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Sample records for scalp eeg meg

  1. Measures of spatial similarity and response magnitude in MEG and scalp EEG.

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    Tian, Xing; Huber, David E

    2008-01-01

    Sensor selection is typically used in magnetoencephalography (MEG) and scalp electroencephalography (EEG) studies, but this practice cannot differentiate between changes in the distribution of neural sources versus changes in the magnitude of neural sources. This problem is further complicated by (1) subject averaging despite sizable individual anatomical differences and (2) experimental designs that produce overlapping waveforms due to short latencies between stimuli. Using data from the entire spatial array of sensors, we present simple multivariate measures that (1) normalize against individual differences by comparison with each individual's standard response; (2) compare the similarity of spatial patterns in different conditions (angle test) to ascertain whether the distribution of neural sources is different; and (3) compare the response magnitude between conditions which are sufficiently similar (projection test). These claims are supported by applying the reported techniques to a short-term word priming paradigm as measured with MEG, revealing more reliable results as compared to traditional sensor selection methodology. Although precise cortical localization remains intractable, these techniques are easy to calculate, relatively assumption free, and yield the important psychological measures of similarity and response magnitude.

  2. Benchmarking for On-Scalp MEG Sensors.

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    Xie, Minshu; Schneiderman, Justin F; Chukharkin, Maxim L; Kalabukhov, Alexei; Riaz, Bushra; Lundqvist, Daniel; Whitmarsh, Stephen; Hamalainen, Matti; Jousmaki, Veikko; Oostenveld, Robert; Winkler, Dag

    2017-06-01

    We present a benchmarking protocol for quantitatively comparing emerging on-scalp magnetoencephalography (MEG) sensor technologies to their counterparts in state-of-the-art MEG systems. As a means of validation, we compare a high-critical-temperature superconducting quantum interference device (high Tc SQUID) with the low- Tc SQUIDs of an Elekta Neuromag TRIUX system in MEG recordings of auditory and somatosensory evoked fields (SEFs) on one human subject. We measure the expected signal gain for the auditory-evoked fields (deeper sources) and notice some unfamiliar features in the on-scalp sensor-based recordings of SEFs (shallower sources). The experimental results serve as a proof of principle for the benchmarking protocol. This approach is straightforward, general to various on-scalp MEG sensors, and convenient to use on human subjects. The unexpected features in the SEFs suggest on-scalp MEG sensors may reveal information about neuromagnetic sources that is otherwise difficult to extract from state-of-the-art MEG recordings. As the first systematically established on-scalp MEG benchmarking protocol, magnetic sensor developers can employ this method to prove the utility of their technology in MEG recordings. Further exploration of the SEFs with on-scalp MEG sensors may reveal unique information about their sources.

  3. Ragu: A Free Tool for the Analysis of EEG and MEG Event-Related Scalp Field Data Using Global Randomization Statistics

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    Thomas Koenig

    2011-01-01

    Full Text Available We present a program (Ragu; Randomization Graphical User interface for statistical analyses of multichannel event-related EEG and MEG experiments. Based on measures of scalp field differences including all sensors, and using powerful, assumption-free randomization statistics, the program yields robust, physiologically meaningful conclusions based on the entire, untransformed, and unbiased set of measurements. Ragu accommodates up to two within-subject factors and one between-subject factor with multiple levels each. Significance is computed as function of time and can be controlled for type II errors with overall analyses. Results are displayed in an intuitive visual interface that allows further exploration of the findings. A sample analysis of an ERP experiment illustrates the different possibilities offered by Ragu. The aim of Ragu is to maximize statistical power while minimizing the need for a-priori choices of models and parameters (like inverse models or sensors of interest that interact with and bias statistics.

  4. Ragu: a free tool for the analysis of EEG and MEG event-related scalp field data using global randomization statistics.

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    Koenig, Thomas; Kottlow, Mara; Stein, Maria; Melie-García, Lester

    2011-01-01

    We present a program (Ragu; Randomization Graphical User interface) for statistical analyses of multichannel event-related EEG and MEG experiments. Based on measures of scalp field differences including all sensors, and using powerful, assumption-free randomization statistics, the program yields robust, physiologically meaningful conclusions based on the entire, untransformed, and unbiased set of measurements. Ragu accommodates up to two within-subject factors and one between-subject factor with multiple levels each. Significance is computed as function of time and can be controlled for type II errors with overall analyses. Results are displayed in an intuitive visual interface that allows further exploration of the findings. A sample analysis of an ERP experiment illustrates the different possibilities offered by Ragu. The aim of Ragu is to maximize statistical power while minimizing the need for a-priori choices of models and parameters (like inverse models or sensors of interest) that interact with and bias statistics.

  5. EEG and MEG: relevance to neuroscience

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    Lopes da Silva, F.

    2013-01-01

    To understand dynamic cognitive processes, the high time resolution of EEG/MEG is invaluable. EEG/MEG signals can play an important role in providing measures of functional and effective connectivity in the brain. After a brief description of the foundations and basic methodological aspects of

  6. Source localization of EEG versus MEG: Emperical comparison using visually evoked responses and theoretical considerations

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    Lopes da silva, F.H.; Wieringa, H.J.; Wieringa, H.J.; Peters, M.J.

    1991-01-01

    Theoretically, the information we can obtain about the functional localization of a source of brain activity from the scalp, for instance evoked by a sensory stimulus, is the same whether one uses EEG or MEG recordings. However, the nature of the sources and, especially of the volume conductor,

  7. Divergent cortical generators of MEG and EEG during human sleep spindles suggested by distributed source modeling.

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    Dehghani, Nima; Cash, Sydney S; Chen, Chih C; Hagler, Donald J; Huang, Mingxiong; Dale, Anders M; Halgren, Eric

    2010-07-07

    Sleep spindles are approximately 1-second bursts of 10-15 Hz activity, occurring during normal stage 2 sleep. In animals, sleep spindles can be synchronous across multiple cortical and thalamic locations, suggesting a distributed stable phase-locked generating system. The high synchrony of spindles across scalp EEG sites suggests that this may also be true in humans. However, prior MEG studies suggest multiple and varying generators. We recorded 306 channels of MEG simultaneously with 60 channels of EEG during naturally occurring spindles of stage 2 sleep in 7 healthy subjects. High-resolution structural MRI was obtained in each subject, to define the shells for a boundary element forward solution and to reconstruct the cortex providing the solution space for a noise-normalized minimum norm source estimation procedure. Integrated across the entire duration of all spindles, sources estimated from EEG and MEG are similar, diffuse and widespread, including all lobes from both hemispheres. However, the locations, phase and amplitude of sources simultaneously estimated from MEG versus EEG are highly distinct during the same spindles. Specifically, the sources estimated from EEG are highly synchronous across the cortex, whereas those from MEG rapidly shift in phase, hemisphere, and the location within the hemisphere. The heterogeneity of MEG sources implies that multiple generators are active during human sleep spindles. If the source modeling is correct, then EEG spindles are generated by a different, diffusely synchronous system. Animal studies have identified two thalamo-cortical systems, core and matrix, that produce focal or diffuse activation and thus could underlie MEG and EEG spindles, respectively. Alternatively, EEG spindles could reflect overlap at the sensors of the same sources as are seen from the MEG. Although our results generally match human intracranial recordings, additional improvements are possible and simultaneous intra- and extra-cranial measures

  8. Divergent cortical generators of MEG and EEG during human sleep spindles suggested by distributed source modeling.

    Directory of Open Access Journals (Sweden)

    Nima Dehghani

    2010-07-01

    Full Text Available Sleep spindles are approximately 1-second bursts of 10-15 Hz activity, occurring during normal stage 2 sleep. In animals, sleep spindles can be synchronous across multiple cortical and thalamic locations, suggesting a distributed stable phase-locked generating system. The high synchrony of spindles across scalp EEG sites suggests that this may also be true in humans. However, prior MEG studies suggest multiple and varying generators.We recorded 306 channels of MEG simultaneously with 60 channels of EEG during naturally occurring spindles of stage 2 sleep in 7 healthy subjects. High-resolution structural MRI was obtained in each subject, to define the shells for a boundary element forward solution and to reconstruct the cortex providing the solution space for a noise-normalized minimum norm source estimation procedure. Integrated across the entire duration of all spindles, sources estimated from EEG and MEG are similar, diffuse and widespread, including all lobes from both hemispheres. However, the locations, phase and amplitude of sources simultaneously estimated from MEG versus EEG are highly distinct during the same spindles. Specifically, the sources estimated from EEG are highly synchronous across the cortex, whereas those from MEG rapidly shift in phase, hemisphere, and the location within the hemisphere.The heterogeneity of MEG sources implies that multiple generators are active during human sleep spindles. If the source modeling is correct, then EEG spindles are generated by a different, diffusely synchronous system. Animal studies have identified two thalamo-cortical systems, core and matrix, that produce focal or diffuse activation and thus could underlie MEG and EEG spindles, respectively. Alternatively, EEG spindles could reflect overlap at the sensors of the same sources as are seen from the MEG. Although our results generally match human intracranial recordings, additional improvements are possible and simultaneous intra- and extra

  9. EEG and MEG Data Analysis in SPM8

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    Vladimir Litvak

    2011-01-01

    Full Text Available SPM is a free and open source software written in MATLAB (The MathWorks, Inc.. In addition to standard M/EEG preprocessing, we presently offer three main analysis tools: (i statistical analysis of scalp-maps, time-frequency images, and volumetric 3D source reconstruction images based on the general linear model, with correction for multiple comparisons using random field theory; (ii Bayesian M/EEG source reconstruction, including support for group studies, simultaneous EEG and MEG, and fMRI priors; (iii dynamic causal modelling (DCM, an approach combining neural modelling with data analysis for which there are several variants dealing with evoked responses, steady state responses (power spectra and cross-spectra, induced responses, and phase coupling. SPM8 is integrated with the FieldTrip toolbox , making it possible for users to combine a variety of standard analysis methods with new schemes implemented in SPM and build custom analysis tools using powerful graphical user interface (GUI and batching tools.

  10. Evaluation of realistic layouts for next generation on-scalp MEG: spatial information density maps.

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    Riaz, Bushra; Pfeiffer, Christoph; Schneiderman, Justin F

    2017-08-01

    While commercial magnetoencephalography (MEG) systems are the functional neuroimaging state-of-the-art in terms of spatio-temporal resolution, MEG sensors have not changed significantly since the 1990s. Interest in newer sensors that operate at less extreme temperatures, e.g., high critical temperature (high-T c ) SQUIDs, optically-pumped magnetometers, etc., is growing because they enable significant reductions in head-to-sensor standoff (on-scalp MEG). Various metrics quantify the advantages of on-scalp MEG, but a single straightforward one is lacking. Previous works have furthermore been limited to arbitrary and/or unrealistic sensor layouts. We introduce spatial information density (SID) maps for quantitative and qualitative evaluations of sensor arrays. SID-maps present the spatial distribution of information a sensor array extracts from a source space while accounting for relevant source and sensor parameters. We use it in a systematic comparison of three practical on-scalp MEG sensor array layouts (based on high-T c SQUIDs) and the standard Elekta Neuromag TRIUX magnetometer array. Results strengthen the case for on-scalp and specifically high-T c SQUID-based MEG while providing a path for the practical design of future MEG systems. SID-maps are furthermore general to arbitrary magnetic sensor technologies and source spaces and can thus be used for design and evaluation of sensor arrays for magnetocardiography, magnetic particle imaging, etc.

  11. Evaluation of MEG vs EEG after sleep deprivation in epilepsy.

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    Colon, A J; Ronner, H E; Boon, P; Ossenblok, P

    2017-02-01

    MEG and EEG after sleep deprivation (EEG-SD) are applied as diagnostic tools in the evaluation of patients with possible epilepsy. There is no gold standard to check whether the diagnosis based on these two modalities is correct. The best standard available is the long-term follow-up of patients. As follow-up of an earlier study in which the additional value of MEG vs EEG-SD diagnosis was evaluated, we investigated the long-term validity of MEG-based and EEG-SD-based diagnosis. Data collected from 46 patients were used in a comparative study of the last known diagnosis against the original one of 8 years ago. Long-term (3-8 years) sensitivity of sharp phenomena (combining spikes and sharp waves) in routine MEG and in EEG-SD for the diagnosis epilepsy is 71% and 62%, respectively. When compared to the original study, this hardly changed. Over time, uncertainty on diagnosis diminishes. MEG as well as EEG-SD are robust long-term predictors for epilepsy. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  12. Combined EEG/MEG can outperform single modality EEG or MEG source reconstruction in presurgical epilepsy diagnosis.

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    Ümit Aydin

    Full Text Available We investigated two important means for improving source reconstruction in presurgical epilepsy diagnosis. The first investigation is about the optimal choice of the number of epileptic spikes in averaging to (1 sufficiently reduce the noise bias for an accurate determination of the center of gravity of the epileptic activity and (2 still get an estimation of the extent of the irritative zone. The second study focuses on the differences in single modality EEG (80-electrodes or MEG (275-gradiometers and especially on the benefits of combined EEG/MEG (EMEG source analysis. Both investigations were validated with simultaneous stereo-EEG (sEEG (167-contacts and low-density EEG (ldEEG (21-electrodes. To account for the different sensitivity profiles of EEG and MEG, we constructed a six-compartment finite element head model with anisotropic white matter conductivity, and calibrated the skull conductivity via somatosensory evoked responses. Our results show that, unlike single modality EEG or MEG, combined EMEG uses the complementary information of both modalities and thereby allows accurate source reconstructions also at early instants in time (epileptic spike onset, i.e., time points with low SNR, which are not yet subject to propagation and thus supposed to be closer to the origin of the epileptic activity. EMEG is furthermore able to reveal the propagation pathway at later time points in agreement with sEEG, while EEG or MEG alone reconstructed only parts of it. Subaveraging provides important and accurate information about both the center of gravity and the extent of the epileptogenic tissue that neither single nor grand-averaged spike localizations can supply.

  13. Combined EEG/MEG can outperform single modality EEG or MEG source reconstruction in presurgical epilepsy diagnosis.

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    Aydin, Ümit; Vorwerk, Johannes; Dümpelmann, Matthias; Küpper, Philipp; Kugel, Harald; Heers, Marcel; Wellmer, Jörg; Kellinghaus, Christoph; Haueisen, Jens; Rampp, Stefan; Stefan, Hermann; Wolters, Carsten H

    2015-01-01

    We investigated two important means for improving source reconstruction in presurgical epilepsy diagnosis. The first investigation is about the optimal choice of the number of epileptic spikes in averaging to (1) sufficiently reduce the noise bias for an accurate determination of the center of gravity of the epileptic activity and (2) still get an estimation of the extent of the irritative zone. The second study focuses on the differences in single modality EEG (80-electrodes) or MEG (275-gradiometers) and especially on the benefits of combined EEG/MEG (EMEG) source analysis. Both investigations were validated with simultaneous stereo-EEG (sEEG) (167-contacts) and low-density EEG (ldEEG) (21-electrodes). To account for the different sensitivity profiles of EEG and MEG, we constructed a six-compartment finite element head model with anisotropic white matter conductivity, and calibrated the skull conductivity via somatosensory evoked responses. Our results show that, unlike single modality EEG or MEG, combined EMEG uses the complementary information of both modalities and thereby allows accurate source reconstructions also at early instants in time (epileptic spike onset), i.e., time points with low SNR, which are not yet subject to propagation and thus supposed to be closer to the origin of the epileptic activity. EMEG is furthermore able to reveal the propagation pathway at later time points in agreement with sEEG, while EEG or MEG alone reconstructed only parts of it. Subaveraging provides important and accurate information about both the center of gravity and the extent of the epileptogenic tissue that neither single nor grand-averaged spike localizations can supply.

  14. Combined EEG/MEG Can Outperform Single Modality EEG or MEG Source Reconstruction in Presurgical Epilepsy Diagnosis

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    Aydin, Ümit; Vorwerk, Johannes; Dümpelmann, Matthias; Küpper, Philipp; Kugel, Harald; Heers, Marcel; Wellmer, Jörg; Kellinghaus, Christoph; Haueisen, Jens; Rampp, Stefan; Stefan, Hermann; Wolters, Carsten H.

    2015-01-01

    We investigated two important means for improving source reconstruction in presurgical epilepsy diagnosis. The first investigation is about the optimal choice of the number of epileptic spikes in averaging to (1) sufficiently reduce the noise bias for an accurate determination of the center of gravity of the epileptic activity and (2) still get an estimation of the extent of the irritative zone. The second study focuses on the differences in single modality EEG (80-electrodes) or MEG (275-gradiometers) and especially on the benefits of combined EEG/MEG (EMEG) source analysis. Both investigations were validated with simultaneous stereo-EEG (sEEG) (167-contacts) and low-density EEG (ldEEG) (21-electrodes). To account for the different sensitivity profiles of EEG and MEG, we constructed a six-compartment finite element head model with anisotropic white matter conductivity, and calibrated the skull conductivity via somatosensory evoked responses. Our results show that, unlike single modality EEG or MEG, combined EMEG uses the complementary information of both modalities and thereby allows accurate source reconstructions also at early instants in time (epileptic spike onset), i.e., time points with low SNR, which are not yet subject to propagation and thus supposed to be closer to the origin of the epileptic activity. EMEG is furthermore able to reveal the propagation pathway at later time points in agreement with sEEG, while EEG or MEG alone reconstructed only parts of it. Subaveraging provides important and accurate information about both the center of gravity and the extent of the epileptogenic tissue that neither single nor grand-averaged spike localizations can supply. PMID:25761059

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

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

    2015-10-01

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

  16. Simultaneous MEG and intracranial EEG recordings during attentive reading.

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    Dalal, Sarang S; Baillet, Sylvain; Adam, Claude; Ducorps, Antoine; Schwartz, Denis; Jerbi, Karim; Bertrand, Olivier; Garnero, Line; Martinerie, Jacques; Lachaux, Jean-Philippe

    2009-05-01

    The relationship between neural oscillations recorded at various spatial scales remains poorly understood partly due to an overall dearth of studies utilizing simultaneous measurements. In an effort to study quantitative markers of attention during reading, we performed simultaneous magnetoencephalography (MEG) and intracranial electroencephalography (iEEG) recordings in four epileptic patients. Patients were asked to attend to a specific color when presented with an intermixed series of red words and green words, with words of a given color forming a cohesive story. We analyzed alpha, beta, and gamma band oscillatory responses to the word presentation and compared the strength and spatial organization of those responses in both electrophysiological recordings. Time-frequency analysis of iEEG revealed a network of clear attention-modulated high gamma band (50-150 Hz) power increases and alpha/beta (9-25 Hz) suppressions in response to the words. In addition to analyses at the sensor level, MEG time-frequency analysis was performed at the source level using a sliding window beamformer technique. Strong alpha/beta suppressions were observed in MEG reconstructions, in tandem with iEEG effects. While the MEG counterpart of high gamma band enhancement was difficult to interpret at the sensor level in two patients, MEG time-frequency source reconstruction revealed additional activation patterns in accordance with iEEG results. Importantly, iEEG allowed us to confirm that several sources of gamma band modulation observed with MEG were indeed of cortical origin rather than EMG muscular or ocular artifact.

  17. Sparse asynchronous cortical generators can produce measurable scalp EEG signals.

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    von Ellenrieder, Nicolás; Dan, Jonathan; Frauscher, Birgit; Gotman, Jean

    2016-09-01

    We investigate to what degree the synchronous activation of a smooth patch of cortex is necessary for observing EEG scalp activity. We perform extensive simulations to compare the activity generated on the scalp by different models of cortical activation, based on intracranial EEG findings reported in the literature. The spatial activation is modeled as a cortical patch of constant activation or as random sets of small generators (0.1 to 3cm(2) each) concentrated in a cortical region. Temporal activation models for the generation of oscillatory activity are either equal phase or random phase across the cortical patches. The results show that smooth or random spatial activation profiles produce scalp electric potential distributions with the same shape. Also, in the generation of oscillatory activity, multiple cortical generators with random phase produce scalp activity attenuated on average only 2 to 4 times compared to generators with equal phase. Sparse asynchronous cortical generators can produce measurable scalp EEG. This is a possible explanation for seemingly paradoxical observations of simultaneous disorganized intracranial activity and scalp EEG signals. Thus, the standard interpretation of scalp EEG might constitute an oversimplification of the underlying brain activity. Copyright © 2016 Elsevier Inc. All rights reserved.

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

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    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

  19. High density scalp EEG in frontal lobe epilepsy.

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    Feyissa, Anteneh M; Britton, Jeffrey W; Van Gompel, Jamie; Lagerlund, Terrance L; So, Elson; Wong-Kisiel, Lilly C; Cascino, Gregory C; Brinkman, Benjamin H; Nelson, Cindy L; Watson, Robert; Worrell, Gregory A

    2017-01-01

    Localization of seizures in frontal lobe epilepsy using the 10-20 system scalp EEG is often challenging because neocortical seizure can spread rapidly, significant muscle artifact, and the suboptimal spatial resolution for seizure generators involving mesial frontal lobe cortex. Our aim in this study was to determine the value of visual interpretation of 76 channel high density EEG (hdEEG) monitoring (10-10 system) in patients with suspected frontal lobe epilepsy, and to evaluate concordance with MRI, subtraction ictal SPECT co-registered to MRI (SISCOM), conventional EEG, and intracranial EEG (iEEG). We performed a retrospective cohort study of 14 consecutive patients who underwent hdEEG monitoring for suspected frontal lobe seizures. The gold standard for localization was considered to be iEEG. Concordance of hdEEG findings with MRI, subtraction ictal SPECT co-registered to MRI (SISCOM), conventional 10-20 EEG, and iEEG as well as correlation of hdEEG localization with surgical outcome were examined. hdEEG localization was concordant with iEEG in 12/14 and was superior to conventional EEG 3/14 (pfrontal epilepsy requiring localization of epileptogenic brain. hdEEG may assist in developing a hypothesis for iEEG monitoring and could potentially augment EEG source localization. Published by Elsevier B.V.

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

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

    2011-01-01

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

  1. Comparison of EEG and MEG in source localization of induced human gamma-band oscillations during visual stimulus.

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    Mideksa, K G; Hoogenboom, N; Hellriegel, H; Krause, H; Schnitzler, A; Deuschl, G; Raethjen, J; Heute, U; Muthuraman, M

    2015-08-01

    High frequency gamma oscillations are indications of information processing in cortical neuronal networks. Recently, non-invasive detection of these oscillations have become one of the main research areas in magnetoencephalography (MEG) and electroencephalography (EEG) studies. The aim of this study, which is a continuation of our previous MEG study, is to compare the capability of the two modalities (EEG and MEG) in localizing the source of the induced gamma activity due to a visual stimulus, using a spatial filtering technique known as dynamic imaging of coherent sources (DICS). To do this, the brain activity was recorded using simultaneous MEG and EEG measurement and the data were analyzed with respect to time, frequency, and location of the strongest response. The spherical head modeling technique, such as, the three-shell concentric spheres and an overlapping sphere (local sphere) have been used as a forward model to calculate the external electromagnetic potentials and fields recorded by the EEG and MEG, respectively. Our results from the time-frequency analysis, at the sensor level, revealed that the parieto-occipital electrodes and sensors from both modalities showed a clear and sustained gamma-band activity throughout the post-stimulus duration and that both modalities showed similar strongest gamma-band peaks. It was difficult to interpret the spatial pattern of the gamma-band oscillatory response on the scalp, at the sensor level, for both modalities. However, the source analysis result revealed that MEG3 sensor type, which measure the derivative along the longitude, showed the source more focally and close to the visual cortex (cuneus) as compared to that of the EEG.

  2. Detecting Epileptic Seizure from Scalp EEG Using Lyapunov Spectrum

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    Truong Quang Dang Khoa

    2012-01-01

    Full Text Available One of the inherent weaknesses of the EEG signal processing is noises and artifacts. To overcome it, some methods for prediction of epilepsy recently reported in the literature are based on the evaluation of chaotic behavior of intracranial electroencephalographic (EEG recordings. These methods reduced noises, but they were hazardous to patients. In this study, we propose using Lyapunov spectrum to filter noise and detect epilepsy on scalp EEG signals only. We determined that the Lyapunov spectrum can be considered as the most expected method to evaluate chaotic behavior of scalp EEG recordings and to be robust within noises. Obtained results are compared to the independent component analysis (ICA and largest Lyapunov exponent. The results of detecting epilepsy are compared to diagnosis from medical doctors in case of typical general epilepsy.

  3. Localizing brain interactions from rhythmic EEG/MEG data.

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    Nolte, G; Holroyd, T; Carver, F; Coppola, R; Hallett, M

    2004-01-01

    The interpretation of MEG/EEG data in terms of brain connectivity is largely obscured by artefacts of volume conduction, i.e. by the fact that a single source is observable in many channels. Here, we analyze a measure which is insensitive to spurious connectivity arising from volume conducted "self-interaction". For rhythmic data such a measure can be given by the imaginary part of the cross-spectrum between EEG/MEG channels. For the derivation we essentially exploit that a signal is not time-lagged to itself. To localize the sources of this observed interaction we fit a model cross-spectrum consisting of N interacting dipoles to the sample cross-spectrum. The relation to the maximum likelihood estimator will be discussed in detail. The method is illustrated for MEG data of human alpha rhythm in eyes closed condition. The eigenvalues of the imaginary cross-spectrum clearly indicate the presence of at least 4 necessarily interacting sources. Fits of 2 to 6 dipoles in a realistic volume conductor all resulted in locations scattered in the mesial part of the occipital lobe.

  4. A skull-based multiple dipole phantom for EEG and MEG studies

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    Spencer, M.E.; Leahy, R.M. [University of Southern California, Los Angeles, CA (United States); Mosher, J.C. [Los Alamos National Lab., NM (United States)

    1996-07-01

    A versatile phantom for use in evaluating forward and inverse methods for MEG and EEG has been designed and is currently being constructed. The phantom consists of three major components: (i) a 32-element cur- rent dipole array, (ii) a PC-controlled dipole driver with 32 isolated channels allowing independent control of each dipole, (iii) spherical and human-skull mounts in which the dipole array is placed. Materials were selected throughout the phantom to produce minimal field distortions and artifacts to enable acquisition of high quality EEG and MEG data. The dipoles are made from a rigid narrow (0.84 mm) stainless steel coax cable. The dipole drivers can be configured as either current or voltage sources, are independently programmable and fully isolated, and are capable of producing arbitrary bipolar waveforms up to a 200 Hz bandwidth. The spherical mount is a single shell sphere filled with conductive gelatin. The human skull mount has three shells: ``brain`` (conducting gelatin), ``skull`` (the skull is impregnated with a low conductivity conducting gelatin), and ``scalp`` (a thin layer of rubber latex mixed with NaCl to achieve a conductivity matched to the brain). The conductivities will be adjusted to achieve approximately an 80:1:80 ratio. Data collected to date from the spherical phantom shows excellent agreement between measured surface potentials and that predicted from theory (27 of the 32 dipoles give better than 99.9% rms fit) and negligible leakage between dipoles. We are currently completing construction of the skull mount.

  5. MEG-EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy.

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    Chowdhury, Rasheda Arman; Zerouali, Younes; Hedrich, Tanguy; Heers, Marcel; Kobayashi, Eliane; Lina, Jean-Marc; Grova, Christophe

    2015-11-01

    The purpose of this study is to develop and quantitatively assess whether fusion of EEG and MEG (MEEG) data within the maximum entropy on the mean (MEM) framework increases the spatial accuracy of source localization, by yielding better recovery of the spatial extent and propagation pathway of the underlying generators of inter-ictal epileptic discharges (IEDs). The key element in this study is the integration of the complementary information from EEG and MEG data within the MEM framework. MEEG was compared with EEG and MEG when localizing single transient IEDs. The fusion approach was evaluated using realistic simulation models involving one or two spatially extended sources mimicking propagation patterns of IEDs. We also assessed the impact of the number of EEG electrodes required for an efficient EEG-MEG fusion. MEM was compared with minimum norm estimate, dynamic statistical parametric mapping, and standardized low-resolution electromagnetic tomography. The fusion approach was finally assessed on real epileptic data recorded from two patients showing IEDs simultaneously in EEG and MEG. Overall the localization of MEEG data using MEM provided better recovery of the source spatial extent, more sensitivity to the source depth and more accurate detection of the onset and propagation of IEDs than EEG or MEG alone. MEM was more accurate than the other methods. MEEG proved more robust than EEG and MEG for single IED localization in low signal-to-noise ratio conditions. We also showed that only few EEG electrodes are required to bring additional relevant information to MEG during MEM fusion.

  6. The value of multichannel MEG and EEG in the presurgical evaluation of 70 epilepsy patients.

    Science.gov (United States)

    Knake, S; Halgren, E; Shiraishi, H; Hara, K; Hamer, H M; Grant, P E; Carr, V A; Foxe, D; Camposano, S; Busa, E; Witzel, T; Hämäläinen, M S; Ahlfors, S P; Bromfield, E B; Black, P M; Bourgeois, B F; Cole, A J; Cosgrove, G R; Dworetzky, B A; Madsen, J R; Larsson, P G; Schomer, D L; Thiele, E A; Dale, A M; Rosen, B R; Stufflebeam, S M

    2006-04-01

    To evaluate the sensitivity of a simultaneous whole-head 306-channel magnetoencephalography (MEG)/70-electrode EEG recording to detect interictal epileptiform activity (IED) in a prospective, consecutive cohort of patients with medically refractory epilepsy that were considered candidates for epilepsy surgery. Seventy patients were prospectively evaluated by simultaneously recorded MEG/EEG. All patients were surgical candidates or were considered for invasive EEG monitoring and had undergone an extensive presurgical evaluation at a tertiary epilepsy center. MEG and EEG raw traces were analysed individually by two independent reviewers. MEG data could not be evaluated due to excessive magnetic artefacts in three patients (4%). In the remaining 67 patients, the overall sensitivity to detect IED was 72% (48/67 patients) for MEG and 61% for EEG (41/67 patients) analysing the raw data. In 13% (9/67 patients), MEG-only IED were recorded, whereas in 3% (2/67 patients) EEG-only IED were recorded. The combined sensitivity was 75% (50/67 patients). Three hundred and six-channel MEG has a similarly high sensitivity to record IED as EEG and appears to be complementary. In one-third of the EEG-negative patients, MEG can be expected to record IED, especially in the case of lateral neocortical epilepsy and/or cortical dysplasia.

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

    Directory of Open Access Journals (Sweden)

    Forrest Sheng Bao

    2011-01-01

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

  8. A Review of Issues Related to Data Acquisition and Analysis in EEG/MEG Studies.

    Science.gov (United States)

    Puce, Aina; Hämäläinen, Matti S

    2017-05-31

    Electroencephalography (EEG) and magnetoencephalography (MEG) are non-invasive electrophysiological methods, which record electric potentials and magnetic fields due to electric currents in synchronously-active neurons. With MEG being more sensitive to neural activity from tangential currents and EEG being able to detect both radial and tangential sources, the two methods are complementary. Over the years, neurophysiological studies have changed considerably: high-density recordings are becoming de rigueur; there is interest in both spontaneous and evoked activity; and sophisticated artifact detection and removal methods are available. Improved head models for source estimation have also increased the precision of the current estimates, particularly for EEG and combined EEG/MEG. Because of their complementarity, more investigators are beginning to perform simultaneous EEG/MEG studies to gain more complete information about neural activity. Given the increase in methodological complexity in EEG/MEG, it is important to gather data that are of high quality and that are as artifact free as possible. Here, we discuss some issues in data acquisition and analysis of EEG and MEG data. Practical considerations for different types of EEG and MEG studies are also discussed.

  9. Sparse EEG/MEG source estimation via a group lasso.

    Directory of Open Access Journals (Sweden)

    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.

  10. Sparse EEG/MEG source estimation via a group lasso

    Science.gov (United States)

    Lim, Michael; Ales, Justin M.; Cottereau, Benoit R.; Hastie, Trevor

    2017-01-01

    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. PMID:28604790

  11. Negligible Motion Artifacts in Scalp Electroencephalography (EEG) During Treadmill Walking.

    Science.gov (United States)

    Nathan, Kevin; Contreras-Vidal, Jose L

    2015-01-01

    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.

  12. 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.

  13. Whole scalp resting state EEG of oscillatory brain activity shows no parametric relationship with psychoacoustic and psychosocial assessment of tinnitus: A repeated measures study.

    Science.gov (United States)

    Pierzycki, Robert H; McNamara, Adam J; Hoare, Derek J; Hall, Deborah A

    2016-01-01

    Tinnitus is a perception of sound that can occur in the absence of an external stimulus. A brief review of electroencephalography (EEG) and magnetoencephalography (MEG) literature demonstrates that there is no clear relationship between tinnitus presence and frequency band power in whole scalp or source oscillatory activity. Yet a preconception persists that such a relationship exists and that resting state EEG could be utilised as an outcome measure for clinical trials of tinnitus interventions, e.g. as a neurophysiological marker of therapeutic benefit. To address this issue, we first examined the test-retest correlation of EEG band power measures in tinnitus patients (n = 42). Second we examined the evidence for a parametric relationship between numerous commonly used tinnitus variables (psychoacoustic and psychosocial) and whole scalp EEG power spectra, directly and after applying factor reduction techniques. Test-retest correlation for both EEG band power measures and tinnitus variables were high. Yet we found no relationship between whole scalp EEG band powers and psychoacoustic or psychosocial variables. We conclude from these data that resting state whole scalp EEG should not be used as a biomarker for tinnitus and that greater caution should be exercised in regard to reporting of findings to avoid confirmation bias. The data was collected during a randomised controlled trial registered at ClinicalTrials.gov (Identifier: NCT01541969). Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

  14. Feedback solutions for low crosstalk in dense arrays of high-T c SQUIDs for on-scalp MEG

    Science.gov (United States)

    Ruffieux, S.; Xie, M.; Chukharkin, M.; Pfeiffer, C.; Kalabukhov, A.; Winkler, D.; Schneiderman, J. F.

    2017-05-01

    Magnetoencephalography (MEG) systems based on a dense array of high critical temperature (high-T c) superconducting quantum interference devices (SQUIDs) can theoretically outperform a state-of-the-art MEG system. On the way towards building such a multichannel system, we evaluate feedback methods suitable for use in dense high-T c SQUID arrays where the sensors are in very close proximity to the head (on-scalp MEG). We test on-chip superconducting coils and direct injection of the feedback current into the SQUID loop as alternatives to the wire-wound copper coils commonly used in single-channel high-T c SQUID-based MEG systems. For the evaluation, we have performed coupling, noise, and crosstalk measurements. We conclude that direct injection is the optimal solution for dense on-scalp MEG as it gives crosstalk below 0.5% even between SQUIDs whose pickup loops are within 0.8 mm of one another. Further, this solution provides sufficient flux coupling without adding additional noise. Finally, it does not compromise the standoff distance, which is important for on-scalp MEG.

  15. Simultaneous recording of MEG, EEG and intracerebral EEG during visual stimulation: from feasibility to single-trial analysis.

    Science.gov (United States)

    Dubarry, Anne-Sophie; Badier, Jean-Michel; Trébuchon-Da Fonseca, Agnès; Gavaret, Martine; Carron, Romain; Bartolomei, Fabrice; Liégeois-Chauvel, Catherine; Régis, Jean; Chauvel, Patrick; Alario, F-Xavier; Bénar, Christian-G

    2014-10-01

    Electroencephalography (EEG), magnetoencephalography (MEG), and intracerebral stereotaxic EEG (SEEG) are the three neurophysiological recording techniques, which are thought to capture the same type of brain activity. Still, the relationships between non-invasive (EEG, MEG) and invasive (SEEG) signals remain to be further investigated. In early attempts at comparing SEEG with either EEG or MEG, the recordings were performed separately for each modality. However such an approach presents substantial limitations in terms of signal analysis. The goal of this technical note is to investigate the feasibility of simultaneously recording these three signal modalities (EEG, MEG and SEEG), and to provide strategies for analyzing this new kind of data. Intracerebral electrodes were implanted in a patient with intractable epilepsy for presurgical evaluation purposes. This patient was presented with a visual stimulation paradigm while the three types of signals were simultaneously recorded. The analysis started with a characterization of the MEG artifact caused by the SEEG equipment. Next, the average evoked activities were computed at the sensor level, and cortical source activations were estimated for both the EEG and MEG recordings; these were shown to be compatible with the spatiotemporal dynamics of the SEEG signals. In the average time-frequency domain, concordant patterns between the MEG/EEG and SEEG recordings were found below the 40 Hz level. Finally, a fine-grained coupling between the amplitudes of the three recording modalities was detected in the time domain, at the level of single evoked responses. Importantly, these correlations have shown a high level of spatial and temporal specificity. These findings provide a case for the ability of trimodal recordings (EEG, MEG, and SEEG) to reach a greater level of specificity in the investigation of brain signals and functions. Copyright © 2014 Elsevier Inc. All rights reserved.

  16. 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.

  17. 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...

  18. Opportunities and methodological challenges in EEG and MEG resting state functional brain network research

    NARCIS (Netherlands)

    van Diessen, E; Numan, T; van Dellen, E; van der Kooi, A W; Boersma, M; Hofman, D; van Lutterveld, R; van Dijk, B W; van Straaten, E C W; Hillebrand, A; Stam, C J

    Electroencephalogram (EEG) and magnetoencephalogram (MEG) recordings during resting state are increasingly used to study functional connectivity and network topology. Moreover, the number of different analysis approaches is expanding along with the rising interest in this research area. The

  19. Added diagnostic value of magnetoencephalography (MEG) in patients suspected for epilepsy, where previous, extensive EEG workup was unrevealing

    DEFF Research Database (Denmark)

    Duez, Lene; Beniczky, Sándor; Tankisi, Hatice

    2016-01-01

    normal EEGs, including sleep-EEG, were prospectively analyzed. The reference standard was inferred from the diagnosis obtained from the medical charts, after at least one-year follow-up. MEG (306-channel, whole-head) and simultaneous EEG (MEG-EEG) was recorded for one hour. The added sensitivity of MEG......OBJECTIVE: To elucidate the possible additional diagnostic yield of MEG in the workup of patients with suspected epilepsy, where repeated EEGs, including sleep-recordings failed to identify abnormalities. METHODS: Fifty-two consecutive patients with clinical suspicion of epilepsy and at least three...

  20. Brainstorm: A User-Friendly Application for MEG/EEG Analysis

    Directory of Open Access Journals (Sweden)

    François Tadel

    2011-01-01

    Full Text Available Brainstorm is a collaborative open-source application dedicated to magnetoencephalography (MEG and electroencephalography (EEG data visualization and processing, with an emphasis on cortical source estimation techniques and their integration with anatomical magnetic resonance imaging (MRI data. The primary objective of the software is to connect MEG/EEG neuroscience investigators with both the best-established and cutting-edge methods through a simple and intuitive graphical user interface (GUI.

  1. MEG-tutkimuksen yhteydessä tehtävä EEG-elektrodien digitoinnin toistettavuus

    OpenAIRE

    Koponen, Miida; Kurkinen, Heidi; Vehola, Emmi

    2015-01-01

    Magnetoenkefalografiatutkimuksen (MEG) yhteydessä potilaalta mitataan elektroenkefalografia (EEG). Ohjelmistokehityksen myötä EEG:n mallinnus MEG-tutkimusten yhteydessä on avautumassa kliiniseen käyttöön, minkä takia myös EEG-mittauksen laadunvarmistukselle on tullut tarvetta. Ennen varsinaista tutkimusta suoritetaan EEG-elektrodien digitointi, jonka avulla potilaan päästä luodaan malli tietokoneelle kolmiulotteiseen koordinaatistoon. Opinnäytetyön tilaajana toimi Helsingin ja Uudenmaan s...

  2. Robust Detection of Dynamical Change in Scalp EEG

    Energy Technology Data Exchange (ETDEWEB)

    Gailey, P.C.; Hively, L.M.; Protopopescu, V.A.

    1999-06-28

    We present a robust, model-independent technique for measuring changes in the dynamics underlying nonlinear time-serial data. We define indicators of dynamical change by comparing distribution functions on the attractor via L{sub 1}-distance and X{sup 2} statistics. We apply the measures to scalp EEG data with the objective of capturing the transition between non-seizure and epileptic brain activity in a timely, accurate, and non-invasive manner. We find a clear superiority of the new metrics in comparison to traditional nonlinear measures as discriminators of dynamical change.

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

    DEFF Research Database (Denmark)

    Zibrandtsen, I. C.; Kidmose, Preben; Christensen, Christian Bech

    2017-01-01

    Objective 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. Methods 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...... 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...

  4. Measuring MEG closer to the brain: Performance of on-scalp sensor arrays.

    Science.gov (United States)

    Iivanainen, Joonas; Stenroos, Matti; Parkkonen, Lauri

    2017-02-15

    Optically-pumped magnetometers (OPMs) have recently reached sensitivity levels required for magnetoencephalography (MEG). OPMs do not need cryogenics and can thus be placed within millimetres from the scalp into an array that adapts to the individual head size and shape, thereby reducing the distance from cortical sources to the sensors. Here, we quantified the improvement in recording MEG with hypothetical on-scalp OPM arrays compared to a 306-channel state-of-the-art SQUID array (102 magnetometers and 204 planar gradiometers). We simulated OPM arrays that measured either normal (nOPM; 102 sensors), tangential (tOPM; 204 sensors), or all components (aOPM; 306 sensors) of the magnetic field. We built forward models based on magnetic resonance images of 10 adult heads; we employed a three-compartment boundary element model and distributed current dipoles evenly across the cortical mantle. Compared to the SQUID magnetometers, nOPM and tOPM yielded 7.5 and 5.3 times higher signal power, while the correlations between the field patterns of source dipoles were reduced by factors of 2.8 and 3.6, respectively. Values of the field-pattern correlations were similar across nOPM, tOPM and SQUID gradiometers. Volume currents reduced the signals of primary currents on average by 10%, 72% and 15% in nOPM, tOPM and SQUID magnetometers, respectively. The information capacities of the OPM arrays were clearly higher than that of the SQUID array. The dipole-localization accuracies of the arrays were similar while the minimum-norm-based point-spread functions were on average 2.4 and 2.5 times more spread for the SQUID array compared to nOPM and tOPM arrays, respectively. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  5. Beamformer Source Analysis and Connectivity on Concurrent EEG and MEG Data during Voluntary Movements

    Science.gov (United States)

    Muthuraman, Muthuraman; Hellriegel, Helge; Hoogenboom, Nienke; Anwar, Abdul Rauf; Mideksa, Kidist Gebremariam; Krause, Holger; Schnitzler, Alfons; Deuschl, Günther; Raethjen, Jan

    2014-01-01

    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. PMID:24618596

  6. 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.

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

    Science.gov (United States)

    Muthuraman, Muthuraman; Hellriegel, Helge; Hoogenboom, Nienke; Anwar, Abdul Rauf; Mideksa, Kidist Gebremariam; Krause, Holger; Schnitzler, Alfons; Deuschl, Günther; Raethjen, Jan

    2014-01-01

    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.

  8. Scanning Reduction Strategy in MEG/EEG Beamformer Source Imaging

    Directory of Open Access Journals (Sweden)

    Jun Hee Hong

    2012-01-01

    Full Text Available MEG/EEG beamformer source imaging is a promising approach which can easily address spatiotemporal multi-dipole problems without a priori information on the number of sources and is robust to noise. Despite such promise, beamformer generally has weakness which is degrading localization performance for correlated sources and is requiring of dense scanning for covering all possible interesting (entire source areas. Wide source space scanning yields all interesting area images, and it results in lengthy computation time. Therefore, an efficient source space scanning strategy would be beneficial in achieving accelerated beamformer source imaging. We propose a new strategy in computing beamformer to reduce scanning points and still maintain effective accuracy (good spatial resolution. This new strategy uses the distribution of correlation values between measurements and lead-field vectors. Scanning source points are chosen yielding higher RMS correlations than the predetermined correlation thresholds. We discuss how correlation thresholds depend on SNR and verify the feasibility and efficacy of our proposed strategy to improve the beamformer through numerical and empirical experiments. Our proposed strategy could in time accelerate the conventional beamformer up to over 40% without sacrificing spatial accuracy.

  9. 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.

  10. On the Keyhole Hypothesis: High Mutual Information between Ear and Scalp EEG

    Directory of Open Access Journals (Sweden)

    Kaare B. Mikkelsen

    2017-06-01

    Full Text Available 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 subjects exposed to a battery of stimuli, including alpha-attenuation, auditory onset, and mismatch-negativity responses and a new medium-long EEG experiment involving data acquisition during 13 h. Linear models were estimated to lower bound the scalp-to-ear capacity, i.e., predicting ear-EEG data from 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 show that the view—represented as a linear mapping—is stable across both time and mental states. Specifically, we find that ear-EEG data can be predicted reliably from scalp EEG. We also address the reverse view, and demonstrate that large portions of the scalp EEG can be predicted from ear-EEG, with the highest predictability achieved in the temporal regions and when using ear-EEG electrodes with a common reference electrode.

  11. 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.

  12. Accounting for linear transformations of EEG and MEG data in source analysis.

    Directory of Open Access Journals (Sweden)

    Joerg F Hipp

    Full Text Available Analyses of electro- and magnetoencephalography (EEG, MEG data often involve a linear modification of signals at the sensor level. Examples include re-referencing of the EEG, computation of synthetic gradiometer in MEG, or the removal of artifactual independent components to clean EEG and MEG data. A question of practical relevance is, if such modifications must be accounted for by adapting the physical forward model (leadfield before subsequent source analysis. Here, we show that two scenarios need to be differentiated. In the first scenario, which corresponds to re-referencing the EEG and synthetic gradiometer computation in MEG, the leadfield must be adapted before source analysis. In the second scenario, which corresponds to removing artifactual components to 'clean' the data, the leadfield must not be changed. We demonstrate and discuss the consequences of wrongly modifying the leadfield in the latter case for an example. Future EEG and MEG studies employing source analyses should carefully consider whether and, if so, how the leadfield must be modified as explicated here.

  13. The impact of EEG/MEG signal processing and modeling in the diagnostic and management of epilepsy

    NARCIS (Netherlands)

    Lopes da Silva, F.H.

    2008-01-01

    This overview covers recent advances in the field of EEG/MEG signal processing and modeling in epilepsy regarding both interictal and ictal phenomena. In the first part, the main methods used in the analysis of interictal EEG/MEG epileptiform spikes are presented and discussed. Source and volume

  14. 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.

  15. A new wavelet transform to sparsely represent cortical current densities for EEG/MEG inverse problems.

    Science.gov (United States)

    Liao, Ke; Zhu, Min; Ding, Lei

    2013-08-01

    The present study investigated the use of transform sparseness of cortical current density on human brain surface to improve electroencephalography/magnetoencephalography (EEG/MEG) inverse solutions. Transform sparseness was assessed by evaluating compressibility of cortical current densities in transform domains. To do that, a structure compression method from computer graphics was first adopted to compress cortical surface structure, either regular or irregular, into hierarchical multi-resolution meshes. Then, a new face-based wavelet method based on generated multi-resolution meshes was proposed to compress current density functions defined on cortical surfaces. Twelve cortical surface models were built by three EEG/MEG softwares and their structural compressibility was evaluated and compared by the proposed method. Monte Carlo simulations were implemented to evaluate the performance of the proposed wavelet method in compressing various cortical current density distributions as compared to other two available vertex-based wavelet methods. The present results indicate that the face-based wavelet method can achieve higher transform sparseness than vertex-based wavelet methods. Furthermore, basis functions from the face-based wavelet method have lower coherence against typical EEG and MEG measurement systems than vertex-based wavelet methods. Both high transform sparseness and low coherent measurements suggest that the proposed face-based wavelet method can improve the performance of L1-norm regularized EEG/MEG inverse solutions, which was further demonstrated in simulations and experimental setups using MEG data. Thus, this new transform on complicated cortical structure is promising to significantly advance EEG/MEG inverse source imaging technologies. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  16. A Active Micromachined Scalp Electrode Array for Eeg Signal Recording.

