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Sample records for high-density eeg brain

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

    DEFF Research Database (Denmark)

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

    2008-01-01

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

  2. High-density EEG characterization of brain responses to auditory rhythmic stimuli during wakefulness and NREM sleep.

    Science.gov (United States)

    Lustenberger, Caroline; Patel, Yogi A; Alagapan, Sankaraleengam; Page, Jessica M; Price, Betsy; Boyle, Michael R; Fröhlich, Flavio

    2018-04-01

    Auditory rhythmic sensory stimulation modulates brain oscillations by increasing phase-locking to the temporal structure of the stimuli and by increasing the power of specific frequency bands, resulting in Auditory Steady State Responses (ASSR). The ASSR is altered in different diseases of the central nervous system such as schizophrenia. However, in order to use the ASSR as biological markers for disease states, it needs to be understood how different vigilance states and underlying brain activity affect the ASSR. Here, we compared the effects of auditory rhythmic stimuli on EEG brain activity during wake and NREM sleep, investigated the influence of the presence of dominant sleep rhythms on the ASSR, and delineated the topographical distribution of these modulations. Participants (14 healthy males, 20-33 years) completed on the same day a 60 min nap session and two 30 min wakefulness sessions (before and after the nap). During these sessions, amplitude modulated (AM) white noise auditory stimuli at different frequencies were applied. High-density EEG was continuously recorded and time-frequency analyses were performed to assess ASSR during wakefulness and NREM periods. Our analysis revealed that depending on the electrode location, stimulation frequency applied and window/frequencies analysed the ASSR was significantly modulated by sleep pressure (before and after sleep), vigilance state (wake vs. NREM sleep), and the presence of slow wave activity and sleep spindles. Furthermore, AM stimuli increased spindle activity during NREM sleep but not during wakefulness. Thus, (1) electrode location, sleep history, vigilance state and ongoing brain activity needs to be carefully considered when investigating ASSR and (2) auditory rhythmic stimuli during sleep might represent a powerful tool to boost sleep spindles. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Bedside functional brain imaging in critically-ill children using high-density EEG source modeling and multi-modal sensory stimulation

    Directory of Open Access Journals (Sweden)

    Danny Eytan

    2016-01-01

    Full Text Available Acute brain injury is a common cause of death and critical illness in children and young adults. Fundamental management focuses on early characterization of the extent of injury and optimizing recovery by preventing secondary damage during the days following the primary injury. Currently, bedside technology for measuring neurological function is mainly limited to using electroencephalography (EEG for detection of seizures and encephalopathic features, and evoked potentials. We present a proof of concept study in patients with acute brain injury in the intensive care setting, featuring a bedside functional imaging set-up designed to map cortical brain activation patterns by combining high density EEG recordings, multi-modal sensory stimulation (auditory, visual, and somatosensory, and EEG source modeling. Use of source-modeling allows for examination of spatiotemporal activation patterns at the cortical region level as opposed to the traditional scalp potential maps. The application of this system in both healthy and brain-injured participants is demonstrated with modality-specific source-reconstructed cortical activation patterns. By combining stimulation obtained with different modalities, most of the cortical surface can be monitored for changes in functional activation without having to physically transport the subject to an imaging suite. The results in patients in an intensive care setting with anatomically well-defined brain lesions suggest a topographic association between their injuries and activation patterns. Moreover, we report the reproducible application of a protocol examining a higher-level cortical processing with an auditory oddball paradigm involving presentation of the patient's own name. This study reports the first successful application of a bedside functional brain mapping tool in the intensive care setting. This application has the potential to provide clinicians with an additional dimension of information to manage

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

    Science.gov (United States)

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

    2014-05-30

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

  5. High-density EEG coherence analysis using functional units applied to mental fatigue

    NARCIS (Netherlands)

    Caat, Michael ten; Lorist, Monicque M.; Bezdan, Eniko; Roerdink, Jos B.T.M.; Maurits, Natasha M.

    2008-01-01

    Electroencephalography (EEG) coherence provides a quantitative measure of functional brain connectivity which is calculated between pairs of signals as a function of frequency. Without hypotheses, traditional coherence analysis would be cumbersome for high-density EEG which employs a large number of

  6. The infant mirror neuron system studied with high density EEG.

    Science.gov (United States)

    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.

  7. Propofol Anesthesia and Sleep: A High-Density EEG Study

    Science.gov (United States)

    Murphy, Michael; Bruno, Marie-Aurelie; Riedner, Brady A.; Boveroux, Pierre; Noirhomme, Quentin; Landsness, Eric C.; Brichant, Jean-Francois; Phillips, Christophe; Massimini, Marcello; Laureys, Steven; Tononi, Giulio; Boly, Melanie

    2011-01-01

    Study Objectives: The electrophysiological correlates of anesthetic sedation remain poorly understood. We used high-density electroencephalography (hd-EEG) and source modeling to investigate the cortical processes underlying propofol anesthesia and compare them to sleep. Design: 256-channel EEG recordings in humans during propofol anesthesia. Setting: Hospital operating room. Patients or Participants: 8 healthy subjects (4 males) Interventions: N/A Measurements and Results: Initially, propofol induced increases in EEG power from 12–25 Hz. Loss of consciousness (LOC) was accompanied by the appearance of EEG slow waves that resembled the slow waves of NREM sleep. We compared slow waves in propofol to slow waves recorded during natural sleep and found that both populations of waves share similar cortical origins and preferentially propagate along the mesial components of the default network. However, propofol slow waves were spatially blurred compared to sleep slow waves and failed to effectively entrain spindle activity. Propofol also caused an increase in gamma (25–40 Hz) power that persisted throughout LOC. Source modeling analysis showed that this increase in gamma power originated from the anterior and posterior cingulate cortices. During LOC, we found increased gamma functional connectivity between these regions compared to the wakefulness. Conclusions: Propofol anesthesia is a sleep-like state and slow waves are associated with diminished consciousness even in the presence of high gamma activity. Citation: Murphy M; Bruno MA; Riedner BA; Boveroux P; Noirhomme Q; Landsness EC; Brichant JF; Phillips C; Massimini M; Laureys S; Tononi G; Boly M. Propofol anesthesia and sleep: a high-density EEG study. SLEEP 2011;34(3):283-291. PMID:21358845

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

    Science.gov (United States)

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

    2014-02-01

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

  9. Automated detection and labeling of high-density EEG electrodes from structural MR images

    Science.gov (United States)

    Marino, Marco; Liu, Quanying; Brem, Silvia; Wenderoth, Nicole; Mantini, Dante

    2016-10-01

    will contribute to a more widespread use of high-density EEG as a brain-imaging tool.

  10. Brain Oscillations in Sport: Toward EEG Biomarkers of Performance

    OpenAIRE

    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 a...

  11. Brain oscillations in sport: toward EEG biomakers of performance

    OpenAIRE

    Guy eCheron; Guy eCheron; Geraldine ePetit; Julian eCheron; Axelle eLeroy; Axelle eLeroy; Ana Maria Cebolla; Carlos eCevallos; Mathieu ePetieau; David eZarka; Thomas eHoellinger; Anne-Marie eClarinval; Bernard eDan; Bernard eDan

    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 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 ap...

  12. A high-density EEG investigation into steady state binaural beat stimulation.

    Directory of Open Access Journals (Sweden)

    Peter Goodin

    Full Text Available Binaural beats are an auditory phenomenon that has been suggested to alter physiological and cognitive processes including vigilance and brainwave entrainment. Some personality traits measured by the NEO Five Factor Model have been found to alter entrainment using pulsing light stimuli, but as yet no studies have examined if this occurs using steady state presentation of binaural beats for a relatively short presentation of two minutes. This study aimed to examine if binaural beat stimulation altered vigilance or cortical frequencies and if personality traits were involved. Thirty-one participants were played binaural beat stimuli designed to elicit a response at either the Theta (7 Hz or Beta (16 Hz frequency bands while undertaking a zero-back vigilance task. EEG was recorded from a high-density electrode cap. No significant differences were found in vigilance or cortical frequency power during binaural beat stimulation compared to a white noise control period. Furthermore, no significant relationships were detected between the above and the Big Five personality traits. This suggests a short presentation of steady state binaural beats are not sufficient to alter vigilance or entrain cortical frequencies at the two bands examined and that certain personality traits were not more susceptible than others.

  13. A high-density EEG investigation into steady state binaural beat stimulation.

    Science.gov (United States)

    Goodin, Peter; Ciorciari, Joseph; Baker, Kate; Carey, Anne-Marie; Carrey, Anne-Marie; Harper, Michelle; Kaufman, Jordy

    2012-01-01

    Binaural beats are an auditory phenomenon that has been suggested to alter physiological and cognitive processes including vigilance and brainwave entrainment. Some personality traits measured by the NEO Five Factor Model have been found to alter entrainment using pulsing light stimuli, but as yet no studies have examined if this occurs using steady state presentation of binaural beats for a relatively short presentation of two minutes. This study aimed to examine if binaural beat stimulation altered vigilance or cortical frequencies and if personality traits were involved. Thirty-one participants were played binaural beat stimuli designed to elicit a response at either the Theta (7 Hz) or Beta (16 Hz) frequency bands while undertaking a zero-back vigilance task. EEG was recorded from a high-density electrode cap. No significant differences were found in vigilance or cortical frequency power during binaural beat stimulation compared to a white noise control period. Furthermore, no significant relationships were detected between the above and the Big Five personality traits. This suggests a short presentation of steady state binaural beats are not sufficient to alter vigilance or entrain cortical frequencies at the two bands examined and that certain personality traits were not more susceptible than others.

  14. Brain oscillations in sport: toward EEG biomakers of performance

    Directory of Open Access Journals (Sweden)

    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.

  15. 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

  16. 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.

  17. Early Left Parietal Activity Elicited by Direct Gaze: A High-Density EEG Study

    Science.gov (United States)

    Burra, Nicolas; Kerzel, Dirk; George, Nathalie

    2016-01-01

    Gaze is one of the most important cues for human communication and social interaction. In particular, gaze contact is the most primary form of social contact and it is thought to capture attention. A very early-differentiated brain response to direct versus averted gaze has been hypothesized. Here, we used high-density electroencephalography to test this hypothesis. Topographical analysis allowed us to uncover a very early topographic modulation (40–80 ms) of event-related responses to faces with direct as compared to averted gaze. This modulation was obtained only in the condition where intact broadband faces–as opposed to high-pass or low-pas filtered faces–were presented. Source estimation indicated that this early modulation involved the posterior parietal region, encompassing the left precuneus and inferior parietal lobule. This supports the idea that it reflected an early orienting response to direct versus averted gaze. Accordingly, in a follow-up behavioural experiment, we found faster response times to the direct gaze than to the averted gaze broadband faces. In addition, classical evoked potential analysis showed that the N170 peak amplitude was larger for averted gaze than for direct gaze. Taken together, these results suggest that direct gaze may be detected at a very early processing stage, involving a parallel route to the ventral occipito-temporal route of face perceptual analysis. PMID:27880776

  18. Understanding Actions of Others: The Electrodynamics of the Left and Right Hemispheres. A High-Density EEG Neuroimaging Study

    Science.gov (United States)

    Ortigue, Stephanie; Sinigaglia, Corrado; Rizzolatti, Giacomo; Grafton, Scott T.

    2010-01-01

    Background When we observe an individual performing a motor act (e.g. grasping a cup) we get two types of information on the basis of how the motor act is done and the context: what the agent is doing (i.e. grasping) and the intention underlying it (i.e. grasping for drinking). Here we examined the temporal dynamics of the brain activations that follow the observation of a motor act and underlie the observer's capacity to understand what the agent is doing and why. Methodology/Principal Findings Volunteers were presented with two-frame video-clips. The first frame (T0) showed an object with or without context; the second frame (T1) showed a hand interacting with the object. The volunteers were instructed to understand the intention of the observed actions while their brain activity was recorded with a high-density 128-channel EEG system. Visual event-related potentials (VEPs) were recorded time-locked with the frame showing the hand-object interaction (T1). The data were analyzed by using electrical neuroimaging, which combines a cluster analysis performed on the group-averaged VEPs with the localization of the cortical sources that give rise to different spatio-temporal states of the global electrical field. Electrical neuroimaging results revealed four major steps: 1) bilateral posterior cortical activations; 2) a strong activation of the left posterior temporal and inferior parietal cortices with almost a complete disappearance of activations in the right hemisphere; 3) a significant increase of the activations of the right temporo-parietal region with simultaneously co-active left hemispheric sources, and 4) a significant global decrease of cortical activity accompanied by the appearance of activation of the orbito-frontal cortex. Conclusions/Significance We conclude that the early striking left hemisphere involvement is due to the activation of a lateralized action-observation/action execution network. The activation of this lateralized network mediates the

  19. Understanding actions of others: the electrodynamics of the left and right hemispheres. A high-density EEG neuroimaging study.

    Directory of Open Access Journals (Sweden)

    Stephanie Ortigue

    Full Text Available BACKGROUND: When we observe an individual performing a motor act (e.g. grasping a cup we get two types of information on the basis of how the motor act is done and the context: what the agent is doing (i.e. grasping and the intention underlying it (i.e. grasping for drinking. Here we examined the temporal dynamics of the brain activations that follow the observation of a motor act and underlie the observer's capacity to understand what the agent is doing and why. METHODOLOGY/PRINCIPAL FINDINGS: Volunteers were presented with two-frame video-clips. The first frame (T0 showed an object with or without context; the second frame (T1 showed a hand interacting with the object. The volunteers were instructed to understand the intention of the observed actions while their brain activity was recorded with a high-density 128-channel EEG system. Visual event-related potentials (VEPs were recorded time-locked with the frame showing the hand-object interaction (T1. The data were analyzed by using electrical neuroimaging, which combines a cluster analysis performed on the group-averaged VEPs with the localization of the cortical sources that give rise to different spatio-temporal states of the global electrical field. Electrical neuroimaging results revealed four major steps: 1 bilateral posterior cortical activations; 2 a strong activation of the left posterior temporal and inferior parietal cortices with almost a complete disappearance of activations in the right hemisphere; 3 a significant increase of the activations of the right temporo-parietal region with simultaneously co-active left hemispheric sources, and 4 a significant global decrease of cortical activity accompanied by the appearance of activation of the orbito-frontal cortex. CONCLUSIONS/SIGNIFICANCE: We conclude that the early striking left hemisphere involvement is due to the activation of a lateralized action-observation/action execution network. The activation of this lateralized network

  20. Effects of partial sleep deprivation on slow waves during non-rapid eye movement sleep: A high density EEG investigation.

    Science.gov (United States)

    Plante, David T; Goldstein, Michael R; Cook, Jesse D; Smith, Richard; Riedner, Brady A; Rumble, Meredith E; Jelenchick, Lauren; Roth, Andrea; Tononi, Giulio; Benca, Ruth M; Peterson, Michael J

    2016-02-01

    Changes in slow waves during non-rapid eye movement (NREM) sleep in response to acute total sleep deprivation are well-established measures of sleep homeostasis. This investigation utilized high-density electroencephalography (hdEEG) to examine topographic changes in slow waves during repeated partial sleep deprivation. Twenty-four participants underwent a 6-day sleep restriction protocol. Spectral and period-amplitude analyses of sleep hdEEG data were used to examine changes in slow wave energy, count, amplitude, and slope relative to baseline. Changes in slow wave energy were dependent on the quantity of NREM sleep utilized for analysis, with widespread increases during sleep restriction and recovery when comparing data from the first portion of the sleep period, but restricted to recovery sleep if the entire sleep episode was considered. Period-amplitude analysis was less dependent on the quantity of NREM sleep utilized, and demonstrated topographic changes in the count, amplitude, and distribution of slow waves, with frontal increases in slow wave amplitude, numbers of high-amplitude waves, and amplitude/slopes of low amplitude waves resulting from partial sleep deprivation. Topographic changes in slow waves occur across the course of partial sleep restriction and recovery. These results demonstrate a homeostatic response to partial sleep loss in humans. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  1. Topographic and sex-related differences in sleep spindles in major depressive disorder: a high-density EEG investigation.

    Science.gov (United States)

    Plante, D T; Goldstein, M R; Landsness, E C; Peterson, M J; Riedner, B A; Ferrarelli, F; Wanger, T; Guokas, J J; Tononi, G; Benca, R M

    2013-03-20

    Sleep spindles are believed to mediate several sleep-related functions including maintaining disconnection from the external environment during sleep, cortical development, and sleep-dependent memory consolidation. Prior studies that have examined sleep spindles in major depressive disorder (MDD) have not demonstrated consistent differences relative to control subjects, which may be due to sex-related variation and limited spatial resolution of spindle detection. Thus, this study sought to characterize sleep spindles in MDD using high-density electroencephalography (hdEEG) to examine the topography of sleep spindles across the cortex in MDD, as well as sex-related variation in spindle topography in the disorder. All-night hdEEG recordings were collected in 30 unipolar MDD participants (19 women) and 30 age and sex-matched controls. Topography of sleep spindle density, amplitude, duration, and integrated spindle activity (ISA) were assessed to determine group differences. Spindle parameters were compared between MDD and controls, including analysis stratified by sex. As a group, MDD subjects demonstrated significant increases in frontal and parietal spindle density and ISA compared to controls. When stratified by sex, MDD women demonstrated increases in frontal and parietal spindle density, amplitude, duration, and ISA; whereas MDD men demonstrated either no differences or decreases in spindle parameters. Given the number of male subjects, this study may be underpowered to detect differences in spindle parameters in male MDD participants. This study demonstrates topographic and sex-related differences in sleep spindles in MDD. Further research is warranted to investigate the role of sleep spindles and sex in the pathophysiology of MDD. Copyright © 2012 Elsevier B.V. All rights reserved.

  2. Sex-related differences in sleep slow wave activity in major depressive disorder: a high-density EEG investigation.

    Science.gov (United States)

    Plante, David T; Landsness, Eric C; Peterson, Michael J; Goldstein, Michael R; Riedner, Brady A; Wanger, Timothy; Guokas, Jeffrey J; Tononi, Giulio; Benca, Ruth M

    2012-09-18

    Sleep disturbance plays an important role in major depressive disorder (MDD). Prior investigations have demonstrated that slow wave activity (SWA) during sleep is altered in MDD; however, results have not been consistent across studies, which may be due in part to sex-related differences in SWA and/or limited spatial resolution of spectral analyses. This study sought to characterize SWA in MDD utilizing high-density electroencephalography (hdEEG) to examine the topography of SWA across the cortex in MDD, as well as sex-related variation in SWA topography in the disorder. All-night recordings with 256 channel hdEEG were collected in 30 unipolar MDD subjects (19 women) and 30 age and sex-matched control subjects. Spectral analyses of SWA were performed to determine group differences. SWA was compared between MDD and controls, including analyses stratified by sex, using statistical non-parametric mapping to correct for multiple comparisons of topographic data. As a group, MDD subjects demonstrated significant increases in all-night SWA primarily in bilateral prefrontal channels. When stratified by sex, MDD women demonstrated global increases in SWA relative to age-matched controls that were most consistent in bilateral prefrontal regions; however, MDD men showed no significant differences relative to age-matched controls. Further analyses demonstrated increased SWA in MDD women was most prominent in the first portion of the night. Women, but not men with MDD demonstrate significant increases in SWA in multiple cortical areas relative to control subjects. Further research is warranted to investigate the role of SWA in MDD, and to clarify how increased SWA in women with MDD is related to the pathophysiology of the disorder.

  3. 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...

  4. EEG

    Science.gov (United States)

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

  5. Adaptation in human somatosensory cortex as a model of sensory memory construction: a study using high-density EEG.

    Science.gov (United States)

    Bradley, Claire; Joyce, Niamh; Garcia-Larrea, Luis

    2016-01-01

    Adaptation in sensory cortices has been seen as a mechanism allowing the creation of transient memory representations. Here we tested the adapting properties of early responses in human somatosensory areas SI and SII by analysing somatosensory-evoked potentials over the very first repetitions of a stimulus. SI and SII generators were identified by well-defined scalp potentials and source localisation from high-density 128-channel EEG. Earliest responses (~20 ms) from area 3b in the depth of the post-central gyrus did not show significant adaptation to stimuli repeated at 300 ms intervals. In contrast, responses around 45 ms from the crown of the gyrus (areas 1 and 2) rapidly lessened to a plateau and abated at the 20th stimulation, and activities from SII in the parietal operculum at ~100 ms displayed strong adaptation with a steady amplitude decrease from the first repetition. Although responses in both SI (1-2) and SII areas showed adapting properties and hence sensory memory capacities, evidence of sensory mismatch detection has been demonstrated only for responses reflecting SII activation. This may index the passage from an early form of sensory storage in SI to more operational memory codes in SII, allowing the prediction of forthcoming input and the triggering of a specific signal when such input differs from the previous sequence. This is consistent with a model whereby the length of temporal receptive windows increases with progression in the cortical hierarchy, in parallel with the complexity and abstraction of neural representations.

  6. A NOS1 variant implicated in cognitive performance influences evoked neural responses during a high density EEG study of early visual perception.

    Science.gov (United States)

    O'Donoghue, Therese; Morris, Derek W; Fahey, Ciara; Da Costa, Andreia; Foxe, John J; Hoerold, Doreen; Tropea, Daniela; Gill, Michael; Corvin, Aiden; Donohoe, Gary

    2012-05-01

    The nitric oxide synthasase-1 gene (NOS1) has been implicated in mental disorders including schizophrenia and variation in cognition. The NOS1 variant rs6490121 identified in a genome wide association study of schizophrenia has recently been associated with variation in general intelligence and working memory in both patients and healthy participants. Whether this variant is also associated with variation in early sensory processing remains unclear. We investigated differences in the P1 visual evoked potential in a high density EEG study of 54 healthy participants. Given both NOS1's association with cognition and recent evidence that cognitive performance and P1 response are correlated, we investigated whether NOS1's effect on P1 response was independent of its effects on cognition using CANTAB's spatial working memory (SWM) task. We found that carriers of the previously identified risk "G" allele showed significantly lower P1 responses than non-carriers. We also found that while P1 response and SWM performance were correlated, NOS1 continued to explain a significant proportion of variation in P1 response even when its effects on cognition were accounted for. The schizophrenia implicated NOS1 variants rs6490121 influences visual sensory processing as measured by the P1 response, either as part of the gene's pleiotropic effects on multiple aspects of brain function, or because of a primary influence on sensory processing that mediates the effects already seen in higher cognitive processes. Copyright © 2011 Wiley-Liss, Inc.

  7. "Cuts in Action": A High-Density EEG Study Investigating the Neural Correlates of Different Editing Techniques in Film.

    Science.gov (United States)

    Heimann, Katrin S; Uithol, Sebo; Calbi, Marta; Umiltà, Maria A; Guerra, Michele; Gallese, Vittorio

    2017-08-01

    In spite of their striking differences with real-life perception, films are perceived and understood without effort. Cognitive film theory attributes this to the system of continuity editing, a system of editing guidelines outlining the effect of different cuts and edits on spectators. A major principle in this framework is the 180° rule, a rule recommendation that, to avoid spectators' attention to the editing, two edited shots of the same event or action should not be filmed from angles differing in a way that expectations of spatial continuity are strongly violated. In the present study, we used high-density EEG to explore the neural underpinnings of this rule. In particular, our analysis shows that cuts and edits in general elicit early ERP component indicating the registration of syntactic violations as known from language, music, and action processing. However, continuity edits and cuts-across the line differ from each other regarding later components likely to be indicating the differences in spatial remapping as well as in the degree of conscious awareness of one's own perception. Interestingly, a time-frequency analysis of the occipital alpha rhythm did not support the hypothesis that such differences in processing routes are mainly linked to visual attention. On the contrary, our study found specific modulations of the central mu rhythm ERD as an indicator of sensorimotor activity, suggesting that sensorimotor networks might play an important role. We think that these findings shed new light on current discussions about the role of attention and embodied perception in film perception and should be considered when explaining spectators' different experience of different kinds of cuts. Copyright © 2016 Cognitive Science Society, Inc.

  8. Brain dynamics of upstream perceptual processes leading to visual object recognition: a high density ERP topographic mapping study.

    Science.gov (United States)

    Schettino, Antonio; Loeys, Tom; Delplanque, Sylvain; Pourtois, Gilles

    2011-04-01

    Recent studies suggest that visual object recognition is a proactive process through which perceptual evidence accumulates over time before a decision can be made about the object. However, the exact electrophysiological correlates and time-course of this complex process remain unclear. In addition, the potential influence of emotion on this process has not been investigated yet. We recorded high density EEG in healthy adult participants performing a novel perceptual recognition task. For each trial, an initial blurred visual scene was first shown, before the actual content of the stimulus was gradually revealed by progressively adding diagnostic high spatial frequency information. Participants were asked to stop this stimulus sequence as soon as they could correctly perform an animacy judgment task. Behavioral results showed that participants reliably gathered perceptual evidence before recognition. Furthermore, prolonged exploration times were observed for pleasant, relative to either neutral or unpleasant scenes. ERP results showed distinct effects starting at 280 ms post-stimulus onset in distant brain regions during stimulus processing, mainly characterized by: (i) a monotonic accumulation of evidence, involving regions of the posterior cingulate cortex/parahippocampal gyrus, and (ii) true categorical recognition effects in medial frontal regions, including the dorsal anterior cingulate cortex. These findings provide evidence for the early involvement, following stimulus onset, of non-overlapping brain networks during proactive processes eventually leading to visual object recognition. Copyright © 2011 Elsevier Inc. All rights reserved.

  9. Wearable ear EEG for brain interfacing

    Science.gov (United States)

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

    2017-02-01

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

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

    DEFF Research Database (Denmark)

    Hansen, Sofie Therese; Hauberg, Søren; Hansen, Lars Kai

    2016-01-01

    Electroencephalography (EEG) is a flexible and accessible tool with excellent temporal resolution but with a spatial resolution hampered by volume conduction. Reconstruction of the cortical sources of measured EEG activity partly alleviates this problem and effectively turns EEG into a brain......-of-concept study, we show that, even when anatomical knowledge is unavailable, a suitable forward model can be estimated directly from the EEG. We propose a data-driven approach that provides a low-dimensional parametrization of head geometry and compartment conductivities, built using a corpus of forward models....... Combined with only a recorded EEG signal, we are able to estimate both the brain sources and a person-specific forward model by optimizing this parametrization. We thus not only solve an inverse problem, but also optimize over its specification. Our work demonstrates that personalized EEG brain imaging...

  11. 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...

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

    Science.gov (United States)

    2016-12-01

    science of binaural beats . Retrieved from http://binauralbrains.com/the-science-of- binaural - beats / Biosignal. (2016). MicroEEG. Retrieved from http...Cap. Source: Binaural Brains (n.d.). ....................................4  Figure 3.  EEG Machine. Source: Refine Medical Technology (n.d...EEG. Figures 2, 3, and 4 display images of a standard EEG cap, EEG machine, and an EEG recording. Figure 2. Standard EEG Cap. Source: Binaural Brains

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

    Science.gov (United States)

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

    2018-01-01

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

  14. EEG

    African Journals Online (AJOL)

    2017-09-03

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

  15. A High Density Electrophysiological Data Analysis System for a Peripheral Nerve Interface Communicating with Individual Neurons in the Brain

    Science.gov (United States)

    2016-11-14

    of-the-art instrumentation to communicate with individual neurons in the brain and the peripheral nervous system. The major theme of the research is...Nerve Interface Communicating with Individual Neurons in the Brain The views, opinions and/or findings contained in this report are those of the author... Communicating with Individual Neurons in the Brain Report Title The high density electrophysiological data acquisition system obtained through this

  16. Correlations of CT and EEG findings in brain affections

    International Nuclear Information System (INIS)

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

    1984-01-01

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

  17. Brain Functional Connectivity in MS: An EEG-NIRS Study

    Science.gov (United States)

    2015-10-01

    1 AWARD NUMBER: W81XWH-14-1-0582 TITLE: Brain Functional Connectivity in MS: An EEG -NIRS Study PRINCIPAL INVESTIGATOR: Heather Wishart...Functional Connectivity in MS: An EEG -NIRS Study 5b. GRANT NUMBER W81XWH-14-1-0582 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER Heather...electrical ( EEG ) and blood volume and blood oxygen-based (NIRS and fMRI) signals, and to use the results to help optimize blood oxygen level

  18. Impaired information processing speed and attention allocation in multiple sclerosis patients versus controls: a high-density EEG study.

    LENUS (Irish Health Repository)

    Whelan, R

    2012-02-01

    BACKGROUND: The no-go P3a is a variant of the P300 event-related potential (ERP) that indexes speed of information processing and attention allocation. The aim of this study was to compare ERP findings with results from the paced auditory serial addition test (PASAT) and to quantify latency, amplitude and topographical differences in P3a ERP components between multiple sclerosis (MS) patients and controls. PATIENTS AND METHODS: Seventy-four subjects (20 relapsing remitting (RRMS) patients, 20 secondary progressive (SPMS) patients and 34 controls) completed a three-stimulus oddball paradigm (target, standard, and non-target). Subjects participated in separate visual and auditory tasks while data were recorded from 134 EEG channels. Latency differences were tested using an ANCOVA. Topographical differences were tested using statistical parametric mapping. RESULTS: Visual P3a amplitude correlated with PASAT score in all MS patients over frontal and parietal areas. There were significant differences in latency, amplitude, and topography between MS patients and controls in the visual condition. RRMS and SPMS patients differed in visual P3a latency and amplitude at frontal and parietal scalp regions. In the auditory condition, there were latency differences between MS patients and controls only over the parietal region. CONCLUSION: The present results demonstrate that information processing speed and attention allocation are impaired in MS.

  19. Developmental changes in brain connectivity assessed using the sleep EEG.

    OpenAIRE

    Tarokh L; Carskadon M A; Achermann P

    2010-01-01

    Adolescence represents a time of significant cortical restructuring. Current theories posit that during this period connections between frequently utilized neural networks are strengthened while underutilized synaptic connections are discarded. The aim of the present study was to examine the developmental evolution of connectivity between brain regions using the sleep EEG. All night sleep EEG recordings in two longitudinal cohorts (children and teens) followed at 1.5 3 year intervals and one ...

  20. Intraindividual Increase of Homeostatic Sleep Pressure Across Acute and Chronic Sleep Loss: A High-Density EEG Study.

    Science.gov (United States)

    Maric, Angelina; Lustenberger, Caroline; Werth, Esther; Baumann, Christian R; Poryazova, Rositsa; Huber, Reto

    2017-09-01

    To compare intraindividually the effects of acute sleep deprivation (ASD) and chronic sleep restriction (CSR) on the homeostatic increase in slow wave activity (SWA) and to relate it to impairments in basic cognitive functioning, that is, vigilance. The increase in SWA after ASD (40 hours of wakefulness) and after CSR (seven nights with time in bed restricted to 5 hours per night) relative to baseline sleep was assessed in nine healthy, male participants (age = 18-26 years) by high-density electroencephalography. The SWA increase during the initial part of sleep was compared between the two conditions of sleep loss. The increase in SWA was related to the increase in lapses of vigilance in the psychomotor vigilance task (PVT) during the preceding days. While ASD induced a stronger increase in initial SWA than CSR, the increase was globally correlated across the two conditions in most electrodes. The increase in initial SWA was positively associated with the increase in PVT lapses. The individual homeostatic response in SWA is globally preserved across acute and chronic sleep loss, that is, individuals showing a larger increase after ASD also do so after CSR and vice versa. Furthermore, the increase in SWA is globally correlated to vigilance impairments after sleep loss over both conditions. Thus, the increase in SWA might therefore provide a physiological marker for individual differences in performance impairments after sleep loss. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

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

    DEFF Research Database (Denmark)

    Hansen, Sofie Therese; Hansen, Lars Kai

    2016-01-01

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

  2. Atypical category processing and hemispheric asymmetries in high-functioning children with autism: revealed through high-density EEG mapping.

    Science.gov (United States)

    Fiebelkorn, Ian C; Foxe, John J; McCourt, Mark E; Dumas, Kristina N; Molholm, Sophie

    2013-05-01

    Behavioral evidence for an impaired ability to group objects based on similar physical or semantic properties in autism spectrum disorders (ASD) has been mixed. Here, we recorded brain activity from high-functioning children with ASD as they completed a visual-target detection task. We then assessed the extent to which object-based selective attention automatically generalized from targets to non-target exemplars from the same well-known object class (e.g., dogs). Our results provide clear electrophysiological evidence that children with ASD (N=17, aged 8-13 years) process the similarity between targets (e.g., a specific dog) and same-category non-targets (SCNT) (e.g., another dog) to a lesser extent than do their typically developing (TD) peers (N=21). A closer examination of the data revealed striking hemispheric asymmetries that were specific to the ASD group. These findings align with mounting evidence in the autism literature of anatomic underconnectivity between the cerebral hemispheres. Years of research in individuals with TD have demonstrated that the left hemisphere (LH) is specialized toward processing local (or featural) stimulus properties and the right hemisphere (RH) toward processing global (or configural) stimulus properties. We therefore propose a model where a lack of communication between the hemispheres in ASD, combined with typical hemispheric specialization, is a root cause for impaired categorization and the oft-observed bias to process local over global stimulus properties. Copyright © 2012 Elsevier Ltd. All rights reserved.

  3. Brain-computer interfaces for EEG neurofeedback: peculiarities and solutions.

    Science.gov (United States)

    Huster, René J; Mokom, Zacharais N; Enriquez-Geppert, Stefanie; Herrmann, Christoph S

    2014-01-01

    Neurofeedback training procedures designed to alter a person's brain activity have been in use for nearly four decades now and represent one of the earliest applications of brain-computer interfaces (BCI). The majority of studies using neurofeedback technology relies on recordings of the electroencephalogram (EEG) and applies neurofeedback in clinical contexts, exploring its potential as treatment for psychopathological syndromes. This clinical focus significantly affects the technology behind neurofeedback BCIs. For example, in contrast to other BCI applications, neurofeedback BCIs usually rely on EEG-derived features with only a minimum of additional processing steps being employed. Here, we highlight the peculiarities of EEG-based neurofeedback BCIs and consider their relevance for software implementations. Having reviewed already existing packages for the implementation of BCIs, we introduce our own solution which specifically considers the relevance of multi-subject handling for experimental and clinical trials, for example by implementing ready-to-use solutions for pseudo-/sham-neurofeedback. © 2013.

  4. Detection of EEG electrodes in brain volumes.

    Science.gov (United States)

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

    2010-01-01

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

  5. Prompt recognition of brain states by their EEG signals

    DEFF Research Database (Denmark)

    Peters, B.O.; Pfurtscheller, G.; Flyvbjerg, H.

    1997-01-01

    Brain states corresponding to intention of movement of left and right index finger and right foot are classified by a ''committee'' of artificial neural networks processing individual channels of 56-electrode electroencephalograms (EEGs). Correct recognition is achieved in 83% of cases...

