Attention and Working Memory-Related EEG Markers of Subtle Cognitive Deterioration in Healthy Elderly Individuals.

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Deiber, Marie-Pierre; Meziane, Hadj Boumediene; Hasler, Roland; Rodriguez, Cristelle; Toma, Simona; Ackermann, Marine; Herrmann, François; Giannakopoulos, Panteleimon

2015-01-01

Future treatments of Alzheimer's disease need the identification of cases at high risk at the preclinical stage of the disease before the development of irreversible structural damage. We investigated here whether subtle cognitive deterioration in a population of healthy elderly individuals could be predicted by EEG signals at baseline under cognitive activation. Continuous EEG was recorded in 97 elderly control subjects and 45 age-matched mild cognitive impairment (MCI) cases during a simple attentional and a 2-back working memory task. Upon 18-month neuropsychological follow-up, the final sample included 55 stable (sCON) and 42 deteriorated (dCON) controls. We examined the P1, N1, P3, and PNwm event-related components as well as the oscillatory activities in the theta (4-7 Hz), alpha (8-13 Hz), and beta (14-25 Hz) frequency ranges (ERD/ERS: event-related desynchronization/synchronization, and ITC: inter-trial coherence). Behavioral performance, P1, and N1 components were comparable in all groups. The P3, PNwm, and all oscillatory activity indices were altered in MCI cases compared to controls. Only three EEG indices distinguished the two control groups: alpha and beta ERD (dCON >  sCON) and beta ITC (dCON memory processes but mostly affects attention, resulting in an enhanced recruitment of attentional resources. In addition, cognitive decline alters neural firing synchronization at high frequencies (14-25 Hz) at early stages, and possibly affects lower frequencies (4-13 Hz) only at more severe stages.

Intrahemispheric theta rhythm desynchronization impairs working memory.

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Alekseichuk, Ivan; Pabel, Stefanie Corinna; Antal, Andrea; Paulus, Walter

2017-01-01

There is a growing interest in large-scale connectivity as one of the crucial factors in working memory. Correlative evidence has revealed the anatomical and electrophysiological players in the working memory network, but understanding of the effective role of their connectivity remains elusive. In this double-blind, placebo-controlled study we aimed to identify the causal role of theta phase connectivity in visual-spatial working memory. The frontoparietal network was over- or de-synchronized in the anterior-posterior direction by multi-electrode, 6 Hz transcranial alternating current stimulation (tACS). A decrease in memory performance and increase in reaction time was caused by frontoparietal intrahemispheric desynchronization. According to the diffusion drift model, this originated in a lower signal-to-noise ratio, known as the drift rate index, in the memory system. The EEG analysis revealed a corresponding decrease in phase connectivity between prefrontal and parietal areas after tACS-driven desynchronization. The over-synchronization did not result in any changes in either the behavioral or electrophysiological levels in healthy participants. Taken together, we demonstrate the feasibility of manipulating multi-site large-scale networks in humans, and the disruptive effect of frontoparietal desynchronization on theta phase connectivity and visual-spatial working memory.

Trajectory-probed instability and statistics of desynchronization events in coupled chaotic systems

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Oliveira, Gilson F. de, E-mail: gilson@otica.ufpb.br; Chevrollier, Martine; Oriá, Marcos [Departamento de Física, Universidade Federal da Paraíba, Caixa Postal 5008, 58051-900 João Pessoa-PB (Brazil); Passerat de Silans, Thierry [Departamento de Física, Universidade Federal da Paraíba, Caixa Postal 5008, 58051-900 João Pessoa-PB (Brazil); UAF, Universidade Federal de Campina Grande, 58429-900 Campina Grande, PB (Brazil); Souza Cavalcante, Hugo L. D. de [Departamento de Informática, Centro de Informática, Universidade Federal da Paraíba, Av. dos Escoteiros s/n, Mangabeira VII, 58055-000 João Pessoa, PB (Brazil)

2015-11-15

Complex systems, such as financial markets, earthquakes, and neurological networks, exhibit extreme events whose mechanisms of formation are not still completely understood. These mechanisms may be identified and better studied in simpler systems with dynamical features similar to the ones encountered in the complex system of interest. For instance, sudden and brief departures from the synchronized state observed in coupled chaotic systems were shown to display non-normal statistical distributions similar to events observed in the complex systems cited above. The current hypothesis accepted is that these desynchronization events are influenced by the presence of unstable object(s) in the phase space of the system. Here, we present further evidence that the occurrence of large events is triggered by the visitation of the system's phase-space trajectory to the vicinity of these unstable objects. In the system studied here, this visitation is controlled by a single parameter, and we exploit this feature to observe the effect of the visitation rate in the overall instability of the synchronized state. We find that the probability of escapes from the synchronized state and the size of those desynchronization events are enhanced in attractors whose shapes permit the chaotic trajectories to approach the region of strong instability. This result shows that the occurrence of large events requires not only a large local instability to amplify noise, or to amplify the effect of parameter mismatch between the coupled subsystems, but also that the trajectories of the system wander close to this local instability.

Trajectory-probed instability and statistics of desynchronization events in coupled chaotic systems

International Nuclear Information System (INIS)

Oliveira, Gilson F. de; Chevrollier, Martine; Oriá, Marcos; Passerat de Silans, Thierry; Souza Cavalcante, Hugo L. D. de

2015-01-01

Complex systems, such as financial markets, earthquakes, and neurological networks, exhibit extreme events whose mechanisms of formation are not still completely understood. These mechanisms may be identified and better studied in simpler systems with dynamical features similar to the ones encountered in the complex system of interest. For instance, sudden and brief departures from the synchronized state observed in coupled chaotic systems were shown to display non-normal statistical distributions similar to events observed in the complex systems cited above. The current hypothesis accepted is that these desynchronization events are influenced by the presence of unstable object(s) in the phase space of the system. Here, we present further evidence that the occurrence of large events is triggered by the visitation of the system's phase-space trajectory to the vicinity of these unstable objects. In the system studied here, this visitation is controlled by a single parameter, and we exploit this feature to observe the effect of the visitation rate in the overall instability of the synchronized state. We find that the probability of escapes from the synchronized state and the size of those desynchronization events are enhanced in attractors whose shapes permit the chaotic trajectories to approach the region of strong instability. This result shows that the occurrence of large events requires not only a large local instability to amplify noise, or to amplify the effect of parameter mismatch between the coupled subsystems, but also that the trajectories of the system wander close to this local instability

Trajectory-probed instability and statistics of desynchronization events in coupled chaotic systems

Science.gov (United States)

de Oliveira, Gilson F.; Chevrollier, Martine; Passerat de Silans, Thierry; Oriá, Marcos; de Souza Cavalcante, Hugo L. D.

2015-11-01

Complex systems, such as financial markets, earthquakes, and neurological networks, exhibit extreme events whose mechanisms of formation are not still completely understood. These mechanisms may be identified and better studied in simpler systems with dynamical features similar to the ones encountered in the complex system of interest. For instance, sudden and brief departures from the synchronized state observed in coupled chaotic systems were shown to display non-normal statistical distributions similar to events observed in the complex systems cited above. The current hypothesis accepted is that these desynchronization events are influenced by the presence of unstable object(s) in the phase space of the system. Here, we present further evidence that the occurrence of large events is triggered by the visitation of the system's phase-space trajectory to the vicinity of these unstable objects. In the system studied here, this visitation is controlled by a single parameter, and we exploit this feature to observe the effect of the visitation rate in the overall instability of the synchronized state. We find that the probability of escapes from the synchronized state and the size of those desynchronization events are enhanced in attractors whose shapes permit the chaotic trajectories to approach the region of strong instability. This result shows that the occurrence of large events requires not only a large local instability to amplify noise, or to amplify the effect of parameter mismatch between the coupled subsystems, but also that the trajectories of the system wander close to this local instability.

Event-related desynchronization and synchronization in MEG: Framework for analysis and illustrative datasets related to discrimination of frequency-modulated tones.

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Zygierewicz, J; Sieluzycki, C; König, R; Durka, P J

2008-02-15

We introduce a complete framework for the calculation of statistically significant event-related desynchronization and synchronization (ERD/ERS) in the time-frequency plane for magnetoencephalographic (MEG) data, and provide free Internet access to software and illustrative datasets related to a classification task of frequency-modulated (FM) tones. Event-related changes in MEG were analysed on the basis of the normal component of the magnetic field acquired by the 148 magnetometers of the hardware configuration of our whole-head MEG device, and by computing planar gradients in longitudinal and latitudinal direction. Time-frequency energy density for the magnetometer as well as the two gradient configurations is first approximated using short-time Fourier transform. Subsequently, detailed information is obtained from high-resolution time-frequency maps for the most interesting sensors by means of the computationally much more demanding matching pursuit parametrization. We argue that the ERD/ERS maps are easier to interpret in the gradient approaches and discuss the superior resolution of the matching pursuit time-frequency representation compared to short-time Fourier and wavelet transforms. Experimental results are accompanied by the following resources, available from http://brain.fuw.edu.pl/MEG: (a) 48 high-resolution figures presenting the results of four subjects in all applicable settings, (b) raw datasets, and (c) complete software environment, allowing to recompute these figures from the raw datasets.

Differential beta-band event-related desynchronization during categorical action sequence planning.

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Hame Park

Full Text Available A primate study reported the existence of neurons from the dorso-lateral prefrontal cortex which fired prior to executing categorical action sequences. The authors suggested these activities may represent abstract level information. Here, we aimed to find the neurophysiological representation of planning categorical action sequences at the population level in healthy humans. Previous human studies have shown beta-band event-related desynchronization (ERD during action planning in humans. Some of these studies showed different levels of ERD according to different types of action preparation. Especially, the literature suggests that variations in cognitive factors rather than physical factors (force, direction, etc modulate the level of beta-ERD. We hypothesized that the level of beta-band power will differ according to planning of different categorical sequences. We measured magnetoencephalography (MEG from 22 subjects performing 11 four-sequence actions--each consisting of one or two of three simple actions--in 3 categories; 'Paired (ooxx', 'Alternative (oxox' and 'Repetitive (oooo' ('o' and 'x' each denoting one of three simple actions. Time-frequency representations were calculated for each category during the planning period, and the corresponding beta-power time-courses were compared. We found beta-ERD during the planning period for all subjects, mostly in the contralateral fronto-parietal areas shortly after visual cue onset. Power increase (transient rebound followed ERD in 20 out of 22 subjects. Amplitudes differed among categories in 20 subjects for both ERD and transient rebound. In 18 out of 20 subjects 'Repetitive' category showed the largest ERD and rebound. The current result suggests that beta-ERD in the contralateral frontal/motor/parietal areas during planning is differentiated by the category of action sequences.

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

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Hanni Kiiski

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

EEG datasets for motor imagery brain-computer interface.

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Cho, Hohyun; Ahn, Minkyu; Ahn, Sangtae; Kwon, Moonyoung; Jun, Sung Chan

2017-07-01

Most investigators of brain-computer interface (BCI) research believe that BCI can be achieved through induced neuronal activity from the cortex, but not by evoked neuronal activity. Motor imagery (MI)-based BCI is one of the standard concepts of BCI, in that the user can generate induced activity by imagining motor movements. However, variations in performance over sessions and subjects are too severe to overcome easily; therefore, a basic understanding and investigation of BCI performance variation is necessary to find critical evidence of performance variation. Here we present not only EEG datasets for MI BCI from 52 subjects, but also the results of a psychological and physiological questionnaire, EMG datasets, the locations of 3D EEG electrodes, and EEGs for non-task-related states. We validated our EEG datasets by using the percentage of bad trials, event-related desynchronization/synchronization (ERD/ERS) analysis, and classification analysis. After conventional rejection of bad trials, we showed contralateral ERD and ipsilateral ERS in the somatosensory area, which are well-known patterns of MI. Finally, we showed that 73.08% of datasets (38 subjects) included reasonably discriminative information. Our EEG datasets included the information necessary to determine statistical significance; they consisted of well-discriminated datasets (38 subjects) and less-discriminative datasets. These may provide researchers with opportunities to investigate human factors related to MI BCI performance variation, and may also achieve subject-to-subject transfer by using metadata, including a questionnaire, EEG coordinates, and EEGs for non-task-related states. © The Authors 2017. Published by Oxford University Press.

Event-Related EEG Oscillations to Semantically Unrelated Words in Normal and Learning Disabled Children

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Fernandez, Thalia; Harmony, Thalia; Mendoza, Omar; Lopez-Alanis, Paula; Marroquin, Jose Luis; Otero, Gloria; Ricardo-Garcell, Josefina

2012-01-01

Learning disabilities (LD) are one of the most frequent problems for elementary school-aged children. In this paper, event-related EEG oscillations to semantically related and unrelated pairs of words were studied in a group of 18 children with LD not otherwise specified (LD-NOS) and in 16 children with normal academic achievement. We propose that…

Assessing quantitative EEG spectrograms to identify non-epileptic events.

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Goenka, Ajay; Boro, Alexis; Yozawitz, Elissa

2017-09-01

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

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

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Su, Kyung-Min; Hairston, W David; Robbins, Kay

2018-01-01

In controlled laboratory EEG experiments, researchers carefully mark events and analyze subject responses time-locked to these events. Unfortunately, such markers may not be available or may come with poor timing resolution for experiments conducted in less-controlled naturalistic environments. We present an integrated event-identification method for identifying particular responses that occur in unlabeled continuously recorded EEG signals based on information from recordings of other subjects potentially performing related tasks. We introduce the idea of timing slack and timing-tolerant performance measures to deal with jitter inherent in such non-time-locked systems. We have developed an implementation available as an open-source MATLAB toolbox (http://github.com/VisLab/EEG-Annotate) and have made test data available in a separate data note. We applied the method to identify visual presentation events (both target and non-target) in data from an unlabeled subject using labeled data from other subjects with good sensitivity and specificity. The method also identified actual visual presentation events in the data that were not previously marked in the experiment. Although the method uses traditional classifiers for initial stages, the problem of identifying events based on the presence of stereotypical EEG responses is the converse of the traditional stimulus-response paradigm and has not been addressed in its current form. In addition to identifying potential events in unlabeled or incompletely labeled EEG, these methods also allow researchers to investigate whether particular stereotypical neural responses are present in other circumstances. Timing-tolerance has the added benefit of accommodating inter- and intra- subject timing variations. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Dissociations between motor-related EEG measures in a cued movement sequence task

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Gladwin, Thomas E.; t' Hart, Bernhard M.; de Jong, Ritske

Different aspects of preparation, especially processes related to knowing what to prepare versus applying that foreknowledge effectively, may be reflected in different types of brain activity, e.g., the lateralized readiness potential (LRP), beta-band event-related desynchronization and phase

Action experience, more than observation, influences mu rhythm desynchronization.

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Erin N Cannon

Full Text Available Since the discovery of mirror neurons in premotor and parietal areas of the macaque monkey, the idea that action and perception may share the same neural code has been of central interest in social, developmental, and cognitive neurosciences. A fundamental question concerns how a putative human mirror neuron system may be tuned to the motor experiences of the individual. The current study tested the hypothesis that prior motor experience modulated the sensorimotor mu and beta rhythms. Specifically, we hypothesized that these sensorimotor rhythms would be more desynchronized after active motor experience compared to passive observation experience. To test our hypothesis, we collected EEG from adult participants during the observation of a relatively novel action: an experimenter used a claw-like tool to pick up a toy. Prior to EEG collection, we trained one group of adults to perform this action with the tool (performers. A second group comprised trained video coders, who only had experience observing the action (observers. Both the performers and the observers had no prior motor and visual experience with the action. A third group of novices was also tested. Performers exhibited the greatest mu rhythm desynchronization in the 8-13 Hz band, particularly in the right hemisphere compared to observers and novices. This study is the first to contrast active tool-use experience and observation experience in the mu rhythm and to show modulation with relatively shorter amounts of experience than prior mirror neuron expertise studies. These findings are discussed with respect to its broader implication as a neural signature for a mechanism of early social learning.

Overt foot movement detection in one single Laplacian EEG derivation.

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Solis-Escalante, Teodoro; Müller-Putz, Gernot; Pfurtscheller, Gert

2008-10-30

In this work one single Laplacian derivation and a full description of band power values in a broad frequency band are used to detect brisk foot movement execution in the ongoing EEG. Two support vector machines (SVM) are trained to detect the event-related desynchronization (ERD) during motor execution and the following beta rebound (event-related synchronization, ERS) independently. Their performance is measured through the simulation of an asynchronous brain switch. ERS (true positive rate=0.74+/-0.21) after motor execution is shown to be more stable than ERD (true positive rate=0.21+/-0.12). A novel combination of ERD and post-movement ERS is introduced. The SVM outputs are combined with a product rule to merge ERD and ERS detection. For this novel approach the average information transfer rate obtained was 11.19+/-3.61bits/min.

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

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Ming-ai Li

2017-01-01

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

Alpha desynchronization/synchronization during working memory testing is compromised in acute mild traumatic brain injury (mTBI).

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Arakaki, Xianghong; Shoga, Michael; Li, Lianyang; Zouridakis, George; Tran, Thao; Fonteh, Alfred N; Dawlaty, Jessica; Goldweber, Robert; Pogoda, Janice M; Harrington, Michael G

2018-01-01

Diagnosing and monitoring recovery of patients with mild traumatic brain injury (mTBI) is challenging because of the lack of objective, quantitative measures. Diagnosis is based on description of injuries often not witnessed, subtle neurocognitive symptoms, and neuropsychological testing. Since working memory (WM) is at the center of cognitive functions impaired in mTBI, this study was designed to define objective quantitative electroencephalographic (qEEG) measures of WM processing that may correlate with cognitive changes associated with acute mTBI. First-time mTBI patients and mild peripheral (limb) trauma controls without head injury were recruited from the emergency department. WM was assessed by a continuous performance task (N-back). EEG recordings were obtained during N-back testing on three occasions: within five days, two weeks, and one month after injury. Compared with controls, mTBI patients showed abnormal induced and evoked alpha activity including event-related desynchronization (ERD) and synchronization (ERS). For induced alpha power, TBI patients had excessive frontal ERD on their first and third visit. For evoked alpha, mTBI patients had lower parietal ERD/ERS at the second and third visits. These exploratory qEEG findings offer new and non-invasive candidate measures to characterize the evolution of injury over the first month, with potential to provide much-needed objective measures of brain dysfunction to diagnose and monitor the consequences of mTBI.

Neural Markers of Performance States in an Olympic Athlete: An EEG Case Study in Air-Pistol Shooting.

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di Fronso, Selenia; Robazza, Claudio; Filho, Edson; Bortoli, Laura; Comani, Silvia; Bertollo, Maurizio

2016-06-01

This study focused on identifying the neural markers underlying optimal and suboptimal performance experiences of an elite air-pistol shooter, based on the tenets of the multi-action plan (MAP) model. According to the MAP model's assumptions, skilled athletes' cortical patterns are expected to differ among optimal/automatic (Type 1), optimal/controlled (Type 2), suboptimal/controlled (Type 3), and suboptimal/automatic (Type 4) performance experiences. We collected performance (target pistol shots), cognitive-affective (perceived control, accuracy, and hedonic tone), and cortical activity data (32-channel EEG) of an elite shooter. Idiosyncratic descriptive analyses revealed differences in perceived accuracy in regard to optimal and suboptimal performance states. Event-Related Desynchronization/Synchronization analysis supported the notion that optimal-automatic performance experiences (Type 1) were characterized by a global synchronization of cortical arousal associated with the shooting task, whereas suboptimal controlled states (Type 3) were underpinned by high cortical activity levels in the attentional brain network. Results are addressed in light of the neural efficiency hypothesis and reinvestment theory. Perceptual training recommendations aimed at restoring optimal performance levels are discussed. Key pointsWe investigated the neural markers underlying optimal and suboptimal performance experiences of an elite air-pistol shooter.Optimal/automatic performance is characterized by a global synchronization of cortical activity associated with the shooting task.Suboptimal controlled performance is characterized by high cortical arousal levels in the attentional brain networks.Focused Event Related Desynchronization activity during Type 1 performance in frontal midline theta was found, with a clear distribution of Event Related Synchronization in the frontal and central areas just prior to shot release.Event Related Desynchronization patterns in low Alpha band

Combined analysis of cortical (EEG) and nerve stump signals improves robotic hand control.

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Tombini, Mario; Rigosa, Jacopo; Zappasodi, Filippo; Porcaro, Camillo; Citi, Luca; Carpaneto, Jacopo; Rossini, Paolo Maria; Micera, Silvestro

2012-01-01

Interfacing an amputee's upper-extremity stump nerves to control a robotic hand requires training of the individual and algorithms to process interactions between cortical and peripheral signals. To evaluate for the first time whether EEG-driven analysis of peripheral neural signals as an amputee practices could improve the classification of motor commands. Four thin-film longitudinal intrafascicular electrodes (tf-LIFEs-4) were implanted in the median and ulnar nerves of the stump in the distal upper arm for 4 weeks. Artificial intelligence classifiers were implemented to analyze LIFE signals recorded while the participant tried to perform 3 different hand and finger movements as pictures representing these tasks were randomly presented on a screen. In the final week, the participant was trained to perform the same movements with a robotic hand prosthesis through modulation of tf-LIFE-4 signals. To improve the classification performance, an event-related desynchronization/synchronization (ERD/ERS) procedure was applied to EEG data to identify the exact timing of each motor command. Real-time control of neural (motor) output was achieved by the participant. By focusing electroneurographic (ENG) signal analysis in an EEG-driven time window, movement classification performance improved. After training, the participant regained normal modulation of background rhythms for movement preparation (α/β band desynchronization) in the sensorimotor area contralateral to the missing limb. Moreover, coherence analysis found a restored α band synchronization of Rolandic area with frontal and parietal ipsilateral regions, similar to that observed in the opposite hemisphere for movement of the intact hand. Of note, phantom limb pain (PLP) resolved for several months. Combining information from both cortical (EEG) and stump nerve (ENG) signals improved the classification performance compared with tf-LIFE signals processing alone; training led to cortical reorganization and

Time is of the Essence: A Review of Electroencephalography (EEG) and Event-Related Brain Potentials (ERPs) in Language Research.

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Beres, Anna M

2017-12-01

The discovery of electroencephalography (EEG) over a century ago has changed the way we understand brain structure and function, in terms of both clinical and research applications. This paper starts with a short description of EEG and then focuses on the event-related brain potentials (ERPs), and their use in experimental settings. It describes the typical set-up of an ERP experiment. A description of a number of ERP components typically involved in language research is presented. Finally, the advantages and disadvantages of using ERPs in language research are discussed. EEG has an extensive use in today's world, including medical, psychology, or linguistic research. The excellent temporal resolution of EEG information allows one to track a brain response in milliseconds and therefore makes it uniquely suited to research concerning language processing.

Joint Maximum Likelihood Time Delay Estimation of Unknown Event-Related Potential Signals for EEG Sensor Signal Quality Enhancement

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Kim, Kyungsoo; Lim, Sung-Ho; Lee, Jaeseok; Kang, Won-Seok; Moon, Cheil; Choi, Ji-Woong

2016-01-01

Electroencephalograms (EEGs) measure a brain signal that contains abundant information about the human brain function and health. For this reason, recent clinical brain research and brain computer interface (BCI) studies use EEG signals in many applications. Due to the significant noise in EEG traces, signal processing to enhance the signal to noise power ratio (SNR) is necessary for EEG analysis, especially for non-invasive EEG. A typical method to improve the SNR is averaging many trials of event related potential (ERP) signal that represents a brain’s response to a particular stimulus or a task. The averaging, however, is very sensitive to variable delays. In this study, we propose two time delay estimation (TDE) schemes based on a joint maximum likelihood (ML) criterion to compensate the uncertain delays which may be different in each trial. We evaluate the performance for different types of signals such as random, deterministic, and real EEG signals. The results show that the proposed schemes provide better performance than other conventional schemes employing averaged signal as a reference, e.g., up to 4 dB gain at the expected delay error of 10°. PMID:27322267

Joint Maximum Likelihood Time Delay Estimation of Unknown Event-Related Potential Signals for EEG Sensor Signal Quality Enhancement

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Kyungsoo Kim

2016-06-01

Full Text Available Electroencephalograms (EEGs measure a brain signal that contains abundant information about the human brain function and health. For this reason, recent clinical brain research and brain computer interface (BCI studies use EEG signals in many applications. Due to the significant noise in EEG traces, signal processing to enhance the signal to noise power ratio (SNR is necessary for EEG analysis, especially for non-invasive EEG. A typical method to improve the SNR is averaging many trials of event related potential (ERP signal that represents a brain’s response to a particular stimulus or a task. The averaging, however, is very sensitive to variable delays. In this study, we propose two time delay estimation (TDE schemes based on a joint maximum likelihood (ML criterion to compensate the uncertain delays which may be different in each trial. We evaluate the performance for different types of signals such as random, deterministic, and real EEG signals. The results show that the proposed schemes provide better performance than other conventional schemes employing averaged signal as a reference, e.g., up to 4 dB gain at the expected delay error of 10°.

Intelligence related upper alpha desynchronization in a semantic memory task.

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Doppelmayr, M; Klimesch, W; Hödlmoser, K; Sauseng, P; Gruber, W

2005-07-30

Recent evidence shows that event-related (upper) alpha desynchronization (ERD) is related to cognitive performance. Several studies observed a positive, some a negative relationship. The latter finding, interpreted in terms of the neural efficiency hypothesis, suggests that good performance is associated with a more 'efficient', smaller extent of cortical activation. Other studies found that ERD increases with semantic processing demands and that this increase is larger for good performers. Studies supporting the neural efficiency hypothesis used tasks that do not specifically require semantic processing. Thus, we assume that the lack of semantic processing demands may at least in part be responsible for the reduced ERD. In the present study we measured ERD during a difficult verbal-semantic task. The findings demonstrate that during semantic processing, more intelligent (as compared to less intelligent) subjects exhibited a significantly larger upper alpha ERD over the left hemisphere. We conclude that more intelligent subjects exhibit a more extensive activation in a semantic processing system and suggest that divergent findings regarding the neural efficiency hypotheses are due to task specific differences in semantic processing demands.

Hilbert-Huang Spectrum as a new field for the identification of EEG event related de-/synchronization for BCI applications.

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Panoulas, Konstantinos I; Hadjileontiadis, Leontios J; Panas, Stavros M

2008-01-01

Brain Computer Interfaces (BCI) usually utilize the suppression of mu-rhythm during actual or imagined motor activity. In order to create a BCI system, a signal processing method is required to extract features upon which the discrimination is based. In this article, the Empirical Mode Decomposition along with the Hilbert-Huang Spectrum (HHS) is found to contain the necessary information to be considered as an input to a discriminator. Also, since the HHS defines amplitude and instantaneous frequency for each sample, it can be used for an online BCI system. Experimental results when the HHS applied to EEG signals from an on-line database (BCI Competition III) show the potentiality of the proposed analysis to capture the imagined motor activity, contributing to a more enhanced BCI performance.

Alpha desynchronization and fronto­parietal connectivity during spatial working memory encoding deficits in ADHD: A simultaneous EEG­fMRI study

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Agatha Lenartowicz

2016-01-01

Full Text Available The underlying mechanisms of alpha band (8–12 Hz neural oscillations are of importance to the functioning of attention control systems as well as to neuropsychiatric conditions that are characterized by deficits of that system, such as attention deficit hyperactivity disorder (ADHD. The objectives of the present study were to test if visual encoding-related alpha event-related desynchronization (ERD correlates with fronto-parieto-occipital connectivity, and whether this is disrupted in ADHD during spatial working memory (SWM performance. We acquired EEG concurrently with fMRI in thirty boys (12–16 yrs. old, 15 with ADHD, during SWM encoding. Psychophysiological connectivity analyses indicated that alpha ERD during SWM encoding was associated with both occipital activation and fronto-parieto-occipital functional connectivity, a finding that expands on prior associations between alpha ERD and occipital activation. This finding provides novel support for the interpretation of alpha ERD (and the associated changes in occipital activation as a phenomenon that involves, and perhaps arises as a result of, top-down network interactions. Alpha ERD was associated less strongly with occipital activity, but associated more strongly with fronto-parieto-occipital connectivity in ADHD, consistent with a compensatory attentional response. Additionally, we illustrate that degradation of EEG data quality by MRI-amplified motion artifacts is robust to existing cleaning algorithms and is significantly correlated with hyperactivity symptoms and the ADHD Combined Type diagnosis. We conclude that persistent motion-related MR artifacts in EEG data can increase variance and introduce bias in interpretation of group differences in populations characterized by hypermobility — a clear limitation of current-state EEG-fMRI methodology.

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

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Alejandro Gonzalez

2014-01-01

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

Assessment of Event-Related EEG Power After Single-Pulse TMS in Unresponsive Wakefulness Syndrome and Minimally Conscious State Patients.

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Formaggio, Emanuela; Cavinato, Marianna; Storti, Silvia Francesca; Tonin, Paolo; Piccione, Francesco; Manganotti, Paolo

2016-03-01

In patients without a behavioral response, non-invasive techniques and new methods of data analysis can complement existing diagnostic tools by providing a method for detecting covert signs of residual cognitive function and awareness. The aim of this study was to investigate the brain oscillatory activities synchronized by single-pulse transcranial magnetic stimulation (TMS) delivered over the primary motor area in the time-frequency domain in patients with the unresponsive wakefulness syndrome or in a minimally conscious state as compared to healthy controls. A time-frequency analysis based on the wavelet transform was used to characterize rapid modifications of oscillatory EEG rhythms induced by TMS in patients as compared to healthy controls. The pattern of EEG changes in the patients differed from that of healthy controls. In the controls there was an early synchronization of slow waves immediately followed by a desynchronization of alpha and beta frequency bands over the frontal and centro-parietal electrodes, whereas an opposite early synchronization, particularly over motor areas for alpha and beta and over the frontal and parietal electrodes for beta power, was seen in the patients. In addition, no relevant modification in slow rhythms (delta and theta) after TMS was noted in patients. The clinical impact of these findings could be relevant in neurorehabilitation settings for increasing the awareness of these patients and defining new treatment procedures.

DESYNC: Self-Organizing Desynchronization and TDMA on Wireless Sensor Networks

OpenAIRE

Degesys, Julius; Rose, Ian; Patel, Ankit; Nagpal, Radhika

2006-01-01

Desynchronization is a novel primitive for sensor networks: it implies that nodes perfectly interleave periodic events to occur in a round-robin schedule. This primitive can be used to evenly distribute sampling burden in a group of nodes, schedule sleep cycles, or organize a collision-free TDMA schedule for transmitting wireless messages. Here we present Desync, a biologically-inspired self-maintaining algorithm for desynchronization in a single-hop network. We present (1) theoretical result...

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

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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).

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

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Andrei V. Sazonov

2007-01-01

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

Effects of rearranged vision on event-related lateralizations of the EEG during pointing.

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Berndt, Isabelle; Franz, Volker H; Bülthoff, Heinrich H; Gotz, Karl G; Wascher, Edmund

2005-01-01

We used event-related lateralizations of the EEG (ERLs) and reversed vision to study visuomotor processing with conflicting proprioceptive and visual information during pointing. Reversed vision decreased arm-related lateralization, probably reflecting the simultaneous activity of left and right arm specific neurons: neurons in the hemisphere contralateral to the observed action were probably activated by visual feedback, neurons in the hemisphere contralateral to the response side by the somatomotor feedback. Lateralization related to the target in parietal cortex increased, indicating that visual to motor transformation in parietal cortex required additional time and resources with reversed vision. A short period of adaptation to an additional lateral displacement of the visual field increased arm-contralateral activity in parietal cortex during the movement. This is in agreement with the, which showed that adaptation to a lateral displacement of the visual field is reflected in increased parietal involvement during pointing.

Predicting Functional Recovery in Chronic Stroke Rehabilitation Using Event-Related Desynchronization-Synchronization during Robot-Assisted Movement

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Gramigna, Cristina; Franceschetti, Silvana

2016-01-01

Although rehabilitation robotics seems to be a promising therapy in the rehabilitation of the upper limb in stroke patients, consensus is still lacking on its additive effects. Therefore, there is a need for determining the possible success of robotic interventions on selected patients, which in turn determine the necessity for new investigating instruments supporting the treatment decision-making process and customization. The objective of the work presented in this preliminary study was to verify that fully robot assistance would not affect the physiological oscillatory cortical activity related to a functional movement in healthy subjects. Further, the clinical results following the robotic treatment of a chronic stroke patient, who positively reacted to the robotic intervention, were analyzed and discussed. First results show that there is no difference in EEG activation pattern between assisted and no-assisted movement in healthy subjects. Even more importantly, the patient's pretreatment EEG activation pattern in no-assisted movement was completely altered, while it recovered to a quasi-physiological one in robot-assisted movement. The functional improvement following treatment was large. Using pretreatment EEG recording during robot-assisted movement might be a valid approach to assess the potential ability of the patient for recovering. PMID:27057546

Validation of the Emotiv EPOC EEG system for research quality auditory event-related potentials in children.

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Badcock, Nicholas A; Preece, Kathryn A; de Wit, Bianca; Glenn, Katharine; Fieder, Nora; Thie, Johnson; McArthur, Genevieve

2015-01-01

Background. Previous work has demonstrated that a commercial gaming electroencephalography (EEG) system, Emotiv EPOC, can be adjusted to provide valid auditory event-related potentials (ERPs) in adults that are comparable to ERPs recorded by a research-grade EEG system, Neuroscan. The aim of the current study was to determine if the same was true for children. Method. An adapted Emotiv EPOC system and Neuroscan system were used to make simultaneous EEG recordings in nineteen 6- to 12-year-old children under "passive" and "active" listening conditions. In the passive condition, children were instructed to watch a silent DVD and ignore 566 standard (1,000 Hz) and 100 deviant (1,200 Hz) tones. In the active condition, they listened to the same stimuli, and were asked to count the number of 'high' (i.e., deviant) tones. Results. Intraclass correlations (ICCs) indicated that the ERP morphology recorded with the two systems was very similar for the P1, N1, P2, N2, and P3 ERP peaks (r = .82 to .95) in both passive and active conditions, and less so, though still strong, for mismatch negativity ERP component (MMN; r = .67 to .74). There were few differences between peak amplitude and latency estimates for the two systems. Conclusions. An adapted EPOC EEG system can be used to index children's late auditory ERP peaks (i.e., P1, N1, P2, N2, P3) and their MMN ERP component.

Validation of the Emotiv EPOC EEG system for research quality auditory event-related potentials in children

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Nicholas A. Badcock

2015-04-01

Full Text Available Background. Previous work has demonstrated that a commercial gaming electroencephalography (EEG system, Emotiv EPOC, can be adjusted to provide valid auditory event-related potentials (ERPs in adults that are comparable to ERPs recorded by a research-grade EEG system, Neuroscan. The aim of the current study was to determine if the same was true for children.Method. An adapted Emotiv EPOC system and Neuroscan system were used to make simultaneous EEG recordings in nineteen 6- to 12-year-old children under “passive” and “active” listening conditions. In the passive condition, children were instructed to watch a silent DVD and ignore 566 standard (1,000 Hz and 100 deviant (1,200 Hz tones. In the active condition, they listened to the same stimuli, and were asked to count the number of ‘high’ (i.e., deviant tones.Results. Intraclass correlations (ICCs indicated that the ERP morphology recorded with the two systems was very similar for the P1, N1, P2, N2, and P3 ERP peaks (r = .82 to .95 in both passive and active conditions, and less so, though still strong, for mismatch negativity ERP component (MMN; r = .67 to .74. There were few differences between peak amplitude and latency estimates for the two systems.Conclusions. An adapted EPOC EEG system can be used to index children’s late auditory ERP peaks (i.e., P1, N1, P2, N2, P3 and their MMN ERP component.

Short desynchronization episodes prevail in synchronous dynamics of human brain rhythms.

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Ahn, Sungwoo; Rubchinsky, Leonid L

2013-03-01

Neural synchronization is believed to be critical for many brain functions. It frequently exhibits temporal variability, but it is not known if this variability has a specific temporal patterning. This study explores these synchronization/desynchronization patterns. We employ recently developed techniques to analyze the fine temporal structure of phase-locking to study the temporal patterning of synchrony of the human brain rhythms. We study neural oscillations recorded by electroencephalograms in α and β frequency bands in healthy human subjects at rest and during the execution of a task. While the phase-locking strength depends on many factors, dynamics of synchrony has a very specific temporal pattern: synchronous states are interrupted by frequent, but short desynchronization episodes. The probability for a desynchronization episode to occur decreased with its duration. The transition matrix between synchronized and desynchronized states has eigenvalues close to 0 and 1 where eigenvalue 1 has multiplicity 1, and therefore if the stationary distribution between these states is perturbed, the system converges back to the stationary distribution very fast. The qualitative similarity of this patterning across different subjects, brain states and electrode locations suggests that this may be a general type of dynamics for the brain. Earlier studies indicate that not all oscillatory networks have this kind of patterning of synchronization/desynchronization dynamics. Thus, the observed prevalence of short (but potentially frequent) desynchronization events (length of one cycle of oscillations) may have important functional implications for the brain. Numerous short desynchronizations (as opposed to infrequent, but long desynchronizations) may allow for a quick and efficient formation and break-up of functionally significant neuronal assemblies.

[Training cortical signals by means of a BMI-EEG system, its evolution and intervention. A case report].

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Monge-Pereira, E; Casatorres Perez-Higueras, I; Fernandez-Gonzalez, P; Ibanez-Pereda, J; Serrano, J I; Molina-Rueda, F

2017-04-16

In the last years, new technologies such as the brain-machine interfaces (BMI) have been incorporated in the rehabilitation process of subjects with stroke. These systems are able to detect motion intention, analyzing the cortical signals using different techniques such as the electroencephalography (EEG). This information could guide different interfaces such as robotic devices, electrical stimulation or virtual reality. A 40 years-old man with stroke with two months from the injury participated in this study. We used a BMI based on EEG. The subject's motion intention was analyzed calculating the event-related desynchronization. The upper limb motor function was evaluated with the Fugl-Meyer Assessment and the participant's satisfaction was evaluated using the QUEST 2.0. The intervention using a physical therapist as an interface was carried out without difficulty. The BMI systems detect cortical changes in a subacute stroke subject. These changes are coherent with the evolution observed using the Fugl-Meyer Assessment.

Predicting Functional Recovery in Chronic Stroke Rehabilitation Using Event-Related Desynchronization-Synchronization during Robot-Assisted Movement

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Marco Caimmi

2016-01-01

Full Text Available Although rehabilitation robotics seems to be a promising therapy in the rehabilitation of the upper limb in stroke patients, consensus is still lacking on its additive effects. Therefore, there is a need for determining the possible success of robotic interventions on selected patients, which in turn determine the necessity for new investigating instruments supporting the treatment decision-making process and customization. The objective of the work presented in this preliminary study was to verify that fully robot assistance would not affect the physiological oscillatory cortical activity related to a functional movement in healthy subjects. Further, the clinical results following the robotic treatment of a chronic stroke patient, who positively reacted to the robotic intervention, were analyzed and discussed. First results show that there is no difference in EEG activation pattern between assisted and no-assisted movement in healthy subjects. Even more importantly, the patient’s pretreatment EEG activation pattern in no-assisted movement was completely altered, while it recovered to a quasi-physiological one in robot-assisted movement. The functional improvement following treatment was large. Using pretreatment EEG recording during robot-assisted movement might be a valid approach to assess the potential ability of the patient for recovering.

Tunable power law in the desynchronization events of coupled chaotic electronic circuits

International Nuclear Information System (INIS)

Oliveira, Gilson F. de; Lorenzo, Orlando di; Chevrollier, Martine; Passerat de Silans, Thierry; Oriá, Marcos; Souza Cavalcante, Hugo L. D. de

2014-01-01

We study the statistics of the amplitude of the synchronization error in chaotic electronic circuits coupled through linear feedback. Depending on the coupling strength, our system exhibits three qualitatively different regimes of synchronization: weak coupling yields independent oscillations; moderate to strong coupling produces a regime of intermittent synchronization known as attractor bubbling; and stronger coupling produces complete synchronization. In the regime of moderate coupling, the probability distribution for the sizes of desynchronization events follows a power law, with an exponent that can be adjusted by changing the coupling strength. Such power-law distributions are interesting, as they appear in many complex systems. However, most of the systems with such a behavior have a fixed value for the exponent of the power law, while here we present an example of a system where the exponent of the power law is easily tuned in real time

Chaos desynchronization in strongly coupled systems

International Nuclear Information System (INIS)

Wu Ye; Liu Weiqing; Xiao, Jinghua; Zhan Meng

2007-01-01

The dynamics of chaos desynchronization in strongly coupled oscillator systems is studied. We find a new bifurcation from synchronous chaotic state, chaotic short wave bifurcation, i.e. a chaotic desynchronization attractor is new born in the systems due to chaos desynchronization. In comparison with the usual periodic short wave bifurcation, very rich but distinct phenomena are observed

Modulation of mu rhythm desynchronization during motor imagery by transcranial direct current stimulation

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Kimura Akio

2010-06-01

Full Text Available Abstract Background The mu event-related desynchronization (ERD is supposed to reflect motor preparation and appear during motor imagery. The aim of this study is to examine the modulation of ERD with transcranial direct current stimulation (tDCS. Methods Six healthy subjects were asked to imagine their right hand grasping something after receiving a visual cue. Electroencephalograms (EEGs were recorded near the left M1. ERD of the mu rhythm (mu ERD by right hand motor imagery was measured. tDCS (10 min, 1 mA was used to modulate the cortical excitability of M1. Anodal, cathodal, and sham tDCS were tested in each subject with a randomized sequence on different days. Each condition was separated from the preceding one by more than 1 week in the same subject. Before and after tDCS, mu ERD was assessed. The motor thresholds (MT of the left M1 were also measured with transcranial magnetic stimulation. Results Mu ERD significantly increased after anodal stimulation, whereas it significantly decreased after cathodal stimulation. There was a significant correlation between mu ERD and MT. Conclusions Opposing effects on mu ERD based on the orientation of the stimulation suggest that mu ERD is affected by cortical excitability.

Cocaine action on peripheral, non-monoamine neural substrates as a trigger of electroencephalographic desynchronization and electromyographic activation following i.v. administration in freely moving rats.

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Smirnov, M S; Kiyatkin, E A

2010-01-20

Many important physiological, behavioral and subjective effects of i.v. cocaine (COC) are exceptionally rapid and transient, suggesting a possible involvement of peripheral neural substrates in their triggering. In the present study, we used high-speed electroencephalographic (EEG) and electromyographic (EMG) recordings (4-s resolution) in freely moving rats to characterize the central electrophysiological effects of i.v. COC at low doses within a self-administration range (0.25-1.0 mg/kg). We found that COC induces rapid, strong, and prolonged desynchronization of cortical EEG (decrease in alpha and increase in beta and gamma activity) and activation of the neck EMG that begin within 2-6 s following the start of a 10-s injection; immediate components of both effects were dose-independent. The rapid effects of COC were mimicked by i.v. COC methiodide (COC-MET), a derivative that cannot cross the blood-brain barrier. At equimolar doses (0.33-1.33 mg/kg), COC-MET had equally fast and strong effects on EEG and EMG total powers, decreasing alpha and increasing beta and gamma activities. Rapid EEG desynchronization and EMG activation was also induced by i.v. procaine, a structurally similar, short-acting local anesthetic with virtually no effects on monoamine uptake; at equipotential doses (1.25-5.0 mg/kg), these effects were weaker and shorter in duration than those of COC. Surprisingly, i.v. saline injection delivered during slow-wave sleep (but not during quiet wakefulness) also induced a transient EEG desynchronization but without changes in EMG and motor activity; these effects were significantly weaker and much shorter than those induced by all tested drugs. These data suggest that in awake animals, i.v. COC induces rapid cortical activation and a subsequent motor response via its action on peripheral non-monoamine neural elements, involving neural transmission via visceral sensory pathways. By providing a rapid neural signal and triggering neural activation, such

EEG Classification for Hybrid Brain-Computer Interface Using a Tensor Based Multiclass Multimodal Analysis Scheme.

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Ji, Hongfei; Li, Jie; Lu, Rongrong; Gu, Rong; Cao, Lei; Gong, Xiaoliang

2016-01-01

Electroencephalogram- (EEG-) based brain-computer interface (BCI) systems usually utilize one type of changes in the dynamics of brain oscillations for control, such as event-related desynchronization/synchronization (ERD/ERS), steady state visual evoked potential (SSVEP), and P300 evoked potentials. There is a recent trend to detect more than one of these signals in one system to create a hybrid BCI. However, in this case, EEG data were always divided into groups and analyzed by the separate processing procedures. As a result, the interactive effects were ignored when different types of BCI tasks were executed simultaneously. In this work, we propose an improved tensor based multiclass multimodal scheme especially for hybrid BCI, in which EEG signals are denoted as multiway tensors, a nonredundant rank-one tensor decomposition model is proposed to obtain nonredundant tensor components, a weighted fisher criterion is designed to select multimodal discriminative patterns without ignoring the interactive effects, and support vector machine (SVM) is extended to multiclass classification. Experiment results suggest that the proposed scheme can not only identify the different changes in the dynamics of brain oscillations induced by different types of tasks but also capture the interactive effects of simultaneous tasks properly. Therefore, it has great potential use for hybrid BCI.

Decreased Modulation of EEG Oscillations in High-Functioning Autism During a Motor Control Task

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Joshua Benjamin Ewen

2016-05-01

Full Text Available Autism spectrum disorders (ASD are thought to result in part from altered cortical excitatory-inhibitory balance; this pathophysiology may impact the generation of oscillations on EEG. We investigated premotor-parietal cortical physiology associated with praxis, which has strong theoretical and empirical associations with ASD symptomatology. 25 children with high-functioning ASD (HFA and 33 controls performed a praxis task involving the pantomiming of tool use, while EEG was recorded. We assessed task-related modulation of signal power in alpha and beta frequency bands. Compared with controls, subjects with HFA showed 27% less left central (motor/premotor beta (18-22 Hz event-related desynchronization (ERD (p = 0.030, as well as 24% less left parietal alpha (7-13 Hz ERD (p = 0.046. Within the HFA group, blunting of central ERD attenuation was associated with impairments in clinical measures of praxis imitation (r = -0.4; p = 0.04 and increased autism severity (r = 0.48; p = 0.016. The modulation of central beta activity is associated, among other things, with motor imagery, which may be necessary for imitation. Impaired imitation has been associated with core features of ASD. Altered modulation of oscillatory activity may be mechanistically involved in those aspects of motor network function that relate to the core symptoms of ASD.

EEG Mu (µ) rhythm spectra and oscillatory activity differentiate stuttering from non-stuttering adults.

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Saltuklaroglu, Tim; Harkrider, Ashley W; Thornton, David; Jenson, David; Kittilstved, Tiffani

2017-06-01

Stuttering is linked to sensorimotor deficits related to internal modeling mechanisms. This study compared spectral power and oscillatory activity of EEG mu (μ) rhythms between persons who stutter (PWS) and controls in listening and auditory discrimination tasks. EEG data were analyzed from passive listening in noise and accurate (same/different) discrimination of tones or syllables in quiet and noisy backgrounds. Independent component analysis identified left and/or right μ rhythms with characteristic alpha (α) and beta (β) peaks localized to premotor/motor regions in 23 of 27 people who stutter (PWS) and 24 of 27 controls. PWS produced μ spectra with reduced β amplitudes across conditions, suggesting reduced forward modeling capacity. Group time-frequency differences were associated with noisy conditions only. PWS showed increased μ-β desynchronization when listening to noise and early in discrimination events, suggesting evidence of heightened motor activity that might be related to forward modeling deficits. PWS also showed reduced μ-α synchronization in discrimination conditions, indicating reduced sensory gating. Together these findings indicate spectral and oscillatory analyses of μ rhythms are sensitive to stuttering. More specifically, they can reveal stuttering-related sensorimotor processing differences in listening and auditory discrimination that also may be influenced by basal ganglia deficits. Copyright © 2017 Elsevier Inc. All rights reserved.