    Science.gov (United States)

    Alizadeh-Taheri, Babak

    This thesis describes the design, microfabrication, and testing of an active scalp EEG (electroencephalograph) electrode that has several distinct advantages over existing technologies. These advantages are: (1) no electrolyte used, (2) no skin preparation, (3) significantly reduced sensor size, and (4) compatibility with EEG monitoring systems. The active electrode array is an integrated system made of an array of capacitive sensors with local integrated circuitry housed in a package with batteries to power the circuitry. This level of integration was required to achieve the functional performance obtained by the electrode. The electrode consists of a silicon sensor substrate fabricated at UCD and a custom circuit substrate fabricated at Orbit Semiconductors, using a 2 μm analog CMOS technology. The circuitry was designed for low 1/f noise. One side of the sensor substrate holds four capacitive sensors with rm Si_3N _4 as the dielectric material. The opposite side holds aluminum pads for bonding to the circuit substrate. A via hole technology was developed to make electrical contact to both sides of the sensor substrate. The via holes are 200 μm square openings etched through the silicon by a reactive ion etching (RIE) process using an rm SF_6/O_2 gas mixture, oxidized, and then filled with sputtered aluminum for contacts through the substrate. The via holes have an aspect ratio of 2:1 (length of opening to depth of hole). Silicon RIE etch rates of up to 18 mu/hr were obtained under optimum conditions, using a 0.8 μm aluminum mask. The circuit and sensor substrates were bonded with silver adhesive, and wire bonding was used to make electrical contacts between the substrates. The two substrates were then integrated in a custom package for testing. The electrode was tested on an electrical test bench and on human subjects in four modalities of EEG activity, namely: (1) spontaneous EEG, (2) sensory event-related potentials, (3) brain stem potentials, and (4

  17. Dynamic causal modeling of evoked responses in EEG and MEG.

    Science.gov (United States)

    David, Olivier; Kiebel, Stefan J; Harrison, Lee M; Mattout, Jérémie; Kilner, James M; Friston, Karl J

    2006-05-01

    Neuronally plausible, generative or forward models are essential for understanding how event-related fields (ERFs) and potentials (ERPs) are generated. In this paper, we present a new approach to modeling event-related responses measured with EEG or MEG. This approach uses a biologically informed model to make inferences about the underlying neuronal networks generating responses. The approach can be regarded as a neurobiologically constrained source reconstruction scheme, in which the parameters of the reconstruction have an explicit neuronal interpretation. Specifically, these parameters encode, among other things, the coupling among sources and how that coupling depends upon stimulus attributes or experimental context. The basic idea is to supplement conventional electromagnetic forward models, of how sources are expressed in measurement space, with a model of how source activity is generated by neuronal dynamics. A single inversion of this extended forward model enables inference about both the spatial deployment of sources and the underlying neuronal architecture generating them. Critically, this inference covers long-range connections among well-defined neuronal subpopulations. In a previous paper, we simulated ERPs using a hierarchical neural-mass model that embodied bottom-up, top-down and lateral connections among remote regions. In this paper, we describe a Bayesian procedure to estimate the parameters of this model using empirical data. We demonstrate this procedure by characterizing the role of changes in cortico-cortical coupling, in the genesis of ERPs. In the first experiment, ERPs recorded during the perception of faces and houses were modeled as distinct cortical sources in the ventral visual pathway. Category-selectivity, as indexed by the face-selective N170, could be explained by category-specific differences in forward connections from sensory to higher areas in the ventral stream. We were able to quantify and make inferences about these

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

    Science.gov (United States)

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

    2015-01-01

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

  19. Performances among various common spatial pattern methods for simultaneous MEG/EEG data

    Science.gov (United States)

    Kang, S.; Ahn, M.; Jun, S. C.

    2010-01-01

    Brain Computer Interface (BCI) is a communication pathway between devices (computers) and the human brain. It treats brain signals in a real-time basis and deciphers some of what the human brain is doing to give us certain information. In this work, we develop the BCI system based on simultaneous electroencephalograph (EEG) and magnetoencephalography (MEG) using various preprocessing and feature extraction methods along with Fisher linear discriminant analysis (FLDA) classifier. Common spatial pattern (CSP) is a spatial filter whose spatially projected signal has maximum power for one class and minimum power for the other. Each single trial is computed by the variance in the time domain. We choose a proper number of patterns in order to make a feature vector. In this work, 6 CSP patterns, the first three and the last three ones are selected. A feature vector consists of 6 variances of each extracted CSP pattern from projected data. Among various CSP methods, we used normal common spatial patterns (CSP), invariant common spatial patterns (iCSP), and common spectral spatial patterns (CSSP) methods to measure the performances. Simultaneous MEG/EEG datasets (340 channels) for four subjects from Eleckta Vectorview system were digitally acquired at a 1 KHz and 8-30Hz bandpass filtered. Total 340 channels consist of three kinds of channel types such as 102 magnetometers, 204 gradiometers and 40 EEG electrodes. Three different modalities such as EEG-only, MEG-only, and simultaneous MEG and EEG were analyzed in order to study comparative BCI performances on three variants of CSP. Particularly, for simultaneous MEG/EEG data we proposed three different combination ways for BCI and their performances were discussed.

  20. A mathematical approach to the temporal stationarity of background noise in MEG/EEG measurements

    NARCIS (Netherlands)

    Mone-Bijma, F.; de Munck, J.C.; Huizenga, H.M.; Heethaar, R.M.

    2003-01-01

    The general spatiotemporal covariance matrix of the background noise in MEG/EEG signals is huge. To reduce the dimensionality of this matrix it is modeled as a Kronecker product of a spatial and a temporal covariance matrix. When the number of time samples is larger than, say, J = 500, the iterative

  1. 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

  2. The coupled dipole model: an integrated model for multiple MEG/EEG data sets

    NARCIS (Netherlands)

    Mone-Bijma, F.; de Munck, J.C.; Bocker, K.B.E.; Huizenga, H.M.; Heethaar, R.M.

    2004-01-01

    Often MEG/EEG is measured in a few slightly different conditions to investigate the functionality of the human brain. This kind of data sets show similarities, though are different for each condition. When solving the inverse problem (IP), performing the source localization, one encounters the

  3. Discrimination of emotional states from scalp- and intracranial EEG using multiscale Rényi entropy.

    Science.gov (United States)

    Tonoyan, Yelena; Chanwimalueang, Theerasak; Mandic, Danilo P; Van Hulle, Marc M

    2017-01-01

    A data-adaptive, multiscale version of Rényi's quadratic entropy (RQE) is introduced for emotional state discrimination from EEG recordings. The algorithm is applied to scalp EEG recordings of 30 participants watching 4 emotionally-charged video clips taken from a validated public database. Krippendorff's inter-rater statistic reveals that multiscale RQE of the mid-frontal scalp electrodes best discriminates between five emotional states. Multiscale RQE is also applied to joint scalp EEG, amygdala- and occipital pole intracranial recordings of an implanted patient watching a neutral and an emotionally charged video clip. Unlike for the neutral video clip, the RQEs of the mid-frontal scalp electrodes and the amygdala-implanted electrodes are observed to coincide in the time range where the crux of the emotionally-charged video clip is revealed. In addition, also during this time range, phase synchrony between the amygdala and mid-frontal recordings is maximal, as well as our 30 participants' inter-rater agreement on the same video clip. A source reconstruction exercise using intracranial recordings supports our assertion that amygdala could contribute to mid-frontal scalp EEG. On the contrary, no such contribution was observed for the occipital pole's intracranial recordings. Our results suggest that emotional states discriminated from mid-frontal scalp EEG are likely to be mirrored by differences in amygdala activations in particular when recorded in response to emotionally-charged scenes.

  4. Discrimination of emotional states from scalp- and intracranial EEG using multiscale Rényi entropy.

    Directory of Open Access Journals (Sweden)

    Yelena Tonoyan

    Full Text Available A data-adaptive, multiscale version of Rényi's quadratic entropy (RQE is introduced for emotional state discrimination from EEG recordings. The algorithm is applied to scalp EEG recordings of 30 participants watching 4 emotionally-charged video clips taken from a validated public database. Krippendorff's inter-rater statistic reveals that multiscale RQE of the mid-frontal scalp electrodes best discriminates between five emotional states. Multiscale RQE is also applied to joint scalp EEG, amygdala- and occipital pole intracranial recordings of an implanted patient watching a neutral and an emotionally charged video clip. Unlike for the neutral video clip, the RQEs of the mid-frontal scalp electrodes and the amygdala-implanted electrodes are observed to coincide in the time range where the crux of the emotionally-charged video clip is revealed. In addition, also during this time range, phase synchrony between the amygdala and mid-frontal recordings is maximal, as well as our 30 participants' inter-rater agreement on the same video clip. A source reconstruction exercise using intracranial recordings supports our assertion that amygdala could contribute to mid-frontal scalp EEG. On the contrary, no such contribution was observed for the occipital pole's intracranial recordings. Our results suggest that emotional states discriminated from mid-frontal scalp EEG are likely to be mirrored by differences in amygdala activations in particular when recorded in response to emotionally-charged scenes.

  5. Automatic and robust noise suppression in EEG and MEG: The SOUND algorithm.

    Science.gov (United States)

    Mutanen, Tuomas P; Metsomaa, Johanna; Liljander, Sara; Ilmoniemi, Risto J

    2018-02-01

    Electroencephalography (EEG) and magnetoencephalography (MEG) often suffer from noise- and artifact-contaminated channels and trials. Conventionally, EEG and MEG data are inspected visually and cleaned accordingly, e.g., by identifying and rejecting the so-called "bad" channels. This approach has several shortcomings: data inspection is laborious, the rejection criteria are subjective, and the process does not fully utilize all the information in the collected data. Here, we present noise-cleaning methods based on modeling the multi-sensor and multi-trial data. These approaches offer objective, automatic, and robust removal of noise and disturbances by taking into account the sensor- or trial-specific signal-to-noise ratios. We introduce a method called the source-estimate-utilizing noise-discarding algorithm (the SOUND algorithm). SOUND employs anatomical information of the head to cross-validate the data between the sensors. As a result, we are able to identify and suppress noise and artifacts in EEG and MEG. Furthermore, we discuss the theoretical background of SOUND and show that it is a special case of the well-known Wiener estimators. We explain how a completely data-driven Wiener estimator (DDWiener) can be used when no anatomical information is available. DDWiener is easily applicable to any linear multivariate problem; as a demonstrative example, we show how DDWiener can be utilized when estimating event-related EEG/MEG responses. We validated the performance of SOUND with simulations and by applying SOUND to multiple EEG and MEG datasets. SOUND considerably improved the data quality, exceeding the performance of the widely used channel-rejection and interpolation scheme. SOUND also helped in localizing the underlying neural activity by preventing noise from contaminating the source estimates. SOUND can be used to detect and reject noise in functional brain data, enabling improved identification of active brain areas. Copyright © 2017 Elsevier Inc. All

  6. 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.

  7. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  9. Influence of the head model on EEG and MEG source connectivity analyses.

    Science.gov (United States)

    Cho, Jae-Hyun; Vorwerk, Johannes; Wolters, Carsten H; Knösche, Thomas R

    2015-04-15

    The results of brain connectivity analysis using reconstructed source time courses derived from EEG and MEG data depend on a number of algorithmic choices. While previous studies have investigated the influence of the choice of source estimation method or connectivity measure, the effects of the head modeling errors or simplifications have not been studied sufficiently. In the present simulation study, we investigated the influence of particular properties of the head model on the reconstructed source time courses as well as on source connectivity analysis in EEG and MEG. Therefore, we constructed a realistic head model and applied the finite element method to solve the EEG and MEG forward problems. We considered the distinction between white and gray matter, the distinction between compact and spongy bone, the inclusion of a cerebrospinal fluid (CSF) compartment, and the reduction to a simple 3-layer model comprising only the skin, skull, and brain. Source time courses were reconstructed using a beamforming approach and the source connectivity was estimated by the imaginary coherence (ICoh) and the generalized partial directed coherence (GPDC). Our results show that in both EEG and MEG, neglecting the white and gray matter distinction or the CSF causes considerable errors in reconstructed source time courses and connectivity analysis, while the distinction between spongy and compact bone is just of minor relevance, provided that an adequate skull conductivity value is used. Large inverse and connectivity errors are found in the same regions that show large topography errors in the forward solution. Moreover, we demonstrate that the very conservative ICoh is relatively safe from the crosstalk effects caused by imperfect head models, as opposed to the GPDC. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  10. Insights Into the Therapeutic Effect of Responsive Neurostimulation Assessed With Scalp EEG Recording: A Case Report.

    Science.gov (United States)

    Bruzzone, Maria Jose; Issa, Naoum; Rose, Sandra; Warnke, Peter; Towle, Vernon L; Tao, James X; Wu, Shasha

    2017-10-10

    The responsive neurostimulation system (RNS) is the first closed-loop neurostimulator approved as an adjunctive treatment for adults with medically refractory focal epilepsy from no more than two seizure foci. In addition to its therapeutic effect, it provides chronic intracranial EEG recordings, with limited storage capacity. Long-term monitoring with scalp EEG recordings can provide additional information regarding seizure patterns, the efficacy of RNS stimulation in aborting individual seizures, and the net effect of RNS on seizure control. We present a 34-year-old woman with medically intractable right temporoparietal lobe epilepsy who failed two resective epilepsy surgeries and MR-guided laser interstitial thermal therapy (MRgLITT), after which RNS was implanted. Long-term scalp EEG performed 16 months after implantation showed continuous right hemisphere slowing and right temporal sharp waves. In addition, RNS stimulation produced bursts of high-voltage, broad-field, surface-negative activity, which allowed correlation of RNS stimulation with scalp EEG patterns. Twenty-seven seizures were captured. Responsive neurostimulation system stimulation did not abort any of the seizures recorded on the scalp EEG. However, the frequency of seizures doubled after RNS stimulation was discontinued and returned to baseline once it was turned back on. This observation supports the neuromodulation effect of RNS.

  11. Epileptic Seizure Prediction Using CSP and LDA for Scalp EEG Signals

    OpenAIRE

    Alotaiby, Turky N.; Saleh A. Alshebeili; Alotaibi, Faisal M.; Alrshoud, Saud R.

    2017-01-01

    This paper presents a patient-specific epileptic seizure predication method relying on the common spatial pattern- (CSP-) based feature extraction of scalp electroencephalogram (sEEG) signals. Multichannel EEG signals are traced and segmented into overlapping segments for both preictal and interictal intervals. The features extracted using CSP are used for training a linear discriminant analysis classifier, which is then employed in the testing phase. A leave-one-out cross-validation strategy...

  12. Mapping cortical dynamics using simultaneous MEG/EEG and anatomically-constrained minimum-norm estimates: an auditory attention example.

    Science.gov (United States)

    Lee, Adrian K C; Larson, Eric; Maddox, Ross K

    2012-10-24

    Magneto- and electroencephalography (MEG/EEG) are neuroimaging techniques that provide a high temporal resolution particularly suitable to investigate the cortical networks involved in dynamical perceptual and cognitive tasks, such as attending to different sounds in a cocktail party. Many past studies have employed data recorded at the sensor level only, i.e., the magnetic fields or the electric potentials recorded outside and on the scalp, and have usually focused on activity that is time-locked to the stimulus presentation. This type of event-related field / potential analysis is particularly useful when there are only a small number of distinct dipolar patterns that can be isolated and identified in space and time. Alternatively, by utilizing anatomical information, these distinct field patterns can be localized as current sources on the cortex. However, for a more sustained response that may not be time-locked to a specific stimulus (e.g., in preparation for listening to one of the two simultaneously presented spoken digits based on the cued auditory feature) or may be distributed across multiple spatial locations unknown a priori, the recruitment of a distributed cortical network may not be adequately captured by using a limited number of focal sources. Here, we describe a procedure that employs individual anatomical MRI data to establish a relationship between the sensor information and the dipole activation on the cortex through the use of minimum-norm estimates (MNE). This inverse imaging approach provides us a tool for distributed source analysis. For illustrative purposes, we will describe all procedures using FreeSurfer and MNE software, both freely available. We will summarize the MRI sequences and analysis steps required to produce a forward model that enables us to relate the expected field pattern caused by the dipoles distributed on the cortex onto the M/EEG sensors. Next, we will step through the necessary processes that facilitate us in denoising

  13. Performance of epileptic single-channel scalp EEG classifications using single wavelet-based features.

    Science.gov (United States)

    Janjarasjitt, Suparerk

    2017-03-01

    Classification of epileptic scalp EEGs are certainly ones of the most crucial tasks in diagnosis of epilepsy. Rather than using multiple quantitative features, a single quantitative feature of single-channel scalp EEG is applied for classifying its corresponding state of the brain, i.e., during seizure activity or non-seizure period. The quantitative features proposed are wavelet-based features obtained from the logarithm of variance of detail and approximation coefficients of single-channel scalp EEG signals. The performance on patient-dependent based epileptic seizure classifications using single wavelet-based features are examined on scalp EEG data of 12 children subjects containing 79 seizures. The 4-fold cross validation is applied to evaluate the performance on patient-dependent based epileptic seizure classifications using single wavelet-based features. From the computational results, it is shown that the wavelet-based features can provide an outstanding performance on patient-dependent based epileptic seizure classification. The average accuracy, sensitivity, and specificity of patient-dependent based epileptic seizure classification are, respectively, 93.24%, 83.34%, and 93.53%.

  14. Sparsity enables estimation of both subcortical and cortical activity from MEG and EEG.

    Science.gov (United States)

    Krishnaswamy, Pavitra; Obregon-Henao, Gabriel; Ahveninen, Jyrki; Khan, Sheraz; Babadi, Behtash; Iglesias, Juan Eugenio; Hämäläinen, Matti S; Purdon, Patrick L

    2017-11-14

    Subcortical structures play a critical role in brain function. However, options for assessing electrophysiological activity in these structures are limited. Electromagnetic fields generated by neuronal activity in subcortical structures can be recorded noninvasively, using magnetoencephalography (MEG) and electroencephalography (EEG). However, these subcortical signals are much weaker than those generated by cortical activity. In addition, we show here that it is difficult to resolve subcortical sources because distributed cortical activity can explain the MEG and EEG patterns generated by deep sources. We then demonstrate that if the cortical activity is spatially sparse, both cortical and subcortical sources can be resolved with M/EEG. Building on this insight, we develop a hierarchical sparse inverse solution for M/EEG. We assess the performance of this algorithm on realistic simulations and auditory evoked response data, and show that thalamic and brainstem sources can be correctly estimated in the presence of cortical activity. Our work provides alternative perspectives and tools for characterizing electrophysiological activity in subcortical structures in the human brain. Copyright © 2017 the Author(s). Published by PNAS.

  15. Predicting epileptic seizures from scalp EEG based on attractor state analysis.

    Science.gov (United States)

    Chu, Hyunho; Chung, Chun Kee; Jeong, Woorim; Cho, Kwang-Hyun

    2017-05-01

    Epilepsy is the second most common disease of the brain. Epilepsy makes it difficult for patients to live a normal life because it is difficult to predict when seizures will occur. In this regard, if seizures could be predicted a reasonable period of time before their occurrence, epilepsy patients could take precautions against them and improve their safety and quality of life. In this paper, we investigate a novel seizure precursor based on attractor state analysis for seizure prediction. We analyze the transition process from normal to seizure attractor state and investigate a precursor phenomenon seen before reaching the seizure attractor state. From the result of an analysis, we define a quantified spectral measure in scalp EEG for seizure prediction. From scalp EEG recordings, the Fourier coefficients of six EEG frequency bands are extracted, and the defined spectral measure is computed based on the coefficients for each half-overlapped 20-second-long window. The computed spectral measure is applied to seizure prediction using a low-complexity methodology. Within scalp EEG, we identified an early-warning indicator before an epileptic seizure occurs. Getting closer to the bifurcation point that triggers the transition from normal to seizure state, the power spectral density of low frequency bands of the perturbation of an attractor in the EEG, showed a relative increase. A low-complexity seizure prediction algorithm using this feature was evaluated, using ∼583h of scalp EEG in which 143 seizures in 16 patients were recorded. With the test dataset, the proposed method showed high sensitivity (86.67%) with a false prediction rate of 0.367h-1 and average prediction time of 45.3min. A novel seizure prediction method using scalp EEG, based on attractor state analysis, shows potential for application with real epilepsy patients. This is the first study in which the seizure-precursor phenomenon of an epileptic seizure is investigated based on attractor

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

    Science.gov (United States)

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

    2017-11-08

    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.

  17. Ictal high-frequency oscillations on scalp EEG recordings in symptomatic West syndrome.

    Science.gov (United States)

    Iwatani, Yoshiko; Kagitani-Shimono, Kuriko; Tominaga, Koji; Okinaga, Takeshi; Kishima, Haruhiko; Kato, Amami; Nagai, Toshisaburo; Ozono, Keiichi

    2012-11-01

    High-frequency oscillations (HFOs) on intracranial electroencephalography (EEG) recordings have been reported to be useful to identify the epileptogenic zone in intractable epilepsy. We investigated whether the ictal HFOs on scalp EEG seen during spasms contributed to identification of the epileptogenic zone in symptomatic West syndrome (S-WS). In S-WS, ictal scalp EEGs were recorded during a series of spasms. The HFOs associated with spasms were visualized in the temporally expanded EEG traces and subjected to time-frequency analysis. The results on the distribution of HFOs were compared with that of cortical lesions indicated by neuroimaging. In the 4 children examined, HFOs at 80-150 Hz preceded the clinical onsets of spasms. The maximum augmentation of these HFOs was larger than that of HFOs at 20-70 Hz. The regions of the maximum augmentation of HFOs at 80-150 Hz were identical to the lesions detected by neuroimaging. Two patients who underwent dissection of the area including the area with HFOs resulted in Engel class I. Ictal HFOs of spasms on scalp EEG showed a strong association with neuroimaging abnormalities presumed to be the epileptogenic zone in S-WS. Ictal HFOs can thus be a useful marker for exploring lesions for epilepsy surgery. Copyright © 2012 Elsevier B.V. All rights reserved.

  18. Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals.

    Science.gov (United States)

    Engemann, Denis A; Gramfort, Alexandre

    2015-03-01

    Magnetoencephalography and electroencephalography (M/EEG) measure non-invasively the weak electromagnetic fields induced by post-synaptic neural currents. The estimation of the spatial covariance of the signals recorded on M/EEG sensors is a building block of modern data analysis pipelines. Such covariance estimates are used in brain-computer interfaces (BCI) systems, in nearly all source localization methods for spatial whitening as well as for data covariance estimation in beamformers. The rationale for such models is that the signals can be modeled by a zero mean Gaussian distribution. While maximizing the Gaussian likelihood seems natural, it leads to a covariance estimate known as empirical covariance (EC). It turns out that the EC is a poor estimate of the true covariance when the number of samples is small. To address this issue the estimation needs to be regularized. The most common approach downweights off-diagonal coefficients, while more advanced regularization methods are based on shrinkage techniques or generative models with low rank assumptions: probabilistic PCA (PPCA) and factor analysis (FA). Using cross-validation all of these models can be tuned and compared based on Gaussian likelihood computed on unseen data. We investigated these models on simulations, one electroencephalography (EEG) dataset as well as magnetoencephalography (MEG) datasets from the most common MEG systems. First, our results demonstrate that different models can be the best, depending on the number of samples, heterogeneity of sensor types and noise properties. Second, we show that the models tuned by cross-validation are superior to models with hand-selected regularization. Hence, we propose an automated solution to the often overlooked problem of covariance estimation of M/EEG signals. The relevance of the procedure is demonstrated here for spatial whitening and source localization of MEG signals. Copyright © 2015 Elsevier Inc. All rights reserved.

  19. Guiding transcranial brain stimulation by EEG/MEG to interact with ongoing brain activity and associated functions: A position paper.

    Science.gov (United States)

    Thut, Gregor; Bergmann, Til Ole; Fröhlich, Flavio; Soekadar, Surjo R; Brittain, John-Stuart; Valero-Cabré, Antoni; Sack, Alexander T; Miniussi, Carlo; Antal, Andrea; Siebner, Hartwig Roman; Ziemann, Ulf; Herrmann, Christoph S

    2017-05-01

    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 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 to fluctuations in excitability states. Moreover, offline EEG/MEG recordings prior to interventions can inform researchers and clinicians how to stimulate: by frequency-tuning NTBS to the oscillation of interest, intrinsic brain oscillations can be up- or down-regulated. In this paper, we provide an overview of existing approaches and ideas of EEG/MEG-guided interventions, and their promises and caveats. We point out potential future lines of research to address challenges. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

  20. Interbrain phase synchronization during turn-taking verbal interaction-a hyperscanning study using simultaneous EEG/MEG.

    Science.gov (United States)

    Ahn, Sangtae; Cho, Hohyun; Kwon, Moonyoung; Kim, Kiwoong; Kwon, Hyukchan; Kim, Bong Soo; Chang, Won Seok; Chang, Jin Woo; Jun, Sung Chan

    2017-10-11

    Recently, neurophysiological findings about social interaction have been investigated widely, and hardware has been developed that can measure multiple subjects' brain activities simultaneously. These hyperscanning studies have enabled us to discover new and important evidences of interbrain interactions. Yet, very little is known about verbal interaction without any visual input. Therefore, we conducted a new hyperscanning study based on verbal, interbrain turn-taking interaction using simultaneous EEG/MEG, which measures rapidly changing brain activities. To establish turn-taking verbal interactions between a pair of subjects, we set up two EEG/MEG systems (19 and 146 channels of EEG and MEG, respectively) located ∼100 miles apart. Subjects engaged in verbal communication via condenser microphones and magnetic-compatible earphones, and a network time protocol synchronized the two systems. Ten subjects participated in this experiment and performed verbal interaction and noninteraction tasks separately. We found significant oscillations in EEG alpha and MEG alpha/gamma bands in several brain regions for all subjects. Furthermore, we estimated phase synchronization between two brains using the weighted phase lag index and found statistically significant synchronization in EEG and MEG data. Our novel paradigm and neurophysiological findings may foster a basic understanding of the functional mechanisms involved in human social interactions. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  1. Task modulation of brain responses in visual word recognition as studied using EEG/MEG and fMRI

    Directory of Open Access Journals (Sweden)

    Yuanyuan eChen

    2013-07-01

    Full Text Available Do task demands change the way we extract information from a stimulus, or only how we use this information for decision making? In order to answer this question for visual word recognition, we used EEG/MEG as well as fMRI to determine the latency ranges and spatial areas in which brain activation to words is modulated by task demands. We presented letter strings in three tasks (lexical decision, semantic decision, silent reading, and measured combined EEG/MEG as well as fMRI responses in two separate experiments. EEG/MEG sensor statistics revealed the earliest reliable task effects at around 150 ms, which were localized, using minimum norm estimates (MNE, to left inferior temporal, right anterior temporal and left precentral gyri. Later task effects (250 ms and 480 ms occurred in left middle and inferior temporal gyri. Our fMRI data showed task effects in left inferior frontal, posterior superior temporal and precentral cortices. Although there was some correspondence between fMRI and EEG/MEG localizations, discrepancies predominated. We suggest that fMRI may be less sensitive to the early short-lived processes revealed in our EEG/MEG data. Our results indicate that task-specific processes start to penetrate word recognition already at 150 ms, suggesting that early word processing is flexible and intertwined with decision making.

  2. Emotion classification using single-channel scalp-EEG recording.

    Science.gov (United States)

    Jalilifard, Amir; Brigante Pizzolato, Ednaldo; Kafiul Islam, Md

    2016-08-01

    Several studies have found evidence for corticolimbic Theta electroencephalographic (EEG) oscillation in the neural processing of visual stimuli perceived as fear or threatening scene. Recent studies showed that neural oscillations' patterns in Theta, Alpha, Beta and Gamma sub-bands play a main role in brain's emotional processing. The main goal of this study is to classify two different emotional states by means of EEG data recorded through a single-electrode EEG headset. Nineteen young subjects participated in an EEG experiment while watching a video clip that evoked three emotional states: neutral, relaxation and scary. Following each video clip, participants were asked to report on their subjective affect by giving a score between 0 to 10. First, recorded EEG data were preprocessed by stationary wavelet transform (SWT) based denoising to remove artifacts. Afterward, the distribution of power in time-frequency space was obtained using short-time Fourier transform (STFT) and then, the mean value of energy was calculated for each EEG sub-band. Finally, 46 features, as the mean energy of frequency bands between 4 and 50 Hz, containing 689 instances - for each subject -were collected in order to classify the emotional states. Our experimental results show that EEG dynamics induced by horror and relaxing movies can be classified with average classification rate of 92% using support vector machine (SVM) classifier. We also compared the performance of SVM to K-nearest neighbors (K-NN). The results show that K-NN achieves a better classification rate by 94% accuracy. The findings of this work are expected to pave the way to a new horizon in neuroscience by proving the point that only single-channel EEG data carry enough information for emotion classification.

  3. MEG and EEG data analysis with MNE-Python

    Directory of Open Access Journals (Sweden)

    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.

  4. Neural decoding of expressive human movement from scalp electroencephalography (EEG

    Directory of Open Access Journals (Sweden)

    Zachery Ryan Hernandez

    2014-04-01

    Full Text Available Although efforts to characterize human movement through EEG have revealed neural activities unique to limb control that can be used to infer movement kinematics, it is still unknown the extent to which EEG can be used to discern the expressive qualities that influence such movements. In this study we used EEG and inertial sensors to record brain activity and movement of five skilled and certified Laban Movement Analysis (LMA dancers. Each dancer performed whole body functional movements of three Action types: movements devoid of expressive qualities ('Neutral', non-expressive movements while thinking about specific expressive qualities ('Think’, and enacted expressive movements ('Do'. The expressive movement qualities that were used in the 'Think' and 'Do' actions consisted of a sequence of eight Laban Efforts as defined by LMA - a notation system and language for describing, visualizing, interpreting and documenting all varieties of human movement. We used delta band (0.2 – 4 Hz EEG as input to a machine learning algorithm that computed locality-preserving Fisher’s discriminant analysis (LFDA for dimensionality reduction followed by Gaussian mixture models (GMMs to decode the type of Action. We also trained our LFDA-GMM models to classify all the possible combinations of Action Type and Laban Effort (giving a total of 17 classes. Classification accuracy rates were 59.4 ± 0.6% for Action Type and 88.2 ± 0.7% for Laban Effort Type. Ancillary analyses of the potential relations between the EEG and movement kinematics of the dancer's body, indicated that motion-related artifacts did not significantly influence our classification results. In summary, this research demonstrates that EEG has valuable information about the expressive qualities of movement. These results may have applications for advancing the understanding of the neural basis of expressive movements and for the development of neuroprosthetics to restore movements.

  5. Neural decoding of expressive human movement from scalp electroencephalography (EEG)

    Science.gov (United States)

    Cruz-Garza, Jesus G.; Hernandez, Zachery R.; Nepaul, Sargoon; Bradley, Karen K.; Contreras-Vidal, Jose L.

    2014-01-01

    Although efforts to characterize human movement through electroencephalography (EEG) have revealed neural activities unique to limb control that can be used to infer movement kinematics, it is still unknown the extent to which EEG can be used to discern the expressive qualities that influence such movements. In this study we used EEG and inertial sensors to record brain activity and movement of five skilled and certified Laban Movement Analysis (LMA) dancers. Each dancer performed whole body movements of three Action types: movements devoid of expressive qualities (“Neutral”), non-expressive movements while thinking about specific expressive qualities (“Think”), and enacted expressive movements (“Do”). The expressive movement qualities that were used in the “Think” and “Do” actions consisted of a sequence of eight Laban Effort qualities as defined by LMA—a notation system and language for describing, visualizing, interpreting and documenting all varieties of human movement. We used delta band (0.2–4 Hz) EEG as input to a machine learning algorithm that computed locality-preserving Fisher's discriminant analysis (LFDA) for dimensionality reduction followed by Gaussian mixture models (GMMs) to decode the type of Action. We also trained our LFDA-GMM models to classify all the possible combinations of Action Type and Laban Effort quality (giving a total of 17 classes). Classification accuracy rates were 59.4 ± 0.6% for Action Type and 88.2 ± 0.7% for Laban Effort quality Type. Ancillary analyses of the potential relations between the EEG and movement kinematics of the dancer's body, indicated that motion-related artifacts did not significantly influence our classification results. In summary, this research demonstrates that EEG has valuable information about the expressive qualities of movement. These results may have applications for advancing the understanding of the neural basis of expressive movements and for the development of

  6. Neural decoding of expressive human movement from scalp electroencephalography (EEG).

    Science.gov (United States)

    Cruz-Garza, Jesus G; Hernandez, Zachery R; Nepaul, Sargoon; Bradley, Karen K; Contreras-Vidal, Jose L

    2014-01-01

    Although efforts to characterize human movement through electroencephalography (EEG) have revealed neural activities unique to limb control that can be used to infer movement kinematics, it is still unknown the extent to which EEG can be used to discern the expressive qualities that influence such movements. In this study we used EEG and inertial sensors to record brain activity and movement of five skilled and certified Laban Movement Analysis (LMA) dancers. Each dancer performed whole body movements of three Action types: movements devoid of expressive qualities ("Neutral"), non-expressive movements while thinking about specific expressive qualities ("Think"), and enacted expressive movements ("Do"). The expressive movement qualities that were used in the "Think" and "Do" actions consisted of a sequence of eight Laban Effort qualities as defined by LMA-a notation system and language for describing, visualizing, interpreting and documenting all varieties of human movement. We used delta band (0.2-4 Hz) EEG as input to a machine learning algorithm that computed locality-preserving Fisher's discriminant analysis (LFDA) for dimensionality reduction followed by Gaussian mixture models (GMMs) to decode the type of Action. We also trained our LFDA-GMM models to classify all the possible combinations of Action Type and Laban Effort quality (giving a total of 17 classes). Classification accuracy rates were 59.4 ± 0.6% for Action Type and 88.2 ± 0.7% for Laban Effort quality Type. Ancillary analyses of the potential relations between the EEG and movement kinematics of the dancer's body, indicated that motion-related artifacts did not significantly influence our classification results. In summary, this research demonstrates that EEG has valuable information about the expressive qualities of movement. These results may have applications for advancing the understanding of the neural basis of expressive movements and for the development of neuroprosthetics to restore

  7. Spike separation from EEG/MEG data using morphological filter and wavelet transform.

    Science.gov (United States)

    Jia, Wenyan; Sclabassi, Robert J; Pon, Lin-Sen; Scheuer, Mark L; Sun, Mingui

    2006-01-01

    In the analysis of epileptic electroencephalographic (EEG) and magnetoencephalography (MEG) data, spike separation is diagnostically important because localization of epileptic focus often depends on accurate extraction of spiky activity from the raw data. In this paper, we present a method to automatically extract spikes using the wavelet transform combined with morphological filtering based on a circular structuring element. Our experimental results have shown that this method is highly effective in spike separation. Comparisons with the wavelet, bandpass filter, empirical mode decomposition (EMD), and independent component analysis (ICA) methods show that the new method is more effective in estimating both spike amplitudes and locations.

  8. MEG and EEG demonstrate similar test-retest reliability of the 40Hz auditory steady-state response.

    Science.gov (United States)

    Legget, Kristina T; Hild, Allison K; Steinmetz, Sarah E; Simon, Steven T; Rojas, Donald C

    2017-04-01

    The auditory steady-state response (ASSR) is increasingly being used as a biomarker in neuropsychiatric disorders, but research investigating the test-retest reliability of this measure is needed. We previously reported ASSR reliability, measured by electroencephalography (EEG), to 40Hz amplitude-modulated white noise and click train stimuli. The purpose of the current study was to (a) assess the reliability of the MEG-measured ASSR to 40Hz amplitude-modulated white noise and click train stimuli, and (b) compare test-retest reliability between MEG and EEG measures of ASSR, which has not previously been investigated. Additionally, impact of stimulus parameter choice on reliability was assessed, by comparing responses to white noise and click train stimuli. Test-retest reliability, across sessions approximately one week apart, was assessed in 17 healthy adults. On each study day, participants completed two passive listening tasks (white noise and click train stimuli) during separate MEG and EEG recordings. Between-session correlations for evoked power and inter-trial phase coherence (ITPC) were assessed following source-space projection. Overall, the MEG-measured ASSR was significantly correlated between sessions (pnoise stimuli, although further study is warranted. No significant differences in reliability were observed between MEG and EEG measures, suggesting they are similarly reliable. This work supports use of the ASSR as a biomarker in clinical interventions with repeated measures. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Brain tumor detection using scalp eeg with modified Wavelet-ICA and multi layer feed forward neural network.

    Science.gov (United States)

    Selvam, V Salai; Shenbagadevi, S

    2011-01-01

    Use of scalp EEG for the diagnosis of various cerebral disorders is progressively increasing. Though the advanced neuroimaging techniques such as MRI and CT-SCAN still stay as principal confirmative methods for detecting and localizing brain tumors, the development of automated systems for the detection of brain tumors using the scalp EEG has started attracting the researchers all over the world notably since 2000. This is because of two important facts: (i) cheapness and easiness of methods of recording and analyzing the scalp EEG and (ii) lower risk and possible early detection. This paper presents a method of detecting the brain tumor using the first, second and third order statistics of the scalp EEG with a Modified Wavelet-Independent Component Analysis (MwICA) technique and a multi-layer feed-forward neural network.

  10. Concordance and discordance between PET images and foci of scalp EEG

    Energy Technology Data Exchange (ETDEWEB)

    Iinuma, Kazuie; Haginoya, Kazuhiro; Yanai, Kazuhiko (Tohoku Univ., Sendai (Japan). School of Medicine); Hatazawa, Jun; Ito, Masatoshi

    1989-09-01

    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.).

  11. Multimodal imaging of repetition priming: Using fMRI, MEG, and intracranial EEG to reveal spatiotemporal profiles of word processing

    Science.gov (United States)

    McDonald, Carrie R.; Thesen, Thomas; Carlson, Chad; Blumberg, Mark; Girard, Holly M.; Trongnetrpunya, Amy; Sherfey, Jason S.; Devinsky, Orrin; Kuzniecky, Rubin; Dolye, Werner K.; Cash, Sydney S.; Leonard, Matt K.; Hagler, Donald J.; Dale, Anders M.; Halgren, Eric

    2010-01-01

    Repetition priming is a core feature of memory processing whose anatomical correlates remain poorly understood. In this study, we use advanced multimodal imaging (functional magnetic resonance imaging (fMRI) and magnetoencephalography; MEG) to investigate the spatiotemporal profile of repetition priming. We use intracranial electroencephalography (iEEG) to validate our fMRI/MEG measurements. Twelve controls completed a semantic judgment task with fMRI and MEG that included words presented once (new, ‘N’) and words that repeated (old, ‘O’). Six patients with epilepsy completed the same task during iEEG recordings. Blood-oxygen level dependent (BOLD) responses for N vs O words were examined across the cortical surface and within regions of interest. MEG waveforms for N vs O words were estimated using a noise-normalized minimum norm solution, and used to interpret the timecourse of fMRI. Spatial concordance was observed between fMRI and MEG repetition effects from 350–450ms within bilateral occipitotemporal and medial temporal, left prefrontal, and left posterior temporal cortex. Additionally, MEG revealed widespread sources within left temporoparietal regions, whereas fMRI revealed bilateral reductions in occipitotemporal and left superior frontal, and increases in inferior parietal, precuneus, and dorsolateral prefrontal activity. BOLD suppression in left posterior temporal, left inferior prefrontal, and right occipitotemporal cortex correlated with MEG repetition-related reductions. IEEG responses from all three regions supported the timecourse of MEG and localization of fMRI. Furthermore, iEEG decreases to repeated words were associated with decreased gamma power in several regions, providing evidence that gamma oscillations are tightly coupled to cognitive phenomena and reflect regional activations seen in the BOLD signal. PMID:20620212

  12. Combining EEG and MEG for the reconstruction of epileptic activity using a calibrated realistic volume conductor model.

    Directory of Open Access Journals (Sweden)

    Ümit Aydin

    Full Text Available To increase the reliability for the non-invasive determination of the irritative zone in presurgical epilepsy diagnosis, we introduce here a new experimental and methodological source analysis pipeline that combines the complementary information in EEG and MEG, and apply it to data from a patient, suffering from refractory focal epilepsy. Skull conductivity parameters in a six compartment finite element head model with brain anisotropy, constructed from individual MRI data, are estimated in a calibration procedure using somatosensory evoked potential (SEP and field (SEF data. These data are measured in a single run before acquisition of further runs of spontaneous epileptic activity. Our results show that even for single interictal spikes, volume conduction effects dominate over noise and need to be taken into account for accurate source analysis. While cerebrospinal fluid and brain anisotropy influence both modalities, only EEG is sensitive to skull conductivity and conductivity calibration significantly reduces the difference in especially depth localization of both modalities, emphasizing its importance for combining EEG and MEG source analysis. On the other hand, localization differences which are due to the distinct sensitivity profiles of EEG and MEG persist. In case of a moderate error in skull conductivity, combined source analysis results can still profit from the different sensitivity profiles of EEG and MEG to accurately determine location, orientation and strength of the underlying sources. On the other side, significant errors in skull modeling are reflected in EEG reconstruction errors and could reduce the goodness of fit to combined datasets. For combined EEG and MEG source analysis, we therefore recommend calibrating skull conductivity using additionally acquired SEP/SEF data.

  13. Combining EEG and MEG for the reconstruction of epileptic activity using a calibrated realistic volume conductor model.

    Science.gov (United States)

    Aydin, Ümit; Vorwerk, Johannes; Küpper, Philipp; Heers, Marcel; Kugel, Harald; Galka, Andreas; Hamid, Laith; Wellmer, Jörg; Kellinghaus, Christoph; Rampp, Stefan; Wolters, Carsten Hermann

    2014-01-01

    To increase the reliability for the non-invasive determination of the irritative zone in presurgical epilepsy diagnosis, we introduce here a new experimental and methodological source analysis pipeline that combines the complementary information in EEG and MEG, and apply it to data from a patient, suffering from refractory focal epilepsy. Skull conductivity parameters in a six compartment finite element head model with brain anisotropy, constructed from individual MRI data, are estimated in a calibration procedure using somatosensory evoked potential (SEP) and field (SEF) data. These data are measured in a single run before acquisition of further runs of spontaneous epileptic activity. Our results show that even for single interictal spikes, volume conduction effects dominate over noise and need to be taken into account for accurate source analysis. While cerebrospinal fluid and brain anisotropy influence both modalities, only EEG is sensitive to skull conductivity and conductivity calibration significantly reduces the difference in especially depth localization of both modalities, emphasizing its importance for combining EEG and MEG source analysis. On the other hand, localization differences which are due to the distinct sensitivity profiles of EEG and MEG persist. In case of a moderate error in skull conductivity, combined source analysis results can still profit from the different sensitivity profiles of EEG and MEG to accurately determine location, orientation and strength of the underlying sources. On the other side, significant errors in skull modeling are reflected in EEG reconstruction errors and could reduce the goodness of fit to combined datasets. For combined EEG and MEG source analysis, we therefore recommend calibrating skull conductivity using additionally acquired SEP/SEF data.

  14. Combining EEG and MEG for the Reconstruction of Epileptic Activity Using a Calibrated Realistic Volume Conductor Model

    Science.gov (United States)

    Aydin, Ümit; Vorwerk, Johannes; Küpper, Philipp; Heers, Marcel; Kugel, Harald; Galka, Andreas; Hamid, Laith; Wellmer, Jörg; Kellinghaus, Christoph; Rampp, Stefan; Wolters, Carsten Hermann

    2014-01-01

    To increase the reliability for the non-invasive determination of the irritative zone in presurgical epilepsy diagnosis, we introduce here a new experimental and methodological source analysis pipeline that combines the complementary information in EEG and MEG, and apply it to data from a patient, suffering from refractory focal epilepsy. Skull conductivity parameters in a six compartment finite element head model with brain anisotropy, constructed from individual MRI data, are estimated in a calibration procedure using somatosensory evoked potential (SEP) and field (SEF) data. These data are measured in a single run before acquisition of further runs of spontaneous epileptic activity. Our results show that even for single interictal spikes, volume conduction effects dominate over noise and need to be taken into account for accurate source analysis. While cerebrospinal fluid and brain anisotropy influence both modalities, only EEG is sensitive to skull conductivity and conductivity calibration significantly reduces the difference in especially depth localization of both modalities, emphasizing its importance for combining EEG and MEG source analysis. On the other hand, localization differences which are due to the distinct sensitivity profiles of EEG and MEG persist. In case of a moderate error in skull conductivity, combined source analysis results can still profit from the different sensitivity profiles of EEG and MEG to accurately determine location, orientation and strength of the underlying sources. On the other side, significant errors in skull modeling are reflected in EEG reconstruction errors and could reduce the goodness of fit to combined datasets. For combined EEG and MEG source analysis, we therefore recommend calibrating skull conductivity using additionally acquired SEP/SEF data. PMID:24671208

  15. Human scalp recorded sigma activity is modulated by slow EEG oscillations during deep sleep.

    Science.gov (United States)

    Fell, Jürgen; Elfadil, Hakim; Röschke, Joachim; Burr, Wieland; Klaver, Peter; Elger, Christian E; Fernández, Guillén

    2002-07-01

    The EEG during deep sleep exhibits a distinct cortically generated slow oscillation of around and below 1 Hz which can be distinguished from other delta (0.5-3.5 Hz) activity. Intracranial studies showed that this slow oscillation triggers and groups cortical network firing. In the present study, we examined whether the phases of the slow oscillation during sleep stage 4 are correlated with the magnitude of sigma (12-16 Hz) and gamma (> 20 Hz) scalp activity. For this purpose, 10-min segments of uninterrupted stage 4 sleep EEG from 9 subjects were analyzed by applying wavelet techniques. We found that scalp recorded sigma, but not gamma, activity is modulated by the phases of the slow oscillation during deep sleep. Enhancement of sigma activity was observed to be triggered by the peak of the surface positive slow wave component, whereas reduction of sigma activity started around the peak of the negative component.

  16. Scalp and Source Power Topography in Sleepwalking and Sleep Terrors: A High-Density EEG Study.

    Science.gov (United States)

    Castelnovo, Anna; Riedner, Brady A; Smith, Richard F; Tononi, Giulio; Boly, Melanie; Benca, Ruth M

    2016-10-01

    To examine scalp and source power topography in sleep arousals disorders (SADs) using high-density EEG (hdEEG). Fifteen adult subjects with sleep arousal disorders (SADs) and 15 age- and gender-matched good sleeping healthy controls were recorded in a sleep laboratory setting using a 256 channel EEG system. Scalp EEG analysis of all night NREM sleep revealed a localized decrease in slow wave activity (SWA) power (1-4 Hz) over centro-parietal regions relative to the rest of the brain in SADs compared to good sleeping healthy controls. Source modelling analysis of 5-minute segments taken from N3 during the first half of the night revealed that the local decrease in SWA power was prominent at the level of the cingulate, motor, and sensori-motor associative cortices. Similar patterns were also evident during REM sleep and wake. These differences in local sleep were present in the absence of any detectable clinical or electrophysiological sign of arousal. Overall, results suggest the presence of local sleep differences in the brain of SADs patients during nights without clinical episodes. The persistence of similar topographical changes in local EEG power during REM sleep and wakefulness points to trait-like functional changes that cross the boundaries of NREM sleep. The regions identified by source imaging are consistent with the current neurophysiological understanding of SADs as a disorder caused by local arousals in motor and cingulate cortices. Persistent localized changes in neuronal excitability may predispose affected subjects to clinical episodes.

  17. 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.

  18. 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.

  19. Measuring time-varying information flow in scalp EEG signals: Orthogonalized partial directed coherence

    OpenAIRE

    Omidvarnia, Amir; Azemi, Ghasem; Boashash, Boualem; Otoole, John M.; Colditz, Paul B.; Vanhatalo, Sampsa

    2014-01-01

    This study aimed to develop a time-frequency method for measuring directional interactions over time and frequency from scalp-recorded electroencephalographic (EEG) signals in a way that is less affected by volume conduction and amplitude scaling. We modified the time-varying generalized partial directed coherence (tv-gPDC) method, by orthogonalization of the strictly causal multivariate autoregressive model coefficients, to minimize the effect of mutual sources. The novel measure, generalize...

  20. Scalp EEG acquisition in a low-noise environment: a quantitative assessment.

    Science.gov (United States)

    Zandi, Ali Shahidi; Dumont, Guy A; Yedlin, Matthew J; Lapeyrie, Philippe; Sudre, Christophe; Gaffet, Stéphane

    2011-08-01

    This pilot study investigates effects of an ultra shielded capsule at the low-noise underground laboratory (LSBB), Rustrel, France, when used to acquire scalp electroencephalogram (EEG). Analysis of EEG recordings from three volunteers confirms that clean EEG signals can be acquired in the LSBB capsule without the need for notch filtering. In addition, using different setups for acquiring EEG in the capsule, statistical analysis of power spectral densities based on a geodesic distance measure reveals that the laptop computer and patient module do not introduce any noise on recorded signals. Moreover, the current study shows that the backward counting task as a mental activity can be better detected using the EEG acquired in the capsule due to the higher level of â-band activities. The counting-relaxed â-band energy ratio is calculated using the S transform and compared between the hospital and capsule, revealing significantly higher values in the capsule (p EEG studies, including establishing novel low-noise EEG benchmarks.

