients׳ brains during different emotional states, EEG recordings were analyzed using nonlinear techniques. The purpose of the present study was to assess whether there are different EEG complexities that discriminate between MDD patients and healthy controls during emotional processing. Therefore, nonlinear parameters, such as Katz fractal dimension (KFD), Higuchi fractal dimension (HFD), Shannon entropy (ShEn), Lempel-Ziv complexity (LZC) and Kolmogorov complexity (KC), were computed from the EEG signals of two groups under different experimental states: noise (negative emotional content) and music (positive emotional content) periods. First, higher complexity values were generated by MDD patients relative to controls. Significant differences were obtained in the frontal and parietal scalp locations using KFD (pemotional bias was demonstrated by their higher brain complexities during the noise period than the music stimulus. Additionally, we found that the KFD, HFD and LZC values were more sensitive in discriminating between patients and controls than the ShEn and KC measures, according to the results of ANOVA and ROC calculations. It can be concluded that the nonlinear analysis may be a useful and discriminative tool in investigating the neuro-dynamic properties of the brain in patients with MDD during emotional stimulation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Poliosis circumscripta unmasking a scalp melanoma.

Science.gov (United States)

Yeo, L; Husain, E; Rajpara, S

2015-12-01

A 28-year-old man presented with a 1-year history of a localized patch of grey hair and an underlying darkly pigmented lesion on his right occipital area. Clinical appearance revealed poliosis overlying an asymmetrical plaque with variable degrees of brown pigmentation and white discolouration. Owing to the suspicious nature of the lesion, excision with a 2 mm margin was performed. Histology revealed an invasive melanoma with extensive regression and prominent involvement of multiple hair follicles. Scalp melanoma with associated poliosis is extremely rare, and has only been reported once in the literature to date. There have been two reports in the opthalmology literature regarding eyelash poliosis associated with orbital melanoma. The pathogenesis of poliosis still remains unclear. This is the second reported case of poliosis circmscripta unmasking a scalp melanoma, and highlights the importance of being vigilant when examining patients with poliosis of the scalp. © 2014 British Association of Dermatologists.

Advanced electronics for the CTF MEG system.

Science.gov (United States)

McCubbin, J; Vrba, J; Spear, P; McKenzie, D; Willis, R; Loewen, R; Robinson, S E; Fife, A A

2004-11-30

Development of the CTF MEG system has been advanced with the introduction of a computer processing cluster between the data acquisition electronics and the host computer. The advent of fast processors, memory, and network interfaces has made this innovation feasible for large data streams at high sampling rates. We have implemented tasks including anti-alias filter, sample rate decimation, higher gradient balancing, crosstalk correction, and optional filters with a cluster consisting of 4 dual Intel Xeon processors operating on up to 275 channel MEG systems at 12 kHz sample rate. The architecture is expandable with additional processors to implement advanced processing tasks which may include e.g., continuous head localization/motion correction, optional display filters, coherence calculations, or real time synthetic channels (via beamformer). We also describe an electronics configuration upgrade to provide operator console access to the peripheral interface features such as analog signal and trigger I/O. This allows remote location of the acoustically noisy electronics cabinet and fitting of the cabinet with doors for improved EMI shielding. Finally, we present the latest performance results available for the CTF 275 channel MEG system including an unshielded SEF (median nerve electrical stimulation) measurement enhanced by application of an adaptive beamformer technique (SAM) which allows recognition of the nominal 20-ms response in the unaveraged signal.

A lipohydroxyacid-containing shampoo improves scalp condition and quality of life in patients with seborrheic dermatitis and light-to-moderate scalp psoriasis.

Science.gov (United States)

Seité, S; Paries, J; Reygagne, P; Hamidou, Z; Jouanique, C; Perez-Pala, G; Rougier, A

2009-06-01

Dandruff is a common scalp disorder affecting almost half of the post-pubertal population of any ethnicity and both genders. It is one of the major reasons for patients to consult a dermatologist and it is the cause of significant psychological and social distress. The aim of this open study was to evaluate the benefit of a 4-week treatment with a shampoo containing 0.1% lipohydroxyacid (LHA) and 1.3% salicylic acid on the scalp condition and on the quality of life of 275 volunteers with seborrheic dermatitis (SD) (n = 226) or light-to-moderate scalp psoriasis (SP) (n = 49). The clinical benefit of the treatment was assessed by scoring the following parameters, i.e., severity of the dermatosis, scaling, itching, excoriations, and superficial burning sensation. The impact on the quality of life was assessed using the Scalpdex, a questionnaire specially developed by Chen et al. for patients with scalp dermatitis, which includes 23 questions regarding the symptoms, functioning and emotions affected by scalp dermatosis. The shampoo used in this study was well tolerated. After a 4-week treatment, dermatologists noticed a significant clinical improvement of all the scalp parameters evaluated (i.e., the composite lesional score was improved in 91% and 77% of the patients with SD or SP respectively). The symptoms, functioning and emotions scores of quality of life were also significantly improved in relation to the improvement of scalp condition. This study not only allowed a better understanding of the SD and SP patient's profile but also demonstrated that the shampoo evaluated is a convenient, efficient, safe, and well-tolerated cosmetic treatment of SD and light-to-moderate SP improving greatly the quality of life of the treated patients.

Incidental Syringomas of the Scalp in a Patient with Scarring Alopecia

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Kristyn Deen

2015-07-01

Full Text Available Syringomas are benign adnexal neoplasms of eccrine lineage, which occur most commonly in the periorbital region in middle-aged females. These cutaneous lesions rarely occur on the scalp, are typically asymptomatic and are predominantly of cosmetic significance. Involvement of the scalp may be indistinguishable from that of scarring alopecia. We present an unusual case of clinically inapparent syringomas occurring on the scalp of a 56-year-old female with alopecia who was subsequently diagnosed with lichen planopilaris after repeated scalp biopsy. In patients with unexplained hair loss, or in cases that are refractive to treatment, clinicians should perform scalp biopsy to exclude the diagnosis of rare neoplastic lesions like syringomas and to diagnose associated conditions.

Fenofibrate inhibited pancreatic cancer cells proliferation via activation of p53 mediated by upregulation of LncRNA MEG3

International Nuclear Information System (INIS)

Hu, Duanmin; Su, Cunjin; Jiang, Min; Shen, Yating; Shi, Aiming; Zhao, Fenglun; Chen, Ruidong; Shen, Zhu; Bao, Junjie; Tang, Wen

2016-01-01

There is still no suitable drug for pancreatic cancer treatment, which is one of the most aggressive human tumors. Maternally expressed gene 3 (MEG3), a LncRNA, has been suggested as a tumor suppressor in a range of human tumors. Studies found fenofibrate exerted anti-tumor roles in various human cancer cell lines. However, its role in pancreatic cancer remains unknown. The present study aimed to explore the impacts of fenofibrate on pancreatic cancer cell lines, and to investigate MEG3 role in its anti-tumor mechanisms. We used MTT assay to determine cells proliferation, genome-wide LncRNA microarray analysis to identify differently expressed LncRNAs, siRNA or pCDNA-MEG3 transfection to interfere or upregulate MEG3 expression, western blot to detect protein levels, real-time PCR to determine MEG3 level. Fenofibrate significantly inhibited proliferation of pancreatic cancer cells, increased MEG3 expression and p53 levels. Moreover, knockdown of MEG3 attenuated cytotoxicity induced by fenofibrate. Furthermore, overexpression of MEG3 induced cells death and increased p53 expression. Our results indicated fenofibrate inhibited pancreatic cancer cells proliferation via activation of p53 mediated by upregulation of MEG3. - Highlights: • We found that fenofibrate suppressed proliferation of pancreatic cancer cells. • We found fenofibrate increased LncRNA-MEG3 expression and p53 level in PANC-1 cells. • Inhibition of MEG3 expression attenuated anti-tumor effects of fenofibrate.

Fenofibrate inhibited pancreatic cancer cells proliferation via activation of p53 mediated by upregulation of LncRNA MEG3

Energy Technology Data Exchange (ETDEWEB)

Hu, Duanmin [Department of Gastroenterology, The Second Affiliated Hospital of Soochow University, Suzhou 215004 (China); Su, Cunjin [Department of Pharmacy, The Second Affiliated Hospital of Soochow University, Suzhou 215004 (China); Jiang, Min [Department of Breast Surgery, The First Affiliated Hospital of Soochow University, Suzhou 215004 (China); Shen, Yating [Department of Gastroenterology, The Second Affiliated Hospital of Soochow University, Suzhou 215004 (China); Shi, Aiming; Zhao, Fenglun [Department of Pharmacy, The Second Affiliated Hospital of Soochow University, Suzhou 215004 (China); Chen, Ruidong [Department of Gastroenterology, The Second Affiliated Hospital of Soochow University, Suzhou 215004 (China); Shen, Zhu [Department of Pharmacy, The Second Affiliated Hospital of Soochow University, Suzhou 215004 (China); Bao, Junjie, E-mail: baojjsdfey@sina.com [Department of Pharmacy, The Second Affiliated Hospital of Soochow University, Suzhou 215004 (China); Tang, Wen, E-mail: sztangwen@163.com [Department of Gastroenterology, The Second Affiliated Hospital of Soochow University, Suzhou 215004 (China)

2016-03-04

There is still no suitable drug for pancreatic cancer treatment, which is one of the most aggressive human tumors. Maternally expressed gene 3 (MEG3), a LncRNA, has been suggested as a tumor suppressor in a range of human tumors. Studies found fenofibrate exerted anti-tumor roles in various human cancer cell lines. However, its role in pancreatic cancer remains unknown. The present study aimed to explore the impacts of fenofibrate on pancreatic cancer cell lines, and to investigate MEG3 role in its anti-tumor mechanisms. We used MTT assay to determine cells proliferation, genome-wide LncRNA microarray analysis to identify differently expressed LncRNAs, siRNA or pCDNA-MEG3 transfection to interfere or upregulate MEG3 expression, western blot to detect protein levels, real-time PCR to determine MEG3 level. Fenofibrate significantly inhibited proliferation of pancreatic cancer cells, increased MEG3 expression and p53 levels. Moreover, knockdown of MEG3 attenuated cytotoxicity induced by fenofibrate. Furthermore, overexpression of MEG3 induced cells death and increased p53 expression. Our results indicated fenofibrate inhibited pancreatic cancer cells proliferation via activation of p53 mediated by upregulation of MEG3. - Highlights: • We found that fenofibrate suppressed proliferation of pancreatic cancer cells. • We found fenofibrate increased LncRNA-MEG3 expression and p53 level in PANC-1 cells. • Inhibition of MEG3 expression attenuated anti-tumor effects of fenofibrate.

Mixed-norm estimates for the M/EEG inverse problem using accelerated gradient methods.

Science.gov (United States)

Gramfort, Alexandre; Kowalski, Matthieu; Hämäläinen, Matti

2012-04-07

Magneto- and electroencephalography (M/EEG) measure the electromagnetic fields produced by the neural electrical currents. Given a conductor model for the head, and the distribution of source currents in the brain, Maxwell's equations allow one to compute the ensuing M/EEG signals. Given the actual M/EEG measurements and the solution of this forward problem, one can localize, in space and in time, the brain regions that have produced the recorded data. However, due to the physics of the problem, the limited number of sensors compared to the number of possible source locations, and measurement noise, this inverse problem is ill-posed. Consequently, additional constraints are needed. Classical inverse solvers, often called minimum norm estimates (MNE), promote source estimates with a small ℓ₂ norm. Here, we consider a more general class of priors based on mixed norms. Such norms have the ability to structure the prior in order to incorporate some additional assumptions about the sources. We refer to such solvers as mixed-norm estimates (MxNE). In the context of M/EEG, MxNE can promote spatially focal sources with smooth temporal estimates with a two-level ℓ₁/ℓ₂ mixed-norm, while a three-level mixed-norm can be used to promote spatially non-overlapping sources between different experimental conditions. In order to efficiently solve the optimization problems of MxNE, we introduce fast first-order iterative schemes that for the ℓ₁/ℓ₂ norm give solutions in a few seconds making such a prior as convenient as the simple MNE. Furthermore, thanks to the convexity of the optimization problem, we can provide optimality conditions that guarantee global convergence. The utility of the methods is demonstrated both with simulations and experimental MEG data.

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

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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.

Effect of a Scalp Cooling Device on Alopecia in Women Undergoing Chemotherapy for Breast Cancer: The SCALP Randomized Clinical Trial.

Science.gov (United States)

Nangia, Julie; Wang, Tao; Osborne, Cynthia; Niravath, Polly; Otte, Kristen; Papish, Steven; Holmes, Frankie; Abraham, Jame; Lacouture, Mario; Courtright, Jay; Paxman, Richard; Rude, Mari; Hilsenbeck, Susan; Osborne, C Kent; Rimawi, Mothaffar

2017-02-14

Chemotherapy may induce alopecia. Although scalp cooling devices have been used to prevent this alopecia, efficacy has not been assessed in a randomized clinical trial. To assess whether a scalp cooling device is effective at reducing chemotherapy-induced alopecia and to assess adverse treatment effects. Multicenter randomized clinical trial of women with breast cancer undergoing chemotherapy. Patients were enrolled from December 9, 2013, to September 30, 2016. One interim analysis was planned to allow the study to stop early for efficacy. Data reported are from the interim analysis. This study was conducted at 7 sites in the United States, and 182 women with breast cancer requiring chemotherapy were enrolled and randomized. Participants were randomized to scalp cooling (n = 119) or control (n = 63). Scalp cooling was done using a scalp cooling device. The primary efficacy end points were successful hair preservation assessed using the Common Terminology Criteria for Adverse Events version 4.0 scale (grade 0 [no hair loss] or grade 1 [Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30, Hospital Anxiety and Depression Scale, and a summary scale of the Body Image Scale. At the time of the interim analysis, 142 participants were evaluable. The mean (SD) age of the patients was 52.6 (10.1) years; 36% (n = 51) received anthracycline-based chemotherapy and 64% (n = 91) received taxane-based chemotherapy. Successful hair preservation was found in 48 of 95 women with cooling (50.5%; 95% CI, 40.7%-60.4%) compared with 0 of 47 women in the control group (0%; 95% CI, 0%-7.6%) (success rate difference, 50.5%; 95% CI, 40.5%-60.6%). Because the 1-tailed P value from the Fisher exact test was women with stage I to II breast cancer receiving chemotherapy with a taxane, anthracycline, or both, those who underwent scalp cooling were significantly more likely to have less than 50% hair loss after the fourth chemotherapy cycle

Radiation therapy for angiosarcoma of the scalp. Treatment outcomes of total scalp irradiation with X-rays and electrons

Energy Technology Data Exchange (ETDEWEB)

Hata, Masaharu; Koike, Izumi; Kasuya, Takeo; Inoue, Tomio [Yokohama City University Graduate School of Medicine, Department of Radiology, Yokohama, Kanagawa (Japan); Wada, Hidefumi [Yokohama City University Graduate School of Medicine, Department of Dermatology, Yokohama, Kanagawa (Japan); Ogino, Ichiro [Yokohama City University Medical Center, Department of Radiation Oncology, Yokohama, Kanagawa (Japan); Omura, Motoko [Yokohama City University Graduate School of Medicine, Department of Radiology, Yokohama, Kanagawa (Japan); Shonankamakura General Hospital, Department of Radiation Oncology, Kamakura, Kanagawa (Japan); Tayama, Yoshibumi [Yokohama Minami Kyousai Hospital, Department of Radiology, Yokohama, Kanagawa (Japan); Odagiri, Kazumasa [Yokohama City University Graduate School of Medicine, Department of Radiology, Yokohama, Kanagawa (Japan); Yokohama Municipal Citizen' s Hospital, Department of Radiation Oncology, Yokohama, Kanagawa (Japan)

2014-10-15

Wide surgical excision is the standard treatment for angiosarcoma of the scalp, but many patients are inoperable. Therefore, we investigated the outcome of radiation therapy for angiosarcoma of the scalp. Seventeen patients with angiosarcoma of the scalp underwent radiation therapy with total scalp irradiation. Four patients had cervical lymph node metastases, but none had distant metastases. A median initial dose of 50 Gy in 25 fractions was delivered to the entire scalp. Subsequently, local radiation boost to the tumor sites achieved a median total dose of 70 Gy in 35 fractions. Fourteen of the 17 patients developed recurrences during the median follow-up period of 14 months after radiation therapy; 7 had recurrences in the scalp, including primary tumor progression in 2 patients and new disease in 5, and 12 patients developed distant metastases. The primary progression-free, scalp relapse-free, and distant metastasis-free rates were 86, 67, and 38 % at 1 year and 86, 38, and 16 % at 3 years, respectively. Thirteen patients died; the overall and cause-specific survival rates were both 73 % at 1 year and 23 and 44 % at 3 years, respectively. The median survival time was 16 months. There were no therapy-related toxicities ≥ grade 3. Total scalp irradiation is safe and effective for local tumor control, but a dose of ≤ 50 Gy in conventional fractions may be insufficient to eradicate microscopic tumors. For gross tumors, a total dose of 70 Gy, and > 70 Gy for tumors with deep invasion, is recommended. (orig.) [German] Umfangreiche chirurgische Exzision ist die Standardbehandlung fuer Angiosarkome der Kopfhaut, aber viele Patienten sind nicht operierbar. Daher haben wir die Ergebnisse einer Strahlenbehandlung fuer Angiosarkome der Kopfhaut untersucht. Insgesamt 17 Patienten mit Angiosarkom der Kopfhaut erhielten eine Strahlenbehandlung der gesamten Kopfhaut. Vier Patienten hatten zervikale Lymphknotenmetastasen, aber keine Fernmetastasen. Die gesamte Kopfhaut

Total scalp irradiation using helical tomotherapy

International Nuclear Information System (INIS)

Orton, Nigel; Jaradat, Hazim; Welsh, James; Tome, Wolfgang

2005-01-01

Homogeneous irradiation of the scalp poses technical and dosimetric challenges due to the extensive, superficial, curved treatment volume. Conventional treatments on a linear accelerator use multiple matched electron fields or a combination of electron and photon fields. Problems with these techniques include dose heterogeneity in the target due to varying source-to-skin distance (SSD) and angle of beam incidence, significant dose to the brain, and the potential for overdose or underdose at match lines between the fields. Linac-based intensity-modulated radiation therapy (IMRT) plans have similar problems. This work presents treatment plans for total scalp irradiation on a helical tomotherapy machine. Helical tomotherapy is well-suited for scalp irradiation because it has the ability to deliver beamlets that are tangential to the scalp at all points. Helical tomotherapy also avoids problems associated with field matching and use of more than one modality. Tomotherapy treatment plans were generated and are compared to plans for treatment of the same patient on a linac. The resulting tomotherapy plans show more homogeneous target dose and improved critical structure dose when compared to state-of-the-art linac techniques. Target equivalent uniform dose (EUD) for the best tomotherapy plan was slightly higher than for the linac plan, while the volume of brain tissue receiving over 30 Gy was reduced by two thirds. Furthermore, the tomotherapy plan can be more reliably delivered than linac treatments, because the patient is aligned prior to each treatment based on megavoltage computed tomography (MVCT)

Diagnostic Accuracy of microEEG: A Miniature, Wireless EEG Device

OpenAIRE

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

2014-01-01

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

IMPORTANCE OF THE TRICHOSCOPY IN SCALP DYSESTHESIA

Directory of Open Access Journals (Sweden)

Maria Bibiana Leroux

2013-10-01

Full Text Available The trichoscopy has been incorporated as a first hand method in patients consulting for scalp problems. Magnifying glass or digital microscope that permit the direct visualization of the hair shaft and the perifolicullar skin are utilized to diagnose cicatricial and non-cicatricial alopecia. A female patient with an alopecia plaque associated with a scalp dysesthesia in which trichoscopy was very useful in its diagnosis is presented.