Event-related oscillations (EROs) and event-related potentials (ERPs) comparison in facial expression recognition.

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Balconi, Michela; Pozzoli, Uberto

2007-09-01

The study aims to explore the significance of event-related potentials (ERPs) and event-related brain oscillations (EROs) (delta, theta, alpha, beta, gamma power) in response to emotional (fear, happiness, sadness) when compared with neutral faces during 180-250 post-stimulus time interval. The ERP results demonstrated that the emotional face elicited a negative peak at approximately 230 ms (N2). Moreover, EEG measures showed that motivational significance of face (emotional vs. neutral) could modulate the amplitude of EROs, but only for some frequency bands (i.e. theta and gamma bands). In a second phase, we considered the resemblance of the two EEG measures by a regression analysis. It revealed that theta and gamma oscillations mainly effect as oscillation activity at the N2 latency. Finally, a posterior increased power of theta was found for emotional faces.

Plastic modulation of PTSD resting-state networks by EEG neurofeedback

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

2015-01-01

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

Mu rhythm desynchronization by tongue thrust observation

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Kotoe eSakihara

2015-09-01

Full Text Available We aimed to investigate the mu rhythm in the sensorimotor area during tongue thrust observation and to obtain an answer to the question as to how subtle non-verbal orofacial movement observation activates the sensorimotor area. Ten healthy volunteers performed finger tap execution, tongue thrust execution, and tongue thrust observation. The electroencephalogram was recorded from 128 electrodes placed on the scalp, and regions of interest were set at sensorimotor areas. The event-related desynchronization (ERD and event-related synchronization (ERS for the mu rhythm (8–13 Hz and beta (13−25 Hz bands were measured. Tongue thrust observation induced mu rhythm ERD, and the ERD was detected at the left hemisphere regardless whether the observed tongue thrust was toward the left or right. Mu rhythm ERD was also recorded during tongue thrust execution. However, temporal analysis revealed that the ERD associated with tongue thrust observation preceded that associated with execution by approximately 2 s. Tongue thrust observation induces mu rhythm ERD in sensorimotor cortex with left hemispheric dominance.

Analysis of the features of untrained human movements based on the multichannel EEG for controlling anthropomorphic robotic arm

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Maksimenko, Vladimir; Runnova, Anastasia; Pchelintseva, Svetlana; Efremova, Tatiana; Zhuravlev, Maksim; Pisarchik, Alexander

2018-04-01

We have considered time-frequency and spatio-temporal structure of electrical brain activity, associated with real and imaginary movements based on the multichannel EEG recordings. We have found that along with wellknown effects of event-related desynchronization (ERD) in α/μ - rhythms and β - rhythm, these types of activity are accompanied by the either ERS (for real movement) or ERD (for imaginary movement) in low-frequency δ - band, located mostly in frontal lobe. This may be caused by the associated processes of decision making, which take place when subject is deciding either perform the movement or imagine it. Obtained features have been found in untrained subject which it its turn gives the possibility to use our results in the development of brain-computer interfaces for controlling anthropomorphic robotic arm.

The dynamics of sensorimotor cortical oscillations during the observation of hand movements: an EEG study.

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Pietro Avanzini

Full Text Available BACKGROUND: The observation of action done by others determines a desynchronization of the rhythms recorded from cortical central regions. Here, we examined whether the observation of different types of hand movements (target directed, non-target directed, cyclic and non-cyclic elicits different EEG cortical temporal patterns. METHODOLOGY: Video-clips of four types of hand movements were shown to right-handed healthy participants. Two were target directed (grasping and pointing motor acts; two were non-target directed (supinating and clenching movements. Grasping and supinating were performed once, while pointing and clenching twice (cyclic movements. High-density EEG was recorded and analyzed by means of wavelet transform, subdividing the time course in time bins of 200 ms. The observation of all presented movements produced a desynchronization of alpha and beta rhythms in central and parietal regions. The rhythms desynchronized as soon as the hand movement started, the nadir being reached around 700 ms after movement onset. At the end of the movement, a large power rebound occurred for all bands. Target and non-target directed movements produced an alpha band desynchronization in the central electrodes at the same time, but with a stronger desynchronization and a prolonged rebound for target directed motor acts. Most interestingly, there was a clear correlation between the velocity profile of the observed movements and beta band modulation. SIGNIFICANCE: Our data show that the observation of motor acts determines a modulation of cortical rhythm analogous to that occurring during motor act execution. In particular, the cortical motor system closely follows the velocity of the observed movements. This finding provides strong evidence for the presence in humans of a mechanism (mirror mechanism mapping action observation on action execution motor programs.

Emotional Granularity Effects on Event-Related Brain Potentials during Affective Picture Processing.

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Lee, Ja Y; Lindquist, Kristen A; Nam, Chang S

2017-01-01

There is debate about whether emotional granularity , the tendency to label emotions in a nuanced and specific manner, is merely a product of labeling abilities, or a systematic difference in the experience of emotion during emotionally evocative events. According to the Conceptual Act Theory of Emotion (CAT) (Barrett, 2006), emotional granularity is due to the latter and is a product of on-going temporal differences in how individuals categorize and thus make meaning of their affective states. To address this question, the present study investigated the effects of individual differences in emotional granularity on electroencephalography-based brain activity during the experience of emotion in response to affective images. Event-related potentials (ERP) and event-related desynchronization and synchronization (ERD/ERS) analysis techniques were used. We found that ERP responses during the very early (60-90 ms), middle (270-300 ms), and later (540-570 ms) moments of stimulus presentation were associated with individuals' level of granularity. We also observed that highly granular individuals, compared to lowly granular individuals, exhibited relatively stable desynchronization of alpha power (8-12 Hz) and synchronization of gamma power (30-50 Hz) during the 3 s of stimulus presentation. Overall, our results suggest that emotional granularity is related to differences in neural processing throughout emotional experiences and that high granularity could be associated with access to executive control resources and a more habitual processing of affective stimuli, or a kind of "emotional complexity." Implications for models of emotion are also discussed.

Tangential derivative mapping of axial MEG applied to event-related desynchronization research

NARCIS (Netherlands)

Bastiaansen, M.C.M.; Knösche, T.R.

2000-01-01

Objectives: A problem with the topographic mapping of MEG data recorded with axial gradiometers is that field extrema are measured at sensors located at either side of a neuronal generator instead of at sensors directly above the source. This is problematic for the computation of event-related

Detection of mental imagery and attempted movements in patients with disorders of consciousness using EEG

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Petar eHorki

2014-12-01

Full Text Available Further development of an EEG based communication device for patients with disorders of consciousness (DoC could benefit from addressing the following gaps in knowledge – first, an evaluation of different types of motor imagery; second, an evaluation of passive feet movement as a mean of an initial classifier setup; and third, rapid delivery of biased feedback. To that end we investigated whether complex and / or familiar mental imagery, passive, and attempted feet movement can be reliably detected in patients with DoC using EEG recordings, aiming to provide them with a means of communication. Six patients in a minimally conscious state (MCS took part in this study. The patients were verbally instructed to perform different mental imagery tasks (sport, navigation, as well as attempted feet movements, to induce distinctive event-related (desynchronization (ERD/S patterns in the EEG. Offline classification accuracies above chance level were reached in all three tasks (i.e. attempted feet, sport, and navigation, with motor tasks yielding significant (p<0.05 results more often than navigation (sport: 10 out of 18 sessions; attempted feet: 7 out of 14 sessions; navigation: 4 out of 12 sessions. The passive feet movements, evaluated in one patient, yielded mixed results: whereas time-frequency analysis revealed task-related EEG changes over neurophysiological plausible cortical areas, the classification results were not significant enough (p<0.05 to setup an initial classifier for the detection of attempted movements. Concluding, the results presented in this study are consistent with the current state of the art in similar studies, to which we contributed by comparing different types of mental tasks, notably complex motor imagery and attempted feet movements, within patients. Furthermore, we explored new venues, such as an evaluation of passive feet movement as a mean of an initial classifier setup, and rapid delivery of biased feedback.

Intelligence related differences in EEG-bandpower.

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Doppelmayr, Michael; Klimesch, W; Sauseng, P; Hödlmoser, K; Stadler, W; Hanslmayr, S

2005-06-24

Several studies on the relationship between event-related desynchronization/synchronization (ERD/ERS) and cognitive performance revealed contradictory results particularly for the alpha band. Studies from our laboratory have shown that good performers show a larger upper alpha ERD (interpreted in terms of larger cortical activation) than bad performers. In contrast, other researchers found evidence for the neural efficiency hypothesis, which states that more intelligent subjects exhibit a smaller extent of cortical activation, which is assumed to be reflected by a smaller upper alpha ERD. Here we address the question whether these divergent results may be due to differences in general task difficulty. Using a modified version of the RAVEN, individually divided into easy and difficult tasks, a group of average and a group of highly intelligent subjects (IQ- and IQ+) have been investigated. While in the theta frequency IQ+ subjects generally exhibited a significantly stronger activation, we found a significant interaction of task difficulty and IQ group in the upper alpha band, indicating both, a weaker activation for the high IQ group during the easy tasks, and a significant increase from easy to difficult tasks for IQ+ only.

Detection of braking intention in diverse situations during simulated driving based on EEG feature combination.

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Kim, Il-Hwa; Kim, Jeong-Woo; Haufe, Stefan; Lee, Seong-Whan

2015-02-01

We developed a simulated driving environment for studying neural correlates of emergency braking in diversified driving situations. We further investigated to what extent these neural correlates can be used to detect a participant's braking intention prior to the behavioral response. We measured electroencephalographic (EEG) and electromyographic signals during simulated driving. Fifteen participants drove a virtual vehicle and were exposed to several kinds of traffic situations in a simulator system, while EEG signals were measured. After that, we extracted characteristic features to categorize whether the driver intended to brake or not. Our system shows excellent detection performance in a broad range of possible emergency situations. In particular, we were able to distinguish three different kinds of emergency situations (sudden stop of a preceding vehicle, sudden cutting-in of a vehicle from the side and unexpected appearance of a pedestrian) from non-emergency (soft) braking situations, as well as from situations in which no braking was required, but the sensory stimulation was similar to stimulations inducing an emergency situation (e.g., the sudden stop of a vehicle on a neighboring lane). We proposed a novel feature combination comprising movement-related potentials such as the readiness potential, event-related desynchronization features besides the event-related potentials (ERP) features used in a previous study. The performance of predicting braking intention based on our proposed feature combination was superior compared to using only ERP features. Our study suggests that emergency situations are characterized by specific neural patterns of sensory perception and processing, as well as motor preparation and execution, which can be utilized by neurotechnology based braking assistance systems.

Detection of braking intention in diverse situations during simulated driving based on EEG feature combination

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Kim, Il-Hwa; Kim, Jeong-Woo; Haufe, Stefan; Lee, Seong-Whan

2015-02-01

Objective. We developed a simulated driving environment for studying neural correlates of emergency braking in diversified driving situations. We further investigated to what extent these neural correlates can be used to detect a participant's braking intention prior to the behavioral response. Approach. We measured electroencephalographic (EEG) and electromyographic signals during simulated driving. Fifteen participants drove a virtual vehicle and were exposed to several kinds of traffic situations in a simulator system, while EEG signals were measured. After that, we extracted characteristic features to categorize whether the driver intended to brake or not. Main results. Our system shows excellent detection performance in a broad range of possible emergency situations. In particular, we were able to distinguish three different kinds of emergency situations (sudden stop of a preceding vehicle, sudden cutting-in of a vehicle from the side and unexpected appearance of a pedestrian) from non-emergency (soft) braking situations, as well as from situations in which no braking was required, but the sensory stimulation was similar to stimulations inducing an emergency situation (e.g., the sudden stop of a vehicle on a neighboring lane). Significance. We proposed a novel feature combination comprising movement-related potentials such as the readiness potential, event-related desynchronization features besides the event-related potentials (ERP) features used in a previous study. The performance of predicting braking intention based on our proposed feature combination was superior compared to using only ERP features. Our study suggests that emergency situations are characterized by specific neural patterns of sensory perception and processing, as well as motor preparation and execution, which can be utilized by neurotechnology based braking assistance systems.

Temporal dynamics of sensorimotor integration in speech perception and production: Independent component analysis of EEG data

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David eJenson

2014-07-01

Full Text Available Activity in premotor and sensorimotor cortices is found in speech production and some perception tasks. Yet, how sensorimotor integration supports these functions is unclear due to a lack of data examining the timing of activity from these regions. Beta (~20Hz and alpha (~10Hz spectral power within the EEG µ rhythm are considered indices of motor and somatosensory activity, respectively. In the current study, perception conditions required discrimination (same/different of syllables pairs (/ba/ and /da/ in quiet and noisy conditions. Production conditions required covert and overt syllable productions and overt word production. Independent component analysis was performed on EEG data obtained during these conditions to 1 identify clusters of µ components common to all conditions and 2 examine real-time event-related spectral perturbations (ERSP within alpha and beta bands. 17 and 15 out of 20 participants produced left and right µ-components, respectively, localized to precentral gyri. Discrimination conditions were characterized by significant (pFDR<.05 early alpha event-related synchronization (ERS prior to and during stimulus presentation and later alpha event-related desynchronization (ERD following stimulus offset. Beta ERD began early and gained strength across time. Differences were found between quiet and noisy discrimination conditions. Both overt syllable and word productions yielded similar alpha/beta ERD that began prior to production and was strongest during muscle activity. Findings during covert production were weaker than during overt production. One explanation for these findings is that µ-beta ERD indexes early predictive coding (e.g., internal modeling and/or overt and covert attentional / motor processes. µ-alpha ERS may index inhibitory input to the premotor cortex from sensory regions prior to and during discrimination, while µ-alpha ERD may index re-afferent sensory feedback during speech rehearsal and production.

Quantitative analysis of sleep EEG microstructure in the time-frequency domain.

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De Carli, Fabrizio; Nobili, Lino; Beelke, Manolo; Watanabe, Tsuyoshi; Smerieri, Arianna; Parrino, Liborio; Terzano, Mario Giovanni; Ferrillo, Franco

2004-06-30

A number of phasic events influence sleep quality and sleep macrostructure. The detection of arousals and the analysis of cyclic alternating patterns (CAP) support the evaluation of sleep fragmentation and instability. Sixteen polygraphic overnight recordings were visually inspected for conventional Rechtscaffen and Kales scoring, while arousals were detected following the criteria of the American Sleep Disorders Association (ASDA). Three electroencephalograph (EEG) segments were associated to each event, corresponding to background activity, pre-arousal period and arousal. The study was supplemented by the analysis of time-frequency distribution of EEG within each subtype of phase A in the CAP. The arousals were characterized by the increase of alpha and beta power with regard to background. Within NREM sleep most of the arousals were preceded by a transient increase of delta power. The time-frequency evolution of the phase A of the CAP sequence showed a strong prevalence of delta activity during the whole A1, but high amplitude delta waves were found also in the first 2/3 s of A2 and A3, followed by desynchronization. Our results underline the strict relationship between the ASDA arousals, and the subtype A2 and A3 within the CAP: in both the association between a short sequence of transient slow waves and the successive increase of frequency and decrease of amplitude characterizes the arousal response.

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

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

2017-09-01

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

Lateralization patterns of covert but not overt movements change with age: An EEG neurofeedback study.

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Zich, Catharina; Debener, Stefan; De Vos, Maarten; Frerichs, Stella; Maurer, Stefanie; Kranczioch, Cornelia

2015-08-01

The mental practice of movements has been suggested as a promising add-on therapy to facilitate motor recovery after stroke. In the case of mentally practised movements, electroencephalogram (EEG) can be utilized to provide feedback about an otherwise covert act. The main target group for such an intervention are elderly patients, though research so far is largely focused on young populations (study therefore aimed to examine the influence of age on the neural correlates of covert movements (CMs) in a real-time EEG neurofeedback framework. CM-induced event-related desynchronization (ERD) was studied in young (mean age: 23.6 years) and elderly (mean age: 62.7 years) healthy adults. Participants performed covert and overt hand movements. CMs were based on kinesthetic motor imagery (MI) or quasi-movements (QM). Based on previous studies investigating QM in the mu frequency range (8-13Hz) QM were expected to result in more lateralized ERD% patterns and accordingly higher classification accuracies. Independent of CM strategy the elderly were characterized by a significantly reduced lateralization of ERD%, due to stronger ipsilateral ERD%, and in consequence, reduced classification accuracies. QM were generally perceived as more vivid, but no differences were evident between MI and QM in ERD% or classification accuracies. EEG feedback enhanced task-related activity independently of strategy and age. ERD% measures of overt and covert movements were strongly related in young adults, whereas in the elderly ERD% lateralization is dissociated. In summary, we did not find evidence in support of more pronounced ERD% lateralization patterns in QM. Our finding of a less lateralized activation pattern in the elderly is in accordance to previous research and with the idea that compensatory processes help to overcome neurodegenerative changes related to normal ageing. Importantly, it indicates that EEG neurofeedback studies should place more emphasis on the age of the potential end

Synchronization and desynchronization in the Olami-Feder-Christensen earthquake model and potential implications for real seismicity

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S. Hergarten

2011-09-01

Full Text Available The Olami-Feder-Christensen model is probably the most studied model in the context of self-organized criticality and reproduces several statistical properties of real earthquakes. We investigate and explain synchronization and desynchronization of earthquakes in this model in the nonconservative regime and its relevance for the power-law distribution of the event sizes (Gutenberg-Richter law and for temporal clustering of earthquakes. The power-law distribution emerges from synchronization, and its scaling exponent can be derived as τ = 1.775 from the scaling properties of the rupture areas' perimeter. In contrast, the occurrence of foreshocks and aftershocks according to Omori's law is closely related to desynchronization. This mechanism of foreshock and aftershock generation differs strongly from the widespread idea of spontaneous triggering and gives an idea why some even large earthquakes are not preceded by any foreshocks in nature.

High Definition Transcranial Direct Current Stimulation Induces Both Acute and Persistent Changes in Broadband Cortical Synchronization: a Simultaneous tDCS-EEG Study

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Roy, Abhrajeet; Baxter, Bryan

2014-01-01

The goal of this study was to develop methods for simultaneously acquiring electrophysiological data during high definition transcranial direct current stimulation (tDCS) using high resolution electroencephalography (EEG). Previous studies have pointed to the after effects of tDCS on both motor and cognitive performance, and there appears to be potential for using tDCS in a variety of clinical applications. However, little is known about the real-time effects of tDCS on rhythmic cortical activity in humans due to the technical challenges of simultaneously obtaining electrophysiological data during ongoing stimulation. Furthermore, the mechanisms of action of tDCS in humans are not well understood. We have conducted a simultaneous tDCS-EEG study in a group of healthy human subjects. Significant acute and persistent changes in spontaneous neural activity and event related synchronization (ERS) were observed during and after the application of high definition tDCS over the left sensorimotor cortex. Both anodal and cathodal stimulation resulted in acute global changes in broadband cortical activity which were significantly different than the changes observed in response to sham stimulation. For the group of 8 subjects studied, broadband individual changes in spontaneous activity during stimulation were apparent both locally and globally. In addition, we found that high definition tDCS of the left sensorimotor cortex can induce significant ipsilateral and contralateral changes in event related desynchronization (ERD) and ERS during motor imagination following the end of the stimulation period. Overall, our results demonstrate the feasibility of acquiring high resolution EEG during high definition tDCS and provide evidence that tDCS in humans directly modulates rhythmic cortical synchronization during and after its administration. PMID:24956615

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

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

2014-08-01

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

Desynchronizing electrical and sensory coordinated reset neuromodulation

OpenAIRE

Popovych, Oleksandr V.; Tass, Peter A.

2012-01-01

Coordinated reset (CR) stimulation is a desynchronizing stimulation technique based on timely coordinated phase resets of sub-populations of a synchronized neuronal ensemble. It has initially been computationally developed for electrical deep brain stimulation (DBS), to enable an effective desynchronization and unlearning of pathological synchrony and connectivity (anti-kindling). Here we computationally show for ensembles of spiking and bursting model neurons interacting via excitatory and i...

Desynchronizing Electrical and Sensory Coordinated Reset Neuromodulation

OpenAIRE

Oleksandr V. Popovych; Peter A. Tass; Peter A. Tass

2012-01-01

Coordinated reset (CR) stimulation is a desynchronizing stimulation technique based on timely coordinated phase resets of sub-populations of a synchronized neuronal ensemble. It has initially been computationally developed for electrical deep brain stimulation (DBS),to enable an effective desynchronization and unlearning of pathological synchrony and connectivity (anti-kindling). Here we computationally show for ensembles of spiking and bursting model neurons interacting via excitatory and in...

Different event-related patterns of gamma-band power in brain waves of fast- and slow-reacting subjects.

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Jokeit, H; Makeig, S

1994-01-01

Fast- and slow-reacting subjects exhibit different patterns of gamma-band electroencephalogram (EEG) activity when responding as quickly as possible to auditory stimuli. This result appears to confirm long-standing speculations of Wundt that fast- and slow-reacting subjects produce speeded reactions in different ways and demonstrates that analysis of event-related changes in the amplitude of EEG activity recorded from the human scalp can reveal information about event-related brain processes unavailable using event-related potential measures. Time-varying spectral power in a selected (35- to 43-Hz) gamma frequency band was averaged across trials in two experimental conditions: passive listening and speeded reacting to binaural clicks, forming 40-Hz event-related spectral responses. Factor analysis of between-subject event-related spectral response differences split subjects into two near-equal groups composed of faster- and slower-reacting subjects. In faster-reacting subjects, 40-Hz power peaked near 200 ms and 400 ms poststimulus in the react condition, whereas in slower-reacting subjects, 40-Hz power just before stimulus delivery was larger in the react condition. These group differences were preserved in separate averages of relatively long and short reaction-time epochs for each group. gamma-band (20-60 Hz)-filtered event-related potential response averages did not differ between the two groups or conditions. Because of this and because gamma-band power in the auditory event-related potential is small compared with the EEG, the observed event-related spectral response features must represent gamma-band EEG activity reliably induced by, but not phase-locked to, experimental stimuli or events. PMID:8022783

Brain wave correlates of attentional states: Event related potentials and quantitative EEG analysis during performance of cognitive and perceptual tasks

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Freeman, Frederick G.

1993-01-01

The increased use of automation in the cockpits of commercial planes has dramatically decreased the workload requirements of pilots, enabling them to function more efficiently and with a higher degree of safety. Unfortunately, advances in technology have led to an unexpected problem: the decreased demands on pilots have increased the probability of inducing 'hazardous states of awareness.' A hazardous state of awareness is defined as a decreased level of alertness or arousal which makes an individual less capable of reacting to unique or emergency types of situations. These states tend to be induced when an individual is not actively processing information. Under such conditions a person is likely to let his/her mind wander, either to internal states or to irrelevant external conditions. As a result, they are less capable of reacting quickly to emergency situations. Since emergencies are relatively rare, and since the high automated cockpit requires progressively decreasing levels of engagement, the probability of being seduced into a lowered state of awareness is increasing. This further decreases the readiness of the pilot to react to unique circumstances such as system failures. The HEM Lab at NASA-Langley Research Center has been studying how these states of awareness are induced and what the physiological correlates of these different states are. Specifically, they have been interested in studying electroencephalographic (EEG) measures of different states of alertness to determine if such states can be identified and, hopefully, avoided. The project worked on this summer involved analyzing the EEG and the event related potentials (ERP) data collected while subjects performed under two conditions. Each condition required subjects to perform a relatively boring vigilance task. The purpose of using these tasks was to induce a decreased state of awareness while still requiring the subject to process information. Each task involved identifying an infrequently

Desynchronization of Theta-Phase Gamma-Amplitude Coupling during a Mental Arithmetic Task in Children with Attention Deficit/Hyperactivity Disorder.

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Jun Won Kim

Full Text Available Theta-phase gamma-amplitude coupling (TGC measurement has recently received attention as a feasible method of assessing brain functions such as neuronal interactions. The purpose of this electroencephalographic (EEG study is to understand the mechanisms underlying the deficits in attentional control in children with attention deficit/hyperactivity disorder (ADHD by comparing the power spectra and TGC at rest and during a mental arithmetic task.Nineteen-channel EEGs were recorded from 97 volunteers (including 53 subjects with ADHD from a camp for hyperactive children under two conditions (rest and task performance. The EEG power spectra and the TGC data were analyzed. Correlation analyses between the Intermediate Visual and Auditory (IVA continuous performance test (CPT scores and EEG parameters were performed.No significant difference in the power spectra was detected between the groups at rest and during task performance. However, TGC was reduced during the arithmetic task in the ADHD group compared with the normal group (F = 16.70, p < 0.001. The TGC values positively correlated with the IVA CPT scores but negatively correlated with theta power.Our findings suggest that desynchronization of TGC occurred during the arithmetic task in ADHD children. TGC in ADHD children is expected to serve as a promising neurophysiological marker of network deactivation during attention-demanding tasks.

Desynchronizing electrical and sensory coordinated reset neuromodulation.

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Popovych, Oleksandr V; Tass, Peter A

2012-01-01

Coordinated reset (CR) stimulation is a desynchronizing stimulation technique based on timely coordinated phase resets of sub-populations of a synchronized neuronal ensemble. It has initially been computationally developed for electrical deep brain stimulation (DBS), to enable an effective desynchronization and unlearning of pathological synchrony and connectivity (anti-kindling). Here we computationally show for ensembles of spiking and bursting model neurons interacting via excitatory and inhibitory adaptive synapses that a phase reset of neuronal populations as well as a desynchronization and an anti-kindling can robustly be achieved by direct electrical stimulation or indirect (synaptically-mediated) excitatory and inhibitory stimulation. Our findings are relevant for DBS as well as for sensory stimulation in neurological disorders characterized by pathological neuronal synchrony. Based on the obtained results, we may expect that the local effects in the vicinity of a depth electrode (realized by direct stimulation of the neurons' somata or stimulation of axon terminals) and the non-local CR effects (realized by stimulation of excitatory or inhibitory efferent fibers) of deep brain CR neuromodulation may be similar or even identical. Furthermore, our results indicate that an effective desynchronization and anti-kindling can even be achieved by non-invasive, sensory CR neuromodulation. We discuss the concept of sensory CR neuromodulation in the context of neurological disorders.

Desynchronizing Electrical and Sensory Coordinated Reset Neuromodulation

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Oleksandr V. Popovych

2012-03-01

Full Text Available Coordinated reset (CR stimulation is a desynchronizing stimulation technique based on timely coordinated phase resets of sub-populations of a synchronized neuronal ensemble. It has initially been computationally developed for electrical deep brain stimulation (DBS,to enable an effective desynchronization and unlearning of pathological synchrony and connectivity (anti-kindling. Here we computationally show for ensembles of spiking and bursting model neurons interacting via excitatory and inhibitory adaptive synapses that a phase reset of neuronal populations as well as a desynchronization and an anti-kindling can robustly be achieved by direct electrical stimulation or indirect (synaptically-mediated excitatory and inhibitory stimulation.Our findings are relevant for DBS as well as for sensory stimulation in neurological disorders characterized by pathological neuronalsynchrony. Based on the obtained results, we may expect that the local effects in the vicinity of a depth electrode (realized by direct stimulation of the neurons' somata or stimulation of axon terminals and the non-local CR effects (realized by stimulation of excitatory or inhibitory efferent fibers of deep brain CR neuromodulation may be similar or even identical. Furthermore, ourresults indicate that an effective desynchronization and anti-kindlingcan even be achieved by non-invasive, sensory CR neuromodulation. We discuss the concept of sensory CR neuromodulation in the context of neurological disorders.

Classification of Single-Trial Auditory Events Using Dry-Wireless EEG During Real and Motion Simulated Flight

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Daniel eCallan

2015-02-01

Full Text Available Application of neuro-augmentation technology based on dry-wireless EEG may be considerably beneficial for aviation and space operations because of the inherent dangers involved. In this study we evaluate classification performance of perceptual events using a dry-wireless EEG system during motion platform based flight simulation and actual flight in an open cockpit biplane to determine if the system can be used in the presence of considerable environmental and physiological artifacts. A passive task involving 200 random auditory presentations of a chirp sound was used for evaluation. The advantage of this auditory task is that it does not interfere with the perceptual motor processes involved with piloting the plane. Classification was based on identifying the presentation of a chirp sound versus silent periods. Evaluation of Independent component analysis and Kalman filtering to enhance classification performance by extracting brain activity related to the auditory event from other non-task related brain activity and artifacts was assessed. The results of permutation testing revealed that single trial classification of presence or absence of an auditory event was significantly above chance for all conditions on a novel test set. The best performance could be achieved with both ICA and Kalman filtering relative to no processing: Platform Off (83.4% vs 78.3%, Platform On (73.1% vs 71.6%, Biplane Engine Off (81.1% vs 77.4%, and Biplane Engine On (79.2% vs 66.1%. This experiment demonstrates that dry-wireless EEG can be used in environments with considerable vibration, wind, acoustic noise, and physiological artifacts and achieve good single trial classification performance that is necessary for future successful application of neuro-augmentation technology based on brain-machine interfaces.

Analysis of EEG Related Saccadic Eye Movement

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

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

The Effects of Fluency Enhancing Conditions on Sensorimotor Control of Speech in Typically Fluent Speakers: An EEG Mu Rhythm Study

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Tiffani Kittilstved

2018-04-01

Full Text Available Objective: To determine whether changes in sensorimotor control resulting from speaking conditions that induce fluency in people who stutter (PWS can be measured using electroencephalographic (EEG mu rhythms in neurotypical speakers.Methods: Non-stuttering (NS adults spoke in one control condition (solo speaking and four experimental conditions (choral speech, delayed auditory feedback (DAF, prolonged speech and pseudostuttering. Independent component analysis (ICA was used to identify sensorimotor μ components from EEG recordings. Time-frequency analyses measured μ-alpha (8–13 Hz and μ-beta (15–25 Hz event-related synchronization (ERS and desynchronization (ERD during each speech condition.Results: 19/24 participants contributed μ components. Relative to the control condition, the choral and DAF conditions elicited increases in μ-alpha ERD in the right hemisphere. In the pseudostuttering condition, increases in μ-beta ERD were observed in the left hemisphere. No differences were present between the prolonged speech and control conditions.Conclusions: Differences observed in the experimental conditions are thought to reflect sensorimotor control changes. Increases in right hemisphere μ-alpha ERD likely reflect increased reliance on auditory information, including auditory feedback, during the choral and DAF conditions. In the left hemisphere, increases in μ-beta ERD during pseudostuttering may have resulted from the different movement characteristics of this task compared with the solo speaking task. Relationships to findings in stuttering are discussed.Significance: Changes in sensorimotor control related feedforward and feedback control in fluency-enhancing speech manipulations can be measured using time-frequency decompositions of EEG μ rhythms in neurotypical speakers. This quiet, non-invasive, and temporally sensitive technique may be applied to learn more about normal sensorimotor control and fluency enhancement in PWS.

Multichannel linear descriptors analysis for event-related EEG of vascular dementia patients during visual detection task.

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Lou, Wutao; Xu, Jin; Sheng, Hengsong; Zhao, Songzhen

2011-11-01

Multichannel EEG recorded in a task condition could contain more information about cognition. However, that has not been widely investigated in the vascular-dementia (VaD)- related studies. The purpose of this study was to explore the differences of brain functional states between VaD patients and normal controls while performing a detection task. Three multichannel linear descriptors, i.e. spatial complexity (Ω), field strength (Σ) and frequency of field changes (Φ), were applied to analyse four frequency bands (delta, theta, alpha and beta) of multichannel event-related EEG signals for 12 VaD patients (mean age ± SD: 69.25 ± 10.56 years ; MMSE score ± SD: 22.58 ± 4.42) and 12 age-matched healthy subjects (mean age ± SD: 67.17 ± 5.97 years ; MMSE score ± SD: 29.08 ± 0.9). The correlations between the three measures and MMSE scores were also analysed. VaD patients showed a significant higher Ω value in the delta (p = 0.013) and theta (p = 0.021) frequency bands, a lower Σ value (p = 0.011) and a higher Φ (p = 0.008) value in the delta frequency band compared with normal controls. The MMSE scores were negatively correlated with the Ω (r = -0.52, p = 0.01) and Φ (r = -0.47, p = 0.02) values in the delta frequency band. The results indicated the VaD patients presented a reduction of synchronization in the slow frequency band during target detection, and suggested more neurons might be activated in VaD patients compared with normal controls. The Ω and Φ measures in the delta frequency band might be used to evaluate the degree of cognitive dysfunction. The multichannel linear descriptors are promising measures to reveal the differences in brain functions between VaD patients and normal subjects, and could potentially be used to evaluate the degree of cognitive dysfunction in VaD patients. Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

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

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Bleichner, Martin G.; Debener, Stefan

2017-01-01

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

Computationally Developed Sham Stimulation Protocol for Multichannel Desynchronizing Stimulation

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Magteld Zeitler

2018-05-01

Full Text Available A characteristic pattern of abnormal brain activity is abnormally strong neuronal synchronization, as found in several brain disorders, such as tinnitus, Parkinson's disease, and epilepsy. As observed in several diseases, different therapeutic interventions may induce a placebo effect that may be strong and hinder reliable clinical evaluations. Hence, to distinguish between specific, neuromodulation-induced effects and unspecific, placebo effects, it is important to mimic the therapeutic procedure as precisely as possibly, thereby providing controls that actually lack specific effects. Coordinated Reset (CR stimulation has been developed to specifically counteract abnormally strong synchronization by desynchronization. CR is a spatio-temporally patterned multichannel stimulation which reduces the extent of coincident neuronal activity and aims at an anti-kindling, i.e., an unlearning of both synaptic connectivity and neuronal synchrony. Apart from acute desynchronizing effects, CR may cause sustained, long-lasting desynchronizing effects, as already demonstrated in pre-clinical and clinical proof of concept studies. In this computational study, we set out to computationally develop a sham stimulation protocol for multichannel desynchronizing stimulation. To this end, we compare acute effects and long-lasting effects of six different spatio-temporally patterned stimulation protocols, including three variants of CR, using a no-stimulation condition as additional control. This is to provide an inventory of different stimulation algorithms with similar fundamental stimulation parameters (e.g., mean stimulation rates but qualitatively different acute and/or long-lasting effects. Stimulation protocols sharing basic parameters, but inducing nevertheless completely different or even no acute effects and/or after-effects, might serve as controls to validate the specific effects of particular desynchronizing protocols such as CR. In particular, based on

MEG event-related desynchronization and synchronization deficits during basic somatosensory processing in individuals with ADHD

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Wang Frank

2008-02-01

Full Text Available Abstract Background Attention-Deficit/Hyperactivity Disorder (ADHD is a prevalent, complex disorder which is characterized by symptoms of inattention, hyperactivity, and impulsivity. Convergent evidence from neurobiological studies of ADHD identifies dysfunction in fronto-striatal-cerebellar circuitry as the source of behavioural deficits. Recent studies have shown that regions governing basic sensory processing, such as the somatosensory cortex, show abnormalities in those with ADHD suggesting that these processes may also be compromised. Methods We used event-related magnetoencephalography (MEG to examine patterns of cortical rhythms in the primary (SI and secondary (SII somatosensory cortices in response to median nerve stimulation, in 9 adults with ADHD and 10 healthy controls. Stimuli were brief (0.2 ms non-painful electrical pulses presented to the median nerve in two counterbalanced conditions: unpredictable and predictable stimulus presentation. We measured changes in strength, synchronicity, and frequency of cortical rhythms. Results Healthy comparison group showed strong event-related desynchrony and synchrony in SI and SII. By contrast, those with ADHD showed significantly weaker event-related desynchrony and event-related synchrony in the alpha (8–12 Hz and beta (15–30 Hz bands, respectively. This was most striking during random presentation of median nerve stimulation. Adults with ADHD showed significantly shorter duration of beta rebound in both SI and SII except for when the onset of the stimulus event could be predicted. In this case, the rhythmicity of SI (but not SII in the ADHD group did not differ from that of controls. Conclusion Our findings suggest that somatosensory processing is altered in individuals with ADHD. MEG constitutes a promising approach to profiling patterns of neural activity during the processing of sensory input (e.g., detection of a tactile stimulus, stimulus predictability and facilitating our

Task-and phase-related changes in cortico-muscular coherence

DEFF Research Database (Denmark)

Masakado, Yoshihisa; Nielsen, Jens Bo

2008-01-01

-level tonic dorsiflexion. In all subjects coherence disappeared during the ramp phase for both isometric and quasi-isotonic contraction. Coherence at other frequencies was also not observed in any of the subjects during the ramp phase. During the hold phase at the stronger level of contraction coherence...... reappeared quickly and had the same size as at the low level of contraction. However, a significantly larger level of coherence was found during quasi-isotonic than during the isometric contraction. This demonstrates that cortico-muscular coherence in the 15-35 Hz frequency band is phase- and task......-related. The decrease in 15-35 Hz coherence during the ramp phase may be related to event-related desynchronization of EEG activity. The larger level of coherence during quasi-isotonic contraction may reflect a higher demand of precise control of the joint position. It may also reflect a greater need for binding...

Unsupervised Event Characterization and Detection in Multichannel Signals: An EEG application

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Angel Mur

2016-04-01

Full Text Available In this paper, we propose a new unsupervised method to automatically characterize and detect events in multichannel signals. This method is used to identify artifacts in electroencephalogram (EEG recordings of brain activity. The proposed algorithm has been evaluated and compared with a supervised method. To this end an example of the performance of the algorithm to detect artifacts is shown. The results show that although both methods obtain similar classification, the proposed method allows detecting events without training data and can also be applied in signals whose events are unknown a priori. Furthermore, the proposed method provides an optimal window whereby an optimal detection and characterization of events is found. The detection of events can be applied in real-time.

Trial latencies estimation of event-related potentials in EEG by means of genetic algorithms

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Da Pelo, P.; De Tommaso, M.; Monaco, A.; Stramaglia, S.; Bellotti, R.; Tangaro, S.

2018-04-01

Objective. Event-related potentials (ERPs) are usually obtained by averaging thus neglecting the trial-to-trial latency variability in cognitive electroencephalography (EEG) responses. As a consequence the shape and the peak amplitude of the averaged ERP are smeared and reduced, respectively, when the single-trial latencies show a relevant variability. To date, the majority of the methodologies for single-trial latencies inference are iterative schemes providing suboptimal solutions, the most commonly used being the Woody’s algorithm. Approach. In this study, a global approach is developed by introducing a fitness function whose global maximum corresponds to the set of latencies which renders the trial signals most aligned as possible. A suitable genetic algorithm has been implemented to solve the optimization problem, characterized by new genetic operators tailored to the present problem. Main results. The results, on simulated trials, showed that the proposed algorithm performs better than Woody’s algorithm in all conditions, at the cost of an increased computational complexity (justified by the improved quality of the solution). Application of the proposed approach on real data trials, resulted in an increased correlation between latencies and reaction times w.r.t. the output from RIDE method. Significance. The above mentioned results on simulated and real data indicate that the proposed method, providing a better estimate of single-trial latencies, will open the way to more accurate study of neural responses as well as to the issue of relating the variability of latencies to the proper cognitive and behavioural correlates.

Neural Markers of Performance States in an Olympic Athlete: An EEG Case Study in Air-Pistol Shooting

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Selenia di Fronso, Claudio Robazza, Edson Filho, Laura Bortoli, Silvia Comani, Maurizio Bertollo

2016-06-01

Full Text Available This study focused on identifying the neural markers underlying optimal and suboptimal performance experiences of an elite air-pistol shooter, based on the tenets of the multi-action plan (MAP model. According to the MAP model’s assumptions, skilled athletes’ cortical patterns are expected to differ among optimal/automatic (Type 1, optimal/controlled (Type 2, suboptimal/controlled (Type 3, and suboptimal/automatic (Type 4 performance experiences. We collected performance (target pistol shots, cognitive-affective (perceived control, accuracy, and hedonic tone, and cortical activity data (32-channel EEG of an elite shooter. Idiosyncratic descriptive analyses revealed differences in perceived accuracy in regard to optimal and suboptimal performance states. Event-Related Desynchronization/Synchronization analysis supported the notion that optimal-automatic performance experiences (Type 1 were characterized by a global synchronization of cortical arousal associated with the shooting task, whereas suboptimal controlled states (Type 3 were underpinned by high cortical activity levels in the attentional brain network. Results are addressed in light of the neural efficiency hypothesis and reinvestment theory. Perceptual training recommendations aimed at restoring optimal performance levels are discussed.

Working memory load related modulations of the oscillatory brain activity. N-back ERD/ERS study

International Nuclear Information System (INIS)

Nakao, Yoshiaki; Tamura, Toshiyo; Kodabashi, Atsushi; Fujimoto, Toshiro; Yarita, Masaru

2011-01-01

In recent cognitive neuroscience, a lot of studies of the human working memory were examined, and electroencephalography (EEG) measurements during n-back task were often used. However, they were almost studied by event related potentials (ERP) analysis. In the ERP study, time-locked components can be elicited, but non time-locked components such as the modulated brain oscillatory activity might be lost by an averaging procedure. To elucidate the contribution of the modulations of the brain oscillatory activity to the human working memory, we examined event related desynchronization (ERD)/event related synchronization (ERS) analysis on the source waveforms during n-back task. Source waveforms were calculated from a source model which was constructed with the sources seeded from fMRI meta-analysis of n-back task and additional sources in the orbitofrontal cortex and the visual cortex estimated with P100 and P360 components in the n-back ERP. Our results suggested the network which included the prefrontal cortex and the parietal lobe had a contribution to human working memory process, and it was mediated by theta oscillatory activity. (author)

Metabolic Desynchronization in Critical Conditions: Experimental Study

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G. V. Livanov

2006-01-01

Full Text Available Objective. To conduct an experimental study of the impact of the time of administration of succinic acid preparations on central nervous system (CNS function and gas exchange while simulating metabolic therapy for severe poisoning by ethyl alcohol. The study was performed on 74 male albino rats weighing 140—180 g. Acute severe and very severe intoxication was simulated, by intraabdominally administering 30% ethanol to the rats. Cytoflavin was used to simulate experimental therapy. The rate of gas exchange was estimated by the oxygen uptake determined by the closed chamber method in a Regnault apparatus (Germany. Spontaneous bioelectrical activity was recorded in the frontooccipital lead by the routine procedure. External pain stimulation and rhythmical photostimulation were employed to evaluate cerebral responsiveness. Heterodirectional EEG changes in the «early» and «late» administration of succinate were not followed by the similar alterations of gas exchange: oxygen consumption in both the «early» and «late» administration of succinate remained significantly lower than in the control animals. With the late administration of succinate to the animals with mixed (toxic and hypoxic coma, the so-called discrepancy between the noticeably increased energy production and brutally diminished metabolism occurred. It may be just the pathological mechanism that was the basis for higher mortality in the late succinate administration group. The findings and their analysis make it possible to advance a hypothesis that succinate may cause metabolic desynchronization if activation of metabolic processes takes place under severe tissue respiratory tissue depression. In these cases, there is a severe damage to tissue and chiefly the brain. This manifests itself as EEG epileptiform activity splashes preceding the animals’ death. Therefore, resuscitation aimed at restoring the transport of oxygen and its involvement in tissue energy processes should

EEG activation differences in the pre-motor cortex and supplementary motor area between normal individuals with high and low traits of autism.

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Puzzo, Ignazio; Cooper, Nicholas R; Vetter, Petra; Russo, Riccardo

2010-06-25

The human mirror neuron system (hMNS) is believed to provide a basic mechanism for social cognition. Event-related desynchronization (ERD) in alpha (8-12Hz) and low beta band (12-20Hz) over sensori-motor cortex has been suggested to index mirror neurons' activity. We tested whether autistic traits revealed by high and low scores on the Autistic Quotient (AQ) in the normal population are linked to variations in the electroencephalogram (EEG) over motor, pre-motor cortex and supplementary motor area (SMA) during action observation. Results revealed that in the low AQ group, the pre-motor cortex and SMA were more active during hand action than static hand observation whereas in the high AQ group the same areas were active both during static and hand action observation. In fact participants with high traits of autism showed greater low beta ERD while observing the static hand than those with low traits and this low beta ERD was not significantly different when they watched hand actions. Over primary motor cortex, the classical alpha and low beta ERD during hand actions relative to static hand observation was found across all participants. These findings suggest that the observation-execution matching system works differently according to the degree of autism traits in the normal population and that this is differentiated in terms of the EEG according to scalp site and bandwidth. Copyright 2010 Elsevier B.V. All rights reserved.

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

African Journals Online (AJOL)

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

The infant mirror neuron system studied with high density EEG.

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Nyström, Pär

2008-01-01

The mirror neuron system has been suggested to play a role in many social capabilities such as action understanding, imitation, language and empathy. These are all capabilities that develop during infancy and childhood, but the human mirror neuron system has been poorly studied using neurophysiological measures. This study measured the brain activity of 6-month-old infants and adults using a high-density EEG net with the aim of identifying mirror neuron activity. The subjects viewed both goal-directed movements and non-goal-directed movements. An independent component analysis was used to extract the sources of cognitive processes. The desynchronization of the mu rhythm in adults has been shown to be a marker for activation of the mirror neuron system and was used as a criterion to categorize independent components between subjects. The results showed significant mu desynchronization in the adult group and significantly higher ERP activation in both adults and 6-month-olds for the goal-directed action observation condition. This study demonstrate that infants as young as 6 months display mirror neuron activity and is the first to present a direct ERP measure of the mirror neuron system in infants.

Dynamic oscillatory signatures of central neuropathic pain in spinal cord injury.

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Vuckovic, Aleksandra; Hasan, Muhammad A; Fraser, Matthew; Conway, Bernard A; Nasseroleslami, Bahman; Allan, David B

2014-06-01

Central neuropathic pain (CNP) is believed to be accompanied by increased activation of the sensorimotor cortex. Our knowledge of this interaction is based mainly on functional magnetic resonance imaging studies, but there is little direct evidence on how these changes manifest in terms of dynamic neuronal activity. This study reports on the presence of transient electroencephalography (EEG)-based measures of brain activity during motor imagery in spinal cord-injured patients with CNP. We analyzed dynamic EEG responses during imaginary movements of arms and legs in 3 groups of 10 volunteers each, comprising able-bodied people, paraplegic patients with CNP (lower abdomen and legs), and paraplegic patients without CNP. Paraplegic patients with CNP had increased event-related desynchronization in the theta, alpha, and beta bands (16-24 Hz) during imagination of movement of both nonpainful (arms) and painful limbs (legs). Compared to patients with CNP, paraplegics with no pain showed a much reduced power in relaxed state and reduced event-related desynchronization during imagination of movement. Understanding these complex dynamic, frequency-specific activations in CNP in the absence of nociceptive stimuli could inform the design of interventional therapies for patients with CNP and possibly further understanding of the mechanisms involved. This study compares the EEG activity of spinal cord-injured patients with CNP to that of spinal cord-injured patients with no pain and also to that of able-bodied people. The study shows that the presence of CNP itself leads to frequency-specific EEG signatures that could be used to monitor CNP and inform neuromodulatory treatments of this type of pain. Copyright © 2014 American Pain Society. Published by Elsevier Inc. All rights reserved.