  1. White Matter Connectivity Pattern Associate with Characteristics of Scalp EEG Signals.

    Science.gov (United States)

    Gong, Jinnan; Luo, Cheng; Chang, Xuebin; Zhang, Rui; Klugah-Brown, Benjamin; Guo, Lanjin; Xu, Peng; Yao, Dezhong

    2017-11-01

    The rhythm of electroencephalogram (EEG) depends on the neuroanatomical-based parameters such as white matter (WM) connectivity. However, the impacts of these parameters on the specific characteristics of EEG have not been clearly understood. Previous studies demonstrated that, these parameters contribute the inter-subject differences of EEG during performance of specific task such as motor imagery (MI). Though researchers have worked on this phenomenon, the idea is yet to be understood in terms of the mechanism that underlies such differences. Here, to tackle this issue, we began our investigations by first examining the structural features related to scalp EEG characteristics, which are event-related desynchronizations (ERDs), during MI using diffusion MRI. Twenty-four right-handed subjects were recruited to accomplish MI tasks and MRI scans. Based on the high spatial resolution of the structural and diffusion images, the motor-related WM links, such as basal ganglia (BG)-primary somatosensory cortex (SM1) pathway and supplementary motor area (SMA)-SM1 connection, were reconstructed by using probabilistic white matter tractography. Subsequently, the relationships of WM characteristics with EEG signals were investigated. These analyses demonstrated that WM pathway characteristics, including the connectivity strength and the positional characteristics of WM connectivity on SM1 (defined by the gyrus-sulcus ratio of connectivity, GSR), have a significant impact on ERDs when doing MI. Interestingly, the high GSR of WM connections between SM1 and BG were linked to the better ERDs. These results therefore, indicated that the connectivity in the gyrus of SM1 interacted with MI network which played the critical role for the scalp EEG signal extraction of MI to a great extent. The study provided the coupling mechanism between structural and dynamic physiological features of human brain, which would also contribute to understanding individual differences of EEG in MI

  2. A maximum-likelihood estimator for trial-to-trial variations in noisy MEG/EEG data sets

    NARCIS (Netherlands)

    de Munck, J.C.; Mone-Bijma, F.; Gaura, P.; Sieluzycki, C.A.; Branco, M.I.; Heethaar, R.M.

    2004-01-01

    The standard procedure to determine the brain response from a multitrial evoked magnetoencephalography (MEG) of electroencephalography (EEG) data set is to average the individual trials of these data, time locked to the stimulus onset. When the brain responses vary from trial-to-trial this approach

  3. 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

    it reduces the artifacts interfering with the signal. However, ICA also adds noise, or correction errors, to the waveform when the signal-to-noise ratio (SNR) in the original data is relatively low—in particular to EEG and to MEG magnetometer data. In conclusion, ICA is recommended over SSP, but one should...

  4. Paradoxical lateralization of parasagittal spikes revealed by back averaging of EEG and MEG in a case with epilepsia partialis continua.

    Science.gov (United States)

    Oishi, Ayame; Tobimatsu, Shozo; Ochi, Hirofumi; Ohyagi, Yasumasa; Kubota, Takamichi; Taniwaki, Takayuki; Yamamoto, Tomoya; Furuya, Hirokazu; Kira, Jun-ichi

    2002-01-15

    Our aim was to localize the generator site of parasagittal epileptiform discharges in a patient with epilepsia partialis continua (EPC) in the right leg. We examined a 32-year-old woman with EPC whose conventional EEG did not show any epileptic discharge. We performed the jerk-locked back averaging (JLA) of EEG and magnetoencephalography (MEG) to localize the dipole source of sharp transients. The myoclonic discharges in the right soleus muscle were used as a trigger pulse. JLA revealed consistent EEG and MEG sharp transients that coincided consistently and constantly preceded the myoclonic jerks. JLA of EEG demonstrated sharp waves paradoxically distributed over the vertex and right hemisphere. However, the estimated dipoles of MEG were localized in a restricted area in the primary leg motor area in the left hemisphere, which was closely located in the abnormal lesion on the brain MRI. JLA of MEG is considered to be a useful non-invasive method for localizing the epileptogenic area in EPC even when paradoxical lateralization of electroencephalographic discharges was noted.

  5. When EMG contamination does not necessarily hide high-frequency EEG: scalp electrical recordings before and after Dysport injections.

    Science.gov (United States)

    Boytsova, Julia A; Danko, Sergey G; Medvedev, Svyatoslav V

    2016-11-01

    The main aim of the present study was to investigate effects of partial reductions of electromyogram (EMG) on high-frequency scalp electroencephalogram (EEG) at rest and during performance of certain cognitive tasks. Nineteen healthy women performed the same cognitive tasks before and after cosmetic injections of Dysport in certain sites of facial muscles. Scalp EEG and EMG were recorded. Impact of Dysport injections on changes of spectral power in β2 and low γ frequency ranges (18-40 Hz) in EEG and EMG derivations was investigated. Also changes of spectral power in EEG and EMG derivations during comparisons of different cognitive states were calculated before and after Dysport injections separately. Dysport injections led to EMG decreases in facial muscles around the injection zones and also led to reductions of power of electric processes in scalp derivations. Along with it results of EEG power comparisons between the pairs of the cognitive states were qualitatively similar before and after Dysport injections. These facts to all appearance demonstrate that though scalp EEGs in the range above 15-40 Hz are contaminated by EMG, in certain experimental situations EMG contamination does not preclude qualitative detections of electroencephalographic correlates of mental activities in β2 and low γ frequency ranges. Parallel EEG and EMG registrations can help not to overestimate EMG contamination in psychophysiological EEG studies.

  6. Epileptic seizure classifications of single-channel scalp EEG data using wavelet-based features and SVM.

    Science.gov (United States)

    Janjarasjitt, Suparerk

    2017-02-13

    In this study, wavelet-based features of single-channel scalp EEGs recorded from subjects with intractable seizure are examined for epileptic seizure classification. The wavelet-based features extracted from scalp EEGs are simply based on detail and approximation coefficients obtained from the discrete wavelet transform. Support vector machine (SVM), one of the most commonly used classifiers, is applied to classify vectors of wavelet-based features of scalp EEGs into either seizure or non-seizure class. In patient-based epileptic seizure classification, a training data set used to train SVM classifiers is composed of wavelet-based features of scalp EEGs corresponding to the first epileptic seizure event. Overall, the excellent performance on patient-dependent epileptic seizure classification is obtained with the average accuracy, sensitivity, and specificity of, respectively, 0.9687, 0.7299, and 0.9813. The vector composed of two wavelet-based features of scalp EEGs provide the best performance on patient-dependent epileptic seizure classification in most cases, i.e., 19 cases out of 24. The wavelet-based features corresponding to the 32-64, 8-16, and 4-8 Hz subbands of scalp EEGs are the mostly used features providing the best performance on patient-dependent classification. Furthermore, the performance on both patient-dependent and patient-independent epileptic seizure classifications are also validated using tenfold cross-validation. From the patient-independent epileptic seizure classification validated using tenfold cross-validation, it is shown that the best classification performance is achieved using the wavelet-based features corresponding to the 64-128 and 4-8 Hz subbands of scalp EEGs.

  7. 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

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

    Science.gov (United States)

    O'Reilly, Christian; Lewis, John D; Elsabbagh, Mayada

    2017-01-01

    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 reported

  9. 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.

  10. Musical experience, plasticity, and maturation: issues in measuring developmental change using EEG and MEG.

    Science.gov (United States)

    Trainor, Laurel J

    2012-04-01

    The neuroscientific study of musical behavior has become a significant field of research during the last decade, and reports of this research in the popular press have caught the imagination of the public. This enterprise has also made it evident that studying the development of musical behavior can make a significant contribution to important questions in the field, such as the evolutionary origins of music, cross-cultural similarity and diversity, the effects of experience on musical processing, and relations between music and other domains. Studying musical development brings a unique set of methodological issues. We discuss a select set of these related to measurement of the electroencephalogram (EEG) and magnetoencephalogram (MEG). We use specific examples from our laboratory to illustrate the types of questions that can be answered with different data analysis techniques. © 2012 New York Academy of Sciences.

  11. FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data

    Directory of Open Access Journals (Sweden)

    Robert Oostenveld

    2011-01-01

    Full Text Available 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.

  12. 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.

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

    Science.gov (United States)

    Larson, Eric; Taulu, Samu

    2017-07-31

    Here we review the theory of suppression of spatially uncorrelated, sensor-specific noise in electro- and magento-encephalography (EEG and MEG) arrays, and introduce a novel method for suppression. Our method requires only that the signals of interest are spatially oversampled by the sensor array, 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 efficiently optimizes noise suppression performance while controlling for spatial bias of the signal of interest. 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 trade-off between noise suppression and adaptation to time-varying sensor characteristics. This is important in applications where sensor noise significantly limits the signal-to-noise ratio, such as high-frequency brain oscillations.

  14. 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.

  15. Epileptic Seizure Prediction Using CSP and LDA for Scalp EEG Signals

    Directory of Open Access Journals (Sweden)

    Turky N. Alotaiby

    2017-01-01

    Full Text Available This paper presents a patient-specific epileptic seizure predication method relying on the common spatial pattern- (CSP- based feature extraction of scalp electroencephalogram (sEEG signals. Multichannel EEG signals are traced and segmented into overlapping segments for both preictal and interictal intervals. The features extracted using CSP are used for training a linear discriminant analysis classifier, which is then employed in the testing phase. A leave-one-out cross-validation strategy is adopted in the experiments. The experimental results for seizure prediction obtained from the records of 24 patients from the CHB-MIT database reveal that the proposed predictor can achieve an average sensitivity of 0.89, an average false prediction rate of 0.39, and an average prediction time of 68.71 minutes using a 120-minute prediction horizon.

  16. 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.

  17. A Comparative Study on the Detection of Covert Attention in Event-Related EEG and MEG Signals to Control a BCI

    Directory of Open Access Journals (Sweden)

    Christoph Reichert

    2017-10-01

    Full Text Available In brain-computer interface (BCI applications the detection of neural processing as revealed by event-related potentials (ERPs is a frequently used approach to regain communication for people unable to interact through any peripheral muscle control. However, the commonly used electroencephalography (EEG provides signals of low signal-to-noise ratio, making the systems slow and inaccurate. As an alternative noninvasive recording technique, the magnetoencephalography (MEG could provide more advantageous electrophysiological signals due to a higher number of sensors and the magnetic fields not being influenced by volume conduction. We investigated whether MEG provides higher accuracy in detecting event-related fields (ERFs compared to detecting ERPs in simultaneously recorded EEG, both evoked by a covert attention task, and whether a combination of the modalities is advantageous. In our approach, a detection algorithm based on spatial filtering is used to identify ERP/ERF components in a data-driven manner. We found that MEG achieves higher decoding accuracy (DA compared to EEG and that the combination of both further improves the performance significantly. However, MEG data showed poor performance in cross-subject classification, indicating that the algorithm's ability for transfer learning across subjects is better in EEG. Here we show that BCI control by covert attention is feasible with EEG and MEG using a data-driven spatial filter approach with a clear advantage of the MEG regarding DA but with a better transfer learning in EEG.

  18. A Comparative Study on the Detection of Covert Attention in Event-Related EEG and MEG Signals to Control a BCI.

    Science.gov (United States)

    Reichert, Christoph; Dürschmid, Stefan; Heinze, Hans-Jochen; Hinrichs, Hermann

    2017-01-01

    In brain-computer interface (BCI) applications the detection of neural processing as revealed by event-related potentials (ERPs) is a frequently used approach to regain communication for people unable to interact through any peripheral muscle control. However, the commonly used electroencephalography (EEG) provides signals of low signal-to-noise ratio, making the systems slow and inaccurate. As an alternative noninvasive recording technique, the magnetoencephalography (MEG) could provide more advantageous electrophysiological signals due to a higher number of sensors and the magnetic fields not being influenced by volume conduction. We investigated whether MEG provides higher accuracy in detecting event-related fields (ERFs) compared to detecting ERPs in simultaneously recorded EEG, both evoked by a covert attention task, and whether a combination of the modalities is advantageous. In our approach, a detection algorithm based on spatial filtering is used to identify ERP/ERF components in a data-driven manner. We found that MEG achieves higher decoding accuracy (DA) compared to EEG and that the combination of both further improves the performance significantly. However, MEG data showed poor performance in cross-subject classification, indicating that the algorithm's ability for transfer learning across subjects is better in EEG. Here we show that BCI control by covert attention is feasible with EEG and MEG using a data-driven spatial filter approach with a clear advantage of the MEG regarding DA but with a better transfer learning in EEG.

  19. 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.

  20. Distinct Somatic Discrimination Reflected by Laser-Evoked Potentials Using Scalp EEG Leads.

    Science.gov (United States)

    Hsueh, Jen-Jui; Chen, Jia-Jin Jason; Shaw, Fu-Zen

    Discrimination is an important function in pain processing of the somatic cortex. The involvement of the somatic cortex has been studied using equivalent dipole analysis and neuroimaging, but the results are inconsistent. Scalp electroencephalography (EEG) can reflect functional changes of particular brain regions underneath a lead. However, the responses of EEG leads close to the somatic cortex in response to pain have not been systematically evaluated. The present study applied CO2 laser stimulation to the dorsum of the left hand. Laser-evoked potentials (LEPs) of C4, T3, and T4 leads and pain ratings in response to four stimulus intensities were analyzed. LEPs started earlier at the C4 and T4 leads. The onset latency and peak latency of LEPs for C4 and T4 leads were the same. Only 10 of 22 subjects (45 %) presented equivalent current dipoles within the primary somatosensory or motor cortices. LEP amplitudes of these leads increased as stimulation intensity increased. The stimulus-response pattern of the C4 lead was highly correlated with pain rating. In contrast, an S-shaped stimulus-response curve was obtained for the T3 and T4 leads. The present study provides supporting evidence that particular scalp channels are able to reflect the functional characteristics of their underlying cortical areas. Our data strengthen the clinical application of somatic-cortex-related leads for pain discrimination.

  1. 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.

  2. A robust adaptive denoising framework for real-time artifact removal in scalp EEG measurements

    Science.gov (United States)

    Kilicarslan, Atilla; Grossman, Robert G.; Contreras-Vidal, Jose Luis

    2016-04-01

    Objective. Non-invasive measurement of human neural activity based on the scalp electroencephalogram (EEG) allows for the development of biomedical devices that interface with the nervous system for scientific, diagnostic, therapeutic, or restorative purposes. However, EEG recordings are often considered as prone to physiological and non-physiological artifacts of different types and frequency characteristics. Among them, ocular artifacts and signal drifts represent major sources of EEG contamination, particularly in real-time closed-loop brain-machine interface (BMI) applications, which require effective handling of these artifacts across sessions and in natural settings. Approach. We extend the usage of a robust adaptive noise cancelling (ANC) scheme ({H}∞ filtering) for removal of eye blinks, eye motions, amplitude drifts and recording biases simultaneously. We also characterize the volume conduction, by estimating the signal propagation levels across all EEG scalp recording areas due to ocular artifact generators. We find that the amplitude and spatial distribution of ocular artifacts vary greatly depending on the electrode location. Therefore, fixed filtering parameters for all recording areas would naturally hinder the true overall performance of an ANC scheme for artifact removal. We treat each electrode as a separate sub-system to be filtered, and without the loss of generality, they are assumed to be uncorrelated and uncoupled. Main results. Our results show over 95-99.9% correlation between the raw and processed signals at non-ocular artifact regions, and depending on the contamination profile, 40-70% correlation when ocular artifacts are dominant. We also compare our results with the offline independent component analysis and artifact subspace reconstruction methods, and show that some local quantities are handled better by our sample-adaptive real-time framework. Decoding performance is also compared with multi-day experimental data from 2 subjects

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

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    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.

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

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    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.

  5. Multi-modal causality analysis of eyes-open and eyes-closed data from simultaneously recorded EEG and MEG.

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    Anwar, Abdul Rauf; Mideska, Kidist Gebremariam; Hellriegel, Helge; Hoogenboom, Nienke; Krause, Holger; Schnitzler, Alfons; Deuschl, Günther; Raethjen, Jan; Heute, Ulrich; Muthuraman, Muthuraman

    2014-01-01

    Owing to the recent advances in multi-modal data analysis, the aim of the present study was to analyze the functional network of the brain which remained the same during the eyes-open (EO) and eyes-closed (EC) resting task. The simultaneously recorded electroencephalogram (EEG) and magnetoencephalogram (MEG) were used for this study, recorded from five distinct cortical regions of the brain. We focused on the 'alpha' functional network, corresponding to the individual peak frequency in the alpha band. The total data set of 120 seconds was divided into three segments of 18 seconds each, taken from start, middle, and end of the recording. This segmentation allowed us to analyze the evolution of the underlying functional network. The method of time-resolved partial directed coherence (tPDC) was used to assess the causality. This method allowed us to focus on the individual peak frequency in the 'alpha' band (7-13 Hz). Because of the significantly higher power in the recorded EEG in comparison to MEG, at the individual peak frequency of the alpha band, results rely only on EEG. The MEG was used only for comparison. Our results show that different regions of the brain start to `disconnect' from one another over the course of time. The driving signals, along with the feedback signals between different cortical regions start to recede over time. This shows that, with the course of rest, brain regions reduce communication with each another.

  6. The use of single bipolar scalp derivation for the detection of ictal events during long-term EEG monitoring.

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    Bennis, Frank C; Geertsema, Evelien E; Velis, Demetrios N; Reus, Elise Em; Visser, Gerhard H

    2017-09-01

    Epilepsy is difficult to diagnose using routine EEG recordings of short duration in patients who have low seizure frequency. Long-term EEG may be useful but is impractical in an out-of-hospital setting. We investigated whether single-channel scalp EEG placed behind the earlobe is suitable for seizure identification during prolonged EEG monitoring. Scalp EEG samples were selected from subjects over 15 years of age, and comprised two segments of either background followed by seizure or background followed by background. Bipolar EEG derivations in three directions (F8-T8, C4-T8 and T8-P8) were evaluated for the presence of a seizure by two experienced reviewers. For each EEG segment containing a seizure, one pair of electrodes was oriented towards the suspected region of seizure onset, while two pairs of electrodes were oriented elsewhere. The EEG data contained five frontally localized seizures, five parietal, five temporal, two occipital, and four primary or secondary generalized seizures. The sensitivity and specificity for recognition of seizures was 86% and 95% for Reviewer 1, and 79% and 99% for Reviewer 2, respectively. When identifying a seizure with the lead orientation towards the region of seizure onset, both reviewers identified 20 out of 21 seizures (95%). When the lead was not oriented towards the region of seizure onset, the reviewers identified 34 and 30 out of 42 ictal records correctly, respectively. These results suggest that it is possible to identify epileptic seizures by bipolar EEG derivation using only two scalp electrodes. Lead orientation towards the suspected region of seizure onset is important for optimal detection sensitivity.

  7. Localizing true brain interactions from EEG and MEG data with subspace methods and modified beamformers.

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    Shahbazi Avarvand, Forooz; Ewald, Arne; Nolte, Guido

    2012-01-01

    To address the problem of mixing in EEG or MEG connectivity analysis we exploit that noninteracting brain sources do not contribute systematically to the imaginary part of the cross-spectrum. Firstly, we propose to apply the existing subspace method "RAP-MUSIC" to the subspace found from the dominant singular vectors of the imaginary part of the cross-spectrum rather than to the conventionally used covariance matrix. Secondly, to estimate the specific sources interacting with each other, we use a modified LCMV-beamformer approach in which the source direction for each voxel was determined by maximizing the imaginary coherence with respect to a given reference. These two methods are applicable in this form only if the number of interacting sources is even, because odd-dimensional subspaces collapse to even-dimensional ones. Simulations show that (a) RAP-MUSIC based on the imaginary part of the cross-spectrum accurately finds the correct source locations, that (b) conventional RAP-MUSIC fails to do so since it is highly influenced by noninteracting sources, and that (c) the second method correctly identifies those sources which are interacting with the reference. The methods are also applied to real data for a motor paradigm, resulting in the localization of four interacting sources presumably in sensory-motor areas.

  8. Localizing True Brain Interactions from EEG and MEG Data with Subspace Methods and Modified Beamformers

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    Forooz Shahbazi Avarvand

    2012-01-01

    Full Text Available To address the problem of mixing in EEG or MEG connectivity analysis we exploit that noninteracting brain sources do not contribute systematically to the imaginary part of the cross-spectrum. Firstly, we propose to apply the existing subspace method “RAP-MUSIC” to the subspace found from the dominant singular vectors of the imaginary part of the cross-spectrum rather than to the conventionally used covariance matrix. Secondly, to estimate the specific sources interacting with each other, we use a modified LCMV-beamformer approach in which the source direction for each voxel was determined by maximizing the imaginary coherence with respect to a given reference. These two methods are applicable in this form only if the number of interacting sources is even, because odd-dimensional subspaces collapse to even-dimensional ones. Simulations show that (a RAP-MUSIC based on the imaginary part of the cross-spectrum accurately finds the correct source locations, that (b conventional RAP-MUSIC fails to do so since it is highly influenced by noninteracting sources, and that (c the second method correctly identifies those sources which are interacting with the reference. The methods are also applied to real data for a motor paradigm, resulting in the localization of four interacting sources presumably in sensory-motor areas.

  9. Harmony: EEG/MEG linear inverse source reconstruction in the anatomical basis of spherical harmonics.

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    Yury Petrov

    Full Text Available EEG/MEG source localization based on a "distributed solution" is severely underdetermined, because the number of sources is much larger than the number of measurements. In particular, this makes the solution strongly affected by sensor noise. A new way to constrain the problem is presented. By using the anatomical basis of spherical harmonics (or spherical splines instead of single dipoles the dimensionality of the inverse solution is greatly reduced without sacrificing the quality of the data fit. The smoothness of the resulting solution reduces the surface bias and scatter of the sources (incoherency compared to the popular minimum-norm algorithms where single-dipole basis is used (MNE, depth-weighted MNE, dSPM, sLORETA, LORETA, IBF and allows to efficiently reduce the effect of sensor noise. This approach, termed Harmony, performed well when applied to experimental data (two exemplars of early evoked potentials and showed better localization precision and solution coherence than the other tested algorithms when applied to realistically simulated data.

  10. Delving into α-stable distribution in noise suppression for seizure detection from scalp EEG

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    Wang, Yueming; Qi, Yu; Wang, Yiwen; Lei, Zhen; Zheng, Xiaoxiang; Pan, Gang

    2016-10-01

    Objective. There is serious noise in EEG caused by eye blink and muscle activities. The noise exhibits similar morphologies to epileptic seizure signals, leading to relatively high false alarms in most existing seizure detection methods. The objective in this paper is to develop an effective noise suppression method in seizure detection and explore the reason why it works. Approach. Based on a state-space model containing a non-linear observation function and multiple features as the observations, this paper delves deeply into the effect of the α-stable distribution in the noise suppression for seizure detection from scalp EEG. Compared with the Gaussian distribution, the α-stable distribution is asymmetric and has relatively heavy tails. These properties make it more powerful in modeling impulsive noise in EEG, which usually can not be handled by the Gaussian distribution. Specially, we give a detailed analysis in the state estimation process to show the reason why the α-stable distribution can suppress the impulsive noise. Main results. To justify each component in our model, we compare our method with 4 different models with different settings on a collected 331-hour epileptic EEG data. To show the superiority of our method, we compare it with the existing approaches on both our 331-hour data and 892-hour public data. The results demonstrate that our method is most effective in both the detection rate and the false alarm. Significance. This is the first attempt to incorporate the α-stable distribution to a state-space model for noise suppression in seizure detection and achieves the state-of-the-art performance.

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

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    Niels Trusbak Haumann

    2016-01-01

    Full Text Available 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 it reduces the artifacts interfering with the signal. However, ICA also adds noise, or correction errors, to the waveform when the signal-to-noise ratio (SNR in the original data is relatively low—in particular to EEG and to MEG magnetometer data. In conclusion, ICA is recommended over SSP, but one should be careful when applying ICA to reduce artifacts on neurophysiological data with relatively low SNR.

  12. Circadian variation of scalp EEG: a novel measure based on wavelet packet transform and differential entropy.

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

    2013-01-01

    We propose a novel entropy-based measure to quantify the circadian variations of scalp electroencephalogram (EEG) by analyzing waking epochs of nap opportunities under an ultradian sleep-wake cycle (USW) protocol. To compute this circadian measure for a nap opportunity, each waking epoch (~1 sec) is decomposed using wavelet packet transform and the relative energy for the desired frequency band (here, 10-12 Hz) is calculated. Then, in a bootstrapping procedure, a shape statistic (skewness or kurtosis) of the relative energy distribution, after each resampling, is computed. Finally, the probability density function of this statistic is estimated, and the corresponding differential entropy is considered as the circadian measure. This measure was evaluated using EEG recordings from 4 healthy subjects during a 72-h USW procedure. According to the results, the proposed measure showed a significant circadian variation both for individual and group data, with peak values occurring near the core body temperature minimum. The performance of the entropy-based measure was also compared with that of two other measures, namely mean energy logarithm and mean energy ratio, revealing the superiority of this measure.

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

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    Kati Keuper

    Full Text Available 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.

  14. State dependent properties of epileptic brain networks: comparative graph-theoretical analyses of simultaneously recorded EEG and MEG.

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    Horstmann, Marie-Therese; Bialonski, Stephan; Noennig, Nina; Mai, Heinke; Prusseit, Jens; Wellmer, Jörg; Hinrichs, Hermann; Lehnertz, Klaus

    2010-02-01

    To investigate whether functional brain networks of epilepsy patients treated with antiepileptic medication differ from networks of healthy controls even during the seizure-free interval. We applied different rules to construct binary and weighted networks from EEG and MEG data recorded under a resting-state eyes-open and eyes-closed condition from 21 epilepsy patients and 23 healthy controls. The average shortest path length and the clustering coefficient served as global statistical network characteristics. Independent on the behavioral condition, epileptic brains exhibited a more regular functional network structure. Similarly, the eyes-closed condition was characterized by a more regular functional network structure in both groups. The amount of network reorganization due to behavioral state changes was similar in both groups. Consistent findings could be achieved for networks derived from EEG but hardly from MEG recordings, and network construction rules had a rather strong impact on our findings. Despite the locality of the investigated processes epileptic brain networks differ in their global characteristics from non-epileptic brain networks. Further methodological developments are necessary to improve the characterization of disturbed and normal functional networks. An increased regularity and a diminished modulation capability appear characteristic of epileptic brain networks. Copyright (c) 2009 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

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

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    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.

  16. TopoToolbox: Using Sensor Topography to Calculate Psychologically Meaningful Measures from Event-Related EEG/MEG

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    Xing Tian

    2011-01-01

    Full Text Available 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.

  17. 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).

  18. A time-frequency analysis of the dynamics of cortical networks of sleep spindles from MEG-EEG recordings

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    Younes eZerouali

    2014-10-01

    Full Text Available Sleep spindles are a hallmark of NREM sleep. They result from a widespread thalamo-cortical loop and involve synchronous cortical networks that are still poorly understood. We investigated whether brain activity during spindles can be characterized by specific patterns of functional connectivity among cortical generators. For that purpose, we developed a wavelet-based approach aimed at imaging the synchronous oscillatory cortical networks from simultaneous MEG-EEG recordings. First, we detected spindles on the EEG and extracted the corresponding frequency-locked MEG activity under the form of an analytic ridge signal in the time-frequency plane (Zerouali et al., 2013. Secondly, we performed source reconstruction of the ridge signal within the Maximum Entropy on the Mean framework (Amblard et al., 2004, yielding a robust estimate of the cortical sources producing observed oscillations. Lastly, we quantified functional connectivity among cortical sources using phase-locking values. The main innovations of this methodology are 1 to reveal the dynamic behavior of functional networks resolved in the time-frequency plane and 2 to characterize functional connectivity among MEG sources through phase interactions. We showed, for the first time, that the switch from fast to slow oscillatory mode during sleep spindles is required for the emergence of specific patterns of connectivity. Moreover, we show that earlier synchrony during spindles was associated with mainly intra-hemispheric connectivity whereas later synchrony was associated with global long-range connectivity. We propose that our methodology can be a valuable tool for studying the connectivity underlying neural processes involving sleep spindles, such as memory, plasticity or aging.

  19. A time-frequency analysis of the dynamics of cortical networks of sleep spindles from MEG-EEG recordings.

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    Zerouali, Younes; Lina, Jean-Marc; Sekerovic, Zoran; Godbout, Jonathan; Dube, Jonathan; Jolicoeur, Pierre; Carrier, Julie

    2014-01-01

    Sleep spindles are a hallmark of NREM sleep. They result from a widespread thalamo-cortical loop and involve synchronous cortical networks that are still poorly understood. We investigated whether brain activity during spindles can be characterized by specific patterns of functional connectivity among cortical generators. For that purpose, we developed a wavelet-based approach aimed at imaging the synchronous oscillatory cortical networks from simultaneous MEG-EEG recordings. First, we detected spindles on the EEG and extracted the corresponding frequency-locked MEG activity under the form of an analytic ridge signal in the time-frequency plane (Zerouali et al., 2013). Secondly, we performed source reconstruction of the ridge signal within the Maximum Entropy on the Mean framework (Amblard et al., 2004), yielding a robust estimate of the cortical sources producing observed oscillations. Lastly, we quantified functional connectivity among cortical sources using phase-locking values. The main innovations of this methodology are (1) to reveal the dynamic behavior of functional networks resolved in the time-frequency plane and (2) to characterize functional connectivity among MEG sources through phase interactions. We showed, for the first time, that the switch from fast to slow oscillatory mode during sleep spindles is required for the emergence of specific patterns of connectivity. Moreover, we show that earlier synchrony during spindles was associated with mainly intra-hemispheric connectivity whereas later synchrony was associated with global long-range connectivity. We propose that our methodology can be a valuable tool for studying the connectivity underlying neural processes involving sleep spindles, such as memory, plasticity or aging.

  20. Ultra-low-noise EEG/MEG systems enable bimodal non-invasive detection of spike-like human somatosensory evoked responses at 1 kHz.

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    Fedele, T; Scheer, H J; Burghoff, M; Curio, G; Körber, R

    2015-02-01

    Non-invasive EEG detection of very high frequency somatosensory evoked potentials featuring frequencies up to and above 1 kHz has been recently reported. Here, we establish the detectability of such components by combined low-noise EEG/MEG. We recorded SEP/SEF simultaneously using median nerve stimulation in five healthy human subjects inside an electromagnetically shielded room, combining a low-noise EEG custom-made amplifier (4.7 nV/√Hz) and a custom-made single-channel low-noise MEG (0.5 fT/√Hz @ 1 kHz). Both, low-noise EEG and MEG revealed three spectrally distinct and temporally overlapping evoked components: N20 (EEG [10 nV] ≅ MEG [1 fT]). Pronounced waveform (peak-by-peak) overlap of EEG and MEG signals is observed in the sigma band, whereas in the kappa band overlap was only partial. A decreasing signal-to-noise ratio (SNR; calculated for n = 12.000 averages) from sigma to kappa components characterizes both, electric and magnetic field recordings: Sigma-band SNR was 12.9  ±  5.5/19.8  ±  12.6 for EEG/MEG, and kappa-band SNR at 3.77  ±  0.8/4.5  ±  2.9. High-frequency performance of a tailor-made MEG matches closely with simultaneously recorded low-noise EEG for the non-invasive detection of somatosensory evoked activity at and above 1 kHz. Thus, future multi-channel dual-mode low-noise technology could offer complementary views for source reconstruction of the neural generators underlying such high-frequency responses, and render neural high-frequency processes related to multi-unit spike discharges accessible in non-invasive recordings.

  1. Simultaneous scalp electroencephalography (EEG), electromyography (EMG), and whole-body segmental inertial recording for multi-modal neural decoding.

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    Bulea, Thomas C; Kilicarslan, Atilla; Ozdemir, Recep; Paloski, William H; Contreras-Vidal, Jose L

    2013-07-26

    Recent studies support the involvement of supraspinal networks in control of bipedal human walking. Part of this evidence encompasses studies, including our previous work, demonstrating that gait kinematics and limb coordination during treadmill walking can be inferred from the scalp electroencephalogram (EEG) with reasonably high decoding accuracies. These results provide impetus for development of non-invasive brain-machine-interface (BMI) systems for use in restoration and/or augmentation of gait- a primary goal of rehabilitation research. To date, studies examining EEG decoding of activity during gait have been limited to treadmill walking in a controlled environment. However, to be practically viable a BMI system must be applicable for use in everyday locomotor tasks such as over ground walking and turning. Here, we present a novel protocol for non-invasive collection of brain activity (EEG), muscle activity (electromyography (EMG)), and whole-body kinematic data (head, torso, and limb trajectories) during both treadmill and over ground walking tasks. By collecting these data in the uncontrolled environment insight can be gained regarding the feasibility of decoding unconstrained gait and surface EMG from scalp EEG.

  2. Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

    Science.gov (United States)

    Bulea, Thomas C.; Kilicarslan, Atilla; Ozdemir, Recep; Paloski, William H.; Contreras-Vidal, Jose L.

    2013-01-01

    Recent studies support the involvement of supraspinal networks in control of bipedal human walking. Part of this evidence encompasses studies, including our previous work, demonstrating that gait kinematics and limb coordination during treadmill walking can be inferred from the scalp electroencephalogram (EEG) with reasonably high decoding accuracies. These results provide impetus for development of non-invasive brain-machine-interface (BMI) systems for use in restoration and/or augmentation of gait- a primary goal of rehabilitation research. To date, studies examining EEG decoding of activity during gait have been limited to treadmill walking in a controlled environment. However, to be practically viable a BMI system must be applicable for use in everyday locomotor tasks such as over ground walking and turning. Here, we present a novel protocol for non-invasive collection of brain activity (EEG), muscle activity (electromyography (EMG)), and whole-body kinematic data (head, torso, and limb trajectories) during both treadmill and over ground walking tasks. By collecting these data in the uncontrolled environment insight can be gained regarding the feasibility of decoding unconstrained gait and surface EMG from scalp EEG. PMID:23912203

  3. Automated real-time epileptic seizure detection in scalp EEG recordings using an algorithm based on wavelet packet transform.

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    Zandi, Ali Shahidi; Javidan, Manouchehr; Dumont, Guy A; Tafreshi, Reza

    2010-07-01

    A novel wavelet-based algorithm for real-time detection of epileptic seizures using scalp EEG is proposed. In a moving-window analysis, the EEG from each channel is decomposed by wavelet packet transform. Using wavelet coefficients from seizure and nonseizure references, a patient-specific measure is developed to quantify the separation between seizure and nonseizure states for the frequency range of 1-30 Hz. Utilizing this measure, a frequency band representing the maximum separation between the two states is determined and employed to develop a normalized index, called combined seizure index (CSI). CSI is derived for each epoch of every EEG channel based on both rhythmicity and relative energy of that epoch as well as consistency among different channels. Increasing significantly during ictal states, CSI is inspected using one-sided cumulative sum test to generate proper channel alarms. Analyzing alarms from all channels, a seizure alarm is finally generated. The algorithm was tested on scalp EEG recordings from 14 patients, totaling approximately 75.8 h with 63 seizures. Results revealed a high sensitivity of 90.5%, a false detection rate of 0.51 h(-1) and a median detection delay of 7 s. The algorithm could also lateralize the focus side for patients with temporal lobe epilepsy.

  4. Anatomical substrate and scalp EEG markers are correlated in subjects with cognitive impairment and Alzheimer’s disease

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    davide v Moretti

    2011-01-01

    Full Text Available Dementia is a syndromic diagnosis, encompassing various stage of severity and different anatomo-physiological substrates. The hippocampus is one of the first and most affected brain regions affected by both Alzheimer’s disease (AD and mild cognitive impairment (MCI. Morevoer, cronic cerebrovascular disease (CVD is one of the major risk factor for developing dementia. Recent studies have demonstrated different relationship between the anatomical substrate and scalp electroencephalography (EEG markers. Indeed, modifications of EEG rhythmicity is not proportional to the hippocampal atrophy, whereas changes in EEG activity are directly proportional to the load of subcortical CVD.Quantitative EEG have been demonstrated a reliable tool in identifying specific patterns in dementia research (Coburn et al., 2006; John and Prichep, 2006. The computation of the spectral power and the analysis of the functional coupling of brain areas, through linear coherence, are two of the most known processing methods in EEG research. Two specific EEG markers, theta/gamma and alpha3/alpha2 frequency ratio have been reliable associated to the atrophy of amygdalo-hippocampal complex. Moreover, theta/gamma ratio has been related to MCI conversion i

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

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    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.

  6. Movement priming of EEG/MEG brain responses for action-words characterizes the link between language and action

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    Mollo, Giovanna; Pulvermüller, Friedemann; Hauk, Olaf

    2016-01-01

    Activation in sensorimotor areas of the brain following perception of linguistic stimuli referring to objects and actions has been interpreted as evidence for strong theories of embodied semantics. Although a large number of studies have demonstrated this “language-to-action” link, important questions about how activation in the sensorimotor system affects language performance (“action-to-language” link) are yet unanswered. As several authors have recently pointed out, the debate should move away from an “embodied or not” focus, and rather aim to characterize the functional contributions of sensorimotor systems to language processing in more detail. For this purpose, we here introduce a novel movement priming paradigm in combination with electro- and magnetoencephalography (EEG/MEG), which allows investigating effects of motor cortex pre-activation on the spatio-temporal dynamics of action-word evoked brain activation. Participants initiated experimental trials by either finger- or foot-movements before executing a two alternative forced choice task employing action-words. We found differential brain activation during the early stages of subsequent hand- and leg-related word processing, respectively, albeit in the absence of behavioral effects. Distributed source estimation based on combined EEG/MEG measurements revealed that congruency effects between effector type used for response initiation (hand or foot) and action-word category (hand- or foot-related) occurred not only in motor cortex, but also in a classical language comprehension area, posterior superior temporal cortex, already 150 msec after the visual presentation of the word stimulus. This suggests that pre-activation of hand- and leg-motor networks may differentially facilitate the ignition of semantic cell assemblies for hand- and leg-related words, respectively. Our results demonstrate the usefulness of movement priming in combination with neuroimaging to functionally characterize the

  7. Movement priming of EEG/MEG brain responses for action-words characterizes the link between language and action.

    Science.gov (United States)

    Mollo, Giovanna; Pulvermüller, Friedemann; Hauk, Olaf

    2016-01-01

    Activation in sensorimotor areas of the brain following perception of linguistic stimuli referring to objects and actions has been interpreted as evidence for strong theories of embodied semantics. Although a large number of studies have demonstrated this "language-to-action" link, important questions about how activation in the sensorimotor system affects language performance ("action-to-language" link) are yet unanswered. As several authors have recently pointed out, the debate should move away from an "embodied or not" focus, and rather aim to characterize the functional contributions of sensorimotor systems to language processing in more detail. For this purpose, we here introduce a novel movement priming paradigm in combination with electro- and magnetoencephalography (EEG/MEG), which allows investigating effects of motor cortex pre-activation on the spatio-temporal dynamics of action-word evoked brain activation. Participants initiated experimental trials by either finger- or foot-movements before executing a two alternative forced choice task employing action-words. We found differential brain activation during the early stages of subsequent hand- and leg-related word processing, respectively, albeit in the absence of behavioral effects. Distributed source estimation based on combined EEG/MEG measurements revealed that congruency effects between effector type used for response initiation (hand or foot) and action-word category (hand- or foot-related) occurred not only in motor cortex, but also in a classical language comprehension area, posterior superior temporal cortex, already 150 msec after the visual presentation of the word stimulus. This suggests that pre-activation of hand- and leg-motor networks may differentially facilitate the ignition of semantic cell assemblies for hand- and leg-related words, respectively. Our results demonstrate the usefulness of movement priming in combination with neuroimaging to functionally characterize the link between

  8. 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.

  9. Presurgical evaluation for partial epilepsy: Relative contributions of chronic depth-electrode recordings versus FDG-PET and scalp-sphenoidal ictal EEG

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    Engel, J. Jr.; Henry, T.R.; Risinger, M.W.; Mazziotta, J.C.; Sutherling, W.W.; Levesque, M.F.; Phelps, M.E.

    1990-11-01

    One hundred fifty-three patients with medically refractory partial epilepsy underwent chronic stereotactic depth-electrode EEG (SEEG) evaluations after being studied by positron emission tomography (PET) with 18F-fluorodeoxyglucose (FDG) and scalp-sphenoidal EEG telemetry. We carried out retrospective standardized reviews of local cerebral metabolism and scalp-sphenoidal ictal onsets to determine when SEEG recordings revealed additional useful information. FDG-PET localization was misleading in only 3 patients with temporal lobe SEEG ictal onsets for whom extratemporal or contralateral hypometabolism could be attributed to obvious nonepileptic structural defects. Two patients with predominantly temporal hypometabolism may have had frontal epileptogenic regions, but ultimate localization remains uncertain. Scalp-sphenoidal ictal onsets were misleading in 5 patients. For 37 patients with congruent focal scalp-sphenoidal ictal onsets and temporal hypometabolic zones, SEEG recordings never demonstrated extratemporal or contralateral epileptogenic regions; however, 3 of these patients had nondiagnostic SEEG evaluations. The results of subsequent subdural grid recordings indicated that at least 1 of these patients may have been denied beneficial surgery as a result of an equivocal SEEG evaluation. Weighing risks and benefits, it is concluded that anterior temporal lobectomy is justified without chronic intracranial recording when specific criteria for focal scalp-sphenoidal ictal EEG onsets are met, localized hypometabolism predominantly involves the same temporal lobe, and no other conflicting information has been obtained from additional tests of focal functional deficit, structural imaging, or seizure semiology.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    Ruhnau, Philipp; Herrmann, Björn; Maess, Burkhard; Brauer, Jens; Friederici, Angela D.; Schröger, Erich

    2013-01-01

    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 (RTs) 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 toward complex distractors operate comparably in school-aged children and adults, yet undergoing generator maturation. PMID:24155730

  12. The electrophysiology of neuroHIV: A systematic review of EEG and MEG studies in people with HIV infection since the advent of highly-active antiretroviral therapy.

    Science.gov (United States)

    Fernández-Cruz, Ana Lucia; Fellows, Lesley K

    2017-06-01

    The Human Immunodeficiency Virus (HIV) has an impact on the brain, even when the infection is well-controlled with modern highly-active antiretroviral therapy (HAART). While dementia is rare in those on HAART, milder cognitive impairment is common. The causes, patterns, and evolution of brain dysfunction in people living with HIV remain uncertain. We evaluate whether electrophysiological methods provide informative measures of brain dysfunction in this population. A systematic literature search identified studies that used EEG or MEG to evaluate persons living with HIV published between 1996 (when HAART became available) and 2016. Twenty-eight studies were identified. Most involved small samples, and all but four were cross-sectional. Reduced amplitude of Event Related Potentials and decreased power in the alpha band at rest were the most frequent differences between people with and without HIV infection. Of the 16 studies that also assessed cognitive ability, 13 found a significant relationship between cognition and electrophysiological changes in the HIV+ groups. Five of those studies also reported a significant relationship with current immunosuppression, suggesting a direct effect of HIV on the brain. There were few longitudinal studies; whether these electrophysiological changes progress over time, or respond to treatment, remains unclear. EEG and MEG can provide useful information about brain dysfunction in people with HIV infection, but more consistent assessments of both cognition and EEG patterns, as well as longitudinal studies with larger, better characterized samples are needed. This is the first systematic review of electrophysiological findings in HIV since the availability of HAART. EEG and MEG measures are sensitive to brain dysfunction in this population, and could complement other approaches in improving the assessment, understanding and treatment of neurocognitive disorders in HIV. Copyright © 2017 International Federation of Clinical

  13. Assessing time-dependent association between scalp EEG and muscle activation: A functional random-effects model approach.

    Science.gov (United States)

    Wang, X F; Yang, Qi; Fan, Zhaozhi; Sun, Chang-Kai; Yue, Guang H

    2009-02-15

    This study investigates time-dependent associations between source strength estimated from high-density scalp electroencephalogram (EEG) and force of voluntary handgrip contraction at different intensity levels. We first estimate source strength from raw EEG signals collected during voluntary muscle contractions at different levels and then propose a functional random-effects model approach in which both functional fixed effects and functional random-effects are considered for the data. Two estimation procedures for the functional model are discussed. The first estimation procedure is a two-step method which involves no iterations. It can flexibly use different smoothing methods and smoothing parameters. The second estimation procedure benefits from the connection between linear mixed models and regression splines and can be fitted using existing software. Functional ANOVA is then suggested to assess the experimental effects from the functional point of view. The statistical analysis shows that the time-dependent source strength function exhibits a nonlinear feature, where a bump is detected around the force onset time. However, there is the lack of significant variations in source strength on different force levels and different cortical areas. The proposed functional random-effects model procedure can be applied to other types of functional data in neuroscience.

  14. Sitting and Standing Intention Can be Decoded from Scalp EEG Recorded Prior to Movement Execution

    Directory of Open Access Journals (Sweden)

    Thomas C Bulea

    2014-11-01

    Full Text Available Low frequency signals recorded from non-invasive electroencephalography (EEG, in particular movement-related cortical potentials (MRPs, are associated with preparation and execution of movement and thus present a target for use in brain-machine interfaces. We investigated the ability to decode movement intent from delta-band (0.1-4 Hz EEG recorded immediately before movement execution in healthy volunteers. We used data from epochs starting 1.5 sec before movement onset to classify future movements into one of three classes: stand-up, sit-down, or quiet. We assessed classification accuracy in both externally triggered and self-paced paradigms. Movement onset was determined from electromyography (EMG recordings synchronized with EEG signals. We employed an artifact subspace reconstruction (ASR algorithm to eliminate high amplitude noise before building our time-embedded EEG features. We applied local Fisher’s discriminant analysis to reduce the dimensionality of our spatio-temporal features and subsequently used a Gaussian mixture model classifier for our three class problem. Our results demonstrate significantly better than chance classification accuracy (chance level = 33.3% for the self-initiated (78.0 ± 2.6% and triggered (74.7 ± 5.7% paradigms. Surprisingly, we found no significant difference in classification accuracy between the self-paced and cued paradigms when using the full set of non-peripheral electrodes. However, accuracy was significantly increased for self-paced movements when only electrodes over the primary motor area were used. Overall, this study demonstrates that delta-band EEG recorded immediately before movement carries discriminative information regarding movement type. Our results suggest that EEG-based classifiers could improve lower-limb neuroprostheses and neurorehabilitation techniques by providing earlier detection of movement intent, which could be used in robot-assisted strategies for motor training and

  15. Sitting and standing intention can be decoded from scalp EEG recorded prior to movement execution.

    Science.gov (United States)

    Bulea, Thomas C; Prasad, Saurabh; Kilicarslan, Atilla; Contreras-Vidal, Jose L

    2014-01-01

    Low frequency signals recorded from non-invasive electroencephalography (EEG), in particular movement-related cortical potentials (MRPs), are associated with preparation and execution of movement and thus present a target for use in brain-machine interfaces. We investigated the ability to decode movement intent from delta-band (0.1-4 Hz) EEG recorded immediately before movement execution in healthy volunteers. We used data from epochs starting 1.5 s before movement onset to classify future movements into one of three classes: stand-up, sit-down, or quiet. We assessed classification accuracy in both externally triggered and self-paced paradigms. Movement onset was determined from electromyography (EMG) recordings synchronized with EEG signals. We employed an artifact subspace reconstruction (ASR) algorithm to eliminate high amplitude noise before building our time-embedded EEG features. We applied local Fisher's discriminant analysis to reduce the dimensionality of our spatio-temporal features and subsequently used a Gaussian mixture model classifier for our three class problem. Our results demonstrate significantly better than chance classification accuracy (chance level = 33.3%) for the self-initiated (78.0 ± 2.6%) and triggered (74.7 ± 5.7%) paradigms. Surprisingly, we found no significant difference in classification accuracy between the self-paced and cued paradigms when using the full set of non-peripheral electrodes. However, accuracy was significantly increased for self-paced movements when only electrodes over the primary motor area were used. Overall, this study demonstrates that delta-band EEG recorded immediately before movement carries discriminative information regarding movement type. Our results suggest that EEG-based classifiers could improve lower-limb neuroprostheses and neurorehabilitation techniques by providing earlier detection of movement intent, which could be used in robot-assisted strategies for motor training and recovery of function.

  16. Human scalp recorded sigma activity is modulated by slow EEG oscillations during deep sleep.

    NARCIS (Netherlands)

    Fell, J.; Elfadil, H.; Roschke, J.; Burr, W.; Klaver, P.; Elger, C.E.; Fernandez, G.S.E.

    2002-01-01

    The EEG during deep sleep exhibits a distinct cortically generated slow oscillation of around and below 1 Hz which can be distinguished from other delta (0.5-3.5 Hz) activity. Intracranial studies showed that this slow oscillation triggers and groups cortical network firing. In the present study, we

  17. A framework for the design of flexible cross-talk functions for spatial filtering of EEG/MEG data: DeFleCT.

    Science.gov (United States)

    Hauk, Olaf; Stenroos, Matti

    2014-04-01

    Brain activation estimated from EEG and MEG data is the basis for a number of time-series analyses. In these applications, it is essential to minimize "leakage" or "cross-talk" of the estimates among brain areas. Here, we present a novel framework that allows the design of flexible cross-talk functions (DeFleCT), combining three types of constraints: (1) full separation of multiple discrete brain sources, (2) minimization of contributions from other (distributed) brain sources, and (3) minimization of the contribution from measurement noise. Our framework allows the design of novel estimators by combining knowledge about discrete sources with constraints on distributed source activity and knowledge about noise covariance. These estimators will be useful in situations where assumptions about sources of interest need to be combined with uncertain information about additional sources that may contaminate the signal (e.g. distributed sources), and for which existing methods may not yield optimal solutions. We also show how existing estimators, such as maximum-likelihood dipole estimation, L2 minimum-norm estimation, and linearly-constrained minimum variance as well as null-beamformers, can be derived as special cases from this general formalism. The performance of the resulting estimators is demonstrated for the estimation of discrete sources and regions-of-interest in simulations of combined EEG/MEG data. Our framework will be useful for EEG/MEG studies applying time-series analysis in source space as well as for the evaluation and comparison of linear estimators. Copyright © 2013 Wiley Periodicals, Inc.