Clinical and EEG features of ischemic stroke patients with abnormal discharges

Directory of Open Access Journals (Sweden)

Jia-lei YANG

2016-05-01

Full Text Available Objective To investigate the clinical and EEG features of ischemic stroke patients with abnormal discharges.  Methods Clinical data and 24-hour EEG monitoring of 162 ischemic stroke patients were analyzed retrospectively. One-year follow-up was carried out and post-ischemic epilepsy was diagnosed.  Results Among 162 ischemic stroke patients, 24-hour EEG was abnormal in 87 cases (53.70%. According to the correspondence of site of infarcts and abnormal discharges, these 87 cases were classified into 2 groups: matched group (N = 24, 27.59% and unmatched group (N = 63, 72.41%. There was no significant difference between 2 groups in terms of Oxfordshire Community Stroke Project (OCSP and TOAST classification (P = 0.792, 0.111, while there was significant difference between 2 groups on the site of infarcts (P = 0.000. In matched group, the infarcts were mainly located in cortex (N = 23, 95.83%. However, in unmatched group, the infarcts were mainly located in cortex and basal ganglia (N = 27, 42.86%, or in basal ganglia only (N = 24, 38.10%. In matched group, 24-hour EEG showed slowing of background activities, and sharp waves and sharp and slow wave complex which were corresponding to the infarct sites. The abnormal discharges could only be recorded around the infarct unilaterally. In unmatched group, the epileptiform discharges were recorded in both contralateral and ipsilateral ischemic hemispheres, usually with widespread slow waves and asymmetric background. The infarcts were limited, but abnormal discharges were widespread. For example, the infarct was located in deep brain, while scalp abnormal discharges were recorded. Although there was no significant difference in terms of epilepsy incidence between 2 groups (P = 0.908, the types of epilepsy were statistically different between 2 groups (P = 0.000. In matched group, the main type was partial seizure. But in unmatched group, the main types of epilepsy were secondary generalized seizure and

MEG source localization using invariance of noise space.

Directory of Open Access Journals (Sweden)

Junpeng Zhang

Full Text Available We propose INvariance of Noise (INN space as a novel method for source localization of magnetoencephalography (MEG data. The method is based on the fact that modulations of source strengths across time change the energy in signal subspace but leave the noise subspace invariant. We compare INN with classical MUSIC, RAP-MUSIC, and beamformer approaches using simulated data while varying signal-to-noise ratios as well as distance and temporal correlation between two sources. We also demonstrate the utility of INN with actual auditory evoked MEG responses in eight subjects. In all cases, INN performed well, especially when the sources were closely spaced, highly correlated, or one source was considerably stronger than the other.

Complexity Analysis of Resting-State MEG Activity in Early-Stage Parkinson's Disease Patients

NARCIS (Netherlands)

Gómez, C.; Olde Dubbelink, K.T.E.; Stam, C.J.; Abasolo, D.; Berendse, H.W.; Hornero, R.

2011-01-01

The aim of the present study was to analyze resting-state brain activity in patients with Parkinson's disease (PD), a degenerative disorder of the nervous system. Magnetoencephalography (MEG) signals were recorded with a 151-channel whole-head radial gradiometer MEG system in 18 early-stage

EEG Topographic Mapping of Visual and Kinesthetic Imagery in Swimmers.

Science.gov (United States)

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

2016-03-01

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

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

Science.gov (United States)

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

2008-04-07

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

Cortico-muscular coherence on artifact corrected EEG-EMG data recorded with a MRI scanner.

Science.gov (United States)

Muthuraman, M; Galka, A; Hong, V N; Heute, U; Deuschl, G; Raethjen, J

2013-01-01

Simultaneous recording of electroencephalogram (EEG) and electromyogram (EMG) with magnetic resonance imaging (MRI) provides great potential for studying human brain activity with high temporal and spatial resolution. But, due to the MRI, the recorded signals are contaminated with artifacts. The correction of these artifacts is important to use these signals for further spectral analysis. The coherence can reveal the cortical representation of peripheral muscle signal in particular motor tasks, e.g. finger movements. The artifact correction of these signals was done by two different algorithms the Brain vision analyzer (BVA) and the Matlab FMRIB plug-in for EEGLAB. The Welch periodogram method was used for estimating the cortico-muscular coherence. Our analysis revealed coherence with a frequency of 5Hz in the contralateral side of the brain. The entropy is estimated for the calculated coherence to get the distribution of coherence in the scalp. The significance of the paper is to identify the optimal algorithm to rectify the MR artifacts and as a first step to use both these signals EEG and EMG in conjunction with MRI for further studies.

Barriers and enablers to implementing scalp cooling in Australia: a qualitative study of health professionals' attitudes to and experience with scalp cooling.

Science.gov (United States)

Shaw, Joanne M; O'Brien, Jane; Chua, Susan; De Boer, Richard; Dear, Rachel; Murray, Nicholas; Boyle, Fran

2018-01-01

Chemotherapy-induced alopecia is a common and distressing adverse event for patients. Scalp cooling to reduce this alopecia has been available in Europe for more than a decade, but only recently introduced in Australia. The aim of this study was to qualitatively explore health professionals' perceptions of the barriers and enablers to the implementation of scalp cooling in Australian cancer centres. Using a qualitative methodology, telephone interviews were conducted with 21 health professionals working in a tumour stream where chemotherapy-induced alopecia is an adverse event of treatment. Participants were recruited from five centres in Australia where scalp cooling is currently available and one centre without access to the technology. Four interrelated themes were identified: (1) health professional attitudes, (2) concerns for patient equity, (3) logistical considerations and (4) organisational support. This qualitative study provides the first methodological exploration of Australian health professionals' perceptions of barriers and enablers to scalp cooling uptake. The results highlighted health professional support drives the introduction of scalp cooling. Integration of the technology requires adjustments to nursing practice to manage the increased time, workload and change in patient flow. Strategies to manage the change in practice and organisational support for change in work flow are essential for successful implementation into routine care.

Actinomycetoma of the scalp after a car accident.

Science.gov (United States)

Welsh, Oliverio; Morales-Toquero, Amelia; Vera-Cabrera, Lucio; Cabrera-Vera, Lucio; Vazquez-Martinez, Osvaldo; Gómez-Flores, Minerva; Ocampo-Candiani, Jorge

2011-07-01

Actinomycetoma is the most frequent type of mycetoma in Mexico. Localization on the scalp is very rare. Because of this topography and potential spread to the brain, the present case became a diagnostic and therapeutic challenge. We report the case of a 44-year-old woman with a 6 × 5 cm red, friable, granulomatous, vascular neoformation on the scalp and eye diagnosed as Nocardia brasiliensis actinomycetoma. A combination of amikacin and oral trimethoprim-sulfamethoxazole (SXT) was successfully administered with an excellent outcome and no side effects. This is a rare presentation of mycetoma of the scalp that was cured in 12 weeks with a combination of amikacin and SXT. © 2011 The International Society of Dermatology.

Measurement and imaging of brain function using MRI, MEG, and TMS

International Nuclear Information System (INIS)

Iramina, Keiji

2008-01-01

This paper reviews functional imaging techniques in neuroscience such as magnetic resonance imaging (MRI) functional MRI (fMRI), magnetoencephalogray (MEG), and transcranial magnetic stimulation (TMS). fMRI and MEG allow the neuronal activity of the brain to be measured non-invasively. MEG detects an electrical activity as neuronal activity, while, fMRI detects a hemodynamic response as neuronal activity. TMS is the application of a brief magnetic pulse or a train of pulses to the skull, which results in the induction of a local electric current in the underlying surface of the brain, thereby producing a localized axonal depolarization. As a non-invasive and effective method to make reversible lesions in the human brain, TMS has a long and successful history. All of these techniques have major potential for applications in the neuroscience and medicine. (author)

Body to scalp: Evolving trends in body hair transplantation

Directory of Open Access Journals (Sweden)

Kuldeep Saxena

2017-01-01

Full Text Available Follicular unit extraction (FUE is becoming an increasingly popular method for hair restoration. As FUE leaves behind no linear scars, it is more suitable to harvest from various body areas including beard, chest, and extremities in hirsute individuals. Body hair characteristics such as thickness, length, and hair cycle may not completely match to that of the scalp hair. The techniques of harvesting body hairs are more time consuming, requiring higher degree of skill than regular scalp FUE. Body hair transplantation can be successfully used either alone or in combination with scalp hair in advanced grades of baldness, for improving the cosmetic appearance of hairlines and in scarring alopecia when there is paucity of donor scalp hair. Harvesting of body hairs opens up a new viable donor source for hair restoration surgeons, especially in cases of advanced Norwood grades five and above of androgenetic alopecia.

Neglected Giant Scalp Basal Cell Carcinoma

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Anne Kristine Larsen, MD

2014-03-01

Full Text Available Summary: Rarely, basal cell carcinoma grows to a giant size, invading the underlying deep tissue and complicating the treatment and reconstruction modalities. A giant basal cell carcinoma on the scalp is in some cases treated with a combination of surgery and radiation therapy, resulting in local control, a satisfactory long-term cosmetic and functional result. We present a case with a neglected basal cell scalp carcinoma, treated with wide excision and postoperative radiotherapy, reconstructed with a free latissimus dorsi flap. The cosmetic result is acceptable and there is no sign of recurrence 1 year postoperatively.

The drift chamber system of the MEG experiment

Energy Technology Data Exchange (ETDEWEB)

Hildebrandt, Malte, E-mail: malte.hildebrandt@psi.c [Paul Scherrer Institut, CH-5232 Villigen PSI (Switzerland)

2010-11-01

The MEG experiment searches for the lepton flavour violating decay {mu}{yields}e{gamma} and is aiming for a sensitivity of 10{sup -13} in the branching ratio in order to probe new physics beyond the standard model. The experiment is located at the Paul Scherrer Institut (PSI) in Switzerland, where one of the world's most intensive surface muon beams is located. Physics data taking started in September 2008. The drift chamber system is part of the innovative positron spectrometer of the MEG experiment and consists of 16 drift chamber modules. The system is designed to ensure precision measurement of 52.8 MeV/c positrons. Design, construction, geometrical alignment and performance of the drift chamber system are presented.

Ultrasonography of Midline Scalp Masses : A Preliminary Report

Energy Technology Data Exchange (ETDEWEB)

Choi, Hyo Kyeong; Lee, Ho Kyu; Choi, Choong Gon; Kim, Kyeong Sook; Jung, Seung Mun; Suh, Dae Chul [Asan Medical Center University of Ulsan College of Medicine, Seoul (Korea, Republic of)

1995-06-15

We report our ultrasonographic experiences in the evaluation of small midline scalp masses. Ultrasonography was performed in four patients with midline scalp mass less than 3cm and its connecting tract into the cranialcavity. Ultrasonographic findings were correlated with pathologic results. There were three cephaloceles and one cystic lymph angioma. Two encephalomenin-goceles, located in occipital region, were mixed cystic and solid lesions and one atretic meningocele in parietal region was a solid lesion. Ultrasonogram of all three cases showed calvarial defect and connecting tract into the cranial cavity. On the contrary, a cystic lymph angioma in occipital region was a purely cystic mass without an associated calvarial defect. We suppose that ultrasonography could be a useful screening tool in the evaluation of midline scalp masses

Scalp edema: don't forget sunburn in children.

Science.gov (United States)

Shah, Binod; Yavuz, Süleyman Tolga; Tekşam, Ozlem

2012-01-01

Scalp edema is an uncommon and striking finding in children that may alarm both parents and physicians. The objectives of this case report were to raise awareness among pediatric emergency physicians of the unusual presentation of sunburn as scalp edema. We present the case of an eight-year-old boy with sunburn of the head, presenting with scalp and face edema. Pitting edema and erythema were dominant on the forehead. Shaving of the boy's head the day before the symptoms was the most striking issue, and the sunburn healed gradually without any complications. Healthcare professionals should be aware of this condition, and the diagnosis of sunburn must be kept in mind in otherwise healthy-looking patients with a unique history.

Macroanatomical Landmarks Featuring Junctions of Major Sulci and Fissures and Scalp Landmarks Based on the International 10–10 System for Analyzing Lateral Cortical Development of Infants

Directory of Open Access Journals (Sweden)

Daisuke Tsuzuki

2017-07-01

Full Text Available The topographic relationships between the macroanatomical structure of the lateral cortex, including sulci and fissures, and anatomical landmarks on the external surface of the head are known to be consistent. This allows the coregistration of EEG electrodes or functional near-infrared spectroscopy over the scalp with underlying cortical regions. However, limited information is available as to whether the topographic relationships are maintained in rapidly developing infants, whose brains and heads exhibit drastic growth. We used MRIs of infants ranging in age from 3 to 22 months old, and identified 20 macroanatomical landmarks, featuring the junctions of major sulci and fissures, as well as cranial landmarks and virtually determined positions of the international 10-20 and 10-10 systems. A Procrustes analysis revealed developmental trends in changes of shape in both the cortex and head. An analysis of Euclidian distances between selected pairs of cortical landmarks at standard stereotactic coordinates showed anterior shifts of the relative positions of the premotor and parietal cortices with age. Finally, cortical landmark positions and their spatial variability were compared with 10-10 landmark positions. The results indicate that variability in the distribution of each macroanatomical landmark was much smaller than the pitch of the 10-10 landmarks. This study demonstrates that the scalp-based 10-10 system serves as a good frame of reference in infants not only for assessing the development of the macroanatomy of the lateral cortical structure, but also for functional studies of cortical development using transcranial modalities such as EEG and fNIRS.

FY1995 study of the new generation system for the vector type biomagnetmeter and optimization of the system; 1995 nendo jisedai seitai jiki tajigen keisoku system oyobi saitekika no kenkyu

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-03-01

The most advanced devices for magneto-encephalography(MEG),so far developed are equipped with more than 100 channels which measure the z-component of the magnetic field perpendicular to the surface of the scalp or of the chest, However, there do not exist any multi-channel MEG measuring device capable of measuring the three components of the MEG vectors. The purpose of this study is to develop a SQUID magnetometer with more than 180 channels with the configuration for the three-component vector measurement and to apply the device to the investigation of the higher functions of the brain of which the mechanisms are still largely unknown. Furthermore, it will open up new clinical methods for various discases. 1) We arranged three coils in a column to measure the x,y and z-components of the magnetic field and arranged 60 of those columns so that they cover the whole scalp and measure the 3-component MEG at 60 points simultaneously. 2) We developed a dewar in which more than 200 SQUID elements can be immersed in liquid helium and at the same time the arrangement of the coils allows as close fit as possible to the scalp to be measured. 3) A gantry was developed for the above dewar so that the dewar might be fixed at an arbitary position and its vibrations were minimized. 4) DOIT-type circuit was adopted for the FLL circuit, which realized a simple system. 5) We established a signal processing system which samples the signal from all the SQUID sensors simultaneously at a high sampling rate and analyzes the data efficiently. 6) We measured 3-component MEG signals and found that it can bring out new information useful for investigating the higher functions of the brain. (NEDO)

Increased intra-participant variability in children with autistic spectrum disorder: Evidence from single trial analyses of evoked EEG.

Directory of Open Access Journals (Sweden)

Elizabeth eMilne

2011-03-01

Full Text Available Intra-participant variability in clinical conditions such as autistic spectrum disorder (ASD is an important indicator of pathophysiological processing. The data reported here illustrate that trial-by-trial variability can be reliably measured from EEG, and that intra-participant EEG variability is significantly greater in those with ASD than in neuro-typical matched controls. EEG recorded at the scalp is a linear mixture of activity arising from muscle artifacts and numerous concurrent brain processes. To minimise these additional sources of variability, EEG data were subjected to two different methods of spatial filtering. (i The data were decomposed using infomax Independent Component Analysis (ICA, a method of blind source separation which un-mixes the EEG signal into components with maximally independent time-courses, and (ii a surface Laplacian transform was performed (Current Source Density interpolation in order to reduce the effects of volume conduction. Data are presented from thirteen high functioning adolescents with ASD without co-morbid ADHD, and twelve neuro-typical age- IQ- and gender-matched controls. Comparison of variability between the ASD and neuro-typical groups indicated that intra-participant variability of P1 latency and P1 amplitude was greater in the participants with ASD, and inter-trial α-band phase coherence was lower in the participants with ASD. These data support the suggestion that individuals with ASD are less able to synchronise the activity of stimulus-related cell assemblies than neuro-typical individuals, and provide empirical evidence in support of theories of increased neural noise in ASD.

White piedra of scalp hair by Trichosporon inkin.

Science.gov (United States)

Viswanath, Vishalakshi; Kriplani, Dimple; Miskeen, Autar Kishen; Patel, Bharti; Torsekar, Raghunandan Govind

2011-01-01

White piedra is a rare fungal infection of hair and is reported to be all the more rare on scalp. Trichosporon inkin is usually associated with white piedra of pubic hair. We report a case of white piedra of scalp hair caused by T. inkin. This is the first case reported from India and the fifth case reported worldwide. A 50-year-old Muslim female presented with white knots over scalp hair. Diagnosis of Trichosporon was made by examining KOH mounts of epilated hair and Lactophenol Cotton Blue preparations of the growth in culture. Automated mini-API test (for biochemical profiles) and Electronmicroscopy studies (for cell wall structures) helped in identification of the species. Mini-API test was also positive for Cryptococcus curvatus which could be due to similarity in biochemical and physiological properties of the two species. Absence of C. curvatus on culture further supports this view. Topical antifungal therapy resulted in clinical clearance within 2 months. Higher incidence of scalp white piedra is observed in Muslim females; contributing factor being the custom of using a veil, leading to higher humidity and limited sunlight exposure.

Discrimination of cortical laminae using MEG.

Science.gov (United States)

Troebinger, Luzia; López, José David; Lutti, Antoine; Bestmann, Sven; Barnes, Gareth

2014-11-15

Typically MEG source reconstruction is used to estimate the distribution of current flow on a single anatomically derived cortical surface model. In this study we use two such models representing superficial and deep cortical laminae. We establish how well we can discriminate between these two different cortical layer models based on the same MEG data in the presence of different levels of co-registration noise, Signal-to-Noise Ratio (SNR) and cortical patch size. We demonstrate that it is possible to make a distinction between superficial and deep cortical laminae for levels of co-registration noise of less than 2mm translation and 2° rotation at SNR > 11 dB. We also show that an incorrect estimate of cortical patch size will tend to bias layer estimates. We then use a 3D printed head-cast (Troebinger et al., 2014) to achieve comparable levels of co-registration noise, in an auditory evoked response paradigm, and show that it is possible to discriminate between these cortical layer models in real data. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Significant one week efficacy of a calcipotriol plus betamethasone dipropionate scalp formulation

DEFF Research Database (Denmark)

Jemec, G.B.E.; Van De Kerkhof, P.C.M.; Enevold, A.

2011-01-01

Background A two-compound scalp formulation containing calcipotriol (50 μg/g) and betamethasone (0.5 mg/g; as dipropionate) (Xamiol, Taclonex Scalp) has been shown to be an effective and safe treatment for scalp psoriasis. Objective The aim of this study was to investigate the clinical efficacy o...

Epileptic MEG Spike Detection Using Statistical Features and Genetic Programming with KNN

Directory of Open Access Journals (Sweden)

Turky N. Alotaiby

2017-01-01

Full Text Available Epilepsy is a neurological disorder that affects millions of people worldwide. Monitoring the brain activities and identifying the seizure source which starts with spike detection are important steps for epilepsy treatment. Magnetoencephalography (MEG is an emerging epileptic diagnostic tool with high-density sensors; this makes manual analysis a challenging task due to the vast amount of MEG data. This paper explores the use of eight statistical features and genetic programing (GP with the K-nearest neighbor (KNN for interictal spike detection. The proposed method is comprised of three stages: preprocessing, genetic programming-based feature generation, and classification. The effectiveness of the proposed approach has been evaluated using real MEG data obtained from 28 epileptic patients. It has achieved a 91.75% average sensitivity and 92.99% average specificity.