  6. EEG datasets for motor imagery brain-computer interface.

    Science.gov (United States)

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

    2017-07-01

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

  7. Progress in EEG-Based Brain Robot Interaction Systems

    Directory of Open Access Journals (Sweden)

    Xiaoqian Mao

    2017-01-01

    Full Text Available The most popular noninvasive Brain Robot Interaction (BRI technology uses the electroencephalogram- (EEG- based Brain Computer Interface (BCI, to serve as an additional communication channel, for robot control via brainwaves. This technology is promising for elderly or disabled patient assistance with daily life. The key issue of a BRI system is to identify human mental activities, by decoding brainwaves, acquired with an EEG device. Compared with other BCI applications, such as word speller, the development of these applications may be more challenging since control of robot systems via brainwaves must consider surrounding environment feedback in real-time, robot mechanical kinematics, and dynamics, as well as robot control architecture and behavior. This article reviews the major techniques needed for developing BRI systems. In this review article, we first briefly introduce the background and development of mind-controlled robot technologies. Second, we discuss the EEG-based brain signal models with respect to generating principles, evoking mechanisms, and experimental paradigms. Subsequently, we review in detail commonly used methods for decoding brain signals, namely, preprocessing, feature extraction, and feature classification, and summarize several typical application examples. Next, we describe a few BRI applications, including wheelchairs, manipulators, drones, and humanoid robots with respect to synchronous and asynchronous BCI-based techniques. Finally, we address some existing problems and challenges with future BRI techniques.

  8. Continuous EEG-SEP monitoring in severe brain injury.

    Science.gov (United States)

    Amantini, A; Fossi, S; Grippo, A; Innocenti, P; Amadori, A; Bucciardini, L; Cossu, C; Nardini, C; Scarpelli, S; Roma, V; Pinto, F

    2009-04-01

    To monitor acute brain injury in the neurological intensive care unit (NICU), we used EEG and somatosensory evoked potentials (SEP) in combination to achieve more accuracy in detecting brain function deterioration. Sixty-eight patients (head trauma and intracranial hemorrhage; GCSSEP and intracranial pressure monitoring (ICP). Fifty-five patients were considered "stable" or improving, considering the GCS and CT scan: in this group, SEP didn't show significant changes. Thirteen patients showed neurological deteriorations and, in all patients, cortical SEP showed significant alterations (amplitude decrease>50% often till complete disappearance). SEP deterioration anticipated ICP increase in 30%, was contemporary in 38%, and followed ICP increase in 23%. Considering SEP and ICP in relation to clinical course, all patients but one with ICP less than 20 mmHg were stable, while the three patients with ICP greater than 40 mmHg all died. Among the 26 patients with ICP of 20-40 mmHg, 17 were stable, while nine showed clinical and neurophysiological deterioration. Thus, there is a range of ICP values (20-40 mmHg) were ICP is scarcely indicative of clinical deterioration, rather it is the SEP changes that identify brain function deterioration. Therefore, SEP have a twofold interest with respect to ICP: their changes can precede an ICP increase and they can constitute a complementary tool to interpret ICP trends. It has been very important to associate SEP and EEG: about 60% of our patients were deeply sedated and, because of their relative insensitivity to anesthetics, only SEP allowed us to monitor brain damage evolution when EEG was scarcely valuable. We observed 3% of nonconvulsive status epilepticus compared to 18% of neurological deterioration. If the aim of neurophysiological monitoring is to "detect and protect", it may not be limited to detecting seizures, rather it should be able to identify brain deterioration, so we propose the combined monitoring of EEG with SEP.

  9. Localizing Brain Activity from Multiple Distinct Sources via EEG

    Directory of Open Access Journals (Sweden)

    George Dassios

    2014-01-01

    Full Text Available An important question arousing in the framework of electroencephalography (EEG is the possibility to recognize, by means of a recorded surface potential, the number of activated areas in the brain. In the present paper, employing a homogeneous spherical conductor serving as an approximation of the brain, we provide a criterion which determines whether the measured surface potential is evoked by a single or multiple localized neuronal excitations. We show that the uniqueness of the inverse problem for a single dipole is closely connected with attaining certain relations connecting the measured data. Further, we present the necessary and sufficient conditions which decide whether the collected data originates from a single dipole or from numerous dipoles. In the case where the EEG data arouses from multiple parallel dipoles, an isolation of the source is, in general, not possible.

  10. Estimating Brain Load from the EEG

    Directory of Open Access Journals (Sweden)

    Anu Holm

    2009-01-01

    Full Text Available Modern work requires cognitively demanding multitasking and the need for sustained vigilance, which may result in work-related stress and may increase the possibility of human error. Objective methods for estimating cognitive overload and mental fatigue of the brain on-line, during work performance, are needed. We present a two-channel electroencephalography (EEG–based index, theta Fz/alpha Pz ratio, potentially implementable into a compact wearable device. The index reacts to both acute external and cumulative internal load. The index increased with the number of tasks to be performed concurrently (p = 0.004 and with increased time awake, both after normal sleep (p = 0.002 and sleep restriction (p = 0.004. Moreover, the increase of the index was more pronounced in the afternoon after sleep restriction (p = 0.006. As a measure of brain state and its dynamics, the index can be considered equivalent to the heartbeat, an indicator of the cardiovascular state, thus inspiring the name "brainbeat".

  11. Computerized EEG and brain imaging studies in untreated schizophrenic patients

    International Nuclear Information System (INIS)

    Miyauchi, Toshiro; Kishimoto, Hideji; Hagimoto, Hiroshi; Fujita, Haruhiro; Tanaka, Kenkichi

    1993-01-01

    We undertook routine EEG, Z-map, CT and PET scans in seven acute untreated schizophrenics. Routine EEGs showed slower activity in only one case. However, the Z-map showed slower activity in all the cases. CT demonstrated brain atrophy in three of the cases, and PET revealed hypofrontality in two, right hypoparietality in four, and both conditions in one case. There was no relation between CT and PET or the Z-map. However, a significant increase in alpha 1 activity was demonstrated on the Z-map in cases who were found to be the parietal type on PET; this was not conspicuous in the frontal type on PET. Moreover, in three of the patients, the Z-map findings were similar to the lesion indicated on PET. (author)

  12. Brain Network Analysis from High-Resolution EEG Signals

    Science.gov (United States)

    de Vico Fallani, Fabrizio; Babiloni, Fabio

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

  13. Functional imaging of the human brain using a modular, fibre-less, high-density diffuse optical tomography system.

    Science.gov (United States)

    Chitnis, Danial; Cooper, Robert J; Dempsey, Laura; Powell, Samuel; Quaggia, Simone; Highton, David; Elwell, Clare; Hebden, Jeremy C; Everdell, Nicholas L

    2016-10-01

    We present the first three-dimensional, functional images of the human brain to be obtained using a fibre-less, high-density diffuse optical tomography system. Our technology consists of independent, miniaturized, silicone-encapsulated DOT modules that can be placed directly on the scalp. Four of these modules were arranged to provide up to 128, dual-wavelength measurement channels over a scalp area of approximately 60 × 65 mm 2 . Using a series of motor-cortex stimulation experiments, we demonstrate that this system can obtain high-quality, continuous-wave measurements at source-detector separations ranging from 14 to 55 mm in adults, in the presence of hair. We identify robust haemodynamic response functions in 5 out of 5 subjects, and present diffuse optical tomography images that depict functional haemodynamic responses that are well-localized in all three dimensions at both the individual and group levels. This prototype modular system paves the way for a new generation of wearable, wireless, high-density optical neuroimaging technologies.

  14. Optimal spatiotemporal representation of multichannel EEG for recognition of brain states associated with distinct visual stimulus

    Science.gov (United States)

    Hramov, Alexander; Musatov, Vyacheslav Yu.; Runnova, Anastasija E.; Efremova, Tatiana Yu.; Koronovskii, Alexey A.; Pisarchik, Alexander N.

    2018-04-01

    In the paper we propose an approach based on artificial neural networks for recognition of different human brain states associated with distinct visual stimulus. Based on the developed numerical technique and the analysis of obtained experimental multichannel EEG data, we optimize the spatiotemporal representation of multichannel EEG to provide close to 97% accuracy in recognition of the EEG brain states during visual perception. Different interpretations of an ambiguous image produce different oscillatory patterns in the human EEG with similar features for every interpretation. Since these features are inherent to all subjects, a single artificial network can classify with high quality the associated brain states of other subjects.

  15. Demonstration of brain noise on human EEG signals in perception of bistable images

    Science.gov (United States)

    Grubov, Vadim V.; Runnova, Anastasiya E.; Kurovskaya, Maria K.; Pavlov, Alexey N.; Koronovskii, Alexey A.; Hramov, Alexander E.

    2016-03-01

    In this report we studied human brain activity in the case of bistable visual perception. We proposed a new approach for quantitative characterization of this activity based on analysis of EEG oscillatory patterns and evoked potentials. Accordingly to theoretical background, obtained experimental EEG data and results of its analysis we studied a characteristics of brain activity during decision-making. Also we have shown that decisionmaking process has the special patterns on the EEG data.

  16. Brain order disorder 2nd group report of f-EEG

    Science.gov (United States)

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

    2014-05-01

    Since the Brain Order Disorder (BOD) group reported on a high density Electroencephalogram (EEG) to capture the neuronal information using EEG to wirelessly interface with a Smartphone [1,2], a larger BOD group has been assembled, including the Obama BRAIN program, CUA Brain Computer Interface Lab and the UCSD Swartz Computational Neuroscience Center. We can implement the pair-electrodes correlation functions in order to operate in a real time daily environment, which is of the computation complexity of O(N3) for N=102~3 known as functional f-EEG. The daily monitoring requires two areas of focus. Area #(1) to quantify the neuronal information flow under arbitrary daily stimuli-response sources. Approach to #1: (i) We have asserted that the sources contained in the EEG signals may be discovered by an unsupervised learning neural network called blind sources separation (BSS) of independent entropy components, based on the irreversible Boltzmann cellular thermodynamics(ΔS function. (i) Although the entropy itself is not the information per se, but the concurrence of the entropy sources is the information flow as a functional-EEG, sketched in this 2nd BOD report. Area #(2) applying EEG bio-feedback will improve collective decision making (TBD). Approach to #2: We introduce a novel performance quality metrics, in terms of the throughput rate of faster (Δt) & more accurate (ΔA) decision making, which applies to individual, as well as team brain dynamics. Following Nobel Laureate Daniel Kahnmen's novel "Thinking fast and slow", through the brainwave biofeedback we can first identify an individual's "anchored cognitive bias sources". This is done in order to remove the biases by means of individually tailored pre-processing. Then the training effectiveness can be maximized by the collective product Δt * ΔA. For Area #1, we compute a spatiotemporally windowed EEG in vitro average using adaptive time-window sampling. The sampling rate depends on the type of neuronal

  17. Rhythmic EEG patterns in extremely preterm infants : Classification and association with brain injury and outcome

    NARCIS (Netherlands)

    Weeke, Lauren C; van Ooijen, Inge M; Groenendaal, Floris; van Huffelen, Alexander C.; van Haastert, Ingrid C; van Stam, Carolien; Benders, Manon J; Toet, Mona C; Hellström-Westas, Lena; de Vries, Linda S

    2017-01-01

    OBJECTIVE: Classify rhythmic EEG patterns in extremely preterm infants and relate these to brain injury and outcome. METHODS: Retrospective analysis of 77 infants born <28 weeks gestational age (GA) who had a 2-channel EEG during the first 72 h after birth. Patterns detected by the BrainZ seizure

  18. 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 ...

  19. 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

  20. Transcranial direct current stimulation generates a transient increase of small-world in brain connectivity: an EEG graph theoretical analysis.

    Science.gov (United States)

    Vecchio, Fabrizio; Di Iorio, Riccardo; Miraglia, Francesca; Granata, Giuseppe; Romanello, Roberto; Bramanti, Placido; Rossini, Paolo Maria

    2018-04-01

    Transcranial direct current stimulation (tDCS) is a non-invasive technique able to modulate cortical excitability in a polarity-dependent way. At present, only few studies investigated the effects of tDCS on the modulation of functional connectivity between remote cortical areas. The aim of this study was to investigate-through graph theory analysis-how bipolar tDCS modulate cortical networks high-density EEG recordings were acquired before and after bipolar cathodal, anodal and sham tDCS involving the primary motor and pre-motor cortices of the dominant hemispherein 14 healthy subjects. Results showed that, after bipolar anodal tDCS stimulation, brain networks presented a less evident "small world" organization with a global tendency to be more random in its functional connections with respect to prestimulus condition in both hemispheres. Results suggest that tDCS globally modulates the cortical connectivity of the brain, modifying the underlying functional organization of the stimulated networks, which might be related to changes in synaptic efficiency of the motor network and related brain areas. This study demonstrated that graph analysis approach to EEG recordings is able to intercept changes in cortical functions mediated by bipolar anodal tDCS mainly involving the dominant M1 and related motor areas. Concluding, tDCS could be an useful technique to help understanding brain rhythms and their topographic functional organization and specificity.

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

    Science.gov (United States)

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

    2012-05-01

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

  2. The colorful brain: Visualization of EEG background patterns

    NARCIS (Netherlands)

    van Putten, Michel Johannes Antonius Maria

    2008-01-01

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

  3. Wireless brain-machine interface using EEG and EOG: brain wave classification and robot control

    Science.gov (United States)

    Oh, Sechang; Kumar, Prashanth S.; Kwon, Hyeokjun; Varadan, Vijay K.

    2012-04-01

    A brain-machine interface (BMI) links a user's brain activity directly to an external device. It enables a person to control devices using only thought. Hence, it has gained significant interest in the design of assistive devices and systems for people with disabilities. In addition, BMI has also been proposed to replace humans with robots in the performance of dangerous tasks like explosives handling/diffusing, hazardous materials handling, fire fighting etc. There are mainly two types of BMI based on the measurement method of brain activity; invasive and non-invasive. Invasive BMI can provide pristine signals but it is expensive and surgery may lead to undesirable side effects. Recent advances in non-invasive BMI have opened the possibility of generating robust control signals from noisy brain activity signals like EEG and EOG. A practical implementation of a non-invasive BMI such as robot control requires: acquisition of brain signals with a robust wearable unit, noise filtering and signal processing, identification and extraction of relevant brain wave features and finally, an algorithm to determine control signals based on the wave features. In this work, we developed a wireless brain-machine interface with a small platform and established a BMI that can be used to control the movement of a robot by using the extracted features of the EEG and EOG signals. The system records and classifies EEG as alpha, beta, delta, and theta waves. The classified brain waves are then used to define the level of attention. The acceleration and deceleration or stopping of the robot is controlled based on the attention level of the wearer. In addition, the left and right movements of eye ball control the direction of the robot.

  4. EEG Oscillatory States: Universality, Uniqueness and Specificity across Healthy-Normal, Altered and Pathological Brain Conditions

    Science.gov (United States)

    Fingelkurts, Alexander A.; Fingelkurts, Andrew A.

    2014-01-01

    For the first time the dynamic repertoires and oscillatory types of local EEG states in 13 diverse conditions (examined over 9 studies) that covered healthy-normal, altered and pathological brain states were quantified within the same methodological and conceptual framework. EEG oscillatory states were assessed by the probability-classification analysis of short-term EEG spectral patterns. The results demonstrated that brain activity consists of a limited repertoire of local EEG states in any of the examined conditions. The size of the state repertoires was associated with changes in cognition and vigilance or neuropsychopathologic conditions. Additionally universal, optional and unique EEG states across 13 diverse conditions were observed. It was demonstrated also that EEG oscillations which constituted EEG states were characteristic for different groups of conditions in accordance to oscillations’ functional significance. The results suggested that (a) there is a limit in the number of local states available to the cortex and many ways in which these local states can rearrange themselves and still produce the same global state and (b) EEG individuality is determined by varying proportions of universal, optional and unique oscillatory states. The results enriched our understanding about dynamic microstructure of EEG-signal. PMID:24505292

  5. Functional community analysis of brain: a new approach for EEG-based investigation of the brain pathology.

    Science.gov (United States)

    Ahmadlou, Mehran; Adeli, Hojjat

    2011-09-15

    Analysis of structure of the brain functional connectivity (SBFC) is a fundamental issue for understanding of the brain cognition as well as the pathology of brain disorders. Analysis of communities among sub-parts of a system is increasingly used for social, ecological, and other networks. This paper presents a new methodology for investigation of the SBFC and understanding of the brain based on graph theory and community pattern analysis of functional connectivity graph of the brain obtained from encephalograms (EEGs). The methodology consists of three main parts: fuzzy synchronization likelihood (FSL), community partitioning, and decisions based on partitions. As an example application, the methodology is applied to analysis of brain of patients with attention deficit/hyperactivity disorder (ADHD) and the problem of discrimination of ADHD EEGs from healthy (non-ADHD) EEGs. Copyright © 2011. Published by Elsevier Inc.

  6. Brain Computer Interface: Assessment of Spinal Cord Injury Patient towards Motor Movement through EEG application

    Directory of Open Access Journals (Sweden)

    Syam Syahrull Hi-Fi

    2017-01-01

    Full Text Available Electroencephalography (EEG associated with motor task have been comprehensively investigated and it can also describe the brain activities while spinal cord injury (SCI patient with para/tetraplegia performing movement with their limbs. This paper reviews on conducted research regarding application of brain computer interface (BCI that offer alternative for neural impairments community such as spinal cord injury patient (SCI which include the experimental design, signal analysis of EEG band signal and data processing methods. The findings claim that the EEG signals of SCI patients associated with movement tasks can be stimulated through mental and motor task. Other than that EEG signal component such as alpha and beta frequency bands indicate significance for analysing the brain activity of subjects with SCI during movements.

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

    DEFF Research Database (Denmark)

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

    2017-01-01

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

  8. Could the beta rebound in the EEG be suitable to realize a "brain switch"?

    Science.gov (United States)

    Pfurtscheller, G; Solis-Escalante, T

    2009-01-01

    Performing foot motor imagery is accompanied by a peri-imagery ERD and a post-imagery beta ERS (beta rebound). Our aim was to study whether the post-imagery beta rebound is a suitable feature for a simple "brain switch". Such a brain switch is a specifically designed brain-computer interface (BCI) with the aim to detect only one predefined brain state (e.g. EEG pattern) in ongoing brain activity. One EEG (Laplacian) recorded at the vertex during cue-based brisk foot motor imagery was analysed in 5 healthy subjects. The peri-imagery ERD and the post-imagery beta rebound (ERS) were analysed in detail between 6 and 40Hz and classified with two support vector machines. The ERD was detected in ongoing EEG (simulation of asynchronous BCI) with a true positive rate (TPR) of 28.4%+/-13.5 and the beta rebound with a TPR of 59.2%+/-20.3. In single runs with 30 cues each, the TPR for beta rebound detection was 78.6%+/-12.8. The false positive rate was always kept below 10%. The findings suggest that the beta rebound at Cz during foot motor imagery is a relatively stable and reproducible phenomenon detectable in single EEG trials. Our results indicate that the beta rebound is a suitable feature to realize a "brain switch" with one single EEG (Laplacian) channel only.

  9. 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.

  10. Scale-Free Brain-Wave Music from Simultaneously EEG and fMRI Recordings

    Science.gov (United States)

    Lu, Jing; Wu, Dan; Yang, Hua; Luo, Cheng; Li, Chaoyi; Yao, Dezhong

    2012-01-01

    In the past years, a few methods have been developed to translate human EEG to music. In 2009, PloS One 4 e5915, we developed a method to generate scale-free brainwave music where the amplitude of EEG was translated to music pitch according to the power law followed by both of them, the period of an EEG waveform is translated directly to the duration of a note, and the logarithm of the average power change of EEG is translated to music intensity according to the Fechner's law. In this work, we proposed to adopt simultaneously-recorded fMRI signal to control the intensity of the EEG music, thus an EEG-fMRI music is generated by combining two different and simultaneous brain signals. And most importantly, this approach further realized power law for music intensity as fMRI signal follows it. Thus the EEG-fMRI music makes a step ahead in reflecting the physiological process of the scale-free brain. PMID:23166768

  11. Scale-free brain-wave music from simultaneously EEG and fMRI recordings.

    Science.gov (United States)

    Lu, Jing; Wu, Dan; Yang, Hua; Luo, Cheng; Li, Chaoyi; Yao, Dezhong

    2012-01-01

    In the past years, a few methods have been developed to translate human EEG to music. In 2009, PloS One 4 e5915, we developed a method to generate scale-free brainwave music where the amplitude of EEG was translated to music pitch according to the power law followed by both of them, the period of an EEG waveform is translated directly to the duration of a note, and the logarithm of the average power change of EEG is translated to music intensity according to the Fechner's law. In this work, we proposed to adopt simultaneously-recorded fMRI signal to control the intensity of the EEG music, thus an EEG-fMRI music is generated by combining two different and simultaneous brain signals. And most importantly, this approach further realized power law for music intensity as fMRI signal follows it. Thus the EEG-fMRI music makes a step ahead in reflecting the physiological process of the scale-free brain.

  12. Rhythmic EEG patterns in extremely preterm infants: Classification and association with brain injury and outcome.

    Science.gov (United States)

    Weeke, Lauren C; van Ooijen, Inge M; Groenendaal, Floris; van Huffelen, Alexander C; van Haastert, Ingrid C; van Stam, Carolien; Benders, Manon J; Toet, Mona C; Hellström-Westas, Lena; de Vries, Linda S

    2017-12-01

    Classify rhythmic EEG patterns in extremely preterm infants and relate these to brain injury and outcome. Retrospective analysis of 77 infants born Rhythmic patterns were observed in 62.3% (ictal 1.3%, PEDs 44%, other waveforms 86.3%) with multiple patterns in 36.4%. Ictal discharges were only observed in one and excluded from further analyses. The EEG location of the other waveforms (pRhythmic waveforms related to head position are likely artefacts. Rhythmic EEG patterns may have a different significance in extremely preterm infants. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

  13. Aberrant brain response after auditory deviance in PTSD compared to trauma controls: An EEG study

    NARCIS (Netherlands)

    Bangel, Katrin A.; van Buschbach, Susanne; Smit, Dirk J. A.; Mazaheri, Ali; Olff, Miranda

    2017-01-01

    Part of the symptomatology of post-traumatic stress disorder (PTSD) are alterations in arousal and reactivity which could be related to a maladaptive increase in the automated sensory change detection system of the brain. In the current EEG study we investigated whether the brain's response to a

  14. Extraction of features from sleep EEG for Bayesian assessment of brain development.

    Directory of Open Access Journals (Sweden)

    Vitaly Schetinin

    Full Text Available Brain development can be evaluated by experts analysing age-related patterns in sleep electroencephalograms (EEG. Natural variations in the patterns, noise, and artefacts affect the evaluation accuracy as well as experts' agreement. The knowledge of predictive posterior distribution allows experts to estimate confidence intervals within which decisions are distributed. Bayesian approach to probabilistic inference has provided accurate estimates of intervals of interest. In this paper we propose a new feature extraction technique for Bayesian assessment and estimation of predictive distribution in a case of newborn brain development assessment. The new EEG features are verified within the Bayesian framework on a large EEG data set including 1,100 recordings made from newborns in 10 age groups. The proposed features are highly correlated with brain maturation and their use increases the assessment accuracy.

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

    Science.gov (United States)

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

    2017-08-15

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

  16. {sup 99m}Tc-HMPAO Brain SPECT in Seizure Disorder: Comparison Brain SPECT, MRI / CT and EEG

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Hyung In [Kyunghee University Hospital, Seoul (Korea, Republic of); Im, Ju Hyuk; Choi, Chang Woon; Lee, Dong Soo; Chung, June Key; No, Jae Kyu; Lee, Myung Chul; Koh, Chang Soon [Seoul National University Hospital, Seoul (Korea, Republic of)

    1994-03-15

    We studied 115 patients with seizure who had been performed brain SPECT brain MRI of CT and EEG. To evaluate the pattern of brain SPECT in seizure patients 28 of them had secondary epilepsies, 87 had primary epilepsies. In primary epilepsies, 42 were generalized seizure and 45 were partial seizure. The causes of secondary epilepsies were congenital malformation, cerebromalacia, cerebral infarction ultiple sclerosis, AV-malformation. granuloma and etc, in order. In 28 secondary epilepsies, 25 of them, brain SPECT lesions was concordant with MRI or CT lesions. 3 were disconcordant. The brain SPECT findings of generalized seizure were normal in 22 patients, diffuse irregular decreased perfusion in 8, decreased in frontal cortex in 4. temporal in 5 and frontotemporal in 3. In 45 partial seizure, 19 brain SPECT were concordant with EEG (42.4%).

  17. 99mTc-HMPAO Brain SPECT in Seizure Disorder: Comparison Brain SPECT, MRI / CT and EEG

    International Nuclear Information System (INIS)

    Yang, Hyung In; Im, Ju Hyuk; Choi, Chang Woon; Lee, Dong Soo; Chung, June Key; No, Jae Kyu; Lee, Myung Chul; Koh, Chang Soon

    1994-01-01

    We studied 115 patients with seizure who had been performed brain SPECT brain MRI of CT and EEG. To evaluate the pattern of brain SPECT in seizure patients 28 of them had secondary epilepsies, 87 had primary epilepsies. In primary epilepsies, 42 were generalized seizure and 45 were partial seizure. The causes of secondary epilepsies were congenital malformation, cerebromalacia, cerebral infarction ultiple sclerosis, AV-malformation. granuloma and etc, in order. In 28 secondary epilepsies, 25 of them, brain SPECT lesions was concordant with MRI or CT lesions. 3 were disconcordant. The brain SPECT findings of generalized seizure were normal in 22 patients, diffuse irregular decreased perfusion in 8, decreased in frontal cortex in 4. temporal in 5 and frontotemporal in 3. In 45 partial seizure, 19 brain SPECT were concordant with EEG (42.4%).

  18. Brain perfusion SPECT and EEG findings in Rett syndrome

    International Nuclear Information System (INIS)

    Lappalainen, R.; Liewendahl, K.; Nikkinen, P.; Sainio, K.; Riikonen, R.S.

    1997-01-01

    Thirteen patients (mean age 8.4 + 5.3 years) with Rett syndrome (RS) were studied with EEG and 99m Tc-HMPAO SPECT. Eleven patients had background abnormalities and 10 patients paroxysmal activity in EEG. Hypoperfusion of varying severity was detected in 11 patients, 7 patients having multiple lesions. Bifrontal hypoperfusion, observed in 6 patients, was the most distinctive finding. Hypoperfusion was observed also in other cortical regions, except for the occipital lobes. There was no correlation between severity of the background abnormality or presence of paroxysmal activity in EEG and grade of hypoperfusion. There was, however, an association between the severity of hypoperfusion and early manifestation of symptoms in patients with RS. Whether this early-onset group of patients represents a different disease entity or only reflects disease variability the basic pathology being the same, is a possibility that deserves further clarification. (au) 37 refs

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

    Directory of Open Access Journals (Sweden)

    Farrokh Mansouri

    2017-07-01

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

  20. Similar or disparate brain patterns? The intra-personal EEG variability of three women with multiple personality disorder.

    Science.gov (United States)

    Lapointe, A R; Crayton, J W; DeVito, R; Fichtner, C G; Konopka, L M

    2006-07-01

    Quantitative EEG was used to assess the intra-personal variability of brain electrical activity for 3 women diagnosed with Multiple Personality Disorder (MPD). Two separate control groups (within-subject and between-subject) were used to test the hypothesis that the intra-personal EEG variability between 2 alters would be less than the interpersonal EEG variability between 2 controls, and similar to the intra-personal EEG variability of a single personality. This hypothesis was partially supported. In general, the 2 EEG records of a MPD subject (alter 1 vs. alter 2) were more different from one another than the 2 EEG records of a single control, but less different from one another than the EEG records of 2 separate controls. Most of the EEG variability between alters involved beta activity in the frontal and temporal lobes.

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

    Science.gov (United States)

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

    2007-01-01

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

  2. Development of Brain EEG Connectivity across Early Childhood: Does Sleep Play a Role?

    Directory of Open Access Journals (Sweden)

    Monique K. LeBourgeois

    2013-11-01

    Full Text Available Sleep has beneficial effects on brain function and learning, which are reflected in plastic changes in the cortex. Early childhood is a time of rapid maturation in fundamental skills—e.g., language, cognitive control, working memory—that are predictive of future functioning. Little is currently known about the interactions between sleep and brain maturation during this developmental period. We propose coherent electroencephalogram (EEG activity during sleep may provide unique insight into maturational processes of functional brain connectivity. Longitudinal sleep EEG assessments were performed in eight healthy subjects at ages 2, 3 and 5 years. Sleep EEG coherence increased across development in a region- and frequency-specific manner. Moreover, although connectivity primarily decreased intra-hemispherically across a night of sleep, an inter-hemispheric overnight increase occurred in the frequency range of slow waves (0.8–2 Hz, theta (4.8–7.8 Hz and sleep spindles (10–14 Hz, with connectivity changes of up to 20% across a night of sleep. These findings indicate sleep EEG coherence reflects processes of brain maturation—i.e., programmed unfolding of neuronal networks—and moreover, sleep-related alterations of brain connectivity during the sensitive maturational window of early childhood.

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

    Science.gov (United States)

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

    2015-09-01

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

  4. Impact of metal artefacts due to EEG electrodes in brain PET/CT imaging

    International Nuclear Information System (INIS)

    Lemmens, Catherine; Nuyts, Johan; Dupont, Patrick; Montandon, Marie-Louise; Ratib, Osman; Zaidi, Habib

    2008-01-01

    The goal of this study is to investigate the impact of electroencephalogram (EEG) electrodes on the visual quality and quantification of 18 F-FDG PET images in neurological PET/CT examinations. For this purpose, the scans of 20 epilepsy patients with EEG monitoring were used. The CT data were reconstructed with filtered backprojection (FBP) and with a metal artefact reduction (MAR) algorithm. Both data sets were used for CT-based attenuation correction (AC) of the PET data. Also, a calculated AC (CALC) technique was considered. A volume of interest (VOI)-based analysis and a voxel-based quantitative analysis were performed to compare the different AC methods. Images were also evaluated visually by two observers. It was shown with simulations and phantom measurements that from the considered AC methods, the MAR-AC can be used as the reference in this setting. The visual assessment of PET images showed local hot spots outside the brain corresponding to the locations of the electrodes when using FBP-AC. In the brain, no abnormalities were observed. The quantitative analysis showed a very good correlation between PET-FBP-AC and PET-MAR-AC, with a statistically significant positive bias in the PET-FBP-AC images of about 5-7% in most brain voxels. There was also good correlation between PET-CALC-AC and PET-MAR-AC, but in the PET-CALC-AC images, regions with both a significant positive and negative bias were observed. EEG electrodes give rise to local hot spots outside the brain and a positive quantification bias in the brain. However, when diagnosis is made by mere visual assessment, the presence of EEG electrodes does not seem to alter the diagnosis. When quantification is performed, the bias becomes an issue especially when comparing brain images with and without EEG monitoring

  5. Impact of metal artefacts due to EEG electrodes in brain PET/CT imaging

    Energy Technology Data Exchange (ETDEWEB)

    Lemmens, Catherine; Nuyts, Johan; Dupont, Patrick [Department of Nuclear Medicine and Medical Imaging Center, University Hospital Gasthuisberg and Katholieke Universiteit Leuven, Leuven (Belgium); Montandon, Marie-Louise; Ratib, Osman; Zaidi, Habib [Division of Nuclear Medicine, Geneva University Hospital, CH-1211 Geneva (Switzerland)], E-mail: catherine.lemmens@uz.kuleuven.be

    2008-08-21

    The goal of this study is to investigate the impact of electroencephalogram (EEG) electrodes on the visual quality and quantification of {sup 18}F-FDG PET images in neurological PET/CT examinations. For this purpose, the scans of 20 epilepsy patients with EEG monitoring were used. The CT data were reconstructed with filtered backprojection (FBP) and with a metal artefact reduction (MAR) algorithm. Both data sets were used for CT-based attenuation correction (AC) of the PET data. Also, a calculated AC (CALC) technique was considered. A volume of interest (VOI)-based analysis and a voxel-based quantitative analysis were performed to compare the different AC methods. Images were also evaluated visually by two observers. It was shown with simulations and phantom measurements that from the considered AC methods, the MAR-AC can be used as the reference in this setting. The visual assessment of PET images showed local hot spots outside the brain corresponding to the locations of the electrodes when using FBP-AC. In the brain, no abnormalities were observed. The quantitative analysis showed a very good correlation between PET-FBP-AC and PET-MAR-AC, with a statistically significant positive bias in the PET-FBP-AC images of about 5-7% in most brain voxels. There was also good correlation between PET-CALC-AC and PET-MAR-AC, but in the PET-CALC-AC images, regions with both a significant positive and negative bias were observed. EEG electrodes give rise to local hot spots outside the brain and a positive quantification bias in the brain. However, when diagnosis is made by mere visual assessment, the presence of EEG electrodes does not seem to alter the diagnosis. When quantification is performed, the bias becomes an issue especially when comparing brain images with and without EEG monitoring.

  6. Estimation of effective brain connectivity with dual Kalman filter and EEG source localization methods.

    Science.gov (United States)

    Rajabioun, Mehdi; Nasrabadi, Ali Motie; Shamsollahi, Mohammad Bagher

    2017-09-01

    Effective connectivity is one of the most important considerations in brain functional mapping via EEG. It demonstrates the effects of a particular active brain region on others. In this paper, a new method is proposed which is based on dual Kalman filter. In this method, firstly by using a brain active localization method (standardized low resolution brain electromagnetic tomography) and applying it to EEG signal, active regions are extracted, and appropriate time model (multivariate autoregressive model) is fitted to extracted brain active sources for evaluating the activity and time dependence between sources. Then, dual Kalman filter is used to estimate model parameters or effective connectivity between active regions. The advantage of this method is the estimation of different brain parts activity simultaneously with the calculation of effective connectivity between active regions. By combining dual Kalman filter with brain source localization methods, in addition to the connectivity estimation between parts, source activity is updated during the time. The proposed method performance has been evaluated firstly by applying it to simulated EEG signals with interacting connectivity simulation between active parts. Noisy simulated signals with different signal to noise ratios are used for evaluating method sensitivity to noise and comparing proposed method performance with other methods. Then the method is applied to real signals and the estimation error during a sweeping window is calculated. By comparing proposed method results in different simulation (simulated and real signals), proposed method gives acceptable results with least mean square error in noisy or real conditions.

  7. Cross-sensory gating in schizophrenia and autism spectrum disorder : EEG evidence for impaired brain connectivity?

    NARCIS (Netherlands)

    Magnee, Maurice J. C. M.; Oranje, Bob; van Engeland, Herman; Kahn, Rene S.; Kemner, Chantal

    Autism spectrum disorders (ASD) and schizophrenia are both neurodevelopmental disorders that have extensively been associated with impairments in functional brain connectivity. Using a cross-sensory P50 suppression paradigm, this study investigated low-level audiovisual interactions on cortical EEG

  8. Sleep EEG Changes during Adolescence: An Index of a Fundamental Brain Reorganization

    Science.gov (United States)

    Feinberg, Irwin; Campbell, Ian G.