  18. Stable Scalp EEG Spatiospectral Patterns Across Paradigms Estimated by Group ICA.

    Science.gov (United States)

    Labounek, René; Bridwell, David A; Mareček, Radek; Lamoš, Martin; Mikl, Michal; Slavíček, Tomáš; Bednařík, Petr; Baštinec, Jaromír; Hluštík, Petr; Brázdil, Milan; Jan, Jiří

    2018-01-01

    Electroencephalography (EEG) oscillations reflect the superposition of different cortical sources with potentially different frequencies. Various blind source separation (BSS) approaches have been developed and implemented in order to decompose these oscillations, and a subset of approaches have been developed for decomposition of multi-subject data. Group independent component analysis (Group ICA) is one such approach, revealing spatiospectral maps at the group level with distinct frequency and spatial characteristics. The reproducibility of these distinct maps across subjects and paradigms is relatively unexplored domain, and the topic of the present study. To address this, we conducted separate group ICA decompositions of EEG spatiospectral patterns on data collected during three different paradigms or tasks (resting-state, semantic decision task and visual oddball task). K-means clustering analysis of back-reconstructed individual subject maps demonstrates that fourteen different independent spatiospectral maps are present across the different paradigms/tasks, i.e. they are generally stable.

  19. Development and Experimental Validation of a Dry Non-Invasive Multi-Channel Mouse Scalp EEG Sensor through Visual Evoked Potential Recordings

    Directory of Open Access Journals (Sweden)

    Donghyeon Kim

    2017-02-01

    Full Text Available In this paper, we introduce a dry non-invasive multi-channel sensor for measuring brainwaves on the scalps of mice. The research on laboratory animals provide insights to various practical applications involving human beings and other animals such as working animals, pets, and livestock. An experimental framework targeting the laboratory animals has the potential to lead to successful translational research when it closely resembles the environment of real applications. To serve scalp electroencephalography (EEG research environments for the laboratory mice, the dry non-invasive scalp EEG sensor with sixteen electrodes is proposed to measure brainwaves over the entire brain area without any surgical procedures. We validated the proposed sensor system with visual evoked potential (VEP experiments elicited by flash stimulations. The VEP responses obtained from experiments are compared with the existing literature, and analyzed in temporal and spatial perspectives. We further interpret the experimental results using time-frequency distribution (TFD and distance measurements. The developed sensor guarantees stable operations for in vivo experiments in a non-invasive manner without surgical procedures, therefore exhibiting a high potential to strengthen longitudinal experimental studies and reliable translational research exploiting non-invasive paradigms.

  20. Development and Experimental Validation of a Dry Non-Invasive Multi-Channel Mouse Scalp EEG Sensor through Visual Evoked Potential Recordings.

    Science.gov (United States)

    Kim, Donghyeon; Yeon, Chanmi; Kim, Kiseon

    2017-02-09

    In this paper, we introduce a dry non-invasive multi-channel sensor for measuring brainwaves on the scalps of mice. The research on laboratory animals provide insights to various practical applications involving human beings and other animals such as working animals, pets, and livestock. An experimental framework targeting the laboratory animals has the potential to lead to successful translational research when it closely resembles the environment of real applications. To serve scalp electroencephalography (EEG) research environments for the laboratory mice, the dry non-invasive scalp EEG sensor with sixteen electrodes is proposed to measure brainwaves over the entire brain area without any surgical procedures. We validated the proposed sensor system with visual evoked potential (VEP) experiments elicited by flash stimulations. The VEP responses obtained from experiments are compared with the existing literature, and analyzed in temporal and spatial perspectives. We further interpret the experimental results using time-frequency distribution (TFD) and distance measurements. The developed sensor guarantees stable operations for in vivo experiments in a non-invasive manner without surgical procedures, therefore exhibiting a high potential to strengthen longitudinal experimental studies and reliable translational research exploiting non-invasive paradigms.

  1. Magnetoencephalographic Identification of Epileptic Focus in Children With Generalized Electroencephalographic (EEG) Features but Focal Imaging Abnormalities.

    Science.gov (United States)

    Shukla, Garima; Kazutaka, Jin; Gupta, Ajay; Mosher, John; Jones, Stephen; Alexopoulos, Andreas; Burgess, Richard C

    2017-10-01

    Children with generalized seizures are often excluded as epilepsy surgery candidates. This prospective study was conducted to evaluate the utility of magnetoencephalography (MEG) to refine the location of the "irritative zone" in children with single lesions on magnetic resonance imaging (MRI) but with generalized ictal electroencephalographic (EEG) findings. Patients admitted with refractory epilepsy with imaging studies showing focal or hemispheric abnormalities but scalp video EEG showing generalized or multiregional epileptiform abnormalities were included. Patients were encouraged into natural sleep, and simultaneous whole-head MEG/EEG was recorded. Source localization of epileptic spikes on MEG was carried out while blinded to other results. Acceptable dipoles were classified into 3 groups: focal, hemispheric clusters, and single focal cluster with additional widespread dipoles. Nine patients (4 female, 5 males; ages 10 months to 15 years) were included. Two had focal features on clinical semiology, whereas all had generalized or multiregional interictal and ictal EEG. Etiologies included tuberous sclerosis complex (2), postencephalitic sequelae (1), focal cortical dysplasia (1), and unknown (2). Five patients had clear focal lesions on brain MRI whereas the other 2 had focal positron emission tomography (PET) abnormalities. An average of 38 spikes were accepted (average goodness of fit = 85.3%). A single tight cluster of dipoles was identified in 5 patients, 1 had dipoles with propagation from left occipital to right temporal. One patient had 2 distinct dipole clusters. MEG demonstrated focal findings 9 times more often than the simultaneously recorded scalp EEG, and 3 times more often than the associated multiday video EEG recordings. This study shows that neurophysiologic evidence of focal epileptiform abnormalities in patients with focal brain lesions and generalized EEG findings can be strengthened using MEG. Further feasibility of surgical candidacy

  2. Automated detection of epileptic ripples in MEG using beamformer-based virtual sensors

    Science.gov (United States)

    Migliorelli, Carolina; Alonso, Joan F.; Romero, Sergio; Nowak, Rafał; Russi, Antonio; Mañanas, Miguel A.

    2017-08-01

    Objective. In epilepsy, high-frequency oscillations (HFOs) are expressively linked to the seizure onset zone (SOZ). The detection of HFOs in the noninvasive signals from scalp electroencephalography (EEG) and magnetoencephalography (MEG) is still a challenging task. The aim of this study was to automate the detection of ripples in MEG signals by reducing the high-frequency noise using beamformer-based virtual sensors (VSs) and applying an automatic procedure for exploring the time-frequency content of the detected events. Approach. Two-hundred seconds of MEG signal and simultaneous iEEG were selected from nine patients with refractory epilepsy. A two-stage algorithm was implemented. Firstly, beamforming was applied to the whole head to delimitate the region of interest (ROI) within a coarse grid of MEG-VS. Secondly, a beamformer using a finer grid in the ROI was computed. The automatic detection of ripples was performed using the time-frequency response provided by the Stockwell transform. Performance was evaluated through comparisons with simultaneous iEEG signals. Main results. ROIs were located within the seizure-generating lobes in the nine subjects. Precision and sensitivity values were 79.18% and 68.88%, respectively, by considering iEEG-detected events as benchmarks. A higher number of ripples were detected inside the ROI compared to the same region in the contralateral lobe. Significance. The evaluation of interictal ripples using non-invasive techniques can help in the delimitation of the epileptogenic zone and guide placement of intracranial electrodes. This is the first study that automatically detects ripples in MEG in the time domain located within the clinically expected epileptic area taking into account the time-frequency characteristics of the events through the whole signal spectrum. The algorithm was tested against intracranial recordings, the current gold standard. Further studies should explore this approach to enable the localization of

  3. Multichannel EEG Visualization

    NARCIS (Netherlands)

    Caat, Michael ten

    2008-01-01

    Electroencephalography (EEG) measures electrical brain activity by electrodes attached to the scalp. Multichannel EEG refers to a measurement with a large number of electrodes. EEG has clinical as well as scientific applications, including neurology, psychology, pharmacy, linguistics, and biology.

  4. Stochastic Behavior of Phase Synchronization Index and Cross-frequency Couplings in Epileptogenic Zones During Interictal Periods Measured with Scalp dEEG

    Directory of Open Access Journals (Sweden)

    Ceon eRamon

    2013-05-01

    Full Text Available The stochastic behavior of the phase synchronization index (SI and cross-frequency couplings on different days during a hospital stay of three epileptic patients was studied for noninvasive localization of the epileptogenic areas from high density, 256-channel, scalp EEG (dEEG recordings. The study was performed with short-duration (0-180 sec, seizure-free, epileptiform-free and spike-free interictal dEEG data on different days of three subjects. The seizure areas were localized with subdural recordings with an 8×8 macro-electrode grid array and strip electrodes. The study was performed in theta (3-7 Hz, alpha (7-12 Hz, beta (12-30 Hz and low gamma (30-50 Hz bands. A detrended fluctuation analysis was used to find the long range temporal correlations in the SI that reveals the stochastic behavior of the SI in a given time period. The phase synchronization was computed after taking Hilbert transform of the EEG data. Contour plots were constructed with 20 sec time-frames using a montage of the layout of 256 electrode positions. It was found that the stochastic behavior of the SI was higher in epileptogenic areas and in nearby areas on different days for each subject. The low gamma band was found to be the best to localize the epileptic sites. Also, a stable higher pattern of SI emerged after 60-120 seconds in the epileptogenic areas. The cross-frequency couplings of SI in theta-gamma, beta-gamma and alpha-gamma bands were decreased and spatial patterns were fragmented in epileptogenic areas. Combinations of an increase in the stochastic behavior of the SI and decrease in cross-frequency couplings are potential markers to assist in localizing epileptogenic areas. These findings suggest that it is possible to localize the epileptogenic areas noninvasively from a short-duration (~ 180 sec, seizure-free and spike-free interictal scalp dEEG recordings.

  5. High frequency spectral components after Secobarbital: the contribution of muscular origin--a study with MEG/EEG.

    NARCIS (Netherlands)

    Claus, S.; Velis, D.; Lopes da Silva, F.H.; Viergever, M.A.; Kalitzin, S.

    2012-01-01

    OBJECTIVES: Previously we found that benzodiazepines not only provoke beta-activity in the EEG, but also higher frequency activity. Knowing the origin of this high frequency activity is crucial if localisation of epileptogenic brain tissue is the query. We attempt to differentiate cerebral from

  6. Establishing a Right Frontal Beta Signature for Stopping Action in Scalp EEG: Implications for Testing Inhibitory Control in Other Task Contexts.

    Science.gov (United States)

    Wagner, Johanna; Wessel, Jan R; Ghahremani, Ayda; Aron, Adam R

    2018-01-01

    Many studies have examined the rapid stopping of action as a proxy of human self-control. Several methods have shown that a critical focus for stopping is the right inferior frontal cortex. Moreover, electrocorticography studies have shown beta band power increases in the right inferior frontal cortex and in the BG for successful versus failed stop trials, before the time of stopping elapses, perhaps underpinning a prefrontal-BG network for inhibitory control. Here, we tested whether the same signature might be visible in scalp electroencephalography (EEG)-which would open important avenues for using this signature in studies of the recruitment and timing of prefrontal inhibitory control. We used independent component analysis and time-frequency approaches to analyze EEG from three different cohorts of healthy young volunteers (48 participants in total) performing versions of the standard stop signal task. We identified a spectral power increase in the band 13-20 Hz that occurs after the stop signal, but before the time of stopping elapses, with a right frontal topography in the EEG. This right frontal beta band increase was significantly larger for successful compared with failed stops in two of the three studies. We also tested the hypothesis that unexpected events recruit the same frontal system for stopping. Indeed, we show that the stopping-related right-lateralized frontal beta signature was also active after unexpected events (and we accordingly provide data and scripts for the method). These results validate a right frontal beta signature in the EEG as a temporally precise and functionally significant neural marker of the response inhibition process.

  7. 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

    2015-09-01

    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.

  8. 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

  9. 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.

    Science.gov (United States)

    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.

  10. Increased Intrinsic Connectivity of the Default Mode Network in Temporal Lobe Epilepsy: Evidence from Resting-State MEG Recordings.

    Directory of Open Access Journals (Sweden)

    Fu-Jung Hsiao

    Full Text Available The electrophysiological signature of resting state oscillatory functional connectivity within the default mode network (DMN during spike-free periods in temporal lobe epilepsy (TLE remains unclear. Using magnetoencephalographic (MEG recordings, this study investigated how the connectivity within the DMN was altered in TLE, and we examined the effect of lateralized TLE on functional connectivity. Sixteen medically intractable TLE patients and 22 controls participated in this study. Whole-scalp 306-channel MEG epochs without interictal spikes generated from both MEG and EEG data were analyzed using a minimum norm estimate (MNE and source-based imaginary coherence analysis. With this processing, we obtained the cortical activation and functional connectivity within the DMN. The functional connectivity was increased between DMN and the right medial temporal (MT region at the delta band and between DMN and the bilateral anterior cingulate cortex (ACC regions at the theta band. The functional change was associated with the lateralization of TLE. The right TLE showed enhanced DMN connectivity with the right MT while the left TLE demonstrated increased DMN connectivity with the bilateral MT. There was no lateralization effect of TLE upon the DMN connectivity with ACC. These findings suggest that the resting-state functional connectivity within the DMN is reinforced in temporal lobe epilepsy during spike-free periods. Future studies are needed to examine if the altered functional connectivity can be used as a biomarker for treatment responses, cognitive dysfunction and prognosis in patients with TLE.

  11. 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.

  12. Scalp meningioma

    Directory of Open Access Journals (Sweden)

    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.

  13. Bayesian analysis of MEG visual evoked responses

    Energy Technology Data Exchange (ETDEWEB)

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

    1999-04-01

    The authors developed a method for analyzing neural electromagnetic data that allows probabilistic inferences to be drawn about regions of activation. The method involves the generation of a large number of possible solutions which both fir the data and prior expectations about the nature of probable solutions made explicit by a Bayesian formalism. In addition, they have introduced a model for the current distributions that produce MEG and (EEG) data that allows extended regions of activity, and can easily incorporate prior information such as anatomical constraints from MRI. To evaluate the feasibility and utility of the Bayesian approach with actual data, they analyzed MEG data from a visual evoked response experiment. They compared Bayesian analyses of MEG responses to visual stimuli in the left and right visual fields, in order to examine the sensitivity of the method to detect known features of human visual cortex organization. They also examined the changing pattern of cortical activation as a function of time.

  14. 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

  15. Localization of fast MEG waves in patients with brain tumors and epilepsy.

    NARCIS (Netherlands)

    Jongh, de A.; Munck, de J.C.; Baayen, J.C.; Puligheddu, M; Jonkman, E.J.; Stam, C.J.

    2003-01-01

    8 Hz) can be used to determine the location of the epileptic focus. Automatic dipole analysis was applied to MEG data of 25 patients with intracranial tumors and epilepsy. The frequency range of 8-50 Hz was divided into standard EEG bands. MEG results were overlaid on the MRI scans of the patients.

  16. 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.

  17. Scalp Psoriasis: Signs and Symptoms

    Science.gov (United States)

    ... Kids’ zone Video library Find a dermatologist Scalp psoriasis Overview Scalp psoriasis: When psoriasis forms on the scalp, it can creep beyond the scalp. Scalp psoriasis: Overview Psoriasis (sore-EYE-ah-sis) can appear ...

  18. Scalp Psoriasis: Diagnosis and Treatment

    Science.gov (United States)

    ... Kids’ zone Video library Find a dermatologist Scalp psoriasis Overview Scalp psoriasis: When psoriasis forms on the scalp, it can creep beyond the scalp. Scalp psoriasis: Overview Psoriasis (sore-EYE-ah-sis) can appear ...

  19. Assessing EEG sleep spindle propagation. Part 1: theory and proposed methodology.

    Science.gov (United States)

    O'Reilly, Christian; Nielsen, Tore

    2014-01-15

    A convergence of studies has revealed sleep spindles to be associated with sleep-related cognitive processing and even with fundamental waking state capacities such as intelligence. However, some spindle characteristics, such as propagation direction and delay, may play a decisive role but are only infrequently investigated because of technical complexities. A new methodology for assessing sleep spindle propagation over the human scalp using noninvasive electroencephalography (EEG) is described. This approach is based on the alignment of time-frequency representations of spindle activity across recording channels. This first of a two-part series concentrates on framing theoretical considerations related to EEG spindle propagation and on detailing the methodology. A short example application is provided that illustrates the repeatability of results obtained with the new propagation measure in a sample of 32 night recordings. A more comprehensive experimental investigation is presented in part two of the series. Compared to existing methods, this approach is particularly well adapted for studying the propagation of sleep spindles because it estimates time delays rather than phase synchrony and it computes propagation properties for every individual spindle with windows adjusted to the specific spindle duration. The proposed methodology is effective in tracking the propagation of spindles across the scalp and may thus help in elucidating the temporal aspects of sleep spindle dynamics, as well as other transient EEG and MEG events. A software implementation (the Spyndle Python package) is provided as open source software. Copyright © 2013 Elsevier B.V. All rights reserved.

  20. Source-space ICA for EEG source separation, localization, and time-course reconstruction.

    Science.gov (United States)

    Jonmohamadi, Yaqub; Poudel, Govinda; Innes, Carrie; Jones, Richard

    2014-11-01

    We propose source-space independent component analysis (ICA) for separation, tomography, and time-course reconstruction of EEG and MEG source signals. Source-space ICA is based on the application of singular value decomposition and ICA on the neuroelectrical signals from all brain voxels obtained post minimum-variance beamforming of sensor-space EEG or MEG. We describe the theoretical background and equations, then evaluate the performance of this technique in several different situations, including weak sources, bilateral correlated sources, multiple sources, and cluster sources. In this approach, tomographic maps of sources are obtained by back-projection of the ICA mixing coefficients into the source-space (3-D brain template). The advantages of source-space ICA over the popular alternative approaches of sensor-space ICA together with dipole fitting and power mapping via minimum-variance beamforming are demonstrated. Simulated EEG data were produced by forward head modeling to project the simulated sources onto scalp sensors, then superimposed on real EEG background. To illustrate the application of source-space ICA to real EEG source reconstruction, we show the localization and time-course reconstruction of visual evoked potentials. Source-space ICA is superior to the minimum-variance beamforming in the reconstruction of multiple weak and strong sources, as ICA allows weak sources to be identified and reconstructed in the presence of stronger sources. Source-space ICA is also superior to sensor-space ICA on accuracy of localization of sources, as source-space ICA applies ICA to the time-courses of voxels reconstructed from minimum-variance beamforming on a 3D scanning grid and these time-courses are optimally unmixed via the beamformer. Each component identified by source-space ICA has its own tomographic map which shows the extent to which each voxel has contributed to that component. Copyright © 2014 Elsevier Inc. All rights reserved.

  1. Giant scalp arteriovenous malformation.

    Science.gov (United States)

    Worm, Paulo Valdeci; Ruschel, Leonardo Gilmone; Roxo, Marcelo Rosa; Camelo, Rafael

    2016-12-01

    Arteriovenous malformations (AVMs) of the scalp are rare lesions. The clinical picture presents with complaints of increased scalp, scalp disfigurement, pain and neurological symptoms. Its origin can be congenital or traumatic. We present a case of giant scalp AVMs and its management, followed by a brief literature review on the subject. The diagnosis of scalp AVMs is based on physical examination and confirmed by internal and external carotid angiography or computed tomographic angiography (CTA). Surgical excision is especially effective in scalp AVMs, and is the most frequently used treatment modality.

  2. Treatment of Scalp Scars.

    Science.gov (United States)

    Kim, John

    2017-02-01

    The scalp presents many challenges to the reconstructive surgeon given its visible nature and the various considerations that must be given for optimal reconstruction. In this article, we review the anatomy of the scalp, the various options for reconstruction, and important considerations for improving the chances of optimal reconstruction of scalp defects. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. Identification of epileptic high frequency oscillations in the time domain by using MEG beamformer-based virtual sensors

    NARCIS (Netherlands)

    Van Klink, Nicole; Hillebrand, Arjan; Zijlmans, Maeike

    2016-01-01

    Objective: High frequency oscillations (HFOs, >80. Hz) are biomarkers for epileptogenic cortex in invasive and non-invasive electroencephalography (EEG). Identification of HFOs in magnetoencephalography (MEG) is hindered by noise. Computing spatial filters using beamforming to reconstruct time

  4. Fetal scalp pH testing

    Science.gov (United States)

    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 ...

  5. Automatic detection and visualisation of MEG ripple oscillations in epilepsy

    Directory of Open Access Journals (Sweden)

    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.

  6. MEG source detection revisited

    Science.gov (United States)

    Lei, Tianhu; Roberts, Timothy P. L.

    2010-04-01

    Magnetoencephalography (MEG) is a multi-channel imaging technique. It uses an array composed of a large number of Superconducting Quantum Interference Device (SQUID) to measure the magnetic fields produced by the primary electric currents inside the brain. The measured spatio-temporal magnetic fields are then used to estimate the locations and strengths of these electric currents, often known as MEG sources. The estimated quantities are finally superimposed with the images generated by magnetic resonance imaging (MRI). The combination of information from MEG and MRI forms the magnetic source image (MSI). A great variety of signal processing and modeling techniques such as Inverse problem, Subspace approach, Independent component analysis (ICA) method, and Beamforming (BF) are used to estimate these sources. The first three approaches require the number of sources be detected a priori. Several shortcomings exist in the currently used methods for detecting the source number. First, the source detection is completed only after - not before - MSI is generated. Secondly, the detection methods are somewhat subjective. In order to provide a solution to the problem of detecting MEG source number for all these approaches, a novel method is developed. The covariance matrix of MEG measurements over all channels is decomposed into the signal and the noise subspaces. The number of sources is shown to be equal to the dimension of the signal subspace. The selection of this dimension is translated into a problem of determining the order of the underlying statistics. This statistical identification is resolved by using Information theoretic criteria which are derived based on Kullback-Leibler divergence. Because the method utilizes originally acquired MEG measurements and implemented before magnetic source images are generated, it is an entirely data-driven approach, more efficient, and less likely to be subjective.

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

    Science.gov (United States)

    Andersen, Lau M; Oostenveld, Robert; Pfeiffer, Christoph; Ruffieux, Silvia; Jousmäki, Veikko; Hämäläinen, Matti; Schneiderman, Justin F; Lundqvist, Daniel

    2017-01-01

    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.

  8. 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.

  9. 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...

  10. Scales on the scalp

    Directory of Open Access Journals (Sweden)

    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.

  11. Event-related theta power during lexical-semantic retrieval and decision conflict is modulated by alcohol intoxication: anatomically-constrained MEG

    Directory of Open Access Journals (Sweden)

    Ksenija eMarinkovic

    2012-04-01

    Full Text Available Language processing is commonly characterized by an event-related increase in theta power (4-7 Hz in scalp EEG. Oscillatory brain dynamics underlying alcohol's effects on language are poorly understood despite impairments on verbal tasks. To investigate how moderate alcohol intoxication modulates event-related theta activity during visual word processing, healthy social drinkers (N=22, 11 females participated in both alcohol (0.6 g/kg ethanol for men, 0.55 g/kg for women and placebo conditions in a counterbalanced design. They performed a double-duty lexical decision task as they detected real words among nonwords. An additional requirement to respond to all words that also referred to animals induced response conflict. High density whole head MEG signals and midline scalp EEG data were decomposed for each trial with Morlet wavelets. Each person’s reconstructed cortical surface was used to constrain noise-normalized distributed minimum norm inverse solutions for theta frequencies. Alcohol intoxication increased reaction time and marginally affected accuracy. The overall spatiotemporal pattern is consistent with the left-lateralized fronto-temporal activation observed in language studies applying time domain analysis. Event-related theta power was sensitive to the two functions manipulated by the task. First, theta estimated to the left-lateralized fronto-temporal areas reflected lexical-semantic retrieval, indicating that this measure is well suited for investigating the neural basis of language functions. While alcohol attenuated theta power overall, it was particularly deleterious to semantic retrieval since it reduced theta to real words but not pseudowords. Second, a highly overlapping prefrontal network comprising lateral prefrontal and anterior cingulate cortex was sensitive to decision conflict and was also affected by intoxication, in agreement with previous studies indicating that executive functions are especially vulnerable to

  12. 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.

  13. Scalp imaging techniques

    Science.gov (United States)

    Otberg, Nina; Shapiro, Jerry; Lui, Harvey; Wu, Wen-Yu; Alzolibani, Abdullateef; Kang, Hoon; Richter, Heike; Lademann, Jürgen

    2017-05-01

    Scalp imaging techniques are necessary tools for the trichological practice and for visualization of permeation, penetration and absorption processes into and through the scalp and for the research on drug delivery and toxicology. The present letter reviews different scalp imaging techniques and discusses their utility. Moreover, two different studies on scalp imaging techniques are presented in this letter: (1) scalp imaging with phototrichograms in combination with laser scanning microscopy, and (2) follicular measurements with cyanoacrylate surface replicas and light microscopy in combination with laser scanning microscopy. The experiments compare different methods for the determination of hair density on the scalp and different follicular measures. An average terminal hair density of 132 hairs cm-2 was found in 6 Caucasian volunteers and 135 hairs cm-2 in 6 Asian volunteers. The area of the follicular orifices accounts to 16.3% of the skin surface on average measured with laser scanning microscopy images. The potential volume of the follicular infundibulum was calculated based on the laser scanning measurements and is found to be 4.63 mm3 per cm2 skin on average. The experiments show that hair follicles are quantitatively relevant pathways and potential reservoirs for topically applied drugs and cosmetics.

  14. Source-space ICA for MEG source imaging.

    Science.gov (United States)

    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.

  15. EEG Source Analysis

    OpenAIRE

    Congedo, Marco

    2013-01-01

    Electroencephalographic data recorded on the human scalp can be modeled as a linear mixture of underlying dipolar source generators. The characterization of such generators is the aim of several families of signal processing methods. In this HDR we consider in several details three of such families, namely 1) EEG distributed inverse solutions, 2) diagonalization methods, including spatial filtering and blind source separation and 3) Riemannian geometry. We highlight our contributions in each ...

  16. MEG-based identification of the epileptogenic zone in occult peri-insular epilepsy.

    Science.gov (United States)

    Heers, Marcel; Rampp, Stefan; Stefan, Hermann; Urbach, Horst; Elger, Christian E; von Lehe, Marec; Wellmer, Jörg

    2012-03-01

    Presurgical work-ups of patients with pharmacoresistant epileptic seizures can require multiple diagnostic methods if magnetic resonance imaging (MRI) combined with video-EEG monitoring fails to show an epileptogenic lesion. Yet, the added value of available methods is not clear. In particular, only a minority of epilepsy centres apply magnetoencephalography (MEG). This study explores the potential of MEG for patients whose previous sophisticated work-ups missed deep-seated, peri-insular epileptogenic lesions. Three patients with well documented, frequent, stereotypical hypermotor seizures without clear focus hypotheses after repeated presurgical work-ups including video-EEG-monitoring, 3Tesla (3T) magnetic resonance imaging (MRI), morphometric MRI analysis, PET and SPECT were referred to MEG source localisation. In two out of three patients, MEG source localisation identified very subtle morphological abnormalities formerly missed in MRI or classified as questionable pathology. In the third patient, MEG was not reliable due to insufficient detection of epileptic patterns. Here, a 1 mm × 1 mm × 1 mm 3T fluid-attenuated inversion recovery (FLAIR) MRI revealed a potential epileptogenic lesion. A minimal invasive work-up via lesion-focused depth electrodes confirmed the intralesional seizure onset in all patients, and histology revealed dysplastic lesions. Seizure outcomes were Engel 1a in two patients, and Engel 1d in the third. MEG can contribute to the identification of epileptogenic lesions even when multiple previous methods failed, and when the lesions are located in deep anatomical structures such as peri-insular cortex. For epilepsy centres without MEG capability, referral of patients with cryptogenic focal epilepsies to centres with MEG systems may be indicated. Copyright © 2011 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

  17. EEG and intelligence: relations between EEG coherence, EEG phase delay and power.

    Science.gov (United States)

    Thatcher, R W; North, D; Biver, C

    2005-09-01

    There are two inter-related categories of EEG measurement: 1, EEG currents or power and; 2, EEG network properties such as coherence and phase delays. The purpose of this study was to compare the ability of these two different categories of EEG measurement to predict performance on the Weschler Intelligence test (WISC-R). Resting eyes closed EEG was recorded from 19 scalp locations with a linked ears reference from 442 subjects aged 5-52 years. The Weschler Intelligence test was administered to the same subjects but not while the EEG was recorded. Subjects were divided into high IQ (> or = 120) and low IQ ( EEG coherence > EEG amplitude asymmetry > absolute power > relative power and power ratios. The strongest correlations to IQ were short EEG phase delays in the frontal lobes and long phase delays in the posterior cortical regions, reduced coherence and increased absolute power. The findings are consistent with increased neural efficiency and increased brain complexity as positively related to intelligence, and with frontal lobe synchronization of neural resources as a significant contributing factor to EEG and intelligence correlations. Quantitative EEG predictions of intelligence provide medium to strong effect size estimates of cognitive functioning while simultaneously revealing a deeper understanding of the neurophysiological substrates of intelligence.

  18. Core temperature affects scalp skin temperature during scalp cooling

    NARCIS (Netherlands)

    Daanen, H.A.M.; Peerbooms, M.; van den Hurk, C.J.G.; van Os, B.; Levels, K.; Teunissen, L.P.J.; Breed, W.P.M.

    2015-01-01

    Background: The efficacy of hair loss prevention by scalp cooling to prevent chemotherapy induced hair loss has been shown to be related to scalp skin temperature. Scalp skin temperature, however, is dependent not only on local cooling but also on the thermal status of the body. Objectives: This

  19. Angiosarcoma of the Scalp

    DEFF Research Database (Denmark)

    Andersen, Kim Francis; Albrecht-Beste, Elisabeth; Berthelsen, Anne Kiil

    2015-01-01

    Angiosarcomas are rare and only represent about 2% of all soft tissue sarcomas. They arise from vascular or lymphatic endothelial cells and are most commonly located in the heart, liver, breast, and skin. Cutaneous angiosarcoma of the scalp is highly malignant and with dismal prognosis. Reported ...

  20. On not showing scalps

    DEFF Research Database (Denmark)

    Marselis, Randi Lorenz

    2016-01-01

    makes. This article examines how the National Museum of Denmark attempted to inform and discuss with the Danish public the museum’s decision to not exhibit scalps in their temporary exhibition on Native American culture, Powwow: We Dance, We’re Alive. Building on the new, contingent museum ethics...

  1. Core temperature affects scalp skin temperature during scalp cooling.

    Science.gov (United States)

    Daanen, Hein A M; Peerbooms, Mijke; van den Hurk, Corina J G; van Os, Bernadet; Levels, Koen; Teunissen, Lennart P J; Breed, Wim P M

    2015-08-01

    The efficacy of hair loss prevention by scalp cooling to prevent chemotherapy induced hair loss has been shown to be related to scalp skin temperature. Scalp skin temperature, however, is dependent not only on local cooling but also on the thermal status of the body. This study was conducted to investigate the effect of body temperature on scalp skin temperature. We conducted experiments in which 13 healthy subjects consumed ice slurry to lower body temperature for 15 minutes after the start of scalp cooling and then performed two 12-minute cycle exercise sessions to increase body core temperature. Esophageal temperature (Tes ), rectal temperature (Tre ), mean skin temperature (eight locations, Tskin ), and mean scalp temperature (five locations, Tscalp ) were recorded. During the initial 10 minutes of scalp cooling, Tscalp decreased by >15 °C, whereas Tes decreased by 0.2 °C. After ice slurry ingestion, Tes , Tre , and Tskin were 35.8, 36.5, and 31.3 °C, respectively, and increased after exercise to 36.3, 37.3, and 33.0 °C, respectively. Tscalp was significantly correlated to Tes (r = 0.39, P scalp cooling contributes to the decrease in scalp temperature and may improve the prevention of hair loss. This may be useful if the desired decrease of scalp temperature cannot be obtained by scalp cooling systems. © 2015 The International Society of Dermatology.

  2. EEG recorded from the ear: Characterizing the ear-EEG method

    Directory of Open Access Journals (Sweden)

    Kaare Bjarke Mikkelsen

    2015-11-01

    Full Text Available A method for measuring electroencephalograms (EEG from the outer ear, so-called ear-EEG, has recently been proposed. The method could potentially enable robust recording of EEG in natural environments. The objective of this study was to substantiate the ear-EEG method by using a larger population of subjects and several paradigms. For rigour, we considered simultaneous scalp and ear-EEG recordings with common reference. More precisely, 32 conventional scalp electrodes and 12 ear electrodes allowed a thorough comparison between conventional and ear electrodes, testing several different placements of references.The paradigms probed of auditory onset response, mismatch negativity, auditory steady state response and alpha power attenuation.By comparing event related potential (ERP waveforms from the mismatch response paradigm, the signal measured from the ear electrodes was found to reflect the same cortical activity as that from nearby scalp electrodes. It was also found that referencing the ear-EEG electrodes to another within-ear electrode affects the time-domain recorded waveform (relative to scalp recordings, but not the timing of individual components. It was furthermore found that auditory steady state responses and alpha-band modulation were measured reliably with the ear-EEG modality. Finally, our findings showed that the auditory mismatch response was difficult to monitor with the ear-EEG. We conclude that ear-EEG yields similar performance as conventional EEG for spectrogram-based analysis, similar timing of ERP components, and equal signal strength for sources close to the ear. Ear-EEG can reliably measure activity from regions of the cortex which are located close to the ears, especially in paradigms employing frequency-domain analyses.

  3. Ørsteds Yin & Yang: MEG & TMS

    DEFF Research Database (Denmark)

    Bailey, Christopher; Pallesen, Karen Johanne

    2011-01-01

    A portrait of magnetoencephalography (MEG) and transcranial magnetic stimulation (TMS) from a (bio)physical point of view.......A portrait of magnetoencephalography (MEG) and transcranial magnetic stimulation (TMS) from a (bio)physical point of view....

  4. Virtual EEG: A Software-Based Electroencephalogram Designed for Undergraduate Neuroscience-Related Courses

    OpenAIRE

    Miller, Benjamin R.; Troyer, Melissa; Busey, Thomas

    2008-01-01

    A current topic in neuroscience addresses the link between brain activity and visual awareness. The electroencephalogram (EEG), which uses non-invasive high temporal resolution scalp recordings to measure brain activity, is a common tool used to probe this question. EEG recordings, however, are difficult to implement in the curriculum of laboratory-based courses. Thus, undergraduate students often lack experience with EEG experiments. We report here an EEG program (Virtual EEG) that can be us...

  5. Multi-modal Patient Cohort Identification from EEG Report and Signal Data

    OpenAIRE

    Goodwin, Travis R.; Harabagiu, Sanda M

    2017-01-01

    Clinical electroencephalography (EEG) is the most important investigation in the diagnosis and management of epilepsies. An EEG records the electrical activity along the scalp and measures spontaneous electrical activity of the brain. Because the EEG signal is complex, its interpretation is known to produce moderate inter-observer agreement among neurologists. This problem can be addressed by providing clinical experts with the ability to automatically retrieve similar EEG signals and EEG rep...

  6. 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

  7. Correlation between intra- and extracranial background EEG

    DEFF Research Database (Denmark)

    Duun-Henriksen, Jonas; Kjaer, Troels Wesenberg; Madsen, Rasmus Elsborg

    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...

  8. Malignant nodular hidradenoma of scalp

    Directory of Open Access Journals (Sweden)

    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.

  9. Neonatal scalp haematoma and necrosis.

    Science.gov (United States)

    Schönmeyr, Björn; Becker, Magnus; Svensson, Henry

    2014-12-01

    Birth trauma after prolonged deliveries and instrument-assisted extractions can result in skin lesions and reduced viability of the scalp. In these instances, scalp swellings and haematomas are often also seen. The classification and inter-relationship between these conditions might not, however, always be clear. This report describes three cases of neonates with scalp swellings and necrosis. Nomenclature, underlying causes, work up, treatment options, and outcomes are presented and discussed. The first case consisted of a newborn with a subgaleal haematoma and occipital pressure necrosis that healed by secondary intention. In the second case, an infected scalp haematoma led to scarring and alopecia that required secondary reconstruction with tissue expansion. The third neonate suffered from a subgaleal haematoma and a scalp lesion that required split skin grafting and secondary reconstruction with tissue expansion.

  10. EEG-fMRI validation studies in comparison with icEEG: a review.

    Science.gov (United States)

    Zhang, Jing; Liu, Weifang; Chen, Hui; Xia, Hong; Zhou, Zhen; Wang, Lei; Mei, Shanshan; Liu, Qingzhu; Li, Yunlin

    2012-06-01

    Simultaneous EEG-fMRI is a non-invasive investigation technique developed to localize the generators of interictal epileptiform discharges (IED) in patients with epilepsy. Although the value of EEG-fMRI in epilepsy presurgical evaluation is being assessed clinically, its utility is still controversial. In this review, we considered EEG-fMRI applications in epilepsy presurgical evaluation with a focus on validation studies that compared the results of EEG-fMRI with those of the current "gold standard" intracranial EEG (icEEG) in order to assess its utility of seizure focus localization and the possibility for EEG-fMRI to reduce the need for invasive techniques such as icEEG. Since the advances of EEG-fMRI partially rely on the maturation of its data analysis, we also reviewed the methodological developments in EEG-fMRI analysis. It is possible that combining with other neuroimaging modalities such as MEG/MSI and ESI, EEG-fMRI may play a greater role in epilepsy presurgical evaluation. Copyright © 2012 Elsevier B.V. All rights reserved.

  11. Source counting in MEG neuroimaging

    Science.gov (United States)

    Lei, Tianhu; Dell, John; Magee, Ralphy; Roberts, Timothy P. L.

    2009-02-01

    Magnetoencephalography (MEG) is a multi-channel, functional imaging technique. It measures the magnetic field produced by the primary electric currents inside the brain via a sensor array composed of a large number of superconducting quantum interference devices. The measurements are then used to estimate the locations, strengths, and orientations of these electric currents. This magnetic source imaging technique encompasses a great variety of signal processing and modeling techniques which include Inverse problem, MUltiple SIgnal Classification (MUSIC), Beamforming (BF), and Independent Component Analysis (ICA) method. A key problem with Inverse problem, MUSIC and ICA methods is that the number of sources must be detected a priori. Although BF method scans the source space on a point-to-point basis, the selection of peaks as sources, however, is finally made by subjective thresholding. In practice expert data analysts often select results based on physiological plausibility. This paper presents an eigenstructure approach for the source number detection in MEG neuroimaging. By sorting eigenvalues of the estimated covariance matrix of the acquired MEG data, the measured data space is partitioned into the signal and noise subspaces. The partition is implemented by utilizing information theoretic criteria. The order of the signal subspace gives an estimate of the number of sources. The approach does not refer to any model or hypothesis, hence, is an entirely data-led operation. It possesses clear physical interpretation and efficient computation procedure. The theoretical derivation of this method and the results obtained by using the real MEG data are included to demonstrates their agreement and the promise of the proposed approach.

  12. On the Potential of a New Generation of Magnetometers for MEG: A Beamformer Simulation Study.

    Directory of Open Access Journals (Sweden)

    Elena Boto

    Full Text Available Magnetoencephalography (MEG is a sophisticated tool which yields rich information on the spatial, spectral and temporal signatures of human brain function. Despite unique potential, MEG is limited by a low signal-to-noise ratio (SNR which is caused by both the inherently small magnetic fields generated by the brain, and the scalp-to-sensor distance. The latter is limited in current systems due to a requirement for pickup coils to be cryogenically cooled. Recent work suggests that optically-pumped magnetometers (OPMs might be a viable alternative to superconducting detectors for MEG measurement. They have the advantage that sensors can be brought to within ~4 mm of the scalp, thus offering increased sensitivity. Here, using simulations, we quantify the advantages of hypothetical OPM systems in terms of sensitivity, reconstruction accuracy and spatial resolution. Our results show that a multi-channel whole-head OPM system offers (on average a fivefold improvement in sensitivity for an adult brain, as well as clear improvements in reconstruction accuracy and spatial resolution. However, we also show that such improvements depend critically on accurate forward models; indeed, the reconstruction accuracy of our simulated OPM system only outperformed that of a simulated superconducting system in cases where forward field error was less than 5%. Overall, our results imply that the realisation of a viable whole-head multi-channel OPM system could generate a step change in the utility of MEG as a means to assess brain electrophysiological activity in health and disease. However in practice, this will require both improved hardware and modelling algorithms.

  13. 21 CFR 882.4150 - Scalp clip.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Scalp clip. 882.4150 Section 882.4150 Food and... NEUROLOGICAL DEVICES Neurological Surgical Devices § 882.4150 Scalp clip. (a) Identification. A scalp clip is a plastic or metal clip used to stop bleeding during surgery on the scalp. (b) Classification. Class II...

  14. A Robustness Comparison of Two Algorithms Used for EEG Spike Detection

    OpenAIRE

    Chaibi, Sahbi; Lajnef, Tarek; Ghrob, Abdelbacet; Samet, Mounir; Kachouri, Abdennaceur

    2015-01-01

    Spikes and sharp waves recorded on scalp EEG may play an important role in identifying the epileptogenic network as well as in understanding the central nervous system. Therefore, several automatic and semi-automatic methods have been implemented to detect these two neural transients. A consistent gold standard associated with a high degree of agreement among neuroscientists is required to measure relevant performance of different methods. In fact, scalp EEG data can often be corrupted by a s...

  15. Computer assisted interpretation of the human EEG: improving diagnostic efficiency and consistency in clinical reviews

    NARCIS (Netherlands)

    Lodder, Shaun

    2014-01-01

    Scalp electroencephalography (EEG) measures brain activity non-invasively by using electrodes on the scalp and capturing small electrical fluctuations caused by the firing of neurons. From these recordings, a clinical neurophysiologist can study the captured patterns and waveforms and determine if

  16. Source reconstruction accuracy of MEG and EEG Bayesian inversion approaches.

    Directory of Open Access Journals (Sweden)

    Paolo Belardinelli

    Full Text Available Electro- and magnetoencephalography allow for non-invasive investigation of human brain activation and corresponding networks with high temporal resolution. Still, no correct network detection is possible without reliable source localization. In this paper, we examine four different source localization schemes under a common Variational Bayesian framework. A Bayesian approach to the Minimum Norm Model (MNM, an Empirical Bayesian Beamformer (EBB and two iterative Bayesian schemes (Automatic Relevance Determination (ARD and Greedy Search (GS are quantitatively compared. While EBB and MNM each use a single empirical prior, ARD and GS employ a library of anatomical priors that define possible source configurations. The localization performance was investigated as a function of (i the number of sources (one vs. two vs. three, (ii the signal to noise ratio (SNR; 5 levels and (iii the temporal correlation of source time courses (for the cases of two or three sources. We also tested whether the use of additional bilateral priors specifying source covariance for ARD and GS algorithms improved performance. Our results show that MNM proves effective only with single source configurations. EBB shows a spatial accuracy of few millimeters with high SNRs and low correlation between sources. In contrast, ARD and GS are more robust to noise and less affected by temporal correlations between sources. However, the spatial accuracy of ARD and GS is generally limited to the order of one centimeter. We found that the use of correlated covariance priors made no difference to ARD/GS performance.

  17. MEG and EEG data analysis with MNE-Python

    National Research Council Canada - National Science Library

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

    2013-01-01

    .... 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...

  18. Characterizing Neural Entrainment to Hierarchical Linguistic Units using Electroencephalography (EEG

    Directory of Open Access Journals (Sweden)

    Nai Ding

    2017-09-01

    Full Text Available To understand speech, listeners have to combine the words they hear into phrases and sentences. Recent magnetoencephalography (MEG and electrocorticography (ECoG studies show that cortical activity is concurrently entrained/synchronized to the rhythms of multiple levels of linguistic units including words, phrases, and sentences. Here we investigate whether this phenomenon can be observed using electroencephalography (EEG, a technique that is more widely available than MEG and ECoG. We show that the EEG responses concurrently track the rhythms of hierarchical linguistic units such as syllables/words, phrases, and sentences. The strength of the sentential-rate response correlates with how well each subject can detect random words embedded in a sequence of sentences. In contrast, only a syllabic-rate response is observed for an unintelligible control stimulus. In sum, EEG provides a useful tool to characterize neural encoding of hierarchical linguistic units, potentially even in individual participants.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

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

    2017-06-01

    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. 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. 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. 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.

  1. Risk Acceptance and Expectations of Scalp Allotransplantation.

    Science.gov (United States)

    Choi, Jun Ho; Kim, Kwang Seog; Shin, Jun Ho; Hwang, Jae Ha; Lee, Sam Yong

    2016-06-01

    In scalp allotransplantation, the scalp from a brain-dead donor, including hair, is transferred to a recipient with scalp defects. Opinions differ on the appropriateness of scalp allotransplantation. In order to maintain graft function and cosmetic outcomes, scalp transplantation recipients would need to receive lifelong immunosuppression treatments. The risks of this immunosuppression have to be balanced against the fact that receiving a scalp allotransplant does not extend lifespan or restore a physical function. Therefore, the present study aimed to investigate risk acceptance and expectations regarding scalp allotransplantation in different populations. A questionnaire survey study was conducted. A total of 300 subjects participated; survey was conducted amongst the general public (n=100), kidney transplantation recipients (n=50), a group of patient who required scalp reconstruction due to tumor or trauma (n=50), and physicians (n=100). The survey was modified by using the Korean version of the Louisville instrument for transplantation questionnaire. Risk acceptance and expectations for scalp transplantation varied widely across the groups. Kidney transplantation recipients revealed the highest risk acceptance and expectations, whereas the physicians were most resistant to the risks of scalp transplantation. Our study demonstrates that, in specific groups, scalp allotransplantation and the need for immunosuppression carries an acceptable risk despite the lack of lifeextending benefits. Our results suggest that scalp allotransplantation can be an acceptable alternative to existing scalp reconstruction surgeries in patients with pre-existing need for immunosuppression.

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

    Science.gov (United States)

    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.

  3. Actinic keratosis on the scalp (image)

    Science.gov (United States)

    ... sunshine. Areas with high exposure such as the scalp (bald individuals), forearms, face, and back of the ... damaged and produces lesions like these on the scalp. The lesions, called actinic keratosis, may later become ...

  4. Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements

    Energy Technology Data Exchange (ETDEWEB)

    Taulu, S; Simola, J [Elekta Neuromag Oy, Helsinki (Finland)

    2006-04-07

    Limitations of traditional magnetoencephalography (MEG) exclude some important patient groups from MEG examinations, such as epilepsy patients with a vagus nerve stimulator, patients with magnetic particles on the head or having magnetic dental materials that cause severe movement-related artefact signals. Conventional interference rejection methods are not able to remove the artefacts originating this close to the MEG sensor array. For example, the reference array method is unable to suppress interference generated by sources closer to the sensors than the reference array, about 20-40 cm. The spatiotemporal signal space separation method proposed in this paper recognizes and removes both external interference and the artefacts produced by these nearby sources, even on the scalp. First, the basic separation into brain-related and external interference signals is accomplished with signal space separation based on sensor geometry and Maxwell's equations only. After this, the artefacts from nearby sources are extracted by a simple statistical analysis in the time domain, and projected out. Practical examples with artificial current dipoles and interference sources as well as data from real patients demonstrate that the method removes the artefacts without altering the field patterns of the brain signals.

  5. Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements

    Science.gov (United States)

    Taulu, S.; Simola, J.

    2006-04-01

    Limitations of traditional magnetoencephalography (MEG) exclude some important patient groups from MEG examinations, such as epilepsy patients with a vagus nerve stimulator, patients with magnetic particles on the head or having magnetic dental materials that cause severe movement-related artefact signals. Conventional interference rejection methods are not able to remove the artefacts originating this close to the MEG sensor array. For example, the reference array method is unable to suppress interference generated by sources closer to the sensors than the reference array, about 20-40 cm. The spatiotemporal signal space separation method proposed in this paper recognizes and removes both external interference and the artefacts produced by these nearby sources, even on the scalp. First, the basic separation into brain-related and external interference signals is accomplished with signal space separation based on sensor geometry and Maxwell's equations only. After this, the artefacts from nearby sources are extracted by a simple statistical analysis in the time domain, and projected out. Practical examples with artificial current dipoles and interference sources as well as data from real patients demonstrate that the method removes the artefacts without altering the field patterns of the brain signals.