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

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

2014-06-01

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

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.

Predicting EEG complexity from sleep macro and microstructure

International Nuclear Information System (INIS)

Chouvarda, I; Maglaveras, N; Mendez, M O; Rosso, V; Parrino, L; Grassi, A; Terzano, M; Bianchi, A M; Cerutti, S

2011-01-01

This work investigates the relation between the complexity of electroencephalography (EEG) signal, as measured by fractal dimension (FD), and normal sleep structure in terms of its macrostructure and microstructure. Sleep features are defined, encoding sleep stage and cyclic alternating pattern (CAP) related information, both in short and long term. The relevance of each sleep feature to the EEG FD is investigated, and the most informative ones are depicted. In order to quantitatively assess the relation between sleep characteristics and EEG dynamics, a modeling approach is proposed which employs subsets of the sleep macrostructure and microstructure features as input variables and predicts EEG FD based on these features of sleep micro/macrostructure. Different sleep feature sets are investigated along with linear and nonlinear models. Findings suggest that the EEG FD time series is best predicted by a nonlinear support vector machine (SVM) model, employing both sleep stage/transitions and CAP features at different time scales depending on the EEG activation subtype. This combination of features suggests that short-term and long-term history of macro and micro sleep events interact in a complex manner toward generating the dynamics of sleep

Error-related potentials during continuous feedback: using EEG to detect errors of different type and severity

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Spüler, Martin; Niethammer, Christian

2015-01-01

When a person recognizes an error during a task, an error-related potential (ErrP) can be measured as response. It has been shown that ErrPs can be automatically detected in tasks with time-discrete feedback, which is widely applied in the field of Brain-Computer Interfaces (BCIs) for error correction or adaptation. However, there are only a few studies that concentrate on ErrPs during continuous feedback. With this study, we wanted to answer three different questions: (i) Can ErrPs be measured in electroencephalography (EEG) recordings during a task with continuous cursor control? (ii) Can ErrPs be classified using machine learning methods and is it possible to discriminate errors of different origins? (iii) Can we use EEG to detect the severity of an error? To answer these questions, we recorded EEG data from 10 subjects during a video game task and investigated two different types of error (execution error, due to inaccurate feedback; outcome error, due to not achieving the goal of an action). We analyzed the recorded data to show that during the same task, different kinds of error produce different ErrP waveforms and have a different spectral response. This allows us to detect and discriminate errors of different origin in an event-locked manner. By utilizing the error-related spectral response, we show that also a continuous, asynchronous detection of errors is possible. Although the detection of error severity based on EEG was one goal of this study, we did not find any significant influence of the severity on the EEG. PMID:25859204

Error-related potentials during continuous feedback: using EEG to detect errors of different type and severity

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Martin eSpüler

2015-03-01

Full Text Available When a person recognizes an error during a task, an error-related potential (ErrP can be measured as response. It has been shown that ErrPs can be automatically detected in tasks with time-discrete feedback, which is widely applied in the field of Brain-Computer Interfaces (BCIs for error correction or adaptation. However, there are only a few studies that concentrate on ErrPs during continuous feedback.With this study, we wanted to answer three different questions: (i Can ErrPs be measured in electroencephalography (EEG recordings during a task with continuous cursor control? (ii Can ErrPs be classified using machine learning methods and is it possible to discriminate errors of different origins? (iii Can we use EEG to detect the severity of an error? To answer these questions, we recorded EEG data from 10 subjects during a video game task and investigated two different types of error (execution error, due to inaccurate feedback; outcome error, due to not achieving the goal of an action. We analyzed the recorded data to show that during the same task, different kinds of error produce different ErrP waveforms and have a different spectral response. This allows us to detect and discriminate errors of different origin in an event-locked manner. By utilizing the error-related spectral response, we show that also a continuous, asynchronous detection of errors is possible.Although the detection of error severity based on EEG was one goal of this study, we did not find any significant influence of the severity on the EEG.

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

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Kristine Lynne Snyder

2015-12-01

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

Clinical usefulness and feasibility of time-frequency analysis of chemosensory event-related potentials.

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Huart, C; Rombaux, Ph; Hummel, T; Mouraux, A

2013-09-01

The clinical usefulness of olfactory event-related brain potentials (OERPs) to assess olfactory function is limited by the relatively low signal-to-noise ratio of the responses identified using conventional time-domain averaging. Recently, it was shown that time-frequency analysis of the obtained EEG signals can markedly improve the signal-to-noise ratio of OERPs in healthy controls, because it enhances both phase-locked and non phase-locked EEG responses. The aim of the present study was to investigate the clinical usefulness of this approach and evaluate its feasibility in a clinical setting. We retrospectively analysed EEG recordings obtained from 45 patients (15 anosmic, 15 hyposmic and 15 normos- mic). The responses to olfactory stimulation were analysed using conventional time-domain analysis and joint time-frequency analysis. The ability of the two methods to discriminate between anosmic, hyposmic and normosmic patients was assessed using a Receiver Operating Characteristic analysis. The discrimination performance of OERPs identified using conventional time-domain averaging was poor. In contrast, the discrimination performance of the EEG response identified in the time-frequency domain was relatively high. Furthermore, we found a significant correlation between the magnitude of this response and the psychophysical olfactory score. Time-frequency analysis of the EEG responses to olfactory stimulation could be used as an effective and reliable diagnostic tool for the objective clinical evaluation of olfactory function in patients.

Behavioral and EEG reactions in primary school-aged children to emotionally colored verbal stimuli with the condition of their own or forced choice

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Aiusheeva T. A.

2017-12-01

Full Text Available The aim of the study is to compare behavioral and EEG reactions of primary school-aged children during the recognition of syntactic errors in emotionally (positively or negatively colored sentences that appeal to the choice of the child differently. 20 children (mean age 9,0±0,3 years, 12 boys, 8 girls were examined. We found out that the children with a high quality of solving a linguistic task concentrate all their attention on finding an error in the sentences, and children with a low quality of solving a task demonstrate increased emotionality, possibly connected with their unsuccessfulness. The strongest EEG reactions in the ranges of alpha- and theta- rhythms were recorded in children with slow speed and bad quality of the solution of the task. The recognition of sentences with negative emotions took longer than sentences with positive emotions. The increase of emotions (synchronization in theta range during the recognition of negative sentences was provoked by the expectation of failure and “identification” with it. The children found the mistake better in the sentences with their own choice than in the sentences that describes the forced-choice situation. Desynchronization (i.e. decrease in the spectral power and synchronization (i.e. increase in spectral power was detected on the EEG in the alpha-rhythm range. Desynchronization was associated with the recognition of sentences describing the children’s own choice; synchronization was recorded when recognizing sentences describing the forced-choice situation.

The Voice of Anger: Oscillatory EEG Responses to Emotional Prosody.

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Renata Del Giudice

Full Text Available Emotionally relevant stimuli and in particular anger are, due to their evolutionary relevance, often processed automatically and able to modulate attention independent of conscious access. Here, we tested whether attention allocation is enhanced when auditory stimuli are uttered by an angry voice. We recorded EEG and presented healthy individuals with a passive condition where unfamiliar names as well as the subject's own name were spoken both with an angry and neutral prosody. The active condition instead, required participants to actively count one of the presented (angry names. Results revealed that in the passive condition the angry prosody only elicited slightly stronger delta synchronization as compared to a neutral voice. In the active condition the attended (angry target was related to enhanced delta/theta synchronization as well as alpha desynchronization suggesting enhanced allocation of attention and utilization of working memory resources. Altogether, the current results are in line with previous findings and highlight that attention orientation can be systematically related to specific oscillatory brain responses. Potential applications include assessment of non-communicative clinical groups such as post-comatose patients.

Bristle-sensors—low-cost flexible passive dry EEG electrodes for neurofeedback and BCI applications

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Grozea, Cristian; Voinescu, Catalin D.; Fazli, Siamac

2011-04-01

In this paper, we present a new, low-cost dry electrode for EEG that is made of flexible metal-coated polymer bristles. We examine various standard EEG paradigms, such as capturing occipital alpha rhythms, testing for event-related potentials in an auditory oddball paradigm and performing a sensory motor rhythm-based event-related (de-) synchronization paradigm to validate the performance of the novel electrodes in terms of signal quality. Our findings suggest that the dry electrodes that we developed result in high-quality EEG recordings and are thus suitable for a wide range of EEG studies and BCI applications. Furthermore, due to the flexibility of the novel electrodes, greater comfort is achieved in some subjects, this being essential for long-term use.

Locally optimal extracellular stimulation for chaotic desynchronization of neural populations.

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Wilson, Dan; Moehlis, Jeff

2014-10-01

We use optimal control theory to design a methodology to find locally optimal stimuli for desynchronization of a model of neurons with extracellular stimulation. This methodology yields stimuli which lead to positive Lyapunov exponents, and hence desynchronizes a neural population. We analyze this methodology in the presence of interneuron coupling to make predictions about the strength of stimulation required to overcome synchronizing effects of coupling. This methodology suggests a powerful alternative to pulsatile stimuli for deep brain stimulation as it uses less energy than pulsatile stimuli, and could eliminate the time consuming tuning process.

Expected reward modulates encoding-related theta activity before an event.

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Gruber, Matthias J; Watrous, Andrew J; Ekstrom, Arne D; Ranganath, Charan; Otten, Leun J

2013-01-01

Oscillatory brain activity in the theta frequency range (4-8 Hz) before the onset of an event has been shown to affect the likelihood of successfully encoding the event into memory. Recent work has also indicated that frontal theta activity might be modulated by reward, but it is not clear how reward expectancy, anticipatory theta activity, and memory formation might be related. Here, we used scalp electroencephalography (EEG) to assess the relationship between these factors. EEG was recorded from healthy adults while they memorized a series of words. Each word was preceded by a cue that indicated whether a high or low monetary reward would be earned if the word was successfully remembered in a later recognition test. Frontal theta power between the presentation of the reward cue and the onset of a word was predictive of later memory for the word, but only in the high reward condition. No theta differences were observed before word onset following low reward cues. The magnitude of prestimulus encoding-related theta activity in the high reward condition was correlated with the number of high reward words that were later confidently recognized. These findings provide strong evidence for a link between reward expectancy, theta activity, and memory encoding. Theta activity before event onset seems to be especially important for the encoding of motivationally significant stimuli. One possibility is that dopaminergic activity during reward anticipation mediates frontal theta activity related to memory. Copyright © 2012 Elsevier Inc. All rights reserved.

Cumulative latency advance underlies fast visual processing in desynchronized brain state.

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Wang, Xu-dong; Chen, Cheng; Zhang, Dinghong; Yao, Haishan

2014-01-07

Fast sensory processing is vital for the animal to efficiently respond to the changing environment. This is usually achieved when the animal is vigilant, as reflected by cortical desynchronization. However, the neural substrate for such fast processing remains unclear. Here, we report that neurons in rat primary visual cortex (V1) exhibited shorter response latency in the desynchronized state than in the synchronized state. In vivo whole-cell recording from the same V1 neurons undergoing the two states showed that both the resting and visually evoked conductances were higher in the desynchronized state. Such conductance increases of single V1 neurons shorten the response latency by elevating the membrane potential closer to the firing threshold and reducing the membrane time constant, but the effects only account for a small fraction of the observed latency advance. Simultaneous recordings in lateral geniculate nucleus (LGN) and V1 revealed that LGN neurons also exhibited latency advance, with a degree smaller than that of V1 neurons. Furthermore, latency advance in V1 increased across successive cortical layers. Thus, latency advance accumulates along various stages of the visual pathway, likely due to a global increase of membrane conductance in the desynchronized state. This cumulative effect may lead to a dramatic shortening of response latency for neurons in higher visual cortex and play a critical role in fast processing for vigilant animals.

Automated approach to detecting behavioral states using EEG-DABS

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Zachary B. Loris

2017-07-01

Full Text Available Electrocorticographic (ECoG signals represent cortical electrical dipoles generated by synchronous local field potentials that result from simultaneous firing of neurons at distinct frequencies (brain waves. Since different brain waves correlate to different behavioral states, ECoG signals presents a novel strategy to detect complex behaviors. We developed a program, EEG Detection Analysis for Behavioral States (EEG-DABS that advances Fast Fourier Transforms through ECoG signals time series, separating it into (user defined frequency bands and normalizes them to reduce variability. EEG-DABS determines events if segments of an experimental ECoG record have significantly different power bands than a selected control pattern of EEG. Events are identified at every epoch and frequency band and then are displayed as output graphs by the program. Certain patterns of events correspond to specific behaviors. Once a predetermined pattern was selected for a behavioral state, EEG-DABS correctly identified the desired behavioral event. The selection of frequency band combinations for detection of the behavior affects accuracy of the method. All instances of certain behaviors, such as freezing, were correctly identified from the event patterns generated with EEG-DABS. Detecting behaviors is typically achieved by visually discerning unique animal phenotypes, a process that is time consuming, unreliable, and subjective. EEG-DABS removes variability by using defined parameters of EEG/ECoG for a desired behavior over chronic recordings. EEG-DABS presents a simple and automated approach to quantify different behavioral states from ECoG signals.

A cognitive stressor for event-related potential studies: the Portland arithmetic stress task.

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Atchley, Rachel; Ellingson, Roger; Klee, Daniel; Memmott, Tabatha; Oken, Barry

2017-05-01

In this experiment, we developed and evaluated the Portland Arithmetic Stress Task (PAST) as a cognitive stressor to evaluate acute and sustained stress reactivity for event-related potential (ERP) studies. The PAST is a titrated arithmetic task adapted from the Montreal Imaging Stress Task (MIST), with added experimental control over presentation parameters, improved and synchronized acoustic feedback and generation of timing markers needed for physiological analyzes of real-time brain activity. Thirty-one older adults (M = 60 years) completed the PAST. EEG was recorded to assess feedback-related negativity (FRN) and the magnitude of the stress response through autonomic nervous system activity and salivary cortisol. Physiological measures other than EEG included heart rate, respiration rate, heart rate variability, blood pressure and salivary cortisol. These measures were collected at several time points throughout the task. Feedback-related negativity evoked-potential responses were elicited and they significantly differed depending on whether positive or negative feedback was received. The PAST also increased systolic blood pressure, heart rate variability and respiration rates compared to a control condition attentional task. These preliminary results suggest that the PAST is an effective cognitive stressor. Successful measurement of the feedback-related negativity suggests that the PAST is conducive to EEG and time-sensitive ERP experiments. Moreover, the physiological findings support the PAST as a potent method for inducing stress in older adult participants. Further research is needed to confirm these results, but the PAST shows promise as a tool for cognitive stress induction for time-locked event-related potential experiments.

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

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

2014-01-01

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

Synchronization and desynchronization in epilepsy: controversies and hypotheses

Czech Academy of Sciences Publication Activity Database

Jiruška, Přemysl; de Curtis, M.; Jefferys, J. G. R.; Schevon, C.A.; Schiff, S.J.; Schindler, K.

2013-01-01

Roč. 591, č. 4 (2013), s. 787-797 ISSN 0022-3751 Grant - others:GA MZd(CZ) NT11460 Institutional support: RVO:67985823 Keywords : synchronization * desynchronization * epilepsy * seizures * neuronal dynamics Subject RIV: FH - Neurology Impact factor: 4.544, year: 2013

Positive Effects of Mindfulness-Based Training on Energy Maintenance and the EEG Correlates of Sustained Attention in a Cohort of Nurses

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Kian F. Wong

2018-03-01

Full Text Available Mindfulness based training (MBT is becoming increasingly popular as a means to improve general wellbeing through developing enhanced control over metacognitive processes. In this preliminary study, we tested a cohort of 36 nurses (mean age = 30.3, SD = 8.52; 2 male who participated in an 8-week MBT intervention to examine the improvements in sustained attention and its energetic costs that may result from MBT. Changes in sustained attention were measured using the psychomotor vigilance task (PVT and electroencephalography (EEG was collected both during PVT performance, and during a brief period of meditation. As there was substantial variability in training attendance, this variable was used a covariate in all analyses. Following the MBT program, we observed changes in alpha power across all scalp regions during meditation that were correlated with attendance. Similarly, PVT performance worsened over the 8-week period, but that this decline was mitigated by good attendance on the MBT program. The subjective energy depletion due to PVT performance (measured using self-report on Likert-type scales was also less in regular attendees. Finally, changes in known EEG markers of attention during PVT performance (P300 and alpha-band event-related desynchronization paralleled these behavioral shifts. Taken together, our data suggest that sustained attention and its associated costs may be negatively affected over time in the nursing profession, but that regular attendance of MBT may help to attenuate these effects. However, as this study contained no control condition, we cannot rule out that other factors (e.g., motivation, placebo effects may also account for our findings.

Touching lips and hearing fingers: effector-specific congruency between tactile and auditory stimulation modulates N1 amplitude and alpha desynchronization.

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Shen, Guannan; Meltzoff, Andrew N; Marshall, Peter J

2018-01-01

Understanding the interactions between audition and sensorimotor processes is of theoretical importance, particularly in relation to speech processing. Although one current focus in this area is on interactions between auditory perception and the motor system, there has been less research on connections between the auditory and somatosensory modalities. The current study takes a novel approach to this omission by examining specific auditory-tactile interactions in the context of speech and non-speech sound production. Electroencephalography was used to examine brain responses when participants were presented with speech syllables (a bilabial sound /pa/ and a non-labial sound /ka/) or finger-snapping sounds that were simultaneously paired with tactile stimulation of either the lower lip or the right middle finger. Analyses focused on the sensory-evoked N1 in the event-related potential and the extent of alpha band desynchronization elicited by the stimuli. N1 amplitude over fronto-central sites was significantly enhanced when the bilabial /pa/ sound was paired with tactile lip stimulation and when the finger-snapping sound was paired with tactile stimulation of the finger. Post-stimulus alpha desynchronization at central sites was also enhanced when the /pa/ sound was accompanied by tactile stimulation of the lip. These novel findings indicate that neural aspects of somatosensory-auditory interactions are influenced by the congruency between the location of the bodily touch and the bodily origin of a perceived sound.

ERPLAB: An Open-Source Toolbox for the Analysis of Event-Related Potentials

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Javier eLopez-Calderon

2014-04-01

Full Text Available ERPLAB Toolbox is a freely available, open-source toolbox for processing and analyzing event-related potential (ERP data in the MATLAB environment. ERPLAB is closely integrated with EEGLAB, a popular open-source toolbox that provides many EEG preprocessing steps and an excellent user interface design. ERPLAB adds to EEGLAB’s EEG processing functions, providing additional tools for filtering, artifact detection, re-referencing, and sorting of events, among others. ERPLAB also provides robust tools for averaging EEG segments together to create averaged ERPs, for creating difference waves and other recombinations of ERP waveforms through algebraic expressions, for filtering and re-referencing the averaged ERPs, for plotting ERP waveforms and scalp maps, and for quantifying several types of amplitudes and latencies. ERPLAB’s tools can be accessed either from an easy-to-learn graphical user interface or from MATLAB scripts, and a command history function makes it easy for users with no programming experience to write scripts. Consequently, ERPLAB provides both ease of use and virtually unlimited power and flexibility, making it appropriate for the analysis of both simple and complex ERP experiments. Several forms of documentation are available, including a detailed user’s guide, a step-by-step tutorial, a scripting guide, and a set of video-based demonstrations.

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

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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.

Firing patterns transition and desynchronization induced by time delay in neural networks

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Huang, Shoufang; Zhang, Jiqian; Wang, Maosheng; Hu, Chin-Kun

2018-06-01

We used the Hindmarsh-Rose (HR) model (Hindmarsh and Rose, 1984) to study the effect of time delay on the transition of firing behaviors and desynchronization in neural networks. As time delay is increased, neural networks exhibit diversity of firing behaviors, including regular spiking or bursting and firing patterns transitions (FPTs). Meanwhile, the desynchronization of firing and unstable bursting with decreasing amplitude in neural system, are also increasingly enhanced with the increase of time delay. Furthermore, we also studied the effect of coupling strength and network randomness on these phenomena. Our results imply that time delays can induce transition and desynchronization of firing behaviors in neural networks. These findings provide new insight into the role of time delay in the firing activities of neural networks, and can help to better understand the firing phenomena in complex systems of neural networks. A possible mechanism in brain that can cause the increase of time delay is discussed.

Stimulus-dependent spiking relationships with the EEG

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Snyder, Adam C.

2015-01-01

The development and refinement of noninvasive techniques for imaging neural activity is of paramount importance for human neuroscience. Currently, the most accessible and popular technique is electroencephalography (EEG). However, nearly all of what we know about the neural events that underlie EEG signals is based on inference, because of the dearth of studies that have simultaneously paired EEG recordings with direct recordings of single neurons. From the perspective of electrophysiologists there is growing interest in understanding how spiking activity coordinates with large-scale cortical networks. Evidence from recordings at both scales highlights that sensory neurons operate in very distinct states during spontaneous and visually evoked activity, which appear to form extremes in a continuum of coordination in neural networks. We hypothesized that individual neurons have idiosyncratic relationships to large-scale network activity indexed by EEG signals, owing to the neurons' distinct computational roles within the local circuitry. We tested this by recording neuronal populations in visual area V4 of rhesus macaques while we simultaneously recorded EEG. We found substantial heterogeneity in the timing and strength of spike-EEG relationships and that these relationships became more diverse during visual stimulation compared with the spontaneous state. The visual stimulus apparently shifts V4 neurons from a state in which they are relatively uniformly embedded in large-scale network activity to a state in which their distinct roles within the local population are more prominent, suggesting that the specific way in which individual neurons relate to EEG signals may hold clues regarding their computational roles. PMID:26108954

Unsupervised EEG analysis for automated epileptic seizure detection

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Birjandtalab, Javad; Pouyan, Maziyar Baran; Nourani, Mehrdad

2016-07-01

Epilepsy is a neurological disorder which can, if not controlled, potentially cause unexpected death. It is extremely crucial to have accurate automatic pattern recognition and data mining techniques to detect the onset of seizures and inform care-givers to help the patients. EEG signals are the preferred biosignals for diagnosis of epileptic patients. Most of the existing pattern recognition techniques used in EEG analysis leverage the notion of supervised machine learning algorithms. Since seizure data are heavily under-represented, such techniques are not always practical particularly when the labeled data is not sufficiently available or when disease progression is rapid and the corresponding EEG footprint pattern will not be robust. Furthermore, EEG pattern change is highly individual dependent and requires experienced specialists to annotate the seizure and non-seizure events. In this work, we present an unsupervised technique to discriminate seizures and non-seizures events. We employ power spectral density of EEG signals in different frequency bands that are informative features to accurately cluster seizure and non-seizure events. The experimental results tried so far indicate achieving more than 90% accuracy in clustering seizure and non-seizure events without having any prior knowledge on patient's history.

Desynchronization boost by non-uniform coordinated reset stimulation in ensembles of pulse-coupled neurons

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Lücken, Leonhard; Yanchuk, Serhiy; Popovych, Oleksandr V.; Tass, Peter A.

2013-01-01

Several brain diseases are characterized by abnormal neuronal synchronization. Desynchronization of abnormal neural synchrony is theoretically compelling because of the complex dynamical mechanisms involved. We here present a novel type of coordinated reset (CR) stimulation. CR means to deliver phase resetting stimuli at different neuronal sub-populations sequentially, i.e., at times equidistantly distributed in a stimulation cycle. This uniform timing pattern seems to be intuitive and actually applies to the neural network models used for the study of CR so far. CR resets the population to an unstable cluster state from where it passes through a desynchronized transient, eventually resynchronizing if left unperturbed. In contrast, we show that the optimal stimulation times are non-uniform. Using the model of weakly pulse-coupled neurons with phase response curves, we provide an approach that enables to determine optimal stimulation timing patterns that substantially maximize the desynchronized transient time following the application of CR stimulation. This approach includes an optimization search for clusters in a low-dimensional pulse coupled map. As a consequence, model-specific non-uniformly spaced cluster states cause considerably longer desynchronization transients. Intriguingly, such a desynchronization boost with non-uniform CR stimulation can already be achieved by only slight modifications of the uniform CR timing pattern. Our results suggest that the non-uniformness of the stimulation times can be a medically valuable parameter in the calibration procedure for CR stimulation, where the latter has successfully been used in clinical and pre-clinical studies for the treatment of Parkinson's disease and tinnitus. PMID:23750134

EEG Oscillations Are Modulated in Different Behavior-Related Networks during Rhythmic Finger Movements.

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Seeber, Martin; Scherer, Reinhold; Müller-Putz, Gernot R

2016-11-16

Sequencing and timing of body movements are essential to perform motoric tasks. In this study, we investigate the temporal relation between cortical oscillations and human motor behavior (i.e., rhythmic finger movements). High-density EEG recordings were used for source imaging based on individual anatomy. We separated sustained and movement phase-related EEG source amplitudes based on the actual finger movements recorded by a data glove. Sustained amplitude modulations in the contralateral hand area show decrease for α (10-12 Hz) and β (18-24 Hz), but increase for high γ (60-80 Hz) frequencies during the entire movement period. Additionally, we found movement phase-related amplitudes, which resembled the flexion and extension sequence of the fingers. Especially for faster movement cadences, movement phase-related amplitudes included high β (24-30 Hz) frequencies in prefrontal areas. Interestingly, the spectral profiles and source patterns of movement phase-related amplitudes differed from sustained activities, suggesting that they represent different frequency-specific large-scale networks. First, networks were signified by the sustained element, which statically modulate their synchrony levels during continuous movements. These networks may upregulate neuronal excitability in brain regions specific to the limb, in this study the right hand area. Second, movement phase-related networks, which modulate their synchrony in relation to the movement sequence. We suggest that these frequency-specific networks are associated with distinct functions, including top-down control, sensorimotor prediction, and integration. The separation of different large-scale networks, we applied in this work, improves the interpretation of EEG sources in relation to human motor behavior. EEG recordings provide high temporal resolution suitable to relate cortical oscillations to actual movements. Investigating EEG sources during rhythmic finger movements, we distinguish sustained from

How to desynchronize quorum-sensing networks

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Russo, Giovanni

2017-04-01

In this paper we investigate how so-called quorum-sensing networks can be desynchronized. Such networks, which arise in many important application fields, such as systems biology, are characterized by the fact that direct communication between network nodes is superimposed to communication with a shared, environmental variable. In particular, we provide a new sufficient condition ensuring that the trajectories of these quorum-sensing networks diverge from their synchronous evolution. Then, we apply our result to study two applications.

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

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

2012-01-01

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

Association between waking electroencephalography and cognitive event-related potentials in patients with obstructive sleep apnea.

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Baril, Andrée-Ann; Gagnon, Katia; Gagnon, Jean-François; Montplaisir, Jacques; Gosselin, Nadia

2013-07-01

Sleepiness, cognitive deficits, abnormal event-related potentials (ERP), and slowing of the waking electroencephalography (EEG) activity have been reported in patients with obstructive sleep apnea (OSA). Our study aimed at evaluating if an association exists between the severity of ERP abnormalities and EEG slowing to better understand cerebral dysfunctions in OSA. Twelve OSA patients and 12 age-matched controls underwent an overnight polysomnographic recording, an EEG recording of 10 min of wakefulness, and an auditory ERP protocol known to specifically recruit attention. P300 and P3a ERP components were measured as well as the spectral power in each frequency band of the waking EEG. Pearson product moment correlations were used to measure associations between ERP characteristics and EEG spectral power in OSA patients and control subjects. A positive correlation between the late P300 amplitude and θ power in the occipital region was observed in OSA subjects (P<.01). A positive correlation was also found between P3a amplitude and β1 power in central region in OSA subjects (P<.01). No correlation was observed for control subjects. ERP abnormalities observed in an attention task are associated with a slowing of the waking EEG recorded at rest in OSA. Copyright © 2013 Elsevier B.V. All rights reserved.

Synchronization and desynchronization in a network of locally coupled Wilson-Cowan oscillators.

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Campbell, S; Wang, D

1996-01-01

A network of Wilson-Cowan (WC) oscillators is constructed, and its emergent properties of synchronization and desynchronization are investigated by both computer simulation and formal analysis. The network is a 2D matrix, where each oscillator is coupled only to its neighbors. We show analytically that a chain of locally coupled oscillators (the piecewise linear approximation to the WC oscillator) synchronizes, and we present a technique to rapidly entrain finite numbers of oscillators. The coupling strengths change on a fast time scale based on a Hebbian rule. A global separator is introduced which receives input from and sends feedback to each oscillator in the matrix. The global separator is used to desynchronize different oscillator groups. Unlike many other models, the properties of this network emerge from local connections that preserve spatial relationships among components and are critical for encoding Gestalt principles of feature grouping. The ability to synchronize and desynchronize oscillator groups within this network offers a promising approach for pattern segmentation and figure/ground segregation based on oscillatory correlation.

Removing an intersubject variance component in a general linear model improves multiway factoring of event-related spectral perturbations in group EEG studies.

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Spence, Jeffrey S; Brier, Matthew R; Hart, John; Ferree, Thomas C

2013-03-01

Linear statistical models are used very effectively to assess task-related differences in EEG power spectral analyses. Mixed models, in particular, accommodate more than one variance component in a multisubject study, where many trials of each condition of interest are measured on each subject. Generally, intra- and intersubject variances are both important to determine correct standard errors for inference on functions of model parameters, but it is often assumed that intersubject variance is the most important consideration in a group study. In this article, we show that, under common assumptions, estimates of some functions of model parameters, including estimates of task-related differences, are properly tested relative to the intrasubject variance component only. A substantial gain in statistical power can arise from the proper separation of variance components when there is more than one source of variability. We first develop this result analytically, then show how it benefits a multiway factoring of spectral, spatial, and temporal components from EEG data acquired in a group of healthy subjects performing a well-studied response inhibition task. Copyright © 2011 Wiley Periodicals, Inc.

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

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Pletzer, Belinda; Kerschbaum, Hubert; Klimesch, Wolfgang

2010-06-04

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

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

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

2017-05-15

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

Cardiovascular and respiratory changes during slow-wave sleep in rats are associated with electrocorticogram desynchronization

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J.R. Dias-dos-Santos

1997-11-01

Full Text Available In awake rats a single recurrent larger tidal volume (deep breaths occurs at regular intervals, followed by oscillations in arterial pressure and heart rate. In the present study we recorded the changes in blood pressure, heart rate and ventilation during the wakefulness-sleep cycle identified by electrocorticographic records in order to determine whether the deep breaths and cardiovascular oscillations were associated with changes in the electrocorticogram. During several episodes of slow-wave sleep (SWS in 7 rats the deep breaths and oscillations in arterial pressure and heart rate were preceded by SWS desynchronization. The interval between deep breaths during SWS was 71 ± 4 s, the period between initial desynchronization and the generation of deep breaths was 3.98 ± 0.45 s and the duration of SWS desynchronization was 11 ± 0.65 s. Hypotension (-16 ± 1 mmHg and tachycardia (+15 ± 5 bpm were observed during deep breaths in the SWS state. These data indicate that the oscillations in arterial pressure and heart rate during SWS are associated with deep breaths, which in turn are preceded by desynchronization of the electrocorticogram in this state of sleep

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

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I. V. Kichuk

2016-01-01

of a desynchronization pattern.Conclusion. The specific features of EEG in the depression and AD groups may indicate serotonin metabolic disorders and the efficiency of therapy with selective serotonin reuptake inhibitors.

C-fiber-related EEG-oscillations induced by laser radiant heat stimulation of capsaicin-treated skin

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Claudia Domnick

2009-03-01

Full Text Available Claudia Domnick1, Michael Hauck1,2,3, Kenneth L Casey3, Andreas K Engel1, Jürgen Lorenz1,3,41Department of Neurophysiology and Pathophysiology; 2Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; 3Department of Neurology, University of Michigan, Ann Arbor, MI, USA; 4Faculty of Life Sciences, Hamburg University of Applied Sciences, Hamburg, GermanyAbstract: Nociceptive input reaches the brain via two different types of nerve fibers, moderately fast A-delta and slowly conducting C-fibers, respectively. To explore their distinct roles in normal and inflammatory pain we used laser stimulation of normal and capsaicin treated skin at proximal and distal arm sites in combination with time frequency transformation of electroencephalography (EEG data. Comparison of phase-locked (evoked and non-phase-locked (total EEG to laser stimuli revealed three significant pain-related oscillatory responses. First, an evoked response in the delta-theta band, mediated by A-fibers, was reduced by topical capsaicin treatment. Second, a decrease of total power in the alpha-to-gamma band reflected both an A- and C-nociceptor-mediated response with only the latter being reduced by capsaicin treatment. Finally, an enhancement of total power in the upper beta band was mediated exclusively by C-nociceptors and appeared strongly augmented by capsaicin treatment. These findings suggest that phase-locking of brain activity to stimulus onset is a critical feature of A-delta nociceptive input, allowing rapid orientation to salient and potentially threatening events. In contrast, the subsequent C-nociceptive input exhibits clearly less phase coupling to the stimulus. It may primarily signal the tissue status allowing more long-term behavioral adaptations during ongoing inflammatory events that accompany tissue damage.Keywords: C-fibers, oscillations, EEG, laser, capsaicin, inflammatory pain

Relative Power of Specific EEG Bands and Their Ratios during Neurofeedback Training in Children with Autism Spectrum Disorder

Directory of Open Access Journals (Sweden)

Yao eWang

2016-01-01

Full Text Available Neurofeedback is a mode of treatment that is potentially useful for improving self-regulation skills in persons with autism spectrum disorder. We proposed that operant conditioning of EEG in neurofeedback mode can be accompanied by changes in the relative power of EEG bands. However, the details on the change of the relative power of EEG bands during neurofeedback training course in autism are not yet well explored. In this study, we analyzed the EEG recordings of children diagnosed with autism and enrolled in a prefrontal neurofeedback treatment course. The protocol used in this training was aimed at increasing the ability to focus attention, and the procedure represented the wide band EEG amplitude suppression training along with upregulation of the relative power of gamma activity. Quantitative EEG analysis was completed for each session of neurofeedback using wavelet transform to determine the relative power of gamma and theta/beta ratio, and further to detect the statistical changes within and between sessions. We found a linear decrease of theta/beta ratio and a liner increase of relative power of gamma activity over 18 weekly sessions of neurofeedback in 18 high functioning children with autism. The study indicates that neurofeedback is an effective method for altering EEG characteristics associated with the autism spectrum disorder. Also, it provides information about specific changes of EEG activities and details the correlation between changes of EEG and neurofeedback indexes during the course of neurofeedback. This pilot study contributes to the development of more effective approaches to EEG data analysis during prefrontal neurofeedback training in autism.Key word: Electroencephalography, Neurofeedback, Autism Spectrum Disorder, Gamma activity, EEG bands’ ratios

Behavioral and EEG evidence for auditory memory suppression

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Maya Elizabeth Cano

2016-03-01

Full Text Available The neural basis of motivated forgetting using the Think/No-Think (TNT paradigm is receiving increased attention with a particular focus on the mechanisms that enable memory suppression. However, most TNT studies have been limited to the visual domain. To assess whether and to what extent direct memory suppression extends across sensory modalities, we examined behavioral and electroencephalographic (EEG effects of auditory Think/No-Think in healthy young adults by adapting the TNT paradigm to the auditory modality. Behaviorally, suppression of memory strength was indexed by prolonged response times during the retrieval of subsequently remembered No-Think words. We examined task-related EEG activity of both attempted memory retrieval and inhibition of a previously learned target word during the presentation of its paired associate. Event-related EEG responses revealed two main findings: 1 a centralized Think > No-Think positivity during auditory word presentation (from approximately 0-500ms, and 2 a sustained Think positivity over parietal electrodes beginning at approximately 600ms reflecting the memory retrieval effect which was significantly reduced for No-Think words. In addition, word-locked theta (4-8 Hz power was initially greater for No-Think compared to Think during auditory word presentation over fronto-central electrodes. This was followed by a posterior theta increase indexing successful memory retrieval in the Think condition.The observed event-related potential pattern and theta power analysis are similar to that reported in visual Think/No-Think studies and support a modality non-specific mechanism for memory inhibition. The EEG data also provide evidence supporting differing roles and time courses of frontal and parietal regions in the flexible control of auditory memory.

Behavioral and EEG Evidence for Auditory Memory Suppression.

Science.gov (United States)

Cano, Maya E; Knight, Robert T

2016-01-01

The neural basis of motivated forgetting using the Think/No-Think (TNT) paradigm is receiving increased attention with a particular focus on the mechanisms that enable memory suppression. However, most TNT studies have been limited to the visual domain. To assess whether and to what extent direct memory suppression extends across sensory modalities, we examined behavioral and electroencephalographic (EEG) effects of auditory TNT in healthy young adults by adapting the TNT paradigm to the auditory modality. Behaviorally, suppression of memory strength was indexed by prolonged response time (RTs) during the retrieval of subsequently remembered No-Think words. We examined task-related EEG activity of both attempted memory retrieval and inhibition of a previously learned target word during the presentation of its paired associate. Event-related EEG responses revealed two main findings: (1) a centralized Think > No-Think positivity during auditory word presentation (from approximately 0-500 ms); and (2) a sustained Think positivity over parietal electrodes beginning at approximately 600 ms reflecting the memory retrieval effect which was significantly reduced for No-Think words. In addition, word-locked theta (4-8 Hz) power was initially greater for No-Think compared to Think during auditory word presentation over fronto-central electrodes. This was followed by a posterior theta increase indexing successful memory retrieval in the Think condition. The observed event-related potential pattern and theta power analysis are similar to that reported in visual TNT studies and support a modality non-specific mechanism for memory inhibition. The EEG data also provide evidence supporting differing roles and time courses of frontal and parietal regions in the flexible control of auditory memory.

Relative Power of Specific EEG Bands and Their Ratios during Neurofeedback Training in Children with Autism Spectrum Disorder

Science.gov (United States)

Wang, Yao; Sokhadze, Estate M.; El-Baz, Ayman S.; Li, Xiaoli; Sears, Lonnie; Casanova, Manuel F.; Tasman, Allan

2016-01-01

Neurofeedback is a mode of treatment that is potentially useful for improving self-regulation skills in persons with autism spectrum disorder. We proposed that operant conditioning of EEG in neurofeedback mode can be accompanied by changes in the relative power of EEG bands. However, the details on the change of the relative power of EEG bands during neurofeedback training course in autism are not yet well explored. In this study, we analyzed the EEG recordings of children diagnosed with autism and enrolled in a prefrontal neurofeedback treatment course. The protocol used in this training was aimed at increasing the ability to focus attention, and the procedure represented the wide band EEG amplitude suppression training along with upregulation of the relative power of gamma activity. Quantitative EEG analysis was completed for each session of neurofeedback using wavelet transform to determine the relative power of gamma and theta/beta ratio, and further to detect the statistical changes within and between sessions. We found a linear decrease of theta/beta ratio and a liner increase of relative power of gamma activity over 18 weekly sessions of neurofeedback in 18 high functioning children with autism. The study indicates that neurofeedback is an effective method for altering EEG characteristics associated with the autism spectrum disorder. Also, it provides information about specific changes of EEG activities and details the correlation between changes of EEG and neurofeedback indexes during the course of neurofeedback. This pilot study contributes to the development of more effective approaches to EEG data analysis during prefrontal neurofeedback training in autism. PMID:26834615

C-fiber-related EEG-oscillations induced by laser radiant heat stimulation of capsaicin-treated skin

Science.gov (United States)

Domnick, Claudia; Hauck, Michael; Casey, Kenneth L; Engel, Andreas K; Lorenz, Jürgen

2009-01-01

Nociceptive input reaches the brain via two different types of nerve fibers, moderately fast A-delta and slowly conducting C-fibers, respectively. To explore their distinct roles in normal and inflammatory pain we used laser stimulation of normal and capsaicin treated skin at proximal and distal arm sites in combination with time frequency transformation of electroencephalography (EEG) data. Comparison of phase-locked (evoked) and non-phase-locked (total) EEG to laser stimuli revealed three significant pain-related oscillatory responses. First, an evoked response in the delta-theta band, mediated by A-fibers, was reduced by topical capsaicin treatment. Second, a decrease of total power in the alpha-to-gamma band reflected both an A- and C-nociceptor-mediated response with only the latter being reduced by capsaicin treatment. Finally, an enhancement of total power in the upper beta band was mediated exclusively by C-nociceptors and appeared strongly augmented by capsaicin treatment. These findings suggest that phase-locking of brain activity to stimulus onset is a critical feature of A-delta nociceptive input, allowing rapid orientation to salient and potentially threatening events. In contrast, the subsequent C-nociceptive input exhibits clearly less phase coupling to the stimulus. It may primarily signal the tissue status allowing more long-term behavioral adaptations during ongoing inflammatory events that accompany tissue damage. PMID:21197293

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

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Ryouhei eIshii

2014-06-01

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

Robust estimation of event-related potentials via particle filter.

Science.gov (United States)

Fukami, Tadanori; Watanabe, Jun; Ishikawa, Fumito

2016-03-01

In clinical examinations and brain-computer interface (BCI) research, a short electroencephalogram (EEG) measurement time is ideal. The use of event-related potentials (ERPs) relies on both estimation accuracy and processing time. We tested a particle filter that uses a large number of particles to construct a probability distribution. We constructed a simple model for recording EEG comprising three components: ERPs approximated via a trend model, background waves constructed via an autoregressive model, and noise. We evaluated the performance of the particle filter based on mean squared error (MSE), P300 peak amplitude, and latency. We then compared our filter with the Kalman filter and a conventional simple averaging method. To confirm the efficacy of the filter, we used it to estimate ERP elicited by a P300 BCI speller. A 400-particle filter produced the best MSE. We found that the merit of the filter increased when the original waveform already had a low signal-to-noise ratio (SNR) (i.e., the power ratio between ERP and background EEG). We calculated the amount of averaging necessary after applying a particle filter that produced a result equivalent to that associated with conventional averaging, and determined that the particle filter yielded a maximum 42.8% reduction in measurement time. The particle filter performed better than both the Kalman filter and conventional averaging for a low SNR in terms of both MSE and P300 peak amplitude and latency. For EEG data produced by the P300 speller, we were able to use our filter to obtain ERP waveforms that were stable compared with averages produced by a conventional averaging method, irrespective of the amount of averaging. We confirmed that particle filters are efficacious in reducing the measurement time required during simulations with a low SNR. Additionally, particle filters can perform robust ERP estimation for EEG data produced via a P300 speller. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Neurofeedback Effects on Evoked and Induced EEG Gamma Band Reactivity to Drug-related Cues in Cocaine Addiction

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Horrell, Timothy; El-Baz, Ayman; Baruth, Joshua; Tasman, Allan; Sokhadze, Guela; Stewart, Christopher; Sokhadze, Estate

2010-01-01

Introduction Preoccupation with drug and drug-related items is a typical characteristic of cocaine addicted individuals. It has been shown in multiple accounts that prolonged drug use has a profound effect on the EEG recordings of drug addicts when compared to controls during cue reactivity tests. Cue reactivity refers to a phenomenon in which individuals with a history of drug abuse exhibit excessive psychophysiological responses to cues associated with their drug of choice. One of the aims of this pilot study was to determine the presence of an attentional bias to preferentially process drug-related cues using evoked and induced gamma reactivity measures in cocaine addicts before and after biobehavioral treatment based on neurofeedback. Another aim was to show that central SMR amplitude increase and frontal theta control is possible in an experimental outpatient drug users group over 12 neurofeedback sessions. Method Ten current cocaine abusers participated in this pilot research study using neurofeedback combined with Motivational Interviewing sessions. Eight of them completed all planned pre- and post –neurofeedback cue reactivity tests with event-related EEG recording and clinical evaluations. Cue reactivity test represented a visual oddball task with images from the International Affective Picture System and drug-related pictures. Evoked and induced gamma responses to target and non-target drug cues were analyzed using wavelet analysis. Results Outpatient subjects with cocaine addiction completed the biobehavioral intervention and successfully increased SMR while keeping theta practically unchanged in 12 sessions of neurofeedback training. The addition of Motivational Interviewing helped retain patients in the study. Clinical evaluations immediately after completion of the treatment showed decreased self-reports on depression and stress scores, and urine tests collaborated reports of decreased use of cocaine and marijuana. Effects of neurofeedback resulted

Identical event-related potentials to target and frequent stimuli of visual oddball task recorded by intracerebral electrodes

Czech Academy of Sciences Publication Activity Database

Kukleta, M.; Brázdil, M.; Roman, R.; Jurák, Pavel

2003-01-01

Roč. 114, č. 7 (2003), s. 1292 - 1297 ISSN 1388-2457 Institutional research plan: CEZ:AV0Z2065902 Keywords : event-related potential * intra-cerebral EEG recording in humans * oddball task Subject RIV: FA - Cardiovascular Diseases incl. Cardiotharic Surgery Impact factor: 2.485, year: 2003

Stress-associated synchronization and desynchronization in geologic and biologic systems

Science.gov (United States)

Kluchevsky, A. V.; Kluchevskaya, A. A.

2010-12-01

Variations in the annual numbers of representative earthquakes in three areas and six districts of the Baikal rift zone in 1964-2002 were subjected to correlation analysis. Episodes of significant correlations of shock flow rates were found against the background of chaotic seismic activity. They followed the rearrangements (catastrophes) of stresses in the lithosphere, which are also stressing factors for the whole rift geodynamic system. The episode of the late 1970s-early 1980s was particularly long and showed the maximum correlation. Therefore, it can be considered the principal event in seismic process synchronization in the Baikal Rift Zone. The same approach to data analysis revealed similar synchronization and desynchronization phenomena in the behavior of Baikalian turbellaria when they deviated from homeostasis as a result of illumination, which is a stress for this biologic system. Possible reasons for the behavior of biologic and geodynamic systems are discussed in terms of the synergetic concept of phenomena in living and nonliving nature.

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.

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

Directory of Open Access Journals (Sweden)

Giuliana Grimaldi

2014-04-01

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

High-accuracy user identification using EEG biometrics.

Science.gov (United States)

Koike-Akino, Toshiaki; Mahajan, Ruhi; Marks, Tim K; Ye Wang; Watanabe, Shinji; Tuzel, Oncel; Orlik, Philip

2016-08-01

We analyze brain waves acquired through a consumer-grade EEG device to investigate its capabilities for user identification and authentication. First, we show the statistical significance of the P300 component in event-related potential (ERP) data from 14-channel EEGs across 25 subjects. We then apply a variety of machine learning techniques, comparing the user identification performance of various different combinations of a dimensionality reduction technique followed by a classification algorithm. Experimental results show that an identification accuracy of 72% can be achieved using only a single 800 ms ERP epoch. In addition, we demonstrate that the user identification accuracy can be significantly improved to more than 96.7% by joint classification of multiple epochs.