    2010-01-01

    Delta (1-4 Hz) EEG power in non-rapid eye movement (NREM) sleep declines massively during adolescence. This observation stimulated the hypothesis that during adolescence the human brain undergoes an extensive reorganization driven by synaptic elimination. The parallel declines in synaptic density, delta wave amplitude and cortical metabolic rate…

  9. Electroencephalography(EEG)-based instinctive brain-control of a quadruped locomotion robot.

    Science.gov (United States)

    Jia, Wenchuan; Huang, Dandan; Luo, Xin; Pu, Huayan; Chen, Xuedong; Bai, Ou

    2012-01-01

    Artificial intelligence and bionic control have been applied in electroencephalography (EEG)-based robot system, to execute complex brain-control task. Nevertheless, due to technical limitations of the EEG decoding, the brain-computer interface (BCI) protocol is often complex, and the mapping between the EEG signal and the practical instructions lack of logic associated, which restrict the user's actual use. This paper presents a strategy that can be used to control a quadruped locomotion robot by user's instinctive action, based on five kinds of movement related neurophysiological signal. In actual use, the user drives or imagines the limbs/wrists action to generate EEG signal to adjust the real movement of the robot according to his/her own motor reflex of the robot locomotion. This method is easy for real use, as the user generates the brain-control signal through the instinctive reaction. By adopting the behavioral control of learning and evolution based on the proposed strategy, complex movement task may be realized by instinctive brain-control.

  10. Patient Specific Characteristic of Brain Dynamic in Interpretation of Long Term EEG Analysis

    Czech Academy of Sciences Publication Activity Database

    Komárek, V.; Paluš, Milan; Hrnčíř, Z.

    2004-01-01

    Roč. 45, Suppl. 3 (2004), s. 51 ISSN 0013-9580. [European Congress on Epileptology /6./. 30.05.2004-03.06.2004, Vienna] R&D Projects: GA MŠk ME 701 Institutional research plan: CEZ:AV0Z1030915 Keywords : brain dynamic * long term EEG analysis Subject RIV: FH - Neurology

  11. [Intracerebral EEG functioning as a reflexion of the systemic brain organization in norm and pathology].

    Science.gov (United States)

    Boldyreva, G N; Zhavoronkova, L A; Sharova, E V; Dobronravova, I S

    2003-01-01

    The authors summarized the EEG findings and defined the nature of intercentral EEG relationships in different functional states of healthy subjects and patients with organic cerebral pathology based on coherence analysis. The EEG features typical of healthy subjects were identified: an anterior-posterior gradient of the mean coherence and the character of cortical-subcortical relationships in the anterior cerebral structures. Right- and lefthanded subjects showed the frequency and regional differences in EEG coherence, which reflected, mainly, specific intracortical relationships. Development and regression of pathologic signs in right- and lefthanded patients with organic brain lesions are thought to be determined by these differences. As distinct from cortical pathology, lesions of regulatory structures (diencephalic, brainstem, and limbic) were shown to produce more diffuse changes in intercentral relationships with a tendency to reciprocity. Intercentral relations, including their interhemispheric differences, varied with changes in the functional state of healthy subjects (increase and decrease in the level of functioning). A certain time course of changes in intercentral relationships was also revealed in patients with organic brain lesions during recovery of their consciousness and mental activity. Changes in the dominance of activity of individual regulatory structures are considered to be one of the most important factors that determine the dynamic character of EEG coherence.

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

    Directory of Open Access Journals (Sweden)

    Kei Omata

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

  13. The urban brain: analysing outdoor physical activity with mobile EEG.

    Science.gov (United States)

    Aspinall, Peter; Mavros, Panagiotis; Coyne, Richard; Roe, Jenny

    2015-02-01

    Researchers in environmental psychology, health studies and urban design are interested in the relationship between the environment, behaviour settings and emotions. In particular, happiness, or the presence of positive emotional mindsets, broadens an individual's thought-action repertoire with positive benefits to physical and intellectual activities, and to social and psychological resources. This occurs through play, exploration or similar activities. In addition, a body of restorative literature focuses on the potential benefits to emotional recovery from stress offered by green space and 'soft fascination'. However, access to the cortical correlates of emotional states of a person actively engaged within an environment has not been possible until recently. This study investigates the use of mobile electroencephalography (EEG) as a method to record and analyse the emotional experience of a group of walkers in three types of urban environment including a green space setting. Using Emotiv EPOC, a low-cost mobile EEG recorder, participants took part in a 25 min walk through three different areas of Edinburgh. The areas (of approximately equal length) were labelled zone 1 (urban shopping street), zone 2 (path through green space) and zone 3 (street in a busy commercial district). The equipment provided continuous recordings from five channels, labelled excitement (short-term), frustration, engagement, long-term excitement (or arousal) and meditation. A new form of high-dimensional correlated component logistic regression analysis showed evidence of lower frustration, engagement and arousal, and higher meditation when moving into the green space zone; and higher engagement when moving out of it. Systematic differences in EEG recordings were found between three urban areas in line with restoration theory. This has implications for promoting urban green space as a mood-enhancing environment for walking or for other forms of physical or reflective activity. Published

  14. Slow oscillation electrical brain stimulation during waking promotes EEG theta activity and memory encoding

    DEFF Research Database (Denmark)

    Kirov, Roumen; Weiss, Carsten; Siebner, Hartwig R

    2009-01-01

    typically occurring during this state of sleep were also enhanced. Here, we show that the same tSOS applied in the waking brain also induced an increase in endogenous EEG slow oscillations (0.4-1.2 Hz), although in a topographically restricted fashion. Applied during wakefulness tSOS, additionally, resulted......The application of transcranial slow oscillation stimulation (tSOS; 0.75 Hz) was previously shown to enhance widespread endogenous EEG slow oscillatory activity when applied during a sleep period characterized by emerging endogenous slow oscillatory activity. Processes of memory consolidation...... induced by tSOS critically depend on brain state. In response to tSOS during wakefulness the brain transposes stimulation by responding preferentially with theta oscillations and facilitated encoding....

  15. 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.

  16. 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

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2014-02-01

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

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

    Science.gov (United States)

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

    2001-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Stavros I. Dimitriadis

    2017-09-01

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

  1. 123I-iomazenil brain receptor SPECT in focal epilepsy. In comparison with 99mTc-HMPAO brain SPECT, MRI and Video/EEG monitoring

    International Nuclear Information System (INIS)

    Xu Hao; Wang Tongge; Huang Li; Michael Cordes

    1998-01-01

    Purpose: To evaluate the clinical value of 123 I-Iomazenil brain receptor SPECT in diagnosis of focal epilepsy in comparison with 99m Tc-HMPAO brain SPECT, MRI and Video/EEG monitoring. Methods 123 I-Iomazenil brain receptor SPECT was performed on 40 patients with focal epilepsy. The results were compared with those obtained by 99m Tc-HMPAO brain SPECT, MRI and Video/EEG monitoring. Results: In 40 patients, the sensitivity of Video/EEG monitoring for localization of epileptogenic area was 95% (38/40). The sensitivity of 123 I-iomazenil brain receptor SPECT, 99m Tc-HMPAO brain SPECT and MRI for localization of epileptogenic area compared with Video/EEG monitoring ('gold standard') was 65.8%(25/38), 55.3%(21/38) and 47.4%(18/38), respectively. The localization of epileptogenic area with 123 I-Iomazenil brain receptor SPECT was in concordance with Video/EEG monitoring in 20 patients, 99m Tc-HMPAO brain SPECT in 15 patients and MRI in 16 patients, respectively. The sensitivity of 123 I-Iomazenil brain receptor SPECT combined with MRI for localization of epileptogenic area was 84.2%(32/38). Conclusions: 123 I-Iomazenil brain receptor SPECT is a useful method in detecting and localizing epileptogenic area. The combination of 123 I-Iomazenil brain receptor SPECT and MRI has a high sensitivity for detecting epileptogenic area

  2. Analysis of EEG activity during sleep - brain hemisphere symmetry of two classes of sleep spindles

    Science.gov (United States)

    Smolen, Magdalena M.

    2009-01-01

    This paper presents automatic analysis of some selected human electroencephalographic patterns during deep sleep using the Matching Pursuit (MP) algorithm. The periodicity of deep sleep EEG patterns was observed by calculating autocorrelation functions of their percentage contributions. The study confirmed the increasing trend of amplitude-weighted average frequency of sleep spindles from frontal to posterior derivations. The dominant frequencies from the left and the right brain hemisphere were strongly correlated.

  3. Study of heart-brain interactions through EEG, ECG, and emotions

    Science.gov (United States)

    Ramasamy, Mouli; Varadan, Vijay K.

    2017-04-01

    Neurocardiology is the exploration of neurophysiological, neurological and neuroanatomical facets of neuroscience's influence in cardiology. The paraphernalia of emotions on the heart and brain are premeditated because of the interaction between the central and peripheral nervous system. This is an investigative attempt to study emotion based neurocardiology and the factors that influence this phenomenon. The factors include: interaction between sleep EEG (electroencephalogram) and ECG (electrocardiogram), relationship between emotion and music, psychophysiological coherence between the heart and brain, emotion recognition techniques, and biofeedback mechanisms. Emotions contribute vitally to the mundane life and are quintessential to a numerous biological and everyday-functional modality of a human being. Emotions are best represented through EEG signals, and to a certain extent, can be observed through ECG and body temperature. Confluence of medical and engineering science has enabled the monitoring and discrimination of emotions influenced by happiness, anxiety, distress, excitement and several other factors that influence the thinking patterns and the electrical activity of the brain. Similarly, HRV (Heart Rate Variability) widely investigated for its provision and discerning characteristics towards EEG and the perception in neurocardiology.

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

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

    Gutierrez, David

    2008-01-01

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

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

    Science.gov (United States)

    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.

  7. Bayesian learning for spatial filtering in an EEG-based brain-computer interface.

    Science.gov (United States)

    Zhang, Haihong; Yang, Huijuan; Guan, Cuntai

    2013-07-01

    Spatial filtering for EEG feature extraction and classification is an important tool in brain-computer interface. However, there is generally no established theory that links spatial filtering directly to Bayes classification error. To address this issue, this paper proposes and studies a Bayesian analysis theory for spatial filtering in relation to Bayes error. Following the maximum entropy principle, we introduce a gamma probability model for describing single-trial EEG power features. We then formulate and analyze the theoretical relationship between Bayes classification error and the so-called Rayleigh quotient, which is a function of spatial filters and basically measures the ratio in power features between two classes. This paper also reports our extensive study that examines the theory and its use in classification, using three publicly available EEG data sets and state-of-the-art spatial filtering techniques and various classifiers. Specifically, we validate the positive relationship between Bayes error and Rayleigh quotient in real EEG power features. Finally, we demonstrate that the Bayes error can be practically reduced by applying a new spatial filter with lower Rayleigh quotient.

  8. Feature Selection and Blind Source Separation in an EEG-Based Brain-Computer Interface

    Directory of Open Access Journals (Sweden)

    Michael H. Thaut

    2005-11-01

    Full Text Available Most EEG-based BCI systems make use of well-studied patterns of brain activity. However, those systems involve tasks that indirectly map to simple binary commands such as “yes” or “no” or require many weeks of biofeedback training. We hypothesized that signal processing and machine learning methods can be used to discriminate EEG in a direct “yes”/“no” BCI from a single session. Blind source separation (BSS and spectral transformations of the EEG produced a 180-dimensional feature space. We used a modified genetic algorithm (GA wrapped around a support vector machine (SVM classifier to search the space of feature subsets. The GA-based search found feature subsets that outperform full feature sets and random feature subsets. Also, BSS transformations of the EEG outperformed the original time series, particularly in conjunction with a subset search of both spaces. The results suggest that BSS and feature selection can be used to improve the performance of even a “direct,” single-session BCI.

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

    Science.gov (United States)

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

    2011-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Giovanni Vecchiato

    2011-01-01

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

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

    Science.gov (United States)

    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.

  12. Reduction in time-to-sleep through EEG based brain state detection and audio stimulation.

    Science.gov (United States)

    Zhuo Zhang; Cuntai Guan; Ti Eu Chan; Juanhong Yu; Aung Aung Phyo Wai; Chuanchu Wang; Haihong Zhang

    2015-08-01

    We developed an EEG- and audio-based sleep sensing and enhancing system, called iSleep (interactive Sleep enhancement apparatus). The system adopts a closed-loop approach which optimizes the audio recording selection based on user's sleep status detected through our online EEG computing algorithm. The iSleep prototype comprises two major parts: 1) a sleeping mask integrated with a single channel EEG electrode and amplifier, a pair of stereo earphones and a microcontroller with wireless circuit for control and data streaming; 2) a mobile app to receive EEG signals for online sleep monitoring and audio playback control. In this study we attempt to validate our hypothesis that appropriate audio stimulation in relation to brain state can induce faster onset of sleep and improve the quality of a nap. We conduct experiments on 28 healthy subjects, each undergoing two nap sessions - one with a quiet background and one with our audio-stimulation. We compare the time-to-sleep in both sessions between two groups of subjects, e.g., fast and slow sleep onset groups. The p-value obtained from Wilcoxon Signed Rank Test is 1.22e-04 for slow onset group, which demonstrates that iSleep can significantly reduce the time-to-sleep for people with difficulty in falling sleep.

  13. [EEG markers of spontaneous recovery of vertical posture in patients with consequences of severe traumatic brain injury].

    Science.gov (United States)

    Zhavoronkova, L A; Zharikova, A V; Maksakova, O A

    2014-01-01

    9 patients (mean age 23.6 +/- 3.15 y.o.) with severe traumatic brain injury (TBI) and impairment of vertical posture were included in complex clinical and EEG study during spontaneous recovery of vertical posture (VP). Patients were included in three different groups according to severity of deficit according to MPAI, FIM and MMSE scales. EEG data have been compared to those of 10 healthy volunteers (mean age 22.8 +/- 0.67 yo.). In patients with moderate brain impairment and fast recovery of VP (over 2 weeks) change of posture from sitting to standup has been accompanied by EEG-signs similar to those of healthy people. These included predominant increase of coherence in right hemisphere for majority of frequency bands, although in more complex conditions EEG of these patients showed pathological signs. In patients with more severe deficit spontaneous recovery of VP has been accompanied by "hyper-reactive" change of EEG for all frequency bands without local specificity. This finding didn't depend on side ofbrain impairment and could be considered as marker of positive dynamics of VP restoration. In patients with most severe brain impairment and deficit of functions VP didn't recover after 3 month of observation. EEG-investigation has revealed absence of reactive change of EEG during passive verticalisation. This finding can be used as marker of negative prognosis.

  14. Preliminary study of Alzheimer's Disease diagnosis based on brain electrical signals using wireless EEG

    Science.gov (United States)

    Handayani, N.; Akbar, Y.; Khotimah, S. N.; Haryanto, F.; Arif, I.; Taruno, W. P.

    2016-03-01

    This research aims to study brain's electrical signals recorded using EEG as a basis for the diagnosis of patients with Alzheimer's Disease (AD). The subjects consisted of patients with AD, and normal subjects are used as the control. Brain signals are recorded for 3 minutes in a relaxed condition and with eyes closed. The data is processed using power spectral analysis, brain mapping and chaos test to observe the level of complexity of EEG's data. The results show a shift in the power spectral in the low frequency band (delta and theta) in AD patients. The increase of delta and theta occurs in lobus frontal area and lobus parietal respectively. However, there is a decrease of alpha activity in AD patients where in the case of normal subjects with relaxed condition, brain alpha wave dominates the posterior area. This is confirmed by the results of brain mapping. While the results of chaos analysis show that the average value of MMLE is lower in AD patients than in normal subjects. The level of chaos associated with neural complexity in AD patients with lower neural complexity is due to neuronal damage caused by the beta amyloid plaques and tau protein in neurons.

  15. Comparative analysis of brain EEG signals generated from the right and left hand while writing

    Science.gov (United States)

    Sardesai, Neha; Jamali Mahabadi, S. E.; Meng, Qinglei; Choa, Fow-Sen

    2016-05-01

    This paper provides a comparative analysis of right handed people and left handed people when they write with both their hands. Two left handed and one right handed subject were asked to write their respective names on a paper using both, their left and right handed, and their brain signals were measured using EEG. Similarly, they were asked to perform simple mathematical calculations using both their hand. The data collected from the EEG from writing with both hands is compared. It is observed that though it is expected that the right brain only would contribute to left handed writing and vice versa, it is not so. When a right handed person writes with his/her left hand, the initial instinct is to go for writing with the right hand. Hence, both parts of the brain are active when a subject writes with the other hand. However, when the activity is repeated, the brain learns to expect to write with the other hand as the activity is repeated and then only the expected part of the brain is active.

  16. Study on Brain Dynamics by Non Linear Analysis of Music Induced EEG Signals

    Science.gov (United States)

    Banerjee, Archi; Sanyal, Shankha; Patranabis, Anirban; Banerjee, Kaushik; Guhathakurta, Tarit; Sengupta, Ranjan; Ghosh, Dipak; Ghose, Partha

    2016-02-01

    Music has been proven to be a valuable tool for the understanding of human cognition, human emotion, and their underlying brain mechanisms. The objective of this study is to analyze the effect of Hindustani music on brain activity during normal relaxing conditions using electroencephalography (EEG). Ten male healthy subjects without special musical education participated in the study. EEG signals were acquired at the frontal (F3/F4) lobes of the brain while listening to music at three experimental conditions (rest, with music and without music). Frequency analysis was done for the alpha, theta and gamma brain rhythms. The finding shows that arousal based activities were enhanced while listening to Hindustani music of contrasting emotions (romantic/sorrow) for all the subjects in case of alpha frequency bands while no significant changes were observed in gamma and theta frequency ranges. It has been observed that when the music stimulus is removed, arousal activities as evident from alpha brain rhythms remain for some time, showing residual arousal. This is analogous to the conventional 'Hysteresis' loop where the system retains some 'memory' of the former state. This is corroborated in the non linear analysis (Detrended Fluctuation Analysis) of the alpha rhythms as manifested in values of fractal dimension. After an input of music conveying contrast emotions, withdrawal of music shows more retention as evidenced by the values of fractal dimension.

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

    Directory of Open Access Journals (Sweden)

    Dan Wu

    2018-03-01

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

  18. Intracranial EEG fluctuates over months after implanting electrodes in human brain

    Science.gov (United States)

    Ung, Hoameng; Baldassano, Steven N.; Bink, Hank; Krieger, Abba M.; Williams, Shawniqua; Vitale, Flavia; Wu, Chengyuan; Freestone, Dean; Nurse, Ewan; Leyde, Kent; Davis, Kathryn A.; Cook, Mark; Litt, Brian

    2017-10-01

    Objective. Implanting subdural and penetrating electrodes in the brain causes acute trauma and inflammation that affect intracranial electroencephalographic (iEEG) recordings. This behavior and its potential impact on clinical decision-making and algorithms for implanted devices have not been assessed in detail. In this study we aim to characterize the temporal and spatial variability of continuous, prolonged human iEEG recordings. Approach. Intracranial electroencephalography from 15 patients with drug-refractory epilepsy, each implanted with 16 subdural electrodes and continuously monitored for an average of 18 months, was included in this study. Time and spectral domain features were computed each day for each channel for the duration of each patient’s recording. Metrics to capture post-implantation feature changes and inflexion points were computed on group and individual levels. A linear mixed model was used to characterize transient group-level changes in feature values post-implantation and independent linear models were used to describe individual variability. Main results. A significant decline in features important to seizure detection and prediction algorithms (mean line length, energy, and half-wave), as well as mean power in the Berger and high gamma bands, was observed in many patients over 100 d following implantation. In addition, spatial variability across electrodes declines post-implantation following a similar timeframe. All selected features decreased by 14-50% in the initial 75 d of recording on the group level, and at least one feature demonstrated this pattern in 13 of the 15 patients. Our findings indicate that iEEG signal features demonstrate increased variability following implantation, most notably in the weeks immediately post-implant. Significance. These findings suggest that conclusions drawn from iEEG, both clinically and for research, should account for spatiotemporal signal variability and that properly assessing the iEEG in

  19. Design of a 32-channel EEG system for brain control interface applications.

    Science.gov (United States)

    Wang, Ching-Sung

    2012-01-01

    This study integrates the hardware circuit design and the development support of the software interface to achieve a 32-channel EEG system for BCI applications. Since the EEG signals of human bodies are generally very weak, in addition to preventing noise interference, it also requires avoiding the waveform distortion as well as waveform offset and so on; therefore, the design of a preamplifier with high common-mode rejection ratio and high signal-to-noise ratio is very important. Moreover, the friction between the electrode pads and the skin as well as the design of dual power supply will generate DC bias which affects the measurement signals. For this reason, this study specially designs an improved single-power AC-coupled circuit, which effectively reduces the DC bias and improves the error caused by the effects of part errors. At the same time, the digital way is applied to design the adjustable amplification and filter function, which can design for different EEG frequency bands. For the analog circuit, a frequency band will be taken out through the filtering circuit and then the digital filtering design will be used to adjust the extracted frequency band for the target frequency band, combining with MATLAB to design man-machine interface for displaying brain wave. Finally the measured signals are compared to the traditional 32-channel EEG signals. In addition to meeting the IFCN standards, the system design also conducted measurement verification in the standard EEG isolation room in order to demonstrate the accuracy and reliability of this system design.

  20. Comparison of global brain gene expression profiles between inbred long-sleep and inbred short-sleep mice by high-density gene array hybridization.

    Science.gov (United States)

    Xu, Y; Ehringer, M; Yang, F; Sikela, J M

    2001-06-01

    Inbred long-sleep (ILS) and short-sleep (ISS) mice show significant central nervous system-mediated differences in sleep time for sedative dose of ethanol and are frequently used as a rodent model for ethanol sensitivity. In this study, we have used complementary DNA (cDNA) array hybridization methodology to identify genes that are differentially expressed between the brains of ILS and ISS mice. To carry out this analysis, we used both the gene discovery array (GDA) and the Mouse GEM 1 Microarray. GDA consists of 18,378 nonredundant mouse cDNA clones on a single nylon filter. Complex probes were prepared from total brain mRNA of ILS or ISS mice by using reverse transcription and 33P labeling. The labeled probes were hybridized in parallel to the gene array filters. Data from GDA experiments were analyzed with SQL-Plus and Oracle 8. The GEM microarray includes 8,730 sequence-verified clones on a glass chip. Two fluorescently labeled probes were used to hybridize a microarray simultaneously. Data from GEM experiments were analyzed by using the GEMTools software package (Incyte). Differentially expressed genes identified from each method were confirmed by relative quantitative reverse transcription-polymerase chain reaction (RT-PCR). A total of 41 genes or expressed sequence tags (ESTs) display significant expression level differences between brains of ILS and ISS mice after GDA, GEM1 hybridization, and quantitative RT-PCR confirmation. Among them, 18 clones were expressed higher in ILS mice, and 23 clones were expressed higher in ISS mice. The individual gene or EST's function and mapping information have been analyzed. This study identified 41 genes that are differentially expressed between brains of ILS and ISS mice. Some of them may have biological relevance in mediation of phenotypic variation between ILS and ISS mice for ethanol sensitivity. This study also demonstrates that parallel gene expression comparison with high-density cDNA arrays is a rapid and

  1. Mining multi-channel EEG for its information content: An ANN-based method for a brain-computer interface

    DEFF Research Database (Denmark)

    Peters, B.O.; Pfurtscheller, G.; Flyvbjerg, H.

    1998-01-01

    . This high recognition rate makes the classifier suitable for a so-called 'Brain-Computer Interface', a system that allows one to control a computer, or another device, with ones brain waves. Our classifier Laplace filters the EEG spatially, but makes use of its entire frequency range, and automatically...

  2. A Review of EEG-Based Brain-Computer Interfaces as Access Pathways for Individuals with Severe Disabilities

    Science.gov (United States)

    Moghimi, Saba; Kushki, Azadeh; Guerguerian, Anne Marie; Chau, Tom

    2013-01-01

    Electroencephalography (EEG) is a non-invasive method for measuring brain activity and is a strong candidate for brain-computer interface (BCI) development. While BCIs can be used as a means of communication for individuals with severe disabilities, the majority of existing studies have reported BCI evaluations by able-bodied individuals.…

  3. EEG (Electroencephalogram)

    Science.gov (United States)

    ... in diagnosing brain disorders, especially epilepsy or another seizure disorder. An EEG might also be helpful for diagnosing ... Sometimes seizures are intentionally triggered in people with epilepsy during the test, but appropriate medical care is ...

  4. Cross-sensory gating in schizophrenia and autism spectrum disorder: EEG evidence for impaired brain connectivity?

    DEFF Research Database (Denmark)

    Magnée, Maurice J C M; Oranje, Bob; van Engeland, Herman

    2009-01-01

    activation, which provides crucial information about functional integrity of connections between brain areas involved in cross-sensory processing in both disorders. Thirteen high functioning adult males with ASD, 13 high functioning adult males with schizophrenia, and 16 healthy adult males participated...... with the notion that filtering deficits may be secondary to earlier sensory dysfunction. Also, atypical cross-sensory suppression was found, which implies that the cognitive impairments seen in schizophrenia may be due to deficits in the integrity of connections between brain areas involved in low-level cross-sensory......Autism spectrum disorders (ASD) and schizophrenia are both neurodevelopmental disorders that have extensively been associated with impairments in functional brain connectivity. Using a cross-sensory P50 suppression paradigm, this study investigated low-level audiovisual interactions on cortical EEG...

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

    Science.gov (United States)

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

    2015-08-01

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

  6. Parameterized entropy analysis of EEG following hypoxic-ischemic brain injury

    International Nuclear Information System (INIS)

    Tong Shanbao; Bezerianos, Anastasios; Malhotra, Amit; Zhu Yisheng; Thakor, Nitish

    2003-01-01

    In the present study Tsallis and Renyi entropy methods were used to study the electric activity of brain following hypoxic-ischemic (HI) injury. We investigated the performances of these parameterized information measures in describing the electroencephalogram (EEG) signal of controlled experimental animal HI injury. The results show that (a): compared with Shannon and Renyi entropy, the parameterized Tsallis entropy acts like a spatial filter and the information rate can either tune to long range rhythms or to short abrupt changes, such as bursts or spikes during the beginning of recovery, by the entropic index q; (b): Renyi entropy is a compact and predictive indicator for monitoring the physiological changes during the recovery of brain injury. There is a reduction in the Renyi entropy after brain injury followed by a gradual recovery upon resuscitation

  7. Confused or not Confused?: Disentangling Brain Activity from EEG Data Using Bidirectional LSTM Recurrent Neural Networks.

    Science.gov (United States)

    Ni, Zhaoheng; Yuksel, Ahmet Cem; Ni, Xiuyan; Mandel, Michael I; Xie, Lei

    2017-08-01

    Brain fog, also known as confusion, is one of the main reasons for low performance in the learning process or any kind of daily task that involves and requires thinking. Detecting confusion in a human's mind in real time is a challenging and important task that can be applied to online education, driver fatigue detection and so on. In this paper, we apply Bidirectional LSTM Recurrent Neural Networks to classify students' confusion in watching online course videos from EEG data. The results show that Bidirectional LSTM model achieves the state-of-the-art performance compared with other machine learning approaches, and shows strong robustness as evaluated by cross-validation. We can predict whether or not a student is confused in the accuracy of 73.3%. Furthermore, we find the most important feature to detecting the brain confusion is the gamma 1 wave of EEG signal. Our results suggest that machine learning is a potentially powerful tool to model and understand brain activity.

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

    Science.gov (United States)

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

    2017-01-01

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

  9. Simple adaptive sparse representation based classification schemes for EEG based brain-computer interface applications.

    Science.gov (United States)

    Shin, Younghak; Lee, Seungchan; Ahn, Minkyu; Cho, Hohyun; Jun, Sung Chan; Lee, Heung-No

    2015-11-01

    One of the main problems related to electroencephalogram (EEG) based brain-computer interface (BCI) systems is the non-stationarity of the underlying EEG signals. This results in the deterioration of the classification performance during experimental sessions. Therefore, adaptive classification techniques are required for EEG based BCI applications. In this paper, we propose simple adaptive sparse representation based classification (SRC) schemes. Supervised and unsupervised dictionary update techniques for new test data and a dictionary modification method by using the incoherence measure of the training data are investigated. The proposed methods are very simple and additional computation for the re-training of the classifier is not needed. The proposed adaptive SRC schemes are evaluated using two BCI experimental datasets. The proposed methods are assessed by comparing classification results with the conventional SRC and other adaptive classification methods. On the basis of the results, we find that the proposed adaptive schemes show relatively improved classification accuracy as compared to conventional methods without requiring additional computation. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Hybrid EEG-fNIRS Asynchronous Brain-Computer Interface for Multiple Motor Tasks.

    Directory of Open Access Journals (Sweden)

    Alessio Paolo Buccino

    Full Text Available Non-invasive Brain-Computer Interfaces (BCI have demonstrated great promise for neuroprosthetics and assistive devices. Here we aim to investigate methods to combine Electroencephalography (EEG and functional Near-Infrared Spectroscopy (fNIRS in an asynchronous Sensory Motor rhythm (SMR-based BCI. We attempted to classify 4 different executed movements, namely, Right-Arm-Left-Arm-Right-Hand-Left-Hand tasks. Previous studies demonstrated the benefit of EEG-fNIRS combination. However, since normally fNIRS hemodynamic response shows a long delay, we investigated new features, involving slope indicators, in order to immediately detect changes in the signals. Moreover, Common Spatial Patterns (CSPs have been applied to both EEG and fNIRS signals. 15 healthy subjects took part in the experiments and since 25 trials per class were available, CSPs have been regularized with information from the entire population of participants and optimized using genetic algorithms. The different features have been compared in terms of performance and the dynamic accuracy over trials shows that the introduced methods diminish the fNIRS delay in the detection of changes.

  11. Transcranial electrical currents to probe EEG brain rhythms and memory consolidation during sleep in humans.

    Directory of Open Access Journals (Sweden)

    Lisa Marshall

    Full Text Available Previously the application of a weak electric anodal current oscillating with a frequency of the sleep slow oscillation (∼0.75 Hz during non-rapid eye movement sleep (NonREM sleep boosted endogenous slow oscillation activity and enhanced sleep-associated memory consolidation. The slow oscillations occurring during NonREM sleep and theta oscillations present during REM sleep have been considered of critical relevance for memory formation. Here transcranial direct current stimulation (tDCS oscillating at 5 Hz, i.e., within the theta frequency range (theta-tDCS is applied during NonREM and REM sleep. Theta-tDCS during NonREM sleep produced a global decrease in slow oscillatory activity conjoint with a local reduction of frontal slow EEG spindle power (8-12 Hz and a decrement in consolidation of declarative memory, underlining the relevance of these cortical oscillations for sleep-dependent memory consolidation. In contrast, during REM sleep theta-tDCS appears to increase global gamma (25-45 Hz activity, indicating a clear brain state-dependency of theta-tDCS. More generally, results demonstrate the suitability of oscillating-tDCS as a tool to analyze functions of endogenous EEG rhythms and underlying endogenous electric fields as well as the interactions between EEG rhythms of different frequencies.

  12. Modeling epileptic brain states using EEG spectral analysis and topographic mapping.

    Science.gov (United States)

    Direito, Bruno; Teixeira, César; Ribeiro, Bernardete; Castelo-Branco, Miguel; Sales, Francisco; Dourado, António

    2012-09-30

    Changes in the spatio-temporal behavior of the brain electrical activity are believed to be associated to epileptic brain states. We propose a novel methodology to identify the different states of the epileptic brain, based on the topographic mapping of the time varying relative power of delta, theta, alpha, beta and gamma frequency sub-bands, estimated from EEG. Using normalized-cuts segmentation algorithm, points of interest are identified in the topographic mappings and their trajectories over time are used for finding out relations with epileptogenic propagations in the brain. These trajectories are used to train a Hidden Markov Model (HMM), which models the different epileptic brain states and the transition among them. Applied to 10 patients suffering from focal seizures, with a total of 30 seizures over 497.3h of data, the methodology shows good results (an average point-by-point accuracy of 89.31%) for the identification of the four brain states--interictal, preictal, ictal and postictal. The results suggest that the spatio-temporal dynamics captured by the proposed methodology are related to the epileptic brain states and transitions involved in focal seizures. Copyright © 2012 Elsevier B.V. All rights reserved.

  13. Postnatal development of EEG patterns, catecholamine contents and myelination, and effect of hyperthyroidism in Suncus brain.

    Science.gov (United States)

    Takeuchi, T; Sitizyo, K; Harada, E

    1998-03-01

    The postnatal development of the central nervous system (CNS) in house musk shrew in the early stage of maturation was studied. The electroencephalogram (EEG) and visual evoked potential (VEP) in association with catecholamine contents and myelin basic protein (MBP) immunoreactivity were carried out from the 1st to the 20th day of postnatal age. Different EEG patterns which were specific to behavioral states (awake and drowsy) were first recorded on the 5th day, and the total power which was obtained by power spectrum analysis increased after this stage. The latencies of all peaks in VEP markedly shortened between the 5th and the 7th day. Noradrenalin (NA) content of the brain showed a slight increase after the 3rd day, and reached maximum levels on the 7th day, which was delayed a few days compared to dopamine (DA). In hyperthyroidism, the peak latency of VEP was shortened and biosynthesis of NA in cerebral cortex and DA in hippocampus was accelerated. The most obvious change in MBP-immunoreactivity of the telencephalon occurred from the 7th to the 10th day. These morphological changes in the brain advanced at the identical time-course to those in the electrophysiological development and increment of DA and NA contents.

  14. Brain-computer interface on the basis of EEG system Encephalan

    Science.gov (United States)

    Maksimenko, Vladimir; Badarin, Artem; Nedaivozov, Vladimir; Kirsanov, Daniil; Hramov, Alexander

    2018-04-01

    We have proposed brain-computer interface (BCI) for the estimation of the brain response on the presented visual tasks. Proposed BCI is based on the EEG recorder Encephalan-EEGR-19/26 (Medicom MTD, Russia) supplemented by a special home-made developed acquisition software. BCI is tested during experimental session while subject is perceiving the bistable visual stimuli and classifying them according to the interpretation. We have subjected the participant to the different external conditions and observed the significant decrease in the response, associated with the perceiving the bistable visual stimuli, during the presence of distraction. Based on the obtained results we have proposed possibility to use of BCI for estimation of the human alertness during solving the tasks required substantial visual attention.

  15. A New Generation of Brain-Computer Interfaces Driven by Discovery of Latent EEG-fMRI Linkages Using Tensor Decomposition

    OpenAIRE

    Gopikrishna Deshpande; Gopikrishna Deshpande; Gopikrishna Deshpande; D. Rangaprakash; D. Rangaprakash; Luke Oeding; Andrzej Cichocki; Andrzej Cichocki; Andrzej Cichocki; Xiaoping P. Hu

    2017-01-01

    A Brain-Computer Interface (BCI) is a setup permitting the control of external devices by decoding brain activity. Electroencephalography (EEG) has been extensively used for decoding brain activity since it is non-invasive, cheap, portable, and has high temporal resolution to allow real-time operation. Due to its poor spatial specificity, BCIs based on EEG can require extensive training and multiple trials to decode brain activity (consequently slowing down the operation of the BCI). On the o...