  6. Scalp psoriasis, clinical presentations and therapeutic management

    NARCIS (Netherlands)

    van de Kerkhof, P. C.; de Hoop, D.; de Korte, J.; Kuipers, M. V.

    1998-01-01

    The scalp is a well-known predilection site for psoriasis. Many patients indicate that scalp psoriasis is both psychologically and socially distressing. The aim of the present investigation is to provide epidemiological data on the various manifestations of scalp psoriasis, as well as on its

  7. A Hierarchical Bayesian M/EEG Imaging Method Correcting for Incomplete Spatio-Temporal Priors

    DEFF Research Database (Denmark)

    Stahlhut, Carsten; Attias, Hagai T.; Sekihara, Kensuke

    2013-01-01

    In this paper we present a hierarchical Bayesian model, to tackle the highly ill-posed problem that follows with MEG and EEG source imaging. Our model promotes spatiotemporal patterns through the use of both spatial and temporal basis functions. While in contrast to most previous spatio-temporal ......In this paper we present a hierarchical Bayesian model, to tackle the highly ill-posed problem that follows with MEG and EEG source imaging. Our model promotes spatiotemporal patterns through the use of both spatial and temporal basis functions. While in contrast to most previous spatio...

  8. Granuloma faciale of the scalp.

    Science.gov (United States)

    Leite, Inês; Moreira, Ana; Guedes, Rita; Furtado, Antónia; Ferreira, Eduarda Osório; Baptista, Armando

    2011-04-15

    Granuloma faciale (GF) is an uncommon dermatosis with characteristic clinicopathological features. Extrafacial isolated GF is extremely rare. Pulsed dye laser (PDL) is a treatment option for GF to minimize the risk of scarring. We report a case of a 78-year-old male with an extensive GF of the scalp successfully treated with pulsed dye laser (PDL).

  9. Treatment of multiple scalp cylindroma

    Directory of Open Access Journals (Sweden)

    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.

  10. Real-Time Epileptic Seizure Detection Using EEG.

    Science.gov (United States)

    Vidyaratne, Lasitha S; Iftekharuddin, Khan M

    2017-11-01

    This paper proposes a novel patient-specific real-time automatic epileptic seizure onset detection, using both scalp and intracranial electroencephalogram (EEG). The proposed technique obtains harmonic multiresolution and self-similarity-based fractal features from EEG for robust seizure onset detection. A fast wavelet decomposition method, known as harmonic wavelet packet transform (HWPT), is computed based on Fourier transform to achieve higher frequency resolutions without recursive calculations. Similarly, fractal dimension (FD) estimates are obtained to capture self-similar repetitive patterns in the EEG signal. Both FD and HWPT energy features across all EEG channels at each epoch are organized following the spatial information due to electrode placement on the skull. The final feature vector combines feature configurations of each epoch within the specified moving window to reflect the temporal information of EEG. Finally, relevance vector machine is used to classify the feature vectors due to its efficiency in classifying sparse, yet high-dimensional data sets. The algorithm is evaluated using two publicly available long-term scalp EEG (data set A) and short-term intracranial and scalp EEG (data set B) databases. The proposed algorithm is effective in seizure onset detection with 96% sensitivity, 0.1 per hour median false detection rate, and 1.89 s average detection latency, respectively. Results obtained from analyzing the short-term data offer 99.8% classification accuracy. These results demonstrate that the proposed method is effective with both short- and long-term EEG signal analyzes recorded with either scalp or intracranial modes, respectively. Finally, the use of less computationally intensive feature extraction techniques enables faster seizure onset detection when compared with similar techniques in the literature, indicating potential usage in real-time applications.

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

    Science.gov (United States)

    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.

  12. Revealing time-unlocked brain activity from MEG measurements by common waveform estimation.

    Directory of Open Access Journals (Sweden)

    Yusuke Takeda

    Full Text Available Brain activities related to cognitive functions, such as attention, occur with unknown and variable delays after stimulus onsets. Recently, we proposed a method (Common Waveform Estimation, CWE that could extract such brain activities from magnetoencephalography (MEG or electroencephalography (EEG measurements. CWE estimates spatiotemporal MEG/EEG patterns occurring with unknown and variable delays, referred to here as unlocked waveforms, without hypotheses about their shapes. The purpose of this study is to demonstrate the usefulness of CWE for cognitive neuroscience. For this purpose, we show procedures to estimate unlocked waveforms using CWE and to examine their role. We applied CWE to the MEG epochs during Go trials of a visual Go/NoGo task. This revealed unlocked waveforms with interesting properties, specifically large alpha oscillations around the temporal areas. To examine the role of the unlocked waveform, we attempted to estimate the strength of the brain activity of the unlocked waveform in various conditions. We made a spatial filter to extract the component reflecting the brain activity of the unlocked waveform, applied this spatial filter to MEG data under different conditions (a passive viewing, a simple reaction time, and Go/NoGo tasks, and calculated the powers of the extracted components. Comparing the powers across these conditions suggests that the unlocked waveforms may reflect the inhibition of the task-irrelevant activities in the temporal regions while the subject attends to the visual stimulus. Our results demonstrate that CWE is a potential tool for revealing new findings of cognitive brain functions without any hypothesis in advance.

  13. EEG Projekt

    OpenAIRE

    Fogh, Kasper Wandahl; Greve, Marc

    2014-01-01

    This project is investigating EEG-technology, and how this can be used in games. Specificly, we are investigating how EEG measures brain activity, how you can interact with the technology and how good it works. Furthermore we investigate how the interaction can be used in a game. We investigate through theory on EEG, classification algorithms, Emotivs software and our own game working with both active and passive interaction. We found that even though the technology is new at a consumerlev...

  14. The Itchy scalp - scratching for an explanation

    Science.gov (United States)

    saif, Ghada A. Bin; Ericson, Marna E.; Yosipovitch, Gil

    2011-01-01

    Scalp pruritus is a common complaint that is considered a diagnostically and therapeutically challenging situation. Scalp skin has a unique neural structure that contains densely innervated hair follicles and dermal vasculature. In spite of the recent advances in our understanding of itch pathophysiology, scalp itching has not been studied as yet. In this review, we summarize the current knowledge on the neurobiology of scalp and hair follicles as well as itch mediators and provide a putative mechanism for scalp itch with special emphasis on neuroanatomy and pathophysiology. PMID:22092575

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

    OpenAIRE

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

    2015-01-01

    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...

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

    OpenAIRE

    Lepage, Kyle Q.; Kramer, Mark Nathan; Chu, Catherine Jean

    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...

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  18. Intra-cortical propagation of EEG alpha oscillations

    NARCIS (Netherlands)

    Hindriks, Rikkert; van Putten, Michel Johannes Antonius Maria; Deco, G.

    2014-01-01

    The most salient feature of spontaneous human brain activity as recorded with electroencephalography (EEG) are rhythmic fluctuations around 10 Hz. These alpha oscillations have been reported to propagate over the scalp with velocities in the range of 5–15 m/s. Since these velocities are in the range

  19. 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...

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

    Science.gov (United States)

    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.

  1. Canonical Source Reconstruction for MEG

    Directory of Open Access Journals (Sweden)

    Jérémie Mattout

    2007-01-01

    Full Text Available We describe a simple and efficient solution to the problem of reconstructing electromagnetic sources into a canonical or standard anatomical space. Its simplicity rests upon incorporating subject-specific anatomy into the forward model in a way that eschews the need for cortical surface extraction. The forward model starts with a canonical cortical mesh, defined in a standard stereotactic space. The mesh is warped, in a nonlinear fashion, to match the subject's anatomy. This warping is the inverse of the transformation derived from spatial normalization of the subject's structural MRI image, using fully automated procedures that have been established for other imaging modalities. Electromagnetic lead fields are computed using the warped mesh, in conjunction with a spherical head model (which does not rely on individual anatomy. The ensuing forward model is inverted using an empirical Bayesian scheme that we have described previously in several publications. Critically, because anatomical information enters the forward model, there is no need to spatially normalize the reconstructed source activity. In other words, each source, comprising the mesh, has a predetermined and unique anatomical attribution within standard stereotactic space. This enables the pooling of data from multiple subjects and the reporting of results in stereotactic coordinates. Furthermore, it allows the graceful fusion of fMRI and MEG data within the same anatomical framework.

  2. EEG deblurring techniques in a clinical context.

    Science.gov (United States)

    Cincotti, F; Babiloni, C; Miniussi, C; Carducci, F; Moretti, D; Salinari, S; Pascual-Marqui, R; Rossini, P M; Babiloni, F

    2004-01-01

    EEG scalp potential distributions recorded in humans are affected by low spatial resolution and by the dependence on the electrical reference used. High resolution EEG technologies are available to drastically increase the spatial resolution of the raw EEG. Such technologies include the computation of surface Laplacian (SL) of the recorded potentials, as well as the use of realistic head models to estimate the cortical sources via linear inverse procedure (low resolution brain electromagnetic tomography, LORETA). However, these deblurring procedures are generally used in conjunction with EEG recordings with 64-128 scalp electrodes and with realistic head models obtained via sequential magnetic resonance images (MRIs) of the subjects. Such recording setup it is not often available in the clinical context, due to both the unavailability of these technologies and the scarce compliance of the patients with them. In this study we addressed the use of SL and LORETA deblurring techniques to analyze data from a standard 10-20 system (19 electrodes) in a group of Alzheimer disease (AD) patients. EEG data related to unilateral finger movements were gathered from 10 patients affected by AD. SL and LORETA techniques were applied for source estimation of EEG data. The use of MRIs for the construction of head models was avoided by using the quasi-realistic head model of the Brain Imaging Neurology Institute of Montreal. A similar cortical activity estimated by the SL and LORETA techniques was observed during an identical time period of the acquired EEG data in the examined population. The results of the present study suggest that both SL and LORETA approaches can be usefully applied in the clinical context, by using quasi-realistic head modeling and a standard 10-20 system as electrode montage (19 electrodes). These results represent a reciprocal cross-validation of the two mathematically independent techniques in a clinical environment.

  3. Detection of epileptiform activity by human interpreters: blinded comparison between electroencephalography and magnetoencephalography.

    Science.gov (United States)

    Iwasaki, Masaki; Pestana, Elia; Burgess, Richard C; Lüders, Hans O; Shamoto, Hiroshi; Nakasato, Nobukazu

    2005-01-01

    Objectively to evaluate whether independent spike detection by human interpreters is clinically valid in magnetoencephalography (MEG) and to characterize detection differences between MEG and scalp electroencephalography (EEG). We simultaneously recorded scalp EEG and MEG data from 43 patients with intractable focal epilepsy. Raw EEG and MEG waveforms were reviewed independently by two experienced epileptologists, one for EEG and one for MEG, blinded to the other modality and to the clinical information. The number and localization of spikes detected by EEG and/or MEG were compared in relation to clinical diagnosis based on postoperative seizure freedom. Interictal spikes were captured in both EEG and MEG in 31, in MEG alone in eight, in EEG alone in one, and in neither modality in three patients. The number of detections ranged widely with no statistical difference between modalities. A median of 25.7% of total spikes was detectable by both modalities. Spike localization was similarly consistent with the epilepsy diagnosis in 85.2% (EEG) and 78.1% (MEG) of the patients. Inaccurate localization occurred only in those cases with very few spikes detected, especially when the detections were in one modality alone. Interictal epileptiform discharges are easily perceived in MEG. Independent spike identification in MEG can provide clinical results comparable, but not superior, to EEG. Many spikes were seen in only one modality or the other; therefore the use of both EEG and MEG may provide additional information.

  4. Detection of Correlated Sources in EEG using Combination of Beamforming and Surface Laplacian Methods

    OpenAIRE

    Murzin, Vyacheslav; Fuchs, Armin; Kelso, J. A. Scott

    2013-01-01

    Beamforming offers a way to estimate the solution to the inverse problem in EEG and MEG but is also known to perform poorly in the presence of highly correlated sources, e.g during binaural auditory stimulation, when both left and right primary auditory cortices are activated simultaneously. Surface Laplacian, or the second spatial derivative calculated from the electric potential, allows for deblurring of EEG potential recordings reducing the effects of low skull conductivity and is independ...

  5. Sonography in pathologies of scalp and hair

    Science.gov (United States)

    Wortsman, X; Wortsman, J; Matsuoka, L; Saavedra, T; Mardones, F; Saavedra, D; Guerrero, R; Corredoira, Y

    2012-01-01

    Disorders of the scalp often result in severe cosmetic interference with quality of life, creating the need for optimal medical surveillance. We tested the latest generation of ultrasound machines in patients with scalp pathology and prepared a cross-sectional library encompassing a wide assortment of conditions. Normative data on the sonographic anatomy of scalp and human hair, and important methodological considerations, are also included. PMID:22253348

  6. Usability of four commercially-oriented EEG systems.

    Science.gov (United States)

    David Hairston, W; Whitaker, Keith W; Ries, Anthony J; Vettel, Jean M; Cortney Bradford, J; Kerick, Scott E; McDowell, Kaleb

    2014-08-01

    Electroencephalography (EEG) holds promise as a neuroimaging technology that can be used to understand how the human brain functions in real-world, operational settings while individuals move freely in perceptually-rich environments. In recent years, several EEG systems have been developed that aim to increase the usability of the neuroimaging technology in real-world settings. Here, the usability of three wireless EEG systems from different companies are compared to a conventional wired EEG system, BioSemi's ActiveTwo, which serves as an established laboratory-grade 'gold standard' baseline. The wireless systems compared include Advanced Brain Monitoring's B-Alert X10, Emotiv Systems' EPOC and the 2009 version of QUASAR's Dry Sensor Interface 10-20. The design of each wireless system is discussed in relation to its impact on the system's usability as a potential real-world neuroimaging system. Evaluations are based on having participants complete a series of cognitive tasks while wearing each of the EEG acquisition systems. This report focuses on the system design, usability factors and participant comfort issues that arise during the experimental sessions. In particular, the EEG systems are assessed on five design elements: adaptability of the system for differing head sizes, subject comfort and preference, variance in scalp locations for the recording electrodes, stability of the electrical connection between the scalp and electrode, and timing integration between the EEG system, the stimulus presentation computer and other external events.

  7. Usability of four commercially-oriented EEG systems

    Science.gov (United States)

    Hairston, W. David; Whitaker, Keith W.; Ries, Anthony J.; Vettel, Jean M.; Cortney Bradford, J.; Kerick, Scott E.; McDowell, Kaleb

    2014-08-01

    Electroencephalography (EEG) holds promise as a neuroimaging technology that can be used to understand how the human brain functions in real-world, operational settings while individuals move freely in perceptually-rich environments. In recent years, several EEG systems have been developed that aim to increase the usability of the neuroimaging technology in real-world settings. Here, the usability of three wireless EEG systems from different companies are compared to a conventional wired EEG system, BioSemi’s ActiveTwo, which serves as an established laboratory-grade ‘gold standard’ baseline. The wireless systems compared include Advanced Brain Monitoring’s B-Alert X10, Emotiv Systems’ EPOC and the 2009 version of QUASAR’s Dry Sensor Interface 10-20. The design of each wireless system is discussed in relation to its impact on the system’s usability as a potential real-world neuroimaging system. Evaluations are based on having participants complete a series of cognitive tasks while wearing each of the EEG acquisition systems. This report focuses on the system design, usability factors and participant comfort issues that arise during the experimental sessions. In particular, the EEG systems are assessed on five design elements: adaptability of the system for differing head sizes, subject comfort and preference, variance in scalp locations for the recording electrodes, stability of the electrical connection between the scalp and electrode, and timing integration between the EEG system, the stimulus presentation computer and other external events.

  8. The Importance of Properly Compensating for Head Movements During MEG Acquisition Across Different Age Groups.

    Science.gov (United States)

    Larson, Eric; Taulu, Samu

    2017-03-01

    Unlike EEG sensors, which are attached to the head, MEG sensors are located outside the head surface on a fixed external device. Subject head movements during acquisition thus distort the magnetic field distributions measured by the sensors. Previous studies have looked at the effect of head movements, but no study has comprehensively looked at the effect of head movements across age groups, particularly in infants. Using MEG recordings from subjects ranging in age from 3 months through adults, here we first quantify the variability in head position as a function of age group. We then combine these measured head movements with brain activity simulations to determine how head movements bias source localization from sensor magnetic fields measured during movement. We find that large amounts of head movement, especially common in infant age groups, can result in large localization errors. We then show that proper application of head movement compensation techniques can restore localization accuracy to pre-movement levels. We also find that proper noise covariance estimation (e.g., during the baseline period) is important to minimize localization bias following head movement compensation. Our findings suggest that head position measurement during acquisition and compensation during analysis is recommended for researchers working with subject populations or age groups that could have substantial head movements. This is especially important in infant MEG studies.

  9. 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

  10. 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 both...

  11. Emotional responses as independent components in EEG

    DEFF Research Database (Denmark)

    Jensen, Camilla Birgitte Falk; Petersen, Michael Kai; Larsen, Jakob Eg

    2014-01-01

    Combine wireless neuroheadsets with smartphones that enable mobile brain imaging can potentially allow us to design cognitive interfaces which adapt to our affective responses. Neuroimaging experiments using electroencephalography (EEG) initially identified two components elicited by pleasant...... susceptible to noise if captured in a mobile context. Hypothesizing that retrieval of emotional responses in mobile usage scenarios could be enhanced through spatial filtering, we compare a standard EEG electrode based analysis against an approach based on independent component analysis (ICA). By clustering...... scalp maps and time series responses we identify neural signatures that are differentially modulated when passively viewing neutral, pleasant and unpleasant images. While early responses can be detected from the raw EEG signal we identify multiple early and late ICA components that are modulated...

  12. Sequestrated meningocele of the scalp

    Energy Technology Data Exchange (ETDEWEB)

    Alorainy, Ibrahim A. E-mail: alorainy@ksu.edu.sa

    2001-11-01

    A case of occipital sequestrated (rudimentary) meningocele in a 2-year-old girl is presented. The swelling was noticed at birth and did not grow over time. The skull radiograph showed no bone defect and ultrasound and computed tomography examinations demonstrated cystic mass with no connection to dura. The aim of this report is to draw the attention of radiology literature readers to this entity and to elaborate on the role of imaging in the preoperative assessment of such cases. The relation of sequestrated meningocele to the other conditions with ectopic meningeal tissue in the scalp is addressed.

  13. 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.

  14. Facial expression classification using EEG and gyroscope signals.

    Science.gov (United States)

    Toth, Jake; Arvaneh, Mahnaz

    2017-07-01

    In this paper muscle and gyroscope signals provided by a low cost EEG headset were used to classify six different facial expressions. Muscle activities generated by facial expressions are seen in EEG data recorded from scalp. Using the already present EEG device to classify facial expressions allows for a new hybrid brain-computer interface (BCI) system without introducing new hardware such as separate electromyography (EMG) electrodes. To classify facial expressions, time domain and frequency domain EEG data with different sampling rates were used as inputs of the classifiers. The experimental results showed that with sampling rates and classification methods optimized for each participant and feature set, high accuracy classification of facial expressions was achieved. Moreover, adding information extracted from a gyroscope embedded into the used EEG headset increased the performance by an average of 9 to 16%.

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

    Science.gov (United States)

    ... 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 ...

  16. Non-parametric permutation thresholding for adaptive nonlinear beamformer analysis on MEG revealed oscillatory neuronal dynamics in human brain.

    Science.gov (United States)

    Ishii, Ryouhei; Canuet, Leonides; Aoki, Yasunori; Ikeda, Shunichiro; Hata, Masahiro; Iwase, Masao; Takeda, Masatoshi

    2013-01-01

    Adaptive nonlinear beamformer technique for analyzing magnetoencephalography (MEG) data has been proved to be powerful tool for both brain research and clinical applications. A general method of analyzing multiple subject data with a formal statistical treatment for the group data has been developed and applied for various types of MEG data. Our latest application of this method was frontal midline theta rhythm (Fmθ), which indicates focused attention and appears widely distributed over medial prefrontal areas in EEG recordings. To localize cortical generators of the magnetic counterpart of Fmθ precisely and identify cortical sources and underlying neural activity associated with mental calculation processing (i.e., arithmetic subtraction), we applied adaptive nonlinear beamformer and permutation analysis on MEG data. As a result, it was indicated that Fmθ is generated in the dorsal anterior cingulate and adjacent medial prefrontal cortex. Gamma event-related synchronization is as an index of activation in right parietal regions subserving mental subtraction associated with basic numerical processing and number-based spatial attention. Gamma desynchronization appeared in the right lateral prefrontal cortex, likely representing a mechanism to interrupt neural activity that can interfere with the ongoing cognitive task. We suggest that the combination of adaptive nonlinear beamformer and permutation analysis on MEG data is quite powerful tool to reveal the oscillatory neuronal dynamics in human brain.

  17. Spatiotemporal analysis of the appearance of gamma-band Microstates in resting state MEG.

    Science.gov (United States)

    Kelsey, Matthew; Prior, Fred W; Larson-Prior, Linda J

    2015-01-01

    Spatiotemporal analysis of EEG signal has revealed a rich set of methods to quantify neuronal activity using spatially global topographic templates, called Microstates. These methods complement more traditional spectral analysis, which uses band limited source data to determine defining differences in band power and peak characteristics. The high sampling rate and increased resistance to high frequency noise of MEG data offers an opportunity to explore the utility of spatiotemporal analysis over a wider spectrum than in EEG. In this work, we explore the utility of representing band limited MEG source data using established microstate techniques, especially in gamma frequency bands - a range yet unexplored using these techniques. We develop methods for gauging the goodness-of-fit achieved by resultant microstate templates and demonstrate sensor-level dispersion characteristics across wide-band signals as well as across signals filtered by canonical bands. These analyses reveal that, while high-frequency-band derived microstate templates are visually lawful, they fail to exhibit important explained variance and dispersion characteristics present in low- and full-band data necessary to meet the requirements of a microstate model.

  18. Automatic sleep stage classification using ear-EEG.

    Science.gov (United States)

    Stochholm, Andreas; Mikkelsen, Kaare; Kidmose, Preben

    2016-08-01

    Sleep assessment is of great importance in the diagnosis and treatment of sleep disorders. In clinical practice this is typically performed based on polysomnography recordings and manual sleep staging by experts. This procedure has the disadvantages that the measurements are cumbersome, may have a negative influence on the sleep, and the clinical assessment is labor intensive. Addressing the latter, there has recently been encouraging progress in the field of automatic sleep staging [1]. Furthermore, a minimally obtrusive method for recording EEG from electrodes in the ear (ear-EEG) has recently been proposed [2]. The objective of this study was to investigate the feasibility of automatic sleep stage classification based on ear-EEG. This paper presents a preliminary study based on recordings from a total of 18 subjects. Sleep scoring was performed by a clinical expert based on frontal, central and occipital region EEG, as well as EOG and EMG. 5 subjects were excluded from the study because of alpha wave contamination. In one subject the standard polysomnography was supplemented by ear-EEG. A single EEG channel sleep stage classifier was implemented using the same features and the same classifier as proposed in [1]. The performance of the single channel sleep classifier based on the scalp recordings showed an 85.7 % agreement with the manual expert scoring through 10-fold inter-subject cross validation, while the performance of the ear-EEG recordings was based on a 10-fold intra-subject cross validation and showed an 82 % agreement with the manual scoring. These results suggest that automatic sleep stage classification based on ear-EEG recordings may provide similar performance as compared to single channel scalp EEG sleep stage classification. Thereby ear-EEG may be a feasible technology for future minimal intrusive sleep stage classification.

  19. Influence of the location and type of epileptogenic lesion on scalp interictal epileptiform discharges and high-frequency oscillations.

    Science.gov (United States)

    Cuello-Oderiz, Carolina; von Ellenrieder, Nicolas; Dubeau, François; Gotman, Jean

    2017-12-01

    To increase the diagnostic power of scalp electroencephalography (EEG) by investigating whether lesion type and location influence the morphology of interictal epileptic discharges (IEDs) and the likelihood that IEDs and high-frequency oscillations (HFOs) are present. We studied EEG activity in epilepsy patients with lesional epilepsy. Lesions were classified by type and by location (region and depth). We marked a maximum of 50 IEDs during deep non-rapid eye movement sleep. IEDs were identified as spikes or sharp waves with or without slow waves, or bursts of spikes or sharp waves with or without slow waves. We analyzed HFOs in the studies showing at least 50 IEDs. In 192 scalp EEG studies, the differences in the percentage of studies showing IEDs in each depth-related group were not statistically significant, whereas HFOs (55 studies) predominated in patients exhibiting superficial lesions (pinfluence the presence of IEDs, as one might expect, but it influences that of HFOs. This is explained as follows. HFOs are generated in the epileptogenic region, do not propagate, and hence are only visible on scalp EEG with superficial lesions. IEDs can result from a nearby focus or propagate from a deep generator and are therefore equally present with deep, intermediate, and superficial lesions. Additionally, IED morphology provides information in determining the lesion type. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

  20. 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.

  1. 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...

  2. Similarity Analysis of EEG Data Based on Self Organizing Map Neural Network

    OpenAIRE

    Ibrahim Salem Jahan; Michal Prilepok; Vaclav Snasel; Marek Penhaker

    2014-01-01

    The Electroencephalography (EEG) is the recording of electrical activity along the scalp. This recorded data are very complex. EEG has a big role in several applications such as in the diagnosis of human brain diseases and epilepsy. Also, we can use the EEG signals to control an external device via Brain Computer Interface (BCI) by our mind. There are many algorithms to analyse the recorded EEG data, but it still remains one of the big challenges in the world. In this article, we extended our...

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

    Science.gov (United States)

    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.

  4. 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...... 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...... the original implementation a sensitivity of 92.8% and a false positive ratio (FPR) of 0.93/h were obtained. Our extension of the algorithm rendered a 95.9% sensitivity and only 0.65 false detections per hour. Conclusion: Better seizure detection can be performed when the higher frequencies in the iEEG were...

  5. Surface and intracranial EEG spike detection based on discrete wavelet decomposition and random forest classification.

    Science.gov (United States)

    Le Douget, J E; Fouad, A; Maskani Filali, M; Pyrzowski, J; Le Van Quyen, M

    2017-07-01

    Epilepsy is a neurological disorder for which the electroencephalogram (EEG) is the most important diagnostic tool. In particular, this diagnosis heavily depends on the detection of interictal (between seizures) paroxysmal epileptic discharges (IPED) in the EEG. This is a time-consuming task requiring significant training and experience. Automatic detection of these EEG patterns would greatly assist visual inspections of human readers. We present a new method, which allows automatic detection of IPED based on discrete wavelet decomposition and a random forest classifier. The algorithm was trained and cross validated using 17 subjects with scalp EEG and 10 subjects with intracranial EEG. The performance of this method reached 62% recall and 26% precision for surface EEG subjects and 63% recall and 53% precision for intracranial EEG subjects. Thus, the method hereby proposed has great potential for diagnosis support in clinical environments.

  6. Connectivity measures in EEG microstructural sleep elements

    Directory of Open Access Journals (Sweden)

    Dimitris eSakellariou

    2016-02-01

    Full Text Available 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 characterise 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

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

    Science.gov (United States)

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

    2016-12-01

    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 by scalp cooling to prevent CIA are lacking. This study investigated the relation between scalp skin temperature and its efficacy to prevent CIA. In this explorative study, scalp skin temperature was measured during scalp cooling in 62 breast cancer patients undergoing up to six cycles of anthracycline containing chemotherapy. Scalp skin temperature was measured by using two thermocouples at both temporal sides of the head. The primary end-point was the need for a wig or other head covering. Maximal cooling was reached after 45 min and was continued for 90 min after chemotherapy infusion. The scalp skin temperature after 45 min cooling varied from 10 °C to 31 °C, resulting in a mean scalp skin temperature of 19 °C (SEM: 0,4). Intrapersonal scalp skin temperatures during cooling were consistent for each chemotherapy cycle (ANOVA: P = 0,855). Thirteen out of 62 patients (21%) did not require a wig or other head covering. They appeared to have a significantly lower mean scalp skin temperature (18 °C; SEM: 0,7) compared to patients with alopecia (20 °C; SEM: 0,5) (P = 0,01). The efficacy of scalp cooling during chemotherapy is temperature dependent. A precise cut-off point could not be detected, but the best results seem to be obtained when the scalp temperature decreases below 18 °C. TRIALREGISTER. 3082. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. Utility of Independent Component Analysis for Interpretation of Intracranial EEG

    Directory of Open Access Journals (Sweden)

    Diane eWhitmer

    2010-11-01

    Full Text Available Electrode arrays are sometimes implanted in the brains of patients with intractable epilepsy to better localize seizure foci before epilepsy surgery. Analysis of intracranial EEG (iEEG recordings is typically performed in the electrode channel domain without explicit separation of the sources that generate the signals. However, intracranial EEG signals, like scalp EEG signals, could be linear mixtures of local activity and volume conducted activity arising in multiple source areas. Independent component analysis (ICA has recently been applied to scalp EEG data, and shown to separate the signal mixtures into independently generated brain and non-brain source signals. Here, we applied ICA to un-mix source signals from intracranial EEG recordings from four epilepsy patients during a visually cued finger movement task in the presence of background pathological brain activity. This ICA decomposition demonstrated that the iEEG recordings were not maximally independent, but rather are linear mixtures of activity from multiple sources. Many of the independent component (IC projections to the iEEG recording grid were consistent with sources from single brain regions, including components exhibiting classic movement-related dynamics. Notably, the largest IC projection to each channel accounted for no more than 20%-80% of the channel signal variance, implying that in general intracranial recordings cannot be accurately interpreted as recordings of independent brain sources. These results suggest that ICA can be used to identify and monitor major field sources of local and distributed functional networks generating iEEG data. ICA decomposition methods are useful for improving the fidelity of source signals of interest, likely including distinguishing the sources of pathological brain activity.

  9. Wavelet analysis as a tool for investigating movement-related cortical oscillations in EEG-fMRI coregistration.

    Science.gov (United States)

    Storti, Silvia Francesca; Formaggio, Emanuela; Beltramello, Alberto; Fiaschi, Antonio; Manganotti, Paolo

    2010-03-01

    Electroencephalography combined with functional magnetic resonance imaging (EEG-fMRI) identifies blood oxygenation level dependent (BOLD) signal changes associated with physiological and pathological EEG events. In this study we used EEG-fMRI to determine the possible correlation between topographical movement related EEG changes in brain oscillatory activity recorded from EEG electrodes over the scalp and fMRI cortical responses in motor areas during finger movement. Thirty-two channels of EEG were recorded in 12 subjects during eyes-closed condition inside a three T magnetic resonance (MR) scanner using an MR-compatible EEG recording system. Off-line MRI artifact subtraction software was applied to obtain continuous EEG data during fMRI acquisition. For EEG data analysis we used a time-frequency approach to measure time by varying the energy in a signal at a given frequency band by the convolution of the EEG signal with a wavelet family in the alpha and beta bands. The correlation between the BOLD signal associated with the EEG regressor provides that sensory motor region is a source of the EEG. We conclude that combined EEG-fMRI can be used to investigate movement-related oscillations of the human brain inside an MRI scanner and wavelet analysis adds further details on the EEG changes. The movement-related changes in the EEG signals are useful to identify the brain activation sources responsible for BOLD-signal changes.

  10. Latest News from the MEG Experiment

    CERN Multimedia

    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.

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

    Science.gov (United States)

    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

  12. 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.

  13. Final results of the MEG experiment

    Science.gov (United States)

    Mori, Toshinori; MEG Collaboration

    2017-07-01

    Transitions of charged leptons from one generation to another are basically prohibited in the Standard Model because of the mysteriously tiny neutrino masses, although such flavor-violating transitions have long been observed for quarks and neutrinos. Supersymmetric Grand Unified Theories (SUSY GUT), which unify quarks and leptons as well as their forces, predict that charged leptons should also make such transitions at small but experimentally observable rates. The MEG experiment was the first to have explored one of such transitions, μ^+ to e^+ γ decays, down to the branching ratios predicted by SUSY GUT. Here we report the final results of the MEG experiment based on the full dataset collected from 2009 to 2013 at the Paul Scherrer Institut, corresponding to a total of 7.5× 10^{14} stopped muons on target. No excess for μ^+ to e^+ γ decays was found. Thus the most stringent upper bound was placed on the branching ratio, B( μ+_{}↦e+ γ) theories. We are now preparing the upgraded experiment MEG II with the aim to achieve a sensitivity of 4× 10^{-14} after three years of data taking. It is expected to start late in 2017.

  14. Dandruff, Cradle Cap, and Other Scalp Conditions

    Science.gov (United States)

    ... skin. Most of the time, using a dandruff shampoo can help control your dandruff. If that does ... your baby's hair every day with a mild shampoo and gently rubbing their scalp with your fingers ...

  15. 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.

  16. Scalp dysesthesia related to cervical spine disease.

    Science.gov (United States)

    Thornsberry, Laura A; English, Joseph C

    2013-02-01

    Scalp dysesthesia is characterized by abnormal sensations of the scalp in the absence of any other unusual physical examination findings. The pathogenesis of this condition is unknown but has been reported in the setting of underlying psychiatric disorders. Other localized pruritic syndromes, including brachioradial pruritus and notalgia paresthetica, have been associated with pathologic conditions of the spine and have been successfully treated with gabapentin. Among 15 women identified in a retrospective review of medical records as having been seen with scalp dysesthesia, 14 patients had cervical spine disease confirmed by imaging. The most common finding on imaging was degenerative disk disease, with 10 of 14 patients having these changes at C5-C6. Other abnormal imaging findings included anterolisthesis, osteophytic spurring, lordosis, kyphosis, and nerve root impingement. A gabapentin regimen (topical or oral) had been recommended to 14 patients; of 7 patients who were followed up, 4 patients noted improvement in symptoms when taking gabapentin. Patients with scalp dysesthesia also had abnormal cervical spine images. Chronic muscle tension placed on the pericranial muscles and scalp aponeurosis secondary to the underlying cervical spine disease may lead to the symptoms of scalp dysesthesia.

  17. Characteristic Increases in EEG Connectivity Correlate With Changes of Structural MRI in Amyotrophic Lateral Sclerosis.

    Science.gov (United States)

    Nasseroleslami, Bahman; Dukic, Stefan; Broderick, Michael; Mohr, Kieran; Schuster, Christina; Gavin, Brighid; McLaughlin, Russell; Heverin, Mark; Vajda, Alice; Iyer, Parameswaran M; Pender, Niall; Bede, Peter; Lalor, Edmund C; Hardiman, Orla

    2017-11-09

    Amyotrophic lateral sclerosis (ALS) is a terminal progressive adult-onset neurodegeneration of the motor system. Although originally considered a pure motor degeneration, there is increasing evidence of disease heterogeneity with varying degrees of extra-motor involvement. How the combined motor and nonmotor degeneration occurs in the context of broader disruption in neural communication across brain networks has not been well characterized. Here, we have performed high-density crossectional and longitudinal resting-state electroencephalography (EEG) recordings on 100 ALS patients and 34 matched controls, and have identified characteristic patterns of altered EEG connectivity that have persisted in longitudinal analyses. These include strongly increased EEG coherence between parietal-frontal scalp regions (in γ-band) and between bilateral regions over motor areas (in θ-band). Correlation with structural MRI from the same patients shows that disease-specific structural degeneration in motor areas and corticospinal tracts parallels a decrease in neural activity over scalp motor areas, while the EEG over the scalp regions associated with less extensively involved extra-motor regions on MRI exhibit significantly increased neural communication. Our findings demonstrate that EEG-based connectivity mapping can provide novel insights into progressive network decline in ALS. These data pave the way for development of validated cost-effective spectral EEG-based biomarkers that parallel changes in structural imaging. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

    Science.gov (United States)

    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.

  19. 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

  20. The relationship between local scalp skin temperature and cutaneous perfusion during scalp cooling

    NARCIS (Netherlands)

    Janssen, Francis-Paul E.M.; Rajan, Vinayakrishnan; Steenbergen, Wiendelt; van Leeuwen, Gerard M.J.; van Steenhoven, Anton A.

    2007-01-01

    Cooling the scalp during administration of chemotherapy can prevent hair loss. It reduces both skin blood flow and hair follicle temperature, thus affecting drug supply and drug effect in the hair follicle. The extent to which these mechanisms contribute to the hair preservative effect of scalp

  1. Conductive polymer foam surface improves the performance of a capacitive EEG electrode.

    Science.gov (United States)

    Baek, Hyun Jae; Lee, Hong Ji; Lim, Yong Gyu; Park, Kwang Suk

    2012-12-01

    In this paper, a new conductive polymer foam-surfaced electrode was proposed for use as a capacitive EEG electrode for nonintrusive EEG measurements in out-of-hospital environments. The current capacitive electrode has a rigid surface that produces an undefined contact area due to its stiffness, which renders it unable to conform to head curvature and locally isolates hairs between the electrode surface and scalp skin, making EEG measurement through hair difficult. In order to overcome this issue, a conductive polymer foam was applied to the capacitive electrode surface to provide a cushioning effect. This enabled EEG measurement through hair without any conductive contact with bare scalp skin. Experimental results showed that the new electrode provided lower electrode-skin impedance and higher voltage gains, signal-to-noise ratios, signal-to-error ratios, and correlation coefficients between EEGs measured by capacitive and conventional resistive methods compared to a conventional capacitive electrode. In addition, the new electrode could measure EEG signals, while the conventional capacitive electrode could not. We expect that the new electrode presented here can be easily installed in a hat or helmet to create a nonintrusive wearable EEG apparatus that does not make users look strange for real-world EEG applications.

  2. Mindfulness-induced selflessness: A MEG neurophenomenological study

    Directory of Open Access Journals (Sweden)

    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.

  3. [Mechanisms of face perception in humans: an MEG study].

    Science.gov (United States)

    Miki, Kensaku; Kakigi, Ryusuke

    2012-07-01

    In this review article, we summarize our results from magnetoencephalography (MEG) and electroencephalography (EEG) studies on face perception. The primary results were as follows: (1) facial (eye and mouth) movements are processed differently from general motion perception, but eye and mouth movements are likely processed in the same manner. (2) In a study investigating the interaction between auditory and visual stimuli relating to vowel sounds in the auditory cortex, vowel sound perception in the auditory cortex, at least in the primary processing stage, was not affected by simultaneously viewing mouth movements. (3) In a study investigating the effects of face contour and features on early occipitotemporal activity when viewing eye movement, there was evidence of specific information processing for eye movements in the occipitotemporal region, and this activity was significantly influenced by whether the movements appeared with the face contour and/or features. (4) In a study investigating the effects of inverting facial contour (hair and chin) and features (eyes, nose and mouth) on the processing of static and dynamic face perception, activity in the right fusiform area was more affected by the inversion of features, whereas activity in the left fusiform area was more affected by disruption of the spatial relationship between the contour and features in static face perception, and activity in the right occipitotemporal area was most affected by inversion of the facial contour in dynamic face perception. (5) In a study investigating the perception of changes in facial emotion, the areas of the brain involved in perceiving changes in facial emotion were found to have not matured by 14 years of age.

  4. Pediatric scalp burns: hair today, gone tomorrow?

    Science.gov (United States)

    Menon, Seema; Jacques, Madeleine; Harvey, John G; Holland, Andrew J A

    2015-01-01

    Scalp burns in the pediatric population appear relatively uncommon, with most reported cases occurring in adults secondary to electrical burns. We reviewed our experience with the management of these injuries in children. A retrospective review was conducted at our institution from March 2004 to July 2011. Scalp burns were defined as any burn crossing over the hairline into the scalp region. During the 7-year 4-month study, there were 107 scalp burns, representing 1.8% of the 6074 burns treated at our institution during that time. The cause was scald in 97, contact in 4, flame in 3, friction in 2, and chemical in 1. The majority (n = 93, 87%) appeared superficial to mid-dermal, with an average time to complete healing of 10.3 days. The remaining 14 cases (13%) were mid-dermal to full thickness, with an average time to complete healing of 50.8 days. Grafting was required in 12 cases (11%). The mean time to grafting was 4 weeks (range, 2 weeks to 2.5 months). The main complication of scalp burns was alopecia, which occurred in all grafted sites as well as in 4 patients treated conservatively. There were no other complications after grafting and no cases of graft loss. In our pediatric series, scalp burns were most commonly caused by scald injuries and were superficial to mid-dermal in depth. These generally healed rapidly but occasionally resulted in alopecia. The management of deep dermal and full-thickness scalp burns remains challenging in children, with the decision to graft often delayed.

  5. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1999-02-01

    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.

  8. Total Scalp Replantation: Surgical Tricks and Pitfalls.

    Science.gov (United States)

    Nasir, Serdar; Karaaltin, Mehmet; Erdem, Adnan

    2015-06-01

    Two patients were successfully operated on for total scalp avulsions. Ages were between 11 and 35 years, and both patients were female. Bilateral temporal artery and veins were used as the recipient pedicles. Interpositional vein graft harvested from the left forearm was used in 1 patient. No nerve repair was performed. The scalp was successfully replanted in both cases. Venous congestion and arterial insufficiency were observed in 1 patient. Successful revision of the vascular anastomosis was performed. Total necrosis of the upper helical rim was observed in 1 patient. A mean size of 3 × 3 cm of tissue necrosis was observed in the occipital region of all patients. One patient was treated with split-thickness skin grafting, whereas the other one was left for secondary healing. The "replace like tissue with like tissue" represents the philosophy in replantation surgery. Although reconstructive surgeries imply advanced surgical methods, scalp replantation remains the only ideal surgical modality to create an embellishing natural-looking hair-bearing scalp. In this article, we present some tricks and pitfalls of total avulsed scalp replantation as well as our skills and literature review.

  9. Multi-modal Patient Cohort Identification from EEG Report and Signal Data.

    Science.gov (United States)

    Goodwin, Travis R; Harabagiu, Sanda M

    2016-01-01

    Clinical electroencephalography (EEG) is the most important investigation in the diagnosis and management of epilepsies. An EEG records the electrical activity along the scalp and measures spontaneous electrical activity of the brain. Because the EEG signal is complex, its interpretation is known to produce moderate inter-observer agreement among neurologists. This problem can be addressed by providing clinical experts with the ability to automatically retrieve similar EEG signals and EEG reports through a patient cohort retrieval system operating on a vast archive of EEG data. In this paper, we present a multi-modal EEG patient cohort retrieval system called MERCuRY which leverages the heterogeneous nature of EEG data by processing both the clinical narratives from EEG reports as well as the raw electrode potentials derived from the recorded EEG signal data. At the core of MERCuRY is a novel multimodal clinical indexing scheme which relies on EEG data representations obtained through deep learning. The index is used by two clinical relevance models that we have generated for identifying patient cohorts satisfying the inclusion and exclusion criteria expressed in natural language queries. Evaluations of the MERCuRY system measured the relevance of the patient cohorts, obtaining MAP scores of 69.87% and a NDCG of 83.21%.

  10. 3D Printed Dry EEG Electrodes

    Directory of Open Access Journals (Sweden)

    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.

  11. Identifying auditory attention with ear-EEG: cEEGrid versus high-density cap-EEG comparison

    Science.gov (United States)

    Bleichner, Martin G.; Mirkovic, Bojana; Debener, Stefan

    2016-12-01

    Objective. This study presents a direct comparison of a classical EEG cap setup with a new around-the-ear electrode array (cEEGrid) to gain a better understanding of the potential of ear-centered EEG. Approach. Concurrent EEG was recorded from a classical scalp EEG cap and two cEEGrids that were placed around the left and the right ear. Twenty participants performed a spatial auditory attention task in which three sound streams were presented simultaneously. The sound streams were three seconds long and differed in the direction of origin (front, left, right) and the number of beats (3, 4, 5 respectively), as well as the timbre and pitch. The participants had to attend to either the left or the right sound stream. Main results. We found clear attention modulated ERP effects reflecting the attended sound stream for both electrode setups, which agreed in morphology and effect size. A single-trial template matching classification showed that the direction of attention could be decoded significantly above chance (50%) for at least 16 out of 20 participants for both systems. The comparably high classification results of the single trial analysis underline the quality of the signal recorded with the cEEGrids. Significance. These findings are further evidence for the feasibility of around the-ear EEG recordings and demonstrate that well described ERPs can be measured. We conclude that concealed behind-the-ear EEG recordings can be an alternative to classical cap EEG acquisition for auditory attention monitoring.

  12. EEG Source Reconstruction Performance as a Function of Skull Conductance Contrast

    DEFF Research Database (Denmark)

    Hansen, Sofie Therese; Hansen, Lars Kai

    2015-01-01

    Through simulated EEG we investigate the effect of the for-ward model’s applied skull:scalp conductivity ratio on the source reconstruction performance. We show that having a higher conductivity ratio generally leads to improvement of the solution. Additionally we see a clear connection between...... higher conductivity ratios and lower coherence, thus a reduction of the ill-posedness of the EEG inverse problem. Finally we show on real EEG data the stability of the strongest source recovered across conductivity ratios....

  13. Neglected Giant Scalp Basal Cell Carcinoma

    Directory of Open Access Journals (Sweden)

    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.

  14. Neglected giant scalp Basal cell carcinoma

    DEFF Research Database (Denmark)

    Larsen, Anne Kristine; El-Charnoubi, Waseem-Asim Ghulam; Gehl, Julie

    2014-01-01

    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...

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

    Directory of Open Access Journals (Sweden)

    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.

  16. Multifractal detrended fluctuation analysis of human EEG: preliminary investigation and comparison with the wavelet transform modulus maxima technique.

    Directory of Open Access Journals (Sweden)

    Todd Zorick

    Full Text Available Recently, many lines of investigation in neuroscience and statistical physics have converged to raise the hypothesis that the underlying pattern of neuronal activation which results in electroencephalography (EEG signals is nonlinear, with self-affine dynamics, while scalp-recorded EEG signals themselves are nonstationary. Therefore, traditional methods of EEG analysis may miss many properties inherent in such signals. Similarly, fractal analysis of EEG signals has shown scaling behaviors that may not be consistent with pure monofractal processes. In this study, we hypothesized that scalp-recorded human EEG signals may be better modeled as an underlying multifractal process. We utilized the Physionet online database, a publicly available database of human EEG signals as a standardized reference database for this study. Herein, we report the use of multifractal detrended fluctuation analysis on human EEG signals derived from waking and different sleep stages, and show evidence that supports the use of multifractal methods. Next, we compare multifractal detrended fluctuation analysis to a previously published multifractal technique, wavelet transform modulus maxima, using EEG signals from waking and sleep, and demonstrate that multifractal detrended fluctuation analysis has lower indices of variability. Finally, we report a preliminary investigation into the use of multifractal detrended fluctuation analysis as a pattern classification technique on human EEG signals from waking and different sleep stages, and demonstrate its potential utility for automatic classification of different states of consciousness. Therefore, multifractal detrended fluctuation analysis may be a useful pattern classification technique to distinguish among different states of brain function.

  17. Multifractal detrended fluctuation analysis of human EEG: preliminary investigation and comparison with the wavelet transform modulus maxima technique.

    Science.gov (United States)

    Zorick, Todd; Mandelkern, Mark A

    2013-01-01

    Recently, many lines of investigation in neuroscience and statistical physics have converged to raise the hypothesis that the underlying pattern of neuronal activation which results in electroencephalography (EEG) signals is nonlinear, with self-affine dynamics, while scalp-recorded EEG signals themselves are nonstationary. Therefore, traditional methods of EEG analysis may miss many properties inherent in such signals. Similarly, fractal analysis of EEG signals has shown scaling behaviors that may not be consistent with pure monofractal processes. In this study, we hypothesized that scalp-recorded human EEG signals may be better modeled as an underlying multifractal process. We utilized the Physionet online database, a publicly available database of human EEG signals as a standardized reference database for this study. Herein, we report the use of multifractal detrended fluctuation analysis on human EEG signals derived from waking and different sleep stages, and show evidence that supports the use of multifractal methods. Next, we compare multifractal detrended fluctuation analysis to a previously published multifractal technique, wavelet transform modulus maxima, using EEG signals from waking and sleep, and demonstrate that multifractal detrended fluctuation analysis has lower indices of variability. Finally, we report a preliminary investigation into the use of multifractal detrended fluctuation analysis as a pattern classification technique on human EEG signals from waking and different sleep stages, and demonstrate its potential utility for automatic classification of different states of consciousness. Therefore, multifractal detrended fluctuation analysis may be a useful pattern classification technique to distinguish among different states of brain function.

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

    Directory of Open Access Journals (Sweden)

    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

  19. Material and physical model for evaluation of deep brain activity contribution to EEG recordings

    Science.gov (United States)

    Ye, Yan; Li, Xiaoping; Wu, Tiecheng; Li, Zhe; Xie, Wenwen

    2015-12-01

    Deep brain activity is conventionally recorded with surgical implantation of electrodes. During the neurosurgery, brain tissue damage and the consequent side effects to patients are inevitably incurred. In order to eliminate undesired risks, we propose that deep brain activity should be measured using the noninvasive scalp electroencephalography (EEG) technique. However, the deeper the neuronal activity is located, the noisier the corresponding scalp EEG signals are. Thus, the present study aims to evaluate whether deep brain activity could be observed from EEG recordings. In the experiment, a three-layer cylindrical head model was constructed to mimic a human head. A single dipole source (sine wave, 10 Hz, altering amplitudes) was embedded inside the model to simulate neuronal activity. When the dipole source was activated, surface potential was measured via electrodes attached on the top surface of the model and raw data were recorded for signal analysis. Results show that the dipole source activity positioned at 66 mm depth in the model, equivalent to the depth of deep brain structures, is clearly observed from surface potential recordings. Therefore, it is highly possible that deep brain activity could be observed from EEG recordings and deep brain activity could be measured using the noninvasive scalp EEG technique.