Alpha-contingent EEG feedback reduces SPECT rCBF variability

DEFF Research Database (Denmark)

McLaughlin, Thomas; Steinberg, Bruce; Mulholland, Thomas

2005-01-01

EEG feedback methods, which link the occurrence of alpha to the presentation of repeated visual stimuli, reduce the relative variability of subsequent, alpha-blocking event durations. The temporal association between electro-cortical field activation and regional cerebral blood flow (rCBF) led us...... to investigate whether the reduced variability of alpha-blocking durations with feedback is associated with a reduction in rCBF variability. Reduced variability in the rCBF response domain under EEG feedback control might have methodological implications for future brain-imaging studies. Visual stimuli were...... to quantify the variance-reducing effects of ACS across multiple, distributed areas of the brain. Both EEG and rCBF measures demonstrated decreased variability under ACS. This improved control was seen for localized as well as anatomically distributed rCBF measures....

DETECT: a MATLAB toolbox for event detection and identification in time series, with applications to artifact detection in EEG signals.

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Lawhern, Vernon; Hairston, W David; Robbins, Kay

2013-01-01

Recent advances in sensor and recording technology have allowed scientists to acquire very large time-series datasets. Researchers often analyze these datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal. We have developed DETECT, a MATLAB toolbox for detecting event time intervals in long, multi-channel time series. Our primary goal is to produce a toolbox that is simple for researchers to use, allowing them to quickly train a model on multiple classes of events, assess the accuracy of the model, and determine how closely the results agree with their own manual identification of events without requiring extensive programming knowledge or machine learning experience. As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and show the functionality of the tools found in the toolbox. We also discuss the application of DETECT for identifying irregular heartbeat waveforms found in electrocardiogram (ECG) data as an additional illustration.

DETECT: a MATLAB toolbox for event detection and identification in time series, with applications to artifact detection in EEG signals.

Directory of Open Access Journals (Sweden)

Vernon Lawhern

Full Text Available Recent advances in sensor and recording technology have allowed scientists to acquire very large time-series datasets. Researchers often analyze these datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal. We have developed DETECT, a MATLAB toolbox for detecting event time intervals in long, multi-channel time series. Our primary goal is to produce a toolbox that is simple for researchers to use, allowing them to quickly train a model on multiple classes of events, assess the accuracy of the model, and determine how closely the results agree with their own manual identification of events without requiring extensive programming knowledge or machine learning experience. As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and show the functionality of the tools found in the toolbox. We also discuss the application of DETECT for identifying irregular heartbeat waveforms found in electrocardiogram (ECG data as an additional illustration.

The Amount of Time Dilation for Visual Flickers Corresponds to the Amount of Neural Entrainments Measured by EEG.

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Hashimoto, Yuki; Yotsumoto, Yuko

2018-01-01

The neural basis of time perception has long attracted the interests of researchers. Recently, a conceptual model consisting of neural oscillators was proposed and validated by behavioral experiments that measured the dilated duration in perception of a flickering stimulus (Hashimoto and Yotsumoto, 2015). The model proposed that flickering stimuli cause neural entrainment of oscillators, resulting in dilated time perception. In this study, we examined the oscillator-based model of time perception, by collecting electroencephalography (EEG) data during an interval-timing task. Initially, subjects observed a stimulus, either flickering at 10-Hz or constantly illuminated. The subjects then reproduced the duration of the stimulus by pressing a button. As reported in previous studies, the subjects reproduced 1.22 times longer durations for flickering stimuli than for continuously illuminated stimuli. The event-related potential (ERP) during the observation of a flicker oscillated at 10 Hz, reflecting the 10-Hz neural activity phase-locked to the flicker. Importantly, the longer reproduced duration was associated with a larger amplitude of the 10-Hz ERP component during the inter-stimulus interval, as well as during the presentation of the flicker. The correlation between the reproduced duration and the 10-Hz oscillation during the inter-stimulus interval suggested that the flicker-induced neural entrainment affected time dilation. While the 10-Hz flickering stimuli induced phase-locked entrainments at 10 Hz, we also observed event-related desynchronizations of spontaneous neural oscillations in the alpha-frequency range. These could be attributed to the activation of excitatory neurons while observing the flicker stimuli. In addition, neural activity at approximately the alpha frequency increased during the reproduction phase, indicating that flicker-induced neural entrainment persisted even after the offset of the flicker. In summary, our results suggest that the

Developing an EEG based On-line Closed-loop Lapse Detection and Mitigation System

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Yu-Te eWang

2014-10-01

Full Text Available In America, sixty percent of adults reported that they have driven a motor vehicle while feeling drowsy, and at least 15-20% of fatal car accidents are fatigue-related. This study translates previous laboratory-oriented neurophysiological research to design, develop, and test an On-line Closed-loop Lapse Detection and Mitigation (OCLDM System featuring a mobile wireless dry-sensor EEG headgear and a cell-phone based real-time EEG processing platform. Eleven subjects participated in an event-related lane-keeping task, in which they were instructed to manipulate a randomly deviated, fixed-speed cruising car on a 4-lane highway. This was simulated in a 1st person view with an 8-screen and 8-projector immersive virtual-realty environment. When the subjects experienced lapses or failed to respond to events during the experiment, auditory feedback was delivered to rectify the performance decrements. However, the arousing auditory signals were not always effective. The EEG spectra exhibited statistically significant differences between effective and ineffective arousing signals, suggesting that EEG spectra could be used as a countermeasure of the efficacy of arousing signals. In this on-line pilot study, the proposed OCLDM System was able to continuously detect EEG signatures of fatigue, deliver arousing feedback to subjects suffering momentary cognitive lapses, and assess the efficacy of the feedback in near real-time to rectify cognitive lapses. The on-line testing results of the OCLDM System validated the efficacy of the arousing signals in improving subjects' response times to the subsequent lane-departure events. This study may lead to a practical on-line lapse detection and mitigation system in real-world environments.

Developing an EEG-based on-line closed-loop lapse detection and mitigation system.

Science.gov (United States)

Wang, Yu-Te; Huang, Kuan-Chih; Wei, Chun-Shu; Huang, Teng-Yi; Ko, Li-Wei; Lin, Chin-Teng; Cheng, Chung-Kuan; Jung, Tzyy-Ping

2014-01-01

In America, 60% of adults reported that they have driven a motor vehicle while feeling drowsy, and at least 15-20% of fatal car accidents are fatigue-related. This study translates previous laboratory-oriented neurophysiological research to design, develop, and test an On-line Closed-loop Lapse Detection and Mitigation (OCLDM) System featuring a mobile wireless dry-sensor EEG headgear and a cell-phone based real-time EEG processing platform. Eleven subjects participated in an event-related lane-keeping task, in which they were instructed to manipulate a randomly deviated, fixed-speed cruising car on a 4-lane highway. This was simulated in a 1st person view with an 8-screen and 8-projector immersive virtual-reality environment. When the subjects experienced lapses or failed to respond to events during the experiment, auditory warning was delivered to rectify the performance decrements. However, the arousing auditory signals were not always effective. The EEG spectra exhibited statistically significant differences between effective and ineffective arousing signals, suggesting that EEG spectra could be used as a countermeasure of the efficacy of arousing signals. In this on-line pilot study, the proposed OCLDM System was able to continuously detect EEG signatures of fatigue, deliver arousing warning to subjects suffering momentary cognitive lapses, and assess the efficacy of the warning in near real-time to rectify cognitive lapses. The on-line testing results of the OCLDM System validated the efficacy of the arousing signals in improving subjects' response times to the subsequent lane-departure events. This study may lead to a practical on-line lapse detection and mitigation system in real-world environments.

Noise-induced synchronization, desynchronization, and clustering in globally coupled nonidentical oscillators

KAUST Repository

Lai, Yi Ming; Porter, Mason A.

2013-01-01

to synchronize nonidentical oscillators. However, this synchrony depends on the first Fourier mode of a phase-sensitivity function, through which we introduce common noise into the system. We show that higher Fourier modes can cause desynchronization due

Test-retest reliability of cognitive EEG

Science.gov (United States)

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

2000-01-01

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

Slowing and Loss of Complexity in Alzheimer's EEG: Two Sides of the Same Coin?

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Justin Dauwels

2011-01-01

Full Text Available Medical studies have shown that EEG of Alzheimer's disease (AD patients is “slower” (i.e., contains more low-frequency power and is less complex compared to age-matched healthy subjects. The relation between those two phenomena has not yet been studied, and they are often silently assumed to be independent. In this paper, it is shown that both phenomena are strongly related. Strong correlation between slowing and loss of complexity is observed in two independent EEG datasets: (1 EEG of predementia patients (a.k.a. Mild Cognitive Impairment; MCI and control subjects; (2 EEG of mild AD patients and control subjects. The two data sets are from different patients, different hospitals and obtained through different recording systems. The paper also investigates the potential of EEG slowing and loss of EEG complexity as indicators of AD onset. In particular, relative power and complexity measures are used as features to classify the MCI and MiAD patients versus age-matched control subjects. When combined with two synchrony measures (Granger causality and stochastic event synchrony, classification rates of 83% (MCI and 98% (MiAD are obtained. By including the compression ratios as features, slightly better classification rates are obtained than with relative power and synchrony measures alone.

EEG Alpha Synchronization Is Related to Top-Down Processing in Convergent and Divergent Thinking

Science.gov (United States)

Benedek, Mathias; Bergner, Sabine; Konen, Tanja; Fink, Andreas; Neubauer, Aljoscha C.

2011-01-01

Synchronization of EEG alpha activity has been referred to as being indicative of cortical idling, but according to more recent evidence it has also been associated with active internal processing and creative thinking. The main objective of this study was to investigate to what extent EEG alpha synchronization is related to internal processing…

P300 amplitude variation is related to ventral striatum BOLD response during gain and loss anticipation: an EEG and fMRI experiment.

Science.gov (United States)

Pfabigan, Daniela M; Seidel, Eva-Maria; Sladky, Ronald; Hahn, Andreas; Paul, Katharina; Grahl, Arvina; Küblböck, Martin; Kraus, Christoph; Hummer, Allan; Kranz, Georg S; Windischberger, Christian; Lanzenberger, Rupert; Lamm, Claus

2014-08-01

The anticipation of favourable or unfavourable events is a key component in our daily life. However, the temporal dynamics of anticipation processes in relation to brain activation are still not fully understood. A modified version of the monetary incentive delay task was administered during separate functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) sessions in the same 25 participants to assess anticipatory processes with a multi-modal neuroimaging set-up. During fMRI, gain and loss anticipation were both associated with heightened activation in ventral striatum and reward-related areas. EEG revealed most pronounced P300 amplitudes for gain anticipation, whereas CNV amplitudes distinguished neutral from gain and loss anticipation. Importantly, P300, but not CNV amplitudes, were correlated to neural activation in the ventral striatum for both gain and loss anticipation. Larger P300 amplitudes indicated higher ventral striatum blood oxygen level dependent (BOLD) response. Early stimulus evaluation processes indexed by EEG seem to be positively related to higher activation levels in the ventral striatum, indexed by fMRI, which are usually associated with reward processing. The current results, however, point towards a more general motivational mechanism processing salient stimuli during anticipation. Copyright © 2014. Published by Elsevier Inc.

Physiological artifacts in scalp EEG and ear-EEG.

Science.gov (United States)

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

2017-08-11

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

Long-lasting desynchronization in rat hippocampal slice induced by coordinated reset stimulation

International Nuclear Information System (INIS)

Tass, P. A.; Barnikol, U. B.; Silchenko, A. N.; Hauptmann, C.; Speckmann, E.-J.

2009-01-01

In computational models it has been shown that appropriate stimulation protocols may reshape the connectivity pattern of neural or oscillator networks with synaptic plasticity in a way that the network learns or unlearns strong synchronization. The underlying mechanism is that a network is shifted from one attractor to another, so that long-lasting stimulation effects are caused which persist after the cessation of stimulation. Here we study long-lasting effects of multisite electrical stimulation in a rat hippocampal slice rendered epileptic by magnesium withdrawal. We show that desynchronizing coordinated reset stimulation causes a long-lasting desynchronization between hippocampal neuronal populations together with a widespread decrease in the amplitude of the epileptiform activity. In contrast, periodic stimulation induces a long-lasting increase in both synchronization and amplitude.

Transfer function between EEG and BOLD signals of epileptic activity

Directory of Open Access Journals (Sweden)

Marco eLeite

2013-01-01

Full Text Available Simultaneous EEG-fMRI recordings have seen growing application in the evaluation of epilepsy, namely in the characterization of brain networks related to epileptic activity. In EEG-correlated fMRI studies, epileptic events are usually described as boxcar signals based on the timing information retrieved from the EEG, and subsequently convolved with a heamodynamic response function to model the associated BOLD changes. Although more flexible approaches may allow a higher degree of complexity for the haemodynamics, the issue of how to model these dynamics based on the EEG remains an open question. In this work, a new methodology for the integration of simultaneous EEG-fMRI data in epilepsy is proposed, which incorporates a transfer function from the EEG to the BOLD signal. Independent component analysis (ICA of the EEG is performed, and a number of metrics expressing different models of the EEG-BOLD transfer function are extracted from the resulting time courses. These metrics are then used to predict the fMRI data and to identify brain areas associated with the EEG epileptic activity. The methodology was tested on both ictal and interictal EEG-fMRI recordings from one patient with a hypothalamic hamartoma. When compared to the conventional analysis approach, plausible, consistent and more significant activations were obtained. Importantly, frequency-weighted EEG metrics yielded superior results than those weighted solely on the EEG power, which comes in agreement with previous literature. Reproducibility, specificity and sensitivity should be addressed in an extended group of patients in order to further validate the proposed methodology and generalize the presented proof of concept.

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

Directory of Open Access Journals (Sweden)

Zhijie eBian

2014-02-01

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

The effect of repetition of infrequent familiar and unfamiliar visual patterns on components of the event-related brain potential.

NARCIS (Netherlands)

Kok, A.; de Looren de Jong, H.

1980-01-01

Examined changes in the waveforms of the event-related brain potential (ERP) during repeated presentations of infrequent-familiar and infrequent-unfamiliar visual patterns; Ss were 12 male university students. The EEG waveforms were averaged separately for each presentation of the 2 types of stimuli

EEG signatures of arm isometric exertions in preparation, planning and execution.

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Nasseroleslami, Bahman; Lakany, Heba; Conway, Bernard A

2014-04-15

The electroencephalographic (EEG) activity patterns in humans during motor behaviour provide insight into normal motor control processes and for diagnostic and rehabilitation applications. While the patterns preceding brisk voluntary movements, and especially movement execution, are well described, there are few EEG studies that address the cortical activation patterns seen in isometric exertions and their planning. In this paper, we report on time and time-frequency EEG signatures in experiments in normal subjects (n=8), using multichannel EEG during motor preparation, planning and execution of directional centre-out arm isometric exertions performed at the wrist in the horizontal plane, in response to instruction-delay visual cues. Our observations suggest that isometric force exertions are accompanied by transient and sustained event-related potentials (ERP) and event-related (de-)synchronisations (ERD/ERS), comparable to those of a movement task. Furthermore, the ERPs and ERD/ERS are also observed during preparation and planning of the isometric task. Comparison of ear-lobe-referenced and surface Laplacian ERPs indicates the contribution of superficial sources in supplementary and pre-motor (FC(z)), parietal (CP(z)) and primary motor cortical areas (C₁ and FC₁) to ERPs (primarily negative peaks in frontal and positive peaks in parietal areas), but contribution of deep sources to sustained time-domain potentials (negativity in planning and positivity in execution). Transient and sustained ERD patterns in μ and β frequency bands of ear-lobe-referenced and surface Laplacian EEG indicate the contribution of both superficial and deep sources to ERD/ERS. As no physical displacement happens during the task, we can infer that the underlying mechanisms of motor-related ERPs and ERD/ERS patterns do not only depend on change in limb coordinate or muscle-length-dependent ascending sensory information and are primary generated by motor preparation, direction

Acute low-level alcohol consumption reduces phase locking of event-related oscillations in rodents.

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Amodeo, Leslie R; Wills, Derek N; Ehlers, Cindy L

2017-07-14

Event-related oscillations (EROs) are rhythmic changes that are evoked by a sensory and/or cognitive stimulus that can influence the dynamics of the EEG. EROs are defined by the decomposition of the EEG signal into magnitude (energy) and phase information and can be elicited in both humans and animals. EROs have been linked to several relevant genes associated with ethanol dependence phenotypes in humans and are altered in selectively bred alcohol-preferring rats. However, pharmacological studies are only beginning to emerge investigating the impact low intoxicating doses of ethanol can have on event-related neural oscillations. The main goal of this study was to investigate the effects of low levels of voluntary consumption of ethanol, in rats, on phase locking of EROs in order to give further insight into the acute intoxicating effects of ethanol on the brain. To this end, we allow rats to self-administer unsweetened 20% ethanol over 15 intermittent sessions. This method results in a stable low-dose consumption of ethanol. Using an auditory event-related potential "oddball" paradigm, we investigated the effects of alcohol on the phase variability of EROs from electrodes implanted into the frontal cortex, dorsal hippocampus, and amygdala. We found that intermittent ethanol self-administration was sufficient to produce a significant reduction in overall intraregional synchrony across all targeted regions. These data suggest that phase locking of EROs within brain regions known to be impacted by alcohol may represent a sensitive biomarker of low levels of alcohol intoxication. Copyright © 2017 Elsevier B.V. All rights reserved.

Music listening while you learn: no influence of background music on verbal learning.

Science.gov (United States)

Jäncke, Lutz; Sandmann, Pascale

2010-01-07

Whether listening to background music enhances verbal learning performance is still disputed. In this study we investigated the influence of listening to background music on verbal learning performance and the associated brain activations. Musical excerpts were composed for this study to ensure that they were unknown to the subjects and designed to vary in tempo (fast vs. slow) and consonance (in-tune vs. out-of-tune). Noise was used as control stimulus. 75 subjects were randomly assigned to one of five groups and learned the presented verbal material (non-words with and without semantic connotation) with and without background music. Each group was exposed to one of five different background stimuli (in-tune fast, in-tune slow, out-of-tune fast, out-of-tune slow, and noise). As dependent variable, the number of learned words was used. In addition, event-related desynchronization (ERD) and event-related synchronization (ERS) of the EEG alpha-band were calculated as a measure for cortical activation. We did not find any substantial and consistent influence of background music on verbal learning. There was neither an enhancement nor a decrease in verbal learning performance during the background stimulation conditions. We found however a stronger event-related desynchronization around 800 - 1200 ms after word presentation for the group exposed to in-tune fast music while they learned the verbal material. There was also a stronger event-related synchronization for the group exposed to out-of-tune fast music around 1600 - 2000 ms after word presentation. Verbal learning during the exposure to different background music varying in tempo and consonance did not influence learning of verbal material. There was neither an enhancing nor a detrimental effect on verbal learning performance. The EEG data suggest that the different acoustic background conditions evoke different cortical activations. The reason for these different cortical activations is unclear. The most

Music listening while you learn: No influence of background music on verbal learning

Directory of Open Access Journals (Sweden)

Sandmann Pascale

2010-01-01

Full Text Available Abstract Background Whether listening to background music enhances verbal learning performance is still disputed. In this study we investigated the influence of listening to background music on verbal learning performance and the associated brain activations. Methods Musical excerpts were composed for this study to ensure that they were unknown to the subjects and designed to vary in tempo (fast vs. slow and consonance (in-tune vs. out-of-tune. Noise was used as control stimulus. 75 subjects were randomly assigned to one of five groups and learned the presented verbal material (non-words with and without semantic connotation with and without background music. Each group was exposed to one of five different background stimuli (in-tune fast, in-tune slow, out-of-tune fast, out-of-tune slow, and noise. As dependent variable, the number of learned words was used. In addition, event-related desynchronization (ERD and event-related synchronization (ERS of the EEG alpha-band were calculated as a measure for cortical activation. Results We did not find any substantial and consistent influence of background music on verbal learning. There was neither an enhancement nor a decrease in verbal learning performance during the background stimulation conditions. We found however a stronger event-related desynchronization around 800 - 1200 ms after word presentation for the group exposed to in-tune fast music while they learned the verbal material. There was also a stronger event-related synchronization for the group exposed to out-of-tune fast music around 1600 - 2000 ms after word presentation. Conclusion Verbal learning during the exposure to different background music varying in tempo and consonance did not influence learning of verbal material. There was neither an enhancing nor a detrimental effect on verbal learning performance. The EEG data suggest that the different acoustic background conditions evoke different cortical activations. The reason for

Measurement and modification of the EEG and related behavior

Science.gov (United States)

Sterman, M. B.

1991-01-01

Electrophysiological changes in the sensorimotor pathways were found to accompany the effect of rhythmic EEG patterns in the sensorimotor cortex. Additionally, several striking behavioral changes were seen, including in particular an enhancement of sleep and an elevation of seizure threshold to epileptogenic agents. This raised the possibility that human seizure disorders might be influenced therapeutically by similar training. Our objective in human EEG feedback training became not only the facilitation of normal rhythmic patterns, but also the suppression of abnormal activity, thus requiring complex contingencies directed to the normalization of the sensorimotor EEG. To achieve this, a multicomponent frequency analysis was developed to extract and separate normal and abnormal elements of the EEG signal. Each of these elements was transduced to a specific component of a visual display system, and these were combined through logic circuits to present the subject with a symbolic display. Variable criteria provided for the gradual shaping of EEG elements towards the desired normal pattern. Some 50-70% of patients with poorly controlled seizure disorders experienced therapeutic benefits from this approach in our laboratory, and subsequently in many others. A more recent application of this approach to the modification of human brain function in our lab has been directed to the dichotomous problems of task overload and underload in the contemporary aviation environment. At least 70% of all aviation accidents have been attributed to the impact of these kinds of problems on crew performance. The use of EEG in this context has required many technical innovations and the application of the latest advances in EEG signal analysis. Our first goal has been the identification of relevant EEG characteristics. Additionally, we have developed a portable recording and analysis system for application in this context. Findings from laboratory and in-flight studies suggest that we

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

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Mads Jochumsen

2017-01-01

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

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...

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.

Illumination influences working memory: an EEG study.

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

2013-09-05

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

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

Science.gov (United States)

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

2017-09-01

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

Event-related potential correlates of emergent inference in human arbitrary relational learning.

Science.gov (United States)

Wang, Ting; Dymond, Simon

2013-01-01

Two experiments investigated the functional-anatomical correlates of cognition supporting untrained, emergent relational inference in a stimulus equivalence task. In Experiment 1, after learning a series of conditional relations involving words and pseudowords, participants performed a relatedness task during which EEG was recorded. Behavioural performance was faster and more accurate on untrained, indirectly related symmetry (i.e., learn AB and infer BA) and equivalence trials (i.e., learn AB and AC and infer CB) than on unrelated trials, regardless of whether or not a formal test for stimulus equivalence relations had been conducted. Consistent with previous results, event related potentials (ERPs) evoked by trained and emergent trials at parietal and occipital sites differed only for those participants who had not received a prior equivalence test. Experiment 2 further replicated and extended these behavioural and ERP findings using arbitrary symbols as stimuli and demonstrated time and frequency differences for trained and untrained relatedness trials. Overall, the findings demonstrate convincingly the ERP correlates of intra-experimentally established stimulus equivalence relations consisting entirely of arbitrary symbols and offer support for a contemporary cognitive-behavioural model of symbolic categorisation and relational inference. Copyright © 2012 Elsevier B.V. All rights reserved.

Noise-induced synchronization, desynchronization, and clustering in globally coupled nonidentical oscillators

KAUST Repository

Lai, Yi Ming

2013-07-09

We study ensembles of globally coupled, nonidentical phase oscillators subject to correlated noise, and we identify several important factors that cause noise and coupling to synchronize or desynchronize a system. By introducing noise in various ways, we find an estimate for the onset of synchrony of a system in terms of the coupling strength, noise strength, and width of the frequency distribution of its natural oscillations. We also demonstrate that noise alone can be sufficient to synchronize nonidentical oscillators. However, this synchrony depends on the first Fourier mode of a phase-sensitivity function, through which we introduce common noise into the system. We show that higher Fourier modes can cause desynchronization due to clustering effects, and that this can reinforce clustering caused by different forms of coupling. Finally, we discuss the effects of noise on an ensemble in which antiferromagnetic coupling causes oscillators to form two clusters in the absence of noise. © 2013 American Physical Society.

Lateralized EEG components with direction information for the preparation of saccades versus finger movements

NARCIS (Netherlands)

van der Lubbe, Robert Henricus Johannes; Wauschkuhn, Bernd; Wascher, Edmund; Niehoff, Torsten; Kömpf, Detlef; Verleger, Rolf

2000-01-01

During preparation of horizontal saccades in humans, several lateralized (relative to saccade direction), event-related EEG components occur that have been interpreted as reflecting activity of frontal and parietal eye fields. We investigated to what degree these components are specific to saccade

Synchronization and Desynchronizing Control Schemes for Supermarket Refrigeration Systems

DEFF Research Database (Denmark)

Larsen, Lars Finn Sloth; Thybo, Claus Thybo; Izadi-Zamanabadi, Roozbeh

2007-01-01

A supermarket refrigeration system is a hybrid system with switched nonlinear dynamics and discrete-valued input variables such as opening/closing of valves and start/stop of compressors. Practical and simulation studies have shown that the use of distributed hysteresis controllers to operate...... complexity for desynchronizing the valve operations while improving performance. Simulation results indicate the potential increase in efficiency and reduction in wear comparing with traditional control schemes....

Latency correction of event-related potentials between different experimental protocols

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Iturrate, I.; Chavarriaga, R.; Montesano, L.; Minguez, J.; Millán, JdR

2014-06-01

Objective. A fundamental issue in EEG event-related potentials (ERPs) studies is the amount of data required to have an accurate ERP model. This also impacts the time required to train a classifier for a brain-computer interface (BCI). This issue is mainly due to the poor signal-to-noise ratio and the large fluctuations of the EEG caused by several sources of variability. One of these sources is directly related to the experimental protocol or application designed, and may affect the amplitude or latency of ERPs. This usually prevents BCI classifiers from generalizing among different experimental protocols. In this paper, we analyze the effect of the amplitude and the latency variations among different experimental protocols based on the same type of ERP. Approach. We present a method to analyze and compensate for the latency variations in BCI applications. The algorithm has been tested on two widely used ERPs (P300 and observation error potentials), in three experimental protocols in each case. We report the ERP analysis and single-trial classification. Main results. The results obtained show that the designed experimental protocols significantly affect the latency of the recorded potentials but not the amplitudes. Significance. These results show how the use of latency-corrected data can be used to generalize the BCIs, reducing the calibration time when facing a new experimental protocol.

EEG Spectral Analysis in Serious Gaming: An Ad Hoc Experimental Application

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Minchev Z.

2009-12-01

Full Text Available The application of serious gaming technology in different areas of human knowledge for learning is raising the question of quantitative measurement of the training process quality. In the present paper a pilot study of 10 healthy volunteers' EEG spectra is performed for ad hoc selected game events ('win' and 'lose' via continuous wavelet transform (real and complex on the basis of the Morlet mother wavelet function and S-transformation. The results have shown a general decrease of the alpha rhythms power spectra frequencies for the 'lose' events and increase for the 'win' events. This fact corresponds to an opposite behaviour of the theta rhythm of the players for the same 'win' and 'lose' events. Additionally, the frequency changes in the alpha1 (8-10.5 Hz, alpha2 (10.5-13 Hz and theta2 rhythms (6-8 Hz were supposed to be a phenomena related to positive and negative emotions appearance in the EEG activity of the players regarding the selected 'win' and 'lose' states.

Preterm EEG: a multimodal neurophysiological protocol.

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

2012-02-18

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

Structure constrained semi-nonnegative matrix factorization for EEG-based motor imagery classification.

Science.gov (United States)

Lu, Na; Li, Tengfei; Pan, Jinjin; Ren, Xiaodong; Feng, Zuren; Miao, Hongyu

2015-05-01

Electroencephalogram (EEG) provides a non-invasive approach to measure the electrical activities of brain neurons and has long been employed for the development of brain-computer interface (BCI). For this purpose, various patterns/features of EEG data need to be extracted and associated with specific events like cue-paced motor imagery. However, this is a challenging task since EEG data are usually non-stationary time series with a low signal-to-noise ratio. In this study, we propose a novel method, called structure constrained semi-nonnegative matrix factorization (SCS-NMF), to extract the key patterns of EEG data in time domain by imposing the mean envelopes of event-related potentials (ERPs) as constraints on the semi-NMF procedure. The proposed method is applicable to general EEG time series, and the extracted temporal features by SCS-NMF can also be combined with other features in frequency domain to improve the performance of motor imagery classification. Real data experiments have been performed using the SCS-NMF approach for motor imagery classification, and the results clearly suggest the superiority of the proposed method. Comparison experiments have also been conducted. The compared methods include ICA, PCA, Semi-NMF, Wavelets, EMD and CSP, which further verified the effectivity of SCS-NMF. The SCS-NMF method could obtain better or competitive performance over the state of the art methods, which provides a novel solution for brain pattern analysis from the perspective of structure constraint. Copyright © 2015 Elsevier Ltd. All rights reserved.

EEG correlates of virtual reality hypnosis.

Science.gov (United States)

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

2009-01-01

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

Lexical decision making in adults with dyslexia: an event-related potential study

Directory of Open Access Journals (Sweden)

Karen E. Waldie

2012-12-01

Full Text Available http://dx.doi.org/10.5007/2175-8026.2012n63p37   Performance on a lexical decision task was investigated in 12 English speaking adults with dyslexia.  two age-matched comparison groups of unimpaired readers were included: 14 monolingual adults and 15 late proficient bilinguals. The aim of the study was to determine the timing of neural events with event-related potentials (ErPs during lexical decision-making between individuals with dyslexia and unimpaired readers (both unilingual and bilingual. ErPs were calculated for posterior sites in the left and right hemispheres and the P1 and n170 components were compared between groups. Event-related EEG  coherence (measuring  the synchrony of neural events during lexical tasks both between and within cerebral hemispheres was also calculated for seven electrode pairs (three pairs at symmetrical locations between hemispheres, and two pairs within each hemisphere. We chose to recruit two comparison groups of unimpaired readers to better clarify the findings resulting from the right hemisphere (EEG coherence analysis. That is, both late-proficient bilinguals and adults with dyslexia are thought to rely on right hemisphere resources during reading. We hypothesized that those with dyslexia would show less within-hemisphere coherence and more between-hemisphere coherence than bilingual individuals. dyslexics had both lower amplitude and longer latency n170 activation than unimpaired readers, suggesting asynchronous neural activity. Dyslexics showed greater synchrony between hemispheres in gamma range frequencies whereas the bilingual group showed greater synchrony in the theta frequency band (both within and between hemispheres. This study demonstrates that individuals with developmental dyslexia have reduced amplitudes in the n170 and higher synchrony between hemispheres during a reading task. The differences may be due to an asynchrony of neuronal activity at the point where

EEG patterns in theta and gamma frequency range and their probable relation to human voluntary movement organization.

Science.gov (United States)

Popivanov, D; Mineva, A; Krekule, I

1999-05-21

In experiments with EEG accompanying continuous slow goal-directed voluntary movements we found abrupt short-term transients (STs) of the coefficients of EEG time-varying autoregressive (TVAR) model. The onset of STs indicated (i) a positive EEG wave related to an increase of 3-7 Hz oscillations in time period before the movement start, (ii) synchronization of 35-40 Hz prior to movement start and during the movement when the target is nearly reached. Both these phenomena are expressed predominantly over supplementary motor area, premotor and parietal cortices. These patterns were detected after averaging of EEG segments synchronized to the abrupt changes of the TVAR coefficients computed in the time course of EEG single records. The results are discussed regarding the cognitive aspect of organization of goal-directed movements.

Detection of movement intention using EEG in a human-robot interaction environment

Directory of Open Access Journals (Sweden)

Ernesto Pablo Lana

Full Text Available Introduction : This paper presents a detection method for upper limb movement intention as part of a brain-machine interface using EEG signals, whose final goal is to assist disabled or vulnerable people with activities of daily living. Methods EEG signals were recorded from six naïve healthy volunteers while performing a motor task. Every volunteer remained in an acoustically isolated recording room. The robot was placed in front of the volunteers such that it seemed to be a mirror of their right arm, emulating a Brain Machine Interface environment. The volunteers were seated in an armchair throughout the experiment, outside the reaching area of the robot to guarantee safety. Three conditions are studied: observation, execution, and imagery of right arm’s flexion and extension movements paced by an anthropomorphic manipulator robot. The detector of movement intention uses the spectral F test for discrimination of conditions and uses as feature the desynchronization patterns found on the volunteers. Using a detector provides an objective method to acknowledge for the occurrence of movement intention. Results When using four realizations of the task, detection rates ranging from 53 to 97% were found in five of the volunteers when the movement was executed, in three of them when the movement was imagined, and in two of them when the movement was observed. Conclusions Detection rates for movement observation raises the question of how the visual feedback may affect the performance of a working brain-machine interface, posing another challenge for the upcoming interface implementation. Future developments will focus on the improvement of feature extraction and detection accuracy for movement intention using EEG data.

Comparison of event related potentials with and without hypnagogic imagery.

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Michida, N; Hayashi, M; Hori, T

1998-04-01

It is hypothesized that when hypnagogic imagery occurs, an appropriate attention may allocate to the imagery, resulting in the allocation of attention to the external tone stimuli being diminished. N3 amplitude of event related potentials (ERP) obtained a significant difference between the conditions with and without imagery. Arousal level of behavior and electroencephalography were not different between the conditions, therefore it is interpreted that the decrease of the N3 amplitude during imagining reflects the diminution of the allocation of attention to the external tone stimuli. Another late component of ERP, P3, did not make clear peaks in this study despite a large time constant (tau=3.2 s) used for EEG records.

Constant Light Desynchronizes Olfactory versus Object and Visuospatial Recognition Memory Performance.

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Tam, Shu K E; Hasan, Sibah; Choi, Harry M C; Brown, Laurence A; Jagannath, Aarti; Hughes, Steven; Hankins, Mark W; Foster, Russell G; Vyazovskiy, Vladyslav V; Bannerman, David M; Peirson, Stuart N

2017-03-29

Circadian rhythms optimize physiology and behavior to the varying demands of the 24 h day. The master circadian clock is located in the suprachiasmatic nuclei (SCN) of the hypothalamus and it regulates circadian oscillators in tissues throughout the body to prevent internal desynchrony. Here, we demonstrate for the first time that, under standard 12 h:12 h light/dark (LD) cycles, object, visuospatial, and olfactory recognition performance in C57BL/6J mice is consistently better at midday relative to midnight. However, under repeated exposure to constant light ( r LL), recognition performance becomes desynchronized, with object and visuospatial performance better at subjective midday and olfactory performance better at subjective midnight. This desynchrony in behavioral performance is mirrored by changes in expression of the canonical clock genes Period1 and Period2 ( Per1 and Per2 ), as well as the immediate-early gene Fos in the SCN, dorsal hippocampus, and olfactory bulb. Under r LL, rhythmic Per1 and Fos expression is attenuated in the SCN. In contrast, hippocampal gene expression remains rhythmic, mirroring object and visuospatial performance. Strikingly, Per1 and Fos expression in the olfactory bulb is reversed, mirroring the inverted olfactory performance. Temporal desynchrony among these regions does not result in arrhythmicity because core body temperature and exploratory activity rhythms persist under r LL. Our data provide the first demonstration that abnormal lighting conditions can give rise to temporal desynchrony between autonomous circadian oscillators in different regions, with different consequences for performance across different sensory domains. Such a dispersed network of dissociable circadian oscillators may provide greater flexibility when faced with conflicting environmental signals. SIGNIFICANCE STATEMENT A master circadian clock in the suprachiasmatic nuclei (SCN) of the hypothalamus regulates physiology and behavior across the 24 h day by

Constant Light Desynchronizes Olfactory versus Object and Visuospatial Recognition Memory Performance

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Tam, Shu K.E.; Hasan, Sibah; Brown, Laurence A.; Jagannath, Aarti; Hankins, Mark W.; Foster, Russell G.; Vyazovskiy, Vladyslav V.

2017-01-01

Circadian rhythms optimize physiology and behavior to the varying demands of the 24 h day. The master circadian clock is located in the suprachiasmatic nuclei (SCN) of the hypothalamus and it regulates circadian oscillators in tissues throughout the body to prevent internal desynchrony. Here, we demonstrate for the first time that, under standard 12 h:12 h light/dark (LD) cycles, object, visuospatial, and olfactory recognition performance in C57BL/6J mice is consistently better at midday relative to midnight. However, under repeated exposure to constant light (rLL), recognition performance becomes desynchronized, with object and visuospatial performance better at subjective midday and olfactory performance better at subjective midnight. This desynchrony in behavioral performance is mirrored by changes in expression of the canonical clock genes Period1 and Period2 (Per1 and Per2), as well as the immediate-early gene Fos in the SCN, dorsal hippocampus, and olfactory bulb. Under rLL, rhythmic Per1 and Fos expression is attenuated in the SCN. In contrast, hippocampal gene expression remains rhythmic, mirroring object and visuospatial performance. Strikingly, Per1 and Fos expression in the olfactory bulb is reversed, mirroring the inverted olfactory performance. Temporal desynchrony among these regions does not result in arrhythmicity because core body temperature and exploratory activity rhythms persist under rLL. Our data provide the first demonstration that abnormal lighting conditions can give rise to temporal desynchrony between autonomous circadian oscillators in different regions, with different consequences for performance across different sensory domains. Such a dispersed network of dissociable circadian oscillators may provide greater flexibility when faced with conflicting environmental signals. SIGNIFICANCE STATEMENT A master circadian clock in the suprachiasmatic nuclei (SCN) of the hypothalamus regulates physiology and behavior across the 24 h day by

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

Effects of Marijuana on Ictal and Interictal EEG Activities in Idiopathic Generalized Epilepsy.

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Sivakumar, Sanjeev; Zutshi, Deepti; Seraji-Bozorgzad, Navid; Shah, Aashit K

2017-01-01

Marijuana-based treatment for refractory epilepsy shows promise in surveys, case series, and clinical trials. However, literature on their EEG effects is sparse. Our objective is to analyze the effect of marijuana on EEG in a 24-year-old patient with idiopathic generalized epilepsy treated with cannabis. We blindly reviewed 3 long-term EEGs-a 24-hour study while only on antiepileptic drugs, a 72-hour EEG with Cannabis indica smoked on days 1 and 3 in addition to antiepileptic drugs, and a 48-hour EEG with combination C indica/sativa smoked on day 1 plus antiepileptic drugs. Generalized spike-wave discharges and diffuse paroxysmal fast activity were categorized as interictal and ictal, based on duration of less than 10 seconds or greater, respectively. Data from three studies concatenated into contiguous time series, with usage of marijuana modeled as time-dependent discrete variable while interictal and ictal events constituted dependent variables. Analysis of variance as initial test for significance followed by time series analysis using Generalized Autoregressive Conditional Heteroscedasticity model was performed. Statistical significance for lower interictal events (analysis of variance P = 0.001) was seen during C indica use, but not for C indica/sativa mixture (P = 0.629) or ictal events (P = 0.087). However, time series analysis revealed a significant inverse correlation between marijuana use, with interictal (P EEG data, we demonstrate a decrease in interictal and ictal electrographic events during marijuana use. Larger samples of patients and EEG, with standardized cannabinoid formulation and dosing, are needed to validate our findings.

The application of particle filters in single trial event-related potential estimation

International Nuclear Information System (INIS)

Mohseni, Hamid R; Nazarpour, Kianoush; Sanei, Saeid; Wilding, Edward L

2009-01-01

In this paper, an approach for the estimation of single trial event-related potentials (ST-ERPs) using particle filters (PFs) is presented. The method is based on recursive Bayesian mean square estimation of ERP wavelet coefficients using their previous estimates as prior information. To enable a performance evaluation of the approach in the Gaussian and non-Gaussian distributed noise conditions, we added Gaussian white noise (GWN) and real electroencephalogram (EEG) signals recorded during rest to the simulated ERPs. The results were compared to that of the Kalman filtering (KF) approach demonstrating the robustness of the PF over the KF to the added GWN noise. The proposed method also outperforms the KF when the assumption about the Gaussianity of the noise is violated. We also applied this technique to real EEG potentials recorded in an odd-ball paradigm and investigated the correlation between the amplitude and the latency of the estimated ERP components. Unlike the KF method, for the PF there was a statistically significant negative correlation between amplitude and latency of the estimated ERPs, matching previous neurophysiological findings

Brain Oscillations in Sport: Toward EEG Biomarkers of Performance.

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Cheron, Guy; Petit, Géraldine; Cheron, Julian; Leroy, Axelle; Cebolla, Anita; Cevallos, Carlos; Petieau, Mathieu; Hoellinger, Thomas; Zarka, David; Clarinval, Anne-Marie; Dan, Bernard

2016-01-01

Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The non-invasive nature of high-density electroencephalography (EEG) recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical applications of EEG and event-related potentials (ERP) in sport. In this context, the hypotheses of unified brain rhythms and continuity between wake and sleep states should provide a functional template for EEG biomarkers in sport. The oscillations in the thalamo-cortical and hippocampal circuitry including the physiology of the place cells and the grid cells provide a frame of reference for the analysis of delta, theta, beta, alpha (incl.mu), and gamma oscillations recorded in the space field of human performance. Based on recent neuronal models facilitating the distinction between the different dynamic regimes (selective gating and binding) in these different oscillations we suggest an integrated approach articulating together the classical biomechanical factors (3D movements and EMG) and the high-density EEG and ERP signals to allow finer mathematical analysis to optimize sport performance, such as microstates, coherency/directionality analysis and neural generators.

Brain oscillations in sport: toward EEG biomakers of performance

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Guy eCheron

2016-02-01

Full Text Available Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The noninvasive nature of high-density electroencephalography (EEG recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical applications of EEG and event-related potentials (ERP in sport. In this context, the hypotheses of unified brain rhythms and continuity between wake and sleep states should provide a functional template for EEG biomarkers in sport. The oscillations in the thalamo-cortical and hippocampal circuitry including the physiology of the place cells and the grid cells provide a frame of reference for the analysis of delta, theta, beta, alpha (incl.mu and gamma oscillations recorded in the space field of human performance. Based on recent neuronal models facilitating the distinction between the different dynamic regimes (selective gating and binding in these different oscillations we suggest an integrated approach articulating together the classical biomechanical factors (3D movements and EMG and the high-density EEG and ERP signals to allow finer mathematical analysis to optimize sport performance, such as microstates, coherency/directionality analysis and neural generators.

Brain Oscillations in Sport: Toward EEG Biomarkers of Performance

Science.gov (United States)

Cheron, Guy; Petit, Géraldine; Cheron, Julian; Leroy, Axelle; Cebolla, Anita; Cevallos, Carlos; Petieau, Mathieu; Hoellinger, Thomas; Zarka, David; Clarinval, Anne-Marie; Dan, Bernard

2016-01-01

Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The non-invasive nature of high-density electroencephalography (EEG) recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical applications of EEG and event-related potentials (ERP) in sport. In this context, the hypotheses of unified brain rhythms and continuity between wake and sleep states should provide a functional template for EEG biomarkers in sport. The oscillations in the thalamo-cortical and hippocampal circuitry including the physiology of the place cells and the grid cells provide a frame of reference for the analysis of delta, theta, beta, alpha (incl.mu), and gamma oscillations recorded in the space field of human performance. Based on recent neuronal models facilitating the distinction between the different dynamic regimes (selective gating and binding) in these different oscillations we suggest an integrated approach articulating together the classical biomechanical factors (3D movements and EMG) and the high-density EEG and ERP signals to allow finer mathematical analysis to optimize sport performance, such as microstates, coherency/directionality analysis and neural generators. PMID:26955362

Feature selection using angle modulated simulated Kalman filter for peak classification of EEG signals.

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Adam, Asrul; Ibrahim, Zuwairie; Mokhtar, Norrima; Shapiai, Mohd Ibrahim; Mubin, Marizan; Saad, Ismail

2016-01-01

In the existing electroencephalogram (EEG) signals peak classification research, the existing models, such as Dumpala, Acir, Liu, and Dingle peak models, employ different set of features. However, all these models may not be able to offer good performance for various applications and it is found to be problem dependent. Therefore, the objective of this study is to combine all the associated features from the existing models before selecting the best combination of features. A new optimization algorithm, namely as angle modulated simulated Kalman filter (AMSKF) will be employed as feature selector. Also, the neural network random weight method is utilized in the proposed AMSKF technique as a classifier. In the conducted experiment, 11,781 samples of peak candidate are employed in this study for the validation purpose. The samples are collected from three different peak event-related EEG signals of 30 healthy subjects; (1) single eye blink, (2) double eye blink, and (3) eye movement signals. The experimental results have shown that the proposed AMSKF feature selector is able to find the best combination of features and performs at par with the existing related studies of epileptic EEG events classification.

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

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Joshua H Balsters

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

Improving the Specificity of EEG for Diagnosing Alzheimer's Disease

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François-B. Vialatte

2011-01-01

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

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

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

2014-08-01

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

EEG potentials associated with artificial grammar learning in the primate brain.

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Attaheri, Adam; Kikuchi, Yukiko; Milne, Alice E; Wilson, Benjamin; Alter, Kai; Petkov, Christopher I

2015-09-01

Electroencephalography (EEG) has identified human brain potentials elicited by Artificial Grammar (AG) learning paradigms, which present participants with rule-based sequences of stimuli. Nonhuman animals are sensitive to certain AGs; therefore, evaluating which EEG Event Related Potentials (ERPs) are associated with AG learning in nonhuman animals could identify evolutionarily conserved processes. We recorded EEG potentials during an auditory AG learning experiment in two Rhesus macaques. The animals were first exposed to sequences of nonsense words generated by the AG. Then surface-based ERPs were recorded in response to sequences that were 'consistent' with the AG and 'violation' sequences containing illegal transitions. The AG violations strongly modulated an early component, potentially homologous to the Mismatch Negativity (mMMN), a P200 and a late frontal positivity (P500). The macaque P500 is similar in polarity and time of occurrence to a late EEG positivity reported in human AG learning studies but might differ in functional role. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Combining features from ERP components in single-trial EEG for discriminating four-category visual objects

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Wang, Changming; Xiong, Shi; Hu, Xiaoping; Yao, Li; Zhang, Jiacai

2012-10-01

Categorization of images containing visual objects can be successfully recognized using single-trial electroencephalograph (EEG) measured when subjects view images. Previous studies have shown that task-related information contained in event-related potential (ERP) components could discriminate two or three categories of object images. In this study, we investigated whether four categories of objects (human faces, buildings, cats and cars) could be mutually discriminated using single-trial EEG data. Here, the EEG waveforms acquired while subjects were viewing four categories of object images were segmented into several ERP components (P1, N1, P2a and P2b), and then Fisher linear discriminant analysis (Fisher-LDA) was used to classify EEG features extracted from ERP components. Firstly, we compared the classification results using features from single ERP components, and identified that the N1 component achieved the highest classification accuracies. Secondly, we discriminated four categories of objects using combining features from multiple ERP components, and showed that combination of ERP components improved four-category classification accuracies by utilizing the complementarity of discriminative information in ERP components. These findings confirmed that four categories of object images could be discriminated with single-trial EEG and could direct us to select effective EEG features for classifying visual objects.

Early post-traumatic epilepsy following serious craniocerebral trauma, with emphasis on EEG and CT findings

International Nuclear Information System (INIS)

Goeller, T.