Two-way regularization for MEG source reconstruction via multilevel coordinate descent

KAUST Repository

Siva Tian, Tian

2013-12-01

Magnetoencephalography (MEG) source reconstruction refers to the inverse problem of recovering the neural activity from the MEG time course measurements. A spatiotemporal two-way regularization (TWR) method was recently proposed by Tian et al. to solve this inverse problem and was shown to outperform several one-way regularization methods and spatiotemporal methods. This TWR method is a two-stage procedure that first obtains a raw estimate of the source signals and then refines the raw estimate to ensure spatial focality and temporal smoothness using spatiotemporal regularized matrix decomposition. Although proven to be effective, the performance of two-stage TWR depends on the quality of the raw estimate. In this paper we directly solve the MEG source reconstruction problem using a multivariate penalized regression where the number of variables is much larger than the number of cases. A special feature of this regression is that the regression coefficient matrix has a spatiotemporal two-way structure that naturally invites a two-way penalty. Making use of this structure, we develop a computationally efficient multilevel coordinate descent algorithm to implement the method. This new one-stage TWR method has shown its superiority to the two-stage TWR method in three simulation studies with different levels of complexity and a real-world MEG data analysis. © 2013 Wiley Periodicals, Inc., A Wiley Company.

MEG time-frequency analyses for pre- and post-surgical evaluation of patients with epileptic rhythmic fast activity.

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Sueda, Keitaro; Takeuchi, Fumiya; Shiraishi, Hideaki; Nakane, Shingo; Asahina, Naoko; Kohsaka, Shinobu; Nakama, Hideyuki; Otsuki, Taisuke; Sawamura, Yutaka; Saitoh, Shinji

2010-02-01

To evaluate the effectiveness of surgery for epilepsy, we analyzed rhythmic fast activity by magnetoencephalography (MEG) before and after surgery using time-frequency analysis. To assess reliability, the results obtained by pre-surgical MEG and intraoperative electrocorticography were compared. Four children with symptomatic localization-related epilepsy caused by circumscribed cortical lesion were examined in the present study using 204-channel helmet-shaped MEG with a sampling rate of 600Hz. One patient had dysembryoplastic neuroepithelial tumor (DNT) and three patients had focal cortical dysplasia (FCD). Aberrant areas were superimposed, to reconstruct 3D MRI images, and illustrated as moving images. In three patients, short-time Fourier transform (STFT) analyses of MEG showed rhythmic activities just above the lesion with FCD and in the vicinity of DNT. In one patient with FCD in the medial temporal lobe, rhythmic activity appeared in the ipsilateral frontal lobe and temporal lateral aspect. These findings correlate well with the results obtained by intraoperative electrocorticography. After the surgery, three patients were relieved of their seizures, and the area of rhythmic MEG activity disappeared or become smaller. One patient had residual rhythmic MEG activity, and she suffered from seizure relapse. Time-frequency analyses using STFT successfully depicted MEG rhythmic fast activity, and would provide valuable information for pre- and post-surgical evaluations to define surgical strategies for patients with epilepsy.

Analysis of EEG signals regularity in adults during video game play in 2D and 3D.

Science.gov (United States)

Khairuddin, Hamizah R; Malik, Aamir S; Mumtaz, Wajid; Kamel, Nidal; Xia, Likun

2013-01-01

Video games have long been part of the entertainment industry. Nonetheless, it is not well known how video games can affect us with the advancement of 3D technology. The purpose of this study is to investigate the EEG signals regularity when playing video games in 2D and 3D modes. A total of 29 healthy subjects (24 male, 5 female) with mean age of 21.79 (1.63) years participated. Subjects were asked to play a car racing video game in three different modes (2D, 3D passive and 3D active). In 3D passive mode, subjects needed to wear a passive polarized glasses (cinema type) while for 3D active, an active shutter glasses was used. Scalp EEG data was recorded during game play using 19-channel EEG machine and linked ear was used as reference. After data were pre-processed, the signal irregularity for all conditions was computed. Two parameters were used to measure signal complexity for time series data: i) Hjorth-Complexity and ii) Composite Permutation Entropy Index (CPEI). Based on these two parameters, our results showed that the complexity level increased from eyes closed to eyes open condition; and further increased in the case of 3D as compared to 2D game play.

On the Keyhole Hypothesis

DEFF Research Database (Denmark)

Mikkelsen, Kaare B.; Kidmose, Preben; Hansen, Lars Kai

2017-01-01

simultaneously recorded scalp EEG. A cross-validation procedure was employed to ensure unbiased estimates. We present several pieces of evidence in support of the keyhole hypothesis: There is a high mutual information between data acquired at scalp electrodes and through the ear-EEG "keyhole," furthermore we......We propose and test the keyhole hypothesis that measurements from low dimensional EEG, such as ear-EEG reflect a broadly distributed set of neural processes. We formulate the keyhole hypothesis in information theoretical terms. The experimental investigation is based on legacy data consisting of 10...

Decreased expression of MEG3 contributes to retinoblastoma progression and affects retinoblastoma cell growth by regulating the activity of Wnt/β-catenin pathway.

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Gao, Yali; Lu, Xiaohe

2016-02-01

The aberrant expression of MEG3 has been found in some types of cancers; however, little is known concerning the function of MEG3 in retinoblastoma. To elucidate the roles of MEG3 in retinoblastoma, MEG3 expression was quantified in 63 retinoblastoma samples and corresponding nontumor tissues in this work. Moreover, retinoblastoma cell lines were transfected with pcDNA3.1-MEG3 or si-MEG3, after which proliferation, apoptosis, and expression of β-catenin were assayed. TOP-Flash reporter assay was also used to investigate the activity of the Wnt/β-catenin pathway. The results showed that MEG3 was downregulated in retinoblastoma tissues, and the level of MEG3 was negatively associated with IIRC stages and nodal or distant metastasis. More importantly, Kaplan-Meier survival analysis demonstrated that patients with low MEG3 expression had poorer survival and multivariate Cox regression analysis revealed that MEG3 was an independent prognostic factor in retinoblastoma patients. We also observed that MEG3 expression can be modulated by DNA methylation by using 5-aza-CdR treatment. In addition, overexpression of MEG3 suppressed proliferation, promoted apoptosis, and influences the activity of the Wnt/β-catenin pathway in retinoblastoma cell lines. Furthermore, we found that Wnt/β-catenin pathway activator rescued the anticancer effect of MEG3 in retinoblastoma. In conclusion, our study for the first time demonstrated that MEG3 was a tumor suppressor by negatively regulating the activity of the Wnt/β-catenin pathway in the progression of retinoblastoma and might serve as a prognostic biomarker and molecular therapeutic target.

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

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Strychacz, Christopher; Viirre, Erik; Wing, Shawn

2005-05-01

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

Interference of scalp and skull with dynamic isotope studies of brain

International Nuclear Information System (INIS)

Oldendorf, W.H.

1972-01-01

The overlying scalp and skull create artifacts in external brain counting measurements in which isotope appears in these tissues. It is much less of a problem in dynamic studies since high levels of superficial isotope are not found in the first few seconds after introduction into the blood by any anatomic route. Diffusible tracers concentrate somewhat less in the scalp and skull than in the brain immediately after injection by any route. Nondiffusible tracers of low molecular weight attain a much higher concentration in the scalp than the brain only after about the first minute because of passage from plasma to scalp extracellular fluid. This equilibration does not occur in brain because of the blood-brain barrier. Scalp and skull thus create much less of a problem with brief dynamic studies than with chronic long-term studies. Some physical considerations of external collimation are discussed, and means are suggested to minimize superficial isotope contributions to brain counts. (U.S.)

Minoxidil topical treatment may be more efficient if applied on damp scalp in comparison with dry scalp.

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Angelo, T; Barbalho, G N; Gelfuso, G M; Gratieri, T

2016-09-01

There is yet no consensus among prescribers whether minoxidil (MXD) formulations should be applied on wet/damp or dry scalp and no clear FDA guidelines on the matter. We hypothesized that the use of MXD on damp scalp may lead to higher drug penetration. First, because the drug diffusion and consequent deposition into the hair follicle may be favored when follicle cast is humid. Second, because humidity may also prevent drug crystallization and, therefore, maintain a higher thermodynamic activity for longer periods, which leads to increased penetration. Following in vitro experiments on rat and porcine skin we confirmed the hypothesis, which could markedly improve treatment effectiveness. © 2016 Wiley Periodicals, Inc.

Source localization of rhythmic ictal EEG activity: a study of diagnostic accuracy following STARD criteria.

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Beniczky, Sándor; Lantz, Göran; Rosenzweig, Ivana; Åkeson, Per; Pedersen, Birthe; Pinborg, Lars H; Ziebell, Morten; Jespersen, Bo; Fuglsang-Frederiksen, Anders

2013-10-01

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. Source localization of rhythmic ictal scalp EEG activity was performed in 42 consecutive cases fulfilling inclusion criteria. The study was designed according to recommendations for studies on diagnostic accuracy (STARD). The initial ictal EEG signals were selected using a standardized method, based on frequency analysis and voltage distribution of the ictal activity. A distributed source model-local autoregressive average (LAURA)-was used for the source localization. Sensitivity, specificity, and measurement of agreement (kappa) were determined based on the reference standard-the consensus conclusion of the multidisciplinary epilepsy surgery team. Predictive values were calculated from the surgical outcome of the operated patients. To estimate the clinical value of the ictal source analysis, we compared the likelihood ratios of concordant and discordant results. Source localization was performed blinded to the clinical data, and before the surgical decision. Reference standard was available for 33 patients. The ictal source localization had a sensitivity of 70% and a specificity of 76%. The mean measurement of agreement (kappa) was 0.61, corresponding to substantial agreement (95% confidence interval (CI) 0.38-0.84). Twenty patients underwent resective surgery. The positive predictive value (PPV) for seizure freedom was 92% and the negative predictive value (NPV) was 43%. The likelihood ratio was nine times higher for the concordant results, as compared with the discordant ones. Source localization of rhythmic ictal activity using a distributed source model (LAURA) for the ictal EEG signals selected with a standardized method

Lipoedematous scalp: is there an association with fatty infiltration of the parotid?

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Law, Sarah; Jayarajan, Rajshree

2017-10-09

Lipoedematous scalp (LS) is an extremely rare condition characterised by a soft and boggy consistency in the scalp due to an increased layer of subcutaneous tissue.In this report, we present a case of LS in a 64-year-old Indian woman. Clinical examination revealed only vague boggy lumpiness involving the whole of occipital scalp extending to parietal scalp. MRI scalp showed diffuse fatty infiltration of the scalp, particularly at the posterior parietal and occipital convexity extending to both lateral aspects of the cranium, with homogeneous signal in keeping with fat. Incidentally MRI also found diffuse fatty infiltration of the parotids.The aethiopathogenesis of LS is still unknown, however it is believed that the hormone leptin could be the key hormone in the dysregulation of fat deposition and distribution. This case report highlights the subtle features with which these cases can present and explores the literature on reported cases of LS. © BMJ Publishing Group Ltd (unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Fast accurate MEG source localization using a multilayer perceptron trained with real brain noise

International Nuclear Information System (INIS)

Jun, Sung Chan; Pearlmutter, Barak A.; Nolte, Guido

2002-01-01

Iterative gradient methods such as Levenberg-Marquardt (LM) are in widespread use for source localization from electroencephalographic (EEG) and magnetoencephalographic (MEG) signals. Unfortunately, LM depends sensitively on the initial guess, necessitating repeated runs. This, combined with LM's high per-step cost, makes its computational burden quite high. To reduce this burden, we trained a multilayer perceptron (MLP) as a real-time localizer. We used an analytical model of quasistatic electromagnetic propagation through a spherical head to map randomly chosen dipoles to sensor activities according to the sensor geometry of a 4D Neuroimaging Neuromag-122 MEG system, and trained a MLP to invert this mapping in the absence of noise or in the presence of various sorts of noise such as white Gaussian noise, correlated noise, or real brain noise. A MLP structure was chosen to trade off computation and accuracy. This MLP was trained four times, with each type of noise. We measured the effects of initial guesses on LM performance, which motivated a hybrid MLP-start-LM method, in which the trained MLP initializes LM. We also compared the localization performance of LM, MLPs, and hybrid MLP-start-LMs for realistic brain signals. Trained MLPs are much faster than other methods, while the hybrid MLP-start-LMs are faster and more accurate than fixed-4-start-LM. In particular, the hybrid MLP-start-LM initialized by a MLP trained with the real brain noise dataset is 60 times faster and is comparable in accuracy to random-20-start-LM, and this hybrid system (localization error: 0.28 cm, computation time: 36 ms) shows almost as good performance as optimal-1-start-LM (localization error: 0.23 cm, computation time: 22 ms), which initializes LM with the correct dipole location. MLPs trained with noise perform better than the MLP trained without noise, and the MLP trained with real brain noise is almost as good an initial guesser for LM as the correct dipole location. (author) )

Mechanical properties of the human scalp in tension.

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Falland-Cheung, Lisa; Scholze, Mario; Lozano, Pamela F; Ondruschka, Benjamin; Tong, Darryl C; Brunton, Paul A; Waddell, J Neil; Hammer, Niels

2018-08-01

Mechanical properties of the human scalp have not been investigated to a great extent with limited information available. The purpose of this study was to provide new baseline material data for human scalp tissue of various ages, which can be applied to experimental and constitutive models, such as in the area of impact biomechanics. This study used specimens from the left and right temporal, fronto-parietal and occipital regions of the human scalp. It investigated the tensile behavior of scalp tissue using tissues harvested from unfixed, fresh cadavers. These samples were subjected to an osmotic stress analysis and upon testing, cyclic loading followed by stretching until failure in a universal testing machine. Strain evaluation was conducted using digital image correlation in a highly standardized approach. Elastic modulus, tensile strength, strain at maximum load and strain to failure were evaluated computationally. No significant differences were observed comparing the tensile strength between males and females. In contrast to that, a sex-dependent difference was found for the elastic modulus of the occipital scalp region and for the elongation properties. Additionally, regional differences within the male group, as well as an age dependent correlation for females were found in the elastic modulus and tensile strength. Scanning electron microscope analyses have shown the ultrastructural failure patterns, indicated by damaged keratin plates, as well as partially disrupted and retraced collagens at the failure site. The novel data obtained in this study could add valuable information to be used for modeling purposes, as well as provide baseline data for simulant materials and comparisons of tissue properties following head injury or forensic investigations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparative neuroimaging in children with cerebral palsy using fMRI and a novel EEG-based brain mapping during a motor task--a preliminary investigation.

Science.gov (United States)

Lee, Jae Jin; Lee, Dong Ryul; Shin, Yoon Kyum; Lee, Nam Gi; Han, Bong S; You, Sung Joshua Hyun

2013-01-01

The purpose of this study was to compare topographical maps using a novel EEG-based brain mapping system with fMRI in normal and children with cerebral palsy (CP) during a grasping motor task. A normal child (mean ± SD = 13 ± 0 yrs) and four children with CP (mean ± SD = 10.25 ± 2.86 yrs) were recruited from a local community school and medical center. A novel EEG-based brain mapping system with 30 scalp sites (an extension of the 10-20 system) and a 3T MR scanner were used to observe cortical activation patterns during a grasping motor task. Descriptive analysis. In the EEG brain mapping data, the sensorimotor cortex (SMC) and inferior parietal cortex (IPC) were activated in all of the children. The children with CP showed additional activation areas in the premotor cortex (PMC), superior parietal cortex (SPC), and prefrontal cortex (PFC). In the fMRI brain mapping data, SMC activation was observed in all of the children, and the children with CP showed additional activation areas in the PMC and primary somatosensory cortex (PSC). The EEG-based topographical maps were equivalent to the maps obtained from fMRI during the grasping motor task. The results indicate that our novel EEG-based brain mapping system is useful for probing cortical activation patterns in normal children and children with CP.

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

Science.gov (United States)

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.

EEG frontal asymmetry related to pleasantness of music perception in healthy children and cochlear implanted users.

Science.gov (United States)

Vecchiato, G; Maglione, A G; Scorpecci, A; Malerba, P; Marsella, P; Di Francesco, G; Vitiello, S; Colosimo, A; Babiloni, Fabio

2012-01-01

Interestingly, the international debate about the quality of music fruition for cochlear implanted users does not take into account the hypothesis that bilateral users could perceive music in a more pleasant way with respect to monolateral users. In this scenario, the aim of the present study was to investigate if cerebral signs of pleasantness during music perception in healthy child are similar to those observed in monolateral and in bilateral cochlear implanted users. In fact, previous observations in literature on healthy subjects have indicated that variations of the frontal EEG alpha activity are correlated with the perceived pleasantness of the sensory stimulation received (approach-withdrawal theory). In particular, here we described differences between cortical activities estimated in the alpha frequency band for a healthy child and in patients having a monolateral or a bilateral cochlear implant during the fruition of a musical cartoon. The results of the present analysis showed that the alpha EEG asymmetry patterns observed in a healthy child and that of a bilateral cochlear implanted patient are congruent with the approach-withdrawal theory. Conversely, the scalp topographic distribution of EEG power spectra in the alpha band resulting from the monolateral cochlear user presents a different EEG pattern from the normal and bilateral implanted patients. Such differences could be explained at the light of the approach-withdrawal theory. In fact, the present findings support the hypothesis that a monolateral cochlear implanted user could perceive the music in a less pleasant way when compared to a healthy subject or to a bilateral cochlear user.

Unsupervised detection and removal of muscle artifacts from scalp EEG recordings using canonical correlation analysis, wavelets and random forests.

Science.gov (United States)

Anastasiadou, Maria N; Christodoulakis, Manolis; Papathanasiou, Eleftherios S; Papacostas, Savvas S; Mitsis, Georgios D

2017-09-01

This paper proposes supervised and unsupervised algorithms for automatic muscle artifact detection and removal from long-term EEG recordings, which combine canonical correlation analysis (CCA) and wavelets with random forests (RF). The proposed algorithms first perform CCA and continuous wavelet transform of the canonical components to generate a number of features which include component autocorrelation values and wavelet coefficient magnitude values. A subset of the most important features is subsequently selected using RF and labelled observations (supervised case) or synthetic data constructed from the original observations (unsupervised case). The proposed algorithms are evaluated using realistic simulation data as well as 30min epochs of non-invasive EEG recordings obtained from ten patients with epilepsy. We assessed the performance of the proposed algorithms using classification performance and goodness-of-fit values for noisy and noise-free signal windows. In the simulation study, where the ground truth was known, the proposed algorithms yielded almost perfect performance. In the case of experimental data, where expert marking was performed, the results suggest that both the supervised and unsupervised algorithm versions were able to remove artifacts without affecting noise-free channels considerably, outperforming standard CCA, independent component analysis (ICA) and Lagged Auto-Mutual Information Clustering (LAMIC). The proposed algorithms achieved excellent performance for both simulation and experimental data. Importantly, for the first time to our knowledge, we were able to perform entirely unsupervised artifact removal, i.e. without using already marked noisy data segments, achieving performance that is comparable to the supervised case. Overall, the results suggest that the proposed algorithms yield significant future potential for improving EEG signal quality in research or clinical settings without the need for marking by expert

Microsurgical reconstruction of extensive oncological scalp defects

Directory of Open Access Journals (Sweden)

Ole eGoertz

2015-09-01

Full Text Available While most small to medium defects of the scalp can be covered by local flaps, large defects or complicating factors like a history of radiotherapy often require a microsurgical reconstruction.Several factors need to be considered in such procedures. A sufficient preoperative planning is based on adequate imaging of the malignancy and a multi-disciplinary concept. Several flaps are available for such reconstructions, of which the latissimus dorsi and anterior lateral thigh flaps are the most commonly used ones.In very large defects, combined flaps such as a parascapular / latissimus dorsi flaps can be highly useful or necessary. The most commonly used recipient vessels for microsurgical scalp reconstructions are the superficial temporal vessels, but various other feasible choices exist. If the concomitant veins are not sufficient, the jugular veins represent a safe backup alternative but require a vessel interposition or long pedicle. Postoperative care and patient positioning can be difficult in these patients but can be facilitated by various devices. Overall, microsurgical reconstruction of large scalp defects is a feasible undertaking if the mentioned key factors are taken into account.

EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis.

Science.gov (United States)

Delorme, Arnaud; Makeig, Scott

2004-03-15

We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.

Oscillations, networks, and their development: MEG connectivity changes with age.

Science.gov (United States)

Schäfer, Carmen B; Morgan, Benjamin R; Ye, Annette X; Taylor, Margot J; Doesburg, Sam M

2014-10-01

Magnetoencephalographic (MEG) investigations of inter-regional amplitude correlations have yielded new insights into the organization and neurophysiology of resting-state networks (RSNs) first identified using fMRI. Inter-regional MEG amplitude correlations in adult RSNs have been shown to be most prominent in alpha and beta frequency ranges and to express strong congruence with RSN topologies found using fMRI. Despite such advances, little is known about how oscillatory connectivity in RSNs develops throughout childhood and adolescence. This study used a novel fMRI-guided MEG approach to investigate the maturation of resting-state amplitude correlations in physiologically relevant frequency ranges within and among six RSNs in 59 participants, aged 6-34 years. We report age-related increases in inter-regional amplitude correlations that were largest in alpha and beta frequency bands. In contrast to fMRI reports, these changes were observed both within and between the various RSNs analyzed. Our results provide the first evidence of developmental changes in spontaneous neurophysiological connectivity in source-resolved RSNs, which indicate increasing integration within and among intrinsic functional brain networks throughout childhood, adolescence, and early adulthood. Copyright © 2014 Wiley Periodicals, Inc.

Semi-automated identification of artefact and noise signals in MEG sensors

International Nuclear Information System (INIS)

Rettich, E.

2006-09-01

Magnetic encephalography (MEG) is a noninvasive method of measuring cerebral activity. It is based on the registration of magnetic fields that are induced by synaptic ion currents as the brain processes information. These magnetic fields are of a very small magnitude, ranging from a few femto Tesla (1 fT = 10 15 T) to several thousand fT (1 pT). This is equivalent to a ten thousandth to a billionth of the Earth's magnetic field. When applied with a time resolution in the range of milliseconds this technique permits research on time-critical neurophysiological processes. A meaningful analysis of MEG data presupposes that signals have been measured at low noise levels. This in turn requires magnetic shielding, normally in the form of a shielded cabin, and low-noise detectors. Data input from high-noise channels impairs the result of the measurement, possibly rendering it useless. To prevent this it is necessary to identify high-noise channels and remove them from the measurement data. At Juelich Research Center, like at most MEG laboratories, this is done by visual inspection. However, being dependent on the individual observer, this method does not yield objective results. Furthermore, visual inspection presupposes a high degree of experience and is time-consuming. This situation could be significantly improved by automated identification of high-noise channels. The purpose of the present study was to develop an algorithm that analyses measurement signals in a given time and frequency interval on the basis of statistical traits. Using a suitably designed user interface this permits searching MEG data for high-noise channel data below or above statistical threshold values on the basis of predetermined decision criteria. The identified high-noise channels are then output in a selection list, and the measurement data and results of the statistical analysis are displayed. This information enables the user to make changes and decide which high-noise channels to extract

LORETA EEG phase reset of the default mode network.

Science.gov (United States)

Thatcher, Robert W; North, Duane M; Biver, Carl J

2014-01-01

The purpose of this study was to explore phase reset of 3-dimensional current sources in Brodmann areas located in the human default mode network (DMN) using Low Resolution Electromagnetic Tomography (LORETA) of the human electroencephalogram (EEG). The EEG was recorded from 19 scalp locations from 70 healthy normal subjects ranging in age from 13 to 20 years. A time point by time point computation of LORETA current sources were computed for 14 Brodmann areas comprising the DMN in the delta frequency band. The Hilbert transform of the LORETA time series was used to compute the instantaneous phase differences between all pairs of Brodmann areas. Phase shift and lock durations were calculated based on the 1st and 2nd derivatives of the time series of phase differences. Phase shift duration exhibited three discrete modes at approximately: (1) 25 ms, (2) 50 ms, and (3) 65 ms. Phase lock duration present primarily at: (1) 300-350 ms and (2) 350-450 ms. Phase shift and lock durations were inversely related and exhibited an exponential change with distance between Brodmann areas. The results are explained by local neural packing density of network hubs and an exponential decrease in connections with distance from a hub. The results are consistent with a discrete temporal model of brain function where anatomical hubs behave like a "shutter" that opens and closes at specific durations as nodes of a network giving rise to temporarily phase locked clusters of neurons for specific durations.

Coherence and phase synchrony analyses of EEG signals in Mild Cognitive Impairment (MCI): A study of functional brain connectivity

Science.gov (United States)

Handayani, Nita; Haryanto, Freddy; Khotimah, Siti Nurul; Arif, Idam; Taruno, Warsito Purwo

2018-03-01

This paper presents an EEG study for coherence and phase synchrony in mild cognitive impairment (MCI) subjects. MCI is characterized by cognitive decline, which is an early stage of Alzheimer's disease (AD). AD is a neurodegenerative disorder with symptoms such as memory loss and cognitive impairment. EEG coherence is a statistical measure of correlation between signals from electrodes spatially separated on the scalp. The magnitude of phase synchrony is expressed in the phase locking value (PLV), a statistical measure of neuronal connectivity in the human brain. Brain signals were recorded using an Emotiv Epoc 14-channel wireless EEG at a sampling frequency of 128 Hz. In this study, we used 22 elderly subjects consisted of 10 MCI subjects and 12 healthy subjects as control group. The coherence between each electrode pair was measured for all frequency bands (delta, theta, alpha and beta). In the MCI subjects, the value of coherence and phase synchrony was generally lower than in the healthy subjects especially in the beta frequency. A decline of intrahemisphere coherence in the MCI subjects occurred in the left temporo-parietal-occipital region. The pattern of decline in MCI coherence is associated with decreased cholinergic connectivity along the path that connects the temporal, occipital, and parietal areas of the brain to the frontal area of the brain. EEG coherence and phase synchrony are able to distinguish persons who suffer AD in the early stages from healthy elderly subjects.

EEG PHASE RESET OF THE DEFAULT MODE NETWORK

Directory of Open Access Journals (Sweden)

Robert W. Thatcher

2014-07-01

Full Text Available Objectives: The purpose of this study was to explore phase reset of 3-dimensional current sources located in Brodmann areas located in the human default mode network (DMN using Low Resolution Electromagnetic Tomography (LORETA of the human electroencephalogram (EEG. Methods: The EEG was recorded from 19 scalp locations from 70 healthy normal subjects ranging in age from 13 to 20 years. A time point by time point computation of LORETA current sources were computed for 14 Brodman areas comprising the DMN in the delta frequency band. The Hilbert transform of the LORETA time series was used to compute the instantaneous phase differences between all pairs of Brodmann areas. Phase shift and lock durations were calculated based on the 1st & 2nd derivatives of the time series of phase differences. Results: Phase shift duration exhibited three discrete modes at approximately: 1- 30 msec,, 2- 55 msec and, 3- 65 msec. Phase lock duration present primarily at: 1- 300 to 350 msec and, 2- 350 msec to 450 msec. Phase shift and lock durations were inversely related and exhibited an exponential change with distance between Brodmann areas. Conclusions: The results are explained by local neural packing density of network hubs and an exponential decrease in connections with distance from a hub. The results are consistent with a discrete temporal model of brain function where anatomical hubs behave like a ‘shutter’ that opens and closes at specific durations as nodes of a network giving rise to temporarily phase locked clusters of neurons for specific durations.

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

Science.gov (United States)

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.

Clinical observation on effect of scalp electroacupuncture for mild cognitive impairment.

Science.gov (United States)

Zhang, Hong; Zhao, Ling; Yang, Sha; Chen, Zhigang; Li, Yingkun; Peng, Xiaohong; Yang, Yulong; Zhu, Manjia

2013-02-01

To evaluate the therapeutic effect of scalp electroacupuncture for mild cognitive impairment (MCI) in the early stage. Two hundred and thirty three MCI patients were randomly divided into three groups: the drug group, the scalp electroacupuncture group, and the syndrome differentiation group. For the scalp electroacupuncture group, the points of Baihui (DU 20), Sishecong (EX-HN1), Fengchi (GB 20), and Shenting (DU 24) were selected. For the syndrome differentiation group, specific acupoints were added on the basis of syndrome differentiation and according to the scale for the differentiation of syndromes in vascular dementia (SDSVD) beside the acupoints used in the scalp electroacupuncture group. For the drug group, nimodipine was orally administered. Each patient was treated for two courses, eight weeks. The score differences in mini-mental state examination (MMSE), picture recognition, and clock drawing test were observed before and after the treatment. After treatment, the score differences in MMSE and clock drawing test were of obvious statistical significance among three groups (P electroacupuncture group and the syndrome differentiation group (P 0.05). There were statistical significant differences in therapeutic effects between the scalp electroacupuncture group and the drug group, and between the syndrome differentiation group and the drug group (P electroacupuncture group and the syndrome differentiation group (P > 0.05). All the three therapies may improve the cognitive function of MCI patients. The therapeutic effects in the scalp electroacupuncture and syndrome differentiation groups were basically the same, but superior to nimodipine.

EEG frequency PCA in EEG-ERP dynamics.

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Barry, Robert J; De Blasio, Frances M

2018-05-01

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

LncRNA MEG3 enhances cisplatin sensitivity in non-small cell lung cancer by regulating miR-21-5p/SOX7 axis

Directory of Open Access Journals (Sweden)

Wang P

2017-10-01

Full Text Available Pei Wang,* Dong Chen,* Hongbing Ma, Yong LiDepartment of Cardiothoracic Surgery, Huaihe Hospital of Henan University, Kaifeng, People’s Republic of China *These authors contributed equally to this work Background: Long noncoding RNAs (lncRNAs have been revealed to play essential role in drug resistance of multiple cancers. LncRNA MEG3 was previously reported to be associated with cisplatin (DDP resistance in non-small cell lung cancer (NSCLC cells. However, the molecular mechanism of MEG3 affecting DDP resistance in NSCLC remains to be further illustrated. In this study, we attempted to discuss whether MEG3 also could function as a competing endogenous RNA to regulate DDP resistance in NSCLC.Materials and methods: The expression of MEG3, miR-21-5p, and sex-determining region Y-box 7 (SOX7 in NSCLC tissues or cells was examined by quantitative real-time polymerase chain reaction (qRT-PCR. 3-(4,5-Dimethylthazol-2-yl-2,5-diphenyltetrazolium bromide (MTT, flow cytometry, and caspase-3 activity analysis were applied to assess the DDP sensitivity of NSCLC cells. The interaction between MEG3, miR-21-5p, and SOX7 was explored by luciferase reporter assay, RNA immunoprecipitation (RIP assay, qRT-PCR, and Western blot. Mouse NSCLC transplanted tumor was established to verify the functional role of MEG3 in DDP resistance in vivo.Results: MEG3 was downregulated in DDP-resistant NSCLC cells. Overexpression of MEG3 enhanced DDP sensitivity of NSCLC cells in vitro. MEG3 directly interacted with miR-21-5p and suppressed its expression. miR-21-5p significantly abolished the effects of MEG3 on DDP resistance via modulating cell proliferation and apoptosis. SOX7 was identified as a direct target of miR-21-5p and MEG3 positively regulated SOX7 expression by suppressing miR-21-5p. Moreover, MEG3 knockdown-induced pro-proliferative and anti-apoptotic effects were reversed in DDP-resistant NSCLC cells by upregulating SOX7. Furthermore, upregulation of MEG3 induced

Towards a Unified Understanding of Event-Related Changes in the EEG: The Firefly Model of Synchronization through Cross-Frequency Phase Modulation

Science.gov (United States)

Burgess, Adrian P.

2012-01-01

Although event-related potentials (ERPs) are widely used to study sensory, perceptual and cognitive processes, it remains unknown whether they are phase-locked signals superimposed upon the ongoing electroencephalogram (EEG) or result from phase-alignment of the EEG. Previous attempts to discriminate between these hypotheses have been unsuccessful but here a new test is presented based on the prediction that ERPs generated by phase-alignment will be associated with event-related changes in frequency whereas evoked-ERPs will not. Using empirical mode decomposition (EMD), which allows measurement of narrow-band changes in the EEG without predefining frequency bands, evidence was found for transient frequency slowing in recognition memory ERPs but not in simulated data derived from the evoked model. Furthermore, the timing of phase-alignment was frequency dependent with the earliest alignment occurring at high frequencies. Based on these findings, the Firefly model was developed, which proposes that both evoked and induced power changes derive from frequency-dependent phase-alignment of the ongoing EEG. Simulated data derived from the Firefly model provided a close match with empirical data and the model was able to account for i) the shape and timing of ERPs at different scalp sites, ii) the event-related desynchronization in alpha and synchronization in theta, and iii) changes in the power density spectrum from the pre-stimulus baseline to the post-stimulus period. The Firefly Model, therefore, provides not only a unifying account of event-related changes in the EEG but also a possible mechanism for cross-frequency information processing. PMID:23049827

Versatile synchronized real-time MEG hardware controller for large-scale fast data acquisition

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Sun, Limin; Han, Menglai; Pratt, Kevin; Paulson, Douglas; Dinh, Christoph; Esch, Lorenz; Okada, Yoshio; Hämäläinen, Matti

2017-05-01

Versatile controllers for accurate, fast, and real-time synchronized acquisition of large-scale data are useful in many areas of science, engineering, and technology. Here, we describe the development of a controller software based on a technique called queued state machine for controlling the data acquisition (DAQ) hardware, continuously acquiring a large amount of data synchronized across a large number of channels (>400) at a fast rate (up to 20 kHz/channel) in real time, and interfacing with applications for real-time data analysis and display of electrophysiological data. This DAQ controller was developed specifically for a 384-channel pediatric whole-head magnetoencephalography (MEG) system, but its architecture is useful for wide applications. This controller running in a LabVIEW environment interfaces with microprocessors in the MEG sensor electronics to control their real-time operation. It also interfaces with a real-time MEG analysis software via transmission control protocol/internet protocol, to control the synchronous acquisition and transfer of the data in real time from >400 channels to acquisition and analysis workstations. The successful implementation of this controller for an MEG system with a large number of channels demonstrates the feasibility of employing the present architecture in several other applications.

Comparison of different spatial transformations applied to EEG data: A case study of error processing.

Science.gov (United States)

Cohen, Michael X

2015-09-01

The purpose of this paper is to compare the effects of different spatial transformations applied to the same scalp-recorded EEG data. The spatial transformations applied are two referencing schemes (average and linked earlobes), the surface Laplacian, and beamforming (a distributed source localization procedure). EEG data were collected during a speeded reaction time task that provided a comparison of activity between error vs. correct responses. Analyses focused on time-frequency power, frequency band-specific inter-electrode connectivity, and within-subject cross-trial correlations between EEG activity and reaction time. Time-frequency power analyses showed similar patterns of midfrontal delta-theta power for errors compared to correct responses across all spatial transformations. Beamforming additionally revealed error-related anterior and lateral prefrontal beta-band activity. Within-subject brain-behavior correlations showed similar patterns of results across the spatial transformations, with the correlations being the weakest after beamforming. The most striking difference among the spatial transformations was seen in connectivity analyses: linked earlobe reference produced weak inter-site connectivity that was attributable to volume conduction (zero phase lag), while the average reference and Laplacian produced more interpretable connectivity results. Beamforming did not reveal any significant condition modulations of connectivity. Overall, these analyses show that some findings are robust to spatial transformations, while other findings, particularly those involving cross-trial analyses or connectivity, are more sensitive and may depend on the use of appropriate spatial transformations. Copyright © 2014 Elsevier B.V. All rights reserved.

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

International Nuclear Information System (INIS)

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

Ex-vivo measurement of scalp follicular infundibulum delivery of zinc pyrithione and climbazole from an anti-dandruff shampoo.

Science.gov (United States)

Chen, Guoqiang; Ji, Chengdong; Miao, Miao; Yang, Kang; Luo, Yajun; Hoptroff, Michael; Collins, Luisa Z; Janssen, Hans-Gerd

2017-09-05

Efficient delivery of anti-dandruff (AD) actives into the scalp follicular infundibulum as well as onto the scalp surface is critical for the efficacy of AD shampoos. A method involving scalp cyanoacrylate (CA) biopsy sampling, a tailor made cutting device, ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) analysis, scanning electron microscopy (SEM) measurement and Raman imaging has been developed for the measurement of delivery of zinc pyrithione (ZPT) and climbazole (CBZ) from an AD shampoo into the scalp follicular infundibulum. Scalp CA biopsy enables the sampling of ZPT and CBZ delivered into the scalp follicular infundibula as well as onto the scalp surface. Raman imaging of scalp CA biopsy samples allows the visualization of the spatial distribution of ZPT and CBZ deposited on the scalp. A tailor made cutting device enables the separation of the scalp follicular infundibulum sample (20μm below the scalp surface) from the scalp surface samples (including top 20μm of infundibula). UHPLC-MS/MS was used as a sensitive and specific methodology enabling the quantification of ZPT and CBZ without interference. Using this method, both ZPT and CBZ were successfully quantified and spacially visualized within the scalp follicular infundibulum, after scalp was washed with an AD shampoo. Copyright © 2017 Elsevier B.V. All rights reserved.

Treatment of multiple sclerosis with chinese scalp acupuncture.

Science.gov (United States)

Hao, Jason Jishun; Cheng, Wei; Liu, Ming; Li, He; Lü, Xiaolin; Sun, Zhongren

2013-01-01

Chinese scalp acupuncture is a contemporary acupuncture technique with just 40 years of history. It integrates traditional Chinese needling methods with Western medical knowledge of the cerebral cortex and has been proven to be a very effective technique for treating multiple sclerosis (MS) and other central nervous system disorders. A 65-year-old male patient who had had MS for 20 years was treated with Chinese scalp acupuncture. The motor area, sensory area, foot motor and sensory area, balance area, hearing and dizziness area, and tremor area were stimulated once a week for 10 weeks, then once a month for six sessions. After the 16 treatments, the patient showed remarkable improvements. He was able to stand and walk without any problems. The numbness and tingling in his limbs did not bother him anymore. He had more energy and had not experienced incontinence of urine or dizziness after the first treatment. He was able to return to work full time. At this writing, the patient has been in remission for 26 months. This case demonstrates that Chinese scalp acupuncture can be a very effective treatment for patients with MS. Chinese scalp acupuncture holds the potential to expand treatment options for MS in both conventional and complementary or integrative therapies. It can not only relieve symptoms, increase the patient's quality of life, and slow and reverse the progression of physical disability but also reduce the number of relapses and help patients with multiple sclerosis to remain in remission.

Localization Accuracy of Distributed Inverse Solutions for Electric and Magnetic Source Imaging of Interictal Epileptic Discharges in Patients with Focal Epilepsy.