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

    Science.gov (United States)

    Zhavoronkova, L A

    2007-01-01

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

  17. The brain as a distributed intelligent processing system: an EEG study.

    Science.gov (United States)

    da Rocha, Armando Freitas; Rocha, Fábio Theoto; Massad, Eduardo

    2011-03-15

    Various neuroimaging studies, both structural and functional, have provided support for the proposal that a distributed brain network is likely to be the neural basis of intelligence. The theory of Distributed Intelligent Processing Systems (DIPS), first developed in the field of Artificial Intelligence, was proposed to adequately model distributed neural intelligent processing. In addition, the neural efficiency hypothesis suggests that individuals with higher intelligence display more focused cortical activation during cognitive performance, resulting in lower total brain activation when compared with individuals who have lower intelligence. This may be understood as a property of the DIPS. In our study, a new EEG brain mapping technique, based on the neural efficiency hypothesis and the notion of the brain as a Distributed Intelligence Processing System, was used to investigate the correlations between IQ evaluated with WAIS (Wechsler Adult Intelligence Scale) and WISC (Wechsler Intelligence Scale for Children), and the brain activity associated with visual and verbal processing, in order to test the validity of a distributed neural basis for intelligence. The present results support these claims and the neural efficiency hypothesis.

  18. The brain as a distributed intelligent processing system: an EEG study.

    Directory of Open Access Journals (Sweden)

    Armando Freitas da Rocha

    Full Text Available BACKGROUND: Various neuroimaging studies, both structural and functional, have provided support for the proposal that a distributed brain network is likely to be the neural basis of intelligence. The theory of Distributed Intelligent Processing Systems (DIPS, first developed in the field of Artificial Intelligence, was proposed to adequately model distributed neural intelligent processing. In addition, the neural efficiency hypothesis suggests that individuals with higher intelligence display more focused cortical activation during cognitive performance, resulting in lower total brain activation when compared with individuals who have lower intelligence. This may be understood as a property of the DIPS. METHODOLOGY AND PRINCIPAL FINDINGS: In our study, a new EEG brain mapping technique, based on the neural efficiency hypothesis and the notion of the brain as a Distributed Intelligence Processing System, was used to investigate the correlations between IQ evaluated with WAIS (Wechsler Adult Intelligence Scale and WISC (Wechsler Intelligence Scale for Children, and the brain activity associated with visual and verbal processing, in order to test the validity of a distributed neural basis for intelligence. CONCLUSION: The present results support these claims and the neural efficiency hypothesis.

  19. The Brain as a Distributed Intelligent Processing System: An EEG Study

    Science.gov (United States)

    da Rocha, Armando Freitas; Rocha, Fábio Theoto; Massad, Eduardo

    2011-01-01

    Background Various neuroimaging studies, both structural and functional, have provided support for the proposal that a distributed brain network is likely to be the neural basis of intelligence. The theory of Distributed Intelligent Processing Systems (DIPS), first developed in the field of Artificial Intelligence, was proposed to adequately model distributed neural intelligent processing. In addition, the neural efficiency hypothesis suggests that individuals with higher intelligence display more focused cortical activation during cognitive performance, resulting in lower total brain activation when compared with individuals who have lower intelligence. This may be understood as a property of the DIPS. Methodology and Principal Findings In our study, a new EEG brain mapping technique, based on the neural efficiency hypothesis and the notion of the brain as a Distributed Intelligence Processing System, was used to investigate the correlations between IQ evaluated with WAIS (Whechsler Adult Intelligence Scale) and WISC (Wechsler Intelligence Scale for Children), and the brain activity associated with visual and verbal processing, in order to test the validity of a distributed neural basis for intelligence. Conclusion The present results support these claims and the neural efficiency hypothesis. PMID:21423657

  20. Gender effect in human brain responses to bottom-up and top-down attention using the EEG 3D-Vector Field Tomography.

    Science.gov (United States)

    Kosmidou, Vasiliki E; Adam, Aikaterini; Papadaniil, Chrysa D; Tsolaki, Magda; Hadjileontiadis, Leontios J; Kompatsiaris, Ioannis

    2015-01-01

    The effect of gender in rapidly allocating attention to objects, features or locations, as reflected in brain activity, is examined in this study. A visual-attention task, consisting of bottom-up (visual pop-out) and top-down (visual search) conditions during stimuli of four triangles, i.e., a target and three distractors, was engaged. In pop-out condition, both color and orientation of the distractors differed from target, while in search condition they differed only in orientation. During the task, high-density EEG (256 channels) data were recorded and analyzed by means of behavioral, event-related potentials, i.e., the P300 component and brain source localization analysis using 3D-Vector Field Tomography (3D-VFT). Twenty subjects (half female; 32±4.7 years old) participated in the experiments, performing 60 trials for each condition. Behavioral analysis revealed that both female and male outperformed in the pop-out condition compared to the search one, with respect to accuracy and reaction time, whereas no gender-related statistical significant differences were found. Nevertheless, in the search condition, higher P300 amplitudes were detected for females compared to males (p left inferior frontal and superior temporal gyri, whereas in males it was found in the right inferior frontal and superior temporal gyri. Overall, the experimental results show that visual attention depends on contributions from different brain lateralization linked to gender, posing important implications in studying developmental disorders, characterized by gender differences.

  1. Interhemispheric EEG differences in olfactory bulbectomized rats with different cognitive abilities and brain beta-amyloid levels.

    Science.gov (United States)

    Bobkova, Natalia; Vorobyov, Vasily; Medvinskaya, Natalia; Aleksandrova, Irina; Nesterova, Inna

    2008-09-26

    Alterations in electroencephalogram (EEG) asymmetry and deficits in interhemispheric integration of information have been shown in patients with Alzheimer's disease (AD). However, no direct evidence of an association between EEG asymmetry, morphological markers in the brain, and cognition was found either in AD patients or in AD models. In this study we used rats with bilateral olfactory bulbectomy (OBX) as one of the AD models and measured their learning/memory abilities, brain beta-amyloid levels and EEG spectra in symmetrical frontal and occipital cortices. One year after OBX or sham-surgery, the rats were tested with the Morris water paradigm and assigned to three groups: sham-operated rats, SO, and OBX rats with virtually normal, OBX(+), or abnormal, OBX(-), learning (memory) abilities. In OBX vs. SO, the theta EEG activity was enhanced to a higher extent in the right frontal cortex and in the left occipital cortex. This produced significant interhemispheric differences in the frontal cortex of the OBX(-) rats and in the occipital cortex of both OBX groups. The beta1 EEG asymmetry in SO was attenuated in OBX(+) and completely eliminated in OBX(-). OBX produced highly significant beta2 EEG decline in the right frontal cortex, with OBX(-)>OBX(+) rank order of strength. The beta-amyloid level, examined by post-mortem immunological DOT-analysis in the cortex-hippocampus samples, was about six-fold higher in OBX(-) than in SO, but significantly less (enhanced by 82% vs. SO) in OBX(+) than in OBX(-). The involvement of the brain mediatory systems in the observed EEG asymmetry differences is discussed.

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

    Science.gov (United States)

    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.

  3. EEG Analysis of the Brain Activity during the Observation of Commercial, Political, or Public Service Announcements

    Directory of Open Access Journals (Sweden)

    Giovanni Vecchiato

    2010-01-01

    Full Text Available The use of modern brain imaging techniques could be useful to understand what brain areas are involved in the observation of video clips related to commercial advertising, as well as for the support of political campaigns, and also the areas of Public Service Announcements (PSAs. In this paper we describe the capability of tracking brain activity during the observation of commercials, political spots, and PSAs with advanced high-resolution EEG statistical techniques in time and frequency domains in a group of normal subjects. We analyzed the statistically significant cortical spectral power activity in different frequency bands during the observation of a commercial video clip related to the use of a beer in a group of 13 normal subjects. In addition, a TV speech of the Prime Minister of Italy was analyzed in two groups of swing and “supporter” voters. Results suggested that the cortical activity during the observation of commercial spots could vary consistently across the spot. This fact suggest the possibility to remove the parts of the spot that are not particularly attractive by using those cerebral indexes. The cortical activity during the observation of the political speech indicated a major cortical activity in the supporters group when compared to the swing voters. In this case, it is possible to conclude that the communication proposed has failed to raise attention or interest on swing voters. In conclusions, high-resolution EEG statistical techniques have been proved to able to generate useful insights about the particular fruition of TV messages, related to both commercial as well as political fields.

  4. EEG analysis of the brain activity during the observation of commercial, political, or public service announcements.

    Science.gov (United States)

    Vecchiato, Giovanni; Astolfi, Laura; Tabarrini, Alessandro; Salinari, Serenella; Mattia, Donatella; Cincotti, Febo; Bianchi, Luigi; Sorrentino, Domenica; Aloise, Fabio; Soranzo, Ramon; Babiloni, Fabio

    2010-01-01

    The use of modern brain imaging techniques could be useful to understand what brain areas are involved in the observation of video clips related to commercial advertising, as well as for the support of political campaigns, and also the areas of Public Service Announcements (PSAs). In this paper we describe the capability of tracking brain activity during the observation of commercials, political spots, and PSAs with advanced high-resolution EEG statistical techniques in time and frequency domains in a group of normal subjects. We analyzed the statistically significant cortical spectral power activity in different frequency bands during the observation of a commercial video clip related to the use of a beer in a group of 13 normal subjects. In addition, a TV speech of the Prime Minister of Italy was analyzed in two groups of swing and "supporter" voters. Results suggested that the cortical activity during the observation of commercial spots could vary consistently across the spot. This fact suggest the possibility to remove the parts of the spot that are not particularly attractive by using those cerebral indexes. The cortical activity during the observation of the political speech indicated a major cortical activity in the supporters group when compared to the swing voters. In this case, it is possible to conclude that the communication proposed has failed to raise attention or interest on swing voters. In conclusions, high-resolution EEG statistical techniques have been proved to able to generate useful insights about the particular fruition of TV messages, related to both commercial as well as political fields.

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

    Science.gov (United States)

    Henz, Diana; Schöllhorn, Wolfgang I

    2017-01-01

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

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

    Science.gov (United States)

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

    2018-03-01

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

  7. New KF-PP-SVM classification method for EEG in brain-computer interfaces.

    Science.gov (United States)

    Yang, Banghua; Han, Zhijun; Zan, Peng; Wang, Qian

    2014-01-01

    Classification methods are a crucial direction in the current study of brain-computer interfaces (BCIs). To improve the classification accuracy for electroencephalogram (EEG) signals, a novel KF-PP-SVM (kernel fisher, posterior probability, and support vector machine) classification method is developed. Its detailed process entails the use of common spatial patterns to obtain features, based on which the within-class scatter is calculated. Then the scatter is added into the kernel function of a radial basis function to construct a new kernel function. This new kernel is integrated into the SVM to obtain a new classification model. Finally, the output of SVM is calculated based on posterior probability and the final recognition result is obtained. To evaluate the effectiveness of the proposed KF-PP-SVM method, EEG data collected from laboratory are processed with four different classification schemes (KF-PP-SVM, KF-SVM, PP-SVM, and SVM). The results showed that the overall average improvements arising from the use of the KF-PP-SVM scheme as opposed to KF-SVM, PP-SVM and SVM schemes are 2.49%, 5.83 % and 6.49 % respectively.

  8. Evaluation of different EEG acquisition systems concerning their suitability for building a brain-computer interface

    Directory of Open Access Journals (Sweden)

    Andreas Pinegger

    2016-09-01

    Full Text Available One important aspect in non-invasive brain-computer interface (BCI research is to acquire the electroencephalogram (EEG in a proper way. From an end-user perspective this means with maximum comfort and without any extra inconveniences (e.g., washing the hair. Whereas from a technical perspective, the signal quality has to be optimal to make the BCI work effectively and efficiently.In this work we evaluated three different commercially available EEG acquisition systems that differ in the type of electrode (gel-, water-, and dry-based, the amplifier technique, and the data transmission method. Every system was tested regarding three different aspects, namely, technical, BCI effectiveness and efficiency (P300 communication and control, and user satisfaction (comfort.We found that the water-based system had the lowest short circuit noise level, the hydrogel-based system had the highest P300 spelling accuracies, and the dry electrode system caused the least inconveniences.Therefore, building a reliable BCI is possible with all evaluated systems and it is on the user to decide which system meets the given requirements best.

  9. Measuring brain activity cycling (BAC) in long term EEG monitoring of preterm babies

    International Nuclear Information System (INIS)

    Stevenson, Nathan J; Palmu, Kirsi; Wikström, Sverre; Hellström-Westas, Lena; Vanhatalo, Sampsa

    2014-01-01

    Measuring fluctuation of vigilance states in early preterm infants undergoing long term intensive care holds promise for monitoring their neurological well-being. There is currently, however, neither objective nor quantitative methods available for this purpose in a research or clinical environment. The aim of this proof-of-concept study was, therefore, to develop quantitative measures of the fluctuation in vigilance states or brain activity cycling (BAC) in early preterm infants. The proposed measures of BAC were summary statistics computed on a frequency domain representation of the proportional duration of spontaneous activity transients (SAT%) calculated from electroencephalograph (EEG) recordings. Eighteen combinations of three statistics and six frequency domain representations were compared to a visual interpretation of cycling in the SAT% signal. Three high performing measures (band energy/periodogram: R = 0.809, relative band energy/nonstationary frequency marginal: R = 0.711, g-statistic/nonstationary frequency marginal: R = 0.638) were then compared to a grading of sleep wake cycling based on the visual interpretation of the amplitude-integrated EEG trend. These measures of BAC are conceptually straightforward, correlate well with the visual scores of BAC and sleep wake cycling, are robust enough to cope with the technically compromised monitoring data available in intensive care units, and are recommended for further validation in prospective studies. (paper)

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

    Science.gov (United States)

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

    2011-05-01

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

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

    Science.gov (United States)

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

    2018-05-22

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

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

    Directory of Open Access Journals (Sweden)

    Gaoxing Zheng

    2018-03-01

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

  13. Joint Time-Frequency-Space Classification of EEG in a Brain-Computer Interface Application

    Directory of Open Access Journals (Sweden)

    Molina Gary N Garcia

    2003-01-01

    Full Text Available Brain-computer interface is a growing field of interest in human-computer interaction with diverse applications ranging from medicine to entertainment. In this paper, we present a system which allows for classification of mental tasks based on a joint time-frequency-space decorrelation, in which mental tasks are measured via electroencephalogram (EEG signals. The efficiency of this approach was evaluated by means of real-time experimentations on two subjects performing three different mental tasks. To do so, a number of protocols for visualization, as well as training with and without feedback, were also developed. Obtained results show that it is possible to obtain good classification of simple mental tasks, in view of command and control, after a relatively small amount of training, with accuracies around 80%, and in real time.

  14. Application of a brain-computer interface for person authentication using EEG responses to photo stimuli.

    Science.gov (United States)

    Mu, Zhendong; Yin, Jinhai; Hu, Jianfeng

    2018-01-01

    In this paper, a person authentication system that can effectively identify individuals by generating unique electroencephalogram signal features in response to self-face and non-self-face photos is presented. In order to achieve a good stability performance, the sequence of self-face photo including first-occurrence position and non-first-occurrence position are taken into account in the serial occurrence of visual stimuli. In addition, a Fisher linear classification method and event-related potential technique for feature analysis is adapted to yield remarkably better outcomes than that by most of the existing methods in the field. The results have shown that the EEG-based person authentications via brain-computer interface can be considered as a suitable approach for biometric authentication system.

  15. 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.

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

    Science.gov (United States)

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

    2016-08-04

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

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

    Science.gov (United States)

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

    2014-01-01

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

  18. The Track of Brain Activity during the Observation of TV Commercials with the High-Resolution EEG Technology

    Directory of Open Access Journals (Sweden)

    Laura Astolfi

    2009-01-01

    Full Text Available We estimate cortical activity in normal subjects during the observation of TV commercials inserted within a movie by using high-resolution EEG techniques. The brain activity was evaluated in both time and frequency domains by solving the associate inverse problem of EEG with the use of realistic head models. In particular, we recover statistically significant information about cortical areas engaged by particular scenes inserted within the TV commercial proposed with respect to the brain activity estimated while watching a documentary. Results obtained in the population investigated suggest that the statistically significant brain activity during the observation of the TV commercial was mainly concentrated in frontoparietal cortical areas, roughly coincident with the Brodmann areas 8, 9, and 7, in the analyzed population.

  19. Multi-Variate EEG Analysis as a Novel Tool to Examine Brain Responses to Naturalistic Music Stimuli.

    Directory of Open Access Journals (Sweden)

    Irene Sturm

    Full Text Available Note onsets in music are acoustic landmarks providing auditory cues that underlie the perception of more complex phenomena such as beat, rhythm, and meter. For naturalistic ongoing sounds a detailed view on the neural representation of onset structure is hard to obtain, since, typically, stimulus-related EEG signatures are derived by averaging a high number of identical stimulus presentations. Here, we propose a novel multivariate regression-based method extracting onset-related brain responses from the ongoing EEG. We analyse EEG recordings of nine subjects who passively listened to stimuli from various sound categories encompassing simple tone sequences, full-length romantic piano pieces and natural (non-music soundscapes. The regression approach reduces the 61-channel EEG to one time course optimally reflecting note onsets. The neural signatures derived by this procedure indeed resemble canonical onset-related ERPs, such as the N1-P2 complex. This EEG projection was then utilized to determine the Cortico-Acoustic Correlation (CACor, a measure of synchronization between EEG signal and stimulus. We demonstrate that a significant CACor (i can be detected in an individual listener's EEG of a single presentation of a full-length complex naturalistic music stimulus, and (ii it co-varies with the stimuli's average magnitudes of sharpness, spectral centroid, and rhythmic complexity. In particular, the subset of stimuli eliciting a strong CACor also produces strongly coordinated tension ratings obtained from an independent listener group in a separate behavioral experiment. Thus musical features that lead to a marked physiological reflection of tone onsets also contribute to perceived tension in music.

  20. High density dispersion fuel

    International Nuclear Information System (INIS)

    Hofman, G.L.

    1996-01-01

    A fuel development campaign that results in an aluminum plate-type fuel of unlimited LEU burnup capability with an uranium loading of 9 grams per cm 3 of meat should be considered an unqualified success. The current worldwide approved and accepted highest loading is 4.8 g cm -3 with U 3 Si 2 as fuel. High-density uranium compounds offer no real density advantage over U 3 Si 2 and have less desirable fabrication and performance characteristics as well. Of the higher-density compounds, U 3 Si has approximately a 30% higher uranium density but the density of the U 6 X compounds would yield the factor 1.5 needed to achieve 9 g cm -3 uranium loading. Unfortunately, irradiation tests proved these peritectic compounds have poor swelling behavior. It is for this reason that the authors are turning to uranium alloys. The reason pure uranium was not seriously considered as a dispersion fuel is mainly due to its high rate of growth and swelling at low temperatures. This problem was solved at least for relatively low burnup application in non-dispersion fuel elements with small additions of Si, Fe, and Al. This so called adjusted uranium has nearly the same density as pure α-uranium and it seems prudent to reconsider this alloy as a dispersant. Further modifications of uranium metal to achieve higher burnup swelling stability involve stabilization of the cubic γ phase at low temperatures where normally α phase exists. Several low neutron capture cross section elements such as Zr, Nb, Ti and Mo accomplish this in various degrees. The challenge is to produce a suitable form of fuel powder and develop a plate fabrication procedure, as well as obtain high burnup capability through irradiation testing

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

    Directory of Open Access Journals (Sweden)

    Christian O'Reilly

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

  2. A hybrid NIRS-EEG system for self-paced brain computer interface with online motor imagery.

    Science.gov (United States)

    Koo, Bonkon; Lee, Hwan-Gon; Nam, Yunjun; Kang, Hyohyeong; Koh, Chin Su; Shin, Hyung-Cheul; Choi, Seungjin

    2015-04-15

    For a self-paced motor imagery based brain-computer interface (BCI), the system should be able to recognize the occurrence of a motor imagery, as well as the type of the motor imagery. However, because of the difficulty of detecting the occurrence of a motor imagery, general motor imagery based BCI studies have been focusing on the cued motor imagery paradigm. In this paper, we present a novel hybrid BCI system that uses near infrared spectroscopy (NIRS) and electroencephalography (EEG) systems together to achieve online self-paced motor imagery based BCI. We designed a unique sensor frame that records NIRS and EEG simultaneously for the realization of our system. Based on this hybrid system, we proposed a novel analysis method that detects the occurrence of a motor imagery with the NIRS system, and classifies its type with the EEG system. An online experiment demonstrated that our hybrid system had a true positive rate of about 88%, a false positive rate of 7% with an average response time of 10.36 s. As far as we know, there is no report that explored hemodynamic brain switch for self-paced motor imagery based BCI with hybrid EEG and NIRS system. From our experimental results, our hybrid system showed enough reliability for using in a practical self-paced motor imagery based BCI. Copyright © 2014 Elsevier B.V. All rights reserved.

  3. Gaming control using a wearable and wireless EEG-based brain-computer interface device with novel dry foam-based sensors

    Science.gov (United States)

    2012-01-01

    A brain-computer interface (BCI) is a communication system that can help users interact with the outside environment by translating brain signals into machine commands. The use of electroencephalographic (EEG) signals has become the most common approach for a BCI because of their usability and strong reliability. Many EEG-based BCI devices have been developed with traditional wet- or micro-electro-mechanical-system (MEMS)-type EEG sensors. However, those traditional sensors have uncomfortable disadvantage and require conductive gel and skin preparation on the part of the user. Therefore, acquiring the EEG signals in a comfortable and convenient manner is an important factor that should be incorporated into a novel BCI device. In the present study, a wearable, wireless and portable EEG-based BCI device with dry foam-based EEG sensors was developed and was demonstrated using a gaming control application. The dry EEG sensors operated without conductive gel; however, they were able to provide good conductivity and were able to acquire EEG signals effectively by adapting to irregular skin surfaces and by maintaining proper skin-sensor impedance on the forehead site. We have also demonstrated a real-time cognitive stage detection application of gaming control using the proposed portable device. The results of the present study indicate that using this portable EEG-based BCI device to conveniently and effectively control the outside world provides an approach for researching rehabilitation engineering. PMID:22284235

  4. Estimating the Integrated Information Measure Phi from High-Density Electroencephalography during States of Consciousness in Humans.

    Science.gov (United States)

    Kim, Hyoungkyu; Hudetz, Anthony G; Lee, Joseph; Mashour, George A; Lee, UnCheol

    2018-01-01

    The integrated information theory (IIT) proposes a quantitative measure, denoted as Φ, of the amount of integrated information in a physical system, which is postulated to have an identity relationship with consciousness. IIT predicts that the value of Φ estimated from brain activities represents the level of consciousness across phylogeny and functional states. Practical limitations, such as the explosive computational demands required to estimate Φ for real systems, have hindered its application to the brain and raised questions about the utility of IIT in general. To achieve practical relevance for studying the human brain, it will be beneficial to establish the reliable estimation of Φ from multichannel electroencephalogram (EEG) and define the relationship of Φ to EEG properties conventionally used to define states of consciousness. In this study, we introduce a practical method to estimate Φ from high-density (128-channel) EEG and determine the contribution of each channel to Φ. We examine the correlation of power, frequency, functional connectivity, and modularity of EEG with regional Φ in various states of consciousness as modulated by diverse anesthetics. We find that our approximation of Φ alone is insufficient to discriminate certain states of anesthesia. However, a multi-dimensional parameter space extended by four parameters related to Φ and EEG connectivity is able to differentiate all states of consciousness. The association of Φ with EEG connectivity during clinically defined anesthetic states represents a new practical approach to the application of IIT, which may be used to characterize various physiological (sleep), pharmacological (anesthesia), and pathological (coma) states of consciousness in the human brain.

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

    Science.gov (United States)

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

    2018-01-01

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

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

    Science.gov (United States)

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

    2018-01-01

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

  7. STUDI AWAL: PENGARUH GAME KEKERASAN TERHADAP AKTIVITAS OTAK ANAK MELALUI PEMETAAN SINYAL OTAK (BRAIN MAPPING MENGGUNAKAN WIRELESS EEG

    Directory of Open Access Journals (Sweden)

    Nita Handayani

    2017-06-01

    Full Text Available Brain mapping adalah pemetaan aktivitas kelistrikan otak untuk mempelajari fungsional otak manusia. Pada studi ini, brain mapping digunakan untuk mempelajari pengaruh game kekerasan terhadap aktivitas fungsional otak anak dengan menggunakan wireless EEG (electroencephalography berupa Emotiv Epoc 14-channel. Subjek penelitian ini adalah anak-anak pecandu game kekerasan (10 anak dengan rentang usia antara 12-15 tahun. Aktivitas otak pada saat bermain game akan dibandingkan dengan kondisi rileks. Waktu perekaman EEG selama 42 menit untuk setiap subjek. Dari hasil analisis spektral daya menggunakan periodogram Welch menunjukkan bahwa pada saat bermain game, frekuensi gelombang delta dan theta meningkat terutama pada area frontal (F7, F3, FC5, FC6, F4, F8, dan AF4. Spektral daya gelombang alpha mengalami penurunan sedangkan gelombang beta mengalami peningkatan pada saat bermain game. Hal ini mengindikasikan bahwa anak mengalami beban mental dan berada pada kondisi stres pada saat bermain game kekerasan.

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

    Science.gov (United States)

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

    2016-06-01

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

  9. A review of classification algorithms for EEG-based brain-computer interfaces: a 10 year update.

    Science.gov (United States)

    Lotte, F; Bougrain, L; Cichocki, A; Clerc, M; Congedo, M; Rakotomamonjy, A; Yger, F

    2018-06-01

    Most current electroencephalography (EEG)-based brain-computer interfaces (BCIs) are based on machine learning algorithms. There is a large diversity of classifier types that are used in this field, as described in our 2007 review paper. Now, approximately ten years after this review publication, many new algorithms have been developed and tested to classify EEG signals in BCIs. The time is therefore ripe for an updated review of EEG classification algorithms for BCIs. We surveyed the BCI and machine learning literature from 2007 to 2017 to identify the new classification approaches that have been investigated to design BCIs. We synthesize these studies in order to present such algorithms, to report how they were used for BCIs, what were the outcomes, and to identify their pros and cons. We found that the recently designed classification algorithms for EEG-based BCIs can be divided into four main categories: adaptive classifiers, matrix and tensor classifiers, transfer learning and deep learning, plus a few other miscellaneous classifiers. Among these, adaptive classifiers were demonstrated to be generally superior to static ones, even with unsupervised adaptation. Transfer learning can also prove useful although the benefits of transfer learning remain unpredictable. Riemannian geometry-based methods have reached state-of-the-art performances on multiple BCI problems and deserve to be explored more thoroughly, along with tensor-based methods. Shrinkage linear discriminant analysis and random forests also appear particularly useful for small training samples settings. On the other hand, deep learning methods have not yet shown convincing improvement over state-of-the-art BCI methods. This paper provides a comprehensive overview of the modern classification algorithms used in EEG-based BCIs, presents the principles of these methods and guidelines on when and how to use them. It also identifies a number of challenges to further advance EEG classification in BCI.

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

    OpenAIRE

    Blum, Sarah; 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 sma...

  11. A hybrid brain-machine interface based on EEG and EMG activity for the motor rehabilitation of stroke patients.

    Science.gov (United States)

    Sarasola-Sanz, Andrea; Irastorza-Landa, Nerea; Lopez-Larraz, Eduardo; Bibian, Carlos; Helmhold, Florian; Broetz, Doris; Birbaumer, Niels; Ramos-Murguialday, Ander

    2017-07-01

    Including supplementary information from the brain or other body parts in the control of brain-machine interfaces (BMIs) has been recently proposed and investigated. Such enriched interfaces are referred to as hybrid BMIs (hBMIs) and have been proven to be more robust and accurate than regular BMIs for assistive and rehabilitative applications. Electromyographic (EMG) activity is one of the most widely utilized biosignals in hBMIs, as it provides a quite direct measurement of the motion intention of the user. Whereas most of the existing non-invasive EEG-EMG-hBMIs have only been subjected to offline testings or are limited to one degree of freedom (DoF), we present an EEG-EMG-hBMI that allows the simultaneous control of 7-DoFs of the upper limb with a robotic exoskeleton. Moreover, it establishes a biologically-inspired hierarchical control flow, requiring the active participation of central and peripheral structures of the nervous system. Contingent visual and proprioceptive feedback about the user's EEG and EMG activity is provided in the form of velocity modulation during functional task training. We believe that training with this closed-loop system may facilitate functional neuroplastic processes and eventually elicit a joint brain and muscle motor rehabilitation. Its usability is validated during a real-time operation session in a healthy participant and a chronic stroke patient, showing encouraging results for its application to a clinical rehabilitation scenario.

  12. An Intracranial Electroencephalography (iEEG Brain Function Mapping Tool with an Application to Epilepsy Surgery Evaluation

    Directory of Open Access Journals (Sweden)

    Yinghua eWang

    2016-04-01

    Full Text Available Object: Before epilepsy surgeries, intracranial electroencephalography (iEEG is often employed in function mapping and epileptogenic foci localization. Although the implanted electrodes provide crucial information for epileptogenic zone resection, a convenient clinical tool for electrode position registration and brain function mapping visualization is still lacking. In this study, we developed a Brain Function Mapping (BFM Tool, which facilitates electrode position registration and brain function mapping visualization, with an application to epilepsy surgeries.Methods: The BFM Tool mainly utilizes electrode location registration and function mapping based on pre-defined brain models from other software. In addition, the electrode node and mapping properties, such as the node size/color, edge color / thickness, mapping method, can be adjusted easily using the setting panel. Moreover, users may manually import / export location and connectivity data to generate figures for further application. The role of this software is demonstrated by a clinical study of language area localization.Results: The BFM Tool helps clinical doctors and researchers visualize implanted electrodes and brain functions in an easy, quick and flexible manner.Conclusions: Our tool provides convenient electrode registration, easy brain function visualization, and has good performance. It is clinical-oriented and is easy to deploy and use. The BFM tool is suitable for epilepsy and other clinical iEEG applications.

  13. Longitudinal Dynamics of 3-Dimensional Components of Selfhood After Severe Traumatic Brain Injury: A qEEG Case Study.

    Science.gov (United States)

    Fingelkurts, Andrew A; Fingelkurts, Alexander A

    2017-09-01

    In this report, we describe the case of a patient who sustained extremely severe traumatic brain damage with diffuse axonal injury in a traffic accident and whose recovery was monitored during 6 years. Specifically, we were interested in the recovery dynamics of 3-dimensional components of selfhood (a 3-dimensional construct model for the complex experiential selfhood has been recently proposed based on the empirical findings on the functional-topographical specialization of 3 operational modules of brain functional network responsible for the self-consciousness processing) derived from the electroencephalographic (EEG) signal. The analysis revealed progressive (though not monotonous) restoration of EEG functional connectivity of 3 modules of brain functional network responsible for the self-consciousness processing, which was also paralleled by the clinically significant functional recovery. We propose that restoration of normal integrity of the operational modules of the self-referential brain network may underlie the positive dynamics of 3 aspects of selfhood and provide a neurobiological mechanism for their recovery. The results are discussed in the context of recent experimental studies that support this inference. Studies of ongoing recovery after severe brain injury utilizing knowledge about each separate aspect of complex selfhood will likely help to develop more efficient and targeted rehabilitation programs for patients with brain trauma.

  14. Source-space EEG neurofeedback links subjective experience with brain activity during effortless awareness meditation.

    Science.gov (United States)

    van Lutterveld, Remko; Houlihan, Sean D; Pal, Prasanta; Sacchet, Matthew D; McFarlane-Blake, Cinque; Patel, Payal R; Sullivan, John S; Ossadtchi, Alex; Druker, Susan; Bauer, Clemens; Brewer, Judson A

    2017-05-01

    Meditation is increasingly showing beneficial effects for psychiatric disorders. However, learning to meditate is not straightforward as there are no easily discernible outward signs of performance and thus no direct feedback is possible. As meditation has been found to correlate with posterior cingulate cortex (PCC) activity, we tested whether source-space EEG neurofeedback from the PCC followed the subjective experience of effortless awareness (a major component of meditation), and whether participants could volitionally control the signal. Sixteen novice meditators and sixteen experienced meditators participated in the study. Novice meditators were briefly trained to perform a basic meditation practice to induce the subjective experience of effortless awareness in a progressively more challenging neurofeedback test-battery. Experienced meditators performed a self-selected meditation practice to induce this state in the same test-battery. Neurofeedback was provided based on gamma-band (40-57Hz) PCC activity extracted using a beamformer algorithm. Associations between PCC activity and the subjective experience of effortless awareness were assessed by verbal probes. Both groups reported that decreased PCC activity corresponded with effortless awareness (Pneurofeedback to link an objective measure of brain activity with the subjective experience of effortless awareness, and suggest potential utility of this paradigm as a tool for meditation training. Copyright © 2016 Elsevier Inc. All rights reserved.

  15. Evaluation of a Dry EEG System for Application of Passive Brain-Computer Interfaces in Autonomous Driving.

    Science.gov (United States)

    Zander, Thorsten O; Andreessen, Lena M; Berg, Angela; Bleuel, Maurice; Pawlitzki, Juliane; Zawallich, Lars; Krol, Laurens R; Gramann, Klaus

    2017-01-01

    We tested the applicability and signal quality of a 16 channel dry electroencephalography (EEG) system in a laboratory environment and in a car under controlled, realistic conditions. The aim of our investigation was an estimation how well a passive Brain-Computer Interface (pBCI) can work in an autonomous driving scenario. The evaluation considered speed and accuracy of self-applicability by an untrained person, quality of recorded EEG data, shifts of electrode positions on the head after driving-related movements, usability, and complexity of the system as such and wearing comfort over time. An experiment was conducted inside and outside of a stationary vehicle with running engine, air-conditioning, and muted radio. Signal quality was sufficient for standard EEG analysis in the time and frequency domain as well as for the use in pBCIs. While the influence of vehicle-induced interferences to data quality was insignificant, driving-related movements led to strong shifts in electrode positions. In general, the EEG system used allowed for a fast self-applicability of cap and electrodes. The assessed usability of the system was still acceptable while the wearing comfort decreased strongly over time due to friction and pressure to the head. From these results we conclude that the evaluated system should provide the essential requirements for an application in an autonomous driving context. Nevertheless, further refinement is suggested to reduce shifts of the system due to body movements and increase the headset's usability and wearing comfort.

  16. 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.