1981-01-01

In the study on hand, eighty patients with craniocerebral trauma were regularly examined by EEG. Twenty-two of the patients had clinically observable fits. In five other patients, only the EEG revealed paroxysmal events in the first week following trauma. In six patients who were observed to have fits, no corresponding EEG equivalent could be recorded for technical reasons. In case of early epileptical fits, CT always revealed an intercranial hemorrhage, except for two cases, the findings being in agreement with the lateral location of the focus as determined by EEG. The seriousness of cranial injury was directly related to the number of fits observed in the first post-traumatic week. Patients over thirty showed an increase of eraly post-traumatic fits. The lethality of patients with early fits was significantly increased as compared with patients without early fits. EEG examination as early as possible after the craniocerebral trauma is necessary and useful, both for detection of lesions and for appropriate drug therapy. (orig./MG) [de

Combining EEG, MIDI, and motion capture techniques for investigating musical performance.

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Maidhof, Clemens; Kästner, Torsten; Makkonen, Tommi

2014-03-01

This article describes a setup for the simultaneous recording of electrophysiological data (EEG), musical data (MIDI), and three-dimensional movement data. Previously, each of these three different kinds of measurements, conducted sequentially, has been proven to provide important information about different aspects of music performance as an example of a demanding multisensory motor skill. With the method described here, it is possible to record brain-related activity and movement data simultaneously, with accurate timing resolution and at relatively low costs. EEG and MIDI data were synchronized with a modified version of the FTAP software, sending synchronization signals to the EEG recording device simultaneously with keypress events. Similarly, a motion capture system sent synchronization signals simultaneously with each recorded frame. The setup can be used for studies investigating cognitive and motor processes during music performance and music-like tasks--for example, in the domains of motor control, learning, music therapy, or musical emotions. Thus, this setup offers a promising possibility of a more behaviorally driven analysis of brain activity.

Event-Related Potentials for Post-Error and Post-Conflict Slowing

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Chang, Andrew; Chen, Chien-Chung; Li, Hsin-Hung; Li, Chiang-Shan R.

2014-01-01

In a reaction time task, people typically slow down following an error or conflict, each called post-error slowing (PES) and post-conflict slowing (PCS). Despite many studies of the cognitive mechanisms, the neural responses of PES and PCS continue to be debated. In this study, we combined high-density array EEG and a stop-signal task to examine event-related potentials of PES and PCS in sixteen young adult participants. The results showed that the amplitude of N2 is greater during PES but not PCS. In contrast, the peak latency of N2 is longer for PCS but not PES. Furthermore, error-positivity (Pe) but not error-related negativity (ERN) was greater in the stop error trials preceding PES than non-PES trials, suggesting that PES is related to participants' awareness of the error. Together, these findings extend earlier work of cognitive control by specifying the neural correlates of PES and PCS in the stop signal task. PMID:24932780

EEG activity during estral cycle in the rat.

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

1992-10-01

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

Beta event-related desynchronization as an index of individual differences in processing human facial expression: further investigations of autistic traits in typically developing adults

OpenAIRE

Cooper, Nicholas R.; Simpson, Andrew; Till, Amy; Simmons, Kelly; Puzzo, Ignazio

2013-01-01

The human mirror neuron system (hMNS) has been associated with various forms of social cognition and affective processing including vicarious experience. It has also been proposed that a faulty hMNS may underlie some of the deficits seen in the autism spectrum disorders (ASDs). In the present study we set out to investigate whether emotional facial expressions could modulate a putative EEG index of hMNS activation (mu suppression) and if so, would this differ according to the individual level...

Intracranial EEG correlates of implicit relational inference within the hippocampus.

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Reber, T P; Do Lam, A T A; Axmacher, N; Elger, C E; Helmstaedter, C; Henke, K; Fell, J

2016-01-01

Drawing inferences from past experiences enables adaptive behavior in future situations. Inference has been shown to depend on hippocampal processes. Usually, inference is considered a deliberate and effortful mental act which happens during retrieval, and requires the focus of our awareness. Recent fMRI studies hint at the possibility that some forms of hippocampus-dependent inference can also occur during encoding and possibly also outside of awareness. Here, we sought to further explore the feasibility of hippocampal implicit inference, and specifically address the temporal evolution of implicit inference using intracranial EEG. Presurgical epilepsy patients with hippocampal depth electrodes viewed a sequence of word pairs, and judged the semantic fit between two words in each pair. Some of the word pairs entailed a common word (e.g., "winter-red," "red-cat") such that an indirect relation was established in following word pairs (e.g., "winter-cat"). The behavioral results suggested that drawing inference implicitly from past experience is feasible because indirect relations seemed to foster "fit" judgments while the absence of indirect relations fostered "do not fit" judgments, even though the participants were unaware of the indirect relations. A event-related potential (ERP) difference emerging 400 ms post-stimulus was evident in the hippocampus during encoding, suggesting that indirect relations were already established automatically during encoding of the overlapping word pairs. Further ERP differences emerged later post-stimulus (1,500 ms), were modulated by the participants' responses and were evident during encoding and test. Furthermore, response-locked ERP effects were evident at test. These ERP effects could hence be a correlate of the interaction of implicit memory with decision-making. Together, the data map out a time-course in which the hippocampus automatically integrates memories from discrete but related episodes to implicitly influence future

Psychogenic seizures and frontal disconnection: EEG synchronisation study.

Science.gov (United States)

Knyazeva, Maria G; Jalili, Mahdi; Frackowiak, Richard S; Rossetti, Andrea O

2011-05-01

Psychogenic non-epileptic seizures (PNES) are paroxysmal events that, in contrast to epileptic seizures, are related to psychological causes without the presence of epileptiform EEG changes. Recent models suggest a multifactorial basis for PNES. A potentially paramount, but currently poorly understood factor is the interplay between psychiatric features and a specific vulnerability of the brain leading to a clinical picture that resembles epilepsy. Hypothesising that functional cerebral network abnormalities may predispose to the clinical phenotype, the authors undertook a characterisation of the functional connectivity in PNES patients. The authors analysed the whole-head surface topography of multivariate phase synchronisation (MPS) in interictal high-density EEG of 13 PNES patients as compared with 13 age- and sex-matched controls. MPS mapping reduces the wealth of dynamic data obtained from high-density EEG to easily readable synchronisation maps, which provide an unbiased overview of any changes in functional connectivity associated with distributed cortical abnormalities. The authors computed MPS maps for both Laplacian and common-average-reference EEGs. In a between-group comparison, only patchy, non-uniform changes in MPS survived conservative statistical testing. However, against the background of these unimpressive group results, the authors found widespread inverse correlations between individual PNES frequency and MPS within the prefrontal and parietal cortices. PNES appears to be associated with decreased prefrontal and parietal synchronisation, possibly reflecting dysfunction of networks within these regions.

Brain-computer interface training combined with transcranial direct current stimulation in patients with chronic severe hemiparesis: Proof of concept study.

Science.gov (United States)

Kasashima-Shindo, Yuko; Fujiwara, Toshiyuki; Ushiba, Junichi; Matsushika, Yayoi; Kamatani, Daiki; Oto, Misa; Ono, Takashi; Nishimoto, Atsuko; Shindo, Keiichiro; Kawakami, Michiyuki; Tsuji, Tetsuya; Liu, Meigen

2015-04-01

Brain-computer interface technology has been applied to stroke patients to improve their motor function. Event-related desynchronization during motor imagery, which is used as a brain-computer interface trigger, is sometimes difficult to detect in stroke patients. Anodal transcranial direct current stimulation (tDCS) is known to increase event-related desynchronization. This study investigated the adjunctive effect of anodal tDCS for brain-computer interface training in patients with severe hemiparesis. Eighteen patients with chronic stroke. A non-randomized controlled study. Subjects were divided between a brain-computer interface group and a tDCS- brain-computer interface group and participated in a 10-day brain-computer interface training. Event-related desynchronization was detected in the affected hemisphere during motor imagery of the affected fingers. The tDCS-brain-computer interface group received anodal tDCS before brain-computer interface training. Event-related desynchronization was evaluated before and after the intervention. The Fugl-Meyer Assessment upper extremity motor score (FM-U) was assessed before, immediately after, and 3 months after, the intervention. Event-related desynchronization was significantly increased in the tDCS- brain-computer interface group. The FM-U was significantly increased in both groups. The FM-U improvement was maintained at 3 months in the tDCS-brain-computer interface group. Anodal tDCS can be a conditioning tool for brain-computer interface training in patients with severe hemiparetic stroke.

SVM detection of epileptiform activity in routine EEG.

LENUS (Irish Health Repository)

Kelleher, Daniel

2010-01-01

Routine electroencephalogram (EEG) is an important test in aiding the diagnosis of patients with suspected epilepsy. These recordings typically last 20-40 minutes, during which signs of abnormal activity (spikes, sharp waves) are looked for in the EEG trace. It is essential that events of short duration are detected during the routine EEG test. The work presented in this paper examines the effect of changing a range of input values to the detection system on its ability to distinguish between normal and abnormal EEG activity. It is shown that the length of analysis window in the range of 0.5s to 1s are well suited to the task. Additionally, it is reported that patient specific systems should be used where possible due to their better performance.

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

International Nuclear Information System (INIS)

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

1998-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

1998-07-01

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

Mutual information measures applied to EEG signals for sleepiness characterization.

Science.gov (United States)

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

2015-03-01

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

Different slopes for different folks: alpha and delta EEG power predict subsequent video game learning rate and improvements in cognitive control tasks.

Science.gov (United States)

Mathewson, Kyle E; Basak, Chandramallika; Maclin, Edward L; Low, Kathy A; Boot, Walter R; Kramer, Arthur F; Fabiani, Monica; Gratton, Gabriele

2012-12-01

We hypothesized that control processes, as measured using electrophysiological (EEG) variables, influence the rate of learning of complex tasks. Specifically, we measured alpha power, event-related spectral perturbations (ERSPs), and event-related brain potentials during early training of the Space Fortress task, and correlated these measures with subsequent learning rate and performance in transfer tasks. Once initial score was partialled out, the best predictors were frontal alpha power and alpha and delta ERSPs, but not P300. By combining these predictors, we could explain about 50% of the learning rate variance and 10%-20% of the variance in transfer to other tasks using only pretraining EEG measures. Thus, control processes, as indexed by alpha and delta EEG oscillations, can predict learning and skill improvements. The results are of potential use to optimize training regimes. Copyright © 2012 Society for Psychophysiological Research.

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

Science.gov (United States)

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

2016-12-01

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

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. ...

[Event-related EEG potentials associated with error detection in psychiatric disorder: literature review].

Science.gov (United States)

Balogh, Lívia; Czobor, Pál

2010-01-01

Error-related bioelectric signals constitute a special subgroup of event-related potentials. Researchers have identified two evoked potential components to be closely related to error processing, namely error-related negativity (ERN) and error-positivity (Pe), and they linked these to specific cognitive functions. In our article first we give a brief description of these components, then based on the available literature, we review differences in error-related evoked potentials observed in patients across psychiatric disorders. The PubMed and Medline search engines were used in order to identify all relevant articles, published between 2000 and 2009. For the purpose of the current paper we reviewed publications summarizing results of clinical trials. Patients suffering from schizophrenia, anorexia nervosa or borderline personality disorder exhibited a decrease in the amplitude of error-negativity when compared with healthy controls, while in cases of depression and anxiety an increase in the amplitude has been observed. Some of the articles suggest specific personality variables, such as impulsivity, perfectionism, negative emotions or sensitivity to punishment to underlie these electrophysiological differences. Research in the field of error-related electric activity has come to the focus of psychiatry research only recently, thus the amount of available data is significantly limited. However, since this is a relatively new field of research, the results available at present are noteworthy and promising for future electrophysiological investigations in psychiatric disorders.

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.

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.

Calibrating EEG-based motor imagery brain-computer interface from passive movement.

Science.gov (United States)

Ang, Kai Keng; Guan, Cuntai; Wang, Chuanchu; Phua, Kok Soon; Tan, Adrian Hock Guan; Chin, Zheng Yang

2011-01-01

EEG data from performing motor imagery are usually collected to calibrate a subject-specific model for classifying the EEG data during the evaluation phase of motor imagery Brain-Computer Interface (BCI). However, there is no direct objective measure to determine if a subject is performing motor imagery correctly for proper calibration. Studies have shown that passive movement, which is directly observable, induces Event-Related Synchronization patterns that are similar to those induced from motor imagery. Hence, this paper investigates the feasibility of calibrating EEG-based motor imagery BCI from passive movement. EEG data of 12 healthy subjects were collected during motor imagery and passive movement of the hand by a haptic knob robot. The calibration models using the Filter Bank Common Spatial Pattern algorithm on the EEG data from motor imagery were compared against using the EEG data from passive movement. The performances were compared based on the 10×10-fold cross-validation accuracies of the calibration data, and off-line session-to-session transfer kappa values to other sessions of motor imagery performed on another day. The results showed that the calibration performed using passive movement yielded higher model accuracy and off-line session-to-session transfer (73.6% and 0.354) than the calibration performed using motor imagery (71.3% and 0.311), and no significant differences were observed between the two groups (p=0.20, 0.23). Hence, this study shows that it is feasible to calibrate EEG-based motor imagery BCI from passive movement.

Joint time-frequency analysis of EEG signals based on a phase-space interpretation of the recording process

Science.gov (United States)

Testorf, M. E.; Jobst, B. C.; Kleen, J. K.; Titiz, A.; Guillory, S.; Scott, R.; Bujarski, K. A.; Roberts, D. W.; Holmes, G. L.; Lenck-Santini, P.-P.

2012-10-01

Time-frequency transforms are used to identify events in clinical EEG data. Data are recorded as part of a study for correlating the performance of human subjects during a memory task with pathological events in the EEG, called spikes. The spectrogram and the scalogram are reviewed as tools for evaluating spike activity. A statistical evaluation of the continuous wavelet transform across trials is used to quantify phase-locking events. For simultaneously improving the time and frequency resolution, and for representing the EEG of several channels or trials in a single time-frequency plane, a multichannel matching pursuit algorithm is used. Fundamental properties of the algorithm are discussed as well as preliminary results, which were obtained with clinical EEG data.

The changes in relation of auditory and visual input activity between hemispheres analized in cartographic EEG in a child with hyperactivity syndrome

Directory of Open Access Journals (Sweden)

Radičević Zoran

2015-01-01

Full Text Available The paper discusses the changes in relations of visual and auditory inputs between the hemispheres in a child with hyperactive syndrome and its effects which may lead to better attention engagement in auditory and visual information analysis. The method included the use of cartographic EEG and clinical procedure in a 10-year-old boy with hyperactive syndrome and attention deficit disorder, who has theta dysfunction manifested in standard EEG. Cartographic EEG patterns was performed on NihonKohden Corporation, EEG - 1200K Neurofax apparatus in longitudinal bipolar electrode assembly schedule by utilizing10/20 International electrode positioning. Impedance was maintained below 5 kΩ, with not more than 1 kΩ differences between the electrodes. Lower filter was set at 0.53 Hz and higher filter at 35 Hz. Recording was performed in a quiet period and during stimulation procedures that include speech and language basis. Standard EEG and Neurofeedback (NFB treatment indicated higher theta load, alpha 2 and beta 1 activity measured in the cartographic EEG which was done after the relative failure of NFB treatment. After this, the NFB treatment was applied which lasted for six months, in a way that when the boy was reading, the visual input was enhanced to the left hemisphere and auditory input was reduced to the right hemisphere. Repeated EEG mapping analysis showed that there was a significant improvement, both in EEG findings as well as in attention, behavioural and learning disorders. The paper discusses some aspects of learning, attention and behaviour in relation to changes in the standard EEG, especially in cartographic EEG and NFB findings.

Short-Term Dosage Regimen for Stimulation-Induced Long-Lasting Desynchronization

Directory of Open Access Journals (Sweden)

Thanos Manos

2018-04-01

Full Text Available In this paper, we computationally generate hypotheses for dose-finding studies in the context of desynchronizing neuromodulation techniques. Abnormally strong neuronal synchronization is a hallmark of several brain disorders. Coordinated Reset (CR stimulation is a spatio-temporally patterned stimulation technique that specifically aims at disrupting abnormal neuronal synchrony. In networks with spike-timing-dependent plasticity CR stimulation may ultimately cause an anti-kindling, i.e., an unlearning of abnormal synaptic connectivity and neuronal synchrony. This long-lasting desynchronization was theoretically predicted and verified in several pre-clinical and clinical studies. We have shown that CR stimulation with rapidly varying sequences (RVS robustly induces an anti-kindling at low intensities e.g., if the CR stimulation frequency (i.e., stimulus pattern repetition rate is in the range of the frequency of the neuronal oscillation. In contrast, CR stimulation with slowly varying sequences (SVS turned out to induce an anti-kindling more strongly, but less robustly with respect to variations of the CR stimulation frequency. Motivated by clinical constraints and inspired by the spacing principle of learning theory, in this computational study we propose a short-term dosage regimen that enables a robust anti-kindling effect of both RVS and SVS CR stimulation, also for those parameter values where RVS and SVS CR stimulation previously turned out to be ineffective. Intriguingly, for the vast majority of parameter values tested, spaced multishot CR stimulation with demand-controlled variation of stimulation frequency and intensity caused a robust and pronounced anti-kindling. In contrast, spaced CR stimulation with fixed stimulation parameters as well as singleshot CR stimulation of equal integral duration failed to improve the stimulation outcome. In the model network under consideration, our short-term dosage regimen enables to robustly induce

Short-Term Dosage Regimen for Stimulation-Induced Long-Lasting Desynchronization.

Science.gov (United States)

Manos, Thanos; Zeitler, Magteld; Tass, Peter A

2018-01-01

In this paper, we computationally generate hypotheses for dose-finding studies in the context of desynchronizing neuromodulation techniques. Abnormally strong neuronal synchronization is a hallmark of several brain disorders. Coordinated Reset (CR) stimulation is a spatio-temporally patterned stimulation technique that specifically aims at disrupting abnormal neuronal synchrony. In networks with spike-timing-dependent plasticity CR stimulation may ultimately cause an anti-kindling, i.e., an unlearning of abnormal synaptic connectivity and neuronal synchrony. This long-lasting desynchronization was theoretically predicted and verified in several pre-clinical and clinical studies. We have shown that CR stimulation with rapidly varying sequences (RVS) robustly induces an anti-kindling at low intensities e.g., if the CR stimulation frequency (i.e., stimulus pattern repetition rate) is in the range of the frequency of the neuronal oscillation. In contrast, CR stimulation with slowly varying sequences (SVS) turned out to induce an anti-kindling more strongly, but less robustly with respect to variations of the CR stimulation frequency. Motivated by clinical constraints and inspired by the spacing principle of learning theory, in this computational study we propose a short-term dosage regimen that enables a robust anti-kindling effect of both RVS and SVS CR stimulation, also for those parameter values where RVS and SVS CR stimulation previously turned out to be ineffective. Intriguingly, for the vast majority of parameter values tested, spaced multishot CR stimulation with demand-controlled variation of stimulation frequency and intensity caused a robust and pronounced anti-kindling. In contrast, spaced CR stimulation with fixed stimulation parameters as well as singleshot CR stimulation of equal integral duration failed to improve the stimulation outcome. In the model network under consideration, our short-term dosage regimen enables to robustly induce long

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

Science.gov (United States)

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

2015-01-15

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

Kernel PLS Estimation of Single-trial Event-related Potentials

Science.gov (United States)

Rosipal, Roman; Trejo, Leonard J.

2004-01-01

Nonlinear kernel partial least squaes (KPLS) regressior, is a novel smoothing approach to nonparametric regression curve fitting. We have developed a KPLS approach to the estimation of single-trial event related potentials (ERPs). For improved accuracy of estimation, we also developed a local KPLS method for situations in which there exists prior knowledge about the approximate latency of individual ERP components. To assess the utility of the KPLS approach, we compared non-local KPLS and local KPLS smoothing with other nonparametric signal processing and smoothing methods. In particular, we examined wavelet denoising, smoothing splines, and localized smoothing splines. We applied these methods to the estimation of simulated mixtures of human ERPs and ongoing electroencephalogram (EEG) activity using a dipole simulator (BESA). In this scenario we considered ongoing EEG to represent spatially and temporally correlated noise added to the ERPs. This simulation provided a reasonable but simplified model of real-world ERP measurements. For estimation of the simulated single-trial ERPs, local KPLS provided a level of accuracy that was comparable with or better than the other methods. We also applied the local KPLS method to the estimation of human ERPs recorded in an experiment on co,onitive fatigue. For these data, the local KPLS method provided a clear improvement in visualization of single-trial ERPs as well as their averages. The local KPLS method may serve as a new alternative to the estimation of single-trial ERPs and improvement of ERP averages.

Analysis and correction of ballistocardiogram contamination of EEG recordings in MR

International Nuclear Information System (INIS)

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

2005-01-01

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

Event-related potentials elicited by social commerce and electronic-commerce reviews.

Science.gov (United States)

Bai, Yan; Yao, Zhong; Cong, Fengyu; Zhang, Linlin

2015-12-01

There is an increasing interest regarding the use of electroencephalography (EEG) in social commerce and electronic commerce (e-commerce) research. There are several reviews in the field of social commerce or e-commerce; these have great potential value and mining them is fundamental and significant. To our knowledge, EEG is rarely applied to study these. In this study, we examined the neural correlates of social commerce reviews (SCRs) and e-commerce reviews (ECRs) by using them as stimuli to evoke event-related potentials. All SCRs were from friends through a social media platform, whereas ECRs were from strangers through an e-commerce platform. The experimental design was similar to that of a priming paradigm, and included 40 pairs of stimuli consisting of product information (prime stimulus) and reviews (target stimulus). The results showed that the P300 component was successfully evoked by SCR and ECR stimuli. Moreover, the P300 components elicited by SCRs had higher amplitudes than those elicited by ECRs. These findings indicate that participants paid more attention to SCRs than to ECRs. In addition, the associations between neural responses and reviews in social commerce have the potential to assist companies in studying consumer behaviors, thus permitting them to enhance their social commerce strategies.

Immediate relativity: EEG reveals early engagement of comparison in social information processing.

Science.gov (United States)

Ohmann, Katharina; Stahl, Jutta; Mussweiler, Thomas; Kedia, Gayannée

2016-11-01

A wide array of social decisions relies on social comparisons. As such, these decisions require fast access to relative information. Therefore, we expect that signatures of the comparative process should be observable in electrophysiological components at an early stage of information processing. However, to date, little is known about the neural time course of social target comparisons. Therefore, we tested this hypothesis in 2 electroencephalography (EEG) studies using a social distance effect paradigm. The distance effect capitalizes on the fact that stimuli close on a certain dimension take longer to compare than stimuli clearly differing on this dimension. Here, we manipulated the distance of face characteristics regarding their levels of attractiveness (Study 1) and trustworthiness (Study 2), 2 essential social dimensions. In both studies, size comparisons served as a nonsocial control condition. In Study 1, distance related effects were apparent 170 ms (vertex positive potential, VPP) and 200 ms (N2) after stimulus onset for attractiveness comparisons. In Study 2, trustworthiness comparisons took effect already after 100 ms (N1) and likewise carried over to an event-related N2. Remarkably, we observed a similar temporal pattern for social (attractiveness, trustworthiness) and nonsocial (size) dimensions. These results speak in favor of an early encoding of comparative information and emphasize the primary role of comparison in social information processing. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A new method to detect event-related potentials based on Pearson's correlation.

Science.gov (United States)

Giroldini, William; Pederzoli, Luciano; Bilucaglia, Marco; Melloni, Simone; Tressoldi, Patrizio

2016-12-01

Event-related potentials (ERPs) are widely used in brain-computer interface applications and in neuroscience.  Normal EEG activity is rich in background noise, and therefore, in order to detect ERPs, it is usually necessary to take the average from multiple trials to reduce the effects of this noise.  The noise produced by EEG activity itself is not correlated with the ERP waveform and so, by calculating the average, the noise is decreased by a factor inversely proportional to the square root of N , where N is the number of averaged epochs. This is the easiest strategy currently used to detect ERPs, which is based on calculating the average of all ERP's waveform, these waveforms being time- and phase-locked.  In this paper, a new method called GW6 is proposed, which calculates the ERP using a mathematical method based only on Pearson's correlation. The result is a graph with the same time resolution as the classical ERP and which shows only positive peaks representing the increase-in consonance with the stimuli-in EEG signal correlation over all channels.  This new method is also useful for selectively identifying and highlighting some hidden components of the ERP response that are not phase-locked, and that are usually hidden in the standard and simple method based on the averaging of all the epochs.  These hidden components seem to be caused by variations (between each successive stimulus) of the ERP's inherent phase latency period (jitter), although the same stimulus across all EEG channels produces a reasonably constant phase. For this reason, this new method could be very helpful to investigate these hidden components of the ERP response and to develop applications for scientific and medical purposes. Moreover, this new method is more resistant to EEG artifacts than the standard calculations of the average and could be very useful in research and neurology.  The method we are proposing can be directly used in the form of a process written in the well

Tele-transmission of EEG recordings.

Science.gov (United States)

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

2015-03-01

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

Combining and comparing EEG, peripheral physiology and eye-related measures for the assessment of mental workload

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Maarten Andreas Hogervorst

2014-10-01

Full Text Available While studies exist that compare different physiological variables with respect to their association with mental workload, it is still largely unclear which variables supply the best information about momentary workload of an individual and what is the benefit of combining them. We investigated workload using the n-back task, controlling for body movements and visual input. We recorded EEG, skin conductance, respiration, ECG, pupil size and eye blinks of 14 subjects. Various variables were extracted from these recordings and used as features in individually tuned classification models. Online classification was simulated by using the first part of the data as training set and the last part of the data for testing the models. The results indicate that EEG performs best, followed by eye related measures and peripheral physiology. Combining variables from different sensors did not significantly improve workload assessment over the best performing sensor alone. Best classification accuracy, a little over 90% (SD 4%, was reached for distinguishing between high and low workload on the basis of 2 minute segments of EEG and eye related variables. A similar and not significantly different performance of 86% (SD 5% was reached using only EEG from single electrode location Pz.

Electrophysiological Brain Activity during the Control of a Motor Imagery-Based Brain–Computer Interface

Czech Academy of Sciences Publication Activity Database

Frolov, A. A.; Aziatskaya, G.A.; Bobrov, P.D.; Luykmanov, R. Kh.; Fedotova, I.R.; Húsek, Dušan; Snášel, V.

2017-01-01

Roč. 43, č. 5 (2017), s. 501-511 ISSN 0362-1197 Institutional support: RVO:67985807 Keywords : brain–computer interface * neurointerface * EEG * motor imagery * EEG rhythm synchronization and desynchronization * independent component analysis * EEG inverse problem * neurorehabilitation Subject RIV: IN - Informatics, Computer Science OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

On the neural mechanisms underlying the protective function of retroactive cuing against perceptual interference: Evidence by event-related potentials of the EEG.

Science.gov (United States)

Schneider, Daniel; Barth, Anna; Getzmann, Stephan; Wascher, Edmund

2017-03-01

This EEG study investigated the protective effect of retroactive attentional focusing on working memory. To this effect, we used a visuo-spatial working memory task and presented block-wise distractor displays after working memory contents had been updated by means of a retroactive cue (retro-cue). Retroactive attention attenuated the interfering effect of distractors on memory precision. The reduction of working memory load by means of a selective retro-cue was reflected by a decline of a negative slow wave over parietal sites. Posterior N1 to the distractor was reduced following a selective retro-cue compared to a neutral retro-cue condition, most notably at left hemispheric sites. P3b referred to the distractor was suppressed completely only following a selective retro-cue. This suggests that focusing on only a subset of visuo-spatial information represented in working memory releases cognitive resources for preventing the in-depth processing of subsequently irrelevant visual events, thereby inhibiting their transfer into working memory. Copyright © 2017 Elsevier B.V. All rights reserved.

Magnetic resonance imaging in relation to EEG epileptic foci in tuberous sclerosis

International Nuclear Information System (INIS)

Tamaki, Kyoko; Okuno, Takehiko; Ito, Masatoshi; Asato, Reinin; Konishi, Junji; Mikawa, Haruki

1990-01-01

In 20 patients with tuberous sclerosis (TS), who were sequentially treated for epilepsy at our clinic, the high signal lesions in the cerebral cortex and subcortex detected on T2 weighted magnetic resonance imaging (MRI) were compared with the interictal EEG findings. In four cases who showed a unilateral distribution of the MRI lesions, there was a good correlation between the laterality of the affected lobes and the localization of the EEG epileptic foci. Thirteen cases with more than four affected lobes in both hemispheres also showed bilateral epileptic foci on EEG. The MRI lesions in the occipital lobes showed the best correlation with the EEG epileptic foci, while the worst correlation was seen in the frontal lobes. In addition, the cases with four or more affected lobes without laterality on MRI are more likely to show bilateral synchronization on EEG. The prognosis of epilepsy in these cases was found to be rather poor. (author)

Standardized Computer-based Organized Reporting of EEG: SCORE

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

2013-01-01

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

Task-related modulation of anterior theta and posterior alpha EEG reflects top-down preparation

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Park Hae-Jeong

2010-06-01

Full Text Available Abstract Background Prestimulus EEG alpha activity in humans has been considered to reflect ongoing top-down preparation for the performance of subsequent tasks. Since theta oscillations may be related to poststimulus top-down processing, we investigated whether prestimulus EEG theta activity also reflects top-down cognitive preparation for a stimulus. Results We recorded EEG data from 15 healthy controls performing a color and shape discrimination task, and used the wavelet transformation to investigate the time course and power of oscillatory activity in the signals. We observed a relationship between both anterior theta and posterior alpha power in the prestimulus period and the type of subsequent task. Conclusions Since task-differences were reflected in both theta and alpha activities prior to stimulus onset, both prestimulus theta (particularly around the anterior region and prestimulus alpha (particularly around the posterior region activities may reflect prestimulus top-down preparation for the performance of subsequent tasks.

Beta event-related desynchronization as an index of individual differences in processing human facial expression: further investigations of autistic traits in typically developing adults.

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Nicholas Robert Cooper

2013-04-01

Full Text Available The human mirror neuron system (hMNS has been associated with various forms of social cognition and affective processing including vicarious experience. It has also been proposed that a faulty hMNS may underlie some of the deficits seen in the autism spectrum disorders. In the present study we set out to investigate whether emotional facial expressions could modulate a putative EEG index of hMNS activation (mu suppression and if so, would this differ according to the individual level of autistic traits (high versus low AQ score.Participants were presented with 3 second films of actors opening and closing their hands (classic hMNS mu-suppression protocol while simultaneously wearing happy, angry or neutral expressions. Mu-suppression was measured in the alpha and low beta bands. The low AQ group displayed greater low beta ERD to both angry and neutral expressions. The high AQ group displayed greater low beta ERD to angry than to happy expressions. There was also significantly more low beta ERD to happy faces for the low than for the high AQ group.In conclusion, an interesting interaction between AQ group and emotional expression revealed that hMNS activation can be modulated by emotional facial expressions and that this is differentiated according to individual differences in the level of autistic traits. The EEG index of hMNS activation (mu suppression seems to be a sensitive measure of the variability in facial processing in typically developing individuals with high and low self reported traits of autism.

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.

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

Directory of Open Access Journals (Sweden)

Aina Puce

2017-05-01

Full Text Available 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.

Spectral analysis of the EEG during halothane anaesthesia: Input-output relations

NARCIS (Netherlands)

Silva, F.H. Lopes da; Smith, N. Ty; Zwart, Aart; Nichols, W.W.

1. 1. The “Halothane-brain compartment” system was investigated in dogs. The input was the inspired concentration of Halothane. The output was the intensity of EEG spectral components. The EEG was analysed by a hybrid system (analogue filters and digital integration in a small computer). For the

Development of a Novel Motor Imagery Control Technique and Application in a Gaming Environment.

Science.gov (United States)

Li, Ting; Zhang, Jinhua; Xue, Tao; Wang, Baozeng

2017-01-01

We present a methodology for a hybrid brain-computer interface (BCI) system, with the recognition of motor imagery (MI) based on EEG and blink EOG signals. We tested the BCI system in a 3D Tetris and an analogous 2D game playing environment. To enhance player's BCI control ability, the study focused on feature extraction from EEG and control strategy supporting Game-BCI system operation. We compared the numerical differences between spatial features extracted with common spatial pattern (CSP) and the proposed multifeature extraction. To demonstrate the effectiveness of 3D game environment at enhancing player's event-related desynchronization (ERD) and event-related synchronization (ERS) production ability, we set the 2D Screen Game as the comparison experiment. According to a series of statistical results, the group performing MI in the 3D Tetris environment showed more significant improvements in generating MI-associated ERD/ERS. Analysis results of game-score indicated that the players' scores presented an obvious uptrend in 3D Tetris environment but did not show an obvious downward trend in 2D Screen Game. It suggested that the immersive and rich-control environment for MI would improve the associated mental imagery and enhance MI-based BCI skills.

Development of a Novel Motor Imagery Control Technique and Application in a Gaming Environment

Directory of Open Access Journals (Sweden)

Ting Li

2017-01-01

Full Text Available We present a methodology for a hybrid brain-computer interface (BCI system, with the recognition of motor imagery (MI based on EEG and blink EOG signals. We tested the BCI system in a 3D Tetris and an analogous 2D game playing environment. To enhance player’s BCI control ability, the study focused on feature extraction from EEG and control strategy supporting Game-BCI system operation. We compared the numerical differences between spatial features extracted with common spatial pattern (CSP and the proposed multifeature extraction. To demonstrate the effectiveness of 3D game environment at enhancing player’s event-related desynchronization (ERD and event-related synchronization (ERS production ability, we set the 2D Screen Game as the comparison experiment. According to a series of statistical results, the group performing MI in the 3D Tetris environment showed more significant improvements in generating MI-associated ERD/ERS. Analysis results of game-score indicated that the players’ scores presented an obvious uptrend in 3D Tetris environment but did not show an obvious downward trend in 2D Screen Game. It suggested that the immersive and rich-control environment for MI would improve the associated mental imagery and enhance MI-based BCI skills.

EEG potentials predict upcoming emergency brakings during simulated driving

Science.gov (United States)

Haufe, Stefan; Treder, Matthias S.; Gugler, Manfred F.; Sagebaum, Max; Curio, Gabriel; Blankertz, Benjamin

2011-10-01

Emergency braking assistance has the potential to prevent a large number of car crashes. State-of-the-art systems operate in two stages. Basic safety measures are adopted once external sensors indicate a potential upcoming crash. If further activity at the brake pedal is detected, the system automatically performs emergency braking. Here, we present the results of a driving simulator study indicating that the driver's intention to perform emergency braking can be detected based on muscle activation and cerebral activity prior to the behavioural response. Identical levels of predictive accuracy were attained using electroencephalography (EEG), which worked more quickly than electromyography (EMG), and using EMG, which worked more quickly than pedal dynamics. A simulated assistance system using EEG and EMG was found to detect emergency brakings 130 ms earlier than a system relying only on pedal responses. At 100 km h-1 driving speed, this amounts to reducing the braking distance by 3.66 m. This result motivates a neuroergonomic approach to driving assistance. Our EEG analysis yielded a characteristic event-related potential signature that comprised components related to the sensory registration of a critical traffic situation, mental evaluation of the sensory percept and motor preparation. While all these components should occur often during normal driving, we conjecture that it is their characteristic spatio-temporal superposition in emergency braking situations that leads to the considerable prediction performance we observed.

Age-related reduction of hemispheric lateralisation for spatial attention: An EEG study.

Science.gov (United States)

Learmonth, Gemma; Benwell, Christopher S Y; Thut, Gregor; Harvey, Monika

2017-06-01

A group-level visuospatial attention bias towards the left side of space (pseudoneglect) is consistently observed in young adults, which is likely to be a consequence of right parieto-occipital dominance for spatial attention. Conversely, healthy older adults demonstrate a rightward shift of this behavioural bias, hinting that an age-related reduction of lateralised neural activity may occur within visuospatial attention networks. We compared young (aged 18-25) and older (aged 60-80) adults on a computerised line bisection (landmark) task whilst recording event-related potentials (ERPs). Full-scalp cluster mass permutation tests identified a larger right parieto-occipital response for long lines compared to short in young adults (confirming Benwell et al., 2014a) which was not present in the older group. To specifically investigate age-related differences in hemispheric lateralisation, cluster mass permutation tests were then performed on a lateralised EEG dataset (RH-LH electrodes). A period of right lateralisation was identified in response to long lines in young adults, which was not present for short lines. No lateralised clusters were present for either long or short lines in older adults. Additionally, a reduced P300 component amplitude was observed for older adults relative to young. We therefore report here, for the first time, an age-related and stimulus-driven reduction of right hemispheric control of spatial attention in older adults. Future studies will need to determine whether this is representative of the normal aging process or an early indicator of neurodegeneration. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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

2013-01-01

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

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

Directory of Open Access Journals (Sweden)

Anna Elisabetta eVaudano

2013-11-01

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

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

Directory of Open Access Journals (Sweden)

Roberta eSclocco

2014-04-01

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

An EEG-Based Person Authentication System with Open-Set Capability Combining Eye Blinking Signals.

Science.gov (United States)

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

2018-01-24

The electroencephalogram (EEG) signal represents a subject's specific brain activity patterns and is considered as an ideal biometric given its superior forgery prevention. However, the accuracy and stability of the current EEG-based person authentication systems are still unsatisfactory in practical application. In this paper, a multi-task EEG-based person authentication system combining eye blinking is proposed, which can achieve high precision and robustness. Firstly, we design a novel EEG-based biometric evoked paradigm using self- or non-self-face rapid serial visual presentation (RSVP). The designed paradigm could obtain a distinct and stable biometric trait from EEG with a lower time cost. Secondly, the event-related potential (ERP) features and morphological features are extracted from EEG signals and eye blinking signals, respectively. Thirdly, convolutional neural network and back propagation neural network are severally designed to gain the score estimation of EEG features and eye blinking features. Finally, a score fusion technology based on least square method is proposed to get the final estimation score. The performance of multi-task authentication system is improved significantly compared to the system using EEG only, with an increasing average accuracy from 92.4% to 97.6%. Moreover, open-set authentication tests for additional imposters and permanence tests for users are conducted to simulate the practical scenarios, which have never been employed in previous EEG-based person authentication systems. A mean false accepted rate (FAR) of 3.90% and a mean false rejected rate (FRR) of 3.87% are accomplished in open-set authentication tests and permanence tests, respectively, which illustrate the open-set authentication and permanence capability of our systems.

A Context-Aware EEG Headset System for Early Detection of Driver Drowsiness

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Gang Li

2015-08-01

Full Text Available Driver drowsiness is a major cause of mortality in traffic accidents worldwide. Electroencephalographic (EEG signal, which reflects the brain activities, is more directly related to drowsiness. Thus, many Brain-Machine-Interface (BMI systems have been proposed to detect driver drowsiness. However, detecting driver drowsiness at its early stage poses a major practical hurdle when using existing BMI systems. This study proposes a context-aware BMI system aimed to detect driver drowsiness at its early stage by enriching the EEG data with the intensity of head-movements. The proposed system is carefully designed for low-power consumption with on-chip feature extraction and low energy Bluetooth connection. Also, the proposed system is implemented using JAVA programming language as a mobile application for on-line analysis. In total, 266 datasets obtained from six subjects who participated in a one-hour monotonous driving simulation experiment were used to evaluate this system. According to a video-based reference, the proposed system obtained an overall detection accuracy of 82.71% for classifying alert and slightly drowsy events by using EEG data alone and 96.24% by using the hybrid data of head-movement and EEG. These results indicate that the combination of EEG data and head-movement contextual information constitutes a robust solution for the early detection of driver drowsiness.

P300 brain computer interface: current challenges and emerging trends

Science.gov (United States)

Fazel-Rezai, Reza; Allison, Brendan Z.; Guger, Christoph; Sellers, Eric W.; Kleih, Sonja C.; Kübler, Andrea

2012-01-01

A brain-computer interface (BCI) enables communication without movement based on brain signals measured with electroencephalography (EEG). BCIs usually rely on one of three types of signals: the P300 and other components of the event-related potential (ERP), steady state visual evoked potential (SSVEP), or event related desynchronization (ERD). Although P300 BCIs were introduced over twenty years ago, the past few years have seen a strong increase in P300 BCI research. This closed-loop BCI approach relies on the P300 and other components of the ERP, based on an oddball paradigm presented to the subject. In this paper, we overview the current status of P300 BCI technology, and then discuss new directions: paradigms for eliciting P300s; signal processing methods; applications; and hybrid BCIs. We conclude that P300 BCIs are quite promising, as several emerging directions have not yet been fully explored and could lead to improvements in bit rate, reliability, usability, and flexibility. PMID:22822397

Déjà vu phenomenon-related EEG pattern. Case report

OpenAIRE

Vlasov, P.N.; Chervyakov, A.V.; Gnezditskii, V.V.

2013-01-01

Background D?j? vu (DV, from French d?j? vu ? ?already seen?) is an aberration of psychic activity associated with transitory erroneous perception of novel circumstances, objects, or people as already known. Objective This study aimed to record the EEG pattern of d?j? vu. Methods The subjects participated in a survey concerning d?j? vu characteristics and underwent ambulatory EEG monitoring (12?16?h). Results In patients with epilepsy, DV episodes began with polyspike activity in the right te...

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

Science.gov (United States)

Wang, Deng; Miao, Duoqian; Blohm, Gunnar

2012-01-01

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

EEG phase reset due to auditory attention: an inverse time-scale approach

International Nuclear Information System (INIS)

Low, Yin Fen; Strauss, Daniel J

2009-01-01

We propose a novel tool to evaluate the electroencephalograph (EEG) phase reset due to auditory attention by utilizing an inverse analysis of the instantaneous phase for the first time. EEGs were acquired through auditory attention experiments with a maximum entropy stimulation paradigm. We examined single sweeps of auditory late response (ALR) with the complex continuous wavelet transform. The phase in the frequency band that is associated with auditory attention (6–10 Hz, termed as theta–alpha border) was reset to the mean phase of the averaged EEGs. The inverse transform was applied to reconstruct the phase-modified signal. We found significant enhancement of the N100 wave in the reconstructed signal. Analysis of the phase noise shows the effects of phase jittering on the generation of the N100 wave implying that a preferred phase is necessary to generate the event-related potential (ERP). Power spectrum analysis shows a remarkable increase of evoked power but little change of total power after stabilizing the phase of EEGs. Furthermore, by resetting the phase only at the theta border of no attention data to the mean phase of attention data yields a result that resembles attention data. These results show strong connections between EEGs and ERP, in particular, we suggest that the presentation of an auditory stimulus triggers the phase reset process at the theta–alpha border which leads to the emergence of the N100 wave. It is concluded that our study reinforces other studies on the importance of the EEG in ERP genesis

EEG phase reset due to auditory attention: an inverse time-scale approach.

Science.gov (United States)

Low, Yin Fen; Strauss, Daniel J

2009-08-01

We propose a novel tool to evaluate the electroencephalograph (EEG) phase reset due to auditory attention by utilizing an inverse analysis of the instantaneous phase for the first time. EEGs were acquired through auditory attention experiments with a maximum entropy stimulation paradigm. We examined single sweeps of auditory late response (ALR) with the complex continuous wavelet transform. The phase in the frequency band that is associated with auditory attention (6-10 Hz, termed as theta-alpha border) was reset to the mean phase of the averaged EEGs. The inverse transform was applied to reconstruct the phase-modified signal. We found significant enhancement of the N100 wave in the reconstructed signal. Analysis of the phase noise shows the effects of phase jittering on the generation of the N100 wave implying that a preferred phase is necessary to generate the event-related potential (ERP). Power spectrum analysis shows a remarkable increase of evoked power but little change of total power after stabilizing the phase of EEGs. Furthermore, by resetting the phase only at the theta border of no attention data to the mean phase of attention data yields a result that resembles attention data. These results show strong connections between EEGs and ERP, in particular, we suggest that the presentation of an auditory stimulus triggers the phase reset process at the theta-alpha border which leads to the emergence of the N100 wave. It is concluded that our study reinforces other studies on the importance of the EEG in ERP genesis.

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

DEFF Research Database (Denmark)

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

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

Relation of EEG alpha background to cognitive fuction, brain atrophy, and cerebral metabolism in Down's syndrome. Age-specific changes

International Nuclear Information System (INIS)

Devinsky, O.; Sato, S.; Conwit, R.A.; Schapiro, M.B.

1990-01-01

We studied 19 young adults (19 to 37 years old) and 9 older patients (42 to 66 years old) with Down's syndrome (DS) and a control group of 13 healthy adults (22 to 38 years old) to investigate the relation of electroencephalographic (EEG) alpha background to cognitive function and cerebral metabolism. Four of the older patients with DS had a history of mental deterioration, disorientation, and memory loss and were demented. Patients and control subjects had EEGs, psychometric testing, quantitative computed tomography, and positron emission tomography with fludeoxyglucose F 18. A blinded reader classified the EEGs into two groups--those with normal alpha background or those with abnormal background. All the control subjects, the 13 young adult patients with DS, and the 5 older patients with DS had normal EEG backgrounds. In comparison with the age-matched patients with DS with normal alpha background, older patients with DS with decreased alpha background had dementia, fewer visuospatial skills, decreased attention span, larger third ventricles, and a global decrease in cerebral glucose utilization with parietal hypometabolism. In the young patients with DS, the EEG background did not correlate with psychometric or positron emission tomographic findings, but the third ventricles were significantly larger in those with abnormal EEG background. The young patients with DS, with or without normal EEG background, had positron emission tomographic findings similar to those of the control subjects. The mechanism underlying the abnormal EEG background may be the neuropathologic changes of Alzheimer's disease in older patients with DS and may be cerebral immaturity in younger patients with DS

Development of event related negativity together with an internal model of audio-motor associations

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Kai eLutz

2013-09-01

Full Text Available The brain’s reactions to error are manifested in several event related potentials (ERP components, derived from electroencephalographic (EEG signals. Although these components have been known for decades, their interpretation is still controversial. A current hypothesis (first indicator hypothesis claims that the first indication of an action being erroneous leads to a negative deflection of the EEG signal over frontal midline areas. In some cases this requires sensory feedback in the form of knowledge of results (KR. If KR is given, then the first negative deflection can be found around 250 ms after feedback presentation (feedback related negativity, FRN. When KR is not required, a negative deflection is found already around 100 ms after action onset (ERN. This deflection may be evoked when a mismatch between required and actually executed actions is detected. To detect such a mismatch, however, necessitates knowledge about which action is required. To test this assumption, the current study monitored EEG error components during acquisition of an internal model, i.e., acquisition of the knowledge of which actions are needed to reach certain goals. Actions consisted of finger presses on a piano keyboard and goals were tones of a certain pitch to be generated, thus the internal model represented audio-motor mapping. Results show that with increasing proficiency in mapping goals to appropriate actions, the amplitude of the ERN increased, whereas the amplitude of the FRN remained unchanged. Thus, when knowledge is present about which action is required, this supports generation of an ERN around 100ms, likely by detecting a mismatch between required and performed actions. This is in accordance with the first indicator hypothesis. The present study furthermore lends support to the notion that FRN mainly relies on comparison of sensory targets with sensory feedback.

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

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

2017-03-01

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

Exploring potential social influences on brain potentials during anticipation of tactile stimulation.