Science.gov (United States)

Heers, Marcel; Chowdhury, Rasheda A; Hedrich, Tanguy; Dubeau, François; Hall, Jeffery A; Lina, Jean-Marc; Grova, Christophe; Kobayashi, Eliane

2016-01-01

Distributed inverse solutions aim to realistically reconstruct the origin of interictal epileptic discharges (IEDs) from noninvasively recorded electroencephalography (EEG) and magnetoencephalography (MEG) signals. Our aim was to compare the performance of different distributed inverse solutions in localizing IEDs: coherent maximum entropy on the mean (cMEM), hierarchical Bayesian implementations of independent identically distributed sources (IID, minimum norm prior) and spatially coherent sources (COH, spatial smoothness prior). Source maxima (i.e., the vertex with the maximum source amplitude) of IEDs in 14 EEG and 19 MEG studies from 15 patients with focal epilepsy were analyzed. We visually compared their concordance with intracranial EEG (iEEG) based on 17 cortical regions of interest and their spatial dispersion around source maxima. Magnetic source imaging (MSI) maxima from cMEM were most often confirmed by iEEG (cMEM: 14/19, COH: 9/19, IID: 8/19 studies). COH electric source imaging (ESI) maxima co-localized best with iEEG (cMEM: 8/14, COH: 11/14, IID: 10/14 studies). In addition, cMEM was less spatially spread than COH and IID for ESI and MSI (p < 0.001 Bonferroni-corrected post hoc t test). Highest positive predictive values for cortical regions with IEDs in iEEG could be obtained with cMEM for MSI and with COH for ESI. Additional realistic EEG/MEG simulations confirmed our findings. Accurate spatially extended sources, as found in cMEM (ESI and MSI) and COH (ESI) are desirable for source imaging of IEDs because this might influence surgical decision. Our simulations suggest that COH and IID overestimate the spatial extent of the generators compared to cMEM.

Lung cancer revealed by multiple metastases of the scalp | Fetohi ...

African Journals Online (AJOL)

Skin metastases of lung cancer are rare. They are symptoms of progressive disease and usually a sign of a poor prognosis. We report a case of 69-years-old man with no significant medical history, never smoker, which consulted a dermatologist for scalp nodules that appeared for more than 16 months in the scalp and ...

Lipedematous scalp and lipedematous alopecia. Report of three cases in white adults

International Nuclear Information System (INIS)

Yasar, S.; Mansur, A.T.; Goktay, F.; Sungurlu, F.; Vardar Aker, F.; Oezkara, S.

2007-01-01

Lipedematous scalp (LS) and lipedematous alopecia (LA) are rare conditions of unknown etiology characterized by a thick and boggy scalp due to increase in the subcutaneous fat layer. Besides the changes in the texture of skin, varying degrees of hair loss are seen in patients with LA. In this report, we present two cases with LA and one case with LS in white adults. On examination, a boggy and soft swelling of the scalp was detected in all patients. In addition, the patients with LA had alopecic areas over the boggy scalp. Histopathologic examinations of skin biopsy specimens and magnetic resonance imaging of the scalp showed increased thickness of subcutaneous fat tissue in all patients. The exact etiopathogenesis of LA and LS remain unknown. These conditions may be either reactive or compensatory responses versus yet undetected stimuli, or represent a genetic tendency. Both of the these entities have been initially reported mostly in adult black females, however, we believe that LA and LS may well occur in white subjects and may be more widespread and frequently observed than previously supposed. (author)

Changes in the EEG and SEP of patients with cerebrovascular major strokes

International Nuclear Information System (INIS)

Iwayama, Kaoru; Tanaka, Keisei; Yamashiro, Katsumi; Mori, Kazuo

1980-01-01

Changes in the electroencephalogram (EEG) and somatosensory evoked potential (SEP) were studied in 27 cases with unilateral cerebrovascular disorders. From the CT findings (EMI-1010), the locations of the diseases were divided into two types: superficial (within the cortex and subcortical white matter) or deep (at the level of the basal ganglia and thalamus). Each of these was then further subdivided according to the nature of the disease, whether hemorrhage or infarction. The EEG and SEP were recorded from the scalp area corresponding to the post-Rolandic arm area (Shagass' point) throughout the investigation. The stimulus intensities applied to the median nerve were fixed at 5 - 10 V. higher than the motor threshold. EEG power spectrum analysis was done with an ATAC 2300 computer, while slow-wave indices (SWI), the ratio of power in the slow-wave range (2 - 6 Hz) to the total power (2 - 25 Hz), were calculated manually. In deep lesions, the deterioration of the SEP was prominent. Especially in the 5 cases with bleeding, all 5 showed a ''flat SEP.'' These patients also revealed motor and sensory disturbance clinically. In the 6 cases with infarction, although no one showed sensory disturbances, the changes in the SEP were also remarkable. In deep lesions, a decrease in the amplitude of the early components of SEP (N 1 , P 1 ) was the most conspicuous feature. On the contrary, in superficial lesions, changes in the SEP were less prominent, and if they occurred, the late components (P 2 , N 3 ) were more easily affected. The amount of the slow wave increased remarkably and bilaterally in these superficial cases, and the slower the frequency of the EEG, the more attenuation of the amplitude of SEP was noted on the lesion side. On the opposite side, however, no such correlations could be noted between an increased slow-wave power and a decreased amplitude of SEP. Further studies to clarify these differences will be necessary. (author)

Connectivity maps based analysis of EEG for the advanced diagnosis of schizophrenia attributes.

Directory of Open Access Journals (Sweden)

Zack Dvey-Aharon

Full Text Available This article presents a novel connectivity analysis method that is suitable for multi-node networks such as EEG, MEG or EcOG electrode recordings. Its diagnostic power and ability to interpret brain states in schizophrenia is demonstrated on a set of 50 subjects that constituted of 25 healthy and 25 diagnosed with schizophrenia and treated with medication. The method can also be used for the automatic detection of schizophrenia; it exhibits higher sensitivity than state-of-the-art methods with no false positives. The detection is based on an analysis from a minute long pattern-recognition computer task. Moreover, this connectivity analysis leads naturally to an optimal choice of electrodes and hence to highly statistically significant results that are based on data from only 3-5 electrodes. The method is general and can be used for the diagnosis of other psychiatric conditions, provided an appropriate computer task is devised.

A multi-dimensional functional principal components analysis of EEG data.

Science.gov (United States)

Hasenstab, Kyle; Scheffler, Aaron; Telesca, Donatello; Sugar, Catherine A; Jeste, Shafali; DiStefano, Charlotte; Şentürk, Damla

2017-09-01

The electroencephalography (EEG) data created in event-related potential (ERP) experiments have a complex high-dimensional structure. Each stimulus presentation, or trial, generates an ERP waveform which is an instance of functional data. The experiments are made up of sequences of multiple trials, resulting in longitudinal functional data and moreover, responses are recorded at multiple electrodes on the scalp, adding an electrode dimension. Traditional EEG analyses involve multiple simplifications of this structure to increase the signal-to-noise ratio, effectively collapsing the functional and longitudinal components by identifying key features of the ERPs and averaging them across trials. Motivated by an implicit learning paradigm used in autism research in which the functional, longitudinal, and electrode components all have critical interpretations, we propose a multidimensional functional principal components analysis (MD-FPCA) technique which does not collapse any of the dimensions of the ERP data. The proposed decomposition is based on separation of the total variation into subject and subunit level variation which are further decomposed in a two-stage functional principal components analysis. The proposed methodology is shown to be useful for modeling longitudinal trends in the ERP functions, leading to novel insights into the learning patterns of children with Autism Spectrum Disorder (ASD) and their typically developing peers as well as comparisons between the two groups. Finite sample properties of MD-FPCA are further studied via extensive simulations. © 2017, The International Biometric Society.

BabyMEG: A whole-head pediatric magnetoencephalography system for human brain development research

Science.gov (United States)

Okada, Yoshio; Hämäläinen, Matti; Pratt, Kevin; Mascarenas, Anthony; Miller, Paul; Han, Menglai; Robles, Jose; Cavallini, Anders; Power, Bill; Sieng, Kosal; Sun, Limin; Lew, Seok; Doshi, Chiran; Ahtam, Banu; Dinh, Christoph; Esch, Lorenz; Grant, Ellen; Nummenmaa, Aapo; Paulson, Douglas

2016-09-01

We developed a 375-channel, whole-head magnetoencephalography (MEG) system ("BabyMEG") for studying the electrophysiological development of human brain during the first years of life. The helmet accommodates heads up to 95% of 36-month old boys in the USA. The unique two-layer sensor array consists of: (1) 270 magnetometers (10 mm diameter, ˜15 mm coil-to-coil spacing) in the inner layer, (2) thirty-five three-axis magnetometers (20 mm × 20 mm) in the outer layer 4 cm away from the inner layer. Additionally, there are three three-axis reference magnetometers. With the help of a remotely operated position adjustment mechanism, the sensor array can be positioned to provide a uniform short spacing (mean 8.5 mm) between the sensor array and room temperature surface of the dewar. The sensors are connected to superconducting quantum interference devices (SQUIDs) operating at 4.2 K with median sensitivity levels of 7.5 fT/√Hz for the inner and 4 fT/√Hz for the outer layer sensors. SQUID outputs are digitized by a 24-bit acquisition system. A closed-cycle helium recycler provides maintenance-free continuous operation, eliminating the need for helium, with no interruption needed during MEG measurements. BabyMEG with the recycler has been fully operational from March, 2015. Ongoing spontaneous brain activity can be monitored in real time without interference from external magnetic noise sources including the recycler, using a combination of a lightly shielded two-layer magnetically shielded room, an external active shielding, a signal-space projection method, and a synthetic gradiometer approach. Evoked responses in the cortex can be clearly detected without averaging. These new design features and capabilities represent several advances in MEG, increasing the utility of this technique in basic neuroscience as well as in clinical research and patient studies.

CHANGES IN EEG DURING GRADED EXERCISE ON A RECUMBENT CYCLE ERGOMETER

Directory of Open Access Journals (Sweden)

Stephen P. Bailey

2008-12-01

Full Text Available 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

Total scalp avulsion with microvascular reanastomosis: A case report and literature review.

Science.gov (United States)

Plant, Mathew A; Fialkov, Jeffrey

2010-01-01

Total scalp avulsion is a rare but potentially devastating injury that when treated (following a few basic principles) can have very good reconstructive results. The present article reviews the current literature and describes the steps involved in the successful replantation of a complete avulsed scalp of a 33-year-old woman. To the authors' knowledge, the present case regarding replantation of a complete avulsed scalp using only a single artery is the first to be described in the Canadian literature.

Cost-effectiveness analysis of scalp cooling to reduce chemotherapy-induced alopecia

NARCIS (Netherlands)

van den Hurk, C.J.; van den Akker-van Marle, E.M.; Breed, W.P.M.; van de Poll-Franse, L.V.; Nortier, J.; Coebergh, J.W.W.

2014-01-01

Background. Alopecia is a frequently occurring side effect of chemotherapy that often can be prevented by cooling the scalp during the infusion. This study compared effects and costs of scalp cooling with usual general oncological care, i.e. purchasing a wig or head cover. Material and methods.

Molecular and Cellular Profiling of Scalp Psoriasis Reveals Differences and Similarities Compared to Skin Psoriasis

Science.gov (United States)

Ruano, Juan; Suárez-Fariñas, Mayte; Shemer, Avner; Oliva, Margeaux

2016-01-01

Scalp psoriasis shows a variable clinical spectrum and in many cases poses a great therapeutic challenge. However, it remains unknown whether the immune response of scalp psoriasis differs from understood pathomechanisms of psoriasis in other skin areas. We sought to determine the cellular and molecular phenotype of scalp psoriasis by performing a comparative analysis of scalp and skin using lesional and nonlesional samples from 20 Caucasian subjects with untreated moderate to severe psoriasis and significant scalp involvement and 10 control subjects without psoriasis. Our results suggest that even in the scalp, psoriasis is a disease of the inter-follicular skin. The immune mechanisms that mediate scalp psoriasis were found to be similar to those involved in skin psoriasis. However, the magnitude of dysregulation, number of differentially expressed genes, and enrichment of the psoriatic genomic fingerprint were more prominent in skin lesions. Furthermore, the scalp transcriptome showed increased modulation of several gene-sets, particularly those induced by interferon-gamma, compared with that of skin psoriasis, which was mainly associated with activation of TNFα/L-17/IL-22-induced keratinocyte response genes. We also detected differences in expression of gene-sets involving negative regulation, epigenetic regulation, epidermal differentiation, and dendritic cell or Th1/Th17/Th22-related T-cell processes. PMID:26849645

Auditory Evoked Responses in Neonates by MEG

International Nuclear Information System (INIS)

Hernandez-Pavon, J. C.; Sosa, M.; Lutter, W. J.; Maier, M.; Wakai, R. T.

2008-01-01

Magnetoencephalography is a biomagnetic technique with outstanding potential for neurodevelopmental studies. In this work, we have used MEG to determinate if newborns can discriminate between different stimuli during the first few months of life. Five neonates were stimulated during several minutes with auditory stimulation. The results suggest that the newborns are able to discriminate between different stimuli despite their early age

900-L liquid xenon cryogenic system operation for the MEG experiment

CERN Document Server

Haruyama, T; Mihara, S; Hisamatsu, Y; Iawamoto, W; Mori, T; Nishiguchi, H; Otani, W; Sawada, R; Uchiyama, Y; Nishitani, T

2009-01-01

A cryogenic system for the MEG (muon rare decay) experiment has started operation at the Paul Sherrer Institute in Zurich. The main part of the MEG detector is the 900-L liquid xenon calorimeter for gamma ray detection, equipped with 850 photo multipliers directly immersed in liquid xenon. A 200 W pulse tube cryocooler enabled LN2-free operation of this calorimeter. A liquid purification system; using a liquid pump and a zero boil-off 1000-L cryogenic buffer dewar is also included in the system. The first entire engineering run was carried out in November-December 2007 and satisfactory cryogenic performances were confirmed.

fMRI-vs-MEG evaluation of post-stroke interhemispheric asymmetries in primary sensorimotor hand areas.

Science.gov (United States)

Altamura, Claudia; Torquati, Kahtya; Zappasodi, Filippo; Ferretti, Antonio; Pizzella, Vittorio; Tibuzzi, Francesco; Vernieri, Fabrizio; Pasqualetti, Patrizio; Landi, Doriana; Del Gratta, Cosimo; Romani, Gian-Luca; Maria Rossini, Paolo; Tecchio, Franca

2007-04-01

Growing evidence emphasizes a positive role of brain ipsilesional (IL) reorganization in stroke patients with partial recovery. Ten patients affected by a monohemispheric stroke in the middle cerebral artery territory underwent functional magnetic resonance (fMRI) and magnetoencephalography (MEG) evaluation of the primary sensory (S1) activation via the same paradigm (median nerve galvanic stimulation). Four patients did not present S1 fMRI activation [Rossini, P.M., Altamura, C., Ferretti, A., Vernieri, F., Zappasodi, F., Caulo, M., Pizzella, V., Del Gratta, C., Romani, G.L., Tecchio, F., 2004. Does cerebrovascular disease affect the coupling between neuronal activity and local haemodynamics? Brain 127, 99-110], although inclusion criteria required bilateral identifiable MEG responses. Mean Euclidean distance between fMRI and MEG S1 activation Talairach coordinates was 10.1+/-2.9 mm, with a 3D intra-class correlation (ICC) coefficient of 0.986. Interhemispheric asymmetries, evaluated by an MEG procedure independent of Talairach transformation, were outside or at the boundaries of reference ranges in 6 patients. In 3 of them, the IL activation presented medial or lateral shift with respect to the omega-shaped post-rolandic area while in the other 3, IL areas were outside the peri-rolandic region. In conclusion, despite dissociated intensity, the MEG and fMRI activations displayed good spatial consistency in stroke patients, thus confirming excessive interhemispheric asymmetries as a suitable indicator of unusual recruitments in the ipsilesional hemisphere, within or outside the peri-rolandic region.

Feasibility study of an active target for the MEG experiment

Energy Technology Data Exchange (ETDEWEB)

Papa, A., E-mail: angela.papa@psi.ch [Paul Scherrer Institut PSI, CH-5232 Villigen (Switzerland); Cavoto, G. [INFN Sezione di Roma, P.le Aldo Moro, 2, 00185 Roma (Italy); Ripiccini, E. [INFN Sezione di Roma, P.le Aldo Moro, 2, 00185 Roma (Italy); Dipartimento di Fisica dell' Università degli studi di Roma, P.le Aldo Moro, 2, 00185 Roma (Italy)

2014-03-01

We consider the possibility to have an active target for the upgrade of the MEG experiment (MEG II). The active target should work as (1) a beam monitoring, to continuously measure the muon stopping rate and therefore provide a direct evaluation of the detector acceptance (or an absolute normalization of the stopped muon); and as (2) an auxiliary device for the spectrometer, to improve the determination of the muon decay vertex and consequently to achieve a better positron momentum and angular resolutions, detecting the positron from the muon decay. In this work we studied the feasibility of detecting minimum ionizing particle with a single layer of 250 μm fiber and the capability to discriminate between the signal induced by either a muon or a positron.

Feasibility study of an active target for the MEG experiment

International Nuclear Information System (INIS)

Papa, A.; Cavoto, G.; Ripiccini, E.

2014-01-01

We consider the possibility to have an active target for the upgrade of the MEG experiment (MEG II). The active target should work as (1) a beam monitoring, to continuously measure the muon stopping rate and therefore provide a direct evaluation of the detector acceptance (or an absolute normalization of the stopped muon); and as (2) an auxiliary device for the spectrometer, to improve the determination of the muon decay vertex and consequently to achieve a better positron momentum and angular resolutions, detecting the positron from the muon decay. In this work we studied the feasibility of detecting minimum ionizing particle with a single layer of 250 μm fiber and the capability to discriminate between the signal induced by either a muon or a positron

MR findings of primary scalp mass

International Nuclear Information System (INIS)

Kim, Jee Eun; Hwang, Hee Young; Park, Sung Hye; Kim, Young Chae; Lee, Young Suk

1996-01-01

To evaluate the diagnostic value of MRI, we compared MR images of primary scalp mass with pathological findings. Eight cases in seven patients who had presented primary scalp mass during the previous three years were evaluated by MRI and confirmed with surgical excision and pathologic evaluation. 0.38T(Resonex 4000, USA) MRI was used and all MR images were analysed retrospectively. Eight pathologically confirmed cases consisted of three cases of epidermal cysts, one of steatocystoma simplex, three of neurofibromatosis and one of lymphangioma. All epidermal cysts were located in the occipital area and showed a higher signal intensity than CSF in T1WI, and proton density and variable signal intensity in T2WI. The Steatocystoma showed a signal iniensity similar to fat in T1WI and proton density and a lower signal intensity than fat in T2WI. Neurofibromatosis accounted for three cases in two neurofibromatosis patients;one was located in the right parieto-occipital area and accompanied by hematoma and skull defect; two cases were located in the occipital and posterior cervical area of the same patient. The masses showed a higher signal intensity than muscle in T1WI and hyper or isointensity in T2WI with well enhancement. The lymphangioma showed a signal intensity similar to CSF in all pulse sequences and contained a fat component. MRI is a useful modality for evaluating primary scalp mass

Correlation between quantitative EEG and cerebral blood flow and oxygen metabolism in patients with dementia of Alzheimer type

International Nuclear Information System (INIS)

Kudoh, Masako; Takahashi, Satoshi; Yonezawa, Hisashi

1997-01-01

Quantitative scalp EEG and cerebral blood flow (CBF) and oxygen metabolism (CMRO 2 ) measured by the steady-state 15 O technique and positron emission tomography were studied in 19 patients with mild to moderate dementia of Alzheimer type (DAT) and age-matched controls (EEG=19, PET=6). Scalp electrodes were placed according to the international 10-20 method except for Cz, T3, and T4. To evaluate the relative changes in power for each frequency band between the two groups, the percentage power fraction (percentage power for each frequency band at a site compared to the total power at that site; %delta for 2.0-3.8 Hz, %theta for 4.0-7.8 Hz, %alpha for 8.0-12.8 Hz, %beta for 13.0-25.4 Hz) was calculated. Compared with controls, DAT patients showed a significant decrease in %alpha, while significant increases in %theta at all electrodes, and significant increases in %delta at the temporal, parietal and occipital electrodes were observed. The patient group displayed a significant decrease in rCBF and rCMRO 2 in the parietal, temporal and frontal cortices, but the reduction in rCMRO 2 was less remarkable than that of rCBF. %Theta at P3, O1 and O2 showed a significant negative correlation with rCBF, and %theta at P3, O1showed a significant negative correlation with rCMRO 2 . %Delta at P3, P4 and T5 was significantly negatively correlated with rCBF in the corresponding regions, and %alpha at almost all the electrodes (except O1, F3, P3) was significantly positively correlated with rCBF in the corresponding regions. %Delta and %alpha did not show any significant correlation with rCMRO 2 . (author)

Head position in the MEG helmet affects the sensitivity to anterior sources.