  20. SDO-EVE multiple EUV grating spectrograph (MEGS) optical design

    Science.gov (United States)

    Crotser, David A.; Woods, Thomas N.; Eparvier, Francis G.; Ucker, Greg; Kohnert, Richard A.; Berthiaume, Gregory D.; Weitz, David M.

    2004-10-01

    The NASA Solar Dynamics Observatory (SDO), scheduled for launch in 2008, incorporates a suite of instruments including the EUV Variability Experiment (EVE). The EVE instrument package contains grating spectrographs used to measure the solar extreme ultraviolet (EUV) irradiance from 0.1 to 105 nm. The Multiple EUV Grating Spectrograph (MEGS) channels use concave reflection gratings to image solar spectra onto CCDs that are operated at -100°C. MEGS provides 0.1nm spectral resolution between 5-105nm every 10 seconds with an absolute accuracy of better than 25% over the SDO 5-year mission. MEGS-A utilizes a unique grazing-incidence, off-Rowland circle (RC) design to minimize angle of incidence at the detector while meeting high resolution requirements. MEGS-B utilizes a double-pass, cross-dispersed double-Rowland circle design. MEGS-P, a Ly-α monitor, will provide a proxy model calibration in the 60-105 nm range. Finally, the Solar Aspect Monitor (SAM) channel will provide continual pointing information for EVE as well as low-resolution X-ray images of the sun. In-flight calibrations for MEGS will be provided by the on-board EUV Spectrophotometer (ESP) in the 0.1-7nm and 17-37nm ranges, as well as from annual under-flight rocket experiments. We present the methodology used to develop the MEGS optical design.

  1. The standardized EEG electrode array of the IFCN.

    Science.gov (United States)

    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.

  2. Prolific plant regeneration through organogenesis from scalps of ...

    African Journals Online (AJOL)

    Prolific plant regeneration through organogenesis from scalps of Musa sp cv. Tanduk. SMA Elhory, MA Aziz, AA Rashid, AG Yunus. Abstract. A prolific plant regeneration system using scalps derived from shoot tips of Musa spp. cv. Tanduk was developed. Highly proliferating scalps, produced after four monthly subcultures ...

  3. Safety and EEG data quality of concurrent high-density EEG and high-speed fMRI at 3 Tesla.

    Directory of Open Access Journals (Sweden)

    Mette Thrane Foged

    Full Text Available Concurrent EEG and fMRI is increasingly used to characterize the spatial-temporal dynamics of brain activity. However, most studies to date have been limited to conventional echo-planar imaging (EPI. There is considerable interest in integrating recently developed high-speed fMRI methods with high-density EEG to increase temporal resolution and sensitivity for task-based and resting state fMRI, and for detecting interictal spikes in epilepsy. In the present study using concurrent high-density EEG and recently developed high-speed fMRI methods, we investigate safety of radiofrequency (RF related heating, the effect of EEG on cortical signal-to-noise ratio (SNR in fMRI, and assess EEG data quality.The study compared EPI, multi-echo EPI, multi-band EPI and multi-slab echo-volumar imaging pulse sequences, using clinical 3 Tesla MR scanners from two different vendors that were equipped with 64- and 256-channel MR-compatible EEG systems, respectively, and receive only array head coils. Data were collected in 11 healthy controls (3 males, age range 18-70 years and 13 patients with epilepsy (8 males, age range 21-67 years. Three of the healthy controls were scanned with the 256-channel EEG system, the other subjects were scanned with the 64-channel EEG system. Scalp surface temperature, SNR in occipital cortex and head movement were measured with and without the EEG cap. The degree of artifacts and the ability to identify background activity was assessed by visual analysis by a trained expert in the 64 channel EEG data (7 healthy controls, 13 patients.RF induced heating at the surface of the EEG electrodes during a 30-minute scan period with stable temperature prior to scanning did not exceed 1.0° C with either EEG system and any of the pulse sequences used in this study. There was no significant decrease in cortical SNR due to the presence of the EEG cap (p > 0.05. No significant differences in the visually analyzed EEG data quality were found between

  4. Safety and EEG data quality of concurrent high-density EEG and high-speed fMRI at 3 Tesla.

    Science.gov (United States)

    Foged, Mette Thrane; Lindberg, Ulrich; Vakamudi, Kishore; Larsson, Henrik B W; Pinborg, Lars H; Kjær, Troels W; Fabricius, Martin; Svarer, Claus; Ozenne, Brice; Thomsen, Carsten; Beniczky, Sándor; Paulson, Olaf B; Posse, Stefan

    2017-01-01

    Concurrent EEG and fMRI is increasingly used to characterize the spatial-temporal dynamics of brain activity. However, most studies to date have been limited to conventional echo-planar imaging (EPI). There is considerable interest in integrating recently developed high-speed fMRI methods with high-density EEG to increase temporal resolution and sensitivity for task-based and resting state fMRI, and for detecting interictal spikes in epilepsy. In the present study using concurrent high-density EEG and recently developed high-speed fMRI methods, we investigate safety of radiofrequency (RF) related heating, the effect of EEG on cortical signal-to-noise ratio (SNR) in fMRI, and assess EEG data quality. The study compared EPI, multi-echo EPI, multi-band EPI and multi-slab echo-volumar imaging pulse sequences, using clinical 3 Tesla MR scanners from two different vendors that were equipped with 64- and 256-channel MR-compatible EEG systems, respectively, and receive only array head coils. Data were collected in 11 healthy controls (3 males, age range 18-70 years) and 13 patients with epilepsy (8 males, age range 21-67 years). Three of the healthy controls were scanned with the 256-channel EEG system, the other subjects were scanned with the 64-channel EEG system. Scalp surface temperature, SNR in occipital cortex and head movement were measured with and without the EEG cap. The degree of artifacts and the ability to identify background activity was assessed by visual analysis by a trained expert in the 64 channel EEG data (7 healthy controls, 13 patients). RF induced heating at the surface of the EEG electrodes during a 30-minute scan period with stable temperature prior to scanning did not exceed 1.0° C with either EEG system and any of the pulse sequences used in this study. There was no significant decrease in cortical SNR due to the presence of the EEG cap (p > 0.05). No significant differences in the visually analyzed EEG data quality were found between EEG

  5. 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

    . We summarize these insights in an inverse solver, the so-called "Variational Garrote" (Kappen and Gómez, 2013). Using a Markov prior we can incorporate flexible degrees of temporal stationarity. Through spatial basis functions spatially smooth distributions are obtained. Sparsity...... of these are inherent to the Variational Garrote solver. We name our method the MarkoVG and demonstrate its ability to adapt to the temporal smoothness and spatial sparsity in simulated EEG data. Finally a benchmark EEG dataset is used to demonstrate MarkoVG's ability to recover non-stationary brain dynamics.......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...

  6. Functional Brain Imaging by EEG: A Window to the Human Mind

    DEFF Research Database (Denmark)

    Stahlhut, Carsten

    This thesis presents electroencephalography (EEG) brain imaging by covering topics as empirical evaluation of source confusion, probabilistic inverse methods, and source analysis performed on infant EEG data. In terms of source confusion we inspect how current sources within the brain may be conf...... the principled computation of sparse spatial and smooth temporal EEG source reconstructions consistent with neurophysiological assumptions in a variety of event-related imaging paradigms....... topics in EEG source reconstruction, namely, the forward progation model (describing the mapping from the current sources within the brain to the sensors at the scalp) and the temporal patterns present in the EEG. As forward models may suffer from a number of errors including the geometrical...... distributions over the unknown sources given the observed data. Here, we propose a hierarchical Bayesian model that attempts to minimize the influence of uncertainties associated with the forward model on the source estimates. Similarly, we develop a hierarchical spatio-temporal Bayesian model that accommodates...

  7. Generalized Information Equilibrium Approaches to EEG Sleep Stage Discrimination.

    Science.gov (United States)

    Zorick, Todd; Smith, Jason

    2016-01-01

    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.

  8. Corrected Four-Sphere Head Model for EEG Signals

    Directory of Open Access Journals (Sweden)

    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.

  9. Methodological aspects of EEG and Body dynamics measurements during motion.

    Directory of Open Access Journals (Sweden)

    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.

  10. Ballistocardiogram artifact removal with a reference layer and standard EEG cap.

    Science.gov (United States)

    Luo, Qingfei; Huang, Xiaoshan; Glover, Gary H

    2014-08-15

    In simultaneous EEG-fMRI, the EEG recordings are severely contaminated by ballistocardiogram (BCG) artifacts, which are caused by cardiac pulsations. To reconstruct and remove the BCG artifacts, one promising method is to measure the artifacts in the absence of EEG signal by placing a group of electrodes (BCG electrodes) on a conductive layer (reference layer) insulated from the scalp. However, current BCG reference layer (BRL) methods either use a customized EEG cap composed of electrode pairs, or need to construct the custom reference layer through additional model-building experiments for each EEG-fMRI experiment. These requirements have limited the versatility and efficiency of BRL. The aim of this study is to propose a more practical and efficient BRL method and compare its performance with the most popular BCG removal method, the optimal basis sets (OBS) algorithm. By designing the reference layer as a permanent and reusable cap, the new BRL method is able to be used with a standard EEG cap, and no extra experiments and preparations are needed to use the BRL in an EEG-fMRI experiment. The BRL method effectively removed the BCG artifacts from both oscillatory and evoked potential scalp recordings and recovered the EEG signal. Compared to the OBS, this new BRL method improved the contrast-to-noise ratios of the alpha-wave, visual, and auditory evoked potential signals by 101%, 76%, and 75%, respectively, employing 160 BCG electrodes. Using only 20 BCG electrodes, the BRL improved the EEG signal by 74%/26%/41%, respectively. The proposed method can substantially improve the EEG signal quality compared with traditional methods. Copyright © 2014 Elsevier B.V. All rights reserved.

  11. Ageing tests for the MEG II drift chamber

    Energy Technology Data Exchange (ETDEWEB)

    Venturini, M., E-mail: marco.venturini@pi.infn.it [Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126 Pisa (Italy); 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); Baracchini, E. [ICEPP, University of Tokyo 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 (Japan); Cei, F.; D' Onofrio, A. [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Dipartimento di Fisica, Universita di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Dussoni, S.; Galli, L.; Grassi, M. [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Nicolò, D. [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Dipartimento di Fisica, Universita di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Signorelli, G.; Tenchini, F. [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Zermini, A. [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Dipartimento di Fisica, Universita di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy)

    2016-07-11

    The MEG II drift chamber will track positrons from μ{sup +} decays in a very harsh environment. For testing the robustness of the chamber to ageing effects an irradiation facility was set up at INFN Pisa. - Highlights: • We built up an X-ray facility for ageing studies of particle detectors. • Stable irradiation conditions were obtained over one-month timescale. • A moderate gain loss is expected for the MEG II drift chamber.

  12. Novel hydrogel-based preparation-free EEG electrode.

    Science.gov (United States)

    Alba, Nicolas Alexander; Sclabassi, Robert J; Sun, Mingui; Cui, Xinyan Tracy

    2010-08-01

    The largest obstacles to signal transduction for electroencephalography (EEG) recording are the hair and the epidermal stratum corneum of the skin. In typical clinical situations, hair is parted or removed, and the stratum corneum is either abraded or punctured using invasive penetration devices. These steps increase preparation time, discomfort, and the risk of infection. Cross-linked sodium polyacrylate gel swelled with electrolyte was explored as a possible skin contact element for a prototype preparation-free EEG electrode. As a superabsorbent hydrogel, polyacrylate can swell with electrolyte solution to a degree far beyond typical contemporary electrode materials, delivering a strong hydrating effect to the skin surface. This hydrating power allows the material to increase the effective skin contact surface area through wetting, and noninvasively decrease or bypass the highly resistive barrier of the stratum corneum, allowing for reduced impedance and improved electrode performance. For the purposes of the tests performed in this study, the polyacrylate was prepared both as a solid elastic gel and as a flowable paste designed to penetrate dense scalp hair. The gel can hold 99.2% DI water or 91% electrolyte solution, and the water content remains high after 29 h of air exposure. The electrical impedance of the gel electrode on unprepared human forearm is significantly lower than a number of commercial ECG and EEG electrodes. This low impedance was maintained for at least 8 h (the longest time period measured). When a paste form of the electrode was applied directly onto scalp hair, the impedance was found to be lower than that measured with commercially available EEG paste applied in the same manner. Time-frequency transformation analysis of frontal lobe EEG recordings indicated comparable frequency response between the polyacrylate-based electrode on unprepared skin and the commercial EEG electrode on abraded skin. Evoked potential recordings demonstrated

  13. Meditation and the EEG

    OpenAIRE

    West, Michael

    1980-01-01

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

  14. Treatment of paediatric scalp psoriasis with calcipotriene/betamethasone dipropionate scalp formulation: effectiveness, safety and influence on children's quality of life in daily practice

    NARCIS (Netherlands)

    Oostveen, A.M.; Jong, E.M.G.J. de; Donders, A.R.T.; Kerkhof, P.C.M. van de; Seyger, M.M.B.

    2015-01-01

    BACKGROUND: Evidence on efficacy and safety of topical treatments for paediatric scalp psoriasis is lacking. OBJECTIVE: This study aims to evaluate the effectiveness and safety of calcipotriene/betamethasone dipropionate scalp formulation for paediatric scalp psoriasis in daily clinical practice.

  15. Scalp melanoma after anti hair loss mesotherapy.

    Science.gov (United States)

    Arenbergerova, M; Arenberger, P; Gkalpakiotis, S; Dahmen, R A; Sticova, E; Fialova, A

    2017-11-14

    Scalp melanoma comprises 3-5% of all cutaneous melanomas. The median age of the patients is 53 years and males are more frequently affected. The scalp melanomas tend to have nodular histology with a higher mitotic rate (>3/mm) and poorer prognosis (1). The risk factors for development of this tumor are still not defined but UV light and baldness may play a significant role (2-4). Mesotherapy is a non-surgical procedure currently being used to combat hair loss and promote hair growth. Usually a mixture of vitamins, minerals, growth factors, DHT blockers and/or stem cells extracts is injected into the dermal layer of skin (5,6). Although it is a widely used method, the safety profile of this procedure hasn't been studied yet (7,8). This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  16. Mobile EEG in epilepsy

    NARCIS (Netherlands)

    Askamp, Jessica; van Putten, Michel Johannes Antonius Maria

    2014-01-01

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

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

    Science.gov (United States)

    Al-Qazzaz, Noor Kamal; Bin Mohd Ali, Sawal Hamid; Ahmad, Siti Anom; Islam, Mohd Shabiul; Escudero, Javier

    2015-11-17

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  19. Scalp abscess--a cautionary tale.

    LENUS (Irish Health Repository)

    Nugent, Nora F

    2010-08-01

    Transcranial extension of frontal sinus infection is a rare, but not eradicated entity. We present a 21-year-old male, in whom a persistent scalp abscess heralded the discovery of skull vault osteomyelitis and extradural abscesses secondary to frontal sinusitis. Patients with prolonged or unusual symptoms with a history of sinusitis or trauma warrant further investigation as they may have developed serious intracranial complications. Urgent management, both surgical and antimicrobial, is indicated in such scenarios.

  20. [Treatment of autism with scalp acupunctur].

    Science.gov (United States)

    Li, Nuo; Jin, Bing-Xu; Li, Jie-Ling; Liu, Zhen-Huan

    2011-08-01

    To verify the efficacy on autism treated with scalp acupuncture for regaining the consciousness and opening the orifice in children. Seventy cases of child autism were divided into an observation group (30 cases) and a control group (40 cases). In observation group, the cases were treated with scalp acupuncture for regaining the consciousness and opening the orifice, in combination with music therapy and structure education method. Scalp acupuncture was applied to intelligent nine needles (frontal five needles, Sishencong (EX-HN 1)), affection area, heart and liver area, once a day, at the interval once every one week. Totally, 60 treatments made one session. In control group, music therapy and structure education method were applied simply. Clancy Autism Behavior Scale, Childhood Autism Behavior Scale (CARS), Autism Behavior Checklist (ABC) and Gesell Developmental Scale (social adaptive behaviors and language development) were adopted to assess the scores before treatment and after 1 session of treatment. After treatment, the scores in Clancy Autism Behavior Scale, CARS and ABC were lower apparently in observation group as compared with those before treatment (all P Autism Behavior Scale and ABC were lower than those in control group (both P Autism Behavior Scale, ABC and social adaptive development scale did not present statistical significance in group comparison before and after treatment (all P > 0.05). Scalp acupuncture for regaining the consciousness and opening the orifice can significantly improve the efficacy on autism, effectively relieve child autism symptoms and enhance the intelligence, language ability and social adaptive ability. Moreover, the efficacy cannot be impacted by child's age.

  1. The role of full thickness scalp resection for management of primary scalp melanoma

    Science.gov (United States)

    Pannucci, Christopher J.; Collar, Ryan M.; Johnson, Timothy M.; Bradford, Carol R.; Rees, Riley S.

    2015-01-01

    BACKGROUND Scalp melanoma is aggressive and has a proclivity for regional metastasis. We hypothesize that subperiosteal scalp melanoma resection reduces in-transit/satellite recurrence, when compared to subgaleal resection. METHODS We identified patients with intermediate to deep, primary scalp melanoma referred to head/neck surgery over an eight-year period. Patients were compared based on scalp resection depth, including subperiosteal (resection to the level of calvarium) and subgaleal (resection including skin, subcutaneous tissue, and galea). The dependent variables were in-transit/satellite recurrence and time to in-transit/satellite recurrence. RESULTS Among 48 identified patients, the in-transit/satellite recurrence rate was 16.7%. Subgaleal resection patients had higher in-transit/satellite recurrence rates than subperiosteal resection patients (24.0% vs. 8.7%, p=0.155). Among node-negative patients, subgaleal resection had significantly higher in-transit/satellite metastasis rates when compared to subperiosteal resection (26.3% vs. 0%, p=0.047). CONCLUSION For node-negative, primary scalp melanoma, subperiosteal resection significantly decreases in-transit/satellite recurrence when compared to subgaleal resection. Given our small sample size, further studies are necessary to confirm these results. PMID:21734540

  2. Surface Laplacian of scalp electrical signals and independent component analysis resolve EMG contamination of electroencephalogram.

    Science.gov (United States)

    Fitzgibbon, S P; DeLosAngeles, D; Lewis, T W; Powers, D M W; Whitham, E M; Willoughby, J O; Pope, K J

    2015-09-01

    The serious impact of electromyogram (EMG) contamination of electroencephalogram (EEG) is well recognised. The objective of this research is to demonstrate that combining independent component analysis with the surface Laplacian can eliminate EMG contamination of the EEG, and to validate that this processing does not degrade expected neurogenic signals. The method involves sequential application of ICA, using a manual procedure to identify and discard EMG components, followed by the surface Laplacian. The extent of decontamination is quantified by comparing processed EEG with EMG-free data that was recorded during pharmacologically induced neuromuscular paralysis. The combination of the ICA procedure and the surface Laplacian, with a flexible spherical spline, results in a strong suppression of EMG contamination at all scalp sites and frequencies. Furthermore, the ICA and surface Laplacian procedure does not impair the detection of well-known, cerebral responses; alpha activity with eyes-closed; ERP components (N1, P2) in response to an auditory oddball task; and steady state responses to photic and auditory stimulation. Finally, more flexible spherical splines increase the suppression of EMG by the surface Laplacian. We postulate this is due to ICA enabling the removal of local muscle sources of EMG contamination and the Laplacian transform being insensitive to distant (postural) muscle EMG contamination. Copyright © 2014 Elsevier B.V. All rights reserved.

  3. Classification of epilepsy types through global network analysis of scalp electroencephalograms

    Science.gov (United States)

    Lee, Uncheol; Kim, Seunghwan; Jung, Ki-Young

    2006-04-01

    Epilepsy is a dynamic disease in which self-organization and emergent structures occur dynamically at multiple levels of neuronal integration. Therefore, the transient relationship within multichannel electroencephalograms (EEGs) is crucial for understanding epileptic processes. In this paper, we show that the global relationship within multichannel EEGs provides us with more useful information in classifying two different epilepsy types than pairwise relationships such as cross correlation. To demonstrate this, we determine the global network structure within channels of the scalp EEG based on the minimum spanning tree method. The topological dissimilarity of the network structures from different types of temporal lobe epilepsy is described in the form of the divergence rate and is computed for 11 patients with left (LTLE) and right temporal lobe epilepsy (RTLE). We find that patients with LTLE and RTLE exhibit different large scale network structures, which emerge at the epoch immediately before the seizure onset, not in the preceding epochs. Our results suggest that patients with the two different epilepsy types display distinct large scale dynamical networks with characteristic epileptic network structures.

  4. 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

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

    Science.gov (United States)

    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

  6. A Thalamocortical Neural Mass Model of the EEG during NREM Sleep and Its Response to Auditory Stimulation.

    Science.gov (United States)

    Schellenberger Costa, Michael; Weigenand, Arne; Ngo, Hong-Viet V; Marshall, Lisa; Born, Jan; Martinetz, Thomas; Claussen, Jens Christian

    2016-09-01

    Few models exist that accurately reproduce the complex rhythms of the thalamocortical system that are apparent in measured scalp EEG and at the same time, are suitable for large-scale simulations of brain activity. Here, we present a neural mass model of the thalamocortical system during natural non-REM sleep, which is able to generate fast sleep spindles (12-15 Hz), slow oscillations (EEG-data from a recent sleep study in humans, where closed-loop auditory stimulation was applied. The model output relates directly to the EEG, which makes it a useful basis to develop new stimulation protocols.

  7. EEG-microstate dependent emergence of perceptual awareness

    Directory of Open Access Journals (Sweden)

    Juliane eBritz

    2014-05-01

    Full Text Available We investigated whether the differences in perceptual awareness for stimuli at the threshold of awareness can arise from different global brain states before stimulus onset indexed by the EEG microstate. We used a metacontrast backward masking paradigm in which subjects had to discriminate between two weak stimuli and obtained measures of accuracy and awareness while their EEG was recorded from 256 channels. Comparing correctly identified targets with and without awareness allowed us to contrast differences in awareness while keeping performance constant for identical physical stimuli. Two distinct pre-stimulus scalp potential fields (microstate maps dissociated correct identification with and without awareness, and their estimated intracranial generators were stronger in primary visual cortex before correct identification without awareness. This difference in activity cannot be explained by differences in alpha power or phase which were less reliably linked with differential pre-stimulus activation of primary visual cortex. Our results shed a new light on the function of pre-stimulus activity in early visual cortex in visual awareness and emphasize the importance of trial-by-trials analysis of the spatial configuration of the scalp potential field identified with multichannel EEG.

  8. MUSIC seeded multi-dipole MEG modeling using the Constrained Start Spatio-Temporal modeling procedure.

    Science.gov (United States)

    Ranken, D M; Stephen, J M; George, J S

    2004-11-30

    The Constrained Start Spatio-Temporal modeling program (CSST) is an objective multi-dipole, multi-start MEG/EEG analysis procedure that randomly selects from 100 to 100,000 initial dipole configurations, and runs a nonlinear simplex search on each of these configurations employing a reduced Chi-square statistic as the minimization criterion, to obtain a set of dipole configurations that best fit the data [Ranken, 2002]. A parallel version of CSST is implemented in IDL and MPI, making CSST usable on a single computer, or on a Linux cluster. We have now developed a multi-resolution version of MUSIC [Mosher, 1992] [Mosher, 1998] that provides an 80% or more reduction in the number of forward calculations needed to obtain results comparable to a 160,000 point MUSIC scan, on a 2 mm grid that defines a brain volume. The multi-resolution MUSIC scan provides an improved set of initial dipole estimates for the CSST analysis. In preliminary tests on real and simulated MEG data, with model orders ranging between 5 and 7 dipoles, the best performance improvements were obtained by mixing in 1 to 3 dipole locations randomly drawn from the best MUSIC locations, with randomly selected locations from the brain volume to complete the selected model order. We have also developed an improved method for sampling the brain volume for initial configurations. These improvements have led to a 75% reduction in the number of starting configurations required to obtain 5-10 best solutions with equal or lower reduced Chi-square values, when compared to the best solutions from the previous version of CSST.

  9. Early Left-Hemispheric Dysfunction of Face Processing in Congenital Prosopagnosia: An MEG Study

    Science.gov (United States)

    Dobel, Christian; Putsche, Christian; Zwitserlood, Pienie; Junghöfer, Markus

    2008-01-01

    Background Congenital prosopagnosia is a severe face perception impairment which is not acquired by a brain lesion and is presumably present from birth. It manifests mostly by an inability to recognise familiar persons. Electrophysiological research has demonstrated the relevance to face processing of a negative deflection peaking around 170 ms, labelled accordingly as N170 in the electroencephalogram (EEG) and M170 in magnetoencephalography (MEG). The M170 was shown to be sensitive to the inversion of faces and to familiarity-two factors that are assumed to be crucial for congenital prosopagnosia. In order to locate the cognitive dysfunction and its neural correlates, we investigated the time course of neural activity in response to these manipulations. Methodology Seven individuals with congenital prosopagnosia and seven matched controls participated in the experiment. To explore brain activity with high accuracy in time, we recorded evoked magnetic fields (275 channel whole head MEG) while participants were looking at faces differing in familiarity (famous vs. unknown) and orientation (upright vs. inverted). The underlying neural sources were estimated by means of the least square minimum-norm-estimation (L2-MNE) approach. Principal Findings The behavioural data corroborate earlier findings on impaired configural processing in congenital prosopagnosia. For the M170, the overall results replicated earlier findings, with larger occipito-temporal brain responses to inverted than upright faces, and more right- than left-hemispheric activity. Compared to controls, participants with congenital prosopagnosia displayed a general decrease in brain activity, primarily over left occipitotemporal areas. This attenuation did not interact with familiarity or orientation. Conclusions The study substantiates the finding of an early involvement of the left hemisphere in symptoms of prosopagnosia. This might be related to an efficient and overused featural processing strategy

  10. Early left-hemispheric dysfunction of face processing in congenital prosopagnosia: an MEG study.

    Directory of Open Access Journals (Sweden)

    Christian Dobel

    Full Text Available BACKGROUND: Congenital prosopagnosia is a severe face perception impairment which is not acquired by a brain lesion and is presumably present from birth. It manifests mostly by an inability to recognise familiar persons. Electrophysiological research has demonstrated the relevance to face processing of a negative deflection peaking around 170 ms, labelled accordingly as N170 in the electroencephalogram (EEG and M170 in magnetoencephalography (MEG. The M170 was shown to be sensitive to the inversion of faces and to familiarity--two factors that are assumed to be crucial for congenital prosopagnosia. In order to locate the cognitive dysfunction and its neural correlates, we investigated the time course of neural activity in response to these manipulations. METHODOLOGY: Seven individuals with congenital prosopagnosia and seven matched controls participated in the experiment. To explore brain activity with high accuracy in time, we recorded evoked magnetic fields (275 channel whole head MEG while participants were looking at faces differing in familiarity (famous vs. unknown and orientation (upright vs. inverted. The underlying neural sources were estimated by means of the least square minimum-norm-estimation (L2-MNE approach. PRINCIPAL FINDINGS: The behavioural data corroborate earlier findings on impaired configural processing in congenital prosopagnosia. For the M170, the overall results replicated earlier findings, with larger occipito-temporal brain responses to inverted than upright faces, and more right- than left-hemispheric activity. Compared to controls, participants with congenital prosopagnosia displayed a general decrease in brain activity, primarily over left occipitotemporal areas. This attenuation did not interact with familiarity or orientation. CONCLUSIONS: The study substantiates the finding of an early involvement of the left hemisphere in symptoms of prosopagnosia. This might be related to an efficient and overused featural

  11. Diagnostic accuracy of fetal scalp lactate for intrapartum acidosis compared with scalp pH.

    Science.gov (United States)

    Pascual Mancho, Jara; Marti Gamboa, Sabina; Redrado Gimenez, Olga; Crespo Esteras, Raquel; Rodriguez Solanilla, Belen; Castan Mateo, Sergio

    2017-04-01

    To determine the diagnostic accuracy of fetal scalp lactate sampling (FSLS) and to establish an optimal cut-off value for intrapartum acidosis compared with fetal scalp pH. A 20-month retrospective cohort study was conducted of all neonates delivered in our institution for whom fetal scalp blood sampling (FSBS) was performed, matching their intrapartum gasometry to their cord gasometry at delivery (n=243). The time taken from the performance of scalp blood sampling to arterial umbilical cord gas acquisition was 45 min at most. Five arterial cord gasometry patterns were set for assessing the predictive ability of both techniques. Subsequent obstetric management for a pathological value was analysed considering the use of both techniques. The optimal cut-off value for FSLS was 4.8 mmol/L: this value has 100% sensitivity and 63% specificity for umbilical arterial cord gas pH≤7.0 and base deficit (BD)≥12 detection, and 100% sensitivity and 64% specificity for umbilical arterial cord gas pH≤7.10 and BD≥12 detection, with a false negative rate of scalp pH performance. FSLS showed the best area under the curve (AUC) of 0.86 and 0.84 for both arterial cord gasometry patterns, respectively. Expedite birth following lactate criteria would have been the same as following pH criteria (92 obstetric interventions) with no cases of missed metabolic acidosis. In the cohort, 19.8% of cases were discordant, but no cases of metabolic acidosis were in this group. FSLS improves the detection of metabolic acidosis via fetal scalp pH with an optimal cut-off value of 4.8 mmol/L. FSLS can be used without increasing obstetrical interventions or missing metabolic acidosis.

  12. Scalp cooling: management option for chemotherapy-induced alopecia.

    Science.gov (United States)

    Roe, Helen

    Chemotherapy is increasingly being administered as a treatment for cancer and with it are a number of possible side effects. One, which has a negative impact on a patient's quality of life and their self-esteem, is that of chemotherapy-induced alopecia (CIA). A side effect of which, for some, could be prevented by the use of scalp cooling, dependent on the regimen being administered and patient choice. This article explores the issue of CIA from the patient's perspective and scalp cooling as a preventative measure, along with a review of the evidence around the risk associated with developing scalp metastases following scalp cooling. It also discusses why scalp cooling should be available for both male and female patients; along with the potential impact scalp cooling may have on clinical areas delivering chemotherapy.

  13. ICA on sensor or source data: A comparison study in deriving resting state networks from EEG.

    Science.gov (United States)

    Chuang Li; Han Yuan; Urbano, Diamond; Yoon-Hee Cha; Lei Ding

    2017-07-01

    Resting state networks (RSNs) are human brain networks formed by spontaneous activity fluctuations in distributed brain regions when people are in task-free and awake state. RSNs have been so far extensively studied using functional magnetic resonance imaging (fMRI). Recently, electroencephalography (EEG) and magnetoencephalography (MEG) have also been used to derive RSNs, in which independent component analysis (ICA) is the key step. In these studies, ICA has been either directly applied to recorded data at sensors (sensor-space ICA) or estimated source data from sensors using inverse source imaging techniques (source-space ICA). Both sensor-space and source-space ICAs have demonstrated the capability in finding RSNs from EEG/MEG data and their results showed strong correlations to fMRI RSNs. However, their performance was hardly compared even differences have been observed in their results. In the present study, we compared the source-space and sensor-space ICAs in reconstructing spatial, temporal and spectral features of RSNs in both simulated and real EEG data. Results from simulated data indicated that the source-space ICA has better performance in reconstructing spatial, temporal, and spectral feature of RSNs. Results from resting-sate EEG data in seven healthy participants also showed the difference between two procedures and, through the comparison with RSN templates constructed from fMRI data, the source-space ICA indicated relatively better performance than the sensor-space ICA.

  14. Decoding English Alphabet Letters Using EEG Phase Information

    Science.gov (United States)

    Wang, YiYan; Wang, Pingxiao; Yu, Yuguo

    2018-01-01

    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. PMID:29467615

  15. Detection of Epileptic Seizure Event and Onset Using EEG

    Science.gov (United States)

    Ahammad, Nabeel; Fathima, Thasneem; Joseph, Paul

    2014-01-01

    This study proposes a method of automatic detection of epileptic seizure event and onset using wavelet based features and certain statistical features without wavelet decomposition. Normal and epileptic EEG signals were classified using linear classifier. For seizure event detection, Bonn University EEG database has been used. Three types of EEG signals (EEG signal recorded from healthy volunteer with eye open, epilepsy patients in the epileptogenic zone during a seizure-free interval, and epilepsy patients during epileptic seizures) were classified. Important features such as energy, entropy, standard deviation, maximum, minimum, and mean at different subbands were computed and classification was done using linear classifier. The performance of classifier was determined in terms of specificity, sensitivity, and accuracy. The overall accuracy was 84.2%. In the case of seizure onset detection, the database used is CHB-MIT scalp EEG database. Along with wavelet based features, interquartile range (IQR) and mean absolute deviation (MAD) without wavelet decomposition were extracted. Latency was used to study the performance of seizure onset detection. Classifier gave a sensitivity of 98.5% with an average latency of 1.76 seconds. PMID:24616892

  16. Detection of Epileptic Seizure Event and Onset Using EEG

    Directory of Open Access Journals (Sweden)

    Nabeel Ahammad

    2014-01-01

    Full Text Available This study proposes a method of automatic detection of epileptic seizure event and onset using wavelet based features and certain statistical features without wavelet decomposition. Normal and epileptic EEG signals were classified using linear classifier. For seizure event detection, Bonn University EEG database has been used. Three types of EEG signals (EEG signal recorded from healthy volunteer with eye open, epilepsy patients in the epileptogenic zone during a seizure-free interval, and epilepsy patients during epileptic seizures were classified. Important features such as energy, entropy, standard deviation, maximum, minimum, and mean at different subbands were computed and classification was done using linear classifier. The performance of classifier was determined in terms of specificity, sensitivity, and accuracy. The overall accuracy was 84.2%. In the case of seizure onset detection, the database used is CHB-MIT scalp EEG database. Along with wavelet based features, interquartile range (IQR and mean absolute deviation (MAD without wavelet decomposition were extracted. Latency was used to study the performance of seizure onset detection. Classifier gave a sensitivity of 98.5% with an average latency of 1.76 seconds.

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

    Science.gov (United States)

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

    2013-04-01

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

  18. Scalp Metastases of Recurrent Meningiomas: Aggressive Behavior or Surgical Seeding?

    Science.gov (United States)

    Avecillas-Chasin, Josue M; Saceda-Gutierrez, Javier; Alonso-Lera, Pedro; Garcia-Pumarino, Ruben; Issa, Subhi; López, Escarlata; Barcia, Juan A

    2015-07-01

    Scalp metastases of meningiomas seldom have been reported. Here, we report a series of 4 cases of this rare event and discuss the relevant potential risk factors. We performed a retrospective review of patients treated for scalp metastases of meningiomas at our institution. A literature review was performed for the terms "scalp meningioma," "cutaneous meningioma," "skin meningioma," "extracranial meningioma," and "subcutaneous meningioma." Four patients showed scalp metastases of recurrent meningiomas with the following associated clinical features: multiple reoperations (n = 4), immunosuppression (n = 2), radiation therapy (n = 3), surgical wound complications with cerebrospinal fluid fistula (n = 2), and histologic grade progression (n = 2). The timescale for development of scalp metastasis was between 5 months and 13 years after intracranial meningioma surgery. In all cases, the metastases were located close to the surgical scalp incision for the craniotomy. Previously, 11 cases of meningioma with scalp metastasis, with similar features to those described here, were reported in the literature. Spreading of meningioma cells during surgery is a possible mechanism for scalp metastases of recurrent meningiomas. Factors associated with scalp metastases include reoperations, immunosuppression, radiation therapy, torpid course of the surgical wound with cerebrospinal fluid fistula, and histologic progression. Awareness of these features is advisable for neurosurgeons involved in the care of patients with similar profiles. Copyright © 2015 Elsevier Inc. All rights reserved.

  19. Mobile EEG in epilepsy.

    Science.gov (United States)

    Askamp, Jessica; van Putten, Michel J A M

    2014-01-01

    The sensitivity of routine EEG recordings for interictal epileptiform discharges in epilepsy is limited. In some patients, inpatient video-EEG may be performed to increase the likelihood of finding abnormalities. Although many agree that home EEG recordings may provide a cost-effective alternative to these recordings, their use is still not introduced everywhere. We surveyed Dutch neurologists and patients and evaluated a novel mobile EEG device (Mobita, TMSi). Key specifications were compared with three other current mobile EEG devices. We shortly discuss algorithms to assist in the review process. Thirty percent (33 out of 109) of Dutch neurologists reported that home EEG recordings are used in their hospital. The majority of neurologists think that mobile EEG can have additional value in investigation of unclear paroxysms, but not in the initial diagnosis after a first seizure. Poor electrode contacts and signal quality, limited recording time and absence of software for reliable and effective assistance in the interpretation of EEGs have been important constraints for usage, but in recent devices discussed here, many of these problems have been solved. The majority of our patients were satisfied with the home EEG procedure and did not think that our EEG device was uncomfortable to wear, but they did feel uneasy wearing it in public. © 2013.

  20. Dermoscopic Findings of Scalp Aplasia Cutis Congenita.

    Science.gov (United States)

    Damiani, Leandro; Aguiar, Fernanda Musa; da Silva, Mariana Vale Scribel; Miteva, Mariya I; Pinto, Giselle Martins

    2017-01-01

    Aplasia cutis congenita (ACC) is a rare disease characterized by congenital absence of skin, affecting preferentially the scalp. Diagnosis is made clinically; however, recent studies have shown that dermoscopy can be a useful tool for the diagnosis and differentiation from sebaceous nevus. The clinical findings include a shiny atrophic alopecic patch associated with dermoscopic findings of absent follicular openings, thicker vessels and a distinct collar hypertrichosis. We report 2 cases of alopecia presenting from birth. At dermoscopy, the absence of follicular openings and the increase in the caliber of vessels led us to establish the diagnosis of ACC.

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

    Science.gov (United States)

    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.

  2. 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.

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

    Science.gov (United States)

    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.

  4. Inverse source localization for EEG using system identification approach

    Science.gov (United States)

    Xanthopoulos, Petros; Yatsenko, Vitaliy; Kammerdiner, Alla; Pardalos, Panos M.

    2007-11-01

    The reconstruction of the brain current sources from scalp electric recordings (Electroen-cephalogram) also known as the inverse source localization problem is a highly underdetermined problem in the field of computational neuroscience, and this problem still remains open . In this chapter we propose an alternative formulation for the inverse electroencephalography (EEG) problem based on optimization theory. For simulation purposes, a three shell realistic head model based on an averaged magnetic resonance imaging (MRI) segmentation and Boundary Element method (BEM) is constructed. System identification methodology is employed in order to determine the parameters of the system. In the last stage the inverse problem is solved using the computed forward model.

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

    Directory of Open Access Journals (Sweden)

    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.

  6. Adaptive neuro-fuzzy inference system for classification of background EEG signals from ESES patients and controls.

    Science.gov (United States)

    Yang, Zhixian; Wang, Yinghua; Ouyang, Gaoxiang

    2014-01-01

    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.

  7. Sleep affects cortical source modularity in temporal lobe epilepsy: A high-density EEG study.

    Science.gov (United States)

    Del Felice, Alessandra; Storti, Silvia Francesca; Manganotti, Paolo

    2015-09-01

    Interictal epileptiform discharges (IEDs) constitute a perturbation of ongoing cerebral rhythms, usually more frequent during sleep. The aim of the study was to determine whether sleep influences the spread of IEDs over the scalp and whether their distribution depends on vigilance-related modifications in cortical interactions. Wake and sleep 256-channel electroencephalography (EEG) data were recorded in 12 subjects with right temporal lobe epilepsy (TLE) differentiated by whether they had mesial or neocortical TLE. Spikes were selected during wake and sleep. The averaged waking signal was subtracted from the sleep signal and projected on a bidimensional scalp map; sleep and wake spike distributions were compared by using a t-test. The superimposed signal of sleep and wake traces was obtained; the rising phase of the spike, the peak, and the deflections following the spike were identified, and their cortical generator was calculated using low-resolution brain electromagnetic tomography (LORETA) for each group. A mean of 21 IEDs in wake and 39 in sleep per subject were selected. As compared to wake, a larger IED scalp projection was detected during sleep in both mesial and neocortical TLE (pEEG deflections followed the spike, the cortical sources of which displayed alternating activations of different cortical areas in wake, substituted by isolated, stationary activations in sleep in mesial TLE and a silencing in neocortical TLE. During sleep, the IED scalp region increases, while cortical interaction decreases. The interaction of cortical modules in sleep and wake in TLE may influence the appearance of IEDs on scalp EEG; in addition, IEDs could be proxies for cerebral oscillation perturbation. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  8. Brain activity and learning of mathematical rules--effects on the frequencies of EEG.

    Science.gov (United States)

    Skrandies, Wolfgang; Klein, Alexander

    2015-04-07

    We investigated the change of evoked EEG frequencies induced by learning to solve mathematical tasks by applying divisibility rules. The performance on easy (divisibility by 2, 3, or 5) and hard tasks (divisibility by 9 or by 11) was compared. In a behavioral experiment on 52 adults we found a significant increase in performance from 67% to 90% correct responses induced by rule learning. Subsequently, the EEG data recorded from 30 additional volunteers were analyzed. EEG recordings were performed in two parts: First, subjects had to solve 200 tasks without knowing the divisibility rules. Then the rules were explained, followed by another set of 200 tasks. EEG was measured simultaneously in 30 channels, artifacts were removed offline, and the data before and after rule learning were compared. A wavelet transformation with the Morlet-5 wavelet was computed, and the scalp topography of the maximal frequency and its occurrence time was compared. Largest effects were observed with frequencies between about 6 and 18 Hz. In the frequency band between 12 and 30 Hz maximal frequencies were significantly different after successful learning over frontal and centro-parietal scalp areas of the right hemisphere. These changes were paralleled by decreased response times. In summary, our data illustrate a significant relation between successful learning divisibility rules and changes in the frequency content of the task-related EEG. Significant effects were observed after a very short training period of less than 10 min. Copyright © 2014 Elsevier B.V. All rights reserved.

  9. Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis.

    Science.gov (United States)

    Delorme, Arnaud; Sejnowski, Terrence; Makeig, Scott

    2007-02-15

    Detecting artifacts produced in EEG data by muscle activity, eye blinks and electrical noise is a common and important problem in EEG research. It is now widely accepted that independent component analysis (ICA) may be a useful tool for isolating artifacts and/or cortical processes from electroencephalographic (EEG) data. We present results of simulations demonstrating that ICA decomposition, here tested using three popular ICA algorithms, Infomax, SOBI, and FastICA, can allow more sensitive automated detection of small non-brain artifacts than applying the same detection methods directly to the scalp channel data. We tested the upper bound performance of five methods for detecting various types of artifacts by separately optimizing and then applying them to artifact-free EEG data into which we had added simulated artifacts of several types, ranging in size from thirty times smaller (-50 dB) to the size of the EEG data themselves (0 dB). Of the methods tested, those involving spectral thresholding were most sensitive. Except for muscle artifact detection where we found no gain of using ICA, all methods proved more sensitive when applied to the ICA-decomposed data than applied to the raw scalp data: the mean performance for ICA was higher and situated at about two standard deviations away from the performance distribution obtained on raw data. We note that ICA decomposition also allows simple subtraction of artifacts accounted for by single independent components, and/or separate and direct examination of the decomposed non-artifact processes themselves.

  10. 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 ...

  11. Prolific plant regeneration through organogenesis from scalps of ...

    African Journals Online (AJOL)

    STORAGESEVER

    2009-11-16

    Nov 16, 2009 ... Full Length Research Paper. Prolific plant regeneration through organogenesis from scalps of Musa sp ... include the panama disease or Fusarium wilt (Fusarium oxysporum f. sp. Cubense and the black sigatoka (Myco- ... This paper describes prolific shoot regeneration from scalps of Musa sp. cv. Tanduk.

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

    Directory of Open Access Journals (Sweden)

    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.

  13. Erosive pustular dermatosis of the scalp. A chronic recalcitrant dermatosis developed upon CO2 laser treatment

    National Research Council Canada - National Science Library

    Tavares-Bello, Rui

    2009-01-01

    Erosive pustular dermatosis of the scalp (EPDS) is a rare, chronic inflammatory dermatosis that mostly affects elderly patients, who develop erosions, pustulation, crusting and scarring on the scalp...

  14. PHOEBE: a method for real time mapping of optodes-scalp coupling in functional near-infrared spectroscopy.

    Science.gov (United States)

    Pollonini, Luca; Bortfeld, Heather; Oghalai, John S

    2016-12-01

    Recent functional near-infrared spectroscopy (fNIRS) instrumentation encompasses several dozen of optodes to enable reconstructing a hemodynamic image of the entire cerebral cortex. Despite its potential clinical applicability, widespread use of fNIRS with human subjects is currently limited by unresolved issues, namely the collection from the entirety of optical channels of signals with a signal-to-noise ratio (SNR) sufficient to carry out a reliable estimation of cortical hemodynamics, and the considerable amount of time that placing numerous optodes take with individuals for whom achieving good optical coupling to the scalp is difficult due to thick or dark hair. To address these issues, we developed a numerical method that: 1) at the channel level, computes an objective measure of the signal-to-noise ratio (SNR) related to its optical coupling to the scalp, akin to electrode conductivity used in electroencephalography (EEG), and 2) at the optode level, determines and displays the coupling status of all individual optodes in real time on a model of a human head. This approach aims to shorten the pre-acquisition preparation time by visually displaying which optodes require further adjustment for optimum scalp coupling, and to maximize the signal-to-noise ratio (SNR) of all optical channels contributing to the functional hemodynamic mapping. The methodology described in this paper has been implemented in a software tool named PHOEBE (placing headgear optodes efficiently before experimentation) that is freely available for use by the fNIRS community.

  15. Classification of EEG abnormalities in partial epilepsy with simultaneous EEG-fMRI recordings.

    Science.gov (United States)

    Pedreira, C; Vaudano, A E; Thornton, R C; Chaudhary, U J; Vulliemoz, S; Laufs, H; Rodionov, R; Carmichael, D W; Lhatoo, S D; Guye, M; Quian Quiroga, R; Lemieux, L

    2014-10-01

    Scalp EEG recordings and the classification of interictal epileptiform discharges (IED) in patients with epilepsy provide valuable information about the epileptogenic network, particularly by defining the boundaries of the "irritative zone" (IZ), and hence are helpful during pre-surgical evaluation of patients with severe refractory epilepsies. The current detection and classification of epileptiform signals essentially rely on expert observers. This is a very time-consuming procedure, which also leads to inter-observer variability. Here, we propose a novel approach to automatically classify epileptic activity and show how this method provides critical and reliable information related to the IZ localization beyond the one provided by previous approaches. We applied Wave_clus, an automatic spike sorting algorithm, for the classification of IED visually identified from pre-surgical simultaneous Electroencephalogram-functional Magnetic Resonance Imagining (EEG-fMRI) recordings in 8 patients affected by refractory partial epilepsy candidate for surgery. For each patient, two fMRI analyses were performed: one based on the visual classification and one based on the algorithmic sorting. This novel approach successfully identified a total of 29 IED classes (compared to 26 for visual identification). The general concordance between methods was good, providing a full match of EEG patterns in 2 cases, additional EEG information in 2 other cases and, in general, covering EEG patterns of the same areas as expert classification in 7 of the 8 cases. Most notably, evaluation of the method with EEG-fMRI data analysis showed hemodynamic maps related to the majority of IED classes representing improved performance than the visual IED classification-based analysis (72% versus 50%). Furthermore, the IED-related BOLD changes revealed by using the algorithm were localized within the presumed IZ for a larger number of IED classes (9) in a greater number of patients than the expert

  16. The EEG in psychiatry

    African Journals Online (AJOL)

    Adele

    2004-05-20

    May 20, 2004 ... Epilepsy is primarily a clinical diagnosis, but the EEG ... seizure onset and the epilepsy syndrome. However, a normal inter-ictal EEG can never refute or exclude a clinical diagno- sis of epilepsy. Organic mental disorders is increasingly an ... to metabolic changes, infections, toxins, trauma and tumours.

  17. Electroencephalogram (EEG) (For Parents)

    Science.gov (United States)

    ... test. If it's necessary for your child to sleep during the EEG, the doctor will suggest ways to help make this easier. The Procedure An EEG can be done in the doctor's office, a lab, or a hospital. Your child will be asked to lie on ...