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Shen, Guannan; Saby, Joni N; Drew, Ashley R; Marshall, Peter J

2017-03-15

This study explored interpersonal influences on electrophysiological responses during the anticipation of tactile stimulation. It is well-known that broad, negative-going potentials are present in the event-related potential (ERP) between a forewarning cue and a tactile stimulus. It has also been shown that the alpha-range mu rhythm shows a lateralized desynchronization over central electrode sites during anticipation of tactile stimulation of the hand. The current study used a tactile discrimination task in which a visual cue signaled that an upcoming stimulus would either be delivered 1500ms later to the participant's hand, to a task partner's hand, or to neither person. For the condition in which participants anticipated the tactile stimulation to their own hand, a negative potential (contingent negative variation, CNV) was observed in the ERP at central sites in the 1000ms prior to the tactile stimulus. Significant mu rhythm desynchronization was also present in the same time window. The magnitudes of the ERPs and of the mu desynchronization were greater in the contralateral than in the ipsilateral hemisphere prior to right hand stimulation. Similar ERP and EEG changes were not present when the visual cue indicated that stimulation would be delivered to the task partner or to neither person. The absence of social influences during anticipation of tactile stimulation, and the relationship between the two brain signatures of anticipatory attention (CNV and mu rhythm) are discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

EEG frequency PCA in EEG-ERP dynamics.

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Barry, Robert J; De Blasio, Frances M

2018-05-01

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

Automatic seizure detection: going from sEEG to iEEG

DEFF Research Database (Denmark)

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

2010-01-01

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

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

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Maren Stropahl

2018-05-01

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

Right Fronto-Temporal EEG can Differentiate the Affective Responses to Award-Winning Advertisements.

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Wang, Regina W Y; Huarng, Shy-Peih; Chuang, Shang-Wen

2018-04-01

Affective engineering aims to improve service/product design by translating the customer's psychological feelings. Award-winning advertisements (AAs) were selected on the basis of the professional standards that consider creativity as a prerequisite. However, it is unknown if AA is related to satisfactory advertising performance among customers or only to the experts' viewpoints towards the advertisements. This issue in the field of affective engineering and design merits in-depth evaluation. We recruited 30 subjects and performed an electroencephalography (EEG) experiment while watching AAs and non-AAs (NAAs). The event-related potential (ERP) data showed that AAs evoked larger positive potentials 250-1400 [Formula: see text]ms after stimulus onset, particularly in the right fronto-temporal regions. The behavioral results were consistent with the professional recognition given to AAs by experts. The perceived levels of creativity and "product-like" quality were higher for the AAs than for the NAAs. Event-related spectral perturbation (ERSP) analysis further revealed statistically significant differences in the theta, alpha, beta, and gamma band activity in the right fronto-temporal regions between the AAs and NAAs. Our results confirm that EEG features from the time/frequency domains can differentiate affective responses to AAs at a neural circuit level, and provide scientific evidence to support the identification of AAs.

Signal Quality Evaluation of Emerging EEG Devices

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Thea Radüntz

2018-02-01

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

Integration of EEG source imaging and fMRI during continuous viewing of natural movies.

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Whittingstall, Kevin; Bartels, Andreas; Singh, Vanessa; Kwon, Soyoung; Logothetis, Nikos K

2010-10-01

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are noninvasive neuroimaging tools which can be used to measure brain activity with excellent temporal and spatial resolution, respectively. By combining the neural and hemodynamic recordings from these modalities, we can gain better insight into how and where the brain processes complex stimuli, which may be especially useful in patients with different neural diseases. However, due to their vastly different spatial and temporal resolutions, the integration of EEG and fMRI recordings is not always straightforward. One fundamental obstacle has been that paradigms used for EEG experiments usually rely on event-related paradigms, while fMRI is not limited in this regard. Therefore, here we ask whether one can reliably localize stimulus-driven EEG activity using the continuously varying feature intensities occurring in natural movie stimuli presented over relatively long periods of time. Specifically, we asked whether stimulus-driven aspects in the EEG signal would be co-localized with the corresponding stimulus-driven BOLD signal during free viewing of a movie. Secondly, we wanted to integrate the EEG signal directly with the BOLD signal, by estimating the underlying impulse response function (IRF) that relates the BOLD signal to the underlying current density in the primary visual area (V1). We made sequential fMRI and 64-channel EEG recordings in seven subjects who passively watched 2-min-long segments of a James Bond movie. To analyze EEG data in this natural setting, we developed a method based on independent component analysis (ICA) to reject EEG artifacts due to blinks, subject movement, etc., in a way unbiased by human judgment. We then calculated the EEG source strength of this artifact-free data at each time point of the movie within the entire brain volume using low-resolution electromagnetic tomography (LORETA). This provided for every voxel in the brain (i.e., in 3D space) an

A STUDY ON EEG ABNORMALITIES IN CHILDREN WITH MIGRAINE

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Subinay Mandal

2017-04-01

Full Text Available BACKGROUND Migraine is one of the common causes of headache in children. Migraine and epilepsy are both common episodic neurological disorders. The comorbidity of these two conditions is well known. Many researcher have pointed out that neuronal hyperexcitability is the initiating event for occurrence of migraine attack. The aim of the paper was to evaluate the EEG in children with migraine. MATERIALS AND METHODS We retrospectively analysed records of children who attended our paediatric outpatient department with diagnoses as suffering from migraine based on International Headache Society (IHS diagnostic criteria. Apart from detailed clinical history, EEG of every patient was collected and analysed. EEG was performed interictally at least 24 hours after the last episode of headache attack in all the cases. RESULTS 56 children (age range, 4-14 years constituted our study group. 64.3% children had migraine without aura (common type and in 23.2% cases had migraine with aura (classic type other were with migraine variants. Abnormal EEG was reported in 30.3% children. 17% of children with migraine without history of seizure had abnormal EEG. Sixty one percent of patients with aura had abnormal EEG. History of either febrile fits or afebrile fits was present in total 17.1% of cases. The type of paroxysmal discharges we came across was- a Sharp waves, b Spikes and c Spike and slow wave complexes. Abnormal paroxysmal sharp and spike-wave complexes (also called spike-and-slow-wave complexes were the most common EEG abnormality. CONCLUSION EEG abnormality was found in significant number of children with migraine both with and without history of seizure in our study. This indicates neuronal hyperexcitability during episodes of migraine. So, EEG should be considered in patients with clinical diagnoses of migraine to exclude association of any seizure activity.

Rett syndrome: EEG presentation.

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Robertson, R; Langill, L; Wong, P K; Ho, H H

1988-11-01

Rett syndrome, a degenerative neurological disorder of girls, has a classical presentation and typical EEG findings. The electroencephalograms (EEGs) of 7 girls whose records have been followed from the onset of symptoms to the age of 5 or more are presented. These findings are tabulated with the Clinical Staging System of Hagberg and Witt-Engerström (1986). The records show a progressive deterioration in background rhythms in waking and sleep. The abnormalities of the background activity may only become evident at 4-5 years of age or during stage 2--the Rapid Destructive Stage. The marked contrast between waking and sleep background may not occur until stage 3--the Pseudostationary Stage. In essence EEG changes appear to lag behind clinical symptomatology by 1-3 years. An unexpected, but frequent, abnormality was central spikes seen in 5 of 7 girls. They appeared to be age related and could be evoked by tactile stimulation in 2 patients. We hypothesize that the prominent 'hand washing' mannerism may be self-stimulating and related to the appearance of central spike discharges.

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

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Katarzyna Giertuga

2017-05-01

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

Event-related theta synchronization predicts deficit in facial affect recognition in schizophrenia.

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Csukly, Gábor; Stefanics, Gábor; Komlósi, Sarolta; Czigler, István; Czobor, Pál

2014-02-01

Growing evidence suggests that abnormalities in the synchronized oscillatory activity of neurons in schizophrenia may lead to impaired neural activation and temporal coding and thus lead to neurocognitive dysfunctions, such as deficits in facial affect recognition. To gain an insight into the neurobiological processes linked to facial affect recognition, we investigated both induced and evoked oscillatory activity by calculating the Event Related Spectral Perturbation (ERSP) and the Inter Trial Coherence (ITC) during facial affect recognition. Fearful and neutral faces as well as nonface patches were presented to 24 patients with schizophrenia and 24 matched healthy controls while EEG was recorded. The participants' task was to recognize facial expressions. Because previous findings with healthy controls showed that facial feature decoding was associated primarily with oscillatory activity in the theta band, we analyzed ERSP and ITC in this frequency band in the time interval of 140-200 ms, which corresponds to the N170 component. Event-related theta activity and phase-locking to facial expressions, but not to nonface patches, predicted emotion recognition performance in both controls and patients. Event-related changes in theta amplitude and phase-locking were found to be significantly weaker in patients compared with healthy controls, which is in line with previous investigations showing decreased neural synchronization in the low frequency bands in patients with schizophrenia. Neural synchrony is thought to underlie distributed information processing. Our results indicate a less effective functioning in the recognition process of facial features, which may contribute to a less effective social cognition in schizophrenia. PsycINFO Database Record (c) 2014 APA, all rights reserved.

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

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Flasbeck, Vera; Popkirov, Stoyan; Brüne, Martin

2017-01-01

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

Frontal EEG asymmetry as a moderator and mediator of emotion.

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Coan, James A; Allen, John J B

2004-10-01

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

Burst suppression in sleep in a routine outpatient EEG

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Ammar Kheder

2014-01-01

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

Hidden pattern discovery on epileptic EEG with 1-D local binary patterns and epileptic seizures detection by grey relational analysis.

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Kaya, Yılmaz

2015-09-01

This paper proposes a novel approach to detect epilepsy seizures by using Electroencephalography (EEG), which is one of the most common methods for the diagnosis of epilepsy, based on 1-Dimension Local Binary Pattern (1D-LBP) and grey relational analysis (GRA) methods. The main aim of this paper is to evaluate and validate a novel approach, which is a computer-based quantitative EEG analyzing method and based on grey systems, aimed to help decision-maker. In this study, 1D-LBP, which utilizes all data points, was employed for extracting features in raw EEG signals, Fisher score (FS) was employed to select the representative features, which can also be determined as hidden patterns. Additionally, GRA is performed to classify EEG signals through these Fisher scored features. The experimental results of the proposed approach, which was employed in a public dataset for validation, showed that it has a high accuracy in identifying epileptic EEG signals. For various combinations of epileptic EEG, such as A-E, B-E, C-E, D-E, and A-D clusters, 100, 96, 100, 99.00 and 100% were achieved, respectively. Also, this work presents an attempt to develop a new general-purpose hidden pattern determination scheme, which can be utilized for different categories of time-varying signals.

EEG Recording and Online Signal Processing on Android: A Multiapp Framework for Brain-Computer Interfaces on Smartphone.

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Blum, Sarah; Debener, Stefan; Emkes, Reiner; Volkening, Nils; Fudickar, Sebastian; Bleichner, Martin G

2017-01-01

Our aim was the development and validation of a modular signal processing and classification application enabling online electroencephalography (EEG) signal processing on off-the-shelf mobile Android devices. The software application SCALA (Signal ProCessing and CLassification on Android) supports a standardized communication interface to exchange information with external software and hardware. In order to implement a closed-loop brain-computer interface (BCI) on the smartphone, we used a multiapp framework, which integrates applications for stimulus presentation, data acquisition, data processing, classification, and delivery of feedback to the user. We have implemented the open source signal processing application SCALA. We present timing test results supporting sufficient temporal precision of audio events. We also validate SCALA with a well-established auditory selective attention paradigm and report above chance level classification results for all participants. Regarding the 24-channel EEG signal quality, evaluation results confirm typical sound onset auditory evoked potentials as well as cognitive event-related potentials that differentiate between correct and incorrect task performance feedback. We present a fully smartphone-operated, modular closed-loop BCI system that can be combined with different EEG amplifiers and can easily implement other paradigms.

EEG Recording and Online Signal Processing on Android: A Multiapp Framework for Brain-Computer Interfaces on Smartphone

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Sarah Blum

2017-01-01

Full Text Available Objective. Our aim was the development and validation of a modular signal processing and classification application enabling online electroencephalography (EEG signal processing on off-the-shelf mobile Android devices. The software application SCALA (Signal ProCessing and CLassification on Android supports a standardized communication interface to exchange information with external software and hardware. Approach. In order to implement a closed-loop brain-computer interface (BCI on the smartphone, we used a multiapp framework, which integrates applications for stimulus presentation, data acquisition, data processing, classification, and delivery of feedback to the user. Main Results. We have implemented the open source signal processing application SCALA. We present timing test results supporting sufficient temporal precision of audio events. We also validate SCALA with a well-established auditory selective attention paradigm and report above chance level classification results for all participants. Regarding the 24-channel EEG signal quality, evaluation results confirm typical sound onset auditory evoked potentials as well as cognitive event-related potentials that differentiate between correct and incorrect task performance feedback. Significance. We present a fully smartphone-operated, modular closed-loop BCI system that can be combined with different EEG amplifiers and can easily implement other paradigms.

EEG Recording and Online Signal Processing on Android: A Multiapp Framework for Brain-Computer Interfaces on Smartphone

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Debener, Stefan; Emkes, Reiner; Volkening, Nils; Fudickar, Sebastian; Bleichner, Martin G.

2017-01-01

Objective Our aim was the development and validation of a modular signal processing and classification application enabling online electroencephalography (EEG) signal processing on off-the-shelf mobile Android devices. The software application SCALA (Signal ProCessing and CLassification on Android) supports a standardized communication interface to exchange information with external software and hardware. Approach In order to implement a closed-loop brain-computer interface (BCI) on the smartphone, we used a multiapp framework, which integrates applications for stimulus presentation, data acquisition, data processing, classification, and delivery of feedback to the user. Main Results We have implemented the open source signal processing application SCALA. We present timing test results supporting sufficient temporal precision of audio events. We also validate SCALA with a well-established auditory selective attention paradigm and report above chance level classification results for all participants. Regarding the 24-channel EEG signal quality, evaluation results confirm typical sound onset auditory evoked potentials as well as cognitive event-related potentials that differentiate between correct and incorrect task performance feedback. Significance We present a fully smartphone-operated, modular closed-loop BCI system that can be combined with different EEG amplifiers and can easily implement other paradigms. PMID:29349070

Novice Shooters With Lower Pre-shooting Alpha Power Have Better Performance During Competition in a Virtual Reality Scenario

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Michael Pereira

2018-04-01

Full Text Available Competition changes the environment for athletes. The difficulty of training for such stressful events can lead to the well-known effect of “choking” under pressure, which prevents athletes from performing at their best level. To study the effect of competition on the human brain, we recorded pilot electroencephalography (EEG data while novice shooters were immersed in a realistic virtual environment representing a shooting range. We found a differential between-subject effect of competition on mu (8–12 Hz oscillatory activity during aiming; compared to training, the more the subject was able to desynchronize his mu rhythm during competition, the better was his shooting performance. Because this differential effect could not be explained by differences in simple measures of the kinematics and muscular activity, nor by the effect of competition or shooting performance per se, we interpret our results as evidence that mu desynchronization has a positive effect on performance during competition.

Cognitive processes associated with compulsive buying behaviours and related EEG coherence.

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Lawrence, Lee Matthew; Ciorciari, Joseph; Kyrios, Michael

2014-01-30

The behavioural and cognitive phenomena associated with Compulsive Buying (CB) have been investigated previously but the underlying neurophysiological cognitive process has received less attention. This study specifically investigated the electrophysiology of CB associated with executive processing and cue-reactivity in order to reveal differences in neural connectivity (EEG Coherence) and distinguish it from characteristics of addiction or mood disorder. Participants (N=24, M=25.38 yrs, S.D.=7.02 yrs) completed the Sensitivity to Punishment Sensitivity to Reward Questionnaire and a visual memory task associated with shopping items. Sensitivities to reward and punishment were examined with EEG coherence measures for preferred and non-preferred items and compared to CB psychometrics. Widespread EEG coherence differences were found in numerous regions, with an apparent left shifted lateralisation for preferred and right shifted lateralisation for non-preferred items. Different neurophysiological networks presented with CB phenomena, reflecting cue reactivity and episodic memory, from increased arousal and attachment to items. © 2013 Published by Elsevier Ireland Ltd.

Classification of right-hand grasp movement based on EMOTIV Epoc+

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Tobing, T. A. M. L.; Prawito, Wijaya, S. K.

2017-07-01

Combinations of BCT elements for right-hand grasp movement have been obtained, providing the average value of their classification accuracy. The aim of this study is to find a suitable combination for best classification accuracy of right-hand grasp movement based on EEG headset, EMOTIV Epoc+. There are three movement classifications: grasping hand, relax, and opening hand. These classifications take advantage of Event-Related Desynchronization (ERD) phenomenon that makes it possible to differ relaxation, imagery, and movement state from each other. The combinations of elements are the usage of Independent Component Analysis (ICA), spectrum analysis by Fast Fourier Transform (FFT), maximum mu and beta power with their frequency as features, and also classifier Probabilistic Neural Network (PNN) and Radial Basis Function (RBF). The average values of classification accuracy are ± 83% for training and ± 57% for testing. To have a better understanding of the signal quality recorded by EMOTIV Epoc+, the result of classification accuracy of left or right-hand grasping movement EEG signal (provided by Physionet) also be given, i.e.± 85% for training and ± 70% for testing. The comparison of accuracy value from each combination, experiment condition, and external EEG data are provided for the purpose of value analysis of classification accuracy.

The Executive and Memory Functions Processed in the Prefrontal and in the Lateral Temporal Cortices. An Intracerebral Alpha and Beta Event-Related De/Synchronization Study with Writing of Single Letters

Czech Academy of Sciences Publication Activity Database

Bočková, M.; Chládek, J.; Jurák, Pavel; Halámek, Josef; Rektor, I.

2006-01-01

Roč. 7, 2/Suppl. B (2006), B31 ISSN 1335-9592. [International Danube Symposium for Neurological Sciences and Continuing Education /38./. 06.04.2006-08.04.2006, Brno] Institutional research plan: CEZ:AV0Z20650511 Keywords : EEG * ERD * ERS * executive functions * TFA Subject RIV: FS - Medical Facilities ; Equipment

Connectivity Measures in EEG Microstructural Sleep Elements.

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Sakellariou, Dimitris; Koupparis, Andreas M; Kokkinos, Vasileios; Koutroumanidis, Michalis; Kostopoulos, George K

2016-01-01

During Non-Rapid Eye Movement sleep (NREM) the brain is relatively disconnected from the environment, while connectedness between brain areas is also decreased. Evidence indicates, that these dynamic connectivity changes are delivered by microstructural elements of sleep: short periods of environmental stimuli evaluation followed by sleep promoting procedures. The connectivity patterns of the latter, among other aspects of sleep microstructure, are still to be fully elucidated. We suggest here a methodology for the assessment and investigation of the connectivity patterns of EEG microstructural elements, such as sleep spindles. The methodology combines techniques in the preprocessing, estimation, error assessing and visualization of results levels in order to allow the detailed examination of the connectivity aspects (levels and directionality of information flow) over frequency and time with notable resolution, while dealing with the volume conduction and EEG reference assessment. The high temporal and frequency resolution of the methodology will allow the association between the microelements and the dynamically forming networks that characterize them, and consequently possibly reveal aspects of the EEG microstructure. The proposed methodology is initially tested on artificially generated signals for proof of concept and subsequently applied to real EEG recordings via a custom built MATLAB-based tool developed for such studies. Preliminary results from 843 fast sleep spindles recorded in whole night sleep of 5 healthy volunteers indicate a prevailing pattern of interactions between centroparietal and frontal regions. We demonstrate hereby, an opening to our knowledge attempt to estimate the scalp EEG connectivity that characterizes fast sleep spindles via an "EEG-element connectivity" methodology we propose. The application of the latter, via a computational tool we developed suggests it is able to investigate the connectivity patterns related to the occurrence

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

Science.gov (United States)

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

2011-01-01

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

A feasibility study of using event-related potential as a biometrics.

Science.gov (United States)

Yih-Choung Yu; Sicheng Wang; Gabel, Lisa A

2016-08-01

The use of an individual's neural response to stimuli (the event-related potential or ERP) has potential as a biometric because it is highly resistant to fraud relative to other conventional authentication systems. P300 is an ERP in human electroencephalography (EEG) that occurs in response to an oddball stimulus when an individual is actively engaged in a target detection task. Because P300 is consistently detectable from almost every subject, it is considered a potential signal for biometric applications. This paper presents a feasibility study of using topological plots of P300 as a biometric in subject authentication. The variation in latency and location of P300 response of 24 participants performing the P300Speller task were studied. Data sets from four participants were used for algorithm training; data from the other 20 participants were used as imposters for algorithm validation. The result showed that the algorithm was able to correctly identify three out of these four participants. Validation test also proved that the algorithm was able to reject 95% of the imposters for those three authenticated participants.

A Preliminary Study of Muscular Artifact Cancellation in Single-Channel EEG

OpenAIRE

Chen, Xun; Liu, Aiping; Peng, Hu; Ward, Rabab K.

2014-01-01

Electroencephalogram (EEG) recordings are often contaminated with muscular artifacts that strongly obscure the EEG signals and complicates their analysis. For the conventional case, where the EEG recordings are obtained simultaneously over many EEG channels, there exists a considerable range of methods for removing muscular artifacts. In recent years, there has been an increasing trend to use EEG information in ambulatory healthcare and related physiological signal monitoring systems. For pra...

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

DEFF Research Database (Denmark)

Foged, Mette Thrane; Lindberg, Ulrich; Vakamudi, Kishore

2017-01-01

) related heating, the effect of EEG on cortical signal-to-noise ratio (SNR) in fMRI, and assess EEG data quality. MATERIALS AND METHODS: The study compared EPI, multi-echo EPI, multi-band EPI and multi-slab echo-volumar imaging pulse sequences, using clinical 3 Tesla MR scanners from two different vendors...

A Brain–Computer Interface for Potential Nonverbal Facial Communication Based on EEG Signals Related to Specific Emotions

Directory of Open Access Journals (Sweden)

Koji eKashihara

2014-08-01

Full Text Available Unlike assistive technology for verbal communication, the brain–machine or brain–computer interface (BMI/BCI has not been established as a nonverbal communication tool for amyotrophic lateral sclerosis (ALS patients. Face-to-face communication enables access to rich emotional information, but individuals suffering from neurological disorders, such as ALS and autism, may not express their emotions or communicate their negative feelings. Although emotions may be inferred by looking at facial expressions, emotional prediction for neutral faces necessitates advanced judgment. The process that underlies brain neuronal responses to neutral faces and causes emotional changes remains unknown. To address this problem, therefore, this study attempted to decode conditioned emotional reactions to neutral face stimuli. This direction was motivated by the assumption that if electroencephalogram (EEG signals can be used to detect patients’ emotional responses to specific inexpressive faces, the results could be incorporated into the design and development of BMI/BCI-based nonverbal communication tools. To these ends, this study investigated how a neutral face associated with a negative emotion modulates rapid central responses in face processing and then identified cortical activities. The conditioned neutral face-triggered event-related potentials that originated from the posterior temporal lobe statistically significantly changed during late face processing (600–700 ms after stimulus, rather than in early face processing activities, such as P1 and N170 responses. Source localization revealed that the conditioned neutral faces increased activity in the right fusiform gyrus. This study also developed an efficient method for detecting implicit negative emotional responses to specific faces by using EEG signals.

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-11-01

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

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

Science.gov (United States)

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

2017-11-01

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

Spatio-temporal patterns of event-related potentials related to audiovisual synchrony judgments in older adults.

Science.gov (United States)

Chan, Yu Man; Pianta, Michael Julian; Bode, Stefan; McKendrick, Allison Maree

2017-07-01

Older adults have altered perception of the relative timing between auditory and visual stimuli, even when stimuli are scaled to equate detectability. To help understand why, this study investigated the neural correlates of audiovisual synchrony judgments in older adults using electroencephalography (EEG). Fourteen younger (18-32 year old) and 16 older (61-74 year old) adults performed an audiovisual synchrony judgment task on flash-pip stimuli while EEG was recorded. All participants were assessed to have healthy vision and hearing for their age. Observers responded to whether audiovisual pairs were perceived as synchronous or asynchronous via a button press. The results showed that the onset of predictive sensory information for synchrony judgments was not different between groups. Channels over auditory areas contributed more to this predictive sensory information than visual areas. The spatial-temporal profile of the EEG activity also indicates that older adults used different resources to maintain a similar level of performance in audiovisual synchrony judgments compared with younger adults. Copyright © 2017 Elsevier Inc. All rights reserved.

EEG Signal Classification With Super-Dirichlet Mixture Model

DEFF Research Database (Denmark)

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

2012-01-01

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

Using EEG to Study Cognitive Development: Issues and Practices

Science.gov (United States)

Bell, Martha Ann; Cuevas, Kimberly

2012-01-01

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

EEG and Coma.

Science.gov (United States)

Ardeshna, Nikesh I

2016-03-01

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

Spontaneous internal desynchronization of locomotor activity and body temperature rhythms from plasma melatonin rhythm in rats exposed to constant dim light

Directory of Open Access Journals (Sweden)

Bullock Nicole M

2006-04-01

Full Text Available Abstract Background We have recently reported that spontaneous internal desynchronization between the locomotor activity rhythm and the melatonin rhythm may occur in rats (30% of tested animals when they are maintained in constant dim red light (LLdim for 60 days. Previous work has also shown that melatonin plays an important role in the modulation of the circadian rhythms of running wheel activity (Rw and body temperature (Tb. The aim of the present study was to investigate the effect that desynchronization of the melatonin rhythm may have on the coupling and expression of circadian rhythms in Rw and Tb. Methods Rats were maintained in a temperature controlled (23–24°C ventilated lightproof room under LLdim (red dim light 1 μW/cm2 [5 Lux], lower wavelength cutoff at 640 nm. Animals were individually housed in cages equipped with a running wheel and a magnetic sensor system to detect wheel rotation; Tb was monitored by telemetry. Tb and Rw data were recorded in 5-min bins and saved on disk. For each animal, we determined the mesor and the amplitude of the Rw and Tb rhythm using waveform analysis on 7-day segments of the data. After sixty days of LLdim exposure, blood samples (80–100 μM were collected every 4 hours over a 24-hrs period from the tail artery, and serum melatonin levels were measured by radioimmunoassay. Results Twenty-one animals showed clear circadian rhythms Rw and Tb, whereas one animal was arrhythmic. Rw and Tb rhythms were always strictly associated and we did not observe desynchronization between these two rhythms. Plasma melatonin levels showed marked variations among individuals in the peak levels and in the night-to-day ratio. In six rats, the night-to-day ratio was less than 2, whereas in the rat that showed arrhythmicity in Rw and Tb melatonin levels were high and rhythmic with a large night-to-day ratio. In seven animals, serum melatonin levels peaked during the subjective day (from CT0 to CT8, thus suggesting

Event-related delta, theta, alpha and gamma correlates to auditory oddball processing during Vipassana meditation

Science.gov (United States)

Delorme, Arnaud; Polich, John

2013-01-01

Long-term Vipassana meditators sat in meditation vs. a control (instructed mind wandering) states for 25 min, electroencephalography (EEG) was recorded and condition order counterbalanced. For the last 4 min, a three-stimulus auditory oddball series was presented during both meditation and control periods through headphones and no task imposed. Time-frequency analysis demonstrated that meditation relative to the control condition evinced decreased evoked delta (2–4 Hz) power to distracter stimuli concomitantly with a greater event-related reduction of late (500–900 ms) alpha-1 (8–10 Hz) activity, which indexed altered dynamics of attentional engagement to distracters. Additionally, standard stimuli were associated with increased early event-related alpha phase synchrony (inter-trial coherence) and evoked theta (4–8 Hz) phase synchrony, suggesting enhanced processing of the habituated standard background stimuli. Finally, during meditation, there was a greater differential early-evoked gamma power to the different stimulus classes. Correlation analysis indicated that this effect stemmed from a meditation state-related increase in early distracter-evoked gamma power and phase synchrony specific to longer-term expert practitioners. The findings suggest that Vipassana meditation evokes a brain state of enhanced perceptual clarity and decreased automated reactivity. PMID:22648958

Correntropy measures to detect daytime sleepiness from EEG signals

International Nuclear Information System (INIS)

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

2014-01-01

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

Moving Beyond ERP Components: A Selective Review of Approaches to Integrate EEG and Behavior

Science.gov (United States)

Bridwell, David A.; Cavanagh, James F.; Collins, Anne G. E.; Nunez, Michael D.; Srinivasan, Ramesh; Stober, Sebastian; Calhoun, Vince D.

2018-01-01

Relationships between neuroimaging measures and behavior provide important clues about brain function and cognition in healthy and clinical populations. While electroencephalography (EEG) provides a portable, low cost measure of brain dynamics, it has been somewhat underrepresented in the emerging field of model-based inference. We seek to address this gap in this article by highlighting the utility of linking EEG and behavior, with an emphasis on approaches for EEG analysis that move beyond focusing on peaks or “components” derived from averaging EEG responses across trials and subjects (generating the event-related potential, ERP). First, we review methods for deriving features from EEG in order to enhance the signal within single-trials. These methods include filtering based on user-defined features (i.e., frequency decomposition, time-frequency decomposition), filtering based on data-driven properties (i.e., blind source separation, BSS), and generating more abstract representations of data (e.g., using deep learning). We then review cognitive models which extract latent variables from experimental tasks, including the drift diffusion model (DDM) and reinforcement learning (RL) approaches. Next, we discuss ways to access associations among these measures, including statistical models, data-driven joint models and cognitive joint modeling using hierarchical Bayesian models (HBMs). We think that these methodological tools are likely to contribute to theoretical advancements, and will help inform our understandings of brain dynamics that contribute to moment-to-moment cognitive function. PMID:29632480

Desynchronization Chaos Shift Keying Method Based on the Error Second Derivative and Its Security Analysis

Czech Academy of Sciences Publication Activity Database

Čelikovský, Sergej; Lynnyk, Volodymyr

2012-01-01

Roč. 22, č. 9 (2012), 1250231-1-1250231-11 ISSN 0218-1274 R&D Projects: GA ČR(CZ) GAP103/12/1794 Institutional support: RVO:67985556 Keywords : Nonlinear system * desynchronization * chaos shift keying * generalized Lorenz system Subject RIV: BC - Control Systems Theory Impact factor: 0.921, year: 2012 http://library.utia.cas.cz/separaty/2012/TR/celikovsky-0381701.pdf

Multiple linear regression to estimate time-frequency electrophysiological responses in single trials.

Science.gov (United States)

Hu, L; Zhang, Z G; Mouraux, A; Iannetti, G D

2015-05-01

Transient sensory, motor or cognitive event elicit not only phase-locked event-related potentials (ERPs) in the ongoing electroencephalogram (EEG), but also induce non-phase-locked modulations of ongoing EEG oscillations. These modulations can be detected when single-trial waveforms are analysed in the time-frequency domain, and consist in stimulus-induced decreases (event-related desynchronization, ERD) or increases (event-related synchronization, ERS) of synchrony in the activity of the underlying neuronal populations. ERD and ERS reflect changes in the parameters that control oscillations in neuronal networks and, depending on the frequency at which they occur, represent neuronal mechanisms involved in cortical activation, inhibition and binding. ERD and ERS are commonly estimated by averaging the time-frequency decomposition of single trials. However, their trial-to-trial variability that can reflect physiologically-important information is lost by across-trial averaging. Here, we aim to (1) develop novel approaches to explore single-trial parameters (including latency, frequency and magnitude) of ERP/ERD/ERS; (2) disclose the relationship between estimated single-trial parameters and other experimental factors (e.g., perceived intensity). We found that (1) stimulus-elicited ERP/ERD/ERS can be correctly separated using principal component analysis (PCA) decomposition with Varimax rotation on the single-trial time-frequency distributions; (2) time-frequency multiple linear regression with dispersion term (TF-MLRd) enhances the signal-to-noise ratio of ERP/ERD/ERS in single trials, and provides an unbiased estimation of their latency, frequency, and magnitude at single-trial level; (3) these estimates can be meaningfully correlated with each other and with other experimental factors at single-trial level (e.g., perceived stimulus intensity and ERP magnitude). The methods described in this article allow exploring fully non-phase-locked stimulus-induced cortical

The use of Matlab for colour fuzzy representation of multichannel EEG short time spectra.

Science.gov (United States)

Bigan, C; Strungaru, R

1998-01-01

During the last years, a lot of EEG research efforts was directed to intelligent methods for automatic analysis of data from multichannel EEG recordings. However, all the applications reported were focused on specific single tasks like detection of one specific "event" in the EEG signal: spikes, sleep spindles, epileptic seizures, K complexes, alpha or other rhythms or even artefacts. The aim of this paper is to present a complex system being able to perform a representation of the dynamic changes in frequency components of each EEG channel. This representation uses colours as a powerful means to show the only one frequency range chosen from the shortest epoch of signal able to be processed with the conventional "Short Time Fast Fourier Transform" (S.T.F.F.T.) method.

The influence of vertical disparity gradient and cue conflict on EEG omega complexity in Panum's limiting case.

Science.gov (United States)

Li, Huayun; Jia, Huibin; Yu, Dongchuan

2018-03-01

Using behavioral measures and ERP technique, researchers discovered at least two factors could influence the final perception of depth in Panum's limiting case, which are the vertical disparity gradient and the degree of cue conflict between two- and three-dimensional shapes. Although certain event-related potential components have been proved to be sensitive to the different levels of these two factors, some methodological limitations existed in this technique. In this study, we proposed that the omega complexity of EEG signal may serve as an important supplement of the traditional event-related potential technique. We found that the trials with lower vertical gradient disparity have lower omega complexity (i.e., higher global functional connectivity) of the occipital region, especially that of the right-occipital hemisphere. Moreover, for occipital omega complexity, the trials with low-cue conflict have significantly larger omega complexity than those with medium- and high-cue conflict. It is also found that the electrodes located in the middle line of the occipital region (i.e., POz and Oz) are more crucial to the impact of different levels of cue conflict on omega complexity than the other electrodes located in the left- and right-occipital hemispheres. These evidences demonstrated that the EEG omega complexity could reflect distinct neural activities evoked by Panum's limiting case configurations, with different levels of vertical disparity gradient and cue conflict. Besides, the influence of vertical disparity gradient and cue conflict on omega complexity may be regional dependent. NEW & NOTEWORTHY The EEG omega complexity could reflect distinct neural activities evoked by Panum's limiting case configurations with different levels of vertical disparity gradient and cue conflict. The influence of vertical disparity gradient and cue conflict on omega complexity is regional dependent. The omega complexity of EEG signal can serve as an important supplement of the

Transient Effect of the Noise of Passing Trucks on Sleep Eeg

Science.gov (United States)

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

1997-08-01

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

The role of the standard EEG in clinical psychiatry.

LENUS (Irish Health Repository)

O'Sullivan, S S

2012-02-03

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

Frontal cortex electrophysiology in reward- and punishment-related feedback processing during advice-guided decision making: An interleaved EEG-DC stimulation study.

Science.gov (United States)

Wischnewski, Miles; Bekkering, Harold; Schutter, Dennis J L G

2018-04-01

During decision making, individuals are prone to rely on external cues such as expert advice when the outcome is not known. However, the electrophysiological correlates associated with outcome uncertainty and the use of expert advice are not completely understood. The feedback-related negativity (FRN), P3a, and P3b are event-related brain potentials (ERPs) linked to dissociable stages of feedback and attentional processing during decision making. Even though these ERPs are influenced by both reward- and punishment-related feedback, it remains unclear how extrinsic information during uncertainty modulates these brain potentials. In this study, the effects of advice cues on decision making were investigated in two separate experiments. In the first experiment, electroencephalography (EEG) was recorded in healthy volunteers during a decision-making task in which the participants received reward or punishment feedback preceded by novice, amateur, or expert advice. The results showed that the P3a component was significantly influenced by the subjective predictive value of an advice cue, whereas the FRN and P3b were unaffected by the advice cues. In the second, sham-controlled experiment, cathodal transcranial direct current stimulation (ctDCS) was administered in conjunction with EEG in order to explore the direct contributions of the frontal cortex to these brain potentials. Results showed no significant change in either advice-following behavior or decision times. However, ctDCS did decrease FRN amplitudes as compared to sham, with no effect on the P3a or P3b. Together, these findings suggest that advice information may act primarily on attention allocation during feedback processing, whereas the electrophysiological correlates of the detection and updating of internal prediction models are not affected.

Validation of the Emotiv EPOC® EEG gaming system for measuring research quality auditory ERPs

Science.gov (United States)

Mousikou, Petroula; Mahajan, Yatin; de Lissa, Peter; Thie, Johnson; McArthur, Genevieve

2013-01-01

Background. Auditory event-related potentials (ERPs) have proved useful in investigating the role of auditory processing in cognitive disorders such as developmental dyslexia, specific language impairment (SLI), attention deficit hyperactivity disorder (ADHD), schizophrenia, and autism. However, laboratory recordings of auditory ERPs can be lengthy, uncomfortable, or threatening for some participants – particularly children. Recently, a commercial gaming electroencephalography (EEG) system has been developed that is portable, inexpensive, and easy to set up. In this study we tested if auditory ERPs measured using a gaming EEG system (Emotiv EPOC®, www.emotiv.com) were equivalent to those measured by a widely-used, laboratory-based, research EEG system (Neuroscan). Methods. We simultaneously recorded EEGs with the research and gaming EEG systems, whilst presenting 21 adults with 566 standard (1000 Hz) and 100 deviant (1200 Hz) tones under passive (non-attended) and active (attended) conditions. The onset of each tone was marked in the EEGs using a parallel port pulse (Neuroscan) or a stimulus-generated electrical pulse injected into the O1 and O2 channels (Emotiv EPOC®). These markers were used to calculate research and gaming EEG system late auditory ERPs (P1, N1, P2, N2, and P3 peaks) and the mismatch negativity (MMN) in active and passive listening conditions for each participant. Results. Analyses were restricted to frontal sites as these are most commonly reported in auditory ERP research. Intra-class correlations (ICCs) indicated that the morphology of the research and gaming EEG system late auditory ERP waveforms were similar across all participants, but that the research and gaming EEG system MMN waveforms were only similar for participants with non-noisy MMN waveforms (N = 11 out of 21). Peak amplitude and latency measures revealed no significant differences between the size or the timing of the auditory P1, N1, P2, N2, P3, and MMN peaks. Conclusions

Validation of the Emotiv EPOC® EEG gaming system for measuring research quality auditory ERPs

Directory of Open Access Journals (Sweden)

Nicholas A. Badcock

2013-02-01

Full Text Available Background. Auditory event-related potentials (ERPs have proved useful in investigating the role of auditory processing in cognitive disorders such as developmental dyslexia, specific language impairment (SLI, attention deficit hyperactivity disorder (ADHD, schizophrenia, and autism. However, laboratory recordings of auditory ERPs can be lengthy, uncomfortable, or threatening for some participants – particularly children. Recently, a commercial gaming electroencephalography (EEG system has been developed that is portable, inexpensive, and easy to set up. In this study we tested if auditory ERPs measured using a gaming EEG system (Emotiv EPOC®, www.emotiv.com were equivalent to those measured by a widely-used, laboratory-based, research EEG system (Neuroscan.Methods. We simultaneously recorded EEGs with the research and gaming EEG systems, whilst presenting 21 adults with 566 standard (1000 Hz and 100 deviant (1200 Hz tones under passive (non-attended and active (attended conditions. The onset of each tone was marked in the EEGs using a parallel port pulse (Neuroscan or a stimulus-generated electrical pulse injected into the O1 and O2 channels (Emotiv EPOC®. These markers were used to calculate research and gaming EEG system late auditory ERPs (P1, N1, P2, N2, and P3 peaks and the mismatch negativity (MMN in active and passive listening conditions for each participant.Results. Analyses were restricted to frontal sites as these are most commonly reported in auditory ERP research. Intra-class correlations (ICCs indicated that the morphology of the research and gaming EEG system late auditory ERP waveforms were similar across all participants, but that the research and gaming EEG system MMN waveforms were only similar for participants with non-noisy MMN waveforms (N = 11 out of 21. Peak amplitude and latency measures revealed no significant differences between the size or the timing of the auditory P1, N1, P2, N2, P3, and MMN peaks

An embedded EEG analyzing system based on muC/os-II.

Science.gov (United States)

Liu, Boqiang; Zhang, Yanyan; Liu, Zhongguo; Yin, Cong

2007-01-01

An EEG analyzing system based on Advanced RISC Machines (ARM) and muC/os-II real time operating system is discussed in this paper. The detailed system design including the producing of event signals and the synchronization between event signals and EEG signals is described. The details of data acquisition, data preprocessing, data transmitting through USB and system configurations are also contained in the system design. In this paper the design of high capability amplifier and the software of embedded subsystem are discussed. Also the design of realizing multi-task system in muC/os-II, the definition of communicating protocols between PC and the equipment and the detail configurations of USB are given out. The final test shows that the filter behaviors of this equipment are feasible.

How culture gets embrained: Cultural differences in event-related potentials of social norm violations.

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Mu, Yan; Kitayama, Shinobu; Han, Shihui; Gelfand, Michele J

2015-12-15

Humans are unique among all species in their ability to develop and enforce social norms, but there is wide variation in the strength of social norms across human societies. Despite this fundamental aspect of human nature, there has been surprisingly little research on how social norm violations are detected at the neurobiological level. Building on the emerging field of cultural neuroscience, we combine noninvasive electroencephalography (EEG) with a new social norm violation paradigm to examine the neural mechanisms underlying the detection of norm violations and how they vary across cultures. EEG recordings from Chinese and US participants (n = 50) showed consistent negative deflection of event-related potential around 400 ms (N400) over the central and parietal regions that served as a culture-general neural marker of detecting norm violations. The N400 at the frontal and temporal regions, however, was only observed among Chinese but not US participants, illustrating culture-specific neural substrates of the detection of norm violations. Further, the frontal N400 predicted a variety of behavioral and attitudinal measurements related to the strength of social norms that have been found at the national and state levels, including higher culture superiority and self-control but lower creativity. There were no cultural differences in the N400 induced by semantic violation, suggesting a unique cultural influence on social norm violation detection. In all, these findings provided the first evidence, to our knowledge, for the neurobiological foundations of social norm violation detection and its variation across cultures.

EEG Controlled Wheelchair

Directory of Open Access Journals (Sweden)

Swee Sim Kok

2016-01-01

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

Human cortical activity related to unilateral movements. A high resolution EEG study.

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

1996-12-20

In the present study a modern high resolution electroencephalography (EEG) technique was used to investigate the dynamic functional topography of human cortical activity related to simple unilateral internally triggered finger movements. The sensorimotor area (M1-S1) contralateral to the movement as well as the supplementary motor area (SMA) and to a lesser extent the ipsilateral M1-S1 were active during the preparation and execution of these movements. These findings suggest that both hemispheres may cooperate in both planning and production of simple unilateral volitional acts.

A comparison of recording modalities of P300 event-related potentials (ERP) for brain-computer interface (BCI) paradigm.

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Mayaud, L; Congedo, M; Van Laghenhove, A; Orlikowski, D; Figère, M; Azabou, E; Cheliout-Heraut, F

2013-10-01

A brain-computer interface aims at restoring communication and control in severely disabled people by identification and classification of EEG features such as event-related potentials (ERPs). The aim of this study is to compare different modalities of EEG recording for extraction of ERPs. The first comparison evaluates the performance of six disc electrodes with that of the EMOTIV headset, while the second evaluates three different electrode types (disc, needle, and large squared electrode). Ten healthy volunteers gave informed consent and were randomized to try the traditional EEG system (six disc electrodes with gel and skin preparation) or the EMOTIV Headset first. Together with the six disc electrodes, a needle and a square electrode of larger surface were simultaneously recording near lead Cz. Each modality was evaluated over three sessions of auditory P300 separated by one hour. No statically significant effect was found for the electrode type, nor was the interaction between electrode type and session number. There was no statistically significant difference of performance between the EMOTIV and the six traditional EEG disc electrodes, although there was a trend showing worse performance of the EMOTIV headset. However, the modality-session interaction was highly significant (P<0.001) showing that, while the performance of the six disc electrodes stay constant over sessions, the performance of the EMOTIV headset drops dramatically between 2 and 3h of use. Finally, the evaluation of comfort by participants revealed an increasing discomfort with the EMOTIV headset starting with the second hour of use. Our study does not recommend the use of one modality over another based on performance but suggests the choice should be made on more practical considerations such as the expected length of use, the availability of skilled labor for system setup and above all, the patient comfort. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Confirming psychogenic nonepileptic seizures with video-EEG: sex matters.

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Noe, Katherine H; Grade, Madeline; Stonnington, Cynthia M; Driver-Dunckley, Erika; Locke, Dona E C

2012-03-01

The influence of gender on psychogenic nonepileptic seizures (PNES) diagnosis was examined retrospectively in 439 subjects undergoing video-EEG (vEEG) for spell classification, of whom 142 women and 42 men had confirmed PNES. The epileptologist's predicted diagnosis was correct in 72% overall. Confirmed epilepsy was correctly predicted in 94% men and 88% women. In contrast, confirmed PNES was accurately predicted in 86% women versus 61% men (p=0.003). Sex-based differences in likelihood of an indeterminate admission were not observed for predicted epilepsy or physiologic events, but were for predicted PNES (39% men, 12% women, p=0.0002). More frequent failure to record spells in men than women with predicted PNES was not explained by spell frequency, duration of monitoring, age, medication use, or personality profile. PNES are not only less common in men, but also more challenging to recognize in the clinic, and even when suspected more difficult to confirm with vEEG. Copyright © 2012 Elsevier Inc. All rights reserved.

EEG as an Indicator of Cerebral Functioning in Postanoxic Coma.

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

2015-12-01

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

Discovering EEG resting state alterations of semantic dementia.

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

2016-05-01

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

Investigating neural efficiency of elite karate athletes during a mental arithmetic task using EEG.

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Duru, Adil Deniz; Assem, Moataz

2018-02-01

Neural efficiency is proposed as one of the neural mechanisms underlying elite athletic performances. Previous sports studies examined neural efficiency using tasks that involve motor functions. In this study we investigate the extent of neural efficiency beyond motor tasks by using a mental subtraction task. A group of elite karate athletes are compared to a matched group of non-athletes. Electroencephalogram is used to measure cognitive dynamics during resting and increased mental workload periods. Mainly posterior alpha band power of the karate players was found to be higher than control subjects under both tasks. Moreover, event related synchronization/desynchronization has been computed to investigate the neural efficiency hypothesis among subjects. Finally, this study is the first study to examine neural efficiency related to a cognitive task, not a motor task, in elite karate players using ERD/ERS analysis. The results suggest that the effect of neural efficiency in the brain is global rather than local and thus might be contributing to the elite athletic performances. Also the results are in line with the neural efficiency hypothesis tested for motor performance studies.

Probabilistic delay differential equation modeling of event-related potentials.