Science.gov (United States)

Marinkovic, K; Cox, B; Reid, K; Halgren, E

2004-11-30

Current MEG instruments derive the whole-head coverage by utilizing a helmet-shaped opening at the bottom of the dewar. These helmets, however, are quite a bit larger than most people's heads so subjects commonly lean against the back wall of the helmet in order to maintain a steady position. In such cases the anterior brain sources may be too distant to be picked up by the sensors reliably. Potential "invisibility" of the frontal and anterior temporal sources may be particularly troublesome for the studies of cognition and language, as they are subserved significantly by these areas. We examined the sensitivity of the distributed anatomically-constrained MEG (aMEG) approach to the head position ("front" vs. "back") secured within a helmet with custom-tailored bite-bars during a lexical decision task. The anterior head position indeed resulted in much greater sensitivity to language-related activity in frontal and anterior temporal locations. These results emphasize the need to adjust the head position in the helmet in order to maximize the "visibility" of the sources in the anterior brain regions in cognitive and language tasks.

Simultaneous Scalp, Skull, Kidney, and Pancreas Transplant from a Single Donor.

Science.gov (United States)

Selber, Jesse C; Chang, Edward I; Clemens, Mark W; Gaber, Lilian; Hanasono, Matthew M; Klebuc, Michael; Skoracki, Roman J; Trask, Todd; Yu, Peirong; Gaber, A Osama

2016-06-01

Vascularized composite allotransplantation is an emerging field, but the complications of lifelong immunosuppression limit indications. Vascularized composite allotransplantation in solid organ recipients represents a unique opportunity because immunosuppression has already been accepted. This report of a simultaneous scalp, skull, kidney, and pancreas transplant represents both the first skull-scalp transplant and combination of a vascularized composite allotransplantation with double organ transplantation. A previous recipient of a kidney-pancreas transplant presented with osteoradionecrosis of the calvaria and a large area of unstable scalp following successful, curative treatment of a scalp tumor. His kidney and pancreas functions were also critically poor. A multidisciplinary, multi-institutional plan was developed to perform a simultaneous scalp, skull, and repeated kidney and pancreas transplantation, all from a single donor. Eighteen months after the patient was listed with the United Network for Organ Sharing, a donor was identified and the multiorgan vascularized composite allotransplantation was performed. Twenty physicians and 15 hours were required to perform donor and recipient procedures. The patient recovered well and was discharged on postoperative day 15. He has had one episode of scalp rejection confirmed by biopsy and treated successfully. His creatinine value is currently 0.8 mg/dl, from 5.0 mg/dl, and his blood glucose levels are normal without supplemental insulin. Aesthetic outcome is very satisfactory. The patient is now 1 year post-transplantation and doing well. Vascularized composite allotransplantation in solid organ recipients is an expansion of current indications to already immunosuppressed patients. Rejection of the vascularized composite allotransplant without solid organ rejection can occur and is treatable. Methodical planning, an interdisciplinary approach, and careful management of all organs are critical to success

Magnetoencephalographic localization of peritumoral temporal epileptic focus previous surgical resection.

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Amo, Carlos; Saldaña, Cristóbal; Hidalgo, Mercedes González; Maestú, Fernando; Fernández, Alberto; Arrazola, Juan; Ortiz, Tomás

2003-01-01

Magnetoencephalography (MEG) is suggested as a localizing technique of epileptogenic areas in drug-resistant seizure patients due to intracraneal lesions. A male 42-year-old patient who begins at 26 with partial complex drug-resistant seizures is put forward. MRI shows a 9 mm diameter lesion located in left superior temporal gyrus which seems compatible with cavernoma. Both conventional and sleep deprivation EEGs have proved normal. Sleep EEG shows sharp waves in left temporal region. MEG helps to localize interictal spike and spike-wave activity, as well as wide slow wave (2-7 Hz) activity areas. Craniotomy under analgesia and aware sedation conditions is carried out. Intrasurgery cortical electric stimulation assisted by neuronavigator causes a limited partial complex seizure which the patient recognizes to be exactly like his. Thus, MEG localization of the epileptogenic area is confirmed. Surgical resection of both the lesion and the epileptogenic area is carried out. The patient remains free from seizures 9 months after surgery. A control MEG study reveals no epileptogenic nor slow wave activity. in this particular case, MEG has proven to be a useful presurgical evaluation technique to localize epileptogenic activity, validated by intrasurgical cortical stimulation.

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

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

2017-08-01

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

Factors influencing the effectiveness of scalp cooling in the prevention of chemotherapy-induced alopecia.

Science.gov (United States)

Komen, Manon M C; Smorenburg, Carolien H; van den Hurk, Corina J G; Nortier, Johan W R

2013-01-01

The success of scalp cooling in preventing or reducing chemotherapy-induced alopecia (CIA) is highly variable between patients and chemotherapy regimens. The outcome of hair preservation is often unpredictable and depends on various factors. Methods. We performed a structured search of literature published from 1970 to February 2012 for articles that reported on factors influencing the effectiveness of scalp cooling to prevent CIA in patients with cancer. Results. The literature search identified 192 reports, of which 32 studies were considered relevant. Randomized studies on scalp cooling are scarce and there is little information on the determinants of the result. The effectiveness of scalp cooling for hair preservation depends on dose and type of chemotherapy, with less favorable results at higher doses. Temperature seems to be an important determinant. Various studies suggest that a subcutaneous scalp temperature less than 22 °C is required for hair preservation. Conclusions. The effectiveness of scalp cooling for hair preservation varies by chemotherapy type and dose, and probably by the degree and duration of cooling.

Increased phase synchronization during continuous face integration measured simultaneously with EEG and fMRI.

Science.gov (United States)

Kottlow, Mara; Jann, Kay; Dierks, Thomas; Koenig, Thomas

2012-08-01

Gamma zero-lag phase synchronization has been measured in the animal brain during visual binding. Human scalp EEG studies used a phase locking factor (trial-to-trial phase-shift consistency) or gamma amplitude to measure binding but did not analyze common-phase signals so far. This study introduces a method to identify networks oscillating with near zero-lag phase synchronization in human subjects. We presented unpredictably moving face parts (NOFACE) which - during some periods - produced a complete schematic face (FACE). The amount of zero-lag phase synchronization was measured using global field synchronization (GFS). GFS provides global information on the amount of instantaneous coincidences in specific frequencies throughout the brain. Gamma GFS was increased during the FACE condition. To localize the underlying areas, we correlated gamma GFS with simultaneously recorded BOLD responses. Positive correlates comprised the bilateral middle fusiform gyrus and the left precuneus. These areas may form a network of areas transiently synchronized during face integration, including face-specific as well as binding-specific regions and regions for visual processing in general. Thus, the amount of zero-lag phase synchronization between remote regions of the human visual system can be measured with simultaneously acquired EEG/fMRI. Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

MEG Working Memory N-Back Task Reveals Functional Deficits in Combat-Related Mild Traumatic Brain Injury.

Science.gov (United States)

Huang, Ming-Xiong; Nichols, Sharon; Robb-Swan, Ashley; Angeles-Quinto, Annemarie; Harrington, Deborah L; Drake, Angela; Huang, Charles W; Song, Tao; Diwakar, Mithun; Risbrough, Victoria B; Matthews, Scott; Clifford, Royce; Cheng, Chung-Kuan; Huang, Jeffrey W; Sinha, Anusha; Yurgil, Kate A; Ji, Zhengwei; Lerman, Imanuel; Lee, Roland R; Baker, Dewleen G

2018-04-13

Combat-related mild traumatic brain injury (mTBI) is a leading cause of sustained cognitive impairment in military service members and Veterans. However, the mechanism of persistent cognitive deficits including working memory (WM) dysfunction is not fully understood in mTBI. Few studies of WM deficits in mTBI have taken advantage of the temporal and frequency resolution afforded by electromagnetic measurements. Using magnetoencephalography (MEG) and an N-back WM task, we investigated functional abnormalities in combat-related mTBI. Study participants included 25 symptomatic active-duty service members or Veterans with combat-related mTBI and 20 healthy controls with similar combat experiences. MEG source-magnitude images were obtained for alpha (8-12 Hz), beta (15-30 Hz), gamma (30-90 Hz), and low-frequency (1-7 Hz) bands. Compared with healthy combat controls, mTBI participants showed increased MEG signals across frequency bands in frontal pole (FP), ventromedial prefrontal cortex, orbitofrontal cortex (OFC), and anterior dorsolateral prefrontal cortex (dlPFC), but decreased MEG signals in anterior cingulate cortex. Hyperactivations in FP, OFC, and anterior dlPFC were associated with slower reaction times. MEG activations in lateral FP also negatively correlated with performance on tests of letter sequencing, verbal fluency, and digit symbol coding. The profound hyperactivations from FP suggest that FP is particularly vulnerable to combat-related mTBI.

Dosimetric verification of helical tomotherapy for total scalp irradiation

International Nuclear Information System (INIS)

Hardcastle, Nicholas; Soisson, Emilie; Metcalfe, Peter; Rosenfeld, Anatoly B.; Tome, Wolfgang A.

2008-01-01

Total scalp irradiation is a treatment technique used for a variety of superficial malignancies. Helical tomotherapy is an effective technique used for total scalp irradiation. Recent published work has shown the TomoTherapy planning system to overestimate the superficial dose. In this study, the superficial doses for a helical tomotherapy total scalp irradiation have been measured on an anthropomorphic phantom using radiochromic and radiographic film as well as a new skin dosimeter, the MOSkin. The superficial dose was found to be accurately calculated by the TomoTherapy planning system. This is in contrast to recent reports, probably due to a combination of the smaller dose grid resolution used in planning and this particular treatment primarily consisting of beamlets tangential to the scalp. The superficial dose was found to increase from 33.6 to 41.2 Gy and 36.0 to 42.0 Gy over the first 2 mm depth in the phantom in selected regions of the PTV, measured with radiochromic film. The prescription dose was 40 Gy. The superficial dose was at the prescription dose or higher in some regions due to the bolus effect of the thermoplastic head mask and the head rest used to aid treatment setup. It is suggested that to achieve the prescription dose at the surface (≤2 mm depth) bolus or a custom thermoplastic helmet is used.

The temporal evolution of electromagnetic markers sensitive to the capacity limits of visual short-term memory.

Science.gov (United States)

Mitchell, Daniel J; Cusack, Rhodri

2011-01-01

An electroencephalographic (EEG) marker of the limited contents of human visual short-term memory (VSTM) has previously been described. Termed contralateral delay activity, this consists of a sustained, posterior, negative potential that correlates with memory load and is greatest contralateral to the remembered hemifield. The current investigation replicates this finding and uses magnetoencephalography (MEG) to characterize its magnetic counterparts and their neural generators as they evolve throughout the memory delay. A parametric manipulation of memory load, within and beyond capacity limits, allows separation of signals that asymptote with behavioral VSTM performance from additional responses that contribute to a linear increase with set-size. Both EEG and MEG yielded bilateral signals that track the number of objects held in memory, and contralateral signals that are independent of memory load. In MEG, unlike EEG, the contralateral interaction between hemisphere and item load is much weaker, suggesting that bilateral and contralateral markers of memory load reflect distinct sources to which EEG and MEG are differentially sensitive. Nonetheless, source estimation allowed both the bilateral and the weaker contralateral capacity-limited responses to be localized, along with a load-independent contralateral signal. Sources of global and hemisphere-specific signals all localized to the posterior intraparietal sulcus during the early delay. However the bilateral load response peaked earlier and its generators shifted later in the delay. Therefore the hemifield-specific response may be more closely tied to memory maintenance while the global load response may be involved in initial processing of a limited number of attended objects, such as their individuation or consolidation into memory.

The temporal evolution of electromagnetic markers sensitive to the capacity limits of visual short-term memory

Directory of Open Access Journals (Sweden)

Daniel James Mitchell

2011-02-01

Full Text Available An electroencephalographic (EEG marker of the limited contents of human visual short-term memory (VSTM has previously been described. Termed contralateral delay activity (CDA, this consists of a sustained, posterior, negative potential that correlates with memory load and is greatest contralateral to the remembered hemifield. The current investigation replicates this finding and uses magnetoencephalography (MEG to characterise its magnetic counterparts and their neural generators as they evolve throughout the memory delay. A parametric manipulation of memory load, within and beyond capacity limits, allows separation of signals that asymptote with behavioural VSTM performance from additional responses that contribute to a linear increase with set-size. Both EEG and MEG yielded bilateral signals that track the number of objects held in memory, and contralateral signals that are independent of memory load. In MEG, unlike EEG, the contralateral interaction between hemisphere and item load is much weaker, suggesting that bilateral and contralateral markers of memory load reflect distinct sources to which EEG and MEG are differentially sensitive. Nonetheless, source estimation allowed both the bilateral and the weaker contralateral capacity-limited responses to be localised, along with a load-independent contralateral signal. Sources of global and hemisphere-specific signals all localised to the posterior intraparietal sulcus during the early delay. However the bilateral load response peaked earlier and its generators shifted later in the delay. Therefore the hemifield-specific response may be more closely tied to memory maintenance while the global load response may be involved in initial processing of a limited number of attended objects, such as their individuation or consolidation into memory.

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-11-01

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

Outpatient-based scalp surgery without shaving and allowing use of shampoo.

Science.gov (United States)

Hwang, Sun-Chul; Kim, Soon-Kwon; Park, Kwan-Woong; Im, Soo-Bin; Shin, Won-Han; Kim, Bum-Tae

2012-02-01

To assess the authors' experience of wound management following scalp mass surgery after introducing a policy of leaving hair unshaved and allowing patients to use shampoo. The authors retrospectively reviewed 93 patients who underwent outpatient-based excision of a scalp or skull mass. Surgical complications, mass depth, and maximal mass size were analyzed. All of the surgeries were performed without shaving around the lesion; the hair was simply parted along the proposed incision, and the parting was maintained using adhesive plasters. Routine antiseptic scalp preparations, skin closure with staples after mass excision, and topical ointment on the day following surgery were used, and use of shampoo was allowed. The staples were removed on postoperative days 7-10. The masses were located in the skin (23 cases), subcutaneously (64 cases), and subgaleally (6 cases). All patients except one had satisfactory wound healing. No infections occurred. Leaving hair unshaved and allowing patients to use shampoo can be applied in wound management after scalp mass surgery. Copyright © 2012 Elsevier Inc. All rights reserved.

A newly developed removable dental device for fused 3-D MRI/Meg imaging

Energy Technology Data Exchange (ETDEWEB)

Kuboki, Takuo [Okayama Univ. (Japan). Dental School; Clark, G T; Akhtari, M; Sutherling, W W

1999-06-01

Recently 3-D imaging techniques have been used to shed light on the role of abnormal brain functions in such conditions as nocturnal bruxism and orofacial pain. In order to achieve precise 3-D image fusion between magnetic resonance images (MRI) and magnetoencephalography (MEG) data, we developed a removable dental device which attaches rigidly to the teeth. Using this device, correlation of MEG and MRI data points was achieved by the co-registration of 3 or more fiducial points. Using a Polhemus 3-space digitizer the locations of the points were registered on MEG and then a small amount of high-water-content material was placed at each point for registering these same points on MRI. The mean reproducibility of interpoint distances, determined for 2 subjects, was between 0.59 and 0.82 mm. Using a Monte Carlo statistical analysis we determined that the accuracy of a posterior projection from the fiducial points to any point within the strata of the brain is {+-}3.3 mm. The value of this device is that it permits reasonably precise and repeatable co-registration of these points and yet it is easily removed and replaced by the patient. Obviously such a device could also be adapted for use in diagnosis and analysis of brain functions related with other various sensory and motor functions (e.g., taste, pain, clenching) in maxillofacial region using MRI and MEG. (author)

A newly developed removable dental device for fused 3-D MRI/Meg imaging

International Nuclear Information System (INIS)

Kuboki, Takuo; Clark, G.T.; Akhtari, M.; Sutherling, W.W.

1999-01-01

Recently 3-D imaging techniques have been used to shed light on the role of abnormal brain functions in such conditions as nocturnal bruxism and orofacial pain. In order to achieve precise 3-D image fusion between magnetic resonance images (MRI) and magnetoencephalography (MEG) data, we developed a removable dental device which attaches rigidly to the teeth. Using this device, correlation of MEG and MRI data points was achieved by the co-registration of 3 or more fiducial points. Using a Polhemus 3-space digitizer the locations of the points were registered on MEG and then a small amount of high-water-content material was placed at each point for registering these same points on MRI. The mean reproducibility of interpoint distances, determined for 2 subjects, was between 0.59 and 0.82 mm. Using a Monte Carlo statistical analysis we determined that the accuracy of a posterior projection from the fiducial points to any point within the strata of the brain is ±3.3 mm. The value of this device is that it permits reasonably precise and repeatable co-registration of these points and yet it is easily removed and replaced by the patient. Obviously such a device could also be adapted for use in diagnosis and analysis of brain functions related with other various sensory and motor functions (e.g., taste, pain, clenching) in maxillofacial region using MRI and MEG. (author)

Downregulated long non-coding RNA MEG3 in breast cancer regulates proliferation, migration and invasion by depending on p53’s transcriptional activity

Energy Technology Data Exchange (ETDEWEB)

Sun, Lin [West Biostatistics and Cost-effectiveness Research Center, Medical Insurance Office, West China Hospital of Sichuan University, 610041, Sichuan (China); Li, Yu [Department of Anesthesiology, West China Hospital, Sichuan University, 610041, Sichuan (China); Yang, Bangxiang, E-mail: b19933009@qq.coom [Department of Pain Management, West China Hospital of Sichuan University, 610041, Sichuan (China)

2016-09-09

Long non-coding RNAs (lncRNAs) was found to play critical roles in tumorigenesis, hence, screen of tumor-related lncRNAs, identification of their biological roles is important for understanding the processes of tumorigenesis. In this study, we identified the expressing difference of several tumor-related lncRNAs in breast cancer samples and found that, MEG3, which is downregulated in non-small cell lung cancer (NSCLC) tumor tissues, is also downregulated in breast cancer samples compared with adjacent tissues. For figuring out the effect of MEG3 in breast cancer cells MCF7 and MB231, we overexpressed MEG3 in these cells, and found that it resulted the inhibition of proliferation, colony formation, migration and invasion capacities by enhancing p53’s transcriptional activity on its target genes, including p21, Maspin and KAI1. MEG3 presented similar effects in MB157, which is a p53-null breast cancer cell line, when functional p53 but not p53R273H mutant, which lacks transcriptional activity, was introduced. Surprisingly, overexpression of MEG3 activates p53’s transcriptional activity by decreasing MDM2’s transcription level, and thus stabilizes and accumulates P53. Taken together, our findings indicate that MEG3 is downregulated in breast cancer tissues and affects breast cancer cells’ malignant behaviors, which indicate MEG3 a potential therapeutic target for breast cancer. - Highlights: • MEG3 RNA is widely downregulated in breast tumor tissue. • MEG3 regulates P53 indirectly through transcriptional regulation of MDM2. • Under unstressed condition, MEG3-related P53 accumulation transcriptionally activates p53’s target genes. • MEG3 expression level tightly regulates proliferation, colony formation, migration and invasion in breast tumor cells.