  17. Studies of the correlations between morphological brain changes on MRI and computerized EEG changes in schizophrenics

    International Nuclear Information System (INIS)

    Takeuchi, Kouzou

    1992-01-01

    Twenty eight schizophrenic patients, who ranged in age from 21 to 39 years with a mean of 30.2, and 21 age- and sex-matched normal volunteers were studied by magnetic resonance (MR) imaging and electroencephalography (EEG). ALl subjects were given informed consent prior to the present study. They were all right-handed. Schizophrenic patients showed a significantly larger ventricular brain ratio (VBR) on the axial and coronal planes as compared with the control. The bilateral anterior horns, left body, left posterior horn of the lateral ventricle and the third ventricle were significantly larger in schizophrenic patients than the control. The middle half of the corpus callosum was smaller in schizophrenic patients than the control. Schizophrenia was more likely associated not only with delta and theta activities in the centro-parieto-occipital regions but also with beta 1 and beta 2 activities in the front-central regions. In schizophrenic patients, however, alpha 2 activity was markedly decreased in all regions. There were significant positive correlations between the total scores for brief psychiatric rating scale (BPRS) and the areas of the left anterior and posterior horns of the lateral ventricle. The total BPRS scores positively correlated with the area of the third ventricle. In addition, positive correlations were significant between delata activity and the area of the left anterior horn of the lateral ventricle, between delta activity and the area of the third ventricle, and between beta 1 activity and the area of left posteior horn of the lateral ventricle. These results suggest that a dilated third ventricle is associated with electrophysiological brain pathology and psychopathology in schizophrenic patients. (N.K.) 76 refs

  18. Oscillatory brain correlates of live joint attention: a dual-EEG study

    Directory of Open Access Journals (Sweden)

    Fanny eLachat

    2012-06-01

    Full Text Available Joint attention consists in following another’s gaze onto an environmental object, which leads to the alignment of both subjects' attention onto this object. It is a fundamental mechanism of non-verbal communication, and it is essential for dynamic, online, interindividual synchronization during interactions. We aimed at investigating the oscillatory brain correlates of joint attention in a face-to-face paradigm where dyads of participants dynamically oriented their attention toward objects during joint and no-joint attention periods respectively. We also manipulated task instruction: in socially-driven instructions, the participants had to follow explicitly their partner’s gaze, while in color-driven instructions, the objects to be looked at were designated at by their color so that no explicit gaze following was required. We focused on oscillatory activities in the 10 Hz frequency range, where parieto-occipital alpha and the centro-parietal mu rhythms have been described, as these rhythms have been associated with attention and social coordination processes respectively. We tested the hypothesis of a modulation of these oscillatory activities by joint attention. We used dual EEG to record simultaneously the brain activities of the participant dyads during our live, face-to-face joint attention paradigm. We showed that joint attention periods – as compared to the no-joint attention periods – were associated with a decrease of signal power between 11 and 13 Hz over a large set of left centro-parieto-occipital electrodes, encompassing the scalp regions where alpha and mu rhythms have been described. This 11-13 Hz signal power decrease was observed independently of the task instruction: it was similar when joint versus no-joint attention situations were socially-driven and when they were color-driven. These results are interpreted in terms of the processes of attention mirroring, social coordination, and mutual attentiveness associated

  19. Comparative studies of '18F-FDG PET/CT brain imaging and EEG in preoperative localization of temporal lobe epileptic focus

    International Nuclear Information System (INIS)

    Chen Ziqian; Zhao Chunlei; Liu Yao; Ni Ping; Zhong Qun; Bai Wei; Peng Dexin

    2012-01-01

    Objective: To compare the value of 18 F-FDG PET/CT brain imaging and EEG in preoperative localization of the epileptic focus at the temporal lobe. Methods: A total of 152 patients (108 males, 44 females, age ranged from 3 to 59 years old) with past history of temporal lobe epilepsy were included.All patients underwent 18 F-FDG PET/CT brain imaging and long-range or video EEG, and 29 patients underwent intracranial electrode EEG due to the failure to localize the disease focus by non-invasive methods.Histopathologic findings after operative treatment were considered the gold standard for disease localization. All patients were followed up for at least six months after the operation. The accuracy of the 18 F-FDG PET/CT brain imaging and long-range or video EEG examination were compared using χ 2 test. Results: The accuracy of locating the epileptic focus was 80.92% (123/152) for 18 F-FDG PET/CT brain imaging and 43.42% (66/152) for long-range or video EEG (χ 2 =22.72, P<0.01). The accuracy of locating the epileptic focus for the 29 cases with intracranial electrode EEG was 100%. Conclusions: Interictal 18 F-FDG PET/CT brain imaging is a sensitive and effective method to locate the temporal lobe epileptic focus and is better than long-range or video EEG. The combination of 18 F-FDG PET/CT brain imaging and intracranial electrode EEG examination can further improve the accuracy of locating the epileptic focus. (authors)

  20. Preliminary study of Alzheimer's Disease diagnosis based on brain electrical signals using wireless EEG

    International Nuclear Information System (INIS)

    Handayani, N; Akbar, Y; Khotimah, S N; Haryanto, F; Arif, I; Taruno, W P

    2016-01-01

    This research aims to study brain's electrical signals recorded using EEG as a basis for the diagnosis of patients with Alzheimer's Disease (AD). The subjects consisted of patients with AD, and normal subjects are used as the control. Brain signals are recorded for 3 minutes in a relaxed condition and with eyes closed. The data is processed using power spectral analysis, brain mapping and chaos test to observe the level of complexity of EEG's data. The results show a shift in the power spectral in the low frequency band (delta and theta) in AD patients. The increase of delta and theta occurs in lobus frontal area and lobus parietal respectively. However, there is a decrease of alpha activity in AD patients where in the case of normal subjects with relaxed condition, brain alpha wave dominates the posterior area. This is confirmed by the results of brain mapping. While the results of chaos analysis show that the average value of MMLE is lower in AD patients than in normal subjects. The level of chaos associated with neural complexity in AD patients with lower neural complexity is due to neuronal damage caused by the beta amyloid plaques and tau protein in neurons. (paper)

  1. A New Generation of Brain-Computer Interfaces Driven by Discovery of Latent EEG-fMRI Linkages Using Tensor Decomposition

    Directory of Open Access Journals (Sweden)

    Gopikrishna Deshpande

    2017-06-01

    Full Text Available A Brain-Computer Interface (BCI is a setup permitting the control of external devices by decoding brain activity. Electroencephalography (EEG has been extensively used for decoding brain activity since it is non-invasive, cheap, portable, and has high temporal resolution to allow real-time operation. Due to its poor spatial specificity, BCIs based on EEG can require extensive training and multiple trials to decode brain activity (consequently slowing down the operation of the BCI. On the other hand, BCIs based on functional magnetic resonance imaging (fMRI are more accurate owing to its superior spatial resolution and sensitivity to underlying neuronal processes which are functionally localized. However, due to its relatively low temporal resolution, high cost, and lack of portability, fMRI is unlikely to be used for routine BCI. We propose a new approach for transferring the capabilities of fMRI to EEG, which includes simultaneous EEG/fMRI sessions for finding a mapping from EEG to fMRI, followed by a BCI run from only EEG data, but driven by fMRI-like features obtained from the mapping identified previously. Our novel data-driven method is likely to discover latent linkages between electrical and hemodynamic signatures of neural activity hitherto unexplored using model-driven methods, and is likely to serve as a template for a novel multi-modal strategy wherein cross-modal EEG-fMRI interactions are exploited for the operation of a unimodal EEG system, leading to a new generation of EEG-based BCIs.

  2. A New Generation of Brain-Computer Interfaces Driven by Discovery of Latent EEG-fMRI Linkages Using Tensor Decomposition.

    Science.gov (United States)

    Deshpande, Gopikrishna; Rangaprakash, D; Oeding, Luke; Cichocki, Andrzej; Hu, Xiaoping P

    2017-01-01

    A Brain-Computer Interface (BCI) is a setup permitting the control of external devices by decoding brain activity. Electroencephalography (EEG) has been extensively used for decoding brain activity since it is non-invasive, cheap, portable, and has high temporal resolution to allow real-time operation. Due to its poor spatial specificity, BCIs based on EEG can require extensive training and multiple trials to decode brain activity (consequently slowing down the operation of the BCI). On the other hand, BCIs based on functional magnetic resonance imaging (fMRI) are more accurate owing to its superior spatial resolution and sensitivity to underlying neuronal processes which are functionally localized. However, due to its relatively low temporal resolution, high cost, and lack of portability, fMRI is unlikely to be used for routine BCI. We propose a new approach for transferring the capabilities of fMRI to EEG, which includes simultaneous EEG/fMRI sessions for finding a mapping from EEG to fMRI, followed by a BCI run from only EEG data, but driven by fMRI-like features obtained from the mapping identified previously. Our novel data-driven method is likely to discover latent linkages between electrical and hemodynamic signatures of neural activity hitherto unexplored using model-driven methods, and is likely to serve as a template for a novel multi-modal strategy wherein cross-modal EEG-fMRI interactions are exploited for the operation of a unimodal EEG system, leading to a new generation of EEG-based BCIs.

  3. Hybrid brain-computer interface for biomedical cyber-physical system application using wireless embedded EEG systems.

    Science.gov (United States)

    Chai, Rifai; Naik, Ganesh R; Ling, Sai Ho; Nguyen, Hung T

    2017-01-07

    One of the key challenges of the biomedical cyber-physical system is to combine cognitive neuroscience with the integration of physical systems to assist people with disabilities. Electroencephalography (EEG) has been explored as a non-invasive method of providing assistive technology by using brain electrical signals. This paper presents a unique prototype of a hybrid brain computer interface (BCI) which senses a combination classification of mental task, steady state visual evoked potential (SSVEP) and eyes closed detection using only two EEG channels. In addition, a microcontroller based head-mounted battery-operated wireless EEG sensor combined with a separate embedded system is used to enhance portability, convenience and cost effectiveness. This experiment has been conducted with five healthy participants and five patients with tetraplegia. Generally, the results show comparable classification accuracies between healthy subjects and tetraplegia patients. For the offline artificial neural network classification for the target group of patients with tetraplegia, the hybrid BCI system combines three mental tasks, three SSVEP frequencies and eyes closed, with average classification accuracy at 74% and average information transfer rate (ITR) of the system of 27 bits/min. For the real-time testing of the intentional signal on patients with tetraplegia, the average success rate of detection is 70% and the speed of detection varies from 2 to 4 s.

  4. Combined EEG-fNIRS decoding of motor attempt and imagery for brain switch control: an offline study in patients with tetraplegia.

    Science.gov (United States)

    Blokland, Yvonne; Spyrou, Loukianos; Thijssen, Dick; Eijsvogels, Thijs; Colier, Willy; Floor-Westerdijk, Marianne; Vlek, Rutger; Bruhn, Jorgen; Farquhar, Jason

    2014-03-01

    Combining electrophysiological and hemodynamic features is a novel approach for improving current performance of brain switches based on sensorimotor rhythms (SMR). This study was conducted with a dual purpose: to test the feasibility of using a combined electroencephalogram/functional near-infrared spectroscopy (EEG-fNIRS) SMR-based brain switch in patients with tetraplegia, and to examine the performance difference between motor imagery and motor attempt for this user group. A general improvement was found when using both EEG and fNIRS features for classification as compared to using the single-modality EEG classifier, with average classification rates of 79% for attempted movement and 70% for imagined movement. For the control group, rates of 87% and 79% were obtained, respectively, where the "attempted movement" condition was replaced with "actual movement." A combined EEG-fNIRS system might be especially beneficial for users who lack sufficient control of current EEG-based brain switches. The average classification performance in the patient group for attempted movement was significantly higher than for imagined movement using the EEG-only as well as the combined classifier, arguing for the case of a paradigm shift in current brain switch research.

  5. Neural basis for brain responses to TV commercials: a high-resolution EEG study.

    Science.gov (United States)

    Astolfi, Laura; De Vico Fallani, F; Cincotti, F; Mattia, D; Bianchi, L; Marciani, M G; Salinari, S; Colosimo, A; Tocci, A; Soranzo, R; Babiloni, F

    2008-12-01

    We investigated brain activity during the observation of TV commercials by tracking the cortical activity and the functional connectivity changes in normal subjects. The aim was to elucidate if the TV commercials that were remembered by the subjects several days after their first observation elicited particular brain activity and connectivity compared with those generated during the observation of TV commercials that were quickly forgotten. High-resolution electroencephalogram (EEG) recordings were performed in a group of healthy subjects and the cortical activity during the observation of TV commercials was evaluated in several regions of interest coincident with the Brodmann areas (BAs). The patterns of cortical connectivity were obtained in the four principal frequency bands, Theta (3-7 Hz), Alpha (8-12 Hz), Beta (13-30 Hz), Gamma (30-40 Hz) and the directed influences between any given pair of the estimated cortical signals were evaluated by use of a multivariate spectral technique known as partial directed coherence. The topology of the cortical networks has been identified with tools derived from graph theory. Results suggest that the cortical activity and connectivity elicited by the viewing of the TV commercials that were remembered by the experimental subjects are markedly different from the brain activity elicited during the observation of the TV commercials that were forgotten. In particular, during the observation of the TV commercials that were remembered, the amount of cortical spectral activity from the frontal areas (BA 8 and 9) and from the parietal areas (BA 5, 7, and 40) is higher compared with the activity elicited by the observation of TV commercials that were forgotten. In addition, network analysis suggests a clear role of the parietal areas as a target of the incoming flow of information from all the other parts of the cortex during the observation of TV commercials that have been remembered. The techniques presented here shed new light on

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

    Science.gov (United States)

    Chen, A C

    2001-10-01

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

  7. Post-task Effects on EEG Brain Activity Differ for Various Differential Learning and Contextual Interference Protocols

    Directory of Open Access Journals (Sweden)

    Diana Henz

    2018-01-01

    Full Text Available A large body of research has shown superior learning rates in variable practice compared to repetitive practice. More specifically, this has been demonstrated in the contextual interference (CI and in the differential learning (DL approach that are both representatives of variable practice. Behavioral studies have indicate different learning processes in CI and DL. Aim of the present study was to examine immediate post-task effects on electroencephalographic (EEG brain activation patterns after CI and DL protocols that reveal underlying neural processes at the early stage of motor consolidation. Additionally, we tested two DL protocols (gradual DL, chaotic DL to examine the effect of different degrees of stochastic fluctuations within the DL approach with a low degree of fluctuations in gradual DL and a high degree of fluctuations in chaotic DL. Twenty-two subjects performed badminton serves according to three variable practice protocols (CI, gradual DL, chaotic DL, and a repetitive learning protocol in a within-subjects design. Spontaneous EEG activity was measured before, and immediately after each 20-min practice session from 19 electrodes. Results showed distinguishable neural processes after CI, DL, and repetitive learning. Increases in EEG theta and alpha power were obtained in somatosensory regions (electrodes P3, P7, Pz, P4, P8 in both DL conditions compared to CI, and repetitive learning. Increases in theta and alpha activity in motor areas (electrodes C3, Cz, C4 were found after chaotic DL compared to gradual DL, and CI. Anterior areas (electrodes F3, F7, Fz, F4, F8 showed increased activity in the beta and gamma bands after CI. Alpha activity was increased in occipital areas (electrodes O1, O2 after repetitive learning. Post-task EEG brain activation patterns suggest that DL stimulates the somatosensory and motor system, and engages more regions of the cortex than repetitive learning due to a tighter stimulation of the motor and

  8. A Ternary Hybrid EEG-NIRS Brain-Computer Interface for the Classification of Brain Activation Patterns during Mental Arithmetic, Motor Imagery, and Idle State.

    Science.gov (United States)

    Shin, Jaeyoung; Kwon, Jinuk; Im, Chang-Hwan

    2018-01-01

    The performance of a brain-computer interface (BCI) can be enhanced by simultaneously using two or more modalities to record brain activity, which is generally referred to as a hybrid BCI. To date, many BCI researchers have tried to implement a hybrid BCI system by combining electroencephalography (EEG) and functional near-infrared spectroscopy (NIRS) to improve the overall accuracy of binary classification. However, since hybrid EEG-NIRS BCI, which will be denoted by hBCI in this paper, has not been applied to ternary classification problems, paradigms and classification strategies appropriate for ternary classification using hBCI are not well investigated. Here we propose the use of an hBCI for the classification of three brain activation patterns elicited by mental arithmetic, motor imagery, and idle state, with the aim to elevate the information transfer rate (ITR) of hBCI by increasing the number of classes while minimizing the loss of accuracy. EEG electrodes were placed over the prefrontal cortex and the central cortex, and NIRS optodes were placed only on the forehead. The ternary classification problem was decomposed into three binary classification problems using the "one-versus-one" (OVO) classification strategy to apply the filter-bank common spatial patterns filter to EEG data. A 10 × 10-fold cross validation was performed using shrinkage linear discriminant analysis (sLDA) to evaluate the average classification accuracies for EEG-BCI, NIRS-BCI, and hBCI when the meta-classification method was adopted to enhance classification accuracy. The ternary classification accuracies for EEG-BCI, NIRS-BCI, and hBCI were 76.1 ± 12.8, 64.1 ± 9.7, and 82.2 ± 10.2%, respectively. The classification accuracy of the proposed hBCI was thus significantly higher than those of the other BCIs ( p < 0.005). The average ITR for the proposed hBCI was calculated to be 4.70 ± 1.92 bits/minute, which was 34.3% higher than that reported for a previous binary hBCI study.

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

    Directory of Open Access Journals (Sweden)

    Melle J W van der Molen

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

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

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

    2017-08-01

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

  15. Sources of EEG activity most relevant to performance of brain-computer interface based on motor imagery

    Czech Academy of Sciences Publication Activity Database

    Frolov, A.; Húsek, Dušan; Bobrov, P.; Korshakov, A.V.; Chernikova, L.; Konovalov, R.; Mokienko, O.

    2012-01-01

    Roč. 22, č. 1 (2012), s. 21-37 ISSN 1210-0552 R&D Projects: GA ČR GAP202/10/0262 Grant - others:GA MŠk(CZ) ED1.1.00/02.0070 Program:ED Institutional research plan: CEZ:AV0Z10300504 Keywords : brain-computer interface * independent component analysis * pattern classification * motor imagery * inverse problem * fMRI * EEG Subject RIV: IN - Informatics, Computer Science Impact factor: 0.362, year: 2012

  16. Analysis of behavioral and EEG correlatives of attention in the dynamics of recovery of consciousness following severe brain injury

    Directory of Open Access Journals (Sweden)

    E. V. Sharova

    2016-01-01

    Full Text Available Objective: to determine the behavioral manifestations and electroencephalographic correlates of modality-nonspecific attention using a clinical model of severe brain injury (SBI.Patients and methods. 35 patients with SBI in the dynamics of post-coma recovery of mental activity (a study group and 23 healthy subjects (a control group were examined. The behavioral manifestations of NSA from coma to clear consciousness were analyzed in the patients. Changes in the pattern of EEG and in the indices of its coherence in the presence and activation of different forms of attention (an orienting response to the sound and eye opening; involuntary and voluntary visual forms, by applying specially developed computerized techniques, were investigated. The features of associated with attention changes in interhemispheric EEG coherence (IHC with the data of 3T diffusion tensor tractography of the corpus callosum (CC were compared.Results. Attention disorders were shown to be essential and an «axial disorder» in patients with SBI. There were statistically confirmed qualitative and quantitative differences attention-associated changes in the EEG pattern and IHC in reversible and chronic unconsciousness. The important favorable prognostic sign proved to be reactive changes in interhemispheric EEG relations, including frontal ones characterized by the absence of clear external manifestations of consciousness in the very earliest stages. There was a significant correlation between the preservation of CC tracts (primarily, the rostrum, anterior portion, and splenium and attention-related reactivity of IHC, which reflects the specific, though nonrigid, structural determinacy of the latter.

  17. 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.

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

    Science.gov (United States)

    Thomas, Bianca Lee; Viljoen, Margaretha

    2016-01-01

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

  19. [EEG and brain-stem evoked potentials in 125 recent concussions].

    Science.gov (United States)

    Geets, W; Louette, N

    1983-12-01

    EEG and ipsi/contralateral BEPs have been recorded in 125 cases of concussion at most 48 h after the cerebral trauma. In 100 cases of minor concussion the temporary loss of consciousness lasted not more than 2 min. In 25 cases of mild concussion, the loss of consciousness lasted until their arrival at the hospital. In minor concussions an abnormal EEG was found in 17% of the cases and in mild concussions, in 56%. The abnormalities of the BEP, more often seen in mild concussions (60%) than in minor concussions (8%), are an increase of interpeak latencies or distorted responses with average to bad reproducibility. The results are discussed.

  20. Photoionization and High Density Gas

    Science.gov (United States)

    Kallman, T.; Bautista, M.; White, Nicholas E. (Technical Monitor)

    2002-01-01

    We present results of calculations using the XSTAR version 2 computer code. This code is loosely based on the XSTAR v.1 code which has been available for public use for some time. However it represents an improvement and update in several major respects, including atomic data, code structure, user interface, and improved physical description of ionization/excitation. In particular, it now is applicable to high density situations in which significant excited atomic level populations are likely to occur. We describe the computational techniques and assumptions, and present sample runs with particular emphasis on high density situations.

  1. High-density multicore fibers

    DEFF Research Database (Denmark)

    Takenaga, K.; Matsuo, S.; Saitoh, K.

    2016-01-01

    High-density single-mode multicore fibers were designed and fabricated. A heterogeneous 30-core fiber realized a low crosstalk of −55 dB. A quasi-single-mode homogeneous 31-core fiber attained the highest core count as a single-mode multicore fiber.......High-density single-mode multicore fibers were designed and fabricated. A heterogeneous 30-core fiber realized a low crosstalk of −55 dB. A quasi-single-mode homogeneous 31-core fiber attained the highest core count as a single-mode multicore fiber....

  2. Localization of spontaneous bursting neuronal activity in the preterm human brain with simultaneous EEG-fMRI.

    Science.gov (United States)

    Arichi, Tomoki; Whitehead, Kimberley; Barone, Giovanni; Pressler, Ronit; Padormo, Francesco; Edwards, A David; Fabrizi, Lorenzo

    2017-09-12

    Electroencephalographic recordings from the developing human brain are characterized by spontaneous neuronal bursts, the most common of which is the delta brush. Although similar events in animal models are known to occur in areas of immature cortex and drive their development, their origin in humans has not yet been identified. Here, we use simultaneous EEG-fMRI to localise the source of delta brush events in 10 preterm infants aged 32-36 postmenstrual weeks. The most frequent patterns were left and right posterior-temporal delta brushes which were associated in the left hemisphere with ipsilateral BOLD activation in the insula only; and in the right hemisphere in both the insular and temporal cortices. This direct measure of neural and hemodynamic activity shows that the insula, one of the most densely connected hubs in the developing cortex, is a major source of the transient bursting events that are critical for brain maturation.

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

    Directory of Open Access Journals (Sweden)

    Elliott A Beaton

    2008-03-01

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

  4. EEG: Origin and measurement

    NARCIS (Netherlands)

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

    2010-01-01

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

  5. myBrain: a novel EEG embedded system for epilepsy monitoring.

    Science.gov (United States)

    Pinho, Francisco; Cerqueira, João; Correia, José; Sousa, Nuno; Dias, Nuno

    2017-10-01

    The World Health Organisation has pointed that a successful health care delivery, requires effective medical devices as tools for prevention, diagnosis, treatment and rehabilitation. Several studies have concluded that longer monitoring periods and outpatient settings might increase diagnosis accuracy and success rate of treatment selection. The long-term monitoring of epileptic patients through electroencephalography (EEG) has been considered a powerful tool to improve the diagnosis, disease classification, and treatment of patients with such condition. This work presents the development of a wireless and wearable EEG acquisition platform suitable for both long-term and short-term monitoring in inpatient and outpatient settings. The developed platform features 32 passive dry electrodes, analogue-to-digital signal conversion with 24-bit resolution and a variable sampling frequency from 250 Hz to 1000 Hz per channel, embedded in a stand-alone module. A computer-on-module embedded system runs a Linux ® operating system that rules the interface between two software frameworks, which interact to satisfy the real-time constraints of signal acquisition as well as parallel recording, processing and wireless data transmission. A textile structure was developed to accommodate all components. Platform performance was evaluated in terms of hardware, software and signal quality. The electrodes were characterised through electrochemical impedance spectroscopy and the operating system performance running an epileptic discrimination algorithm was evaluated. Signal quality was thoroughly assessed in two different approaches: playback of EEG reference signals and benchmarking with a clinical-grade EEG system in alpha-wave replacement and steady-state visual evoked potential paradigms. The proposed platform seems to efficiently monitor epileptic patients in both inpatient and outpatient settings and paves the way to new ambulatory clinical regimens as well as non-clinical EEG

  6. Effects of green and black tea consumption on brain wave activities in healthy volunteers as measured by a simplified Electroencephalogram (EEG): A feasibility study.

    Science.gov (United States)

    Okello, Edward J; Abadi, Awatf M; Abadi, Saad A

    2016-06-01

    Tea has been associated with many mental benefits, such as attention enhancement, clarity of mind, and relaxation. These psychosomatic states can be measured in terms of brain activity using an electroencephalogram (EEG). Brain activity can be assessed either during a state of passive activity or when performing attention tasks and it can provide useful information about the brain's state. This study investigated the effects of green and black consumption on brain activity as measured by a simplified EEG, during passive activity. Eight healthy volunteers participated in the study. The EEG measurements were performed using a two channel EEG brain mapping instrument - HeadCoach™. Fast Fourier transform algorithm and EEGLAB toolbox using the Matlab software were used for data processing and analysis. Alpha, theta, and beta wave activities were all found to increase after 1 hour of green and black tea consumption, albeit, with very considerable inter-individual variations. Our findings provide further evidence for the putative beneficial effects of tea. The highly significant increase in theta waves (P by 'from field to shelf practices'.

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

    Directory of Open Access Journals (Sweden)

    Rose D. Bharath

    2017-09-01

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

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

    Science.gov (United States)

    Freeman, Frederick G.

    1993-01-01

    presented target stimulus. In addition to the task requirements, irrelevant tones were presented in the background. Research has shown that even though these stimuli are not attended, ERP's to them can still be elicited. The amplitude of the ERP waves has been shown to change as a function of a person's level of alertness. ERP's were also collected and analyzed for the target stimuli for each task. Brain maps were produced based on the ERP voltages for the different stimuli. In addition to the ERP's, a quantitative EEG (QEEG) was performed on the data using a fast Fourier technique to produce a power spectral analysis of the EEG. This analysis was conducted on the continuous EEG while the subjects were performing the tasks. Finally, a QEEG was performed on periods during the task when subjects indicated that they were in an altered state of awareness. During the tasks, subjects were asked to indicate by pressing a button when they realized their level of task awareness had changed. EEG epochs were collected for times just before and just after subjects made this reponse. The purpose of this final analysis was to determine whether or not subjective indices of level of awareness could be correlated with different patterns of EEG.

  9. 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.

  10. A brain-computer interface for potential non-verbal facial communication based on EEG signals related to specific emotions.

    Science.gov (United States)

    Kashihara, Koji

    2014-01-01

    Unlike assistive technology for verbal communication, the brain-machine or brain-computer interface (BMI/BCI) has not been established as a non-verbal 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 non-verbal 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 (FG). This study also developed an efficient method for detecting implicit negative emotional responses to specific faces by using EEG signals. A classification method based on a support vector machine enables the easy classification of neutral faces that trigger specific individual emotions. In

  11. Research on the relation of EEG signal chaos characteristics with high-level intelligence activity of human brain.

    Science.gov (United States)

    Wang, Xingyuan; Meng, Juan; Tan, Guilin; Zou, Lixian

    2010-04-27

    Using phase space reconstruct technique from one-dimensional and multi-dimensional time series and the quantitative criterion rule of system chaos, and combining the neural network; analyses, computations and sort are conducted on electroencephalogram (EEG) signals of five kinds of human consciousness activities (relaxation, mental arithmetic of multiplication, mental composition of a letter, visualizing a 3-dimensional object being revolved about an axis, and visualizing numbers being written or erased on a blackboard). Through comparative studies on the determinacy, the phase graph, the power spectra, the approximate entropy, the correlation dimension and the Lyapunov exponent of EEG signals of 5 kinds of consciousness activities, the following conclusions are shown: (1) The statistic results of the deterministic computation indicate that chaos characteristic may lie in human consciousness activities, and central tendency measure (CTM) is consistent with phase graph, so it can be used as a division way of EEG attractor. (2) The analyses of power spectra show that ideology of single subject is almost identical but the frequency channels of different consciousness activities have slight difference. (3) The approximate entropy between different subjects exist discrepancy. Under the same conditions, the larger the approximate entropy of subject is, the better the subject's innovation is. (4) The results of the correlation dimension and the Lyapunov exponent indicate that activities of human brain exist in attractors with fractional dimensions. (5) Nonlinear quantitative criterion rule, which unites the neural network, can classify different kinds of consciousness activities well. In this paper, the results of classification indicate that the consciousness activity of arithmetic has better differentiation degree than that of abstract.

  12. Analysis of brain activity and response to colour stimuli during learning tasks: an EEG study

    Science.gov (United States)

    Folgieri, Raffaella; Lucchiari, Claudio; Marini, Daniele

    2013-02-01

    The research project intends to demonstrate how EEG detection through BCI device can improve the analysis and the interpretation of colours-driven cognitive processes through the combined approach of cognitive science and information technology methods. To this end, firstly it was decided to design an experiment based on comparing the results of the traditional (qualitative and quantitative) cognitive analysis approach with the EEG signal analysis of the evoked potentials. In our case, the sensorial stimulus is represented by the colours, while the cognitive task consists in remembering the words appearing on the screen, with different combination of foreground (words) and background colours. In this work we analysed data collected from a sample of students involved in a learning process during which they received visual stimuli based on colour variation. The stimuli concerned both the background of the text to learn and the colour of the characters. The experiment indicated some interesting results concerning the use of primary (RGB) and complementary (CMY) colours.

  13. Synergetic fMRI-EEG brain mapping in alpha-rhythm voluntary control mode.

    Science.gov (United States)

    Shtark, M B; Verevkin, E G; Kozlova, L I; Mazhirina, K G; Pokrovskii, M A; Petrovskii, E D; Savelov, A A; Starostin, A S; Yarosh, S V

    2015-03-01

    For the first time in neurobiology-related issues, the synergistic spatial dynamics of EEG and fMRI (BOLD phenomenon) was studied during cognitive alpha biofeedback training in the operant conditioning mode (acoustic reinforcement of alpha-rhythm development and stability). Significant changes in alpha-rhythm intensity were found in T6 electrode area (Brodmann area 37). Brodmann areas related to solving alpha-training tasks and maximally involved in the formation of new neuronal network were middle and superior temporal gyri (areas 21, 22, and 37), fusiform gyrus, inferior frontal gyrus (areas 4, 6, and 46), anterior cingulate gyrus (areas 23 and 24), cuneus, and precuneus (area 7). Wide involvement of Brodmann areas is determined by psychological architecture of alpha-rhythm generating system control that includes complex cognitive activities: decision making, retrieval of long-term memory, evaluation of the reward and control efficiency during alpha-EEG biofeedback.

  14. [Digital electroencephalography in brain death diagnostics : Technical requirements and results of a survey on the compatibility with medical guidelines of digital EEG systems from providers in Germany].

    Science.gov (United States)

    Walter, U; Noachtar, S; Hinrichs, H

    2018-02-01

    The guidelines of the German Medical Association and the German Society for Clinical Neurophysiology and Functional Imaging (DGKN) require a high procedural and technical standard for electroencephalography (EEG) as an ancillary method for diagnosing the irreversible cessation of brain function (brain death). Nowadays, digital EEG systems are increasingly being applied in hospitals. So far it is unclear to what extent the digital EEG systems currently marketed in Germany meet the guidelines for diagnosing brain death. In the present article, the technical und safety-related requirements for digital EEG systems and the EEG documentation for diagnosing brain death are described in detail. On behalf of the DGKN, the authors sent out a questionnaire to all identified distributors of digital EEG systems in Germany with respect to the following technical demands: repeated recording of the calibration signals during an ongoing EEG recording, repeated recording of all electrode impedances during an ongoing EEG recording, assessability of intrasystem noise and galvanic isolation of measurement earthing from earthing conductor (floating input). For 15 of the identified 20 different digital EEG systems the specifications were provided by the distributors (among them all distributors based in Germany). All of these EEG systems are provided with a galvanic isolation (floating input). The internal noise can be tested with all systems; however, some systems do not allow repeated recording of the calibration signals and/or the electrode impedances during an ongoing EEG recording. The majority but not all of the currently available digital EEG systems offered for clinical use are eligible for use in brain death diagnostics as per German guidelines.

  15. To what extent can dry and water-based EEG electrodes replace conductive gel ones?: A Steady State Visual Evoked Potential Brain-Computer Interface Case Study

    NARCIS (Netherlands)

    Mihajlovic, V.; Garcia Molina, G.; Peuscher, J

    2011-01-01

    Recent technological advances in the field of skin electrodes and on-body sensors indicate a possibility of having an alternative to the traditionally used conductive gel electrodes for measuring electrical signals of the brain (electroencephalogram, EEG). This paper evaluates whether water-based

  16. Brain functional connectivity during the experience of thought blocks in schizophrenic patients with persistent auditory verbal hallucinations: an EEG study.

    Science.gov (United States)

    Angelopoulos, Elias; Koutsoukos, Elias; Maillis, Antonis; Papadimitriou, George N; Stefanis, Costas

    2014-03-01

    Thought blocks (TBs) are characterized by regular interruptions in the stream of thought. Outward signs are abrupt and repeated interruptions in the flow of conversation or actions while subjective experience is that of a total and uncontrollable emptying of the mind. In the very limited bibliography regarding TB, the phenomenon is thought to be conceptualized as a disturbance of consciousness that can be attributed to stoppages of continuous information processing due to an increase in the volume of information to be processed. In an attempt to investigate potential expression of the phenomenon on the functional properties of electroencephalographic (EEG) activity, an EEG study was contacted in schizophrenic patients with persisting auditory verbal hallucinations (AVHs) who additionally exhibited TBs. In this case, we hypothesized that the persistent and dense AVHs could serve the role of an increased information flow that the brain is unable to process, a condition that is perceived by the person as TB. Phase synchronization analyses performed on EEG segments during the experience of TBs showed that synchrony values exhibited a long-range common mode of coupling (grouped behavior) among the left temporal area and the remaining central and frontal brain areas. These common synchrony-fluctuation schemes were observed for 0.5 to 2s and were detected in a 4-s window following the estimated initiation of the phenomenon. The observation was frequency specific and detected in the broad alpha band region (6-12Hz). The introduction of synchrony entropy (SE) analysis applied on the cumulative synchrony distribution showed that TB states were characterized by an explicit preference of the system to be functioned at low values of synchrony, while the synchrony values are broadly distributed during the recovery state. Our results indicate that during TB states, the phase locking of several brain areas were converged uniformly in a narrow band of low synchrony values and in a

  17. 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.