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Ostwald, Dirk; Starke, Ludger

2016-08-01

"Dynamic causal models" (DCMs) are a promising approach in the analysis of functional neuroimaging data due to their biophysical interpretability and their consolidation of functional-segregative and functional-integrative propositions. In this theoretical note we are concerned with the DCM framework for electroencephalographically recorded event-related potentials (ERP-DCM). Intuitively, ERP-DCM combines deterministic dynamical neural mass models with dipole-based EEG forward models to describe the event-related scalp potential time-series over the entire electrode space. Since its inception, ERP-DCM has been successfully employed to capture the neural underpinnings of a wide range of neurocognitive phenomena. However, in spite of its empirical popularity, the technical literature on ERP-DCM remains somewhat patchy. A number of previous communications have detailed certain aspects of the approach, but no unified and coherent documentation exists. With this technical note, we aim to close this gap and to increase the technical accessibility of ERP-DCM. Specifically, this note makes the following novel contributions: firstly, we provide a unified and coherent review of the mathematical machinery of the latent and forward models constituting ERP-DCM by formulating the approach as a probabilistic latent delay differential equation model. Secondly, we emphasize the probabilistic nature of the model and its variational Bayesian inversion scheme by explicitly deriving the variational free energy function in terms of both the likelihood expectation and variance parameters. Thirdly, we detail and validate the estimation of the model with a special focus on the explicit form of the variational free energy function and introduce a conventional nonlinear optimization scheme for its maximization. Finally, we identify and discuss a number of computational issues which may be addressed in the future development of the approach. Copyright © 2016 Elsevier Inc. All rights reserved.

Methodological aspects of EEG and Body dynamics measurements during motion.

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Pedro eReis

2014-03-01

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

Mobile EEG in epilepsy

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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

Cortical and Subcortical Coordination of Visual Spatial Attention Revealed by Simultaneous EEG-fMRI Recording.

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Green, Jessica J; Boehler, Carsten N; Roberts, Kenneth C; Chen, Ling-Chia; Krebs, Ruth M; Song, Allen W; Woldorff, Marty G

2017-08-16

Visual spatial attention has been studied in humans with both electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) individually. However, due to the intrinsic limitations of each of these methods used alone, our understanding of the systems-level mechanisms underlying attentional control remains limited. Here, we examined trial-to-trial covariations of concurrently recorded EEG and fMRI in a cued visual spatial attention task in humans, which allowed delineation of both the generators and modulators of the cue-triggered event-related oscillatory brain activity underlying attentional control function. The fMRI activity in visual cortical regions contralateral to the cued direction of attention covaried positively with occipital gamma-band EEG, consistent with activation of cortical regions representing attended locations in space. In contrast, fMRI activity in ipsilateral visual cortical regions covaried inversely with occipital alpha-band oscillations, consistent with attention-related suppression of the irrelevant hemispace. Moreover, the pulvinar nucleus of the thalamus covaried with both of these spatially specific, attention-related, oscillatory EEG modulations. Because the pulvinar's neuroanatomical geometry makes it unlikely to be a direct generator of the scalp-recorded EEG, these covariational patterns appear to reflect the pulvinar's role as a regulatory control structure, sending spatially specific signals to modulate visual cortex excitability proactively. Together, these combined EEG/fMRI results illuminate the dynamically interacting cortical and subcortical processes underlying spatial attention, providing important insight not realizable using either method alone. SIGNIFICANCE STATEMENT Noninvasive recordings of changes in the brain's blood flow using functional magnetic resonance imaging and electrical activity using electroencephalography in humans have individually shown that shifting attention to a location in space

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

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

2015-08-01

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

A novel seizure detection algorithm informed by hidden Markov model event states

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Baldassano, Steven; Wulsin, Drausin; Ung, Hoameng; Blevins, Tyler; Brown, Mesha-Gay; Fox, Emily; Litt, Brian

2016-06-01

Objective. Recently the FDA approved the first responsive, closed-loop intracranial device to treat epilepsy. Because these devices must respond within seconds of seizure onset and not miss events, they are tuned to have high sensitivity, leading to frequent false positive stimulations and decreased battery life. In this work, we propose a more robust seizure detection model. Approach. We use a Bayesian nonparametric Markov switching process to parse intracranial EEG (iEEG) data into distinct dynamic event states. Each event state is then modeled as a multidimensional Gaussian distribution to allow for predictive state assignment. By detecting event states highly specific for seizure onset zones, the method can identify precise regions of iEEG data associated with the transition to seizure activity, reducing false positive detections associated with interictal bursts. The seizure detection algorithm was translated to a real-time application and validated in a small pilot study using 391 days of continuous iEEG data from two dogs with naturally occurring, multifocal epilepsy. A feature-based seizure detector modeled after the NeuroPace RNS System was developed as a control. Main results. Our novel seizure detection method demonstrated an improvement in false negative rate (0/55 seizures missed versus 2/55 seizures missed) as well as a significantly reduced false positive rate (0.0012 h versus 0.058 h-1). All seizures were detected an average of 12.1 ± 6.9 s before the onset of unequivocal epileptic activity (unequivocal epileptic onset (UEO)). Significance. This algorithm represents a computationally inexpensive, individualized, real-time detection method suitable for implantable antiepileptic devices that may considerably reduce false positive rate relative to current industry standards.

Memories of attachment hamper EEG cortical connectivity in dissociative patients.

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

2014-08-01

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

Quantitative EEG in Children and Adults With Attention Deficit Hyperactivity Disorder: Comparison of Absolute and Relative Power Spectra and Theta/Beta Ratio.

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Markovska-Simoska, Silvana; Pop-Jordanova, Nada

2017-01-01

In recent decades, resting state electroencephalographic (EEG) measures have been widely used to document underlying neurophysiological dysfunction in attention deficit hyperactivity disorder (ADHD). Although most EEG studies focus on children, there is a growing interest in adults with ADHD too. The aim of this study was to objectively assess and compare the absolute and relative EEG power as well as the theta/beta ratio in children and adults with ADHD. The evaluated sample comprised 30 male children and 30 male adults with ADHD diagnosed according to DSM-IV criteria. They were compared with 30 boys and 30 male adults matched by age. The mean age (±SD) of the children's group was 9 (±2.44) years and the adult group 35.8 (±8.65) years. EEG was recorded during an eyes-open condition. Spectral analysis of absolute (μV 2 ) and relative power (%) was carried out for 4 frequency bands: delta (2-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), and beta (13-21 Hz). The findings obtained for ADHD children are increased absolute power of slow waves (theta and delta), whereas adults exhibited no differences compared with normal subjects. For the relative power spectra there were no differences between the ADHD and control groups. Across groups, the children showed greater relative power than the adults in the delta and theta bands, but for the higher frequency bands (alpha and beta) the adults showed more relative power than children. Only ADHD children showed greater theta/beta ratio compared to the normal group. Classification analysis showed that ADHD children could be differentiated from the control group by the absolute theta values and theta/beta ratio at Cz, but this was not the case with ADHD adults. The question that should be further explored is if these differences are mainly due to maturation processes or if there is a core difference in cortical arousal between ADHD children and adults. © EEG and Clinical Neuroscience Society (ECNS) 2016.

Validation of the Emotiv EPOC(®) EEG gaming system for measuring research quality auditory ERPs.

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Badcock, Nicholas A; Mousikou, Petroula; Mahajan, Yatin; de Lissa, Peter; Thie, Johnson; McArthur, Genevieve

2013-01-01

Background. Auditory event-related potentials (ERPs) have proved useful in investigating the role of auditory processing in cognitive disorders such as developmental dyslexia, specific language impairment (SLI), attention deficit hyperactivity disorder (ADHD), schizophrenia, and autism. However, laboratory recordings of auditory ERPs can be lengthy, uncomfortable, or threatening for some participants - particularly children. Recently, a commercial gaming electroencephalography (EEG) system has been developed that is portable, inexpensive, and easy to set up. In this study we tested if auditory ERPs measured using a gaming EEG system (Emotiv EPOC(®), www.emotiv.com) were equivalent to those measured by a widely-used, laboratory-based, research EEG system (Neuroscan). Methods. We simultaneously recorded EEGs with the research and gaming EEG systems, whilst presenting 21 adults with 566 standard (1000 Hz) and 100 deviant (1200 Hz) tones under passive (non-attended) and active (attended) conditions. The onset of each tone was marked in the EEGs using a parallel port pulse (Neuroscan) or a stimulus-generated electrical pulse injected into the O1 and O2 channels (Emotiv EPOC(®)). These markers were used to calculate research and gaming EEG system late auditory ERPs (P1, N1, P2, N2, and P3 peaks) and the mismatch negativity (MMN) in active and passive listening conditions for each participant. Results. Analyses were restricted to frontal sites as these are most commonly reported in auditory ERP research. Intra-class correlations (ICCs) indicated that the morphology of the research and gaming EEG system late auditory ERP waveforms were similar across all participants, but that the research and gaming EEG system MMN waveforms were only similar for participants with non-noisy MMN waveforms (N = 11 out of 21). Peak amplitude and latency measures revealed no significant differences between the size or the timing of the auditory P1, N1, P2, N2, P3, and MMN peaks

Brain oscillation and connectivity during a chemistry visual working memory task.

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Huang, Li-Yu; She, Hsiao-Ching; Chou, Wen-Chi; Chuang, Ming-Hua; Duann, Jeng-Ren; Jung, Tzyy-Ping

2013-11-01

Many studies have reported that frontal theta and posterior alpha activities are associated with working memory tasks. However, fewer studies have focused on examining whether or not the frontal alpha or posterior theta can play a role in the working memory task. This study investigates electroencephalography (EEG) dynamics and connectivity among different brain regions' theta and alpha oscillations. The EEG was collected from undergraduate students (n = 64) while they were performing a Sternberg-like working memory task involving chemistry concepts. The results showed that the frontal midline cluster exhibited sustained theta augmentation across the periods of stimulus presentations, maintenance, and probe presentation, suggesting that the frontal midline theta might associate with facilitating the central execute function to maintain information in the working memory. Study of the central parietal and the occipital clusters revealed a sequence of theta augmentation followed by alpha suppression at constant intervals after the onset of stimulus and probe presentations, suggesting that the posterior theta might be associated with sensory processing, theta gating, or stimulus selection. It further suggests that the posterior alpha event-related de-synchronization (ERD) might be linked to direct information flow into and out of the long-term memory (LTM) and precede stimulus recognition. An alternating phasic alpha event-related synchronization (ERS) and ERD following the 1st stimulus and probe presentations were observed at the occipital cluster, in which alpha ERS might be linked to the inhibition of irrelevant information. © 2013.

sBCI-Headset—Wearable and Modular Device for Hybrid Brain-Computer Interface

Directory of Open Access Journals (Sweden)

Tatsiana Malechka

2015-02-01

Full Text Available Severely disabled people, like completely paralyzed persons either with tetraplegia or similar disabilities who cannot use their arms and hands, are often considered as a user group of Brain Computer Interfaces (BCI. In order to achieve high acceptance of the BCI by this user group and their supporters, the BCI system has to be integrated into their support infrastructure. Critical disadvantages of a BCI are the time consuming preparation of the user for the electroencephalography (EEG measurements and the low information transfer rate of EEG based BCI. These disadvantages become apparent if a BCI is used to control complex devices. In this paper, a hybrid BCI is described that enables research for a Human Machine Interface (HMI that is optimally adapted to requirements of the user and the tasks to be carried out. The solution is based on the integration of a Steady-state visual evoked potential (SSVEP-BCI, an Event-related (de-synchronization (ERD/ERS-BCI, an eye tracker, an environmental observation camera, and a new EEG head cap for wearing comfort and easy preparation. The design of the new fast multimodal BCI (called sBCI system is described and first test results, obtained in experiments with six healthy subjects, are presented. The sBCI concept may also become useful for healthy people in cases where a “hands-free” handling of devices is necessary.

Applicability of the "Emotiv EEG Neuroheadset" as a user-friendly input interface.

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Boutani, Hidenori; Ohsuga, Mieko

2013-01-01

We aimed to develop an input interface by using the P3 component of visual event-related potentials (ERPs). When using electroencephalography (EEG) in daily applications, coping with ocular-motor artifacts and ensuring that the equipment is user-friendly are both important. To address the first issue, we applied a previously proposed method that applies an unmixing matrix to acquire independent components (ICs) obtained from another dataset. For the second issue, we introduced a 14-channel EEG commercial headset called the "Emotiv EEG Neuroheadset". An advantage of the Emotiv headset is that users can put it on by themselves within 1 min without any specific skills. However, only a few studies have investigated whether EEG and ERP signals are accurately measured by Emotiv. Additionally, no electrodes of the Emotiv headset are located over the centroparietal area of the head where P3 components are reported to show large amplitudes. Therefore, we first demonstrated that the P3 components obtained by the headset and by commercial plate electrodes and a multipurpose bioelectric amplifier during an oddball task were comparable. Next, we confirmed that eye-blink and ocular movement components could be decomposed by independent component analysis (ICA) using the 14-channel signals measured by the headset. We also demonstrated that artifacts could be removed with an unmixing matrix, as long as the matrix was obtained from the same person, even if they were measured on different days. Finally, we confirmed that the fluctuation of the sampling frequency of the Emotiv headset was not a major problem.

Utilization of independent component analysis for accurate pathological ripple detection in intracranial EEG recordings recorded extra- and intra-operatively.

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Shimamoto, Shoichi; Waldman, Zachary J; Orosz, Iren; Song, Inkyung; Bragin, Anatol; Fried, Itzhak; Engel, Jerome; Staba, Richard; Sharan, Ashwini; Wu, Chengyuan; Sperling, Michael R; Weiss, Shennan A

2018-01-01

To develop and validate a detector that identifies ripple (80-200 Hz) events in intracranial EEG (iEEG) recordings in a referential montage and utilizes independent component analysis (ICA) to eliminate or reduce high-frequency artifact contamination. Also, investigate the correspondence of detected ripples and the seizure onset zone (SOZ). iEEG recordings from 16 patients were first band-pass filtered (80-600 Hz) and Infomax ICA was next applied to derive the first independent component (IC1). IC1 was subsequently pruned, and an artifact index was derived to reduce the identification of high-frequency events introduced by the reference electrode signal. A Hilbert detector identified ripple events in the processed iEEG recordings using amplitude and duration criteria. The identified ripple events were further classified and characterized as true or false ripple on spikes, or ripples on oscillations by utilizing a topographical analysis to their time-frequency plot, and confirmed by visual inspection. The signal to noise ratio was improved by pruning IC1. The precision of the detector for ripple events was 91.27 ± 4.3%, and the sensitivity of the detector was 79.4 ± 3.0% (N = 16 patients, 5842 ripple events). The sensitivity and precision of the detector was equivalent in iEEG recordings obtained during sleep or intra-operatively. Across all the patients, true ripple on spike rates and also the rates of false ripple on spikes, that were generated due to filter ringing, classified the seizure onset zone (SOZ) with an area under the receiver operating curve (AUROC) of >76%. The magnitude and spectral content of true ripple on spikes generated in the SOZ was distinct as compared with the ripples generated in the NSOZ (p ripple rates and properties defined using this approach may accurately delineate the seizure onset zone. Strategies to improve the spatial resolution of intracranial EEG and reduce artifact can help improve the clinical utility of

REHABILITATION OF PATIENTS WITH ENCEPHALOPATHY CAUSED BY ACUTE CHEMICAL AGENTS POISONING. P300 OF AUDITORY EVENT RELATED POTENTIALS AND ELECTROENCEPHALOGRAPHY

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I. U. Berezina

2014-01-01

Full Text Available RELEVANCE. Patients with encephalopathy due to acute chemical agents poisoning have some brain functioning changes and a cognitive impairment during the rehabilitation program. These changes require correction of appropriate diagnostic protocol and treatment.AIM. The aim of this study was to estimate changes of electroencephalography (EEG and the P3 component of the event related potential (P300 ERP that are observed in patients with encephalopathy due to acute chemical agents poisoning during stage of rehabilitation.MATERIAL AND METHODS. The study was included 25 patients (age 37 (32; 51 poisoned different kind of neurotoxic substances (drugs, ethanol and complicated by toxic and hypoxic encephalopathy. They have got the treatment of encephalopathy by mexidol intravenously, mesodiencephalic modulation (MDM and hyperbaric oxygen therapy (HBOT. All patients were recoded EEG (electroencephalograph of “MBN” company, Russia and P300 ERP (“Neuron-Spectrum-5/EP” of “Neurosoft”, Russia according to the international recommendations of clinical neurophysiologists. Neuropsychological testing was used for the assessment of cognitive functions.RESULTS. There were some disturbances in primary electroencephalograms of all subjects. The follow-up EEG recording showed the main group of patients who had got the treatment (mexidol, MDM, HBOT had more often (11 patients the EEG improvements compared to the controls (1 patient. The main group had more rarely the EEG impairments compared to the control group. 6 patients of main group and 3 patients of controls did not have EEG changes during the follow-up EEG recordings. All controls and 17 patients of the main group patients had different cognitive disturbances. After the treatment 15 patients of the main group had improved on neuropsychological tests (MMSE, Munsterberg test, Schulte table, Number Connecting Test. They also had a decrease in the N200, P300 peak latency and an increase in the N200, P300

Highly Efficient Compression Algorithms for Multichannel EEG.

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Shaw, Laxmi; Rahman, Daleef; Routray, Aurobinda

2018-05-01

The difficulty associated with processing and understanding the high dimensionality of electroencephalogram (EEG) data requires developing efficient and robust compression algorithms. In this paper, different lossless compression techniques of single and multichannel EEG data, including Huffman coding, arithmetic coding, Markov predictor, linear predictor, context-based error modeling, multivariate autoregression (MVAR), and a low complexity bivariate model have been examined and their performances have been compared. Furthermore, a high compression algorithm named general MVAR and a modified context-based error modeling for multichannel EEG have been proposed. The resulting compression algorithm produces a higher relative compression ratio of 70.64% on average compared with the existing methods, and in some cases, it goes up to 83.06%. The proposed methods are designed to compress a large amount of multichannel EEG data efficiently so that the data storage and transmission bandwidth can be effectively used. These methods have been validated using several experimental multichannel EEG recordings of different subjects and publicly available standard databases. The satisfactory parametric measures of these methods, namely percent-root-mean square distortion, peak signal-to-noise ratio, root-mean-square error, and cross correlation, show their superiority over the state-of-the-art compression methods.

Studentized Continuous Wavelet Transform (t-CWT in the Analysis of Individual ERPs: Real and Simulated EEG Data

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Ruben Gustav Leonhardt Real

2014-09-01

Full Text Available This study aimed at evaluating the performance of the Studentized Continuous Wavelet Transform (t-CWT as a method for the extraction and assessment of event-related brain potentials (ERP in data from a single subject. Sensitivity, specificity, positive (PPV and negative predictive values (NPV of the t-CWT were assessed and compared to a variety of competing procedures using simulated EEG data at six low signal-to-noise ratios. Results show that the t-CWT combines high sensitivity and specificity with favorable PPV and NPV. Applying the t-CWT to authentic EEG data obtained from 14 healthy participants confirmed its high sensitivity. The t-CWT may thus be well suited for the assessment of weak ERPs in single-subject settings.

Interictal Electroencephalography (EEG) Findings in Children with Epilepsy and Bilateral Brain Lesions on Magnetic Resonance Imaging (MRI).

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Zubcevic, Smail; Milos, Maja; Catibusic, Feriha; Uzicanin, Sajra; Krdzalic, Belma

2015-12-01

Neuroimaging procedures and electroencephalography (EEG) are basic parts of investigation of patients with epilepsies. The aim is to try to assess relationship between bilaterally localized brain lesions found in routine management of children with newly diagnosed epilepsy and their interictal EEG findings. Total amount of 68 patients filled criteria for inclusion in the study that was performed at Neuropediatrics Department, Pediatric Hospital, University Clinical Center Sarajevo, or its outpatient clinic. There were 33 girls (48,5%) and 35 boys (51,5%). Average age at diagnosis of epilepsy was 3,5 years. Both neurological and neuropsychological examination in the moment of making diagnosis of epilepsy was normal in 27 (39,7%) patients, and showed some kind of delay or other neurological finding in 41 (60,3%). Brain MRI showed lesions that can be related to antenatal or perinatal events in most of the patients (ventricular dilation in 30,9%, delayed myelination and post-hypoxic changes in 27,9%). More than half of patients (55,9%) showed bilateral interictal epileptiform discharges on their EEGs, and further 14,7% had other kinds of bilateral abnormalities. Frequency of bilateral epileptic discharges showed statistically significant predominance on level of pEEG finding did not reveal significant type of EEG for assessed brain lesions. We conclude that there exists relationship between bilaterally localized brain MRI lesions and interictal bilateral epileptiform or nonspecific EEG findings in children with newly diagnosed epilepsies. These data are suggesting that in cases when they do not correlate there is a need for further investigation of seizure etiology.

Development of grouped icEEG for the study of cognitive processing

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Cihan Mehmet Kadipasaoglu

2015-07-01

Full Text Available Invasive intracranial EEG (icEEG offers a unique opportunity to study human cognitive networks at an unmatched spatiotemporal resolution. To date, the contributions of icEEG have been limited to the individual-level analyses or cohorts whose data are not integrated in any way. Here we discuss how grouped approaches to icEEG overcome challenges related to sparse-sampling, correct for individual variations in response and provide statistically valid models of brain activity in a population. By the generation of whole-brain activity maps, grouped icEEG enables the study of intra and interregional dynamics between distributed cortical substrates exhibiting task-dependent activity. In this fashion, grouped icEEG analyses can provide significant advances in understanding the mechanisms by which cortical networks give rise to cognitive functions.

WHAT POPS OUT IN POSITIONAL PRIMING OF POP-OUT: INSIGHTS FROM EVENT-RELATED EEG LATERALIZATIONS

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Ahu eGokce

2014-07-01

Full Text Available It is well established that, in visual pop-out search, reaction time (RT performance is influenced by cross-trial repetitions versus changes of target-defining attributes. One instance of this is referred to as ‘positional priming of pop-out (pPoP’ (Maljkovic & Nakayama, 1996. In positional PoP paradigms, the processing of the current target is examined depending on whether it occurs at the previous target or a previous distractor location, relative to a previously empty location (‘neutral’ baseline, permitting target facilitation and distractor inhibition to be dissociated. The present study combined RT measures with specific sensory- and motor-driven event-related lateralizations to track the time course of four distinct processing levels as a function of the target’s position across consecutive trials. The results showed that, relative to targets at previous target and ‘neutral’ locations, the appearance of a target at a previous distractor location was associated with a delayed build-up of the PCN wave, indicating that distractor positions are suppressed at early stages of visual processing. By contrast, presentation of a target at a previous target, relative to ‘neutral’ and distractor locations, modulated the elicitation of the subsequent sLRP wave, indicating that post-selective response selection is facilitated if the target occurred at the same position as on the previous trial. Overall, the results of present study provides electrophysiological evidence for the idea that target location priming (RT benefits does not originate from an enhanced coding of target saliency at repeated (target locations; instead, they arise (near- exclusively from processing levels subsequent to focal-attentional target selection.

Screening EEG in Aircrew Selection: Clinical Aerospace Neurology Perspective

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Clark, Jonathan B.; Riley, Terrence

2001-01-01

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

EEG in connection with coma.

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Wilson, John A; Nordal, Helge J

2013-01-08

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

Information-Theoretical Analysis of EEG Microstate Sequences in Python

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Frederic von Wegner

2018-06-01

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

Video-EEG epilepsian diagnostiikassa - milloin ja miksi?

OpenAIRE

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

2009-01-01

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

A comparative study of event-related coupling patterns during an auditory oddball task in schizophrenia

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Bachiller, Alejandro; Poza, Jesús; Gómez, Carlos; Molina, Vicente; Suazo, Vanessa; Hornero, Roberto

2015-02-01

Objective. The aim of this research is to explore the coupling patterns of brain dynamics during an auditory oddball task in schizophrenia (SCH). Approach. Event-related electroencephalographic (ERP) activity was recorded from 20 SCH patients and 20 healthy controls. The coupling changes between auditory response and pre-stimulus baseline were calculated in conventional EEG frequency bands (theta, alpha, beta-1, beta-2 and gamma), using three coupling measures: coherence, phase-locking value and Euclidean distance. Main results. Our results showed a statistically significant increase from baseline to response in theta coupling and a statistically significant decrease in beta-2 coupling in controls. No statistically significant changes were observed in SCH patients. Significance. Our findings support the aberrant salience hypothesis, since SCH patients failed to change their coupling dynamics between stimulus response and baseline when performing an auditory cognitive task. This result may reflect an impaired communication among neural areas, which may be related to abnormal cognitive functions.

Neurofeedback training aimed to improve focused attention and alertness in children with ADHD: a study of relative power of EEG rhythms using custom-made software application.

Science.gov (United States)

Hillard, Brent; El-Baz, Ayman S; Sears, Lonnie; Tasman, Allan; Sokhadze, Estate M

2013-07-01

Neurofeedback is a nonpharmacological treatment for attention-deficit hyperactivity disorder (ADHD). We propose that operant conditioning of electroencephalogram (EEG) in neurofeedback training aimed to mitigate inattention and low arousal in ADHD, will be accompanied by changes in EEG bands' relative power. Patients were 18 children diagnosed with ADHD. The neurofeedback protocol ("Focus/Alertness" by Peak Achievement Trainer) has a focused attention and alertness training mode. The neurofeedback protocol provides one for Focus and one for Alertness. This does not allow for collecting information regarding changes in specific EEG bands (delta, theta, alpha, low and high beta, and gamma) power within the 2 to 45 Hz range. Quantitative EEG analysis was completed on each of twelve 25-minute-long sessions using a custom-made MatLab application to determine the relative power of each of the aforementioned EEG bands throughout each session, and from the first session to the last session. Additional statistical analysis determined significant changes in relative power within sessions (from minute 1 to minute 25) and between sessions (from session 1 to session 12). Analysis was of relative power of theta, alpha, low and high beta, theta/alpha, theta/beta, and theta/low beta and theta/high beta ratios. Additional secondary measures of patients' post-neurofeedback outcomes were assessed, using an audiovisual selective attention test (IVA + Plus) and behavioral evaluation scores from the Aberrant Behavior Checklist. Analysis of data computed in the MatLab application, determined that theta/low beta and theta/alpha ratios decreased significantly from session 1 to session 12, and from minute 1 to minute 25 within sessions. The findings regarding EEG changes resulting from brain wave self-regulation training, along with behavioral evaluations, will help elucidate neural mechanisms of neurofeedback aimed to improve focused attention and alertness in ADHD.

Electroencephalogy (EEG) Feedback in Decision-Making

Science.gov (United States)

2015-08-26

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

Convolutional neural networks for event-related potential detection: impact of the architecture.

Science.gov (United States)

Cecotti, H

2017-07-01

The detection of brain responses at the single-trial level in the electroencephalogram (EEG) such as event-related potentials (ERPs) is a difficult problem that requires different processing steps to extract relevant discriminant features. While most of the signal and classification techniques for the detection of brain responses are based on linear algebra, different pattern recognition techniques such as convolutional neural network (CNN), as a type of deep learning technique, have shown some interests as they are able to process the signal after limited pre-processing. In this study, we propose to investigate the performance of CNNs in relation of their architecture and in relation to how they are evaluated: a single system for each subject, or a system for all the subjects. More particularly, we want to address the change of performance that can be observed between specifying a neural network to a subject, or by considering a neural network for a group of subjects, taking advantage of a larger number of trials from different subjects. The results support the conclusion that a convolutional neural network trained on different subjects can lead to an AUC above 0.9 by using an appropriate architecture using spatial filtering and shift invariant layers.

Burst suppression in sleep in a routine outpatient EEG ?

OpenAIRE

Kheder, Ammar; Bianchi, Matt T.; Westover, M. Brandon

2014-01-01

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

Cognitive deficits in amyotrophic lateral sclerosis evaluated by event-related potentials.

Science.gov (United States)

Ogawa, Tomohiro; Tanaka, Hideaki; Hirata, Koichi

2009-04-01

To determine the cognitive profiles in non-demented, relatively less handicapped patients with early-stage sporadic amyotrophic lateral sclerosis (ALS) by using neuropsychological tests, event-related potentials (ERPs) and clinical scale. We recruited 19 patients with sporadic ALS (eight with limb-onset, 11 with bulbar-onset) and 19 controls. In addition to the mini-mental state examination and the Wechsler adult intelligence scale-revised, we assessed the frontal lobe function with Wisconsin card sorting test, Stroop test and trail making test. We used auditory 'oddball' counting paradigm for the ERPs under 20-channel electroencephalogram (EEG) recording. Global field power (GFP) was computed, and its peak amplitudes and latencies of N1/N2/P3 were determined. The results of ERP and neuropsychological tests were correlated with respiratory function and clinical scale. No global cognitive impairment except for subtle frontal dysfunction was detected, although N1/N2/P3 GFP latencies were significantly prolonged in ALS patients than in the controls. Vital capacity correlated with P3 GFP amplitude, and the relative bulbar functional rating scale correlated with P3 GFP latency. Our findings indicated the presence of sub-clinical cognitive deficits in non-demented, sporadic ALS patients. In addition, clinical sub-types and respiratory function dependently influenced cognitive function in patients with sporadic ALS. ERP confirmed cognitive impairment in patients with sporadic ALS.

Educational simulation of the electroencephalogram (EEG)

NARCIS (Netherlands)

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

2001-01-01

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

A preliminary study of muscular artifact cancellation in single-channel EEG.

Science.gov (United States)

Chen, Xun; Liu, Aiping; Peng, Hu; Ward, Rabab K

2014-10-01

Electroencephalogram (EEG) recordings are often contaminated with muscular artifacts that strongly obscure the EEG signals and complicates their analysis. For the conventional case, where the EEG recordings are obtained simultaneously over many EEG channels, there exists a considerable range of methods for removing muscular artifacts. In recent years, there has been an increasing trend to use EEG information in ambulatory healthcare and related physiological signal monitoring systems. For practical reasons, a single EEG channel system must be used in these situations. Unfortunately, there exist few studies for muscular artifact cancellation in single-channel EEG recordings. To address this issue, in this preliminary study, we propose a simple, yet effective, method to achieve the muscular artifact cancellation for the single-channel EEG case. This method is a combination of the ensemble empirical mode decomposition (EEMD) and the joint blind source separation (JBSS) techniques. We also conduct a study that compares and investigates all possible single-channel solutions and demonstrate the performance of these methods using numerical simulations and real-life applications. The proposed method is shown to significantly outperform all other methods. It can successfully remove muscular artifacts without altering the underlying EEG activity. It is thus a promising tool for use in ambulatory healthcare systems.

Single Trial Classification of Evoked EEG Signals Due to RGB Colors

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Eman Alharbi

2016-03-01

Full Text Available Recently, the impact of colors on the brain signals has become one of the leading researches in BCI systems. These researches are based on studying the brain behavior after color stimulus, and finding a way to classify its signals offline without considering the real time. Moving to the next step, we present a real time classification model (online for EEG signals evoked by RGB colors stimuli, which is not presented in previous studies. In this research, EEG signals were recorded from 7 subjects through BCI2000 toolbox. The Empirical Mode Decomposition (EMD technique was used at the signal analysis stage. Various feature extraction methods were investigated to find the best and reliable set, including Event-related spectral perturbations (ERSP, Target mean with Feast Fourier Transform (FFT, Wavelet Packet Decomposition (WPD, Auto Regressive model (AR and EMD residual. A new feature selection method was created based on the peak's time of EEG signal when red and blue colors stimuli are presented. The ERP image was used to find out the peak's time, which was around 300 ms for the red color and around 450 ms for the blue color. The classification was performed using the Support Vector Machine (SVM classifier, LIBSVM toolbox being used for that purpose. The EMD residual was found to be the most reliable method that gives the highest classification accuracy with an average of 88.5% and with an execution time of only 14 seconds.

Event-related brain potentials in memory: correlates of episodic, semantic and implicit memory.

Science.gov (United States)

Wieser, Stephan; Wieser, Heinz Gregor

2003-06-01

To study cognitive evoked potentials, recorded from scalp EEG and foramen ovale electrodes, during activation of explicit and implicit memory. The subgroups of explicit memory, episodic and semantic memory, are looked at separately. A word-learning task was used, which has been shown to activate hippocampus in H(2)(15)O positron emission tomography studies. Subjects had to study and remember word pairs using different learning strategies: (i) associative word learning (AWL), which activates the episodic memory, (ii) deep single word encoding (DSWE), which activates the semantic memory, and (iii) shallow single word encoding (SSWE), which activates the implicit memory and serves as a baseline. The test included the 'remember/know' paradigm as a behavioural learning control. During the task condition, a 10-20 scalp EEG with additional electrodes in both temporal lobes regions was recorded from 11 healthy volunteers. In one patient with mesiotemporal lobe epilepsy, the EEG was recorded from bilateral foramen ovale electrodes directly from mesial temporal lobe structures. Event-related potentials (ERPs) were calculated off-line and visual and statistical analyses were made. Associative learning strategy produced the best memory performance and the best noetic awareness experience, whereas shallow single word encoding produced the worst performance and the smallest noetic awareness. Deep single word encoding performance was in between. ERPs differed according to the test condition, during both encoding and retrieval, from both the scalp EEG and the foramen ovale electrode recordings. Encoding showed significant differences between the shallow single word encoding (SSWE), which is mainly a function of graphical characteristics, and the other two strategies, deep single word (DSWE) and associative learning (AWL), in which there is a semantic processing of the meaning. ERPs generated by these two categories, which are both functions of explicit memory, differed as well

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

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Galina V. Portnova

2018-01-01

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

Video-EEG recording: a four-year clinical audit.

LENUS (Irish Health Repository)

O'Rourke, K

2012-02-03

In the setting of a regional neurological unit without an epilepsy surgery service as in our case, video-EEG telemetry is undertaken for three main reasons; to investigate whether frequent paroxysmal events represent seizures when there is clinical doubt, to attempt anatomical localization of partial seizures when standard EEG is unhelpful, and to attempt to confirm that seizures are non-epileptic when this is suspected. A clinical audit of all telemetry performed over a four-year period was carried out, in order to determine the clinical utility of this aspect of the service and to determine means of improving effectiveness in the unit. Analysis of the data showed a high rate of negative studies with no attacks recorded. Of the positive studies approximately 50% showed non-epileptic attacks. Strategies for improving the rate of positive investigations are discussed.

Age-related changes in neural oscillations supporting context memory retrieval.

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Strunk, Jonathan; James, Taylor; Arndt, Jason; Duarte, Audrey

2017-06-01

Recent evidence suggests that directing attention toward single item-context associations during encoding improves young and older adults' context memory performance and reduces demands on executive functions during retrieval. In everyday situations, there are many event features competing for our attention, and our ability to successfully recover those details may depend on our ability to ignore others. Failures of selective attention may contribute to older adults' context memory impairments. In the current electroencephalogram (EEG) study, we assessed the effects of age on processes supporting successful context memory retrieval of selectively attended features as indexed by neural oscillations. During encoding, young and older adults were directed to attend to a picture of an object and its relationship to one of two concurrently presented contextual details: a color or scene. At retrieval, we tested their memory for the object, its attended and unattended context features, and their confidence for both the attended and unattended features. Both groups showed greater memory for attended than unattended contextual features. However, older adults showed evidence of hyper-binding between attended and unattended context features while the young adults did not. EEG results in the theta band suggest that young and older adults recollect similar amounts of information but brain-behavior correlations suggest that this information was supportive of contextual memory performance, particularly for young adults. By contrast, sustained beta desynchronization, indicative of sensory reactivation and episodic reconstruction, was correlated with contextual memory performance for older adults only. We conclude that older adults' inhibition deficits during encoding reduced the selectivity of their contextual memories, which led to reliance on executive functions like episodic reconstruction to support successful memory retrieval. Copyright © 2017 Elsevier Ltd. All rights

Deficient multisensory integration in schizophrenia: an event-related potential study.

Science.gov (United States)

Stekelenburg, Jeroen J; Maes, Jan Pieter; Van Gool, Arthur R; Sitskoorn, Margriet; Vroomen, Jean

2013-07-01

In many natural audiovisual events (e.g., the sight of a face articulating the syllable /ba/), the visual signal precedes the sound and thus allows observers to predict the onset and the content of the sound. In healthy adults, the N1 component of the event-related brain potential (ERP), reflecting neural activity associated with basic sound processing, is suppressed if a sound is accompanied by a video that reliably predicts sound onset. If the sound does not match the content of the video (e.g., hearing /ba/ while lipreading /fu/), the later occurring P2 component is affected. Here, we examined whether these visual information sources affect auditory processing in patients with schizophrenia. The electroencephalography (EEG) was recorded in 18 patients with schizophrenia and compared with that of 18 healthy volunteers. As stimuli we used video recordings of natural actions in which visual information preceded and predicted the onset of the sound that was either congruent or incongruent with the video. For the healthy control group, visual information reduced the auditory-evoked N1 if compared to a sound-only condition, and stimulus-congruency affected the P2. This reduction in N1 was absent in patients with schizophrenia, and the congruency effect on the P2 was diminished. Distributed source estimations revealed deficits in the network subserving audiovisual integration in patients with schizophrenia. The results show a deficit in multisensory processing in patients with schizophrenia and suggest that multisensory integration dysfunction may be an important and, to date, under-researched aspect of schizophrenia. Copyright © 2013. Published by Elsevier B.V.

ADJUST: An automatic EEG artifact detector based on the joint use of spatial and temporal features.

Science.gov (United States)

Mognon, Andrea; Jovicich, Jorge; Bruzzone, Lorenzo; Buiatti, Marco

2011-02-01

A successful method for removing artifacts from electroencephalogram (EEG) recordings is Independent Component Analysis (ICA), but its implementation remains largely user-dependent. Here, we propose a completely automatic algorithm (ADJUST) that identifies artifacted independent components by combining stereotyped artifact-specific spatial and temporal features. Features were optimized to capture blinks, eye movements, and generic discontinuities on a feature selection dataset. Validation on a totally different EEG dataset shows that (1) ADJUST's classification of independent components largely matches a manual one by experts (agreement on 95.2% of the data variance), and (2) Removal of the artifacted components detected by ADJUST leads to neat reconstruction of visual and auditory event-related potentials from heavily artifacted data. These results demonstrate that ADJUST provides a fast, efficient, and automatic way to use ICA for artifact removal. Copyright © 2010 Society for Psychophysiological Research.

EEG Findings in Burnout Patients

NARCIS (Netherlands)

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

2010-01-01

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

Rewarming affects EEG background in term newborns with hypoxic-ischemic encephalopathy undergoing therapeutic hypothermia.

Science.gov (United States)

Birca, Ala; Lortie, Anne; Birca, Veronica; Decarie, Jean-Claude; Veilleux, Annie; Gallagher, Anne; Dehaes, Mathieu; Lodygensky, Gregory A; Carmant, Lionel

2016-04-01

To investigate how rewarming impacts the evolution of EEG background in neonates with hypoxic-ischemic encephalopathy (HIE) undergoing therapeutic hypothermia (TH). We recruited a retrospective cohort of 15 consecutive newborns with moderate (9) and severe (6) HIE monitored with a continuous EEG during TH and at least 12h after its end. EEG background was analyzed using conventional visual and quantitative EEG analysis methods including EEG discontinuity, absolute and relative spectral magnitudes. One patient with seizures on rewarming was excluded from analyses. Visual and quantitative analyses demonstrated significant changes in EEG background from pre- to post-rewarming, characterized by an increased EEG discontinuity, more pronounced in newborns with severe compared to moderate HIE. Neonates with moderate HIE also had an increase in the relative magnitude of slower delta and a decrease in higher frequency theta and alpha waves with rewarming. Rewarming affects EEG background in HIE newborns undergoing TH, which may represent a transient adaptive response or reflect an evolving brain injury. EEG background impairment induced by rewarming may represent a biomarker of evolving encephalopathy in HIE newborns undergoing TH and underscores the importance of continuously monitoring the brain health in critically ill neonates. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

BRAIN-COMPUTER-INTERFACE – SUPPORTED MOTOR IMAGERY TRAININTG FOR PATIENTS WITH HEMIPARESIS

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O. A. Mokienko

2013-01-01

Full Text Available The aim of study was to assess the feasibility of motor imagery supported brain-computer interface in patients with hemiparesis. 13 patients with central paresis of the hand and 15 healthy volunteers were learning to control EEG-based interface with feedback. No differences on interface control quality were found between patients and healthy subjects. The trainings were accompanied by the desynchronization of sensorimotor rhythm. In patients with cortical damage the source of EEG-activity was dislocated.

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

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Vangelis Sakkalis

2008-01-01

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

"Just like EKGs!" Should EEGs undergo a confirmatory interpretation by a clinical neurophysiologist?

Science.gov (United States)

Benbadis, Selim R

2013-01-01

The misdiagnosis of epilepsy is common and has serious consequences. A major contributor to the misdiagnosis of epilepsy is the tendency to overread normal EEGs as abnormal. In fact, the wrong diagnosis of seizures is sometimes based solely on the "abnormal" EEG. Reasons for the common overinterpretation of normal EEGs are mostly related to the lack of standards or mandatory training in EEG, and the erroneous assumption that all neurologists are trained to read EEGs. The most common overread pattern consists of benign, nonspecific, sharply contoured temporal transients. In particular, there is a common misconception that "phase reversals" are indicative of abnormality. Potential solutions include defining and ensuring EEG competency of neurologists who read EEGs, and perhaps providing a confirmatory reading by an electroencephalographer, as is done for EKGs.

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

OpenAIRE

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

2011-01-01

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

EEG use in a tertiary referral centre.

LENUS (Irish Health Repository)

O'Toole, O

2011-11-15

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

EEG activity in Muslim prayer: A pilot study

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Haider H. Alwasiti

2010-12-01

Full Text Available Almost all religions incorporate some form of meditation. Muslim prayer is the meditation of Islam. It is an obligatory prayer for all Muslims that is performed five times a day. Although a large body of literature exists on EEG changes in meditation, to date there has been no research published in a peer-reviewed journal on EEG changes during Muslim prayer. The purpose of this pilot study is to encourage further investigation on this type of meditation. Results of EEG analysis in twenty-five trials of Muslim prayer are reported. Some of the findings are consistent with the majority of the previous meditation studies (alpha rhythm slowing, increased alpha rhythm coherence. However, Muslim prayer does not show an increase in alpha and/or theta power like most of the results of other meditation studies. The possible cause of this discrepancy in meditation-related studies is highlighted and a systematic and standardised roadmap for future Muslim prayer EEG research is proposed.

Spatial-temporal-spectral EEG patterns of BOLD functional network connectivity dynamics

Science.gov (United States)

Lamoš, Martin; Mareček, Radek; Slavíček, Tomáš; Mikl, Michal; Rektor, Ivan; Jan, Jiří

2018-06-01

Objective. Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during electroencephalogram (EEG) data analysis may leave part of the neural activity unrecognized. We propose an approach that blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. Approach. The blind decomposition of EEG spectrogram by parallel factor analysis has been shown to be a useful technique for uncovering patterns of neural activity. The simultaneously acquired BOLD fMRI data were decomposed by independent component analysis. Dynamic functional connectivity was computed on the component’s time series using a sliding window correlation, and between-network connectivity states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of between-network connectivity states and the fluctuations of EEG spectral patterns. Main results. We found three patterns related to the dynamics of between-network connectivity states. The first pattern has dominant peaks in the alpha, beta, and gamma bands and is related to the dynamics between the auditory, sensorimotor, and attentional networks. The second pattern, with dominant peaks in the theta and low alpha bands, is related to the visual and default mode network. The third pattern, also with peaks in the theta and low alpha bands, is related to the auditory and frontal network. Significance. Our previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. In this study, we suggest that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral

Objective Audiometry using Ear-EEG

DEFF Research Database (Denmark)

Christensen, Christian Bech; Kidmose, Preben

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

Evaluation of EEG Features in Decoding Individual Finger Movements from One Hand

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Ran Xiao

2013-01-01

Full Text Available With the advancements in modern signal processing techniques, the field of brain-computer interface (BCI is progressing fast towards noninvasiveness. One challenge still impeding these developments is the limited number of features, especially movement-related features, available to generate control signals for noninvasive BCIs. A few recent studies investigated several movement-related features, such as spectral features in electrocorticography (ECoG data obtained through a spectral principal component analysis (PCA and direct use of EEG temporal data, and demonstrated the decoding of individual fingers. The present paper evaluated multiple movement-related features under the same task, that is, discriminating individual fingers from one hand using noninvasive EEG. The present results demonstrate the existence of a broadband feature in EEG to discriminate individual fingers, which has only been identified previously in ECoG. It further shows that multiple spectral features obtained from the spectral PCA yield an average decoding accuracy of 45.2%, which is significantly higher than the guess level (P<0.05 and other features investigated (P<0.05, including EEG spectral power changes in alpha and beta bands and EEG temporal data. The decoding of individual fingers using noninvasive EEG is promising to improve number of features for control, which can facilitate the development of noninvasive BCI applications with rich complexity.

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

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Lineu C. Fonseca

2011-12-01

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

Analysis of the Influence of Complexity and Entropy of Odorant on Fractal Dynamics and Entropy of EEG Signal.

Science.gov (United States)

Namazi, Hamidreza; Akrami, Amin; Nazeri, Sina; Kulish, Vladimir V

2016-01-01

An important challenge in brain research is to make out the relation between the features of olfactory stimuli and the electroencephalogram (EEG) signal. Yet, no one has discovered any relation between the structures of olfactory stimuli and the EEG signal. This study investigates the relation between the structures of EEG signal and the olfactory stimulus (odorant). We show that the complexity of the EEG signal is coupled with the molecular complexity of the odorant, where more structurally complex odorant causes less fractal EEG signal. Also, odorant having higher entropy causes the EEG signal to have lower approximate entropy. The method discussed here can be applied and investigated in case of patients with brain diseases as the rehabilitation purpose.

Brain single-photon emission tomography with 99mTc-HMPAO in neuropsychiatric systemic lupus erythematosus: relations with EEG and MRI findings and clinical manifestations

International Nuclear Information System (INIS)

Colamussi, P.; Giganti, M.; Cittanti, C.; Dovigo, L.; Trotta, F.; Tola, M.R.; Tamarozzi, R.; Lucignani, G.; Piffanelli, A.

1995-01-01

In the reported study the role of single-photon emission tomography (SPET) with technetium-99m hexamethylpropylene amine oxime (HMPAO) in the evaluation of CNS involvement in SLE was assessed and the relations between SPET perfusion defects, EEG examination, magnetic resonance imaging (MRI) findings and clinical presentation were examined. Twenty SLE patients with different NP manifestations were studied. Multiple areas of hypoperfusion, especially in the territory of the middle cerebral artery, were demonstrated by SPET analysis in all 20 patients. The number of hypoperfused areas and the degree of hypoperfusion, expressed by an asymmetry index (AI), were more marked in patients with multiple NP manifestations. MRI and EEG evaluations were positive for 14 of 18 and for 12 of 20 patients, respectively. In the patients with positive SPET and MRI, 87 MRI focal lesions and 63 hypoperfused areas were found, and for 51 of these 63 at least one MRI lesion was found in the same anatomical region. SPET examination of patients with a normal EEG showed fewer hypoperfused areas and a lower degree of asymmetry compared to patients with an abnormal EEG. SPET of patients with focal EEG abnormalities showed more hypoperfused areas (difference not statistically significant) and a higher AI than did SPET of the patients with diffuse EEG abnormalities. Seven of 11 anatomical regions with focal EEG abnormalities. Seven of 11 anatomical regions with focal EEG abnormalities had co-localized hypoperfused areas and in two of these seven no detectable MRI lesions were found. The analysis of SPET and NP manifestations showed that 12 of 20 patients had at least one positive correlation, always involving the areas with the highest AI. In total, 51/88 (58%) hypoperfused areas correlated with the MRI findings and 31/88 (35%) with NP manifestations; for seven of the latter no concurrent MRI lesions were detected in the same anatomical region. (orig.)