Single-subject-based whole-brain MEG slow-wave imaging approach for detecting abnormality in patients with mild traumatic brain injury

Directory of Open Access Journals (Sweden)

Ming-Xiong Huang

2014-01-01

Full Text Available Traumatic brain injury (TBI is a leading cause of sustained impairment in military and civilian populations. However, mild TBI (mTBI can be difficult to detect using conventional MRI or CT. Injured brain tissues in mTBI patients generate abnormal slow-waves (1–4 Hz that can be measured and localized by resting-state magnetoencephalography (MEG. In this study, we develop a voxel-based whole-brain MEG slow-wave imaging approach for detecting abnormality in patients with mTBI on a single-subject basis. A normative database of resting-state MEG source magnitude images (1–4 Hz from 79 healthy control subjects was established for all brain voxels. The high-resolution MEG source magnitude images were obtained by our recent Fast-VESTAL method. In 84 mTBI patients with persistent post-concussive symptoms (36 from blasts, and 48 from non-blast causes, our method detected abnormalities at the positive detection rates of 84.5%, 86.1%, and 83.3% for the combined (blast-induced plus with non-blast causes, blast, and non-blast mTBI groups, respectively. We found that prefrontal, posterior parietal, inferior temporal, hippocampus, and cerebella areas were particularly vulnerable to head trauma. The result also showed that MEG slow-wave generation in prefrontal areas positively correlated with personality change, trouble concentrating, affective lability, and depression symptoms. Discussion is provided regarding the neuronal mechanisms of MEG slow-wave generation due to deafferentation caused by axonal injury and/or blockages/limitations of cholinergic transmission in TBI. This study provides an effective way for using MEG slow-wave source imaging to localize affected areas and supports MEG as a tool for assisting the diagnosis of mTBI.

Trace elements in scalp hair of leukaemia patients

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Khuder Ali

2014-08-01

Full Text Available The aim of this study was to determine the concentration of Fe, Ni, Cu, Zn and Pb in scalp hair of leukaemia patients and healthy volunteers, using the optimised XRF method. Leukaemia hair samples were classifi ed corresponding to type, growth and age of the participants. The results showed that the studied trace elements (TEs in both of leukaemia and control groups were positively skewed. In comparison with the control group, lower Fe, Cu, Zn and Pb and higher of Ni medians were found in all studied leukaemia patients. The median rank obtained by Mann-Whitney U-test revealed insignifi cant differences between the leukaemia patients subgroups and the controls. An exact probability (α 0.70 in the scalp hair of control group were observed between Ni/Fe-Ni, Cu/Fe-Cu, Zn/Fe-Zn, Pb/Fe-Pb, Cu/Ni-Zn/Ni, Cu/Ni-Pb/Ni, Zn/Ni-Pb/Ni, Zn/Fe-Zn/Cu, Pb/Ni-Ni and Ni/Fe-Pb/Ni, whereas only very strong positive ratios in the scalp hair of leukaemia patients group were observed between Ni/Fe-Ni, Cu/Fe-Cu, Zn/Fe-Zn and Pb/Fe-Pb, all correlations were signifi cant at p < 0.05. Other strong and signifi cant correlations were also observed in scalp hair of both groups. Signifi cant differences between grouping of studied TEs in all classifi ed leukaemia groups and controls were found using principal component analysis (PCA. The results of PCA confi rmed that the type and the growth of leukaemia factors were more important in element loading than the age factor.

Fetal short time variation during labor: a non-invasive alternative to fetal scalp pH measurements?

Science.gov (United States)

Schiermeier, Sven; Reinhard, Joscha; Hatzmann, Hendrike; Zimmermann, Ralf C; Westhof, Gregor

2009-01-01

To determine whether short time variation (STV) of fetal heart beat correlates with scalp pH measurements during labor. From 1279 deliveries, 197 women had at least one fetal scalp pH measurement. Using the CTG-Player, STVs were calculated from the electronically saved cardiotocography (CTG) traces and related to the fetal scalp pH measurements. There was no correlation between STV and fetal scalp pH measurements (r=-0.0592). Fetal STV is an important parameter with high sensitivity for antenatal fetal acidosis. This study shows that STV calculations do not correlate with fetal scalp pH measurements during labor, hence are not helpful in identifying fetal acidosis.

EEG and Coma.

Science.gov (United States)

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.

Neglected giant scalp Basal cell carcinoma

DEFF Research Database (Denmark)

Larsen, Anne Kristine; El-Charnoubi, Waseem-Asim Ghulam; Gehl, Julie

2014-01-01

control, a satisfactory long-term cosmetic and functional result. We present a case with a neglected basal cell scalp carcinoma, treated with wide excision and postoperative radiotherapy, reconstructed with a free latissimus dorsi flap. The cosmetic result is acceptable and there is no sign of recurrence...

Scalp cooling to prevent alopecia after chemotherapy can be considered safe in patients with breast cancer

NARCIS (Netherlands)

van den Hurk, C.J.; van de Poll-Franse, L.V.; Breed, W.P.M.; Coebergh, J.W.W.; Nortier, J.

2013-01-01

With modern scalp cooling equipment cytotoxic damage of hair root cells can be prevented in half of the patients with cancer at high risk of alopecia. However, traditionally doubt has existed whether scalp cooling might facilitate hiding and disseminating scalp skin metastases and thus decrease

Design of Embedded System for Multivariate Classification of Finger and Thumb Movements Using EEG Signals for Control of Upper Limb Prosthesis

Science.gov (United States)

Javed, Amna; Tiwana, Mohsin I.; Khan, Umar Shahbaz

2018-01-01

Brain Computer Interface (BCI) determines the intent of the user from a variety of electrophysiological signals. These signals, Slow Cortical Potentials, are recorded from scalp, and cortical neuronal activity is recorded by implanted electrodes. This paper is focused on design of an embedded system that is used to control the finger movements of an upper limb prosthesis using Electroencephalogram (EEG) signals. This is a follow-up of our previous research which explored the best method to classify three movements of fingers (thumb movement, index finger movement, and first movement). Two-stage logistic regression classifier exhibited the highest classification accuracy while Power Spectral Density (PSD) was used as a feature of the filtered signal. The EEG signal data set was recorded using a 14-channel electrode headset (a noninvasive BCI system) from right-handed, neurologically intact volunteers. Mu (commonly known as alpha waves) and Beta Rhythms (8–30 Hz) containing most of the movement data were retained through filtering using “Arduino Uno” microcontroller followed by 2-stage logistic regression to obtain a mean classification accuracy of 70%. PMID:29888252

Design of Embedded System for Multivariate Classification of Finger and Thumb Movements Using EEG Signals for Control of Upper Limb Prosthesis

Directory of Open Access Journals (Sweden)

Nasir Rashid

2018-01-01

Full Text Available Brain Computer Interface (BCI determines the intent of the user from a variety of electrophysiological signals. These signals, Slow Cortical Potentials, are recorded from scalp, and cortical neuronal activity is recorded by implanted electrodes. This paper is focused on design of an embedded system that is used to control the finger movements of an upper limb prosthesis using Electroencephalogram (EEG signals. This is a follow-up of our previous research which explored the best method to classify three movements of fingers (thumb movement, index finger movement, and first movement. Two-stage logistic regression classifier exhibited the highest classification accuracy while Power Spectral Density (PSD was used as a feature of the filtered signal. The EEG signal data set was recorded using a 14-channel electrode headset (a noninvasive BCI system from right-handed, neurologically intact volunteers. Mu (commonly known as alpha waves and Beta Rhythms (8–30 Hz containing most of the movement data were retained through filtering using “Arduino Uno” microcontroller followed by 2-stage logistic regression to obtain a mean classification accuracy of 70%.

Design of Embedded System for Multivariate Classification of Finger and Thumb Movements Using EEG Signals for Control of Upper Limb Prosthesis.

Science.gov (United States)

Rashid, Nasir; Iqbal, Javaid; Javed, Amna; Tiwana, Mohsin I; Khan, Umar Shahbaz

2018-01-01

Brain Computer Interface (BCI) determines the intent of the user from a variety of electrophysiological signals. These signals, Slow Cortical Potentials, are recorded from scalp, and cortical neuronal activity is recorded by implanted electrodes. This paper is focused on design of an embedded system that is used to control the finger movements of an upper limb prosthesis using Electroencephalogram (EEG) signals. This is a follow-up of our previous research which explored the best method to classify three movements of fingers (thumb movement, index finger movement, and first movement). Two-stage logistic regression classifier exhibited the highest classification accuracy while Power Spectral Density (PSD) was used as a feature of the filtered signal. The EEG signal data set was recorded using a 14-channel electrode headset (a noninvasive BCI system) from right-handed, neurologically intact volunteers. Mu (commonly known as alpha waves) and Beta Rhythms (8-30 Hz) containing most of the movement data were retained through filtering using "Arduino Uno" microcontroller followed by 2-stage logistic regression to obtain a mean classification accuracy of 70%.

Evidence for Morphological Recomposition in Compound Words using MEG

Directory of Open Access Journals (Sweden)

Teon Lamont Brooks

2015-04-01

Full Text Available Psycholinguistic and electrophysiological studies of lexical processing show convergent evidence for morpheme-based lexical access for morphologically complex words that involves early decomposition into their constituent morphemes followed by some combinatorial operation. Considering that both semantically transparent (e.g., sailboat and semantically opaque (e.g., bootleg compounds undergo morphological decomposition during the earlier stages of lexical processing, subsequent combinatorial operations should account for the difference in the contribution of the constituent morphemes to the meaning of these different word types. In this study we use magnetoencephalography (MEG to pinpoint the neural bases of this combinatorial stage in English compound word recognition. MEG data were acquired while participants performed a word naming task in which three word types, transparent compounds (e.g., roadside, opaque compounds (e.g., butterfly, and morphologically simple words (e.g., brothel were contrasted in a partial-repetition priming paradigm where the word of interest was primed by one of its constituent morphemes. Analysis of onset latency revealed shorter latencies to name compound words than simplex words when primed, further supporting a stage of morphological decomposition in lexical access. An analysis of the associated MEG activity uncovered a region of interest implicated in morphological composition, the Left Anterior Temporal Lobe (LATL. Only transparent compounds showed increased activity in this area from 250 to 470 ms. Previous studies using sentences and phrases have highlighted the role of LATL in performing computations for basic combinatorial operations. Results are in tune with decomposition models for morpheme accessibility early in processing and suggest that semantics play a role in combining the meanings of morphemes when their composition is transparent to the overall word meaning.

Fetal short time variation during labor: a non-invasive alternative to fetal scalp pH measurements?

OpenAIRE

Schiermeier, Sven; Reinhard, Joscha; Hatzmann, Hendrike; Zimmermann, Ralf C.; Westhof, Gregor

2009-01-01

Objective: To determine whether short time variation (STV) of fetal heart beat correlates with scalp pH measurements during labor. Patients and methods: From 1279 deliveries, 197 women had at least one fetal scalp pH measurement. Using the CTG-Player®, STVs were calculated from the electronically saved cardiotocography (CTG) traces and related to the fetal scalp pH measurements. Results: There was no correlation between STV and fetal scalp pH measurements (r=−0.0592). Conclusions: Fetal ST...

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

Science.gov (United States)

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.

Spatiotemporal analysis of single-trial EEG of emotional pictures based on independent component analysis and source location

Science.gov (United States)

Liu, Jiangang; Tian, Jie

2007-03-01

The present study combined the Independent Component Analysis (ICA) and low-resolution brain electromagnetic tomography (LORETA) algorithms to identify the spatial distribution and time course of single-trial EEG record differences between neural responses to emotional stimuli vs. the neutral. Single-trial multichannel (129-sensor) EEG records were collected from 21 healthy, right-handed subjects viewing the emotion emotional (pleasant/unpleasant) and neutral pictures selected from International Affective Picture System (IAPS). For each subject, the single-trial EEG records of each emotional pictures were concatenated with the neutral, and a three-step analysis was applied to each of them in the same way. First, the ICA was performed to decompose each concatenated single-trial EEG records into temporally independent and spatially fixed components, namely independent components (ICs). The IC associated with artifacts were isolated. Second, the clustering analysis classified, across subjects, the temporally and spatially similar ICs into the same clusters, in which nonparametric permutation test for Global Field Power (GFP) of IC projection scalp maps identified significantly different temporal segments of each emotional condition vs. neutral. Third, the brain regions accounted for those significant segments were localized spatially with LORETA analysis. In each cluster, a voxel-by-voxel randomization test identified significantly different brain regions between each emotional condition vs. the neutral. Compared to the neutral, both emotional pictures elicited activation in the visual, temporal, ventromedial and dorsomedial prefrontal cortex and anterior cingulated gyrus. In addition, the pleasant pictures activated the left middle prefrontal cortex and the posterior precuneus, while the unpleasant pictures activated the right orbitofrontal cortex, posterior cingulated gyrus and somatosensory region. Our results were well consistent with other functional imaging

Molecular characterization and expression of maternally expressed gene 3 (Meg3/Gtl2) RNA in the mouse inner ear

DEFF Research Database (Denmark)

Manji, S.S.; Sørensen, Brita Singers; Klockars, T.

2006-01-01

The pathways responsible for sound perception in the cochlea involve the coordinated and regulated expression of hundreds of genes. By using microarray analysis, we identified several transcripts enriched in the inner ear, including the maternally expressed gene 3 (Meg3/Gtl2), an imprinted...... noncoding RNA. Real-time PCR analysis demonstrated that Meg3/Gtl2 was highly expressed in the cochlea, brain, and eye. Molecular studies revealed the presence of several Meg3/Gtl2 RNA splice variants in the mouse cochlea, brain, and eye. In situ hybridizations showed intense Meg3/Gtl2 RNA staining...... otocyst and localized to the spiral ganglion, stria vascularis, Reissner's membrane, and greater epithelial ridge (GER) in the cochlear duct. RT-PCR analysis performed on cell lines derived from the organ of Corti, representing neural, supporting, and hair cells, showed significantly elevated levels...

GALA: Group Analysis Leads to Accuracy, a novel approach for solving the inverse problem in exploratory analysis of group MEG recordings

Directory of Open Access Journals (Sweden)

Vladimir eKozunov

2015-04-01

Full Text Available Although MEG/EEG signals are highly variable between subjects, they allow characterizing systematic changes of cortical activity in both space and time. Traditionally a two-step procedure is used. The first step is a transition from sensor to source space by the means of solving an ill-posed inverse problem for each subject individually. The second is mapping of cortical regions consistently active across subjects. In practice the first step often leads to a set of active cortical regions whose location and timecourses display a great amount of interindividual variability hindering the subsequent group analysis.We propose Group Analysis Leads to Accuracy (GALA - a solution that combines the two steps into one. GALA takes advantage of individual variations of cortical geometry and sensor locations. It exploits the ensuing variability in electromagnetic forward model as a source of additional information. We assume that for different subjects functionally identical cortical regions are located in close proximity and partially overlap and their timecourses are correlated. This relaxed similarity constraint on the inverse solution can be expressed within a probabilistic framework, allowing for an iterative algorithm solving the inverse problem jointly for all subjects.A systematic simulation study showed that GALA, as compared with the standard min-norm approach, improves accuracy of true activity recovery, when accuracy is assessed both in terms of spatial proximity of the estimated and true activations and correct specification of spatial extent of the activated regions. This improvement obtained without using any noise normalization techniques for both solutions, preserved for a wide range of between-subject variations in both spatial and temporal features of regional activation. The corresponding activation timecourses exhibit significantly higher similarity across subjects. Similar results were obtained for a real MEG dataset of face

Non-linear canonical correlation for joint analysis of MEG signals from two subjects

Directory of Open Access Journals (Sweden)

Cristina eCampi

2013-06-01

Full Text Available We consider the problem of analysing magnetoencephalography (MEG data measured from two persons undergoing the same experiment, and we propose a method that searches for sources with maximally correlated energies. Our method is based on canonical correlation analysis (CCA, which provides linear transformations, one for each subject, such that the correlation between the transformed MEG signals is maximized. Here, we present a nonlinear version of CCA which measures the correlation of energies. Furthermore, we introduce a delay parameter in the modelto analyse, e.g., leader-follower changes in experiments where the two subjects are engaged in social interaction.

MEG studies prohibited muon decays to explore grand unified theories of elementary particles

International Nuclear Information System (INIS)

Mori, Toshinori

2009-01-01

The MEG experiment, designed and proposed by Japanese physicists, is being carried out at Paul Scherrer Institute (PSI) in Switzerland, in collaboration with physicists from Italy, Switzerland, Russia and U.S.A. The experiment will make an extensive search for a muon's two-body decay into an electron and a gamma ray, μ→eγ, which is prohibited in the Standard Model of elementary particles, to explore Supersymmetric Grand Unified Theories. This article gives a brief description of the MEG experiment with an emphasis on the innovative experimental techniques developed to achieve the unprecedented experimental sensitivity. (author)

Prediction of mineral scale formation in wet gas condensate pipelines and in MEG (mono ethylene glycol) regeneration plants

Energy Technology Data Exchange (ETDEWEB)

Sandengen, Kristian

2006-12-20

Gas hydrate formation is a serious problem in the oil and gas industry, since its formation can plug wells and prevent production. The gas hydrate is a crystalline solid with a natural gas molecule surrounded by a cage of water molecules. It forms at high pressures and low temperatures. This is a problem for offshore gas wells, where the temperature is low in transport lines from well to the production facilities. Mono Ethylene Glycol (MEG) is commonly used as hydrate inhibitor. Classified as a thermodynamic inhibitor, this additive functions just as antifreeze in an automotive radiator. When producing oil and gas there will in most cases also be produced some water, which can contain dissolved salts. These salts may precipitate and they tend to deposit on surfaces. Deposition of inorganic minerals from brine is called scale. Generally MEG has the adverse effect of lowering the solubility of most salts. A common method to prevent corrosion in flow lines is to increase pH by adding basic agents (e.g. NaOH, NaHCO{sub 3}) to the MEG stream. In such cases, carbonate salts are particularly troublesome since an increase in pH by one unit, will reduce the solubility by two orders of magnitude. Thus there will be a trade off between good corrosion protection (high pH) and scale control (low pH). The aim of this work has been to develop a model that can predict mineral solubility in the presence of MEG. Experimental solubility data, together with thermodynamic data taken from literature, have been utilized to construct empirical functions for the influence of MEG on mineral scale formation. These functions enabled the expansion of an already existing aqueous scale model into a model valid for water+MEG mixed solutions. The aqueous scale model combines an equation of state (gas+oil phase) with the Pitzer ion interaction model (water phase) to describe the multiphase behaviour of gas-oil-water systems. This work summarizes the theoretical foundation and proposes how to work

Scalp Hematoma Characteristics Associated With Intracranial Injury in Pediatric Minor Head Injury.