  18. EEG-based emergency braking intention prediction for brain-controlled driving considering one electrode falling-off.

    Science.gov (United States)

    Huikang Wang; Luzheng Bi; Teng Teng

    2017-07-01

    This paper proposes a novel method of electroencephalography (EEG)-based driver emergency braking intention detection system for brain-controlled driving considering one electrode falling-off. First, whether one electrode falls off is discriminated based on EEG potentials. Then, the missing signals are estimated by using the signals collected from other channels based on multivariate linear regression. Finally, a linear decoder is applied to classify driver intentions. Experimental results show that the falling-off discrimination accuracy is 99.63% on average and the correlation coefficient and root mean squared error (RMSE) between the estimated and experimental data are 0.90 and 11.43 μV, respectively, on average. Given one electrode falls off, the system accuracy of the proposed intention prediction method is significantly higher than that of the original method (95.12% VS 79.11%) and is close to that (95.95%) of the original system under normal situations (i. e., no electrode falling-off).

  19. An efficient rhythmic component expression and weighting synthesis strategy for classifying motor imagery EEG in a brain computer interface

    Science.gov (United States)

    Wang, Tao; He, Bin

    2004-03-01

    The recognition of mental states during motor imagery tasks is crucial for EEG-based brain computer interface research. We have developed a new algorithm by means of frequency decomposition and weighting synthesis strategy for recognizing imagined right- and left-hand movements. A frequency range from 5 to 25 Hz was divided into 20 band bins for each trial, and the corresponding envelopes of filtered EEG signals for each trial were extracted as a measure of instantaneous power at each frequency band. The dimensionality of the feature space was reduced from 200 (corresponding to 2 s) to 3 by down-sampling of envelopes of the feature signals, and subsequently applying principal component analysis. The linear discriminate analysis algorithm was then used to classify the features, due to its generalization capability. Each frequency band bin was weighted by a function determined according to the classification accuracy during the training process. The present classification algorithm was applied to a dataset of nine human subjects, and achieved a success rate of classification of 90% in training and 77% in testing. The present promising results suggest that the present classification algorithm can be used in initiating a general-purpose mental state recognition based on motor imagery tasks.

  20. Quantitative EEG and neurofeedback in children and adolescents: anxiety disorders, depressive disorders, comorbid addiction and attention-deficit/hyperactivity disorder, and brain injury.

    Science.gov (United States)

    Simkin, Deborah R; Thatcher, Robert W; Lubar, Joel

    2014-07-01

    This article explores the science surrounding neurofeedback. Both surface neurofeedback (using 2-4 electrodes) and newer interventions, such as real-time z-score neurofeedback (electroencephalogram [EEG] biofeedback) and low-resolution electromagnetic tomography neurofeedback, are reviewed. The limited literature on neurofeedback research in children and adolescents is discussed regarding treatment of anxiety, mood, addiction (with comorbid attention-deficit/hyperactivity disorder), and traumatic brain injury. Future potential applications, the use of quantitative EEG for determining which patients will be responsive to medications, the role of randomized controlled studies in neurofeedback research, and sensible clinical guidelines are considered. Copyright © 2014 Elsevier Inc. All rights reserved.

  1. Speaking and cognitive distractions during EEG-based brain control of a virtual neuroprosthesis-arm

    OpenAIRE

    Foldes, Stephen T; Taylor, Dawn M

    2013-01-01

    Background Brain-computer interface (BCI) systems have been developed to provide paralyzed individuals the ability to command the movements of an assistive device using only their brain activity. BCI systems are typically tested in a controlled laboratory environment were the user is focused solely on the brain-control task. However, for practical use in everyday life people must be able to use their brain-controlled device while mentally engaged with the cognitive responsibilities of daily a...

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

    NARCIS (Netherlands)

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

    2011-01-01

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

  3. Detection of alcoholism based on EEG signals and functional brain network features extraction

    NARCIS (Netherlands)

    Ahmadi, N.; Pei, Y.; Pechenizkiy, M.

    2017-01-01

    Alcoholism is a common disorder that leads to brain defects and associated cognitive, emotional and behavioral impairments. Finding and extracting discriminative biological markers, which are correlated to healthy brain pattern and alcoholic brain pattern, helps us to utilize automatic methods for

  4. Cerebral perfusion abnormalities in therapy-resistant epilepsy in childhood: comparison between EEG, MRI and 99Tcm-ECD brain SPET.

    Science.gov (United States)

    Vattimo, A; Burroni, L; Bertelli, P; Volterrani, D; Vella, A

    1996-01-01

    We performed 99Tcm-ethyl cysteinate dimer (ECD) interictal single photon emission tomography (SPET) in 26 children with severe therapy-resistant epilepsy. All the children underwent a detailed clinical examination, an electroencephalogram (EEG) investigation and brain magnetic resonance imaging (MRI). In 21 of the 26 children, SPET demonstrated brain blood flow abnormalities, in 13 cases in the same territories that showed EEG alterations. MRI showed structural lesions in 6 of the 26 children, while SPET imaging confirmed these abnormalities in only 5 children. The lesion not detected on SPET was shown to be 3 mm thick on MRI. Five symptomatic patients had normal SPET. In one of these patients, the EEG findings were normal and MRI revealed a small calcific nodule (4 mm thick); in the others, the EEG showed non-focal but diffuse abnormalities. These data confirm that brain SPET is sensitive in detecting and localizing hypoperfused areas that could be associated with epileptic foci in this group of patients, even when the MRI image is normal.

  5. Detection of Drug Effects on Brain Activity using EEG-P300 with Similar Stimuli

    Science.gov (United States)

    Turnip, Arjon; Dwi Esti, K.; Faizal Amri, M.; Simbolon, Artha I.; Agung Suhendra, M.; IsKandar, Shelly; Wirakusumah, Firman F.

    2017-07-01

    Drug addiction poses a serious problem to our species. The worry that our significant family might be involved in drug use and are concerned to know how to detect drug use. Examinations of thirty taped EEG recordings were performed. The subjects consist of three group: addictive, methadone treatment (rehabilitation), and control (normal) which 10 subjects for each group. Statistical analysis was performed for the relative frequency of wave bands. The higher average amplitude is obtained from the addiction subjects. In the comparison with the signals source, channels P3 provide slightly higher average amplitude than other channels for all of subjects.

  6. Large Scale Functional Brain Networks Underlying Temporal Integration of Audio-Visual Speech Perception: An EEG Study.

    Science.gov (United States)

    Kumar, G Vinodh; Halder, Tamesh; Jaiswal, Amit K; Mukherjee, Abhishek; Roy, Dipanjan; Banerjee, Arpan

    2016-01-01

    Observable lip movements of the speaker influence perception of auditory speech. A classical example of this influence is reported by listeners who perceive an illusory (cross-modal) speech sound (McGurk-effect) when presented with incongruent audio-visual (AV) speech stimuli. Recent neuroimaging studies of AV speech perception accentuate the role of frontal, parietal, and the integrative brain sites in the vicinity of the superior temporal sulcus (STS) for multisensory speech perception. However, if and how does the network across the whole brain participates during multisensory perception processing remains an open question. We posit that a large-scale functional connectivity among the neural population situated in distributed brain sites may provide valuable insights involved in processing and fusing of AV speech. Varying the psychophysical parameters in tandem with electroencephalogram (EEG) recordings, we exploited the trial-by-trial perceptual variability of incongruent audio-visual (AV) speech stimuli to identify the characteristics of the large-scale cortical network that facilitates multisensory perception during synchronous and asynchronous AV speech. We evaluated the spectral landscape of EEG signals during multisensory speech perception at varying AV lags. Functional connectivity dynamics for all sensor pairs was computed using the time-frequency global coherence, the vector sum of pairwise coherence changes over time. During synchronous AV speech, we observed enhanced global gamma-band coherence and decreased alpha and beta-band coherence underlying cross-modal (illusory) perception compared to unisensory perception around a temporal window of 300-600 ms following onset of stimuli. During asynchronous speech stimuli, a global broadband coherence was observed during cross-modal perception at earlier times along with pre-stimulus decreases of lower frequency power, e.g., alpha rhythms for positive AV lags and theta rhythms for negative AV lags. Thus, our

  7. Predictable Internal Brain Dynamics in EEG and Its Relation to Conscious States

    Directory of Open Access Journals (Sweden)

    Jaewook eYoo

    2014-06-01

    Full Text Available Consciousness is a complex and multi-faceted phenomenon defying scientific explanation. Part of the reason why this is the case is due to its subjective nature. In our previous computational experiments, to avoid such a subjective trap, we took a strategy to investigate objective necessary conditions of consciousness. Our basic hypothesis was that predictive internal dynamics serves as such a condition. This is in line with theories of consciousness that treat retention (memory, protention (anticipation, and primary impression as the tripartite temporal structure of consciousness. To test our hypothesis, we analyzed publicly available sleep and awake electroencephalogram (EEG data. Our results show that EEG signals from awake or rapid eye movement (REM sleep states have more predictable dynamics compared to those from slow-wave sleep (SWS. Since awakeness and REM sleep are associated with conscious states and SWS with unconscious or less consciousness states, these results support our hypothesis. The results suggest an intricate relationship among prediction, consciousness, and time, with potential applications to time perception and neurorobotics.

  8. Performance evaluation of a motor-imagery-based EEG-Brain computer interface using a combined cue with heterogeneous training data in BCI-Naive subjects

    Directory of Open Access Journals (Sweden)

    Lee Youngbum

    2011-10-01

    Full Text Available Abstract Background The subjects in EEG-Brain computer interface (BCI system experience difficulties when attempting to obtain the consistent performance of the actual movement by motor imagery alone. It is necessary to find the optimal conditions and stimuli combinations that affect the performance factors of the EEG-BCI system to guarantee equipment safety and trust through the performance evaluation of using motor imagery characteristics that can be utilized in the EEG-BCI testing environment. Methods The experiment was carried out with 10 experienced subjects and 32 naive subjects on an EEG-BCI system. There were 3 experiments: The experienced homogeneous experiment, the naive homogeneous experiment and the naive heterogeneous experiment. Each experiment was compared in terms of the six audio-visual cue combinations and consisted of 50 trials. The EEG data was classified using the least square linear classifier in case of the naive subjects through the common spatial pattern filter. The accuracy was calculated using the training and test data set. The p-value of the accuracy was obtained through the statistical significance test. Results In the case in which a naive subject was trained by a heterogeneous combined cue and tested by a visual cue, the result was not only the highest accuracy (p Conclusions We propose the use of this measuring methodology of a heterogeneous combined cue for training data and a visual cue for test data by the typical EEG-BCI algorithm on the EEG-BCI system to achieve effectiveness in terms of consistence, stability, cost, time, and resources management without the need for a trial and error process.

  9. Harnessing functional segregation across brain rhythms as a means to detect EEG oscillatory multiplexing during music listening.

    Science.gov (United States)

    Adamos, Dimitrios A; Laskaris, Nikolaos A; Micheloyannis, Sifis

    2018-06-01

    Music, being a multifaceted stimulus evolving at multiple timescales, modulates brain function in a manifold way that encompasses not only the distinct stages of auditory perception, but also higher cognitive processes like memory and appraisal. Network theory is apparently a promising approach to describe the functional reorganization of brain oscillatory dynamics during music listening. However, the music induced changes have so far been examined within the functional boundaries of isolated brain rhythms. Using naturalistic music, we detected the functional segregation patterns associated with different cortical rhythms, as these were reflected in the surface electroencephalography (EEG) measurements. The emerged structure was compared across frequency bands to quantify the interplay among rhythms. It was also contrasted against the structure from the rest and noise listening conditions to reveal the specific components stemming from music listening. Our methodology includes an efficient graph-partitioning algorithm, which is further utilized for mining prototypical modular patterns, and a novel algorithmic procedure for identifying 'switching nodes' (i.e. recording sites) that consistently change module during music listening. Our results suggest the multiplex character of the music-induced functional reorganization and particularly indicate the dependence between the networks reconstructed from the δ and β H rhythms. This dependence is further justified within the framework of nested neural oscillations and fits perfectly within the context of recently introduced cortical entrainment to music. Complying with the contemporary trends towards a multi-scale examination of the brain network organization, our approach specifies the form of neural coordination among rhythms during music listening. Considering its computational efficiency, and in conjunction with the flexibility of in situ electroencephalography, it may lead to novel assistive tools for real

  10. Harnessing functional segregation across brain rhythms as a means to detect EEG oscillatory multiplexing during music listening

    Science.gov (United States)

    Adamos, Dimitrios A.; Laskaris, Nikolaos A.; Micheloyannis, Sifis

    2018-06-01

    Objective. Music, being a multifaceted stimulus evolving at multiple timescales, modulates brain function in a manifold way that encompasses not only the distinct stages of auditory perception, but also higher cognitive processes like memory and appraisal. Network theory is apparently a promising approach to describe the functional reorganization of brain oscillatory dynamics during music listening. However, the music induced changes have so far been examined within the functional boundaries of isolated brain rhythms. Approach. Using naturalistic music, we detected the functional segregation patterns associated with different cortical rhythms, as these were reflected in the surface electroencephalography (EEG) measurements. The emerged structure was compared across frequency bands to quantify the interplay among rhythms. It was also contrasted against the structure from the rest and noise listening conditions to reveal the specific components stemming from music listening. Our methodology includes an efficient graph-partitioning algorithm, which is further utilized for mining prototypical modular patterns, and a novel algorithmic procedure for identifying ‘switching nodes’ (i.e. recording sites) that consistently change module during music listening. Main results. Our results suggest the multiplex character of the music-induced functional reorganization and particularly indicate the dependence between the networks reconstructed from the δ and β H rhythms. This dependence is further justified within the framework of nested neural oscillations and fits perfectly within the context of recently introduced cortical entrainment to music. Significance. Complying with the contemporary trends towards a multi-scale examination of the brain network organization, our approach specifies the form of neural coordination among rhythms during music listening. Considering its computational efficiency, and in conjunction with the flexibility of in situ electroencephalography

  11. Directed cortical information flow during human object recognition: analyzing induced EEG gamma-band responses in brain's source space.

    Directory of Open Access Journals (Sweden)

    Gernot G Supp

    Full Text Available The increase of induced gamma-band responses (iGBRs; oscillations >30 Hz elicited by familiar (meaningful objects is well established in electroencephalogram (EEG research. This frequency-specific change at distinct locations is thought to indicate the dynamic formation of local neuronal assemblies during the activation of cortical object representations. As analytically power increase is just a property of a single location, phase-synchrony was introduced to investigate the formation of large-scale networks between spatially distant brain sites. However, classical phase-synchrony reveals symmetric, pair-wise correlations and is not suited to uncover the directionality of interactions. Here, we investigated the neural mechanism of visual object processing by means of directional coupling analysis going beyond recording sites, but rather assessing the directionality of oscillatory interactions between brain areas directly. This study is the first to identify the directionality of oscillatory brain interactions in source space during human object recognition and suggests that familiar, but not unfamiliar, objects engage widespread reciprocal information flow. Directionality of cortical information-flow was calculated based upon an established Granger-Causality coupling-measure (partial-directed coherence; PDC using autoregressive modeling. To enable comparison with previous coupling studies lacking directional information, phase-locking analysis was applied, using wavelet-based signal decompositions. Both, autoregressive modeling and wavelet analysis, revealed an augmentation of iGBRs during the presentation of familiar objects relative to unfamiliar controls, which was localized to inferior-temporal, superior-parietal and frontal brain areas by means of distributed source reconstruction. The multivariate analysis of PDC evaluated each possible direction of brain interaction and revealed widespread reciprocal information-transfer during familiar

  12. Using Brain Activation (nir-HEG/Q-EEG) and Execution Measures (CPTs) in a ADHD Assessment Protocol.

    Science.gov (United States)

    Areces, Debora; Cueli, Marisol; García, Trinidad; González-Castro, Paloma; Rodríguez, Celestino

    2018-04-01

    Attention Deficit Hyperactivity Disorder (ADHD) is a problem that impacts academic performance and has serious consequences that result in difficulties in scholastic, social and familial contexts. One of the most common problems in the identification of this disorder relates to the apparent over diagnosis of the disorder due to the absence of global protocols for assessment. The research group of School Learning, Difficulties and Academic Performance (ADIR) from the University of Oviedo, has developed a complete protocol that suggests the existence of certain patterns of cortical activation and executive control for identifying ADHD more objectively. This protocol takes into consideration some of the hypothetical determinants of ADHD, including the relationship between activation of selected areas of the brain, and differences in performance on various aspects of executive functioning such as omissions, commissions or response times, using innovative tools of Continuous Performance Testing (based on Virtual Reality CPT and Traditional CPT) and brain activation measures (two different tools, based on Hemoencephalography- nirHEG; and Quantified Electroencephalography --Q-EEG, respectively). This model of assessment aims to provide an effective assessment of ADHD symptomatology in order to design an accurate intervention and make appropriate recommendations for parents and teachers.

  13. Competition in the Brain. The Contribution of EEG and fNIRS Modulation and Personality Effects in Social Ranking.

    Science.gov (United States)

    Balconi, Michela; Vanutelli, Maria E

    2016-01-01

    In the present study, the social ranking perception in competition was explored. Brain response (alpha band oscillations, EEG; hemodynamic activity, O2Hb), as well as self-perception of social ranking, cognitive performance, and personality trait (Behavioral Activation System, BAS) were considered during a competitive joint-action. Subjects were required to develop a strategy to obtain a better outcome than a competitor (C) (in term of error rate, and response time, RT). A pre-feedback (without a specific feedback on the performance) and a post-feedback condition (which reinforced the improved performance) were provided. It was found that higher-BAS participants responded in greater measure to perceived higher cognitive performance (post-feedback condition), with increased left prefrontal activity, higher ranking perception, and a better real performance (reduced RTs). These results were explained in term of increased sense of self-efficacy and social position, probably based on higher-BAS sensitivity to reinforcing conditions. In addition, the hemispheric effect in favor of the left side characterized the competitive behavior, showing an imbalance for high-BAS in comparison to low-BAS in the case of a rewarding (post-feedback) context. Therefore, the present results confirmed the significance of BAS in modulating brain responsiveness, self-perceived social position, and real performance during an interpersonal competitive action which is considered highly relevant for social status.

  14. How does a surgeon’s brain buzz? An EEG coherence study on the interaction between humans and robot

    Science.gov (United States)

    2013-01-01

    Introduction In humans, both primary and non-primary motor areas are involved in the control of voluntary movements. However, the dynamics of functional coupling among different motor areas have not been fully clarified yet. There is to date no research looking to the functional dynamics in the brain of surgeons working in laparoscopy compared with those trained and working in robotic surgery. Experimental procedures We enrolled 16 right-handed trained surgeons and assessed changes in intra- and inter-hemispheric EEG coherence with a 32-channels device during the same motor task with either a robotic or a laparoscopic approach. Estimates of auto and coherence spectra were calculated by a fast Fourier transform algorithm implemented on Matlab 5.3. Results We found increase of coherence in surgeons performing laparoscopy, especially in theta and lower alpha activity, in all experimental conditions (M1 vs. SMA, S1 vs. SMA, S1 vs. pre-SMA and M1 vs. S1; p with different approaches. To the best of our knowledge, this is the first study that tried to assess semi-quantitative differences during the interaction between normal human brain and robotic devices. PMID:23607324

  15. How does a surgeon's brain buzz? An EEG coherence study on the interaction between humans and robot.

    Science.gov (United States)

    Bocci, Tommaso; Moretto, Carlo; Tognazzi, Silvia; Briscese, Lucia; Naraci, Megi; Leocani, Letizia; Mosca, Franco; Ferrari, Mauro; Sartucci, Ferdinando

    2013-04-22

    In humans, both primary and non-primary motor areas are involved in the control of voluntary movements. However, the dynamics of functional coupling among different motor areas have not been fully clarified yet. There is to date no research looking to the functional dynamics in the brain of surgeons working in laparoscopy compared with those trained and working in robotic surgery. We enrolled 16 right-handed trained surgeons and assessed changes in intra- and inter-hemispheric EEG coherence with a 32-channels device during the same motor task with either a robotic or a laparoscopic approach. Estimates of auto and coherence spectra were calculated by a fast Fourier transform algorithm implemented on Matlab 5.3. We found increase of coherence in surgeons performing laparoscopy, especially in theta and lower alpha activity, in all experimental conditions (M1 vs. SMA, S1 vs. SMA, S1 vs. pre-SMA and M1 vs. S1; p right vs. left M1, right vs. left S1, right pre-SMA vs. left M1, left pre-SMA vs. right M1; p brain and robotic devices.

  16. 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.

  17. Simultaneous head tissue conductivity and EEG source location estimation.

    Science.gov (United States)

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

    2016-01-01

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

  18. A System for True and False Memory Prediction Based on 2D and 3D Educational Contents and EEG Brain Signals.

    Science.gov (United States)

    Bamatraf, Saeed; Hussain, Muhammad; Aboalsamh, Hatim; Qazi, Emad-Ul-Haq; Malik, Amir Saeed; Amin, Hafeez Ullah; Mathkour, Hassan; Muhammad, Ghulam; Imran, Hafiz Muhammad

    2016-01-01

    We studied the impact of 2D and 3D educational contents on learning and memory recall using electroencephalography (EEG) brain signals. For this purpose, we adopted a classification approach that predicts true and false memories in case of both short term memory (STM) and long term memory (LTM) and helps to decide whether there is a difference between the impact of 2D and 3D educational contents. In this approach, EEG brain signals are converted into topomaps and then discriminative features are extracted from them and finally support vector machine (SVM) which is employed to predict brain states. For data collection, half of sixty-eight healthy individuals watched the learning material in 2D format whereas the rest watched the same material in 3D format. After learning task, memory recall tasks were performed after 30 minutes (STM) and two months (LTM), and EEG signals were recorded. In case of STM, 97.5% prediction accuracy was achieved for 3D and 96.6% for 2D and, in case of LTM, it was 100% for both 2D and 3D. The statistical analysis of the results suggested that for learning and memory recall both 2D and 3D materials do not have much difference in case of STM and LTM.

  19. An EEG/EOG-based hybrid brain-neural computer interaction (BNCI) system to control an exoskeleton for the paralyzed hand.

    Science.gov (United States)

    Soekadar, Surjo R; Witkowski, Matthias; Vitiello, Nicola; Birbaumer, Niels

    2015-06-01

    The loss of hand function can result in severe physical and psychosocial impairment. Thus, compensation of a lost hand function using assistive robotics that can be operated in daily life is very desirable. However, versatile, intuitive, and reliable control of assistive robotics is still an unsolved challenge. Here, we introduce a novel brain/neural-computer interaction (BNCI) system that integrates electroencephalography (EEG) and electrooculography (EOG) to improve control of assistive robotics in daily life environments. To evaluate the applicability and performance of this hybrid approach, five healthy volunteers (HV) (four men, average age 26.5 ± 3.8 years) and a 34-year-old patient with complete finger paralysis due to a brachial plexus injury (BPI) used EEG (condition 1) and EEG/EOG (condition 2) to control grasping motions of a hand exoskeleton. All participants were able to control the BNCI system (BNCI control performance HV: 70.24 ± 16.71%, BPI: 65.93 ± 24.27%), but inclusion of EOG significantly improved performance across all participants (HV: 80.65 ± 11.28, BPI: 76.03 ± 18.32%). This suggests that hybrid BNCI systems can achieve substantially better control over assistive devices, e.g., a hand exoskeleton, than systems using brain signals alone and thus may increase applicability of brain-controlled assistive devices in daily life environments.

  20. Evolution of the Brain Computing Interface (BCI and Proposed Electroencephalography (EEG Signals Based Authentication Model

    Directory of Open Access Journals (Sweden)

    Ramzan Qaseem

    2018-01-01

    Full Text Available With current advancements in the field of Brain Computer interface it is required to study how it will affect the other technologies currently in use. In this paper, the authors motivate the need of Brain Computing Interface in the era of IoT (Internet of Things, and analyze how BCI in the presence of IoT could have serious privacy breach if not protected by new kind of more secure protocols. Security breach and hacking has been around for a long time but now we are sensitive towards data as our lives depend on it. When everything is interconnected through IoT and considering that we control all interconnected things by means of our brain using BCI (Brain Computer Interface, the meaning of security breach becomes much more sensitive than in the past. This paper describes the old security methods being used for authentication and how they can be compromised. Considering the sensitivity of data in the era of IoT, a new form of authentication is required, which should incorporate BCI rather than usual authentication techniques.

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

    NARCIS (Netherlands)

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

    2015-01-01

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

  2. EpiTools, A software suite for presurgical brain mapping in epilepsy: Intracerebral EEG.

    Science.gov (United States)

    Medina Villalon, S; Paz, R; Roehri, N; Lagarde, S; Pizzo, F; Colombet, B; Bartolomei, F; Carron, R; Bénar, C-G

    2018-03-29

    In pharmacoresistant epilepsy, exploration with depth electrodes can be needed to precisely define the epileptogenic zone. Accurate location of these electrodes is thus essential for the interpretation of Stereotaxic EEG (SEEG) signals. As SEEG analysis increasingly relies on signal processing, it is crucial to make a link between these results and patient's anatomy. Our aims were thus to develop a suite of software tools, called "EpiTools", able to i) precisely and automatically localize the position of each SEEG contact and ii) display the results of signal analysis in each patient's anatomy. The first tool, GARDEL (GUI for Automatic Registration and Depth Electrode Localization), is able to automatically localize SEEG contacts and to label each contact according to a pre-specified nomenclature (for instance that of FreeSurfer or MarsAtlas). The second tool, 3Dviewer, enables to visualize in the 3D anatomy of the patient the origin of signal processing results such as rate of biomarkers, connectivity graphs or Epileptogenicity Index. GARDEL was validated in 30 patients by clinicians and proved to be highly reliable to determine within the patient's individual anatomy the actual location of contacts. GARDEL is a fully automatic electrode localization tool needing limited user interaction (only for electrode naming or contact correction). The 3Dviewer is able to read signal processing results and to display them in link with patient's anatomy. EpiTools can help speeding up the interpretation of SEEG data and improving its precision. Copyright © 2018 Elsevier B.V. All rights reserved.

  3. Clinical and Biochemical Outcomes Following EEG Neurofeedback Training in Traumatic Brain Injury in the Context of Spontaneous Recovery.

    Science.gov (United States)

    Bennett, Cathlyn N; Gupta, Rajnish K; Prabhakar, Puttachandra; Christopher, Rita; Sampath, Somanna; Thennarasu, K; Rajeswaran, Jamuna

    2017-12-01

    It has been found that reduction of posttraumatic stress symptoms is positively associated with the reduction of postconcussive symptoms. Cortisol is commonly used as a biomarker of stress. Understanding the role of posttraumatic stress and cortisol in symptom reduction has implication for neuropsychological rehabilitation particularly in the context of spontaneous recovery. The aim of the research was to study the effectiveness of EEG neurofeedback training on clinical symptoms, perceived stress, and cortisol in traumatic brain injury (TBI) patients in the context of spontaneous recovery. The design was an experimental longitudinal design with the pre-post comparison. The sample comprised 60 patients with the diagnosis of TBI-30 patients in the neurofeedback training (NFT) group and 30 patients in the treatment as usual group (TAU) group. Half of the patients were recruited within 6 months of injury to study the role of spontaneous recovery and the other half were recruited in the 12 to 18 months postinjury phase. Alpha-theta training was given to the NFT group over 20 sessions. Pre and post comparisons were made on clinical symptom rating, perceived stress, and serum cortisol levels. The results indicate significant differences in symptom reporting and perceived stress between the NFT and TAU groups. Significant differences were also seen in cortisol levels with implications for the acute recovery phase. Alpha-theta NFT has a beneficial effect on symptom reduction as well as perceived stress. It also has a beneficial effect on levels of serum cortisol, corroborating these findings.

  4. Neural processing of emotions in traumatized children treated with eye movement desensitization and reprocessing therapy: a hdEEG study

    OpenAIRE

    Trentini, C; Pagani, M; Fania, P; Speranza, AM; Nicolais, G; Sibilia, A; Inguscio, L; Verardo, AR; Fernandez, I; Ammaniti, M

    2015-01-01

    Eye Movement Desensitization and Reprocessing (EMDR) therapy has been proven efficacious in restoring affective regulation in post-traumatic stress disorder (PTSD) patients. However, its effectiveness on emotion processing in children with complex trauma has yet to be explored. High density electroencephalography (hdEEG) was used to investigate the effects of EMDR on brain responses to adults’ emotions on children with histories of early maltreatment. Ten school-aged children were examined be...

  5. Brain states recognition during visual perception by means of artificial neural network in the different EEG frequency ranges

    Science.gov (United States)

    Musatov, V. Yu.; Runnova, A. E.; Andreev, A. V.; Zhuravlev, M. O.

    2018-04-01

    In the present paper, the possibility of classification by artificial neural networks of a certain architecture of ambiguous images is investigated using the example of the Necker cube from the experimentally obtained EEG recording data of several operators. The possibilities of artificial neural network classification of ambiguous images are investigated in the different frequency ranges of EEG recording signals.

  6. Effects of CPAP-therapy on brain electrical activity in obstructive sleep apneic patients: a combined EEG study using LORETA and Omega complexity : reversible alterations of brain activity in OSAS.

    Science.gov (United States)

    Toth, Marton; Faludi, Bela; Kondakor, Istvan

    2012-10-01

    Effects of initiation of continuous positive airway pressure (CPAP) therapy on EEG background activity were investigated in patients with obstructive sleep apnea syndrome (OSAS, N = 25) to test possible reversibility of alterations of brain electrical activity caused by chronic hypoxia. Normal control group (N = 14) was also examined. Two EEG examinations were done in each groups: at night and in the next morning. Global and regional (left vs. right, anterior vs. posterior) measures of spatial complexity (Omega complexity) were used to characterize the degree of spatial synchrony of EEG. Low resolution electromagnetic tomography (LORETA) was used to localize generators of EEG activity in separate frequency bands. Before CPAP-treatment, a significantly lower Omega complexity was found globally and over the right hemisphere. Due to CPAP-treatment, these significant differences vanished. Significantly decreased Omega complexity was found in the anterior region after treatment. LORETA showed a decreased activity in all of the beta bands after therapy in the right hippocampus, premotor and temporo-parietal cortex, and bilaterally in the precuneus, paracentral and posterior cingulate cortex. No significant changes were seen in control group. Comparing controls and patients before sleep, an increased alpha2 band activity was seen bilaterally in the precuneus, paracentral and posterior cingulate cortex, while in the morning an increased beta3 band activity in the left precentral and bilateral premotor cortex and a decreased delta band activity in the right temporo-parietal cortex and insula were observed. These findings indicate that effect of sleep on EEG background activity is different in OSAS patients and normal controls. In OSAS patients, significant changes lead to a more normal EEG after a night under CPAP-treatment. Compensatory alterations of brain electrical activity in regions associated with influencing sympathetic outflow, visuospatial abilities, long

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

    DEFF Research Database (Denmark)

    Cantou, Pauline; Platel, Hervé; Desgranges, Béatrice

    2017-01-01

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

  8. Eye-gaze independent EEG-based brain-computer interfaces for communication

    Science.gov (United States)

    Riccio, A.; Mattia, D.; Simione, L.; Olivetti, M.; Cincotti, F.

    2012-08-01

    The present review systematically examines the literature reporting gaze independent interaction modalities in non-invasive brain-computer interfaces (BCIs) for communication. BCIs measure signals related to specific brain activity and translate them into device control signals. This technology can be used to provide users with severe motor disability (e.g. late stage amyotrophic lateral sclerosis (ALS); acquired brain injury) with an assistive device that does not rely on muscular contraction. Most of the studies on BCIs explored mental tasks and paradigms using visual modality. Considering that in ALS patients the oculomotor control can deteriorate and also other potential users could have impaired visual function, tactile and auditory modalities have been investigated over the past years to seek alternative BCI systems which are independent from vision. In addition, various attentional mechanisms, such as covert attention and feature-directed attention, have been investigated to develop gaze independent visual-based BCI paradigms. Three areas of research were considered in the present review: (i) auditory BCIs, (ii) tactile BCIs and (iii) independent visual BCIs. Out of a total of 130 search results, 34 articles were selected on the basis of pre-defined exclusion criteria. Thirteen articles dealt with independent visual BCIs, 15 reported on auditory BCIs and the last six on tactile BCIs, respectively. From the review of the available literature, it can be concluded that a crucial point is represented by the trade-off between BCI systems/paradigms with high accuracy and speed, but highly demanding in terms of attention and memory load, and systems requiring lower cognitive effort but with a limited amount of communicable information. These issues should be considered as priorities to be explored in future studies to meet users’ requirements in a real-life scenario.

  9. Z-score linear discriminant analysis for EEG based brain-computer interfaces.

    Directory of Open Access Journals (Sweden)

    Rui Zhang

    Full Text Available Linear discriminant analysis (LDA is one of the most popular classification algorithms for brain-computer interfaces (BCI. LDA assumes Gaussian distribution of the data, with equal covariance matrices for the concerned classes, however, the assumption is not usually held in actual BCI applications, where the heteroscedastic class distributions are usually observed. This paper proposes an enhanced version of LDA, namely z-score linear discriminant analysis (Z-LDA, which introduces a new decision boundary definition strategy to handle with the heteroscedastic class distributions. Z-LDA defines decision boundary through z-score utilizing both mean and standard deviation information of the projected data, which can adaptively adjust the decision boundary to fit for heteroscedastic distribution situation. Results derived from both simulation dataset and two actual BCI datasets consistently show that Z-LDA achieves significantly higher average classification accuracies than conventional LDA, indicating the superiority of the new proposed decision boundary definition strategy.

  10. 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

  11. sw-SVM: sensor weighting support vector machines for EEG-based brain-computer interfaces.

    Science.gov (United States)

    Jrad, N; Congedo, M; Phlypo, R; Rousseau, S; Flamary, R; Yger, F; Rakotomamonjy, A

    2011-10-01

    In many machine learning applications, like brain-computer interfaces (BCI), high-dimensional sensor array data are available. Sensor measurements are often highly correlated and signal-to-noise ratio is not homogeneously spread across sensors. Thus, collected data are highly variable and discrimination tasks are challenging. In this work, we focus on sensor weighting as an efficient tool to improve the classification procedure. We present an approach integrating sensor weighting in the classification framework. Sensor weights are considered as hyper-parameters to be learned by a support vector machine (SVM). The resulting sensor weighting SVM (sw-SVM) is designed to satisfy a margin criterion, that is, the generalization error. Experimental studies on two data sets are presented, a P300 data set and an error-related potential (ErrP) data set. For the P300 data set (BCI competition III), for which a large number of trials is available, the sw-SVM proves to perform equivalently with respect to the ensemble SVM strategy that won the competition. For the ErrP data set, for which a small number of trials are available, the sw-SVM shows superior performances as compared to three state-of-the art approaches. Results suggest that the sw-SVM promises to be useful in event-related potentials classification, even with a small number of training trials.