  18. The EEG in psychiatry

    African Journals Online (AJOL)

    Adele

    2004-05-20

    May 20, 2004 ... 13th National Psychiatry Congress. The EEG in psychiatry. Roland Eastman. Division of Neurology, University of Cape Town, Cape Town, South Africa orders. Epilepsy is primarily a clinical diagnosis, but the EEG may provide strong support by the finding of inter-ictal epi- leptogenic discharges and also be ...

  19. Detection of correlated sources in EEG using combination of beamforming and surface Laplacian methods.

    Science.gov (United States)

    Murzin, Vyacheslav; Fuchs, Armin; Scott Kelso, J A

    2013-08-15

    Beamforming offers a way to estimate the solution to the inverse problem in EEG and MEG but is also known to perform poorly in the presence of highly correlated sources, e.g. during binaural auditory stimulation, when both left and right primary auditory cortices are activated simultaneously. Surface Laplacian, or the second spatial derivative calculated from the electric potential, allows for deblurring of EEG potential recordings reducing the effects of low skull conductivity and is independent of the reference electrode location. We show that anatomically constrained beamforming in conjunction with the surface Laplacian allows for detection of both locations and dynamics of temporally correlated sources in EEG. Whole-head 122 channel binaural stimulus EEG data were simulated using a boundary element method (BEM) and realistic geometry forward model. We demonstrate that in contrast to conventional potential-based EEG beamforming, Laplacian beamforming allows to determine locations of correlated source dipoles without any a priori assumption about the number of sources. We also show (by providing simulations of auditory evoked potentials) that the dynamics at the detected source locations can be derived from subsets of electrodes. Deblurring auditory evoked potential maps subdivides EEG signals from each hemisphere and allows for the beamformer to be applied separately for left and right hemispheres. Copyright © 2013 Elsevier B.V. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    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

  1. Long-term EEG in children.

    Science.gov (United States)

    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.

  2. EEG activity in Carmelite nuns during a mystical experience.

    Science.gov (United States)

    Beauregard, Mario; Paquette, Vincent

    2008-10-17

    Mystical experiences relate to a fundamental dimension of human existence. These experiences, which are characterized by a sense of union with God, are commonly reported across all cultures. To date, no electroencephalography (EEG) study has been conducted to identify the neuroelectrical correlates of such experiences. The main objective of this study was to measure EEG spectral power and coherence in 14 Carmelite nuns during a mystical experience. EEG activity was recorded from 19 scalp locations during a resting state, a control condition and a mystical condition. In the mystical condition compared to control condition, electrode sites showed greater theta power at F3, C3, P3, Fz, Cz and Pz, and greater gamma1 power was detected at T4 and P4. Higher delta/beta ratio, theta/alpha ratio and theta/beta ratio were found for several electrode sites. In addition, FP1-C3 pair of electrodes displayed greater coherence for theta band while F4-P4, F4-T6, F8-T6 and C4-P4 pairs of electrodes showed greater coherence for alpha band. These results indicate that mystical experiences are mediated by marked changes in EEG power and coherence. These changes implicate several cortical areas of the brain in both hemispheres.

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

    Science.gov (United States)

    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.

  4. Statistical methods to estimate treatment effects from multichannel electroencephalography (EEG) data in clinical trials.

    Science.gov (United States)

    Ma, Junshui; Wang, Shubing; Raubertas, Richard; Svetnik, Vladimir

    2010-07-15

    With the increasing popularity of using electroencephalography (EEG) to reveal the treatment effect in drug development clinical trials, the vast volume and complex nature of EEG data compose an intriguing, but challenging, topic. In this paper the statistical analysis methods recommended by the EEG community, along with methods frequently used in the published literature, are first reviewed. A straightforward adjustment of the existing methods to handle multichannel EEG data is then introduced. In addition, based on the spatial smoothness property of EEG data, a new category of statistical methods is proposed. The new methods use a linear combination of low-degree spherical harmonic (SPHARM) basis functions to represent a spatially smoothed version of the EEG data on the scalp, which is close to a sphere in shape. In total, seven statistical methods, including both the existing and the newly proposed methods, are applied to two clinical datasets to compare their power to detect a drug effect. Contrary to the EEG community's recommendation, our results suggest that (1) the nonparametric method does not outperform its parametric counterpart; and (2) including baseline data in the analysis does not always improve the statistical power. In addition, our results recommend that (3) simple paired statistical tests should be avoided due to their poor power; and (4) the proposed spatially smoothed methods perform better than their unsmoothed versions. Copyright 2010 Elsevier B.V. All rights reserved.

  5. Similarity Analysis of EEG Data Based on Self Organizing Map Neural Network

    Directory of Open Access Journals (Sweden)

    Ibrahim Salem Jahan

    2014-01-01

    Full Text Available The Electroencephalography (EEG is the recording of electrical activity along the scalp. This recorded data are very complex. EEG has a big role in several applications such as in the diagnosis of human brain diseases and epilepsy. Also, we can use the EEG signals to control an external device via Brain Computer Interface (BCI by our mind. There are many algorithms to analyse the recorded EEG data, but it still remains one of the big challenges in the world. In this article, we extended our previous proposed method. Our extended method uses Self-organizing Map (SOM as an EEG data classifier. The proposed method we can divide in following steps: capturing EEG raw data from the sensors, applying filters on this data, we will use the frequencies in the range from 0.5~Hz to 60~Hz, smoothing the data with 15-th order of Polynomial Curve Fitting, converting filtered data into text using Turtle Graphic, Lempel-Ziv complexity for measuring similarity between two EEG data trials and Self-Organizing Map Neural Network as a final classifiers. The experiment results show that our model is able to detect up to 96% finger movements correctly.

  6. Hybrid wavelet and EMD/ICA approach for artifact suppression in pervasive EEG.

    Science.gov (United States)

    Bono, Valentina; Das, Saptarshi; Jamal, Wasifa; Maharatna, Koushik

    2016-07-15

    Electroencephalogram (EEG) signals are often corrupted with unintended artifacts which need to be removed for extracting meaningful clinical information from them. Typically a priori knowledge of the nature of the artifacts is needed for such purpose. Artifact contamination of EEG is even more prominent for pervasive EEG systems where the subjects are free to move and thereby introducing a wide variety of motion-related artifacts. This makes hard to get a priori knowledge about their characteristics rendering conventional artifact removal techniques often ineffective. In this paper, we explore the performance of two hybrid artifact removal algorithms: Wavelet Packet Transform followed by Independent Component Analysis (WPTICA) and Wavelet Packet Transform followed by Empirical Mode Decomposition (WPTEMD) in pervasive EEG recording scenario, assuming existence of no a priori knowledge about the artifacts and compare their performance with two existing artifact removal algorithms. Artifact cleaning performance has been measured using Root Mean Square Error (RMSE) and Artifact to Signal Ratio (ASR)-an index similar to traditional Signal to Noise Ratio (SNR), and also by observing normalized power distribution topography over the scalp. Comparison has been made first using semi-simulated signals and then with real experimentally acquired EEG data with commercially available 19-channel pervasive EEG system Enobio corrupted by eight types of artifact. Our explorations show that WPTEMD consistently gives best artifact cleaning performance not only in semi-simulated scenario but also in the case of real EEG data containing artifacts. Copyright © 2016 Elsevier B.V. All rights reserved.

  7. EEG alpha phenotypes: linkage analyses and relation to alcohol dependence in an American Indian community study

    Directory of Open Access Journals (Sweden)

    Phillips Evelyn

    2010-03-01

    Full Text Available Abstract Background Evidence for a high degree of heritability of EEG alpha phenotypes has been demonstrated in twin and family studies in a number of populations. However, information on linkage of this phenotype to specific chromosome locations is still limited. This study's aims were to map loci linked to EEG alpha phenotypes and to determine if there was overlap with loci previously mapped for alcohol dependence in an American Indian community at high risk for substance dependence. Methods Each participant gave a blood sample and completed a structured diagnostic interview using the Semi Structured Assessment for the Genetics of Alcoholism. Bipolar EEGs were collected and spectral power determined in the alpha (7.5-12.0 Hz frequency band for two composite scalp locations previously identified by principal components analyses (bilateral fronto-central and bilateral centro-parietal-occipital. Genotypes were determined for a panel of 791 micro-satellite polymorphisms in 410 members of multiplex families using SOLAR. Results Sixty percent of this study population had a lifetime diagnosis of alcohol dependence. Analyses of multipoint variance component LOD scores, for the EEG alpha power phenotype, revealed two loci that had a LOD score of 3.0 or above for the fronto-central scalp region on chromosomes 1 and 6. Additionally, 4 locations were identified with LOD scores above 2.0 on chromosomes 4, 11, 14, 16 for the fronto-central location and one on chromosome 2 for the centro-parietal-occipital location. Conclusion These results corroborate the importance of regions on chromosome 4 and 6 highlighted in prior segregation studies in this and other populations for alcohol dependence-related phenotypes, as well as other areas that overlap with other substance dependence phenotypes identified in previous linkage studies in other populations. These studies additionally support the construct that EEG alpha recorded from fronto-central scalp areas may

  8. Treatment of total scalp avulsion by an advanced microsurgical method involving the subcutaneous tissue suspension by the tight suture of scalp tissue around anastomotic stoma.

    Science.gov (United States)

    Ding, Wei; Liu, Minfeng; Chen, Li; Xu, Lei; Rui, Yongjun; Gu, Yudong

    2015-03-01

    Total scalp avulsion is a rare but challenging surgical trauma to manage. This study reports 8 cases of total scalp avulsion between 2001 and 2008. In all these cases, the patients were subjected to vascular replantation of the scalp. Microvascular technique after the debridement was used for scalp replantation in all these patients. Study outcome was that between 2001 and 2004, only 1 case had shown major scalp revival and scalp survival whereas in 3 other cases, the scalp survival failed. This may be attributed to the poor microscopic anastomosis. However, between 2005 and 2008, scalp survival was reported in all the cases, which was chiefly due the advanced microsurgical method adopted. In this advanced microsurgical technique, the subcutaneous tissue was suspended by the tight suture of scalp tissue around the anastomotic stoma, which resulted in scalp survival in all the cases. Microsurgical scalp replantation is an effective treatment for scalp avulsion. The key to the successful scalp replantation is high-quality vascular anastomosis involving subcutaneous tissue suspension via the tight suture of scalp tissue around the anastomotic stoma careful debridement.

  9. Scalp hyperkeratosis and alopecia in children of color.

    Science.gov (United States)

    Coley, Marcelyn K; Bhanusali, Dhaval G; Silverberg, Jonathan I; Alexis, Andrew F; Silverberg, Nanette B

    2011-05-01

    Scalp hyperkeratosis and/or alopecia are common pediatric dermatologic findings. In Caucasian children, scalp hyperkeratosis of childhood is most often associated with atopic and seborrheic dermatides. Recent data is lacking on the clinical meaning of scalp hyperkeratosis and alopecia in children of color. To determine diagnosis associated with scalp hyperkeratosis and/or alopecia in a predominately Black and Hispanic pediatric patient population. A retrospective chart review was conducted for all children (0-17 years of age) seen at our institution who had a scalp fungal culture for the evaluation of scalp hyperkeratosis and/or alopecia from January 2007 to September 2009. Fungal culture was performed using cotton swab technique, plating onto Sabouraud's and Mycosel media. Demographic features, fungal culture results, clinical symptoms, physical findings and final diagnosis were reviewed. 164 children were identified who were eligible for inclusion in the study, 75 of whom were Black and 56 Hispanic/Latino. Scalp hyperkeratosis was noted in 106 patients and alopecia was noted in 71 subjects. Tinea capitis was the final diagnosis in 50 out of 80 children who had hyperkeratosis without alopecia (60%), 16 of 43 children with alopecia alone (37.2%) and 23 of 28 children with both hyperkeratosis and alopecia (82.1%, P=0.0007). The odds ratio of tinea capitis in the presence of hyperkeratosis with alopecia was 7.49 with a 95 percent confidence limit of 2.19-25.70. Scalp hyperkeratosis, especially when accompanied by alopecia, is usually associated with tinea capitis in Black and Hispanic children. Fungal culture and empirical anti-fungal therapy are warranted in children of color with scalp hyperkeratosis.

  10. 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.

  11. Delayed Diagnosis: Giant Basal Cell Carcinoma of Scalp

    Directory of Open Access Journals (Sweden)

    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.

  12. 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

    Energy Technology Data Exchange (ETDEWEB)

    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)

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  14. Deployment of Mobile EEG Technology in an Art Museum Setting: Evaluation of Signal Quality and Usability

    Directory of Open Access Journals (Sweden)

    Jesus G. Cruz-Garza

    2017-11-01

    Full Text Available Electroencephalography (EEG has emerged as a powerful tool for quantitatively studying the brain that enables natural and mobile experiments. Recent advances in EEG have allowed for the use of dry electrodes that do not require a conductive medium between the recording electrode and the scalp. The overall goal of this research was to gain an understanding of the overall usability and signal quality of dry EEG headsets compared to traditional gel-based systems in an unconstrained environment. EEG was used to collect Mobile Brain-body Imaging (MoBI data from 432 people as they experienced an art exhibit in a public museum. The subjects were instrumented with either one of four dry electrode EEG systems or a conventional gel electrode EEG system. Each of the systems was evaluated based on the signal quality and usability in a real-world setting. First, we describe the various artifacts that were characteristic of each of the systems. Second, we report on each system's usability and their limitations in a mobile setting. Third, to evaluate signal quality for task discrimination and characterization, we employed a data driven clustering approach on the data from 134 of the 432 subjects (those with reliable location tracking information and usable EEG data to evaluate the power spectral density (PSD content of the EEG recordings. The experiment consisted of a baseline condition in which the subjects sat quietly facing a white wall for 1 min. Subsequently, the participants were encouraged to explore the exhibit for as long as they wished (piece-viewing. No constraints were placed upon the individual in relation to action, time, or navigation of the exhibit. In this freely-behaving approach, the EEG systems varied in their capacity to record characteristic modulations in the EEG data, with the gel-based system more clearly capturing stereotypical alpha and beta-band modulations.

  15. Toward a quantitative description of large-scale neocortical dynamic function and EEG.

    Science.gov (United States)

    Nunez, P L

    2000-06-01

    A general conceptual framework for large-scale neocortical dynamics based on data from many laboratories is applied to a variety of experimental designs, spatial scales, and brain states. Partly distinct, but interacting local processes (e.g., neural networks) arise from functional segregation. Global processes arise from functional integration and can facilitate (top down) synchronous activity in remote cell groups that function simultaneously at several different spatial scales. Simultaneous local processes may help drive (bottom up) macroscopic global dynamics observed with electroencephalography (EEG) or magnetoencephalography (MEG). A local/global dynamic theory that is consistent with EEG data and the proposed conceptual framework is outlined. This theory is neutral about properties of neural networks embedded in macroscopic fields, but its global component makes several qualitative and semiquantitative predictions about EEG measures of traveling and standing wave phenomena. A more general "metatheory" suggests what large-scale quantitative theories of neocortical dynamics may be like when more accurate treatment of local and nonlinear effects is achieved. The theory describes the dynamics of excitatory and inhibitory synaptic action fields. EEG and MEG provide large-scale estimates of modulation of these synaptic fields around background levels. Brain states are determined by neuromodulatory control parameters. Purely local states are dominated by local feedback gains and rise and decay times of postsynaptic potentials. Dominant local frequencies vary with brain region. Other states are purely global, with moderate to high coherence over large distances. Multiple global mode frequencies arise from a combination of delays in corticocortical axons and neocortical boundary conditions. Global frequencies are identical in all cortical regions, but most states involve dynamic interactions between local networks and the global system. EEG frequencies may involve a

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

    Science.gov (United States)

    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.

  17. Cross-conditional entropy and coherence analysis of pharmaco-EEG changes induced by alprazolam.

    Science.gov (United States)

    Alonso, J F; Mañanas, M A; Romero, S; Rojas-Martínez, M; Riba, J

    2012-06-01

    Quantitative analysis of electroencephalographic signals (EEG) and their interpretation constitute a helpful tool in the assessment of the bioavailability of psychoactive drugs in the brain. Furthermore, psychotropic drug groups have typical signatures which relate biochemical mechanisms with specific EEG changes. To analyze the pharmacological effect of a dose of alprazolam on the connectivity of the brain during wakefulness by means of linear and nonlinear approaches. EEG signals were recorded after alprazolam administration in a placebo-controlled crossover clinical trial. Nonlinear couplings assessed by means of corrected cross-conditional entropy were compared to linear couplings measured with the classical magnitude squared coherence. Linear variables evidenced a statistically significant drug-induced decrease, whereas nonlinear variables showed significant increases. All changes were highly correlated to drug plasma concentrations. The spatial distribution of the observed connectivity changes clearly differed from a previous study: changes before and after the maximum drug effect were mainly observed over the anterior half of the scalp. Additionally, a new variable with very low computational cost was defined to evaluate nonlinear coupling. This is particularly interesting when all pairs of EEG channels are assessed as in this study. Results showed that alprazolam induced changes in terms of uncoupling between regions of the scalp, with opposite trends depending on the variables: decrease in linear ones and increase in nonlinear features. Maps provided consistent information about the way brain changed in terms of connectivity being definitely necessary to evaluate separately linear and nonlinear interactions.

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

    Science.gov (United States)

    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.

  19. Lasting depression in corticomotor excitability associated with local scalp cooling.

    Science.gov (United States)

    Tremblay, François; Remaud, Anthony; Mekonnen, Abeye; Gholami-Boroujeny, Shiva; Racine, Karl-Édouard; Bolic, Miodrag

    2015-07-23

    In this study, we investigated the effect of local scalp cooling on corticomotor excitability with transcranial magnetic simulation (TMS). Participants (healthy male adults, n=12) were first assessed with TMS to derive baseline measure of excitability from motor evoked potentials (MEPs) using the right first dorsal interosseous as the target muscle. Then, local cooling was induced on the right hemi-scalp (upper frontal region ∼ 15 cm(2)) by means of a cold wrap. The cooling was maintained for 10-15 min to get a decrease of at least 10°C from baseline temperature. In the post-cooling period, both scalp temperature and MEPs were reassessed at specific time intervals (i.e., T0, T10, T20 and T30 min). Scalp surface temperatures dropped on average by 12.5°C from baseline at T0 (pscalp temperature with lasting changes in corticomotor excitability. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  20. Body to Scalp: Evolving Trends in Body Hair Transplantation

    Science.gov (United States)

    Saxena, Kuldeep; Savant, Sandeep S.

    2017-01-01

    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. PMID:28584752

  1. 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.

  2. Body to Scalp: Evolving Trends in Body Hair Transplantation.

    Science.gov (United States)

    Saxena, Kuldeep; Savant, Sandeep S

    2017-01-01

    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.

  3. Simultaneous EEG-fMRI for working memory of the human brain.

    Science.gov (United States)

    Ahmad, Rana Fayyaz; Malik, Aamir Saeed; Kamel, Nidal; Reza, Faruque; Abdullah, Jafri Malin

    2016-06-01

    Memory plays an important role in human life. Memory can be divided into two categories, i.e., long term memory and short term memory (STM). STM or working memory (WM) stores information for a short span of time and it is used for information manipulations and fast response activities. WM is generally involved in the higher cognitive functions of the brain. Different studies have been carried out by researchers to understand the WM process. Most of these studies were based on neuroimaging modalities like fMRI, EEG, MEG etc., which use standalone processes. Each neuroimaging modality has some pros and cons. For example, EEG gives high temporal resolution but poor spatial resolution. On the other hand, the fMRI results have a high spatial resolution but poor temporal resolution. For a more in depth understanding and insight of what is happening inside the human brain during the WM process or during cognitive tasks, high spatial as well as high temporal resolution is desirable. Over the past decade, researchers have been working to combine different modalities to achieve a high spatial and temporal resolution at the same time. Developments of MRI compatible EEG equipment in recent times have enabled researchers to combine EEG-fMRI successfully. The research publications in simultaneous EEG-fMRI have been increasing tremendously. This review is focused on the WM research involving simultaneous EEG-fMRI data acquisition and analysis. We have covered the simultaneous EEG-fMRI application in WM and data processing. Also, it adds to potential fusion methods which can be used for simultaneous EEG-fMRI for WM and cognitive tasks.

  4. Aplasia Cutis Congenita of the Scalp with a Familial Pattern.

    Science.gov (United States)

    AlShehri, Waleed; AlFadil, Sara; AlOthri, Alhanouf; Alabdulkarim, Abdulaziz O; Wani, Shabeer A; Rabah, Sari M

    2016-01-01

    Aplasia Cutis Congenita (ACC) is a condition characterized by congenital absence of skin, usually on the scalp. ACC can occur as an isolated condition or in the presence of other congenital anomalies. Here we describe a case of a 16-day-old baby girl with an isolated ACC of the scalp. Her elder two siblings have been diagnosed with ACC with concomitant cardiac or limb anomalies. The patient was managed conservatively until the defect has formed scar tissue 6 months later.

  5. Congenital skull defect and neurofibroma: without scalp and other abnormalities.

    Science.gov (United States)

    Wang, Jie-Cong; Wei, Liu; Xu, Jia; Liu, Jian-Feng; Gui, Lai

    2012-07-01

    Congenital skull defect is a rare malformation that is usually associated with congenital anomalies of the scalp and comparable lesions in the brain, spinal cord, limbs, and skeletal muscle. Most previously reported cases have described skull defects with aplasia cutis congenita and other congenital abnormalities. Very few patients with skull defects present with an intact scalp or neurofibroma. The authors report an adult patient with a rare congenital skull defect and local neurofibroma.

  6. Gaze-direction-based MEG averaging during audiovisual speech perception

    Directory of Open Access Journals (Sweden)

    Lotta Hirvenkari

    2010-03-01

    Full Text Available To take a step towards real-life-like experimental setups, we simultaneously recorded magnetoencephalographic (MEG signals and subject’s gaze direction during audiovisual speech perception. The stimuli were utterances of /apa/ dubbed onto two side-by-side female faces articulating /apa/ (congruent and /aka/ (incongruent in synchrony, repeated once every 3 s. Subjects (N = 10 were free to decide which face they viewed, and responses were averaged to two categories according to the gaze direction. The right-hemisphere 100-ms response to the onset of the second vowel (N100m’ was a fifth smaller to incongruent than congruent stimuli. The results demonstrate the feasibility of realistic viewing conditions with gaze-based averaging of MEG signals.

  7. 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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  10. EEG Controlled Wheelchair

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    Swee Sim Kok

    2016-01-01

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

  11. Managing Scalp Psoriasis: An Evidence-Based Review.

    Science.gov (United States)

    Wang, Ting-Shun; Tsai, Tsen-Fang

    2017-02-01

    Scalp psoriasis is commonly the initial presentation of psoriasis, and almost 80 % of patients with psoriasis will eventually experience it. Although several systematic reviews and guidelines exist, an up-to-date evidence-based review including more recent progress on the use of biologics and new oral small molecules was timely. Of the 475 studies initially retrieved from PubMed and the 845 from Embase (up to May 2016), this review includes 27 clinical trials, four papers reporting pooled analyses of other clinical trials, ten open-label trials, one case series, and two case reports after excluding non-English literature. To our knowledge, few randomized controlled trials (RCTs) are conducted specifically in scalp psoriasis. Topical corticosteroids provide good effects and are usually recommended as first-line treatment. Calcipotriol-betamethasone dipropionate is well tolerated and more effective than either of its individual components. Localized phototherapy is better than generalized phototherapy on hair-bearing areas. Methotrexate, cyclosporine, fumaric acid esters, and acitretin are well-recognized agents in the treatment of psoriasis, but we found no published RCTs evaluating these agents specifically in scalp psoriasis. Biologics and new small-molecule agents show excellent effects on scalp psoriasis, but the high cost of these treatments mean they may be limited to use in extensive scalp psoriasis. More controlled studies are needed for an evidence-based approach to scalp psoriasis.

  12. Scalp reconstruction: an algorithmic approach and systematic review.

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    Desai, Shaun C; Sand, Jordan P; Sharon, Jeffrey D; Branham, Gregory; Nussenbaum, Brian

    2015-01-01

    Reconstruction of the scalp after acquired defects remains a common challenge for the reconstructive surgeon, especially in a patient with a history of radiation to the area. To review the current literature and describe a novel algorithm to help guide the reconstructive surgeon in determining the optimal reconstruction from a cosmetic and functional standpoint. Pertinent surgical anatomy, considerations for patient and technique selection, reconstructive goals, as well as the reconstructive ladder, are also discussed. A PubMed and Medline search was performed of the entire English literature with respect to scalp reconstruction. Priority of review was given to those studies with higher-quality levels of evidence. Size, location, radiation history, and potential for hairline distortion are important factors in determining the ideal reconstruction. The tighter and looser areas of the scalp play a major role in the potential for primary or local flap closure. Patients with medium to large defects and a history of radiation will likely benefit from free tissue transfer. Ideal reconstruction of scalp defects relies on a comprehensive understanding of scalp anatomy, a full consideration of the armamentarium of surgical techniques, and a detailed appraisal of patient factors and expectations. The simplest reconstruction should be used whenever possible to provide the most functional and aesthetic scalp reconstruction, with the least amount of complexity. NA.

  13. Using Feily's method prevented scalp necrosis in three patients incline to the scalp recipient necrosis; what is new in prevention of scalp necrosis?

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    Feily, Amir; Feily, Ahmad

    2017-01-01

    Serious complications arising from surgical hair restoration are relatively uncommon following well-performed and well-planned surgery by skillful surgical techniques, good communication, and postoperative follow-up. Surgical complications often categorized as those which occur in the donor site and the recipient site. In this paper among recipient area complication we focused on recipient area necrosis that arises when an increased number of recipient grafts are utilized and de-vascularization of the scalp occurs as a result of the large wound area due to the dense packing splitting of recipient skin. Recently, Feily et al. explained an interesting method to prevent development of recipient area necrosis following a hair transplant procedure. Herein we reported three cases of dense hair transplantation using the Feilys method that after slitting they troubled by unusual long lasting dark areas on the scalp and they need more than 24 hr's patience for prevention of scalp necrosis. © 2016 Wiley Periodicals, Inc.

  14. Hyperscanning MEG for understanding mother–child cerebral interactions

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    Masayuki eHirata

    2014-03-01

    Full Text Available Child development is seriously affected by social interactions with caregivers, which may lead to forming social minds in our daily life afterward. However, the underlying neural mechanism for such interactions has not yet been revealed. This article introduces a magnetoencephalographic (MEG hyperscanning system to examine brain-to-brain interactions between a mother and her child.We used two whole-head MEG systems placed in the same magnetically-shielded room. One is a 160-channel gradiometer system for an adult and the other is a 151-channel gradiometer system for a child. We developed an audio-visual presentation system, which enabled a mother and her child to look at each other in real time. In each MEG system, a video camera was placed behind a half-mirror screen for visual presentation to obtain the subjects’ facial expressions. The visual presentation system is capable of displaying not only real-time facial expression but also processed facial expression such as a still face or delayed facial expressions. A projector system displays the side-by-side face images of the mother and child, and the images are divided into each face using splitting mirrors and each face is displayed on the half-mirror screen in front of the other subject.To the best of our knowledge, our system is the first MEG hyperscanning system in a single shielded room, and may contribute to elucidating brain-to-brain interactions not only between a mother and her child but also in general inter-individual, brain-to-brain interactions.

  15. Comparative Study of Wavelet-Based Unsupervised Ocular Artifact Removal Techniques for Single-Channel EEG Data.

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    Khatun, Saleha; Mahajan, Ruhi; Morshed, Bashir I

    2016-01-01

    Electroencephalogram (EEG) is a technique for recording the asynchronous activation of neuronal firing inside the brain with non-invasive scalp electrodes. Artifacts, such as eye blink activities, can corrupt these neuronal signals. While ocular artifact (OA) removal is well investigated for multiple channel EEG systems, in alignment with the recent momentum toward minimalistic EEG systems for use in natural environments, we investigate unsupervised and effective removal of OA from single-channel streaming raw EEG data. In this paper, the unsupervised wavelet transform (WT) decomposition technique was systematically evaluated for the effectiveness of OA removal for a single-channel EEG system. A set of seven raw EEG data set was analyzed. Two commonly used WT methods, Discrete Wavelet Transform (DWT) and Stationary Wavelet Transform (SWT), were applied. Four WT basis functions, namely, haar, coif3, sym3, and bior4.4, were considered for OA removal with universal threshold and statistical threshold (ST). To quantify OA removal efficacy from single-channel EEG, five performance metrics were utilized: correlation coefficients, mutual information, signal-to-artifact ratio, normalized mean square error, and time-frequency analysis. The temporal and spectral analysis shows that the optimal combination could be DWT with ST with coif3 or bior4.4 to remove OA among 16 combinations. This paper demonstrates that the WT can be an effective tool for unsupervised OA removal from single-channel EEG data for real-time applications.

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

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    Oliveira Filho, Florêncio Mendes; Leyva Cruz, Juan Alberto

    2017-01-01

    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. PMID:28910294

  17. 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 [scalp cooling and control groups. Only adverse events related to device use were collected; 54 adverse events were reported in the cooling group, all grades 1 and 2. There were no serious adverse device events. Among 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 compared with those who received no scalp cooling. Further research is needed to assess longer-term efficacy and adverse effects. clinicaltrials.gov Identifier: NCT01986140.

  18. Detection of epileptic activity in fMRI without recording the EEG

    Science.gov (United States)

    Lopes, R.; Lina, J.M.; Fahoum, F.; Gotman, J.

    2013-01-01

    EEG–fMRI localizes epileptic foci by detecting cerebral hemodynamic changes that are correlated to epileptic events visible in EEG. However, scalp EEG is insensitive to activity restricted to deep structures and recording the EEG in the scanner is complex and results in major artifacts that are difficult to remove. This study presents a new framework for identifying the BOLD manifestations of epileptic discharges without having to record the EEG. The first stage is based on the detection of epileptic events for each voxel by sparse representation in the wavelet domain. The second stage is to gather voxels according to proximity in time and space of detected activities. This technique was evaluated on data generated by superposing artificial responses at different locations and responses amplitude in the brain for 6 control subject runs. The method was able to detect effectively and consistently for responses amplitude of at least 1% above baseline. 46 runs from 15 patients with focal epilepsy were investigated. The results demonstrate that the method detected at least one concordant event in 37/41 runs. The maps of activation obtained from our method were more similar to those obtained by EEG–fMRI than to those obtained by the other method used in this context, 2D-Temporal Cluster Analysis. For 5 runs without event read on scalp EEG, 3 runs showed an activation concordant with the patient’s diagnostic. It may therefore be possible, at least when spikes are infrequent, to detect their BOLD manifestations without having to record the EEG. PMID:22306797

  19. ReliefF-Based EEG Sensor Selection Methods for Emotion Recognition.

    Science.gov (United States)

    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

  20. Analysis of EEG signals under flash stimulation for migraine and epileptic patients.

    Science.gov (United States)

    Akben, Selahaddin Batuhan; Subasi, Abdülhamit; Tuncel, Deniz

    2011-06-01

    Migraine and epilepsy are both persistent disorders characterised by recurrent neurological attacks. Visual symptoms and hypersensitivity to light stimuli are frequent in migraine. Analysis of EEG signals under flash stimulation for migraine and epileptic patients is not a new method. But magnitude increasing under flash stimulation for migraine patients has not been studied yet. The aims of this study is the analysis of multichannel electroencephalogram (EEG) in migraine and epileptic patients by visual evoked potentials (VEP) and investigate the existence of magnitude increasing under flash stimulation for migraine patients. In this study as a method of flash stimuli at frequencies of 2, 4 and 6 Hz were applied to different migraine and epileptic patients under pain-free phase with the EEG recorded from 18 scalp electrodes, referred to the linked earlobes. We used AR parametric method to analyze and characterize EEG signals in migraine and epileptic patients. The variations in the EEG power spectra shapes were examined in order to obtain medical information. These power spectra were then used to compare the applied method in terms of their frequency resolution and the effects in determination of migraine and epilepsy. Global performance of the proposed methods was evaluated by means of the visual inspection of power spectral densities (PSDs). For the migraine patients, an increase in amplitude has observed at the beta bands of EEG signals under flash stimulation as compared to EEG signals without stimulation. As opposed to this, for epileptic patients, an increase in amplitude has observed at the alpha bands of EEG signals without flash stimulation. Meanwhile for the control groups, there is no change between EEG signals under flash stimulation and without flash stimulation.

  1. A Multivariate Approach for Patient-Specific EEG Seizure Detection Using Empirical Wavelet Transform.

    Science.gov (United States)

    Bhattacharyya, Abhijit; Pachori, Ram Bilas

    2017-09-01

    This paper investigates the multivariate oscillatory nature of electroencephalogram (EEG) signals in adaptive frequency scales for epileptic seizure detection. The empirical wavelet transform (EWT) has been explored for the multivariate signals in order to determine the joint instantaneous amplitudes and frequencies in signal adaptive frequency scales. The proposed multivariate extension of EWT has been studied on multivariate multicomponent synthetic signal, as well as on multivariate EEG signals of Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) scalp EEG database. In a moving-window-based analysis, 2-s-duration multivariate EEG signal epochs containing five automatically selected channels have been decomposed and three features have been extracted from each 1-s part of the 2-s-duration joint instantaneous amplitudes of multivariate EEG signals. The extracted features from each oscillatory level have been processed using a proposed feature processing step and joint features have been computed in order to achieve better discrimination of seizure and seizure-free EEG signal epochs. The proposed detection method has been evaluated over 177 h of EEG records using six classifiers. We have achieved average sensitivity, specificity, and accuracy values as 97.91%, 99.57%, and 99.41%, respectively, using tenfold cross-validation method, which are higher than the compared state of art methods studied on this database. Efficient detection of epileptic seizure is achieved when seizure events appear for long duration in hours long EEG recordings. The proposed method develops time-frequency plane for multivariate signals and builds patient-specific models for EEG seizure detection.

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

    Science.gov (United States)

    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.

  3. 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.

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

    Science.gov (United States)

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

    2014-09-30

    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 that modify the recorded traces and seek to minimize the impact of reference electrode activity upon functions of the original EEG recordings. We provide a novel, statistically robust procedure that adapts a robust maximum-likelihood type estimator to the problem of reference estimation, reduces the influence of neural activity from the re-referencing operation, and maintains good performance in a wide variety of empirical scenarios. The performance of the proposed and existing re-referencing procedures are validated in simulation and with examples of EEG recordings. To facilitate this comparison, channel-to-channel correlations are investigated theoretically and in simulation. The proposed procedure avoids using data contaminated by neural signal and remains unbiased in recording scenarios where physical references, the common average reference (CAR) and the reference estimation standardization technique (REST) are not optimal. The proposed procedure is simple, fast, and avoids the potential for substantial bias when analyzing low-density EEG data. Copyright © 2014 Elsevier B.V. All rights reserved.

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

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    Parameswaran Mahadeva Iyer

    Full Text Available 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 (p<0.0005. Among patients, clustering coefficient in alpha and gamma bands was increased in all regions of the scalp and connectivity were significantly increased (p=0.02. Nodal network showed increased assortativity in alpha band in the patients group. The Clustering Coefficient in Partial Directed Connectivity (PDC showed significantly higher values for patients in alpha, beta, gamma, theta and delta frequencies (p=0.05.There is increased connectivity in the fronto-central regions of the scalp and areas corresponding to Salience and Default Mode network in ALS, suggesting a pathologic disruption of neuronal networking in early disease states. Spectral EEG has potential utility as a biomarker in ALS.

  6. A Robustness Comparison of Two Algorithms Used for EEG Spike Detection.

    Science.gov (United States)

    Chaibi, Sahbi; Lajnef, Tarek; Ghrob, Abdelbacet; Samet, Mounir; Kachouri, Abdennaceur

    2015-01-01

    Spikes and sharp waves recorded on scalp EEG may play an important role in identifying the epileptogenic network as well as in understanding the central nervous system. Therefore, several automatic and semi-automatic methods have been implemented to detect these two neural transients. A consistent gold standard associated with a high degree of agreement among neuroscientists is required to measure relevant performance of different methods. In fact, scalp EEG data can often be corrupted by a set of artifacts and are not always served as data of gold standard. For this reason, the use of intracerebral EEG data mixed with gaussian noise seems to best resemble the output of scalp EEG brain and serves as a consistent gold standard. In the present framework, we test the robustness of two important methods that have been previously used for the automatic detection of epileptiform transients (spikes and sharp waves). These methods are based respectively on Discrete Wavelet Transform (DWT) and Continuous Wavelet Transform (CWT). Our purpose is to elaborate a comparative study in terms of sensitivity and selectivity changes via the decrease of Signal to Noise Ratio (SNR), which is ranged from 10 dB up to -10 dB. The results demonstrate that, DWT approach turns to be more stable in terms of sensitivity, and it successfully follows the detection of relevant spikes with the decrease of SNR. However, CWT-based approach remains more stable in terms of selectivity, so that, it performs well in terms of rejecting false spikes compared to DWT approach.

  7. Changes in EEG alpha power during simulated driving: a demonstration.

    Science.gov (United States)

    Schier, M A

    2000-08-01

    The aim was to assess the suitability of EEG-based techniques to recording activity during a driving simulation task. To achieve this, an inexpensive driving simulator (comprising a steering wheel, pedals and gear shift) were made to function with a personal computer running 'Need for Speed' simulation software. Simulators of this type are both inexpensive and relatively realistic. The EEG was recorded from four sites on the scalp (P3, P4, F3, F4) for two laps during the driving task, and during a replay task. The driving task involved participants driving a vehicle on a simulated undulating, sealed surface circuit, without any other vehicles present. Two men were participants in this experiment. Power spectra were computed and integrated to produce values of relative alpha activity for each channel and recording epoch, a time-series of alpha activity during each recorded segment. Overall values for alpha activity indicated an increase for replay compared to driving, and also driving on lap 5 compared to driving on lap 2. The EEG changes are consistent with the notion of overall reduction of attention during the later laps and the replay task and indicate the potential of such measures for complex motor behaviour.

  8. Functional connectivity of EEG signals under laser stimulation in migraine

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    MARINA eDE TOMMASO

    2015-11-01

    Full Text Available In previous studies migraine patients showed some abnormalities of pain related evoked responses, as reduced habituation to repetitive stimulation. In this study we aimed to apply a novel analysis of EEG bands synchronization and directed dynamical influences under painful stimuli in migraine patients compared to non migraine healthy volunteers. Thirty-one migraine without aura outpatients (MIGR were evaluated and compared to 19 controls (CONT. The right hand was stimulated by means of 30 consecutive CO2 laser stimuli. EEG signal was examined by means of Morlet wavelet, synchronization entropy and Granger causality, and the statistic results embedded into a scalp model. The vertex complex of averaged laser evoked responses (LEPs showed reduced habituation compared to controls. In the pre-stimulus phase enhanced synchronization entropy in the 0, 5-30 Hz range was present in MIGR and CONT between the bilateral temporal parietal and the frontal regions around the midline. Migraine patients showed an anticipation of EEG changes preceding the painful stimulation compared to controls. In the post-stimulus phase, the same cortical areas were more connected in MIGR vs CONT. In the totality of patients and controls, the habituation index was negatively correlated with the Granger Causality scores. A different pattern of cortical activation after painful stimulation was present in migraine. The increase in cortical connections during repetitive painful stimulation may subtend the phenomenon of LEPs reduced habituation. Brain network analysis may give an aid in understanding subtle changes of pain processing under laser stimuli in migraine patients.

  9. Detection of EEG-resting state independent networks by eLORETA-ICA method.

    Science.gov (United States)

    Aoki, Yasunori; Ishii, Ryouhei; Pascual-Marqui, Roberto D; Canuet, Leonides; Ikeda, Shunichiro; Hata, Masahiro; Imajo, Kaoru; Matsuzaki, Haruyasu; Musha, Toshimitsu; Asada, Takashi; Iwase, Masao; Takeda, Masatoshi

    2015-01-01

    Recent functional magnetic resonance imaging (fMRI) studies have shown that functional networks can be extracted even from resting state data, the so called "Resting State independent Networks" (RS-independent-Ns) by applying independent component analysis (ICA). However, compared to fMRI, electroencephalography (EEG) and magnetoencephalography (MEG) have much higher temporal resolution and provide a direct estimation of cortical activity. To date, MEG studies have applied ICA for separate frequency bands only, disregarding cross-frequency couplings. In this study, we aimed to detect EEG-RS-independent-Ns and their interactions in all frequency bands. We applied exact low resolution brain electromagnetic tomography-ICA (eLORETA-ICA) to resting-state EEG data in 80 healthy subjects using five frequency bands (delta, theta, alpha, beta and gamma band) and found five RS-independent-Ns in alpha, beta and gamma frequency bands. Next, taking into account previous neuroimaging findings, five RS-independent-Ns were identified: (1) the visual network in alpha frequency band, (2) dual-process of visual perception network, characterized by a negative correlation between the right ventral visual pathway (VVP) in alpha and beta frequency bands and left posterior dorsal visual pathway (DVP) in alpha frequency band, (3) self-referential processing network, characterized by a negative correlation between the medial prefrontal cortex (mPFC) in beta frequency band and right temporoparietal junction (TPJ) in alpha frequency band, (4) dual-process of memory perception network, functionally related to a negative correlation between the left VVP and the precuneus in alpha frequency band; and (5) sensorimotor network in beta and gamma frequency bands. We selected eLORETA-ICA which has many advantages over the other network visualization methods and overall findings indicate that eLORETA-ICA with EEG data can identify five RS-independent-Ns in their intrinsic frequency bands, and correct

  10. MEG-based detection and localization of perilesional dysfunction in chronic stroke

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    Ron K.O. Chu

    2015-01-01

    Full Text Available Post-stroke impairment is associated not only with structural lesions, but also with dysfunction in surviving perilesional tissue. Previous studies using equivalent current dipole source localization of MEG/EEG signals have demonstrated a preponderance of slow-wave activity localized to perilesional areas. Recent studies have also demonstrated the utility of nonlinear analyses such as multiscale entropy (MSE for quantifying neuronal dysfunction in a wide range of pathologies. The current study utilized beamformer-based reconstruction of signals in source space to compare spectral and nonlinear measures of electrical activity in perilesional and healthy cortices. Data were collected from chronic stroke patients and healthy controls, both young and elderly. We assessed relative power in the delta (1–4 Hz, theta (4–7 Hz, alpha (8–12 Hz and beta (15–30 Hz frequency bands, and also measured the nonlinear complexity of electrical activity using MSE. Perilesional tissue exhibited a general slowing of the power spectrum (increased delta/theta, decreased beta as well as a reduction in MSE. All measures tested were similarly sensitive to changes in the posterior perilesional regions, but anterior perilesional dysfunction was detected better by MSE and beta power. The findings also suggest that MSE is specifically sensitive to electrophysiological dysfunction in perilesional tissue, while spectral measures were additionally affected by an increase in rolandic beta power with advanced age. Furthermore, perilesional electrophysiological abnormalities in the left hemisphere were correlated with the degree of language task-induced activation in the right hemisphere. Finally, we demonstrate that single subject spectral and nonlinear analyses can identify dysfunctional perilesional regions within individual patients that may be ideal targets for interventions with noninvasive brain stimulation.

  11. [Scalp penetration acupuncture for insomnia: a randomized controlled trial].

    Science.gov (United States)

    Zhou, Zhang-ling; Shi, Xian; Li, Shao-dan; Guan, Ling

    2010-02-01

    Insomnia has become a threat to public health, and acupuncture has shown an advantage in treatment of insomnia with good efficacy and few side effects. To observe the therapeutic effects of scalp penetration acupuncture for insomnia. A total of 70 insomnia cases meeting inclusion criteria from Department of Acupuncture and Moxibustion, General Hospital of People's Liberation Army were randomly divided into routine acupuncture group and scalp penetration acupuncture group. There were 32 cases in the scalp penetration acupuncture group, and 34 cases in the routine acupuncture group, for four cases lost to follow-up. The insomnia patients were all treated for four weeks. The therapeutic effects, cumulative scores of Pittsburgh Sleep Quality Index (PSQI) and contents of sleep architecture were compared before and after treatment in the two groups. The total response rate of 90.6% in the scalp penetration acupuncture group was higher than 73.5% in the routine acupuncture group (Pefficiency in the scalp penetration acupuncture group were superior to those in the routine acupuncture group (Pacupuncture group significantly increased as compared with those in the routine acupuncture group (Pacupuncture are better than those of routine acupuncture, especially for improving sleep quality, sleep time and sleep efficiency.

  12. Management of aplasia cutis congenita of the scalp.

    Science.gov (United States)

    Harvey, Georgina; Solanki, Nicholas S; Anderson, Peter J; Carney, Bernard; Snell, Broughton J

    2012-11-01

    Aplasia cutis congenita (ACC) is a rare condition commonly affecting the scalp in which there is a focal deficiency of cutaneous tissues of varying severity ranging from an absence of skin through to full thickness defects involving deeper elements such as bone and dura. Lesions of the scalp can be associated with complications including infection, hemorrhage, thrombosis, and seizures. Opinions in the current literature regarding management of this condition are varied with both conservative and surgical management advocated. Conservative treatment consists of regular wound dressings and systemic antibiotics, while surgical management commonly involves skin grafting and local flaps. A retrospective case review was performed to audit the outcomes of patients with ACC of the scalp managed at the Women's and Children's Hospital (WCH) in Adelaide, Australia from 2002 to 2012. Cases were identified from admission coding diagnoses and data was retrieved from patient case notes. Seventeen cases of ACC were identified. The most common location involved was the scalp vertex. Thirteen patients were managed conservatively and 4 had primary surgical intervention. Of the cases that were managed with primary surgery, 2 had complications. None of the conservatively managed patients had complications in the acute setting. At the WCH, we advocate adopting a conservative approach to management of ACC of the scalp. Defects can be successfully managed with a combination of regular dressings and systemic antibiotics. Regular wound monitoring is essential to detect any complications early to instigate appropriate treatment and determine the need for emergency surgical management.

  13. Sarcoidosis presenting as non-scarring non-scalp alopecia.

    Science.gov (United States)

    Dan, Luke; Relic, John

    2016-08-01

    In this article we describe a 39-year-old man who presented with non-scarring non-scalp alopecia of his limbs as the initial presentation of sarcoidosis. Alopecia is a rare cutaneous manifestation of sarcoidosis. A literature review has found only one other example of sarcoidosis presenting as non-scarring non-scalp alopecia in an area other than the scalp in a patient who was otherwise asymptomatic. Several reported cases have described scarring alopecia of the scalp, which is the area of skin most commonly affected by sarcoidosis. There has been one documented case of sarcoidosis manifesting as total body non-scarring alopecia in a patient who had systemic symptoms of sarcoidosis. Other cases have presented rare cutaneous manifestations of sarcoidosis but in all these cases several other organ systems have been involved, and the patient has had systemic symptoms on presentation or the cutaneous presentation did not include non-scalp non-scarring alopecia. © 2015 The Australasian College of Dermatologists.

  14. Rejecting deep brain stimulation artefacts from MEG data using ICA and mutual information.

    Science.gov (United States)

    Abbasi, Omid; Hirschmann, Jan; Schmitz, Georg; Schnitzler, Alfons; Butz, Markus

    2016-08-01

    Recording brain activity during deep brain stimulation (DBS) using magnetoencephalography (MEG) can potentially help clarifying the neurophysiological mechanism of DBS. The DBS artefact, however, distorts MEG data significantly. We present an artefact rejection approach to remove the DBS artefact from MEG data. We developed an approach consisting of four consecutive steps: (i) independent component analysis was used to decompose MEG data to independent components (ICs); (ii) mutual information (MI) between stimulation signal and all ICs was calculated; (iii) artefactual ICs were identified by means of an MI threshold; and (iv) the MEG signal was reconstructed using only non-artefactual ICs. This approach was applied to MEG data from five Parkinson's disease patients with implanted DBS stimulators. MEG was recorded with DBS ON (unilateral stimulation of the subthalamic nucleus) and DBS OFF during two experimental conditions: a visual attention task and alternating right and left median nerve stimulation. With the presented approach most of the artefact could be removed. The signal of interest could be retrieved in both conditions. In contrast to existing artefact rejection methods for MEG-DBS data (tSSS and S(3)P), the proposed method uses the actual artefact source, i.e. the stimulation signal, as reference signal. Using the presented method, the DBS artefact can be significantly rejected and the physiological data can be restored. This will facilitate research addressing the impact of DBS on brain activity during rest and various tasks. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. Multifocal scalp abscess with subcutaneous fat necrosis and scarring alopecia as a complication of scalp mesotherapy.

    Science.gov (United States)

    Kadry, Razan; Hamadah, Issam; Al-Issa, Abdullah; Field, Lawrence; Alrabiah, Fahad

    2008-01-01

    Over the past several years, there has been a growing interest in the treatment method termed mesotherapy. Marketed for nonsurgical fat melting, skin rejuvenation, and hair regrowth, this technique has become increasingly popular and, in the public's view, it is considered to be a relatively benign intervention method. Mesotherapy was introduced over 50 years ago by M. Pistor, a French physician who utilized this technique initially as a novel analgesic therapeutic method for a variety of rheumatologic disorders. Since its introduction, the basic principal of locally injecting subcutaneous doses of varying chemicals has been expanded and is now utilized for the aforementioned cosmetic concerns. With its increased popularity, there has been an increase in the number of reported side effects resulting from mesotherapeutic intervention. We report multifocal scalp abscesses with subcutaneous fat necrosis as a direct result of mesotherapy; therefore, requiring extensive surgical repair.