Science.gov (United States)

Burns, Emma C M; Grool, Anne M; Klassen, Terry P; Correll, Rhonda; Jarvis, Anna; Joubert, Gary; Bailey, Benoit; Chauvin-Kimoff, Laurel; Pusic, Martin; McConnell, Don; Nijssen-Jordan, Cheri; Silver, Norm; Taylor, Brett; Osmond, Martin H

2016-05-01

Minor head trauma accounts for a significant proportion of pediatric emergency department (ED) visits. In children younger than 24 months, scalp hematomas are thought to be associated with the presence of intracranial injury (ICI). We investigated which scalp hematoma characteristics were associated with increased odds of ICI in children less than 17 years who presented to the ED following minor head injury and whether an underlying linear skull fracture may explain this relationship. This was a secondary analysis of 3,866 patients enrolled in the Canadian Assessment of Tomography of Childhood Head Injury (CATCH) study. Information about scalp hematoma presence (yes/no), location (frontal, temporal/parietal, occipital), and size (small and localized, large and boggy) was collected by emergency physicians using a structured data collection form. ICI was defined as the presence of an acute brain lesion on computed tomography. Logistic regression analyses were adjusted for age, sex, dangerous injury mechanism, irritability on examination, suspected open or depressed skull fracture, and clinical signs of basal skull fracture. ICI was present in 159 (4.1%) patients. The presence of a scalp hematoma (n = 1,189) in any location was associated with significantly greater odds of ICI (odds ratio [OR] = 4.4, 95% confidence interval [CI] = 3.06 to 6.02), particularly for those located in temporal/parietal (OR = 6.0, 95% CI = 3.9 to 9.3) and occipital regions (OR = 5.6, 95% CI = 3.5 to 8.9). Both small and localized and large and boggy hematomas were significantly associated with ICI, although larger hematomas conferred larger odds (OR = 9.9, 95% CI = 6.3 to 15.5). Although the presence of a scalp hematoma was associated with greater odds of ICI in all age groups, odds were greatest in children aged 0 to 6 months (OR = 13.5, 95% CI = 1.5 to 119.3). Linear skull fractures were present in 156 (4.0%) patients. Of the 111 patients with scalp hematoma and ICI, 57 (51%) patients had

[Donor supply of scalp and specificities of hair transplantation in Asians].

Science.gov (United States)

Tsilosani, A Z; Mshvenieradze, E G

2008-01-01

In 2005--2007 in a hair transplantation clinic 'Talizi' the flow of international patients increased dramatically, including those from Central and Eastern Asia. During this period 211 ethnic Asian patients underwent operations, including 146 patients from South Korea, 2--from China, 62-- from Kazakhstan and 1--from Philippines. Black and straight hair give impact of low density due to considerable contrast with characteristic for Asians light color scalp; therefore, from the very beginning we tried to transplant as many grafts (follicular units - FU) as possible. For the operation we chose strip version (FUSS) that enables to receive large number of grafts. The scale of transplantation varied in a range of 1200-3800 FU, on average--2500-3000 FU. Though, even from the very first cases we faced specificities of ethnic Asian scalp that significantly complicated our work: low density and low hair/graft ratio in donor zone in contrast to information from special literature, and low laxity (flexibility) of the scalp. We set an objective to specify indicators of donor density (number of FU on a sq.cm and hair/FU ratio), to study bio-mechanical specificities of ethnic Asian scalp and develop optimal surgical tactics for these patients after the evaluation of transplantation results. Observation group was composed of 211 patients from abovementioned countries and a sub-group--50 Korean patients for medium-scale hair transplantation (2000-3000 FU) by strip version. Study of donor characteristics of these patients revealed low density--74 FU/cm2; on 1 cm2 grow only 121 hairs, whereas hair/FU ration was 1,63. Strength required to close would edges (scalp tension power) varied from 1,4 kg-f to 2,6 kg-f depending on scalp flexibility and number of transplanted grafts (strip width), and amounted on average to 2,16 +/- 0,02 kg-f, p flexibility of the scalps this resulted in high percentage (10-15%) of wide (4-10 mm) scar formation in donor area. In order to find the way out from

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

Directory of Open Access Journals (Sweden)

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.

[Interactive dynamic scalp acupuncture combined with occupational therapy for upper limb motor impairment in stroke: a randomized controlled trial].

Science.gov (United States)

Wang, Jun; Pei, Jian; Cui, Xiao; Sun, Kexing; Ni, Huanhuan; Zhou, Cuixia; Wu, Ji; Huang, Mei; Ji, Li

2015-10-01

To compare the clinical efficacy on upper limb motor impairment in stroke between the interactive dynamic scalp acupuncture therapy and the traditional scalp acupuncture therapy. The randomized controlled trial and MINIMIZE layering randomization software were adopted. Seventy patients of upper limb with III to V grade in Brunnstrom scale after stroke were randomized into an interactive dynamic scalp acupuncture group and a traditional scalp acupuncture group, 35 cases in each one. In the interactive dynamic scalp acupuncture group, the middle 2/5 of Dingnieqianxiexian (anterior oblique line of vertex-temporal), the middle 2/5 of Dingniehouxiexian (posterior oblique line of vertex-temporal) and Dingpangerxian (lateral line 2 of vertex) on the affected side were selected as the stimulation areas. Additionally, the rehabilitation training was applied during scalp acupuncture treatment. In the traditional scalp acupuncture group, the scalp stimulation areas were same as the interactive dynamic scalp acupuncture group. But the rehabilitation training was applied separately. The rehabilitation training was applied in the morning and the scalp acupuncture was done in the afternoon. The results in Fugl-Meyer for the upper limb motor function (U-FMA), the Wolf motor function measure scale (WM- FT) and the modified Barthel index in the two groups were compared between the two groups before treatment and in 1 and 2 months of treatment, respectively. After treatment, the U-FMA score, WMFT score and the score of the modified Barthel index were all apparently improved as compared with those before treatment (all P acupuncture group was better than that in the traditional scalp acupuncture group (P acupuncture group were improved apparently as compared with those in the traditional scalp acupuncture group (P acupuncture group were not different significantly as compared with those in the traditional scalp acupuncture group (both P > 0.05). For the patients of IV to V grade in

Cortical and Subcortical Coordination of Visual Spatial Attention Revealed by Simultaneous EEG-fMRI Recording.

Science.gov (United States)

Green, Jessica J; Boehler, Carsten N; Roberts, Kenneth C; Chen, Ling-Chia; Krebs, Ruth M; Song, Allen W; Woldorff, Marty G

2017-08-16

Visual spatial attention has been studied in humans with both electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) individually. However, due to the intrinsic limitations of each of these methods used alone, our understanding of the systems-level mechanisms underlying attentional control remains limited. Here, we examined trial-to-trial covariations of concurrently recorded EEG and fMRI in a cued visual spatial attention task in humans, which allowed delineation of both the generators and modulators of the cue-triggered event-related oscillatory brain activity underlying attentional control function. The fMRI activity in visual cortical regions contralateral to the cued direction of attention covaried positively with occipital gamma-band EEG, consistent with activation of cortical regions representing attended locations in space. In contrast, fMRI activity in ipsilateral visual cortical regions covaried inversely with occipital alpha-band oscillations, consistent with attention-related suppression of the irrelevant hemispace. Moreover, the pulvinar nucleus of the thalamus covaried with both of these spatially specific, attention-related, oscillatory EEG modulations. Because the pulvinar's neuroanatomical geometry makes it unlikely to be a direct generator of the scalp-recorded EEG, these covariational patterns appear to reflect the pulvinar's role as a regulatory control structure, sending spatially specific signals to modulate visual cortex excitability proactively. Together, these combined EEG/fMRI results illuminate the dynamically interacting cortical and subcortical processes underlying spatial attention, providing important insight not realizable using either method alone. SIGNIFICANCE STATEMENT Noninvasive recordings of changes in the brain's blood flow using functional magnetic resonance imaging and electrical activity using electroencephalography in humans have individually shown that shifting attention to a location in space

Preliminary Results of Ocular Artefacts Identification in EEC Series by Neural Network

Directory of Open Access Journals (Sweden)

M. Kofronova

1996-06-01

Full Text Available The human electroencephalogram (EEG, is record of the electrical activity of the brain and contains useful diagnostic information on a variety of neurological disorders. Normal EEG signal are usually registered from electrodes placed on the scalp, and are often very small in amplitude, of 20 µV. The EEG, like all biomedical signals, is very susceptible to a variety of large signal contamination or artefacts (signals of other than brain activity which reduce its clinical usefulness. For example, blinking or moving eyes produces large electrical potentials around the eyes called the electrooculogram (EOG. The EOG spreads across the scalp to contaminate the EEG, when it is referred to as an ocular artefact (OA. This paper includes method of identification portion of the EEG record where ocular artefact appears and classification its type by neural network.

EEG Controlled Wheelchair

Directory of Open Access Journals (Sweden)

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.

Tracking single dynamic MEG dipole sources using the projected Extended Kalman Filter.

Science.gov (United States)

Yao, Yuchen; Swindlehurst, A Lee

2011-01-01

This paper presents two new algorithms based on the Extended Kalman Filter (EKF) for tracking the parameters of single dynamic magnetoencephalography (MEG) dipole sources. We assume a dynamic MEG dipole source with possibly both time-varying location and dipole orientation. The standard EKF-based tracking algorithm performs well under the assumption that the dipole source components vary in time as a Gauss-Markov process, provided that the background noise is temporally stationary. We propose a Projected-EKF algorithm that is adapted to a more forgiving condition where the background noise is temporally nonstationary, as well as a Projected-GLS-EKF algorithm that works even more universally, when the dipole components vary arbitrarily from one sample to the next.

Risk of traumatic brain injuries in children younger than 24 months with isolated scalp hematomas.

Science.gov (United States)

Dayan, Peter S; Holmes, James F; Schutzman, Sara; Schunk, Jeffrey; Lichenstein, Richard; Foerster, Lillian A; Hoyle, John; Atabaki, Shireen; Miskin, Michelle; Wisner, David; Zuspan, SallyJo; Kuppermann, Nathan

2014-08-01

We aimed to determine the association between scalp hematoma characteristics and traumatic brain injuries in young children with blunt head trauma who have no other symptoms or signs suggestive of traumatic brain injuries (defined as "isolated scalp hematomas"). This was a secondary analysis of children younger than 24 months with minor blunt head trauma from a prospective cohort study in 25 Pediatric Emergency Care Applied Research Network emergency departments. Treating clinicians completed a structured data form. For children with isolated scalp hematomas, we determined the prevalence of and association between scalp hematoma characteristics and (1) clinically important traumatic brain injury (death, neurosurgery for traumatic brain injury, intubation >24 hours for traumatic brain injury, or positive computed tomography (CT) scan in association with hospitalization ≥2 nights for traumatic brain injury); and (2) traumatic brain injury on CT. Of 10,659 patients younger than 24 months were enrolled, 2,998 of 10,463 (28.7%) with complete data had isolated scalp hematomas. Clinically important traumatic brain injuries occurred in 12 patients (0.4%; 95% confidence interval [CI] 0.2% to 0.7%); none underwent neurosurgery (95% CI 0% to 0.1%). Of 570 patients (19.0%) for whom CTs were obtained, 50 (8.8%; 95% CI 6.6% to 11.4%) had traumatic brain injuries on CT. Younger age, non-frontal scalp hematoma location, increased scalp hematoma size, and severe injury mechanism were independently associated with traumatic brain injury on CT. In patients younger than 24 months with isolated scalp hematomas, a minority received CTs. Despite the occasional presence of traumatic brain injuries on CT, the prevalence of clinically important traumatic brain injuries was very low, with no patient requiring neurosurgery. Clinicians should use patient age, scalp hematoma location and size, and injury mechanism to help determine which otherwise asymptomatic children should undergo

Equivalent charge source model based iterative maximum neighbor weight for sparse EEG source localization.

Science.gov (United States)

Xu, Peng; Tian, Yin; Lei, Xu; Hu, Xiao; Yao, Dezhong

2008-12-01

How to localize the neural electric activities within brain effectively and precisely from the scalp electroencephalogram (EEG) recordings is a critical issue for current study in clinical neurology and cognitive neuroscience. In this paper, based on the charge source model and the iterative re-weighted strategy, proposed is a new maximum neighbor weight based iterative sparse source imaging method, termed as CMOSS (Charge source model based Maximum neighbOr weight Sparse Solution). Different from the weight used in focal underdetermined system solver (FOCUSS) where the weight for each point in the discrete solution space is independently updated in iterations, the new designed weight for each point in each iteration is determined by the source solution of the last iteration at both the point and its neighbors. Using such a new weight, the next iteration may have a bigger chance to rectify the local source location bias existed in the previous iteration solution. The simulation studies with comparison to FOCUSS and LORETA for various source configurations were conducted on a realistic 3-shell head model, and the results confirmed the validation of CMOSS for sparse EEG source localization. Finally, CMOSS was applied to localize sources elicited in a visual stimuli experiment, and the result was consistent with those source areas involved in visual processing reported in previous studies.

Bispectral pairwise interacting source analysis for identifying systems of cross-frequency interacting brain sources from electroencephalographic or magnetoencephalographic signals

Science.gov (United States)

Chella, Federico; Pizzella, Vittorio; Zappasodi, Filippo; Nolte, Guido; Marzetti, Laura

2016-05-01

Brain cognitive functions arise through the coordinated activity of several brain regions, which actually form complex dynamical systems operating at multiple frequencies. These systems often consist of interacting subsystems, whose characterization is of importance for a complete understanding of the brain interaction processes. To address this issue, we present a technique, namely the bispectral pairwise interacting source analysis (biPISA), for analyzing systems of cross-frequency interacting brain sources when multichannel electroencephalographic (EEG) or magnetoencephalographic (MEG) data are available. Specifically, the biPISA makes it possible to identify one or many subsystems of cross-frequency interacting sources by decomposing the antisymmetric components of the cross-bispectra between EEG or MEG signals, based on the assumption that interactions are pairwise. Thanks to the properties of the antisymmetric components of the cross-bispectra, biPISA is also robust to spurious interactions arising from mixing artifacts, i.e., volume conduction or field spread, which always affect EEG or MEG functional connectivity estimates. This method is an extension of the pairwise interacting source analysis (PISA), which was originally introduced for investigating interactions at the same frequency, to the study of cross-frequency interactions. The effectiveness of this approach is demonstrated in simulations for up to three interacting source pairs and for real MEG recordings of spontaneous brain activity. Simulations show that the performances of biPISA in estimating the phase difference between the interacting sources are affected by the increasing level of noise rather than by the number of the interacting subsystems. The analysis of real MEG data reveals an interaction between two pairs of sources of central mu and beta rhythms, localizing in the proximity of the left and right central sulci.

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

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Chiara Spironelli

2017-12-01

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

High precision anatomy for MEG☆

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Troebinger, Luzia; López, José David; Lutti, Antoine; Bradbury, David; Bestmann, Sven; Barnes, Gareth

2014-01-01

Precise MEG estimates of neuronal current flow are undermined by uncertain knowledge of the head location with respect to the MEG sensors. This is either due to head movements within the scanning session or systematic errors in co-registration to anatomy. Here we show how such errors can be minimized using subject-specific head-casts produced using 3D printing technology. The casts fit the scalp of the subject internally and the inside of the MEG dewar externally, reducing within session and between session head movements. Systematic errors in matching to MRI coordinate system are also reduced through the use of MRI-visible fiducial markers placed on the same cast. Bootstrap estimates of absolute co-registration error were of the order of 1 mm. Estimates of relative co-registration error were < 1.5 mm between sessions. We corroborated these scalp based estimates by looking at the MEG data recorded over a 6 month period. We found that the between session sensor variability of the subject's evoked response was of the order of the within session noise, showing no appreciable noise due to between-session movement. Simulations suggest that the between-session sensor level amplitude SNR improved by a factor of 5 over conventional strategies. We show that at this level of coregistration accuracy there is strong evidence for anatomical models based on the individual rather than canonical anatomy; but that this advantage disappears for errors of greater than 5 mm. This work paves the way for source reconstruction methods which can exploit very high SNR signals and accurate anatomical models; and also significantly increases the sensitivity of longitudinal studies with MEG. PMID:23911673

Meditation and the EEG

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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...

Long non-coding RNA MEG3 inhibits the proliferation and metastasis of oral squamous cell carcinoma by regulating the WNT/β-catenin signaling pathway.

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Liu, Zongxiang; Wu, Cui; Xie, Nina; Wang, Penglai

2017-10-01

This study aimed to investigate how long non-coding RNA (lncRNA) maternally expressed gene 3 (MEG3) inhibits the growth and metastasis of oral squamous cell carcinoma (OSCC) by regulating WNT/β-catenin signaling pathway in order to explore the antitumor effect of MEG3 and to provide a potential molecular target for the treatment of OSCC. The RT-qPCR technique was used to quantitatively analyze the expression of MEG3 in cancer and adjacent tissues collected from the patients after surgery. Using the Lipofectamine method, the MEG3 overexpression vector and the siRNA interference vector were constructed and transfected into SCC15 and Cal27 cells, respectively, followed by cell proliferation, apoptosis and metastasis analyses. The semi-quantitative analysis of the expression of the β-catenin protein in transfected cells was performed by the western blot analysis, and the activity of the WNT/β-catenin signaling pathway was analyzed using the TOP/FOP flash reporters. In addition, the cells were treated with decitabine to investigate the correlation between the MEG3 expression and the DNA methylation. Results showed that the expression level of MEG3 was significantly decreased in OSCC (psuppressor by inhibiting the WNT/β-catenin signaling pathway. In addition, the expression of the MEG3 was significantly affected by the degree of DNA methylation. It was concluded that the lncRNA MEG3 can inhibit the growth and metastasis of OSCC by negatively regulating the WNT/β-catenin signaling pathway.

Scalp and skull influence on near infrared photon propagation in the Colin27 brain template.

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Strangman, Gary E; Zhang, Quan; Li, Zhi

2014-01-15

Near-infrared neuromonitoring (NIN) is based on near-infrared spectroscopy (NIRS) measurements performed through the intact scalp and skull. Despite the important effects of overlying tissue layers on the measurement of brain hemodynamics, the influence of scalp and skull on NIN sensitivity are not well characterized. Using 3555 Monte Carlo simulations, we estimated the sensitivity of individual continuous-wave NIRS measurements to brain activity over the entire adult human head by introducing a small absorption perturbation to brain gray matter and quantifying the influence of scalp and skull thickness on this sensitivity. After segmenting the Colin27 template into five tissue types (scalp, skull, cerebrospinal fluid, gray matter and white matter), the average scalp thickness was 6.9 ± 3.6 mm (range: 3.6-11.2mm), while the average skull thickness was 6.0 ± 1.9 mm (range: 2.5-10.5mm). Mean NIN sensitivity - defined as the partial path length through gray matter divided by the total photon path length - ranged from 0.06 (i.e., 6% of total path length) at a 20mm source-detector separation, to over 0.19 at 50mm separations. NIN sensitivity varied substantially around the head, with occipital pole exhibiting the highest NIRS sensitivity to gray matter, whereas inferior frontal regions had the lowest sensitivity. Increased scalp and skull thickness were strongly associated with decreased sensitivity to brain tissue. Scalp thickness always exhibited a slightly larger effect on sensitivity than skull thickness, but the effect of both varied with SD separation. We quantitatively characterize sensitivity around the head as well as the effects of scalp and skull, which can be used to interpret NIN brain activation studies as well as guide the design, development and optimization of NIRS devices and sensors. Copyright © 2013 Elsevier Inc. All rights reserved.

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

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Miralena I. Tomescu

2015-09-01

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

[Effects of recombinant human alpha-2b and gamma interferons on bone marrow megakaryocyte progenitors (CFU-Meg) from patients with chronic myelocytic leukemia].

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