  12. Classification of EEG-P300 Signals Extracted from Brain Activities in BCI Systems Using ν-SVM and BLDA Algorithms

    Directory of Open Access Journals (Sweden)

    Ali MOMENNEZHAD

    2014-06-01

    Full Text Available In this paper, a linear predictive coding (LPC model is used to improve classification accuracy, convergent speed to maximum accuracy, and maximum bitrates in brain computer interface (BCI system based on extracting EEG-P300 signals. First, EEG signal is filtered in order to eliminate high frequency noise. Then, the parameters of filtered EEG signal are extracted using LPC model. Finally, the samples are reconstructed by LPC coefficients and two classifiers, a Bayesian Linear discriminant analysis (BLDA, and b the υ-support vector machine (υ-SVM are applied in order to classify. The proposed algorithm performance is compared with fisher linear discriminant analysis (FLDA. Results show that the efficiency of our algorithm in improving classification accuracy and convergent speed to maximum accuracy are much better. As example at the proposed algorithms, respectively BLDA with LPC model and υ-SVM with LPC model with8 electrode configuration for subject S1 the total classification accuracy is improved as 9.4% and 1.7%. And also, subject 7 at BLDA and υ-SVM with LPC model algorithms (LPC+BLDA and LPC+ υ-SVM after block 11th converged to maximum accuracy but Fisher Linear Discriminant Analysis (FLDA algorithm did not converge to maximum accuracy (with the same configuration. So, it can be used as a promising tool in designing BCI systems.

  13. High density harp for SSCL linac

    International Nuclear Information System (INIS)

    Fritsche, C.T.; Krogh, M.L.; Crist, C.E.

    1993-01-01

    AlliedSignal Inc., Kansas City Division, and the Superconducting Super Collider Laboratory (SSCL) are collaboratively developing a high density harp for the SSCL linac. This harp is designed using hybrid microcircuit (HMC) technology to obtain a higher wire density than previously available. The developed harp contains one hundred twenty-eight 33-micron-diameter carbon wires on 0.38-mm centers. The harp features an onboard broken wire detection circuit. Carbon wire preparation and attachment processes were developed. High density surface mount connectors were located. The status of high density harp development will be presented along with planned future activities

  14. High density harp for SSCL linac

    International Nuclear Information System (INIS)

    Fritsche, C.T.; Krogh, M.L.

    1993-05-01

    AlliedSignal Inc., Kansas City Division, and the Superconducting Super Collider Laboratory (SSCL) are collaboratively developing a high density harp for the SSCL linac. This harp is designed using hybrid microcircuit (HMC) technology to obtain a higher wire density than previously available. The developed harp contains one hundred twenty-eight 33-micron-diameter carbon wires on 0.38-mm centers. The harp features an onboard broken wire detection circuit. Carbon wire preparation and attachment processes were developed. High density surface mount connectors were located. The status of high density harp development will be presented along with planned future activities

  15. Functional Disorganization of Small-World Brain Networks in mild Alzheimer’s Disease and amnestic Mild Cognitive Impairment: An EEG Study using Relative Wavelet Entropy (RWE

    Directory of Open Access Journals (Sweden)

    Christos A. Frantzidis

    2014-08-01

    Full Text Available Previous neuroscientific findings have linked Alzheimer’s disease (AD with less efficient information processing and brain network disorganization. However, pathological alterations of the brain networks during the preclinical phase of amnestic Mild Cognitive Impairment (aMCI remain largely unknown. The present study aimed at comparing patterns of the detection of functional disorganization in MCI relative to Mild Dementia (MD. Participants consisted of 23 cognitively healthy adults, 17 aMCI and 24 mild AD patients who underwent electroencephalographic (EEG data acquisition during a resting-state condition. Synchronization analysis through the Orthogonal Discrete Wavelet Transform (ODWT, and directional brain network analysis were applied on the EEG data. This computational model was performed for networks that have the same number of edges (N=500, 600, 700, 800 edges across all participants and groups (fixed density values. All groups exhibited a small-world (SW brain architecture. However, we found a significant reduction in the SW brain architecture in both aMCI and MD patients relative to the group of Healthy controls. This functional disorganization was also correlated with the participant’s generic cognitive status. The deterioration of the network’s organization was caused mainly by deficient local information processing as quantified by the mean cluster coefficient value. Functional hubs were identified through the normalized betweenness centrality metric. Analysis of the local characteristics showed relative hub preservation even with statistically significant reduced strength. Compensatory phenomena were also evident through the formation of additional hubs on left frontal and parietal regions. Our results indicate a declined functional network organization even during the prodromal phase. Degeneration is evident even in the preclinical phase and coexists with transient network reorganization due to compensation.

  16. Design and optimization of an EEG-based brain machine interface (BMI to an upper-limb exoskeleton for stroke survivors

    Directory of Open Access Journals (Sweden)

    Nikunj Arunkumar Bhagat

    2016-03-01

    Full Text Available This study demonstrates the feasibility of detecting motor intent from brain activity of chronic stroke patients using an asynchronous electroencephalography (EEG-based brain machine interface (BMI. Intent was inferred from movement related cortical potentials (MRCPs measured over an optimized set of EEG electrodes. Successful intent detection triggered the motion of an upper-limb exoskeleton (MAHI Exo-II, to guide movement and to encourage active user participation by providing instantaneous sensory feedback. Several BMI design features were optimized to increase system performance in the presence of single-trial variability of MRCPs in the injured brain: 1 an adaptive time window was used for extracting features during BMI calibration; 2 training data from two consecutive days were pooled for BMI calibration to increase robustness to handle the day-to-day variations typical of EEG, and 3 BMI predictions were gated by residual electromyography (EMG activity from the impaired arm, to reduce the number of false positives. This patient-specific BMI calibration approach can accommodate a broad spectrum of stroke patients with diverse motor capabilities. Following BMI optimization on day 3, testing of the closed-loop BMI-MAHI exoskeleton, on 4th and 5th days of the study, showed consistent BMI performance with overall mean true positive rate (TPR = 62.7 +/- 21.4 % on day 4 and 67.1 +/- 14.6 % on day 5. The overall false positive rate (FPR across subjects was 27.74 +/- 37.46 % on day 4 and 27.5 +/- 35.64 % on day 5; however for two subjects who had residual motor function and could benefit from the EMG-gated BMI, the mean FPR was quite low (< 10 %. On average, motor intent was detected -367 +/- 328 ms before movement onset during closed-loop operation. These findings provide evidence that closed-loop EEG-based BMI for stroke patients can be designed and optimized to perform well across multiple days without system recalibration.

  17. Design and Optimization of an EEG-Based Brain Machine Interface (BMI) to an Upper-Limb Exoskeleton for Stroke Survivors

    Science.gov (United States)

    Bhagat, Nikunj A.; Venkatakrishnan, Anusha; Abibullaev, Berdakh; Artz, Edward J.; Yozbatiran, Nuray; Blank, Amy A.; French, James; Karmonik, Christof; Grossman, Robert G.; O'Malley, Marcia K.; Francisco, Gerard E.; Contreras-Vidal, Jose L.

    2016-01-01

    This study demonstrates the feasibility of detecting motor intent from brain activity of chronic stroke patients using an asynchronous electroencephalography (EEG)-based brain machine interface (BMI). Intent was inferred from movement related cortical potentials (MRCPs) measured over an optimized set of EEG electrodes. Successful intent detection triggered the motion of an upper-limb exoskeleton (MAHI Exo-II), to guide movement and to encourage active user participation by providing instantaneous sensory feedback. Several BMI design features were optimized to increase system performance in the presence of single-trial variability of MRCPs in the injured brain: (1) an adaptive time window was used for extracting features during BMI calibration; (2) training data from two consecutive days were pooled for BMI calibration to increase robustness to handle the day-to-day variations typical of EEG, and (3) BMI predictions were gated by residual electromyography (EMG) activity from the impaired arm, to reduce the number of false positives. This patient-specific BMI calibration approach can accommodate a broad spectrum of stroke patients with diverse motor capabilities. Following BMI optimization on day 3, testing of the closed-loop BMI-MAHI exoskeleton, on 4th and 5th days of the study, showed consistent BMI performance with overall mean true positive rate (TPR) = 62.7 ± 21.4% on day 4 and 67.1 ± 14.6% on day 5. The overall false positive rate (FPR) across subjects was 27.74 ± 37.46% on day 4 and 27.5 ± 35.64% on day 5; however for two subjects who had residual motor function and could benefit from the EMG-gated BMI, the mean FPR was quite low (< 10%). On average, motor intent was detected −367 ± 328 ms before movement onset during closed-loop operation. These findings provide evidence that closed-loop EEG-based BMI for stroke patients can be designed and optimized to perform well across multiple days without system recalibration. PMID:27065787

  18. Modified CC-LR algorithm with three diverse feature sets for motor imagery tasks classification in EEG based brain-computer interface.

    Science.gov (United States)

    Siuly; Li, Yan; Paul Wen, Peng

    2014-03-01

    Motor imagery (MI) tasks classification provides an important basis for designing brain-computer interface (BCI) systems. If the MI tasks are reliably distinguished through identifying typical patterns in electroencephalography (EEG) data, a motor disabled people could communicate with a device by composing sequences of these mental states. In our earlier study, we developed a cross-correlation based logistic regression (CC-LR) algorithm for the classification of MI tasks for BCI applications, but its performance was not satisfactory. This study develops a modified version of the CC-LR algorithm exploring a suitable feature set that can improve the performance. The modified CC-LR algorithm uses the C3 electrode channel (in the international 10-20 system) as a reference channel for the cross-correlation (CC) technique and applies three diverse feature sets separately, as the input to the logistic regression (LR) classifier. The present algorithm investigates which feature set is the best to characterize the distribution of MI tasks based EEG data. This study also provides an insight into how to select a reference channel for the CC technique with EEG signals considering the anatomical structure of the human brain. The proposed algorithm is compared with eight of the most recently reported well-known methods including the BCI III Winner algorithm. The findings of this study indicate that the modified CC-LR algorithm has potential to improve the identification performance of MI tasks in BCI systems. The results demonstrate that the proposed technique provides a classification improvement over the existing methods tested. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  19. INTELLIGENT EEG ANALYSIS

    Directory of Open Access Journals (Sweden)

    M. Murugesan

    2011-04-01

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

  20. Design of an EEG-based brain-computer interface (BCI) from standard components running in real-time under Windows.

    Science.gov (United States)

    Guger, C; Schlögl, A; Walterspacher, D; Pfurtscheller, G

    1999-01-01

    An EEG-based brain-computer interface (BCI) is a direct connection between the human brain and the computer. Such a communication system is needed by patients with severe motor impairments (e.g. late stage of Amyotrophic Lateral Sclerosis) and has to operate in real-time. This paper describes the selection of the appropriate components to construct such a BCI and focuses also on the selection of a suitable programming language and operating system. The multichannel system runs under Windows 95, equipped with a real-time Kernel expansion to obtain reasonable real-time operations on a standard PC. Matlab controls the data acquisition and the presentation of the experimental paradigm, while Simulink is used to calculate the recursive least square (RLS) algorithm that describes the current state of the EEG in real-time. First results of the new low-cost BCI show that the accuracy of differentiating imagination of left and right hand movement is around 95%.

  1. Wake High-Density Electroencephalographic Spatiospectral Signatures of Insomnia

    Science.gov (United States)

    Colombo, Michele A.; Ramautar, Jennifer R.; Wei, Yishul; Gomez-Herrero, Germán; Stoffers, Diederick; Wassing, Rick; Benjamins, Jeroen S.; Tagliazucchi, Enzo; van der Werf, Ysbrand D.; Cajochen, Christian; Van Someren, Eus J.W.

    2016-01-01

    Study Objectives: Although daytime complaints are a defining characteristic of insomnia, most EEG studies evaluated sleep only. We used high-density electroencephalography to investigate wake resting state oscillations characteristic of insomnia disorder (ID) at a fine-grained spatiospectral resolution. Methods: A case-control assessment during eyes open (EO) and eyes closed (EC) was performed in a laboratory for human physiology. Participants (n = 94, 74 female, 21–70 y) were recruited through www.sleepregistry.nl: 51 with ID, according to DSM-5 and 43 matched controls. Exclusion criteria were any somatic, neurological or psychiatric condition. Group differences in the spectral power topographies across multiple frequencies (1.5 to 40 Hz) were evaluated using permutation-based inference with Threshold-Free Cluster-Enhancement, to correct for multiple comparisons. Results: As compared to controls, participants with ID showed less power in a narrow upper alpha band (11–12.7 Hz, peak: 11.7 Hz) over bilateral frontal and left temporal regions during EO, and more power in a broad beta frequency range (16.3–40 Hz, peak: 19 Hz) globally during EC. Source estimates suggested global rather than cortically localized group differences. Conclusions: The widespread high power in a broad beta band reported previously during sleep in insomnia is present as well during eyes closed wakefulness, suggestive of a round-the-clock hyperarousal. Low power in the upper alpha band during eyes open is consistent with low cortical inhibition and attentional filtering. The fine-grained HD-EEG findings suggest that, while more feasible than PSG, wake EEG of short duration with a few well-chosen electrodes and frequency bands, can provide valuable features of insomnia. Citation: Colombo MA, Ramautar JR, Wei Y, Gomez-Herrero G, Stoffers D, Wassing R, Benjamins JS, Tagliazucchi E, van der Werf YD, Cajochen C, Van Someren EJW. Wake high-density electroencephalographic spatiospectral

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

    Science.gov (United States)

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

    2017-01-01

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

  3. Near-infrared spectroscopy (NIRS - electroencephalography (EEG based brain-state dependent electrotherapy (BSDE: A computational approach based on excitation-inhibition balance hypothesis

    Directory of Open Access Journals (Sweden)

    Snigdha Dagar

    2016-08-01

    Full Text Available Stroke is the leading cause of severe chronic disability and the second cause of death worldwide with 15 million new cases and 50 million stroke survivors. The post stroke chronic disability may be ameliorated with early neuro rehabilitation where non-invasive brain stimulation (NIBS techniques can be used as an adjuvant treatment to hasten the effects. However, the heterogeneity in the lesioned brain will require individualized NIBS intervention where innovative neuroimaging technologies of portable electroencephalography (EEG and functional-near-infrared spectroscopy (fNIRS can be leveraged for Brain State Dependent Electrotherapy (BSDE. In this hypothesis and theory article, we propose a computational approach based on excitation-inhibition (E-I balance hypothesis to objectively quantify the post stroke individual brain state using online fNIRS-EEG joint imaging. One of the key events that occurs following Stroke is the imbalance in local excitation-inhibition (that is the ratio of Glutamate/GABA which may be targeted with NIBS using a computational pipeline that includes individual forward models to predict current flow patterns through the lesioned brain or brain target region. The current flow will polarize the neurons which can be captured with excitation-inhibition based brain models. Furthermore, E-I balance hypothesis can be used to find the consequences of cellular polarization on neuronal information processing which can then be implicated in changes in function. We first review evidence that shows how this local imbalance between excitation-inhibition leading to functional dysfunction can be restored in targeted sites with NIBS (Motor Cortex, Somatosensory Cortex resulting in large scale plastic reorganization over the cortex, and probably facilitating recovery of functions. Secondly, we show evidence how BSDE based on inhibition–excitation balance hypothesis may target a specific brain site or network as an adjuvant treatment

  4. High Density Digital Data Storage System

    Science.gov (United States)

    Wright, Kenneth D., II; Gray, David L.; Rowland, Wayne D.

    1991-01-01

    The High Density Digital Data Storage System was designed to provide a cost effective means for storing real-time data from the field-deployable digital acoustic measurement system. However, the high density data storage system is a standalone system that could provide a storage solution for many other real time data acquisition applications. The storage system has inputs for up to 20 channels of 16-bit digital data. The high density tape recorders presently being used in the storage system are capable of storing over 5 gigabytes of data at overall transfer rates of 500 kilobytes per second. However, through the use of data compression techniques the system storage capacity and transfer rate can be doubled. Two tape recorders have been incorporated into the storage system to produce a backup tape of data in real-time. An analog output is provided for each data channel as a means of monitoring the data as it is being recorded.

  5. Experienced Mindfulness Meditators Exhibit Higher Parietal-Occipital EEG Gamma Activity during NREM Sleep

    Science.gov (United States)

    Ferrarelli, Fabio; Smith, Richard; Dentico, Daniela; Riedner, Brady A.; Zennig, Corinna; Benca, Ruth M.; Lutz, Antoine; Davidson, Richard J.; Tononi, Giulio

    2013-01-01

    Over the past several years meditation practice has gained increasing attention as a non-pharmacological intervention to provide health related benefits, from promoting general wellness to alleviating the symptoms of a variety of medical conditions. However, the effects of meditation training on brain activity still need to be fully characterized. Sleep provides a unique approach to explore the meditation-related plastic changes in brain function. In this study we performed sleep high-density electroencephalographic (hdEEG) recordings in long-term meditators (LTM) of Buddhist meditation practices (approximately 8700 mean hours of life practice) and meditation naive individuals. We found that LTM had increased parietal-occipital EEG gamma power during NREM sleep. This increase was specific for the gamma range (25–40 Hz), was not related to the level of spontaneous arousal during NREM and was positively correlated with the length of lifetime daily meditation practice. Altogether, these findings indicate that meditation practice produces measurable changes in spontaneous brain activity, and suggest that EEG gamma activity during sleep represents a sensitive measure of the long-lasting, plastic effects of meditative training on brain function. PMID:24015304

  6. Magnetization of High Density Hadronic Fluid

    DEFF Research Database (Denmark)

    Bohr, Henrik; Providencia, Constanca; da Providencia, João

    2012-01-01

    In the present paper the magnetization of a high density relativistic fluid of elementary particles is studied. At very high densities, such as may be found in the interior of a neutron star, when the external magnetic field is gradually increased, the energy of the normal phase of the fluid...... in the particle fluid. For nuclear densities above 2 to 3 rho(0), where rho(0) is the equilibrium nuclear density, the resulting magnetic field turns out to be rather huge, of the order of 10(17) Gauss....

  7. Presentation of 60 Cases of Infantile Spasms Based on Etiology, Clinical Manifestation EEG and Brain CT Scan in Mofid Children Hospital

    Directory of Open Access Journals (Sweden)

    Mohammad Mehdi Taghdiri

    2002-06-01

    Full Text Available Objective: Among different epileptic syndrome infantile spasm is one of the most malignant forms which cause irrepairable brain damage in the child. Consequently the longer this type of epilepsy lasts the more harmful results will follow. The majority of children with infantile spasm are younger than one year age and only 5 percent of affected children are in the age group above one year. Materials & Methods: This descriptive study was done on 60 (36 male and 24 female infants 2-24 months age with clinical examination, observation, interview and questionnaire  in pediatric neurology department of Mofid children hospital during two years. Results: From 60 patients (36 male and 24 female, 48 case (80% symptomatic and 12 case (20% cryptogenic and idiopathic. Based on clinical manifestation 35 case (58% were flexor type. 6 case (10% extensor and 19 cases (32% mixed. In EEG hypsarrhythmia in all patients was seen. Brain CT scan in 11 cases showed brain atrophy and in remainder was normal. Conclusion: In our study etiologically symptomatic and clinically flexor type was more common. Hysparrhythmia in all patients was seen and brain CT scan in 80% of patients was normal.

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

    Science.gov (United States)

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

    2000-12-22

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

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

    Science.gov (United States)

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

    2013-06-01

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

  10. 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.

  11. Supernovae and high density nuclear matter

    International Nuclear Information System (INIS)

    Kahana, S.

    1986-01-01

    The role of the nuclear equation of state (EOS) in producing prompt supernova explosions is examined. Results of calculations of Baron, Cooperstein, and Kahana incorporating general relativity and a new high density EOS are presented, and the relevance of these calculations to laboratory experiments with heavy ions considered. 31 refs., 6 figs., 2 tabs

  12. Supernovae and high density nuclear matter

    Energy Technology Data Exchange (ETDEWEB)

    Kahana, S.

    1986-01-01

    The role of the nuclear equation of state (EOS) in producing prompt supernova explosions is examined. Results of calculations of Baron, Cooperstein, and Kahana incorporating general relativity and a new high density EOS are presented, and the relevance of these calculations to laboratory experiments with heavy ions considered. 31 refs., 6 figs., 2 tabs.

  13. High Density GEOSAT/GM Altimeter Data

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The high density Geosat/GM altimeter data south of 30 S have finally arrived. In addition, ERS-1 has completed more than 6 cycles of its 35-day repeat track. These...

  14. High density aseismic spent fuel storage racks

    International Nuclear Information System (INIS)

    Louvat, J.P.

    1985-05-01

    After the reasons of the development of high density aseismic spent fuel racks by FRAMATOME and LEMER, a description is presented, as also the codes, standards and regulations used to design this FRAMATOME storage rack. Tests have been carried out concerning criticality, irradiation of Cadminox, corrosion of the cell, and the seismic behaviour

  15. Variation in anticonvulsant selection and EEG monitoring following severe traumatic brain injury in children – Understanding resource availability in sites participating in a comparative effectiveness study

    Science.gov (United States)

    Kurz, Jonathan E.; Poloyac, Samuel M.; Abend, Nicholas S.; Fabio, Anthony; Bell, Michael J.; Wainwright, Mark S.

    2016-01-01

    Objective Early post-traumatic seizures (PTS) may contribute to worsened outcomes after traumatic brain injury (TBI). Evidence to guide the evaluation and management of early PTS in children is limited. We undertook a survey of current practices of continuous electroencephalographic monitoring (cEEG), seizure prophylaxis and the management of early PTS to provide essential information for trial design and the development of PTS management pathways. Design Surveys were sent to site principal investigators at all 43 sites participating in the ADAPT (Approaches and Decisions in Acute Pediatric TBI) trial at the time of the survey. Surveys consisted of 12 questions addressing strategies to (i) implement cEEG monitoring, (ii) PTS prophylaxis, (iii) treat acute PTS, (iv) treat status epilepticus (SE) and refractory status epilepticus (RSE) and (v) monitor anti-seizure drug levels. Setting Institutions comprised a mixture of free-standing children’s hospitals and university medical centers across the United States and Europe. Measurements and Main Results cEEG monitoring was available in the pediatric intensive care unit in the overwhelming majority of clinical sites (98%); however, the plans to operationalize such monitoring for children varied considerably. A similar majority of sites report that administration of prophylactic anti-seizure medications is anticipated in children (93%), yet a minority reports that a specified protocol for treatment of PTS is in place (43%). Reported medication choices varied substantially between sites, but the majority of sites reported pentobarbital for RSE (81%). Presence of an treatment protocols for seizure prophylaxis, early PTS, post-traumatic SE and RSE was associated with decreased reported medications (all p pediatric severe TBI. The substantial variation in cEEG implementation, choice of seizure prophylaxis medications, and management of early PTS across institutions was reported, signifying areas of clinical uncertainty that

  16. Brain-Computer Interfaces for 1-D and 2-D Cursor Control: Designs Using Volitional Control of the EEG Spectrum or Steady-State Visual Evoked Potentials

    Science.gov (United States)

    Trejo, Leonard J.; Matthews, Bryan; Rosipal, Roman

    2005-01-01

    We have developed and tested two EEG-based brain-computer interfaces (BCI) for users to control a cursor on a computer display. Our system uses an adaptive algorithm, based on kernel partial least squares classification (KPLS), to associate patterns in multichannel EEG frequency spectra with cursor controls. Our first BCI, Target Practice, is a system for one-dimensional device control, in which participants use biofeedback to learn voluntary control of their EEG spectra. Target Practice uses a KF LS classifier to map power spectra of 30-electrode EEG signals to rightward or leftward position of a moving cursor on a computer display. Three subjects learned to control motion of a cursor on a video display in multiple blocks of 60 trials over periods of up to six weeks. The best subject s average skill in correct selection of the cursor direction grew from 58% to 88% after 13 training sessions. Target Practice also implements online control of two artifact sources: a) removal of ocular artifact by linear subtraction of wavelet-smoothed vertical and horizontal EOG signals, b) control of muscle artifact by inhibition of BCI training during periods of relatively high power in the 40-64 Hz band. The second BCI, Think Pointer, is a system for two-dimensional cursor control. Steady-state visual evoked potentials (SSVEP) are triggered by four flickering checkerboard stimuli located in narrow strips at each edge of the display. The user attends to one of the four beacons to initiate motion in the desired direction. The SSVEP signals are recorded from eight electrodes located over the occipital region. A KPLS classifier is individually calibrated to map multichannel frequency bands of the SSVEP signals to right-left or up-down motion of a cursor on a computer display. The display stops moving when the user attends to a central fixation point. As for Target Practice, Think Pointer also implements wavelet-based online removal of ocular artifact; however, in Think Pointer muscle

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

    Science.gov (United States)

    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

  18. Preterm EEG: a multimodal neurophysiological protocol.

    Science.gov (United States)

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

    2012-02-18

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

  19. Expanding the (kaleido)scope: exploring current literature trends for translating electroencephalography (EEG) based brain-computer interfaces for motor rehabilitation in children

    Science.gov (United States)

    Kinney-Lang, E.; Auyeung, B.; Escudero, J.

    2016-12-01

    Rehabilitation applications using brain-computer interfaces (BCI) have recently shown encouraging results for motor recovery. Effective BCI neurorehabilitation has been shown to exploit neuroplastic properties of the brain through mental imagery tasks. However, these applications and results are currently restricted to adults. A systematic search reveals there is essentially no literature describing motor rehabilitative BCI applications that use electroencephalograms (EEG) in children, despite advances in such applications with adults. Further inspection highlights limited literature pursuing research in the field, especially outside of neurofeedback paradigms. Then the question naturally arises, do current literature trends indicate that EEG based BCI motor rehabilitation applications could be translated to children? To provide further evidence beyond the available literature for this particular topic, we present an exploratory survey examining some of the indirect literature related to motor rehabilitation BCI in children. Our goal is to establish if evidence in the related literature supports research on this topic and if the related studies can help explain the dearth of current research in this area. The investigation found positive literature trends in the indirect studies which support translating these BCI applications to children and provide insight into potential pitfalls perhaps responsible for the limited literature. Careful consideration of these pitfalls in conjunction with support from the literature emphasize that fully realized motor rehabilitation BCI applications for children are feasible and would be beneficial. • BCI intervention has improved motor recovery in adult patients and offer supplementary rehabilitation options to patients. • A systematic literature search revealed that essentially no research has been conducted bringing motor rehabilitation BCI applications to children, despite advances in BCI. • Indirect studies discovered

  20. Expanding the (kaleido)scope: exploring current literature trends for translating electroencephalography (EEG) based brain-computer interfaces for motor rehabilitation in children.

    Science.gov (United States)

    Kinney-Lang, E; Auyeung, B; Escudero, J

    2016-12-01

    Rehabilitation applications using brain-computer interfaces (BCI) have recently shown encouraging results for motor recovery. Effective BCI neurorehabilitation has been shown to exploit neuroplastic properties of the brain through mental imagery tasks. However, these applications and results are currently restricted to adults. A systematic search reveals there is essentially no literature describing motor rehabilitative BCI applications that use electroencephalograms (EEG) in children, despite advances in such applications with adults. Further inspection highlights limited literature pursuing research in the field, especially outside of neurofeedback paradigms. Then the question naturally arises, do current literature trends indicate that EEG based BCI motor rehabilitation applications could be translated to children? To provide further evidence beyond the available literature for this particular topic, we present an exploratory survey examining some of the indirect literature related to motor rehabilitation BCI in children. Our goal is to establish if evidence in the related literature supports research on this topic and if the related studies can help explain the dearth of current research in this area. The investigation found positive literature trends in the indirect studies which support translating these BCI applications to children and provide insight into potential pitfalls perhaps responsible for the limited literature. Careful consideration of these pitfalls in conjunction with support from the literature emphasize that fully realized motor rehabilitation BCI applications for children are feasible and would be beneficial. •  BCI intervention has improved motor recovery in adult patients and offer supplementary rehabilitation options to patients. •  A systematic literature search revealed that essentially no research has been conducted bringing motor rehabilitation BCI applications to children, despite advances in BCI. •  Indirect studies

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

    Science.gov (United States)

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

    2013-01-01

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

  2. 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.

  3. Analysis of connectivity in NeuCube spiking neural network models trained on EEG data for the understanding of functional changes in the brain: A case study on opiate dependence treatment.

    Science.gov (United States)

    Capecci, Elisa; Kasabov, Nikola; Wang, Grace Y

    2015-08-01

    The paper presents a methodology for the analysis of functional changes in brain activity across different conditions and different groups of subjects. This analysis is based on the recently proposed NeuCube spiking neural network (SNN) framework and more specifically on the analysis of the connectivity of a NeuCube model trained with electroencephalography (EEG) data. The case study data used to illustrate this method is EEG data collected from three groups-subjects with opiate addiction, patients undertaking methadone maintenance treatment, and non-drug users/healthy control group. The proposed method classifies more accurately the EEG data than traditional statistical and artificial intelligence (AI) methods and can be used to predict response to treatment and dose-related drug effect. But more importantly, the method can be used to compare functional brain activities of different subjects and the changes of these activities as a result of treatment, which is a step towards a better understanding of both the EEG data and the brain processes that generated it. The method can also be used for a wide range of applications, such as a better understanding of disease progression or aging. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Some recent efforts toward high density implosions

    International Nuclear Information System (INIS)

    McClellan, G.E.

    1980-01-01

    Some recent Livermore efforts towards achieving high-density implosions are presented. The implosion dynamics necessary to compress DT fuel to 10 to 100 times liquid density are discussed. Methods of diagnosing the maximum DT density for a specific design are presented along with results to date. The dynamics of the double-shelled target with an exploding outer shell are described, and some preliminary experimental results are presented

  5. Framatome offers new high density Cadminox racks

    International Nuclear Information System (INIS)

    Anon.

    1985-01-01

    Framatome have developed a new material called Cadminox for use in high density spent fuel storage racks. It is claimed that Cadminox will remain stable stable in pond storage when racks submerged in boronated water are irradiated by the spent fuel they contain. A brief description of the storage module is given, including the aseismic bearing device which minimises loads on pond walls, racks and fuel assemblies. (UK)

  6. Spin polarization in high density quark matter

    DEFF Research Database (Denmark)

    Bohr, Henrik; Panda, Prafulla K.; Providênci, Constanca

    2013-01-01

    We investigate the occurrence of a ferromagnetic phase transition in high density hadronic matter (e.g., in the interior of a neutron star). This could be induced by a four-fermion interaction analogous to the one which is responsible for chiral symmetry breaking in the Nambu-Jona-Lasinio model, ...... the so-called 2 flavor super-conducting phase to the ferromagnetic phase arises. The color-flavor-locked phase may be completely hidden by the FP....

  7. The car parking problem at high densities

    Science.gov (United States)

    Burgos, E.; Bonadeo, H.

    1989-04-01

    The radial distribution functions of random 1-D systems of sequential hard rods have been studied in the range of very high densities. It is found that as the number of samples rejected before completion increases, anomalies in the pairwise distribution functions arise. These are discussed using analytical solutions for systems of three rods and numerical simulations with twelve rods. The probabilities of different spatial orderings with respect to the sequential order are examined.

  8. EEG in connection with coma.

    Science.gov (United States)

    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.

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

    LENUS (Irish Health Repository)

    McHugh, J C

    2009-09-01

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

  10. Involvement of the anterior cingulate cortex in time-based prospective memory task monitoring: An EEG analysis of brain sources using Independent Component and Measure Projection Analysis.

    Directory of Open Access Journals (Sweden)

    Gabriela Cruz

    Full Text Available Time-based prospective memory (PM, remembering to do something at a particular moment in the future, is considered to depend upon self-initiated strategic monitoring, involving a retrieval mode (sustained maintenance of the intention plus target checking (intermittent time checks. The present experiment was designed to explore what brain regions and brain activity are associated with these components of strategic monitoring in time-based PM tasks.24 participants were asked to reset a clock every four minutes, while performing a foreground ongoing word categorisation task. EEG activity was recorded and data were decomposed into source-resolved activity using Independent Component Analysis. Common brain regions across participants, associated with retrieval mode and target checking, were found using Measure Projection Analysis.Participants decreased their performance on the ongoing task when concurrently performed with the time-based PM task, reflecting an active retrieval mode that relied on withdrawal of limited resources from the ongoing task. Brain activity, with its source in or near the anterior cingulate cortex (ACC, showed changes associated with an active retrieval mode including greater negative ERP deflections, decreased theta synchronization, and increased alpha suppression for events locked to the ongoing task while maintaining a time-based intention. Activity in the ACC was also associated with time-checks and found consistently across participants; however, we did not find an association with time perception processing per se.The involvement of the ACC in both aspects of time-based PM monitoring may be related to different functions that have been attributed to it: strategic control of attention during the retrieval mode (distributing attentional resources between the ongoing task and the time-based task and anticipatory/decision making processing associated with clock-checks.

  11. EEG Negativity in Fixations Used for Gaze-Based Control: Toward Converting Intentions into Actions with an Eye-Brain-Computer Interface

    Science.gov (United States)

    Shishkin, Sergei L.; Nuzhdin, Yuri O.; Svirin, Evgeny P.; Trofimov, Alexander G.; Fedorova, Anastasia A.; Kozyrskiy, Bogdan L.; Velichkovsky, Boris M.