  16. Uncovering cortical MEG responses to listened audiobook stories.

    Science.gov (United States)

    Koskinen, M; Seppä, M

    2014-10-15

    Naturalistic stimuli, such as normal speech and narratives, are opening up intriguing prospects in neuroscience, especially when merging neuroimaging with machine learning methodology. Here we propose a task-optimized spatial filtering strategy for uncovering individual magnetoencephalographic (MEG) responses to audiobook stories. Ten subjects listened to 1-h-long recording once, as well as to 48 repetitions of a 1-min-long speech passage. Employing response replicability as statistical validity and utilizing unsupervised learning methods, we trained spatial filters that were able to generalize over datasets of an individual. For this blind-signal-separation (BSS) task, we derived a version of multi-set similarity-constrained canonical correlation analysis (SimCCA) that theoretically provides maximal signal-to-noise ratio (SNR) in this setting. Irrespective of significant noise in unaveraged MEG traces, the method successfully uncovered feasible time courses up to ~120 Hz, with the most prominent signals below 20 Hz. Individual trial-to-trial correlations of such time courses reached the level of 0.55 (median 0.33 in the group) at ~0.5 Hz, with considerable variation between subjects. By this filtering, the SNR increased up to 20 times. In comparison, independent component analysis (ICA) or principal component analysis (PCA) did not improve SNR notably. The validity of the extracted brain signals was further assessed by inspecting their associations with the stimulus, as well as by mapping the contributing cortical signal sources. The results indicate that the proposed methodology effectively reduces noise in MEG recordings to that extent that brain responses can be seen to nonrecurring audiobook stories. The study paves the way for applications aiming at accurately modeling the stimulus-response-relationship by tackling the response variability, as well as for real-time monitoring of brain signals of individuals in naturalistic experimental conditions. Copyright

  17. 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.

  18. Ultrasonography of Midline Scalp Masses : A Preliminary Report

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    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

  19. Surgical management of scalp arterio-venous malformation and scalp venous malformation: An experience of eleven cases

    Directory of Open Access Journals (Sweden)

    Forhad Hossain Chowdhury

    2013-01-01

    Full Text Available Aims: Scalp arterio-venous malformation (AVM and scalp venous malformation (SVM are rare conditions that usually need surgical treatment. Here, we have reported our experience of the surgical management of such lesions with a short review of the literature. Materials and Methods: In this prospective study, 11 patients with scalp AVM and SVM, who underwent surgical excision of lesion in our hospital from 2006 to 2012, were included. All suspected high-flow AVM were investigated with the selective internal and external carotid digital subtraction angiogram (DSA ± computed tomography (CT scan of brain with CT angiogram or magnetic resonance imaging (MRI of brain with MR angiogram, and all suspected low-flow vascular malformation (VM was investigated with MRI of brain + MR angiogram. Eight were high-flow and three were low-flow VM. Results: All lesions were successfully excised. Scalp cosmetic aspects were acceptable in all cases. There was no major post-operative complication or recurrence till last follow-up. Conclusions: With preoperative appropriate surgical planning, scalp AVM and SVM can be excised without major complication.

  20. Lateralization of language function in epilepsy patients: A high-density scalp-derived event-related potentials (ERP) study.

    Science.gov (United States)

    Trimmel, Karin; Sachsenweger, Jens; Lindinger, Gerald; Auff, Eduard; Zimprich, Fritz; Pataraia, Ekaterina

    2017-03-01

    Language functional magnetic resonance imaging (fMRI) represents the clinical standard for language lateralization assessment in presurgical epilepsy evaluation, but still many patients experience postoperative language deficits. Event-related potentials (ERPs), especially the negative component around and after 400ms, are related to language processing and could therefore represent a complementary method of language lateralization assessment. Scalp EEG was recorded from 64 locations in 36 epilepsy patients and 37 controls during three visually presented language tasks: A short-term language memory task (differentiation memorized vs. unknown words), a phonological task (detection of rhymes in word pairs), and a semantic decision task (differentiation words vs. pseudowords). ERPs were analyzed in the 300ms-800ms epoch. Language fMRI was routinely obtained in patients. ERPs were significantly more negative over the left compared to the right hemisphere in all three tasks in patients and controls. Laterality indices showed highest concordance with fMRI for the Word/Pseudoword Task. ERPs of language processing were lateralized to the left hemisphere in the majority of epilepsy patients and controls. In patients, single-subject laterality indices showed high concordance with fMRI results. Results indicate that scalp-derived ERPs are a promising tool to investigate lateralization of language function in epilepsy patients. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

  1. Dipole localization using simulated intracerebral EEG.

    Science.gov (United States)

    Chang, Nathalie; Gulrajani, Ramesh; Gotman, Jean

    2005-11-01

    In the clinical interpretation of intracerebral EEGs, epileptic foci are commonly identified by visually analyzing the amplitude of the potentials. This is potentially misleading since electrodes record activity from several sources, but the nearest ones generate large amplitudes that can overpower distant sources. Our objective was to improve foci detection in intracerebral recordings by applying source localization methods. Data were simulated by placing 3 sources in a semi-infinite medium near 3 intracerebral electrodes. Potentials were generated and contaminated with white and correlated noise. Two inverse problem algorithms, beamforming and RAP-MUSIC, were used to calculate equivalent dipoles. Simulations for each noise types showed that the two methods detected the source locations accurately, with RAP-MUSIC reporting lower orientation errors. With correlated noise, beamforming reconstructed original source waveforms poorly. A spatial resolution analysis was performed, in which beamforming adequately distinguished sources separated by 1.2 cm, whereas RAP-MUSIC separated sources as close as 0.4-0.6 cm. Both source localization methods proved useful in detecting the location of dipolar sources based on simulated intracerebral potentials. For all simulations, RAP-MUSIC was more accurate than beamforming. It is possible to use source localization methods traditionally applied to scalp recordings for improving source detection from intracerebral recordings.

  2. EEG dynamics during music appreciation.

    Science.gov (United States)

    Lin, Yuan-Pin; Jung, Tzyy-Ping; Chen, Jyh-Horng

    2009-01-01

    This study explores the electroencephalographic (EEG) correlates of emotions during music listening. Principal component analysis (PCA) is used to correlate EEG features with complex music appreciation. This study also applies machine-leaning algorithms to demonstrate the feasibility of classifying EEG dynamics in four subjectively-reported emotional states. The high classification accuracy (81.58+/-3.74%) demonstrates the feasibility of using EEG features to assess emotional states of human subjects. Further, the spatial and spectral patterns of the EEG most relevant to emotions seem reproducible across subjects.

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

    Science.gov (United States)

    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.

  4. Dynamic coupling between fMRI local connectivity and interictal EEG in focal epilepsy: A wavelet analysis approach.

    Science.gov (United States)

    Omidvarnia, Amir; Pedersen, Mangor; Vaughan, David N; Walz, Jennifer M; Abbott, David F; Zalesky, Andrew; Jackson, Graeme D

    2017-11-01

    Simultaneous scalp EEG-fMRI recording is a noninvasive neuroimaging technique for combining electrophysiological and hemodynamic aspects of brain function. Despite the time-varying nature of both measurements, their relationship is usually considered as time-invariant. The aim of this study was to detect direct associations between scalp-recorded EEG and regional changes of hemodynamic brain connectivity in focal epilepsy through a time-frequency paradigm. To do so, we developed a voxel-wise framework that analyses wavelet coherence between dynamic regional phase synchrony (DRePS, calculated from fMRI) and band amplitude fluctuation (BAF) of a target EEG electrode with dominant interictal epileptiform discharges (IEDs). As a proof of concept, we applied this framework to seven patients with focal epilepsy. The analysis produced patient-specific spatial maps of DRePS-BAF coupling, which highlight regions with a strong link between EEG power and local fMRI connectivity. Although we observed DRePS-BAF coupling proximate to the suspected seizure onset zone in some patients, our results suggest that DRePS-BAF is more likely to identify wider 'epileptic networks'. We also compared DRePS-BAF with standard EEG-fMRI analysis based on general linear modelling (GLM). There was, in general, little overlap between the DRePS-BAF maps and GLM maps. However, in some subjects the spatial clusters revealed by these two analyses appeared to be adjacent, particularly in medial posterior cortices. Our findings suggest that (1) there is a strong time-varying relationship between local fMRI connectivity and interictal EEG power in focal epilepsy, and (2) that DRePS-BAF reflect different aspects of epileptic network activity than standard EEG-fMRI analysis. These two techniques, therefore, appear to be complementary. Hum Brain Mapp 38:5356-5374, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  5. Continuous and routine eeg in intensive care

    OpenAIRE

    Ney, JP; Van Der Goes, DN; Nuwer, MR; Nelson, L; Eccher, MA

    2013-01-01

    Objectives: To evaluate the effect of intensive care unit continuous EEG (cEEG) monitoring on inpatient mortality, hospital charges, and length of stay. Methods: A retrospective cross-sectional study was conducted using the Nationwide Inpatient Sample, a dataset representing 20% of inpatient discharges in nonfederal US hospitals. Adult discharge records reporting mechanical ventilation and EEG (routine EEG or cEEG) were included. cEEG was compared with routine EEG alone in association with th...

  6. Aplasia Cutis Congenita of the Scalp with a Familial Pattern

    Directory of Open Access Journals (Sweden)

    Waleed AlShehri

    2016-01-01

    Full Text Available Aplasia Cutis Congenita (ACC is a condition characterized by congenital absence of skin, usually on the scalp. ACC can occur as an isolated condition or in the presence of other congenital anomalies. Here we describe a case of a 16-day-old baby girl with an isolated ACC of the scalp. Her elder two siblings have been diagnosed with ACC with concomitant cardiac or limb anomalies. The patient was managed conservatively until the defect has formed scar tissue 6 months later.

  7. Reconstruction of face and scalp after dog bites in children

    OpenAIRE

    MACEDO,JEFFERSON LESSA SOARES; ROSA,SIMONE CORRÊA; QUEIROZ,MURILO NEVES DE; GOMES,TABATHA GONÇALVES ANDRADE CASTELO BRANCO

    2016-01-01

    ABSTRACT Objective: to evaluate the immediate reconstruction of face and scalp after canine bites in children. Methods: we conducted a prospective series of cases treated at the Emergency Unit of the Asa Norte Regional Hospital, Brasília - DF, from January 1999 to December 2014. At the time of patient admission to the emergency, the primary wound closure of the face and scalp bite was performed, regardless of the time or day of the event. The primary treatment of the bites was by means of d...

  8. Multiple giant scalp metastases of a follicular thyroid carcinoma

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    Rehders Alexander

    2008-08-01

    Full Text Available Abstract Background The occurrence of skin metastases are rare events in the course of a follicular thyroid carcinoma (FTC and usually indicate advanced tumor stages. The scalp is the most affected area of these metastases. Case presentation We present a case of a 76 year old Woman with multiple giant scalp metastases of a follicular carcinoma. These metastases had been resected and wounds had been closed with mesh graft. The 14-months follow up is presented. Conclusion We demonstrate another case with multicentric form. Because of its location and size a primary wound closure was not possible. A healing could be reached using vacuum therapy and mesh graft transplantation.

  9. Two cases of giant pyogenic granuloma of scalp

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    B Satish Chandra

    2013-01-01

    Full Text Available Pyogenic granuloma is a benign vascular tumor of unknown etiology, though multiple factors play a role in its onset, e.g., trauma, chronic irritation, drugs etc., It is commonly seen in children and adolescents. Giant pyogenic granuloma is its atypical variant. We are presenting two cases of giant pyogenic granuloma, one, in a 28-year-old adult, presenting as a giant fluffy swelling of scalp and the other in a 11-year-old child, presenting as a giant ulcerated globular swelling of the scalp.

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

    Science.gov (United States)

    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/.

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

    Science.gov (United States)

    Bae, Gi-Yeul; Luck, Steven J

    2017-11-22

    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 StatementWorking 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

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

    Directory of Open Access Journals (Sweden)

    Mahmoud Hassan

    Full Text Available 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/.

  13. Reward feedback stimuli elicit high-beta EEG oscillations in human dorsolateral prefrontal cortex.

    Science.gov (United States)

    HajiHosseini, Azadeh; Hosseini, Azadeh Haji; Holroyd, Clay B

    2015-08-17

    Reward-related feedback stimuli have been observed to elicit a burst of power in the beta frequency range over frontal areas of the human scalp. Recent discussions have suggested possible neural sources for this activity but there is a paucity of empirical evidence on the question. Here we recorded EEG from participants while they navigated a virtual T-maze to find monetary rewards. Consistent with previous studies, we found that the reward feedback stimuli elicited an increase in beta power (20-30 Hz) over a right-frontal area of the scalp. Source analysis indicated that this signal was produced in the right dorsolateral prefrontal cortex (DLPFC). These findings align with previous observations of reward-related beta oscillations in the DLPFC in non-human primates. We speculate that increased power in the beta frequency range following reward receipt reflects the activation of task-related neural assemblies that encode the stimulus-response mapping in working memory.

  14. Magnetoencephalography demonstrates multiple asynchronous generators during human sleep spindles.

    Science.gov (United States)

    Dehghani, Nima; Cash, Sydney S; Rossetti, Andrea O; Chen, Chih Chuan; Halgren, Eric

    2010-07-01

    Sleep spindles are approximately 1 s bursts of 10-16 Hz activity that occur during stage 2 sleep. Spindles are highly synchronous across the cortex and thalamus in animals, and across the scalp in humans, implying correspondingly widespread and synchronized cortical generators. However, prior studies have noted occasional dissociations of the magnetoencephalogram (MEG) from the EEG during spindles, although detailed studies of this phenomenon have been lacking. We systematically compared high-density MEG and EEG recordings during naturally occurring spindles in healthy humans. As expected, EEG was highly coherent across the scalp, with consistent topography across spindles. In contrast, the simultaneously recorded MEG was not synchronous, but varied strongly in amplitude and phase across locations and spindles. Overall, average coherence between pairs of EEG sensors was approximately 0.7, whereas MEG coherence was approximately 0.3 during spindles. Whereas 2 principle components explained approximately 50% of EEG spindle variance, >15 were required for MEG. Each PCA component for MEG typically involved several widely distributed locations, which were relatively coherent with each other. These results show that, in contrast to current models based on animal experiments, multiple asynchronous neural generators are active during normal human sleep spindles and are visible to MEG. It is possible that these multiple sources may overlap sufficiently in different EEG sensors to appear synchronous. Alternatively, EEG recordings may reflect diffusely distributed synchronous generators that are less visible to MEG. An intriguing possibility is that MEG preferentially records from the focal core thalamocortical system during spindles, and EEG from the distributed matrix system.

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

    Science.gov (United States)

    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

  16. The ballistic performance of the bombard Mons Meg

    Directory of Open Access Journals (Sweden)

    Ian Lewtas

    2016-04-01

    Full Text Available The bombard Mons Meg, located in Edinburgh Castle, with a diameter of 19 inches (48 cm, was one of the largest calibre cannons ever built. Constructed in 1449 and presented to King James II of Scotland in 1454, Mons Meg was used in both military and ceremonial roles in Scotland until its barrel burst in 1680. This paper examines the history, internal, external and terminal ballistics of the cannon and its shot. The likely muzzle velocity was estimated by varying the propellant type and the cannon profile was investigated to identify weak spots in the design that may have led to its failure. Using the muzzle velocity calculated from the internal ballistics, simulations were performed with granite and sandstone shot for varying launch angle and ground temperature. The likely trajectory and range of the cannonballs are described. The internal and external ballistics informed the initial conditions of the terminal ballistic impact scenarios. The performance of the cannonball against both period and modern targets, in the form of a pseudo-castle wall and a monolithic concrete target, respectively, were simulated and are presented and discussed.

  17. Recognising upright and inverted faces: MEG source localisation.

    Science.gov (United States)

    Taylor, M J; Bayless, S J; Mills, T; Pang, E W

    2011-03-24

    Face recognition is a complex cognitive task that involves a distributed network of neural sources. While some components of this network have been identified, the temporal sequence of these components is not well understood. Magnetoencephalography (MEG), analyzed with a spatial filtering source localisation algorithm, was used to determine frontal contributions to face recognition. We tested 22 adults (mean age 26.3 years; 10 females). Upright and inverted faces were presented in counter-balanced blocks and subjects identified repetitions in a 1-back protocol. MEG data were recorded continuously from a 151 channel CTF machine and source localised to each participant's MRI. The classic face components, M100 and M170, were seen for upright and inverted faces with M100 localizing to bilateral occipital areas and M170 to bilateral fusiform areas. A third component, M240, showed high global field power to correctly recognised repeated faces and localised to right middle frontal and insula sources at 240 ms for upright faces and bilateral mid-frontal sources for inverted faces. The effect of repetition was examined and a source identified at 250 ms in the cingulate, for inverted faces. These results provide timing information on frontal lobe activation, seen reliably in fMRI memory studies; the immediate recognition of repeated faces activates the right frontal sources at 240-250 ms, with bilateral activation to repeated inverted faces, perhaps due to increased task difficulty. Copyright © 2011 Elsevier B.V. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    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.

  19. EEG based topography analysis in string recognition task

    Science.gov (United States)

    Ma, Xiaofei; Huang, Xiaolin; Shen, Yuxiaotong; Qin, Zike; Ge, Yun; Chen, Ying; Ning, Xinbao

    2017-03-01

    Vision perception and recognition is a complex process, during which different parts of brain are involved depending on the specific modality of the vision target, e.g. face, character, or word. In this study, brain activities in string recognition task compared with idle control state are analyzed through topographies based on multiple measurements, i.e. sample entropy, symbolic sample entropy and normalized rhythm power, extracted from simultaneously collected scalp EEG. Our analyses show that, for most subjects, both symbolic sample entropy and normalized gamma power in string recognition task are significantly higher than those in idle state, especially at locations of P4, O2, T6 and C4. It implies that these regions are highly involved in string recognition task. Since symbolic sample entropy measures complexity, from the perspective of new information generation, and normalized rhythm power reveals the power distributions in frequency domain, complementary information about the underlying dynamics can be provided through the two types of indices.

  20. Fused multivariate empirical mode decomposition (MEMD) and inverse solution method for EEG source localization.

    Science.gov (United States)

    Khosropanah, Pegah; Ramli, Abdul Rahman; Lim, Kheng Seang; Marhaban, Mohammad Hamiruce; Ahmedov, Anvarjon

    2017-07-22

    EEG source localization is determining possible cortical sources of brain activities with scalp EEG. Generally, every step of the data processing sequence affects the accuracy of EEG source localization. In this paper, we introduce a fused multivariate empirical mode decomposing (MEMD) and inverse solution algorithm with an embedded unsupervised eye blink remover in order to localize the epileptogenic zone accurately. For this purpose, we constructed realistic forward models using MRI and boundary element method (BEM) for each patient to obtain results that are more realistic. We also developed an unsupervised algorithm utilizing a wavelet method to remove eye blink artifacts. Additionally, we applied MEMD, which is one of the recent and suitable feature extraction methods for non-linear, non-stationary, and multivariate signals such as EEG, to extract the signal of interest. We examined the localization results using the two most reliable linear distributed inverse methods in the literature: weighted minimum norm estimation (wMN) and standardized low resolution tomography (sLORETA). Results affirm the success of the proposed algorithm with the highest agreement compared to MRI reference by a specialist. Fusion of MEMD and sLORETA results in approximately zero localization error in terms of spatial difference with the validated MRI reference. High accuracy results of proposed algorithm using non-invasive and low-resolution EEG provide the potential of using this work for pre-surgical evaluation towards epileptogenic zone localization in clinics.

  1. Registration of EEG electrode positions to PET and fMRI images

    Science.gov (United States)

    Špiclin, Žiga; Likar, Boštjan; Pernuš, Franjo

    2009-02-01

    Integration and correlation of brain's electrical (EEG) and physiological activity (PET, fMRI) is crucial for the early evaluation of patients with neurophysiological disorders, such as epilepsy. Based on the scalp-recorded EEG signals, the source image of brain's electrical activity can be reconstructed and spatially correlated with tomographic functional images, thereby aiding to the characterization and localization of epileptic foci. However, mis-localization of the electrode positions, with respect to the underlying anatomy, adversely affects the localization precision performed by the interpretation of the source image. In this paper, a novel method for registration of EEG electrode positions to tomographic functional images of the brain is proposed. Accuracy and robustness of the registration were evaluated on three databases of real and simulated PET and real fMRI images. The registration method showed good convergence properties for both PET [>10 mm] and especially fMRI images [>30 mm]. Based on Monte Carlo simulations, the obtained mean registration error of electrode positions in tomographic functional images was in the range of 1-2 corresponding voxel size. In this way, the constant bias in the reconstructed source image, that is due to the mis-registration of EEG electrode positions, can be suppressed with respect to the random errors induced by EEG signal noise. Finally, we aim to improve, or at all enable, the integration and application of the many functional modalities involved in the analysis and evaluation of clinical neurophysiological disorders.

  2. Removal of ocular artifacts from EEG using adaptive thresholding of wavelet coefficients

    Science.gov (United States)

    Krishnaveni, V.; Jayaraman, S.; Anitha, L.; Ramadoss, K.

    2006-12-01

    Electroencephalogram (EEG) gives researchers a non-invasive way to record cerebral activity. It is a valuable tool that helps clinicians to diagnose various neurological disorders and brain diseases. Blinking or moving the eyes produces large electrical potential around the eyes known as electrooculogram. It is a non-cortical activity which spreads across the scalp and contaminates the EEG recordings. These contaminating potentials are called ocular artifacts (OAs). Rejecting contaminated trials causes substantial data loss, and restricting eye movements/blinks limits the possible experimental designs and may affect the cognitive processes under investigation. In this paper, a nonlinear time-scale adaptive denoising system based on a wavelet shrinkage scheme has been used for removing OAs from EEG. The time-scale adaptive algorithm is based on Stein's unbiased risk estimate (SURE) and a soft-like thresholding function which searches for optimal thresholds using a gradient based adaptive algorithm is used. Denoising EEG with the proposed algorithm yields better results in terms of ocular artifact reduction and retention of background EEG activity compared to non-adaptive thresholding methods and the JADE algorithm.

  3. 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. ...

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

    Directory of Open Access Journals (Sweden)

    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.

  5. 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.

  6. Long-term management of scalp psoriasis: perspectives from the International Psoriasis Council

    NARCIS (Netherlands)

    Kragballe, K.; Menter, A.; Lebwohl, M.; Tebbey, P.W.; Kerkhof, P.C.M. van de

    2013-01-01

    The scalp is a well-known predilection site for psoriasis. Epidemiological data on the various manifestations of scalp psoriasis as well as on its therapeutic management are sparse. The understanding of the natural course of scalp psoriasis is relevant for its therapeutic management. In over 25% of

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

    NARCIS (Netherlands)

    Jemec, G.B.; Kerkhof, P.C. van de; Enevold, A.; Ganslandt, C.

    2011-01-01

    BACKGROUND: A two-compound scalp formulation containing calcipotriol (50 mug/g) and betamethasone (0.5mg/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 of

  8. 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

  9. Reconstruction of scalp defects with the radial forearm free flap

    Science.gov (United States)

    2012-01-01

    Background Advanced and recurrent cutaneous squamous cell carcinoma of the scalp and forehead require aggressive surgical excision often resulting in complex defects requiring reconstruction. This study evaluates various microvascular free flap reconstructions in this patient population, including the rarely utilized radial forearm free flap. Patients and methods A retrospective review of patients undergoing free flap surgeries (n = 47) of the scalp between 1997 and 2011 were included. Patients were divided primarily into two cohorts: a new primary lesion (n = 21) or recurrence (n = 26). Factors examined include patient demographics, indication for surgery, defect, type of flap used, complications (major and minor), and outcomes. Results The patients were primarily male (n = 34), with a mean age of 67 years (25–91). A total of 58 microvascular free flap reconstructions were performed (radial forearm free flap: n = 28, latissimus dorsi: n = 20, rectus abdominis: n = 9, scapula: n = 1). Following reconstruction with a radial forearm free flap, duration of hospitalization was shorter (P = 0.04) and complications rates were similar (P = 0.46). Donor site selection correlated with defect area (P scalp are aggressive and challenging to treat. The radial forearm free flap is an underutilized free flap in the reconstruction of complex scalp defects. PMID:22583845

  10. Blindness and scalp haematoma in a child following a snakebite ...

    African Journals Online (AJOL)

    Conclusion: Snakebite is associated with lifelong morbidity. Ocular manifestations must be treated as emergency. This case highlights the effect of ignorance and poverty in a setting of a common medical emergency leading to blindness and reduced quality of life. Keywords: snakebite, blindness, scalp haematoma, child ...

  11. Reconstruction of face and scalp after dog bites in children

    Directory of Open Access Journals (Sweden)

    JEFFERSON LESSA SOARES MACEDO

    Full Text Available ABSTRACT Objective: to evaluate the immediate reconstruction of face and scalp after canine bites in children. Methods: we conducted a prospective series of cases treated at the Emergency Unit of the Asa Norte Regional Hospital, Brasília - DF, from January 1999 to December 2014. At the time of patient admission to the emergency, the primary wound closure of the face and scalp bite was performed, regardless of the time or day of the event. The primary treatment of the bites was by means of direct suture, flaps rotation or grafting, depending on the type of wound and surgeon's decision. Results: the study comprised 146 children, with the zygomatic region and scalp being the main sites of head bites. All patients received surgical treatment within the first 24 hours after admission. There were no infectious complications in the cases studied. Conclusion: the findings suggest that the immediate closure of canine bites on the face and scalp in children is safe, even when carried out several hours after injury.

  12. Reconstruction of face and scalp after dog bites in children.

    Science.gov (United States)

    Macedo, Jefferson Lessa Soares; Rosa, Simone Corrêa; Queiroz, Murilo Neves DE; Gomes, Tabatha Gonçalves Andrade Castelo Branco

    2016-12-01

    to evaluate the immediate reconstruction of face and scalp after canine bites in children. we conducted a prospective series of cases treated at the Emergency Unit of the Asa Norte Regional Hospital, Brasília - DF, from January 1999 to December 2014. At the time of patient admission to the emergency, the primary wound closure of the face and scalp bite was performed, regardless of the time or day of the event. The primary treatment of the bites was by means of direct suture, flaps rotation or grafting, depending on the type of wound and surgeon's decision. the study comprised 146 children, with the zygomatic region and scalp being the main sites of head bites. All patients received surgical treatment within the first 24 hours after admission. There were no infectious complications in the cases studied. the findings suggest that the immediate closure of canine bites on the face and scalp in children is safe, even when carried out several hours after injury.

  13. Fetal scalp blood sampling in labor - a review

    DEFF Research Database (Denmark)

    Jørgensen, Jan Stener; Weber, Tom

    2014-01-01

    During the 1970s and 1980s, electronic fetal monitoring and fetal scalp blood sampling (FBS) were introduced without robust evidence. With a methodical review of the published literature, and using one randomized controlled trial, seven controlled studies, nine randomized studies of various surve...

  14. Atopic dermatitis of the face, scalp, and neck

    DEFF Research Database (Denmark)

    Jensen-Jarolim, E; Poulsen, L K; With, H

    1992-01-01

    We have previously reported that a lipophilic yeast, Pityrosporum ovale (P. ovale) produced a high frequency of positive skin prick tests and in vitro histamine-release (HR) tests in patients suffering from atopic dermatitis (AD) of the face, scalp, and neck. In the present study, our aim...

  15. Opioid consumption after levobupivacaine scalp nerve block for craniosynostosis surgery.

    Science.gov (United States)

    Pardey Bracho, Gilda F; Pereira de Souza Neto, Edmundo; Grousson, Sébastien; Mottolese, Carmine; Dailler, Frédéric

    2014-06-01

    Craniosynostosis surgery is considered a very painful procedure due to extended scalp and periosteal detachment, and is associated with prolonged postoperative consumption of opioids and their side effects. In this observational descriptive case series study, we investigated perioperative opioid consumption in children undergoing craniosynostosis repair under general anesthesia when scalp nerve block with levobupivacaine was involved. After standard anesthesia induction, scalp nerve block with levobupivacaine 2 mg/kg plus epinephrine 1:800,000 was performed. Hemodynamic parameters and opioid consumption were noted. Patients were monitored in the recovery room. Requirements of additional analgesia, indicated by the Children's Hospital of Eastern Ontario Pain Scale (CHEOPS) pain score of >9, and incidence of side effects (sedation, nausea, and vomiting) were recorded during the first 24 hours. A total of 32 patients were recruited in this study; 88% of them needed morphine rescue in the recovery room because they had high CHEOPS scores. Trigonocephaly was the most frequent type of craniosynostosis (37.5%), requiring 50% more opioids in the postoperative period than other forms of craniosynostosis. Scalp nerve block can be proposed as a complement to the routine craniosynostosis anesthetic protocol, because it is easy to perform, seems to reduce the need for supplementary opioids during the perioperative period, and can reduce the risk of developing acute opioid tolerance and chronic pain. In the event of trigonocephaly or craniofacial reconstruction, a complementary infraorbital nerve block can be added. Copyright © 2014. Published by Elsevier B.V.

  16. Excess of counterclockwise scalp hair-whorl rotation in homosexual ...

    Indian Academy of Sciences (India)

    Unknown

    Journal of Genetics, Vol. 83, No. 3, December 2004. 251. Excess of counterclockwise scalp hair- ... on genes and/or prenatal hormone environments influenc- ing the neuronal circuitry on which sexual preference is ... This assessment was reinforced by the dearth of females and children on the beach. More importantly,.

  17. Quantifying variation in human scalp hair fiber shape and pigmentation.

    Science.gov (United States)

    Lasisi, Tina; Ito, Shosuke; Wakamatsu, Kazumasa; Shaw, Colin N

    2016-06-01

    This study aims to evaluate the use of quantitative methods of measuring variation in scalp hair fiber shape and pigmentation and carry out exploratory data analysis on a limited sample of individuals from diverse populations in order to inform future avenues of research for the evolution of modern human hair variation. Cross-sectional area and shape and average curvature of scalp hair fibers were quantified using ImageJ. Pigmentation was analyzed using chemical methods estimating total melanin content through spectrophotometric methods, and eumelanin and pheomelanin content through HLPC analysis of melanin-specific degradation products. The initial results reinforced findings from earlier, traditional studies. African and African Diaspora scalp hair was significantly curled, (East) Asian hair was significantly thick, and European hair was significantly lighter in color. However, pigmentation analyses revealed a high level of variability in the melanin content of non-European populations and analysis of curvature found a large range of variation in the average curvature of East African individuals. Overall, these results suggest the usefulness of chemical methods for the elucidation of nonperceptible differences in scalp hair color and highlight the need for improvements in our assessment and understanding of hair fiber curvature. Am J Phys Anthropol 160:341-352, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  18. Blindness and scalp haematoma in a child following a snakebite

    African Journals Online (AJOL)

    Abstract. Background: Snake envenomation is a major public health problem of the Savannah regions of West Africa. Ocular man- ... Methods: A report of scalp haematoma and blindness in a 10 year old child presenting 2 weeks after a snake bite (pre- sumably .... Pre-event: Health education to correct myths that snakebites ...

  19. Individual somatotopy of primary sensorimotor cortex revealed by intermodal matching of MEG, PET, and MRI.

    Science.gov (United States)

    Walter, H; Kristeva, R; Knorr, U; Schlaug, G; Huang, Y; Steinmetz, H; Nebeling, B; Herzog, H; Seitz, R J

    1992-01-01

    A method for comparing estimated magnetoencephalographic (MEG) dipole localizations with regional cerebral blood flow (rCBF) activation areas is presented. This approach utilizes individual intermodal matching of MEG data, of rCBF measurements with [15O]-butanol and positron emission tomography (PET), and of anatomical information obtained from magnetic resonance (MR) images. The MEG data and the rCBF measurements were recorded in a healthy subject during right-sided simple voluntary movements of the foot, thumb, index finger, and mouth. High resolution 3D-FLASH MR images of the brain consisting of 128 contiguous sagittal slices of 1.17-mm thickness were used. MEG/MR integration was performed by superimposing the 3D head coordinate system constructed during the MEG measurement onto the MR image data using identical anatomical landmarks as references. PET/MR integration was achieved by a phantom-validated iterative front-to-back-projection algorithm resulting in one integrated MEG/PET/MR image. The estimated dipole locations followed the somatotopic organisation of the task-specific rCBF increases as evident from PET, although they did not match point-to-point. Our results demonstrate that intermodal matching of MEG, PET and MR data provides a tool for relating estimated neuromagnetic field locations to task-specific rCBF changes in individual subjects. Our method offers the perspective of refined dipole modelling.

  20. Expression of DLK1 and MEG3 genes in porcine tissues during postnatal development

    Directory of Open Access Journals (Sweden)

    Maria Oczkowicz

    2010-01-01

    Full Text Available The Drosophila-like homolog 1 (DLK1, a transmembrane signal protein similar to other members of the Notch/Delta/Serrate family, regulates the differentiation process in many types of mammalian cells. Callipyge sheep and DLK1 knockout mice are excellent examples of a fundamental role of the gene encoding DLK1 in muscle growth and fat deposition. DLK1 is located within co-regulated imprinted clusters (the DLK1/DIO3 domain, along with other imprinted genes. Some of these, e.g. the RNA coding MEG3 gene, presumedly interfere with DLK1 transcription. The aim of our study was to analyze DLK1 and MEG3 gene expression in porcine tissues (muscle, liver, kidney, heart, brain stem during postnatal development. The highest expression of both DLK1 and MEG3 variant 1 (MEG3 var.1 was observed in the brain-stem and muscles, whereas that of MEG3 variant 2 (MEG3 var.2 was the most abundant in muscles and the heart. During development (between 60 and 210 days of age expression of analyzed genes was down-regulated in all the tissues. An exception was the brain-stem, where there was no significant change in MEG3 (both variants mRNA level, and relatively little decline (2-fold in that of DLK1 transcription. This may indicate a distinct function of the DLK1 gene in the brain-stem, when compared with other tissues.

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

    Science.gov (United States)

    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.

  2. Primary cutaneous melanoma of the scalp: Patterns of recurrence.

    Science.gov (United States)

    Sparks, David S; Read, Tavis; Lonne, Michael; Barbour, Andrew P; Wagels, Michael; Bayley, Gerard J; Smithers, B Mark

    2017-03-01

    Patients with primary melanoma of the scalp have been reported to have worse disease-related outcomes compared with other anatomical regions. There are few studies in the literature specifically addressing recurrence patterns and treatment outcomes for primary scalp melanoma as a discrete anatomical sub-region. We sought to identify key features adversely influencing disease control and survival and to clarify the role of resection plane, margin, and method of reconstruction in the management of this disease process. A retrospective clinical study of medical records was performed evaluating all patients with primary melanoma of the scalp treated at two hospitals in southeast Queensland between 2004 and 2014. A total of 107 patients were eligible for analysis. There were 46 recurrences in 38 patients in the cohort accounting for a recurrence rate of 35.5%. The local recurrence rate was 15.9% with 12 in-transit metastases after diagnosis. Regional and distant recurrence rates were 12.1% and 15%, respectively. At a median follow up of 30.5 months, disease-free survival was 47% and overall survival was also 47%. On multi-variate analysis, the deeper resection plane (sub-galeal) had a lower disease-free survival rate compared with the supra-galeal resection plane (P = 0.032). Our results support the hypothesis that primary scalp melanoma represents a unique aggressive subcategory with high rates of in-transit disease and poor disease-related and survival outcomes. There is a need for robust prospective comparative studies to address the significance of resection plane in the management of patients with scalp melanoma. © 2016 Wiley Periodicals, Inc.

  3. EEG analyses with SOBI.

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-02-01

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

  4. Aplasia cutis congenita--plastic reconstruction of three scalp and skull defects with two opposed scalp rotation flaps and split thickness skin grafting.

    Science.gov (United States)

    Schnabl, S M; Horch, R E; Ganslandt, O; Schroth, M; Dragu, A; Bach, A D; Kneser, U

    2009-06-01

    Aplasia cutis congenita (ACC) is a rare congenital defect of skin and subcutaneous tissue, more rarely of periosteum, skull and dura. The lesions can involve any location, but most common are scalp defects. We report on the successful treatment of three large defects of the scalp with skull involvement in a newborn girl by early debridement and defect closure with two opposed scalp rotation flaps and an occipital split-thickness skin graft.

  5. The priming of basic combinatory responses in MEG.

    Science.gov (United States)

    Blanco-Elorrieta, Esti; Ferreira, Victor S; Del Prato, Paul; Pylkkänen, Liina

    2017-09-21

    Priming has been a powerful tool for the study of human memory and especially the memory representations relevant for language. However, although it is well established that lexical access can be primed, we do not know exactly what types of computations can be primed above the word level. This work took a neurobiological approach and assessed the ways in which the complex representation of a minimal combinatory phrase, such as red boat, can be primed, as evidenced by the spatiotemporal profiles of magnetoencephalography (MEG) signals. Specifically, we built upon recent progress on the neural signatures of phrasal composition and tested whether the brain activities implicated for the basic combination of two words could be primed. In two experiments, MEG was recorded during a picture naming task where the prime trials were designed to replicate previously reported combinatory effects and the target trials to test whether those combinatory effects could be primed. The manipulation of the primes was successful in eliciting larger activity for adjective-noun combinations than single nouns in left anterior temporal and ventromedial prefrontal cortices, replicating prior MEG studies on parallel contrasts. Priming of similarly timed activity was observed during target trials in anterior temporal cortex, but only when the prime and target shared an adjective. No priming in temporal cortex was observed for single word repetition and two control tasks showed that the priming effect was not elicited if the prime pictures were simply viewed but not named. In sum, this work provides evidence that very basic combinatory operations can be primed, with the necessity for some lexical overlap between prime and target suggesting combinatory conceptual, as opposed to syntactic processing. Both our combinatory and priming effects were early, onsetting between 100 and 150ms after picture onset and thus are likely to reflect the very earliest planning stages of a combinatory message

  6. 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

  7. Automatic Identification of Artifact-Related Independent Components for Artifact Removal in EEG Recordings.

    Science.gov (United States)

    Zou, Yuan; Nathan, Viswam; Jafari, Roozbeh

    2016-01-01

    Electroencephalography (EEG) is the recording of electrical activity produced by the firing of neurons within the brain. These activities can be decoded by signal processing techniques. However, EEG recordings are always contaminated with artifacts which hinder the decoding process. Therefore, identifying and removing artifacts is an important step. Researchers often clean EEG recordings with assistance from independent component analysis (ICA), since it can decompose EEG recordings into a number of artifact-related and event-related potential (ERP)-related independent components. However, existing ICA-based artifact identification strategies mostly restrict themselves to a subset of artifacts, e.g., identifying eye movement artifacts only, and have not been shown to reliably identify artifacts caused by nonbiological origins like high-impedance electrodes. In this paper, we propose an automatic algorithm for the identification of general artifacts. The proposed algorithm consists of two parts: 1) an event-related feature-based clustering algorithm used to identify artifacts which have physiological origins; and 2) the electrode-scalp impedance information employed for identifying nonbiological artifacts. The results on EEG data collected from ten subjects show that our algorithm can effectively detect, separate, and remove both physiological and nonbiological artifacts. Qualitative evaluation of the reconstructed EEG signals demonstrates that our proposed method can effectively enhance the signal quality, especially the quality of ERPs, even for those that barely display ERPs in the raw EEG. The performance results also show that our proposed method can effectively identify artifacts and subsequently enhance the classification accuracies compared to four commonly used automatic artifact removal methods.

  8. The EEG segmentation

    OpenAIRE

    Nečadová, Anežka

    2013-01-01

    Předmětem této bakalářské práce je seznámení se signálem EEG. Jsou zde rozebrány jeho vlastnosti, použití a způsoby zpracování. Hlavní část se zabývá segmentací EEG signálu. Dvě metody segmentace jsou realizovány v programu Matlab, a to adaptivní segmentace na základě míry diference střední amplitudy a míry diference střední frekvence a adaptivní segmentace na základě míry diference odhadnuté z rychlé Fourierovy transformace. Funkčnost algoritmu je ověřena na reálných EEG signálech. Subjec...

  9. Sleep EEG analysis

    OpenAIRE

    Vávrová, Eva

    2014-01-01

    Tato bakalářská práce se zabývá analýzou spánkových EEG, která je provedena pomocí výpočtu vybraných parametrů z časové a frekvenční oblasti. Parametry se počítají z jednotlivých úseků EEG signálů, které odpovídají jednotlivým spánkovým fázím. Na základě analýzy se rozhodne, které parametry EEG jsou vhodné pro automatickou detekci fází a která metoda je vhodnější pro hodnocení dat v hypnogramu. K analýze byl použit program MATLAB, ve kterém byla daná data porovnána. This thesis deals with ...

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

    Directory of Open Access Journals (Sweden)

    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

  11. EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review.

    Science.gov (United States)

    Michel, Christoph M; Koenig, Thomas

    2017-11-28

    The present review discusses a well-established method for characterizing resting-state activity of the human brain using multichannel electroencephalography (EEG). This method involves the examination of electrical microstates in the brain, which are defined as successive short time periods during which the configuration of the scalp potential field remains semi-stable, suggesting quasi-simultaneity of activity among the nodes of large-scale networks. A few prototypic microstates, which occur in a repetitive sequence across time, can be reliably identified across participants. Researchers have proposed that these microstates represent the basic building blocks of the chain of spontaneous conscious mental processes, and that their occurrence and temporal dynamics determine the quality of mentation. Several studies have further demonstrated that disturbances of mental processes associated with neurological and psychiatric conditions manifest as changes in the temporal dynamics of specific microstates. Combined EEG-fMRI studies and EEG source imaging studies have indicated that EEG microstates are closely associated with resting-state networks as identified using fMRI. The scale-free properties of the time series of EEG microstates explain why similar networks can be observed at such different time scales. The present review will provide an overview of these EEG microstates, available methods for analysis, the functional interpretations of findings regarding these microstates, and their behavioral and clinical correlates. Copyright © 2017. Published by Elsevier Inc.

  12. Simple flaps for reconstruction of pediatric scalp defects after electrical burn

    Directory of Open Access Journals (Sweden)

    Makboul Mohamed

    2013-08-01

    Full Text Available 【Abstract】 Objective: To analyze the management of high-voltage electrical burn injury of the scalp in our hospital. Methods: This study involved 10 patients who suf-fered from high-voltage electrical burn injury of the scalp. Scalp reconstruction was done by different modalities ac-cording to the size and location of the defect. Results: Complete flap viability was achieved in all the cases. We had one case of gapped wound which was managed only by dressing. Widening of the scar was found in 2 cases. Conclusion: Rotation, advancement and transposi-tion scalp flaps are used for reconstructing scalp defects caused by electrical burn. The choice of ideal flaps for re-construction depends upon the size and site of scalp defect. Key words: Burns, electric; Scalp; Reconstructive surgical procedures; Surgical flaps; Skull

  13. 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.

  14. LIMO EEG: A Toolbox for Hierarchical LInear MOdeling of ElectroEncephaloGraphic Data

    Directory of Open Access Journals (Sweden)

    Cyril R. Pernet

    2011-01-01

    Full Text Available 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.

  15. Using Brain Connectivity Measure of EEG Synchrostates for Discriminating Typical and Autism Spectrum Disorder

    CERN Document Server

    Jamal, Wasifa; Maharatna, Koushik; Kuyucu, Doga; Sicca, Federico; Billeci, Lucia; Apicella, Fabio; Muratori, Filippo

    2016-01-01

    In this paper we utilized the concept of stable phase synchronization topography - synchrostates - over the scalp derived from EEG recording for formulating brain connectivity network in Autism Spectrum Disorder (ASD) and typically-growing children. A synchronization index is adapted for forming the edges of the connectivity graph capturing the stability of each of the synchrostates. Such network is formed for 11 ASD and 12 control group children. Comparative analyses of these networks using graph theoretic measures show that children with autism have a different modularity of such networks from typical children. This result could pave the way to a new modality for possible identification of ASD from non-invasively recorded EEG data.

  16. 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.

  17. Functional brain connectivity from EEG in epilepsy: seizure prediction and epileptogenic focus localization.

    Science.gov (United States)

    van Mierlo, Pieter; Papadopoulou, Margarita; Carrette, Evelien; Boon, Paul; Vandenberghe, Stefaan; Vonck, Kristl; Marinazzo, Daniele

    2014-10-01

    Today, neuroimaging techniques are frequently used to investigate the integration of functionally specialized brain regions in a network. Functional connectivity, which quantifies the statistical dependencies among the dynamics of simultaneously recorded signals, allows to infer the dynamical interactions of segregated brain regions. In this review we discuss how the functional connectivity patterns obtained from intracranial and scalp electroencephalographic (EEG) recordings reveal information about the dynamics of the epileptic brain and can be used to predict upcoming seizures and to localize the seizure onset zone. The added value of extracting information that is not visibly identifiable in the EEG data using functional connectivity analysis is stressed. Despite the fact that many studies have showed promising results, we must conclude that functional connectivity analysis has not made its way into clinical practice yet. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Morphology-based wavelet features and multiple mother wavelet strategy for spike classification in EEG signals.

    Science.gov (United States)

    Zhou, Jing; Schalkoff, Robert J; Dean, Brian C; Halford, Jonathan J

    2012-01-01

    New wavelet-derived features and strategies that can improve autonomous EEG classifier performance are presented. Various feature sets based on the morphological structure of wavelet subband coefficients are derived and evaluated. The performance of these new feature sets is superior to Guler's classic features in both sensitivity and specificity. In addition, the use of (scalp electrode) spatial information is also shown to improve EEG classification. Finally, a new strategy based upon concurrent use of several mother wavelets is shown to result in increased sensitivity and specificity. Various attempts at reducing feature vector dimension are shown. A non-parametric method, k-NNR, is implemented for classification and 10-fold cross-validation is used for assessment.

  19. LncRNA MEG3 Inhibits Cell Proliferation and Metastasis in Chronic Myeloid Leukemia via Targeting MiR-184.

    Science.gov (United States)

    Li, Jingdong; Zi, Youmei; Wang, Wanling; Li, Yan

    2017-06-22

    Maternally expressed gene 3 (MEG3), a long non-coding RNA, has been reported to be associated with the pathogenesis ofmultiple malignancies. However, little is known regarding the role of MEG3 in leukemia. In this study, we found that the expression of MEG3 was decreased in leukemia patients and cell lines, and has potential to be considered as a biomarker for leukemia. In addition, overexpression of MEG3 inhibited cell proliferation and invasion in vitro and in vivo . Moreover, a potential bonding site between miR-184 and MEG3 was predicted, and low expression of miR-184 was found in leukemia patients and cell lines. In vitro loss- and gain-of-function showed that overexpression of MEG3 significantly decreased the expression of miR-184 and MEG3 knockdown markedly increased it. Furthermore, our results showed that MEG3 interacted with miR-184 and subsequently mitigated the proliferation and invasion of leukemia cells by down-regulating related proteins. In conclusion, our study has identified a novel pathway through which MEG3 acts as a tumor suppressor in leukemia at the level of miRNAs, and provided a molecular basis for potential applications of MEG3 in the prognosis and treatment of leukemia.

  20. Evaluation of a minimum-norm based beamforming technique, sLORETA, for reducing tonic muscle contamination of EEG at sensor level.

    Science.gov (United States)

    Janani, Azin S; Grummett, Tyler S; Lewis, Trent W; Fitzgibbon, Sean P; Whitham, Emma M; DelosAngeles, Dylan; Bakhshayesh, Hanieh; Willoughby, John O; Pope, Kenneth J

    2017-08-15

    Cranial and cervical muscle activity (electromyogram, EMG) contaminates the surface electroencephalogram (EEG) from frequencies below 20 through to frequencies above 100Hz. It is not possible to have a reliable measure of cognitive tasks expressed in EEG at gamma-band frequencies until the muscle contamination is removed. In the present work, we introduce a new approach of using a minimum-norm based beamforming technique (sLORETA) to reduce tonic muscle contamination at sensor level. Using a generic volume conduction model of the head, which includes three layers (brain, skull, and scalp), and sLORETA, we estimated time-series of sources distributed within the brain and scalp. The sources within the scalp were considered to be muscle and discarded in forward modelling. (1) The method reduced EMG contamination, more strongly at peripheral channels; (2) task-induced cortical activity was retained or revealed after removing putative muscle activity. This approach can decrease tonic muscle contamination in scalp measurements without relying on time-consuming processing of expensive MRI data. In addition, it is competitive to ICA in muscle reduction and can be reliably applied on any length of recorded data that captures the dynamics of the signals of interest. This study suggests that sLORETA can be used as a method to quantitate cranial muscle activity and reduce its contamination at sensor level. Copyright © 2017 Elsevier B.V. All rights reserved.