Analysis of Small Muscle Movement Effects on EEG Signals

Science.gov (United States)

2016-12-22

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

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.

EEG correlates of P300-based brain-computer interface (BCI) performance in people with amyotrophic lateral sclerosis

Science.gov (United States)

Mak, Joseph N.; McFarland, Dennis J.; Vaughan, Theresa M.; McCane, Lynn M.; Tsui, Phillippa Z.; Zeitlin, Debra J.; Sellers, Eric W.; Wolpaw, Jonathan R.

2012-04-01

The purpose of this study was to identify electroencephalography (EEG) features that correlate with P300-based brain-computer interface (P300 BCI) performance in people with amyotrophic lateral sclerosis (ALS). Twenty people with ALS used a P300 BCI spelling application in copy-spelling mode. Three types of EEG features were found to be good predictors of P300 BCI performance: (1) the root-mean-square amplitude and (2) the negative peak amplitude of the event-related potential to target stimuli (target ERP) at Fz, Cz, P3, Pz, and P4; and (3) EEG theta frequency (4.5-8 Hz) power at Fz, Cz, P3, Pz, P4, PO7, PO8 and Oz. A statistical prediction model that used a subset of these features accounted for >60% of the variance in copy-spelling performance (p < 0.001, mean R2 = 0.6175). The correlations reflected between-subject, rather than within-subject, effects. The results enhance understanding of performance differences among P300 BCI users. The predictors found in this study might help in: (1) identifying suitable candidates for long-term P300 BCI operation; (2) assessing performance online. Further work on within-subject effects needs to be done to establish whether P300 BCI user performance could be improved by optimizing one or more of these EEG features.

The EEG as an index of neuromodulator balance in memory and mental illness

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Costa eVakalopoulos

2014-04-01

Full Text Available There is a strong correlation between signature EEG frequency patterns and the relative levels of distinct neuromodulators. These associations become particularly evident during the sleep-wake cycle. The monoamine-acetylcholine balance hypothesis is a theory of neurophysiological markers of the EEG and a detailed description of the findings that support this proposal are presented in this paper. According to this model alpha rhythm reflects the relative predominance of cholinergic muscarinic signals and delta rhythm that of monoaminergic receptor effects. Both high voltage synchronized rhythms are likely mediated by inhibitory Gαi/o-mediated transduction of inhibitory interneurons. Cognitively, alpha and delta EEG measures are proposed to indicate automatic and flexible strategies, respectively. Sleep is associated with marked changes in relative neuromodulator levels corresponding to EEG markers of distinct stages. Sleep studies on memory consolidation present some of the strongest evidence yet for the respective roles of monoaminergic and cholinergic projections in declarative and non-declarative memory processes, a key theoretical premise for understanding the data. Affective dysregulation is reflected in altered EEG patterns during sleep.

The EEG as an index of neuromodulator balance in memory and mental illness.

Science.gov (United States)

Vakalopoulos, Costa

2014-01-01

There is a strong correlation between signature EEG frequency patterns and the relative levels of distinct neuromodulators. These associations become particularly evident during the sleep-wake cycle. The monoamine-acetylcholine balance hypothesis is a theory of neurophysiological markers of the EEG and a detailed description of the findings that support this proposal are presented in this paper. According to this model alpha rhythm reflects the relative predominance of cholinergic muscarinic signals and delta rhythm that of monoaminergic receptor effects. Both high voltage synchronized rhythms are likely mediated by inhibitory Gαi/o-mediated transduction of inhibitory interneurons. Cognitively, alpha and delta EEG measures are proposed to indicate automatic and flexible strategies, respectively. Sleep is associated with marked changes in relative neuromodulator levels corresponding to EEG markers of distinct stages. Sleep studies on memory consolidation present some of the strongest evidence yet for the respective roles of monoaminergic and cholinergic projections in declarative and non-declarative memory processes, a key theoretical premise for understanding the data. Affective dysregulation is reflected in altered EEG patterns during sleep.

The definition of exertion-related cardiac events.

Science.gov (United States)

Rai, M; Thompson, P D

2011-02-01

Vigorous physical activity increases the risk of sudden cardiac death (SCD) and acute myocardial infarction (AMI) but there is no standard definition as to what constitutes an exertion-related cardiac event, specifically the time interval between physical exertion and cardiac event. A systematic review of studies related to exertion-related cardiac events was performed and the time interval between exertion and the event or the symptoms leading to the event was looked for in all the articles selected for inclusion. A total of 12 of 26 articles "suggested" or "defined" exertion-related events as those events whose symptoms started during or within 1 h of exertion. Others used definitions of 0.5 h, 2 h, "during exertion", "during or immediately post exertion" and "during or within several hours after exertion". It is suggested, therefore, that the definition of an exertion-related cardiac event be established as a cardiac event in which symptoms started during or within 1 h of physical exertion.

Applying an Archetype-Based Approach to Electroencephalography/Event-Related Potential Experiments in the EEGBase Resource.

Science.gov (United States)

Papež, Václav; Mouček, Roman

2017-01-01

The purpose of this study is to investigate the feasibility of applying openEHR (an archetype-based approach for electronic health records representation) to modeling data stored in EEGBase, a portal for experimental electroencephalography/event-related potential (EEG/ERP) data management. The study evaluates re-usage of existing openEHR archetypes and proposes a set of new archetypes together with the openEHR templates covering the domain. The main goals of the study are to (i) link existing EEGBase data/metadata and openEHR archetype structures and (ii) propose a new openEHR archetype set describing the EEG/ERP domain since this set of archetypes currently does not exist in public repositories. The main methodology is based on the determination of the concepts obtained from EEGBase experimental data and metadata that are expressible structurally by the openEHR reference model and semantically by openEHR archetypes. In addition, templates as the third openEHR resource allow us to define constraints over archetypes. Clinical Knowledge Manager (CKM), a public openEHR archetype repository, was searched for the archetypes matching the determined concepts. According to the search results, the archetypes already existing in CKM were applied and the archetypes not existing in the CKM were newly developed. openEHR archetypes support linkage to external terminologies. To increase semantic interoperability of the new archetypes, binding with the existing odML electrophysiological terminology was assured. Further, to increase structural interoperability, also other current solutions besides EEGBase were considered during the development phase. Finally, a set of templates using the selected archetypes was created to meet EEGBase requirements. A set of eleven archetypes that encompassed the domain of experimental EEG/ERP measurements were identified. Of these, six were reused without changes, one was extended, and four were newly created. All archetypes were arranged in the

A New Approach to Eliminate High Amplitude Artifacts in EEG Signals

Directory of Open Access Journals (Sweden)

Ana Rita Teixeira

2016-09-01

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

Hypnagogic imagery and EEG activity.

Science.gov (United States)

Hayashi, M; Katoh, K; Hori, T

1999-04-01

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

EEG applications for sport and performance.

Science.gov (United States)

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

2008-08-01

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

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

Science.gov (United States)

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

2017-07-01

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

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

Science.gov (United States)

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

2017-09-01

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

Acoustic processing of temporally modulated sounds in infants: evidence from a combined near-infrared spectroscopy and EEG study

Directory of Open Access Journals (Sweden)

Silke eTelkemeyer

2011-04-01

Full Text Available Speech perception requires rapid extraction of the linguistic content from the acoustic signal. The ability to efficiently process rapid changes in auditory information is important for decoding speech and thereby crucial during language acquisition. Investigating functional networks of speech perception in infancy might elucidate neuronal ensembles supporting perceptual abilities that gate language acquisition. Interhemispheric specializations for language have been demonstrated in infants. How these asymmetries are shaped by basic temporal acoustic properties is under debate. We recently provided evidence that newborns process non-linguistic sounds sharing temporal features with language in a differential and lateralized fashion. The present study used the same material while measuring brain responses of 6 and 3 month old infants using simultaneous recordings of electroencephalography (EEG and near-infrared spectroscopy (NIRS. NIRS reveals that the lateralization observed in newborns remains constant over the first months of life. While fast acoustic modulations elicit bilateral neuronal activations, slow modulations lead to right-lateralized responses. Additionally, auditory evoked potentials and oscillatory EEG responses show differential responses for fast and slow modulations indicating a sensitivity for temporal acoustic variations. Oscillatory responses reveal an effect of development, that is, 6 but not 3 month old infants show stronger theta-band desynchronization for slowly modulated sounds. Whether this developmental effect is due to increasing fine-grained perception for spectrotemporal sounds in general remains speculative. Our findings support the notion that a more general specialization for acoustic properties can be considered the basis for lateralization of speech perception. The results show that concurrent assessment of vascular based imaging and electrophysiological responses have great potential in the research on language

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

Science.gov (United States)

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

1998-06-01

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

Analysis of the Influence of Complexity and Entropy of Odorant on Fractal Dynamics and Entropy of EEG Signal

OpenAIRE

Hamidreza Namazi; Amin Akrami; Sina Nazeri; Vladimir V. Kulish

2016-01-01

An important challenge in brain research is to make out the relation between the features of olfactory stimuli and the electroencephalogram (EEG) signal. Yet, no one has discovered any relation between the structures of olfactory stimuli and the EEG signal. This study investigates the relation between the structures of EEG signal and the olfactory stimulus (odorant). We show that the complexity of the EEG signal is coupled with the molecular complexity of the odorant, where more structurally ...

Distinct modulation of event-related potentials during motor preparation in patients with motor conversion disorder.

Directory of Open Access Journals (Sweden)

Rebekah L Blakemore

Full Text Available OBJECTIVE: Conversion paresis patients and healthy people feigning weakness both exhibit weak voluntary movement without detectable neuropathology. Uniquely, conversion patients lack a sense of conscious awareness of the origin of their impairment. We investigated whether conversion paresis patients show distinct electroencephalographic (EEG markers associated with their unconscious movement deficits. METHODS: Six unilateral upper limb conversion paresis patients, 12 feigning participants asked to mimic weakness and 12 control participants performed a precued reaction time task, requiring movements of either hand, depending on precue information. Performance measures (force, reaction and movement time, and event-related EEG potentials (ERP were compared, between groups and across hands or hemisphere, using linear mixed models. RESULTS: Feigners generated the same inter-hand difference in reaction and movement time as expressed by patients, even though no specific targets were set nor feedback given on these measures. We found novel ERP signatures specific to patients. When the symptomatic hand was precued, the P3 ERP component accompanying the precue was dramatically larger in patients than in feigning participants. Additionally, in patients the earlier N1 ERP component was diminished when the precue signalled either the symptomatic or asymptomatic hand. CONCLUSIONS: These results are consistent with previous suggestions that lack of awareness of the origin of their symptoms in conversion disorder patients may result from suppression of brain activity normally related to self-agency. In patients the diminished N1 to all precues is consistent with a generalised reduction in cognitive processing of movement-related precues. The P3 enhancement in patients is unlikely to simply reflect changes required for generation of impaired movements, because it was not seen in feigners showing the same behavioural deficits. Rather, this P3 enhancement in

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

Science.gov (United States)

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

2018-01-01

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

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

Science.gov (United States)

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

2016-06-01

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

Standardized EEG interpretation in patients after cardiac arrest: Correlation with other prognostic predictors.

OpenAIRE

Beuchat, I.; Solari, D.; Novy, J.; Oddo, M.; Rossetti, A.O.

2018-01-01

Standardized EEG patterns according to the American Clinical Neurophysiology Society (ACNS) ("highly malignant", "malignant" and "benign") demonstrated good correlation with outcome after cardiac arrest (CA). However, this approach relates to EEGs after target temperature management (TTM), and correlation to other recognized outcome predictors remains unknown. To investigate the relationship between categorized EEG and other outcome predictors, during and after TTM, at different temperatur...

A Longitudinal Investigation of Mandarin-speaking Preschoolers' Relation of Events in Narratives: From Unrelated to Related Events

Directory of Open Access Journals (Sweden)

Wen-hui Sah

2007-06-01

Full Text Available This study focuses on the way preschoolers relate events in a story. Twelve Mandarin-speaking preschoolers served as subjects; their narratives were elicited through the use of a picture book, Frog, where are you? Our data suggest that children’s progression from treating single, unrelated events to related ones requires proper linguistic and cognitive capacities. The data also support earlier findings that most 5-year-olds are not able to relate a chain of events well. Additionally, it is found that there is dissociation in abilities for producing linguistic expressions and for inferring relations between events. We try to interpret the dissociation in terms of Karmiloff-Smith’s problem-solving model.

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

Science.gov (United States)

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

2017-12-01

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

Embedding Dimension Selection for Adaptive Singular Spectrum Analysis of EEG Signal.

Science.gov (United States)

Xu, Shanzhi; Hu, Hai; Ji, Linhong; Wang, Peng

2018-02-26

The recorded electroencephalography (EEG) signal is often contaminated with different kinds of artifacts and noise. Singular spectrum analysis (SSA) is a powerful tool for extracting the brain rhythm from a noisy EEG signal. By analyzing the frequency characteristics of the reconstructed component (RC) and the change rate in the trace of the Toeplitz matrix, it is demonstrated that the embedding dimension is related to the frequency bandwidth of each reconstructed component, in consistence with the component mixing in the singular value decomposition step. A method for selecting the embedding dimension is thereby proposed and verified by simulated EEG signal based on the Markov Process Amplitude (MPA) EEG Model. Real EEG signal is also collected from the experimental subjects under both eyes-open and eyes-closed conditions. The experimental results show that based on the embedding dimension selection method, the alpha rhythm can be extracted from the real EEG signal by the adaptive SSA, which can be effectively utilized to distinguish between the eyes-open and eyes-closed states.

Embedding Dimension Selection for Adaptive Singular Spectrum Analysis of EEG Signal

Directory of Open Access Journals (Sweden)

Shanzhi Xu

2018-02-01

Full Text Available The recorded electroencephalography (EEG signal is often contaminated with different kinds of artifacts and noise. Singular spectrum analysis (SSA is a powerful tool for extracting the brain rhythm from a noisy EEG signal. By analyzing the frequency characteristics of the reconstructed component (RC and the change rate in the trace of the Toeplitz matrix, it is demonstrated that the embedding dimension is related to the frequency bandwidth of each reconstructed component, in consistence with the component mixing in the singular value decomposition step. A method for selecting the embedding dimension is thereby proposed and verified by simulated EEG signal based on the Markov Process Amplitude (MPA EEG Model. Real EEG signal is also collected from the experimental subjects under both eyes-open and eyes-closed conditions. The experimental results show that based on the embedding dimension selection method, the alpha rhythm can be extracted from the real EEG signal by the adaptive SSA, which can be effectively utilized to distinguish between the eyes-open and eyes-closed states.

Brain single-photon emission tomography with {sup 99m}Tc-HMPAO in neuropsychiatric systemic lupus erythematosus: relations with EEG and MRI findings and clinical manifestations

Energy Technology Data Exchange (ETDEWEB)

Colamussi, P. [Dept. of Nuclear Medicine, Univ. of Ferrara (Italy); Giganti, M. [Dept. of Nuclear Medicine, Univ. of Ferrara (Italy); Cittanti, C. [Dept. of Nuclear Medicine, Univ. of Ferrara (Italy); Dovigo, L. [Inst. of Neurology, Univ. of Ferrara (Italy); Trotta, F. [Inst. of Neurology, Univ. of Ferrara (Italy); Tola, M.R. [Div. of Rheumatology, S. Anna Hospital, Ferrara (Italy); Tamarozzi, R. [Radiology Dept., S. Anna Hospital, Ferrara (Italy); Lucignani, G. [INB-CNR Dept. of Nuclear Medicine, H.S. Raffaele, Milan (Italy); Piffanelli, A. [Dept. of Nuclear Medicine, Univ. of Ferrara (Italy)

1995-01-01

In the reported study the role of single-photon emission tomography (SPET) with technetium-99m hexamethylpropylene amine oxime (HMPAO) in the evaluation of CNS involvement in SLE was assessed and the relations between SPET perfusion defects, EEG examination, magnetic resonance imaging (MRI) findings and clinical presentation were examined. Twenty SLE patients with different NP manifestations were studied. Multiple areas of hypoperfusion, especially in the territory of the middle cerebral artery, were demonstrated by SPET analysis in all 20 patients. The number of hypoperfused areas and the degree of hypoperfusion, expressed by an asymmetry index (AI), were more marked in patients with multiple NP manifestations. MRI and EEG evaluations were positive for 14 of 18 and for 12 of 20 patients, respectively. In the patients with positive SPET and MRI, 87 MRI focal lesions and 63 hypoperfused areas were found, and for 51 of these 63 at least one MRI lesion was found in the same anatomical region. SPET examination of patients with a normal EEG showed fewer hypoperfused areas and a lower degree of asymmetry compared to patients with an abnormal EEG. SPET of patients with focal EEG abnormalities showed more hypoperfused areas (difference not statistically significant) and a higher AI than did SPET of the patients with diffuse EEG abnormalities. Seven of 11 anatomical regions with focal EEG abnormalities. Seven of 11 anatomical regions with focal EEG abnormalities had co-localized hypoperfused areas and in two of these seven no detectable MRI lesions were found. The analysis of SPET and NP manifestations showed that 12 of 20 patients had at least one positive correlation, always involving the areas with the highest AI. In total, 51/88 (58%) hypoperfused areas correlated with the MRI findings and 31/88 (35%) with NP manifestations; for seven of the latter no concurrent MRI lesions were detected in the same anatomical region. (orig.)

Orthographic recognition in late adolescents: an assessment through event-related brain potentials.

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González-Garrido, Andrés Antonio; Gómez-Velázquez, Fabiola Reveca; Rodríguez-Santillán, Elizabeth

2014-04-01

Reading speed and efficiency are achieved through the automatic recognition of written words. Difficulties in learning and recognizing the orthography of words can arise despite reiterative exposure to texts. This study aimed to investigate, in native Spanish-speaking late adolescents, how different levels of orthographic knowledge might result in behavioral and event-related brain potential differences during the recognition of orthographic errors. Forty-five healthy high school students were selected and divided into 3 equal groups (High, Medium, Low) according to their performance on a 5-test battery of orthographic knowledge. All participants performed an orthographic recognition task consisting of the sequential presentation of a picture (object, fruit, or animal) followed by a correctly, or incorrectly, written word (orthographic mismatch) that named the picture just shown. Electroencephalogram (EEG) recording took place simultaneously. Behavioral results showed that the Low group had a significantly lower number of correct responses and increased reaction times while processing orthographical errors. Tests showed significant positive correlations between higher performance on the experimental task and faster and more accurate reading. The P150 and P450 components showed higher voltages in the High group when processing orthographic errors, whereas N170 seemed less lateralized to the left hemisphere in the lower orthographic performers. Also, trials with orthographic errors elicited a frontal P450 component that was only evident in the High group. The present results show that higher levels of orthographic knowledge correlate with high reading performance, likely because of faster and more accurate perceptual processing, better visual orthographic representations, and top-down supervision, as the event-related brain potential findings seem to suggest.

A Brain-Machine Interface Based on ERD/ERS for an Upper-Limb Exoskeleton Control.

Science.gov (United States)

Tang, Zhichuan; Sun, Shouqian; Zhang, Sanyuan; Chen, Yumiao; Li, Chao; Chen, Shi

2016-12-02

To recognize the user's motion intention, brain-machine interfaces (BMI) usually decode movements from cortical activity to control exoskeletons and neuroprostheses for daily activities. The aim of this paper is to investigate whether self-induced variations of the electroencephalogram (EEG) can be useful as control signals for an upper-limb exoskeleton developed by us. A BMI based on event-related desynchronization/synchronization (ERD/ERS) is proposed. In the decoder-training phase, we investigate the offline classification performance of left versus right hand and left hand versus both feet by using motor execution (ME) or motor imagery (MI). The results indicate that the accuracies of ME sessions are higher than those of MI sessions, and left hand versus both feet paradigm achieves a better classification performance, which would be used in the online-control phase. In the online-control phase, the trained decoder is tested in two scenarios (wearing or without wearing the exoskeleton). The MI and ME sessions wearing the exoskeleton achieve mean classification accuracy of 84.29% ± 2.11% and 87.37% ± 3.06%, respectively. The present study demonstrates that the proposed BMI is effective to control the upper-limb exoskeleton, and provides a practical method by non-invasive EEG signal associated with human natural behavior for clinical applications.

Frontal EEG asymmetry in borderline personality disorder is associated with alexithymia

OpenAIRE

Flasbeck, Vera; Popkirov, Stoyan; Brüne, Martin

2017-01-01

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

The Mozart Effect: A quantitative EEG study.

Science.gov (United States)

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

2015-09-01

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

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%.

Computerized spectral analyses of EEG in chronic schizophrenic patients

International Nuclear Information System (INIS)

Fujita, Haruhiro

1985-01-01

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

A study of verbal and spatial information processing using event-related potentials and positron emission tomography

International Nuclear Information System (INIS)

Ninomiya, Hideaki; Ichimiya, Atsushi; Chen, Chung-Ho; Onitsuka, Toshiaki; Kuwabara, Yasuo; Otsuka, Makoto; Ichiya, Yuichi

1997-01-01

The activated cerebral regions and the timing of information processing in the hemispheres was investigated using event-related potentials (ERP) and regional cerebral blood flow (rCBF) as the neurophysiological indicators. Seven men and one woman (age 19-27 years) were asked to categorize two-syllable Japanese nouns (verbal condition) and to judge the difference between pairs of rectangles (spatial condition), both tests presented on a monochrome display. In the electroencephalogram (EEG) session, EEG were recorded from 16 electrode sites, with linked earlobe electrodes as reference. In the positron emission tomography (PET) session, rCBF were measured by the 15 O-labeled H 2 O bolus injection method. Regions of interest were the frontal, temporal, parietal, occipital and central lobes, and the entire cerebral hemispheres. When the subtracted voltages of the ERP in homologous scalp sites were compared for the verbal and spatial conditions, the significant differences were at F7·F8 and T5·T6 (the 10-20 system). The latencies of the differences at T5·T6 were around 200, 250 and 320 ms. A significant difference in rCBF between the verbal and spatial conditions was found only in the temporal region. It was concluded that early processing of information, that is, registration and simple recognition, may be performed mainly in the left temporal lobe for verbal information and in the right for spatial information. (author)

Change in brain activity through virtual reality-based brain-machine communication in a chronic tetraplegic subject with muscular dystrophy.

Science.gov (United States)

Hashimoto, Yasunari; Ushiba, Junichi; Kimura, Akio; Liu, Meigen; Tomita, Yutaka

2010-09-16

For severely paralyzed people, a brain-computer interface (BCI) provides a way of re-establishing communication. Although subjects with muscular dystrophy (MD) appear to be potential BCI users, the actual long-term effects of BCI use on brain activities in MD subjects have yet to be clarified. To investigate these effects, we followed BCI use by a chronic tetraplegic subject with MD over 5 months. The topographic changes in an electroencephalogram (EEG) after long-term use of the virtual reality (VR)-based BCI were also assessed. Our originally developed BCI system was used to classify an EEG recorded over the sensorimotor cortex in real time and estimate the user's motor intention (MI) in 3 different limb movements: feet, left hand, and right hand. An avatar in the internet-based VR was controlled in accordance with the results of the EEG classification by the BCI. The subject was trained to control his avatar via the BCI by strolling in the VR for 1 hour a day and then continued the same training twice a month at his home. After the training, the error rate of the EEG classification decreased from 40% to 28%. The subject successfully walked around in the VR using only his MI and chatted with other users through a voice-chat function embedded in the internet-based VR. With this improvement in BCI control, event-related desynchronization (ERD) following MI was significantly enhanced (p < 0.01) for feet MI (from -29% to -55%), left-hand MI (from -23% to -42%), and right-hand MI (from -22% to -51%). These results show that our subject with severe MD was able to learn to control his EEG signal and communicate with other users through use of VR navigation and suggest that an internet-based VR has the potential to provide paralyzed people with the opportunity for easy communication.

Change in brain activity through virtual reality-based brain-machine communication in a chronic tetraplegic subject with muscular dystrophy

Directory of Open Access Journals (Sweden)

Liu Meigen

2010-09-01

Full Text Available Abstract Background For severely paralyzed people, a brain-computer interface (BCI provides a way of re-establishing communication. Although subjects with muscular dystrophy (MD appear to be potential BCI users, the actual long-term effects of BCI use on brain activities in MD subjects have yet to be clarified. To investigate these effects, we followed BCI use by a chronic tetraplegic subject with MD over 5 months. The topographic changes in an electroencephalogram (EEG after long-term use of the virtual reality (VR-based BCI were also assessed. Our originally developed BCI system was used to classify an EEG recorded over the sensorimotor cortex in real time and estimate the user's motor intention (MI in 3 different limb movements: feet, left hand, and right hand. An avatar in the internet-based VR was controlled in accordance with the results of the EEG classification by the BCI. The subject was trained to control his avatar via the BCI by strolling in the VR for 1 hour a day and then continued the same training twice a month at his home. Results After the training, the error rate of the EEG classification decreased from 40% to 28%. The subject successfully walked around in the VR using only his MI and chatted with other users through a voice-chat function embedded in the internet-based VR. With this improvement in BCI control, event-related desynchronization (ERD following MI was significantly enhanced (p Conclusions These results show that our subject with severe MD was able to learn to control his EEG signal and communicate with other users through use of VR navigation and suggest that an internet-based VR has the potential to provide paralyzed people with the opportunity for easy communication.

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.

Integration of EEG lead placement templates into traditional technologist-based staffing models reduces costs in continuous video-EEG monitoring service.

Science.gov (United States)

Kolls, Brad J; Lai, Amy H; Srinivas, Anang A; Reid, Robert R

2014-06-01

The purpose of this study was to determine the relative cost reductions within different staffing models for continuous video-electroencephalography (cvEEG) service by introducing a template system for 10/20 lead application. We compared six staffing models using decision tree modeling based on historical service line utilization data from the cvEEG service at our center. Templates were integrated into technologist-based service lines in six different ways. The six models studied were templates for all studies, templates for intensive care unit (ICU) studies, templates for on-call studies, templates for studies of ≤ 24-hour duration, technologists for on-call studies, and technologists for all studies. Cost was linearly related to the study volume for all models with the "templates for all" model incurring the lowest cost. The "technologists for all" model carried the greatest cost. Direct cost comparison shows that any introduction of templates results in cost savings, with the templates being used for patients located in the ICU being the second most cost efficient and the most practical of the combined models to implement. Cost difference between the highest and lowest cost models under the base case produced an annual estimated savings of $267,574. Implementation of the ICU template model at our institution under base case conditions would result in a $205,230 savings over our current "technologist for all" model. Any implementation of templates into a technologist-based cvEEG service line results in cost savings, with the most significant annual savings coming from using the templates for all studies, but the most practical implementation approach with the second highest cost reduction being the template used in the ICU. The lowered costs determined in this work suggest that a template-based cvEEG service could be supported at smaller centers with significantly reduced costs and could allow for broader use of cvEEG patient monitoring.

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-07-01

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

Event-related potential correlates of suspicious thoughts in individuals with schizotypal personality features.

Science.gov (United States)

Li, Xue-bing; Huang, Jia; Cheung, Eric F C; Gong, Qi-yong; Chan, Raymond C K

2011-01-01

Suspiciousness is a common feature of schizophrenia. However, suspicious thoughts are also commonly experienced by the general population. This study aimed to examine the underlying neural mechanism of suspicious thoughts in individuals with and without schizotypal personality disorder (SPD)-proneness, using an event-related potential (ERP) paradigm. Electroencephalography (EEG) was recorded when the "feeling of being seen through" was evoked in the participants. The findings showed a prominent positive deflection of the difference wave within the time window 250-400 ms after stimuli presentation in both SPD-prone and non-SPD-prone groups. Furthermore, the P3 amplitude was significantly reduced in the SPD-prone group compared to the non-SPD-prone group. The current density analysis also indicated hypoactivity in both frontal and temporal regions in the SPD-prone group, suggesting that the frontotemporal cortical network may play a role in the onset of suspicious thoughts. The P3 of difference wave was inversely correlated with the cognitive-perception factor and the suspiciousness/paranoid ideation trait, which provided preliminary electrophysiological evidence for the association of suspiciousness with SPD features.

Aircraft noise effects on sleep: a systematic comparison of EEG awakenings and automatically detected cardiac activations

International Nuclear Information System (INIS)

Basner, Mathias; Müller, Uwe; Elmenhorst, Eva-Maria; Kluge, Götz; Griefahn, Barbara

2008-01-01

Polysomnography is the gold standard for investigating noise effects on sleep, but data collection and analysis are sumptuous and expensive. We recently developed an algorithm for the automatic identification of cardiac activations associated with cortical arousals, which uses heart rate information derived from a single electrocardiogram (ECG) channel. We hypothesized that cardiac activations can be used as estimates for EEG awakenings. Polysomnographic EEG awakenings and automatically detected cardiac activations were systematically compared using laboratory data of 112 subjects (47 male, mean ± SD age 37.9 ± 13 years), 985 nights and 23 855 aircraft noise events (ANEs). The probability of automatically detected cardiac activations increased monotonically with increasing maximum sound pressure levels of ANEs, exceeding the probability of EEG awakenings by up to 18.1%. If spontaneous reactions were taken into account, exposure–response curves were practically identical for EEG awakenings and cardiac activations. Automatically detected cardiac activations may be used as estimates for EEG awakenings. More investigations are needed to further validate the ECG algorithm in the field and to investigate inter-individual differences in its ability to predict EEG awakenings. This inexpensive, objective and non-invasive method facilitates large-scale field studies on the effects of traffic noise on sleep

Rhythms of EEG and cognitive processes

Directory of Open Access Journals (Sweden)

Novikova S.I.

2015-06-01

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

Synaptic damage underlies EEG abnormalities in postanoxic encephalopathy: A computational study.

Science.gov (United States)

Ruijter, B J; Hofmeijer, J; Meijer, H G E; van Putten, M J A M

2017-09-01

In postanoxic coma, EEG patterns indicate the severity of encephalopathy and typically evolve in time. We aim to improve the understanding of pathophysiological mechanisms underlying these EEG abnormalities. We used a mean field model comprising excitatory and inhibitory neurons, local synaptic connections, and input from thalamic afferents. Anoxic damage is modeled as aggravated short-term synaptic depression, with gradual recovery over many hours. Additionally, excitatory neurotransmission is potentiated, scaling with the severity of anoxic encephalopathy. Simulations were compared with continuous EEG recordings of 155 comatose patients after cardiac arrest. The simulations agree well with six common categories of EEG rhythms in postanoxic encephalopathy, including typical transitions in time. Plausible results were only obtained if excitatory synapses were more severely affected by short-term synaptic depression than inhibitory synapses. In postanoxic encephalopathy, the evolution of EEG patterns presumably results from gradual improvement of complete synaptic failure, where excitatory synapses are more severely affected than inhibitory synapses. The range of EEG patterns depends on the excitation-inhibition imbalance, probably resulting from long-term potentiation of excitatory neurotransmission. Our study is the first to relate microscopic synaptic dynamics in anoxic brain injury to both typical EEG observations and their evolution in time. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

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

Science.gov (United States)

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

2007-05-01

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

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

OpenAIRE

Gang Wang; Doutian Ren

2013-01-01

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

Concordance and discordance between PET images and foci of scalp EEG

International Nuclear Information System (INIS)

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

1989-01-01

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

Gender and Age Related Effects While Watching TV Advertisements: An EEG Study.

Science.gov (United States)

Cartocci, Giulia; Cherubino, Patrizia; Rossi, Dario; Modica, Enrica; Maglione, Anton Giulio; di Flumeri, Gianluca; Babiloni, Fabio

2016-01-01

The aim of the present paper is to show how the variation of the EEG frontal cortical asymmetry is related to the general appreciation perceived during the observation of TV advertisements, in particular considering the influence of the gender and age on it. In particular, we investigated the influence of the gender on the perception of a car advertisement (Experiment 1) and the influence of the factor age on a chewing gum commercial (Experiment 2). Experiment 1 results showed statistically significant higher approach values for the men group throughout the commercial. Results from Experiment 2 showed significant lower values by older adults for the spot, containing scenes not very enjoyed by them. In both studies, there was no statistical significant difference in the scene relative to the product offering between the experimental populations, suggesting the absence in our study of a bias towards the specific product in the evaluated populations. These evidences state the importance of the creativity in advertising, in order to attract the target population.

Response inhibition in borderline personality disorder: event-related potentials in a Go/Nogo task.

Science.gov (United States)

Ruchsow, M; Groen, G; Kiefer, M; Buchheim, A; Walter, H; Martius, P; Reiter, M; Hermle, L; Spitzer, M; Ebert, D; Falkenstein, M

2008-01-01

Borderline personality disorder (BPD) has been related to a dysfunction of anterior cingulate cortex, amygdala, and prefrontal cortex and has been associated clinically with impulsivity, affective instability, and significant interpersonal distress. We examined 17 patients with BPD and 17 age-, sex-, and education matched control participants with no history of Axis I or II psychopathology using event-related potentials (ERPs). Participants performed a hybrid flanker-Go/Nogo task while multichannel EEG was recorded. Our study focused on two ERP components: the Nogo-N2 and the Nogo-P3, which have been discussed in the context of response inhibition and response conflict. ERPs were computed on correct Go trials (button press) and correct Nogo trials (no button press), separately. Groups did not differ with regard to the Nogo-N2. However, BPD patients showed reduced Nogo-P3 amplitudes. For the entire group (n = 34) we found a negative correlation with the Barratt Impulsiveness Scale (BIS-10) and Becks's depression inventory (BDI). The present study is the first to examine Nogo-N2 and Nogo-P3 in BPD and provides further evidence for impaired response inhibition in BPD patients.

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

Science.gov (United States)

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

2013-01-01

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

EEG correlates of visual short-term memory in older age vary with adult lifespan cognitive development.

Science.gov (United States)

Wiegand, Iris; Lauritzen, Martin J; Osler, Merete; Mortensen, Erik Lykke; Rostrup, Egill; Rask, Lene; Richard, Nelly; Horwitz, Anna; Benedek, Krisztina; Vangkilde, Signe; Petersen, Anders

2018-02-01

Visual short-term memory (vSTM) is a cognitive resource that declines with age. This study investigated whether electroencephalography (EEG) correlates of vSTM vary with cognitive development over individuals' lifespan. We measured vSTM performance and EEG in a lateralized whole-report task in a healthy birth cohort, whose cognitive function (intelligence quotient) was assessed in youth and late-middle age. Higher vSTM capacity (K; measured by Bundesen's theory of visual attention) was associated with higher amplitudes of the contralateral delay activity (CDA) and the central positivity (CP). In addition, rightward hemifield asymmetry of vSTM (K λ ) was associated with lower CDA amplitudes. Furthermore, more severe cognitive decline from young adulthood to late-middle age predicted higher CDA amplitudes, and the relationship between K and the CDA was less reliable in individuals who show higher levels of cognitive decline compared to individuals with preserved abilities. By contrast, there was no significant effect of lifespan cognitive changes on the CP or the relationship between behavioral measures of vSTM and the CP. Neither the CDA, nor the CP, nor the relationships between K or K λ and the event-related potentials were predicted by individuals' current cognitive status. Together, our findings indicate complex age-related changes in processes underlying behavioral and EEG measures of vSTM and suggest that the K-CDA relationship might be a marker of cognitive lifespan trajectories. Copyright © 2017 Elsevier Inc. All rights reserved.

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

EEG-based decoding of error-related brain activity in a real-world driving task

Science.gov (United States)

Zhang, H.; Chavarriaga, R.; Khaliliardali, Z.; Gheorghe, L.; Iturrate, I.; Millán, J. d. R.

2015-12-01

Objectives. Recent studies have started to explore the implementation of brain-computer interfaces (BCI) as part of driving assistant systems. The current study presents an EEG-based BCI that decodes error-related brain activity. Such information can be used, e.g., to predict driver’s intended turning direction before reaching road intersections. Approach. We executed experiments in a car simulator (N = 22) and a real car (N = 8). While subject was driving, a directional cue was shown before reaching an intersection, and we classified the presence or not of an error-related potentials from EEG to infer whether the cued direction coincided with the subject’s intention. In this protocol, the directional cue can correspond to an estimation of the driving direction provided by a driving assistance system. We analyzed ERPs elicited during normal driving and evaluated the classification performance in both offline and online tests. Results. An average classification accuracy of 0.698 ± 0.065 was obtained in offline experiments in the car simulator, while tests in the real car yielded a performance of 0.682 ± 0.059. The results were significantly higher than chance level for all cases. Online experiments led to equivalent performances in both simulated and real car driving experiments. These results support the feasibility of decoding these signals to help estimating whether the driver’s intention coincides with the advice provided by the driving assistant in a real car. Significance. The study demonstrates a BCI system in real-world driving, extending the work from previous simulated studies. As far as we know, this is the first online study in real car decoding driver’s error-related brain activity. Given the encouraging results, the paradigm could be further improved by using more sophisticated machine learning approaches and possibly be combined with applications in intelligent vehicles.

Effect of instructive visual stimuli on neurofeedback training for motor imagery-based brain-computer interface.

Science.gov (United States)

Kondo, Toshiyuki; Saeki, Midori; Hayashi, Yoshikatsu; Nakayashiki, Kosei; Takata, Yohei

2015-10-01

Event-related desynchronization (ERD) of the electroencephalogram (EEG) from the motor cortex is associated with execution, observation, and mental imagery of motor tasks. Generation of ERD by motor imagery (MI) has been widely used for brain-computer interfaces (BCIs) linked to neuroprosthetics and other motor assistance devices. Control of MI-based BCIs can be acquired by neurofeedback training to reliably induce MI-associated ERD. To develop more effective training conditions, we investigated the effect of static and dynamic visual representations of target movements (a picture of forearms or a video clip of hand grasping movements) during the BCI neurofeedback training. After 4 consecutive training days, the group that performed MI while viewing the video showed significant improvement in generating MI-associated ERD compared with the group that viewed the static image. This result suggests that passively observing the target movement during MI would improve the associated mental imagery and enhance MI-based BCIs skills. Copyright © 2014 Elsevier B.V. All rights reserved.

Classification of Two Class Motor Imagery Tasks Using Hybrid GA-PSO Based K-Means Clustering.

Science.gov (United States)

Suraj; Tiwari, Purnendu; Ghosh, Subhojit; Sinha, Rakesh Kumar

2015-01-01

Transferring the brain computer interface (BCI) from laboratory condition to meet the real world application needs BCI to be applied asynchronously without any time constraint. High level of dynamism in the electroencephalogram (EEG) signal reasons us to look toward evolutionary algorithm (EA). Motivated by these two facts, in this work a hybrid GA-PSO based K-means clustering technique has been used to distinguish two class motor imagery (MI) tasks. The proposed hybrid GA-PSO based K-means clustering is found to outperform genetic algorithm (GA) and particle swarm optimization (PSO) based K-means clustering techniques in terms of both accuracy and execution time. The lesser execution time of hybrid GA-PSO technique makes it suitable for real time BCI application. Time frequency representation (TFR) techniques have been used to extract the feature of the signal under investigation. TFRs based features are extracted and relying on the concept of event related synchronization (ERD) and desynchronization (ERD) feature vector is formed.

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.

EEG Based Inference of Spatio-Temporal Brain Dynamics

DEFF Research Database (Denmark)

Hansen, Sofie Therese

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

Hippocampal EEG and motor activity in the cat: The role of eye movements and body acceleration

NARCIS (Netherlands)

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

1984-01-01

In cat the relation between various behaviours and the spectral properties of the hippocampal EEG was investigated. Both EEG and behaviour were quantified and results were evaluated statistically. Significant relationships were found between the properties of the hippocampal EEG and motor acts

Event-related potential correlates of mindfulness meditation competence.

Science.gov (United States)

Atchley, R; Klee, D; Memmott, T; Goodrich, E; Wahbeh, H; Oken, B

2016-04-21

This cross-sectional study evaluated event-related potentials (ERPs) across three groups: naïve, novice, and experienced meditators as potential physiological markers of mindfulness meditation competence. Electroencephalographic (EEG) data were collected during a target tone detection task and a Breath Counting task. The Breath Counting task served as the mindfulness meditation condition for the novice and experienced meditator groups. Participants were instructed to respond to target tones with a button press in the first task (Tones), and then ignore the primed tones while Breath Counting. The primary outcomes were ERP responses to target tones, namely the N2 and P3, as markers of stimulus discrimination and attention, respectively. As expected, P3 amplitudes elicited by target tones were attenuated within groups during the Breath Counting task in comparison to the Tones task (pmeditator groups displayed greater change in peak-to-trough P3 amplitudes, with higher amplitudes during the Tones condition and more pronounced reductions in P3 amplitudes during the Breath Counting meditation task in comparison to the naïve group. Meditators had stronger P3 amplitude responses to target tones when instructed to attend to the tones, and a greater attenuation of P3 amplitudes when instructed to ignore the same tones during the Breath Counting task. This study introduces the idea of identifying ERP markers as a means of measuring mindfulness meditation competence, and results suggest this may be a valid approach. This information has the potential to improve mindfulness meditation interventions by allowing objective assessment of mindfulness meditation quality. Published by Elsevier Ltd.

An embedded implementation based on adaptive filter bank for brain-computer interface systems.

Science.gov (United States)

Belwafi, Kais; Romain, Olivier; Gannouni, Sofien; Ghaffari, Fakhreddine; Djemal, Ridha; Ouni, Bouraoui

2018-07-15

Brain-computer interface (BCI) is a new communication pathway for users with neurological deficiencies. The implementation of a BCI system requires complex electroencephalography (EEG) signal processing including filtering, feature extraction and classification algorithms. Most of current BCI systems are implemented on personal computers. Therefore, there is a great interest in implementing BCI on embedded platforms to meet system specifications in terms of time response, cost effectiveness, power consumption, and accuracy. This article presents an embedded-BCI (EBCI) system based on a Stratix-IV field programmable gate array. The proposed system relays on the weighted overlap-add (WOLA) algorithm to perform dynamic filtering of EEG-signals by analyzing the event-related desynchronization/synchronization (ERD/ERS). The EEG-signals are classified, using the linear discriminant analysis algorithm, based on their spatial features. The proposed system performs fast classification within a time delay of 0.430 s/trial, achieving an average accuracy of 76.80% according to an offline approach and 80.25% using our own recording. The estimated power consumption of the prototype is approximately 0.7 W. Results show that the proposed EBCI system reduces the overall classification error rate for the three datasets of the BCI-competition by 5% compared to other similar implementations. Moreover, experiment shows that the proposed system maintains a high accuracy rate with a short processing time, a low power consumption, and a low cost. Performing dynamic filtering of EEG-signals using WOLA increases the recognition rate of ERD/ERS patterns of motor imagery brain activity. This approach allows to develop a complete prototype of a EBCI system that achieves excellent accuracy rates. Copyright © 2018 Elsevier B.V. All rights reserved.

Electroencephalogram-Based Brain–Computer Interface and Lower-Limb Prosthesis Control: A Case Study

Directory of Open Access Journals (Sweden)

Douglas P. Murphy

2017-12-01

Full Text Available ObjectiveThe purpose of this study was to establish the feasibility of manipulating a prosthetic knee directly by using a brain–computer interface (BCI system in a transfemoral amputee. Although the other forms of control could be more reliable and quick (e.g., electromyography control, the electroencephalography (EEG-based BCI may provide amputees an alternative way to control a prosthesis directly from brain.MethodsA transfemoral amputee subject was trained to activate a knee-unlocking switch through motor imagery of the movement of his lower extremity. Surface scalp electrodes transmitted brain wave data to a software program that was keyed to activate the switch when the event-related desynchronization in EEG reached a certain threshold. After achieving more than 90% reliability for switch activation by EEG rhythm-feedback training, the subject then progressed to activating the knee-unlocking switch on a prosthesis that turned on a motor and unlocked a prosthetic knee. The project took place in the prosthetic department of a Veterans Administration medical center. The subject walked back and forth in the parallel bars and unlocked the knee for swing phase and for sitting down. The success of knee unlocking through this system was measured. Additionally, the subject filled out a questionnaire on his experiences.ResultsThe success of unlocking the prosthetic knee mechanism ranged from 50 to 100% in eight test segments.ConclusionThe performance of the subject supports the feasibility for BCI control of a lower extremity prosthesis using surface scalp EEG electrodes. Investigating direct brain control in different types of patients is important to promote real-world BCI applications.

Processing of emotional faces in congenital amusia: An emotional music priming event-related potential study.

Science.gov (United States)

Zhishuai, Jin; Hong, Liu; Daxing, Wu; Pin, Zhang; Xuejing, Lu

2017-01-01

Congenital amusia is characterized by lifelong impairments in music perception and processing. It is unclear whether pitch detection deficits impact amusic individuals' perception of musical emotion. In the current work, 19 amusics and 21 healthy controls were subjected to electroencephalography (EEG) while being exposed to music excerpts and emotional faces. We assessed each individual's ability to discriminate positive- and negative-valenced emotional faces and analyzed electrophysiological indices, in the form of event-related potentials (ERPs) recorded at 32 sites, following exposure to emotionally positive or negative music excerpts. We observed smaller N2 amplitudes in response to facial expressions in the amusia group than in the control group, suggesting that amusics were less affected by the musical stimuli. The late-positive component (LPC) in amusics was similar to that in controls. Our results suggest that the neurocognitive deficit characteristic of congenital amusia is fundamentally an impairment in musical information processing rather than an impairment in emotional processing.

Processing of emotional faces in congenital amusia: An emotional music priming event-related potential study

Directory of Open Access Journals (Sweden)

Jin Zhishuai

2017-01-01

Full Text Available Congenital amusia is characterized by lifelong impairments in music perception and processing. It is unclear whether pitch detection deficits impact amusic individuals' perception of musical emotion. In the current work, 19 amusics and 21 healthy controls were subjected to electroencephalography (EEG while being exposed to music excerpts and emotional faces. We assessed each individual's ability to discriminate positive- and negative-valenced emotional faces and analyzed electrophysiological indices, in the form of event-related potentials (ERPs recorded at 32 sites, following exposure to emotionally positive or negative music excerpts. We observed smaller N2 amplitudes in response to facial expressions in the amusia group than in the control group, suggesting that amusics were less affected by the musical stimuli. The late-positive component (LPC in amusics was similar to that in controls. Our results suggest that the neurocognitive deficit characteristic of congenital amusia is fundamentally an impairment in musical information processing rather than an impairment in emotional processing.

Diagnosis and interpretation of EEG on non-convulsive status epilepticus

Directory of Open Access Journals (Sweden)

Xiao-gang KANG

2015-11-01

Full Text Available It is difficult to diagnose non-convulsive status epilepticus (NCSE clinically because of the complicated etiology and various clinical and electroencephalographic features of NCSE without a universally accepted definition. Although the diagnosis of NCSE relies largely on electroencephalogram (EEG findings, the determination of NCSE on EEG is inevitably subjective, and the EEG changes of most patients is lack of specificity. As the diagnosis of NCSE is related to clinical and electroencephalographic manifestations, diagnostic criteria for NCSE should take into account both clinical and electroencephalographic features, and their response to antiepileptic drugs (AEDs. DOI: 10.3969/j.issn.1672-6731.2015.11.005

Preparing laboratory and real-world EEG data for large-scale analysis: A containerized approach