    2016-01-01

    We usually look at an object when we are going to manipulate it. Thus, eye tracking can be used to communicate intended actions. An effective human-machine interface, however, should be able to differentiate intentional and spontaneous eye movements. We report an electroencephalogram (EEG) marker that differentiates gaze fixations used for control from spontaneous fixations involved in visual exploration. Eight healthy participants played a game with their eye movements only. Their gaze-synchronized EEG data (fixation-related potentials, FRPs) were collected during game's control-on and control-off conditions. A slow negative wave with a maximum in the parietooccipital region was present in each participant's averaged FRPs in the control-on conditions and was absent or had much lower amplitude in the control-off condition. This wave was similar but not identical to stimulus-preceding negativity, a slow negative wave that can be observed during feedback expectation. Classification of intentional vs. spontaneous fixations was based on amplitude features from 13 EEG channels using 300 ms length segments free from electrooculogram contamination (200–500 ms relative to the fixation onset). For the first fixations in the fixation triplets required to make moves in the game, classified against control-off data, a committee of greedy classifiers provided 0.90 ± 0.07 specificity and 0.38 ± 0.14 sensitivity. Similar (slightly lower) results were obtained for the shrinkage Linear Discriminate Analysis (LDA) classifier. The second and third fixations in the triplets were classified at lower rate. We expect that, with improved feature sets and classifiers, a hybrid dwell-based Eye-Brain-Computer Interface (EBCI) can be built using the FRP difference between the intended and spontaneous fixations. If this direction of BCI development will be successful, such a multimodal interface may improve the fluency of interaction and can possibly become the basis for a new input device

  12. EEG Negativity in Fixations Used for Gaze-Based Control: Toward Converting Intentions into Actions with an Eye-Brain-Computer Interface

    Directory of Open Access Journals (Sweden)

    Sergei L. Shishkin

    2016-11-01

    Full Text Available We usually look at an object when we are going to manipulate it. Thus, eye tracking can be used to communicate intended actions. An effective human-machine interface, however, should be able to differentiate intentional and spontaneous eye movements. We report an electroencephalogram (EEG marker that differentiates gaze fixations used for control from spontaneous fixations involved in visual exploration. Eight healthy participants played a game with their eye movements only. Their gaze-synchronized EEG data (fixation-related potentials, FRPs were collected during game’s control-on and control-off conditions. A slow negative wave with a maximum in the parietooccipital region was present in each participant’s averaged FRPs in the control-on conditions and was absent or had much lower amplitude in the control-off condition. This wave was similar but not identical to stimulus-preceding negativity, a slow negative wave that can be observed during feedback expectation. Classification of intentional vs. spontaneous fixations was based on amplitude features from 13 EEG channels using 300 ms length segments free from electrooculogram contamination (200..500 ms relative to the fixation onset. For the first fixations in the fixation triplets required to make moves in the game, classified against control-off data, a committee of greedy classifiers provided 0.90 ± 0.07 specificity and 0.38 ± 0.14 sensitivity. Similar (slightly lower results were obtained for the shrinkage LDA classifier. The second and third fixations in the triplets were classified at lower rate. We expect that, with improved feature sets and classifiers, a hybrid dwell-based Eye-Brain-Computer Interface (EBCI can be built using the FRP difference between the intended and spontaneous fixations. If this direction of BCI development will be successful, such a multimodal interface may improve the fluency of interaction and can possibly become the basis for a new input device for

  13. A review and experimental study on the application of classifiers and evolutionary algorithms in EEG-based brain-machine interface systems

    Science.gov (United States)

    Tahernezhad-Javazm, Farajollah; Azimirad, Vahid; Shoaran, Maryam

    2018-04-01

    Objective. Considering the importance and the near-future development of noninvasive brain-machine interface (BMI) systems, this paper presents a comprehensive theoretical-experimental survey on the classification and evolutionary methods for BMI-based systems in which EEG signals are used. Approach. The paper is divided into two main parts. In the first part, a wide range of different types of the base and combinatorial classifiers including boosting and bagging classifiers and evolutionary algorithms are reviewed and investigated. In the second part, these classifiers and evolutionary algorithms are assessed and compared based on two types of relatively widely used BMI systems, sensory motor rhythm-BMI and event-related potentials-BMI. Moreover, in the second part, some of the improved evolutionary algorithms as well as bi-objective algorithms are experimentally assessed and compared. Main results. In this study two databases are used, and cross-validation accuracy (CVA) and stability to data volume (SDV) are considered as the evaluation criteria for the classifiers. According to the experimental results on both databases, regarding the base classifiers, linear discriminant analysis and support vector machines with respect to CVA evaluation metric, and naive Bayes with respect to SDV demonstrated the best performances. Among the combinatorial classifiers, four classifiers, Bagg-DT (bagging decision tree), LogitBoost, and GentleBoost with respect to CVA, and Bagging-LR (bagging logistic regression) and AdaBoost (adaptive boosting) with respect to SDV had the best performances. Finally, regarding the evolutionary algorithms, single-objective invasive weed optimization (IWO) and bi-objective nondominated sorting IWO algorithms demonstrated the best performances. Significance. We present a general survey on the base and the combinatorial classification methods for EEG signals (sensory motor rhythm and event-related potentials) as well as their optimization methods

  14. User Adapted Motor-Imaginary Brain-Computer Interface by means of EEG Channel Selection Based on Estimation of Distributed Algorithms

    Directory of Open Access Journals (Sweden)

    Aitzol Astigarraga

    2016-01-01

    Full Text Available Brain-Computer Interfaces (BCIs have become a research field with interesting applications, and it can be inferred from published papers that different persons activate different parts of the brain to perform the same action. This paper presents a personalized interface design method, for electroencephalogram- (EEG- based BCIs, based on channel selection. We describe a novel two-step method in which firstly a computationally inexpensive greedy algorithm finds an adequate search range; and, then, an Estimation of Distribution Algorithm (EDA is applied in the reduced range to obtain the optimal channel subset. The use of the EDA allows us to select the most interacting channels subset, removing the irrelevant and noisy ones, thus selecting the most discriminative subset of channels for each user improving accuracy. The method is tested on the IIIa dataset from the BCI competition III. Experimental results show that the resulting channel subset is consistent with motor-imaginary-related neurophysiological principles and, on the other hand, optimizes performance reducing the number of channels.

  15. High density data recording for SSCL linac

    International Nuclear Information System (INIS)

    VanDeusen, A.L.; Crist, C.

    1993-01-01

    The Superconducting Super Collider Laboratory and AlliedSignal Aerospace have collaboratively developed a high density data monitoring system for beam diagnostic activities. The 128 channel data system is based on a custom multi-channel high speed digitizer card for the VXI bus. The card is referred to as a Modular Input VXI (MIX) digitizer. Multiple MIX cards are used in the complete system to achieve the necessary high channel density requirements. Each MIX digitizer card also contains programmable signal conditioning, and enough local memory to complete an entire beam scan without assistance from the host processor

  16. Plasma Diagnostics in High Density Reactors

    International Nuclear Information System (INIS)

    Daltrini, A. M.; Moshkalyov, S.; Monteiro, M. J. R.; Machida, M.; Kostryukov, A.; Besseler, E.; Biasotto, C.; Diniz, J. A.

    2006-01-01

    Langmuir electric probes and optical emission spectroscopy diagnostics were developed for applications in high density plasmas. These diagnostics were employed in two plasma sources: an electron cyclotron resonance (ECR) plasma and an RF driven inductively coupled plasma (ICP) plasma. Langmuir probes were tested using a number of probing dimensions, probe tip materials, circuits for probe bias and filters. Then, the results were compared with the optical spectroscopy measurements. With these diagnostics, analyses of various plasma processes were performed in both reactors. For example, it has been shown that species like NH radicals generated in gas phase can have critical impact on films deposited by ECR plasmas. In the ICP source, plasmas in atomic and molecular gases were shown to have different spatial distributions, likely due to nonlocal electron heating. The low-to-high density transitions in the ICP plasma were also studied. The role of metastables is shown to be significant in Ar plasmas, in contrast to plasmas with additions of molecular gases

  17. Models for Experimental High Density Housing

    Science.gov (United States)

    Bradecki, Tomasz; Swoboda, Julia; Nowak, Katarzyna; Dziechciarz, Klaudia

    2017-10-01

    The article presents the effects of research on models of high density housing. The authors present urban projects for experimental high density housing estates. The design was based on research performed on 38 examples of similar housing in Poland that have been built after 2003. Some of the case studies show extreme density and that inspired the researchers to test individual virtual solutions that would answer the question: How far can we push the limits? The experimental housing projects show strengths and weaknesses of design driven only by such indexes as FAR (floor attenuation ratio - housing density) and DPH (dwellings per hectare). Although such projects are implemented, the authors believe that there are reasons for limits since high index values may be in contradiction to the optimum character of housing environment. Virtual models on virtual plots presented by the authors were oriented toward maximising the DPH index and DAI (dwellings area index) which is very often the main driver for developers. The authors also raise the question of sustainability of such solutions. The research was carried out in the URBAN model research group (Gliwice, Poland) that consists of academic researchers and architecture students. The models reflect architectural and urban regulations that are valid in Poland. Conclusions might be helpful for urban planners, urban designers, developers, architects and architecture students.

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

    African Journals Online (AJOL)

    salah

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

  19. Prediction of treatment outcome in patients with obsessive-compulsive disorder with Low-Resolution Brain Electromagnetic Tomography: a prospective EEG study

    Directory of Open Access Journals (Sweden)

    Daniela eKrause

    2016-01-01

    Full Text Available The issue of predicting treatment response and identifying, in advance, which patient will profit from treating obsessive-compulsive disorder (OCD seems to be an elusive goal. This prospective study investigated brain electric activity (using Low-Resolution Brain Electromagnetic Tomography (LORETA for the purpose of predicting response to treatment. Forty-one unmedicated patients with a DSM-IV diagnosis of OCD were included. A resting 32-channel EEG was obtained from each participant before and after ten weeks of standardized treatment with sertraline and behavioral therapy. LORETA was used to localize the sources of brain electrical activity. At week ten, patients were divided into responders and non-responders (according to a reduction of symptom severity > 50% on the Y-BOCS. LORETA analysis revealed that at baseline responders showed compared to non-responders a significantly lower brain electric activity within the beta 1 (t=2.86, p<0.05, 2 (t=2.81, p<0.05 and 3 (t=2.76, p<0.05 frequency bands and ROI analysis confirmed a reduced activity in alpha 2 (t=2.06, p<0.05 in the anterior cingulate cortex (ACC. When baseline LORETA data were compared to follow-up data, the analysis showed in the responder group a significantly lower brain electrical resting activity in the beta 1 (t=3.17. p<0.05 and beta 3 (t=3.11. p<0.05 frequency bands and equally for the ROI analysis of the orbitofrontal cortex (OFC in the alpha 2 (t=2.15. p<0.05 frequency band. In the group of non-responders the opposite results were found. In addition, a positive correlation between frequency alpha 2 (rho=0.40, p=0.010, beta 3 (rho=0.42, p=0.006, delta (rho=0.33, p=0.038, theta (rho=0.34, p=0.031, alpha 1 (rho=0.38, p=0.015 and beta1 (rho=0.34, p=0.028 of the OFC and the bands delta (rho=0.33, p=0.035, alpha 1 (rho=0.36, p=0.019, alpha 2 (rho=0.34, p=0.031 and beta 3 (rho=0.38, p=0.015 of the ACC with a reduction of the Y-BOCS scores was identified.Our results suggest that

  20. EEG frequency PCA in EEG-ERP dynamics.

    Science.gov (United States)

    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.

  1. The speed of passionate love, as a subliminal prime: A high-density electrical neuroimaging stud

    OpenAIRE

    Cacioppo Stephanie; Grafton Scott T.; Bianchi-Demicheli F

    2012-01-01

    In line with the psychological model of self expansion recent neuroimaging evidence shows an overlap between the brain network mediating passionate love and that involved in self representation. Nevertheless little remains known about the temporal dynamics of these brain areas. To address this question we recorded brain activity from 20 healthy participants using high density electrophysiological recordings while participants were performing a cognitive priming paradigm known to activate the ...

  2. Nanotechnology for Synthetic High Density Lipoproteins

    Science.gov (United States)

    Luthi, Andrea J.; Patel, Pinal C.; Ko, Caroline H.; Mutharasan, R. Kannan; Mirkin, Chad A.; Thaxton, C. Shad

    2014-01-01

    Atherosclerosis is the disease mechanism responsible for coronary heart disease (CHD), the leading cause of death worldwide. One strategy to combat atherosclerosis is to increase the amount of circulating high density lipoproteins (HDL), which transport cholesterol from peripheral tissues to the liver for excretion. The process, known as reverse cholesterol transport, is thought to be one of the main reasons for the significant inverse correlation observed between HDL blood levels and the development of CHD. This article highlights the most common strategies for treating atherosclerosis using HDL. We further detail potential treatment opportunities that utilize nanotechnology to increase the amount of HDL in circulation. The synthesis of biomimetic HDL nanostructures that replicate the chemical and physical properties of natural HDL provides novel materials for investigating the structure-function relationships of HDL and for potential new therapeutics to combat CHD. PMID:21087901

  3. Ground state of high-density matter

    Science.gov (United States)

    Copeland, ED; Kolb, Edward W.; Lee, Kimyeong

    1988-01-01

    It is shown that if an upper bound to the false vacuum energy of the electroweak Higgs potential is satisfied, the true ground state of high-density matter is not nuclear matter, or even strange-quark matter, but rather a non-topological soliton where the electroweak symmetry is exact and the fermions are massless. This possibility is examined in the standard SU(3) sub C tensor product SU(2) sub L tensor product U(1) sub Y model. The bound to the false vacuum energy is satisfied only for a narrow range of the Higgs boson masses in the minimal electroweak model (within about 10 eV of its minimum allowed value of 6.6 GeV) and a somewhat wider range for electroweak models with a non-minimal Higgs sector.

  4. High Density Lipoprotein and it's Dysfunction.

    Science.gov (United States)

    Eren, Esin; Yilmaz, Necat; Aydin, Ozgur

    2012-01-01

    Plasma high-density lipoprotein cholesterol(HDL-C) levels do not predict functionality and composition of high-density lipoprotein(HDL). Traditionally, keeping levels of low-density lipoprotein cholesterol(LDL-C) down and HDL-C up have been the goal of patients to prevent atherosclerosis that can lead to coronary vascular disease(CVD). People think about the HDL present in their cholesterol test, but not about its functional capability. Up to 65% of cardiovascular death cannot be prevented by putative LDL-C lowering agents. It well explains the strong interest in HDL increasing strategies. However, recent studies have questioned the good in using drugs to increase level of HDL. While raising HDL is a theoretically attractive target, the optimal approach remains uncertain. The attention has turned to the quality, rather than the quantity, of HDL-C. An alternative to elevations in HDL involves strategies to enhance HDL functionality. The situation poses an opportunity for clinical chemists to take the lead in the development and validation of such biomarkers. The best known function of HDL is the capacity to promote cellular cholesterol efflux from peripheral cells and deliver cholesterol to the liver for excretion, thereby playing a key role in reverse cholesterol transport (RCT). The functions of HDL that have recently attracted attention include anti-inflammatory and anti-oxidant activities. High antioxidant and anti-inflammatory activities of HDL are associated with protection from CVD.This review addresses the current state of knowledge regarding assays of HDL functions and their relationship to CVD. HDL as a therapeutic target is the new frontier with huge potential for positive public health implications.

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

    Directory of Open Access Journals (Sweden)

    Galina V. Portnova

    2018-01-01

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

  6. Brain signal analysis using EEG and Entropy to study the effect of physical and mental tasks on cognitive performance

    Directory of Open Access Journals (Sweden)

    Dineshen Chuckravanen

    2015-07-01

    Full Text Available Some theoretical control models posit that the fatigue which is developed during physical activity is not always peripheral and it is the brain which causes this feeling of fatigue. This fatigue develops due to a decrease of metabolic resources to and from the brain that modulates physical performance. Therefore, this research was conducted to find out if there was finite level ofmetabolic energy resources in the brain, by performing both mental and physical activities to exhaustion. It was found that there was an overflow of information during the exercise-involved experiment. The circular relationship between fatigue, cognitive performance and arousal state insinuates that one should apply more effort to maintain performance levels which would require more energy resources that eventually accelerates the development of fatigue. Thus, there appeared to be a limited amount of energy resources in the brain as shown by the cognitive performance of the participants.

  7. Amplitude spectrum EEG signal evidence for the dissociation of motor and perceptual spatial working memory in the human brain.

    Science.gov (United States)

    Smyrnis, Nikolaos; Protopapa, Foteini; Tsoukas, Evangelos; Balogh, Allison; Siettos, Constantinos I; Evdokimidis, Ioannis

    2014-02-01

    This study investigated the question whether spatial working memory related to movement plans (motor working memory) and spatial working memory related to spatial attention and perceptual processes (perceptual spatial working memory) share the same neurophysiological substrate or there is evidence for separate motor and perceptual working memory streams of processing. Towards this aim, ten healthy human subjects performed delayed responses to visual targets presented at different spatial locations. Two tasks were attained, one in which the spatial location of the target was the goal for a pointing movement and one in which the spatial location of the target was used for a perceptual (yes or no) change detection. Each task involved two conditions: a memory condition in which the target remained visible only for the first 250 ms of the delay period and a delay condition in which the target location remained visible throughout the delay period. The amplitude spectrum analysis of the EEG revealed that the alpha (8-12 Hz) band signal was smaller, while the beta (13-30 Hz) and gamma (30-45 Hz) band signals were larger in the memory compared to the non-memory condition. The alpha band signal difference was confined to the frontal midline area; the beta band signal difference extended over the right hemisphere and midline central area, and the gamma band signal difference was confined to the right occipitoparietal area. Importantly, both in beta and gamma bands, we observed a significant increase in the movement-related compared to the perceptual-related memory-specific amplitude spectrum signal in the central midline area. This result provides clear evidence for the dissociation of motor and perceptual spatial working memory.

  8. Correlation between intra- and extracranial background EEG

    DEFF Research Database (Denmark)

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

    2012-01-01

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

  9. Electroencephalographic (eeg coherence between visual and motor areas of the left and the right brain hemisphere while performing visuomotor task with the right and the left hand

    Directory of Open Access Journals (Sweden)

    Simon Brežan

    2007-09-01

    Full Text Available Background: Unilateral limb movements are based on the activation of contralateral primary motor cortex and the bilateral activation of premotor cortices. Performance of a visuomotor task requires a visuomotor integration between motor and visual cortical areas. The functional integration (»binding« of different brain areas, is probably mediated by the synchronous neuronal oscillatory activity, which can be determined by electroencephalographic (EEG coherence analysis. We introduced a new method of coherence analysis and compared coherence and power spectra in the left and right hemisphere for the right vs. left hand visuomotor task, hypothesizing that the increase in coherence and decrease in power spectra while performing the task would be greater in the contralateral hemisphere.Methods: We analyzed 6 healthy subjects and recorded their electroencephalogram during visuomotor task with the right or the left hand. For data analysis, a special Matlab computer programme was designed. The results were statistically analysed by a two-way analysis of variance, one-way analysis of variance and post-hoc t-tests with Bonferroni correction.Results: We demonstrated a significant increase in coherence (p < 0.05 for the visuomotor task compared to control tasks in alpha (8–13 Hz in beta 1 (13–20 Hz frequency bands between visual and motor electrodes. There were no significant differences in coherence nor power spectra depending on the hand used. The changes of coherence and power spectra between both hemispheres were symmetrical.Conclusions: In previous studies, a specific increase of coherence and decrease of power spectra for the visuomotor task was found, but we found no conclusive asymmetries when performing the task with right vs. left hand. This could be explained in a way that increases in coherence and decreases of power spectra reflect symmetrical activation and cooperation between more complex visual and motor brain areas.

  10. High-density lipoprotein cholesterol: How High

    Directory of Open Access Journals (Sweden)

    G Rajagopal

    2012-01-01

    Full Text Available The high-density lipoprotein cholesterol (HDL-C is considered anti-atherogenic good cholesterol. It is involved in reverse transport of lipids. Epidemiological studies have found inverse relationship of HDL-C and coronary heart disease (CHD risk. When grouped according to HDL-C, subjects having HDL-C more than 60 mg/dL had lesser risk of CHD than those having HDL-C of 40-60 mg/dL, who in turn had lesser risk than those who had HDL-C less than 40 mg/dL. No upper limit for beneficial effect of HDL-C on CHD risk has been identified. The goals of treating patients with low HDL-C have not been firmly established. Though many drugs are known to improve HDL-C concentration, statins are proven to improve CHD risk and mortality. Cholesteryl ester transfer protein (CETP is involved in metabolism of HDL-C and its inhibitors are actively being screened for clinical utility. However, final answer is still awaited on CETP-inhibitors.

  11. High-density hybrid interconnect methodologies

    International Nuclear Information System (INIS)

    John, J.; Zimmermann, L.; Moor, P.De; Hoof, C.Van

    2003-01-01

    Full text: The presentation gives an overview of the state-of-the-art of hybrid integration and in particular the IMEC technological approaches that will be able to address future hybrid detector needs. The dense hybrid flip-chip integration of an array of detectors and its dedicated readout electronics can be achieved with a variety of solderbump techniques such as pure Indium or Indium alloys, Ph-In, Ni/PbSn, but also conducting polymers... Particularly for cooled applications or ultra-high density applications, Indium solderbump technology (electroplated or evaporated) is the method of choice. The state-of-the-art of solderbump technologies that are to a high degree independent of the underlying detector material will be presented and examples of interconnect densities between 5x1E4cm-2 and 1x1E6 cm-2 will be demonstrated. For several classes of detectors, flip-chip integration is not allowed since the detectors have to be illuminated from the top. This applies to image sensors for EUV applications such as GaN/AlGaN based detectors and to MEMS-based sensors. In such cases, the only viable interconnection method has to be through the (thinned) detector wafer followed by a solderbump-based integration. The approaches for dense and ultra-dense through-the-wafer interconnect 'vias' will be presented and wafer thinning approaches will be shown

  12. HIGH DENSITY QCD WITH HEAVY-IONS

    CERN Multimedia

    The Addendum 1 to Volume 2 of the CMS Physics TDR has been published The Heavy-Ion analysis group completed the writing of a TDR summarizing the CMS plans in using heavy ion collisions to study high density QCD. The document was submitted to the LHCC in March and presented in the Open Session of the LHCC on May 9th. The study of heavy-ion physics at the LHC is promising to be very exciting. LHC will open a new energy frontier in ultra-relativistic heavy-ion physics. The collision energy of heavy nuclei at sNN = 5.5 TeV will be thirty times larger than what is presently available at RHIC. We will certainly probe quark and gluon matter at unprecedented values of energy density. The prime goal of this research programme is to study the fundamental theory of the strong interaction - Quantum Chromodynamics (QCD) - in extreme conditions of temperature, density and parton momentum fraction (low-x). Such studies, with impressive experimental and theoretical advances in recent years thanks to the wealth of high-qua...

  13. High-density oxidized porous silicon

    International Nuclear Information System (INIS)

    Gharbi, Ahmed; Souifi, Abdelkader; Remaki, Boudjemaa; Halimaoui, Aomar; Bensahel, Daniel

    2012-01-01

    We have studied oxidized porous silicon (OPS) properties using Fourier transform infraRed (FTIR) spectroscopy and capacitance–voltage C–V measurements. We report the first experimental determination of the optimum porosity allowing the elaboration of high-density OPS insulators. This is an important contribution to the research of thick integrated electrical insulators on porous silicon based on an optimized process ensuring dielectric quality (complete oxidation) and mechanical and chemical reliability (no residual pores or silicon crystallites). Through the measurement of the refractive indexes of the porous silicon (PS) layer before and after oxidation, one can determine the structural composition of the OPS material in silicon, air and silica. We have experimentally demonstrated that a porosity approaching 56% of the as-prepared PS layer is required to ensure a complete oxidation of PS without residual silicon crystallites and with minimum porosity. The effective dielectric constant values of OPS materials determined from capacitance–voltage C–V measurements are discussed and compared to FTIR results predictions. (paper)

  14. Potential brain language reorganization in a boy with refractory epilepsy; an fNIRS–EEG and fMRI comparison

    Directory of Open Access Journals (Sweden)

    Phetsamone Vannasing

    2016-01-01

    Full Text Available As part of a presurgical investigation for a resection of a tumor located in the left temporal brain region, we evaluated pre- and postsurgical language lateralization in a right-handed boy with refractory epilepsy. In this study, we compared functional near infrared spectroscopy (fNIRS results obtained while the participant performed expressive and receptive language tasks with those obtained using functional magnetic resonance imaging (fMRI. This case study illustrates the potential for NIRS to contribute favorably to the localization of language functions in children with epilepsy and cognitive or behavioral problems and its potential advantages over fMRI in presurgical assessment. Moreover, it suggests that fNIRS is sensitive in localizing an atypical language network or potential brain reorganization related to epilepsy in young patients.

  15. An Efficient Framework for EEG Analysis with Application to Hybrid Brain Computer Interfaces Based on Motor Imagery and P300

    Directory of Open Access Journals (Sweden)

    Jinyi Long

    2017-01-01

    Full Text Available The hybrid brain computer interface (BCI based on motor imagery (MI and P300 has been a preferred strategy aiming to improve the detection performance through combining the features of each. However, current methods used for combining these two modalities optimize them separately, which does not result in optimal performance. Here, we present an efficient framework to optimize them together by concatenating the features of MI and P300 in a block diagonal form. Then a linear classifier under a dual spectral norm regularizer is applied to the combined features. Under this framework, the hybrid features of MI and P300 can be learned, selected, and combined together directly. Experimental results on the data set of hybrid BCI based on MI and P300 are provided to illustrate competitive performance of the proposed method against other conventional methods. This provides an evidence that the method used here contributes to the discrimination performance of the brain state in hybrid BCI.

  16. EOG Artifacts Removal in EEG Measurements for Affective Interaction

    NARCIS (Netherlands)

    Qi, Wen

    2014-01-01

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

  17. Investigation of the Correlation Between Neurocognitive Function with Advanced Magnetic Resonance Imaging (MRI), Electroencephalography (EEG) in Patients with Traumatic Brain Injury Exposure: Neurocognitive function and advanced MRI and EEG

    Science.gov (United States)

    2011-01-01

    child (MVA007), pneumonia (MVA017), urinary infection (MVA018), appendix (MVA026), a leg fracture (MVA008), and tonsils and fractures (MVA019). The...Toronto CR 2011-015 59 Glossary ..... DTI – diffusion tensor imaging EEG – electroencephalography FLAIR – fluid-attenuated inversion recovery

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

    Science.gov (United States)

    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

  19. Brain Oscillatory and Hemodynamic Activity in a Bimanual Coordination Task Following Transcranial Alternating Current Stimulation (tACS): A Combined EEG-fNIRS Study.

    Science.gov (United States)

    Berger, Alisa; Pixa, Nils H; Steinberg, Fabian; Doppelmayr, Michael

    2018-01-01

    Motor control is associated with synchronized oscillatory activity at alpha (8-12 Hz) and beta (12-30 Hz) frequencies in a cerebello-thalamo-cortical network. Previous studies demonstrated that transcranial alternating current stimulation (tACS) is capable of entraining ongoing oscillatory activity while also modulating motor control. However, the modulatory effects of tACS on both motor control and its underlying electro- and neurophysiological mechanisms remain ambiguous. Thus, the purpose of this study was to contribute to gathering neurophysiological knowledge regarding tACS effects by investigating the after-effects of 10 Hz tACS and 20 Hz tACS at parietal brain areas on bimanual coordination and its concurrent oscillatory and hemodynamic activity. Twenty-four right-handed healthy volunteers (12 females) aged between 18 and 30 ( M = 22.35 ± 3.62) participated in the study and performed a coordination task requiring bimanual movements. Concurrent to bimanual motor training, participants received either 10 Hz tACS, 20 Hz tACS or a sham stimulation over the parietal cortex (at P3/P4 electrode positions) for 20 min via small gel electrodes (3,14 cm 2 Ag/AgCl, amperage = 1 mA). Before and three time-points after tACS (immediately, 30 min and 1 day), bimanual coordination performance was assessed. Oscillatory activities were measured by electroencephalography (EEG) and hemodynamic changes were examined using functional near-infrared spectroscopy (fNIRS). Improvements of bimanual coordination performance were not differently between groups, thus, no tACS-specific effect on bimanual coordination performance emerged. However, physiological measures during the task revealed significant increases in parietal alpha activity immediately following 10 Hz tACS and 20 Hz tACS which were accompanied by significant decreases of Hboxy concentration in the right hemispheric motor cortex compared to the sham group. Based on the physiological responses, we conclude that t

  20. Brain Oscillatory and Hemodynamic Activity in a Bimanual Coordination Task Following Transcranial Alternating Current Stimulation (tACS: A Combined EEG-fNIRS Study

    Directory of Open Access Journals (Sweden)

    Alisa Berger

    2018-04-01

    Full Text Available Motor control is associated with synchronized oscillatory activity at alpha (8–12 Hz and beta (12–30 Hz frequencies in a cerebello-thalamo-cortical network. Previous studies demonstrated that transcranial alternating current stimulation (tACS is capable of entraining ongoing oscillatory activity while also modulating motor control. However, the modulatory effects of tACS on both motor control and its underlying electro- and neurophysiological mechanisms remain ambiguous. Thus, the purpose of this study was to contribute to gathering neurophysiological knowledge regarding tACS effects by investigating the after-effects of 10 Hz tACS and 20 Hz tACS at parietal brain areas on bimanual coordination and its concurrent oscillatory and hemodynamic activity. Twenty-four right-handed healthy volunteers (12 females aged between 18 and 30 (M = 22.35 ± 3.62 participated in the study and performed a coordination task requiring bimanual movements. Concurrent to bimanual motor training, participants received either 10 Hz tACS, 20 Hz tACS or a sham stimulation over the parietal cortex (at P3/P4 electrode positions for 20 min via small gel electrodes (3,14 cm2 Ag/AgCl, amperage = 1 mA. Before and three time-points after tACS (immediately, 30 min and 1 day, bimanual coordination performance was assessed. Oscillatory activities were measured by electroencephalography (EEG and hemodynamic changes were examined using functional near-infrared spectroscopy (fNIRS. Improvements of bimanual coordination performance were not differently between groups, thus, no tACS-specific effect on bimanual coordination performance emerged. However, physiological measures during the task revealed significant increases in parietal alpha activity immediately following 10 Hz tACS and 20 Hz tACS which were accompanied by significant decreases of Hboxy concentration in the right hemispheric motor cortex compared to the sham group. Based on the physiological responses, we conclude that

  1. Dual-EEG of joint finger tapping: what can two interacting brains teach us about social interaction?

    DEFF Research Database (Denmark)

    Konvalinka, Ivana

    -frequency analysis revealed a left-motor and right-frontal suppression at 10 Hz during task execution, when carrying the task out interactively in contrast with the uncoupled computer-driven task. We used machine-learning approaches to identify the brain signals driving the interaction. The raw-power at 10 Hz during...... tapping emanating from electrodes of member one and member two were used as features. We combined data from both participants in each pair, and applied logistic regression using feature selection in order to classify the two conditions. The first seven (frontal) electrodes consistently emerged as good...... classifiers, with 85-99% accuracy. There was a tendency for one member’s frontal electrodes to drive the classifier over the other’s, which predicted the leader of the interaction in 8/9 pairs. This study reveals new neural mechanisms underlying two-person interactions. It also shows how analyzing two...

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

    Science.gov (United States)

    Ying, Xiaoguo; Lin, Han; Hui, Guohua

    2015-01-01

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

  3. Contribution of EEG in transient neurological deficits.

    Science.gov (United States)

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

    2018-01-01

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

  4. Deep brain stimulation of the nucleus basalis of Meynert attenuates early EEG components associated with defective sensory gating in patients with Alzheimer disease - a two-case study.

    Science.gov (United States)

    Dürschmid, Stefan; Reichert, Christoph; Kuhn, Jens; Freund, Hans-Joachim; Hinrichs, Hermann; Heinze, Hans-Jochen

    2017-10-20

    Alzheimer's disease (AD) is associated with deterioration of memory and cognitive function and a degeneration of neurons of the nucleus basalis of Meynert (NBM). The NBM is the major input source of acetylcholine (ACh) to the cortex. The decreasing cholinergic innervation of the cortex due to degeneration of the NBM might be the cause of loss of memory function. NBM-Deep brain stimulation (NBM-DBS) is considered to serve as a potential therapeutic option for patients with AD by supporting residual cholinergic transmission to stabilize oscillatory activity in memory-relevant circuits. However, whether DBS could improve sensory memory functions in patients with AD is not clear. Here, in a passive auditory oddball paradigm, patients with AD (N = 2) listened to repetitive background tones (standard tones) randomly interrupted by frequency deviants in two blocks with NBM-DBS OFF and then NBM-DBS ON, while age-matched healthy controls (N = 6) repeated the experiment twice. The mismatch negativity in NBM-DBS OFF significantly differed from controls in both blocks, but not under NBM-DBS, which was likely due to a pronounced P50 increase overlapping with the N1 in NBM-DBS OFF. This early complex of EEG components recovered under stimulation to a normal level as defined by responses in controls. In this temporal interval, we found in patients with NBM-DBS ON (but not with NBM-DBS OFF) and in controls a strong repetition suppression effect to standard tones - with more attenuated responses to frequently repeated standard tones. This highlights the role of NBM-DBS for sensory gating of familiar auditory information into sensory memory. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

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

    Directory of Open Access Journals (Sweden)

    Azeez eAdebimpe

    2016-03-01

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

  6. 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.

  7. 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.)

  8. 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.)

  9. PENGEMBANGAN ALAT BANTU PEMODELAN TERAPI LENGAN PASCA STROKE DENGAN MEMANFAATKAN SINYAL ELECTROENCEPHALOGRAPHY (EEG) MENGGUNAKAN EMOTIV

    OpenAIRE

    Fatmawati, Ester; Prawito, Prawito; Wijaya, Sastra Kusuma

    2016-01-01

    Design modeling has been done post-stroke therapy arm by utilizing command brain signals generated by Electroencephalography (EEG). EEG signals provides a lot of information, one of which is motor information. Every body moving describe the unique form of brain signals. In conditions paralysis, motor information on the EEG signals will still be found when someone tries to move his limbs. The basic concepts of this study are the EEG signal acquisition using the Emotiv EPOC +, controling signal...

  10. Brain Activity Related to the Judgment of Face-Likeness: Correlation between EEG and Face-Like Evaluation.

    Science.gov (United States)

    Nihei, Yuji; Minami, Tetsuto; Nakauchi, Shigeki

    2018-01-01

    Faces represent important information for social communication, because social information, such as face-color, expression, and gender, is obtained from faces. Therefore, individuals' tend to find faces unconsciously, even in objects. Why is face-likeness perceived in non-face objects? Previous event-related potential (ERP) studies showed that the P1 component (early visual processing), the N170 component (face detection), and the N250 component (personal detection) reflect the neural processing of faces. Inverted faces were reported to enhance the amplitude and delay the latency of P1 and N170. To investigate face-likeness processing in the brain, we explored the face-related components of the ERP through a face-like evaluation task using natural faces, cars, insects, and Arcimboldo paintings presented upright or inverted. We found a significant correlation between the inversion effect index and face-like scores in P1 in both hemispheres and in N170 in the right hemisphere. These results suggest that judgment of face-likeness occurs in a relatively early stage of face processing.

  11. Brain Activity Related to the Judgment of Face-Likeness: Correlation between EEG and Face-Like Evaluation

    Directory of Open Access Journals (Sweden)

    Yuji Nihei

    2018-02-01

    Full Text Available Faces represent important information for social communication, because social information, such as face-color, expression, and gender, is obtained from faces. Therefore, individuals' tend to find faces unconsciously, even in objects. Why is face-likeness perceived in non-face objects? Previous event-related potential (ERP studies showed that the P1 component (early visual processing, the N170 component (face detection, and the N250 component (personal detection reflect the neural processing of faces. Inverted faces were reported to enhance the amplitude and delay the latency of P1 and N170. To investigate face-likeness processing in the brain, we explored the face-related components of the ERP through a face-like evaluation task using natural faces, cars, insects, and Arcimboldo paintings presented upright or inverted. We found a significant correlation between the inversion effect index and face-like scores in P1 in both hemispheres and in N170 in the right hemisphere. These results suggest that judgment of face-likeness occurs in a relatively early stage of face processing.

  12. Neural processing of emotions in traumatized children treated with Eye Movement Desensitization and Reprocessing therapy: A hdEEG study

    Directory of Open Access Journals (Sweden)

    Cristina eTrentini

    2015-11-01

    Full Text Available Eye Movement Desensitization and Reprocessing (EMDR therapy has been proven efficacious in restoring affective regulation in Post–Traumatic Stress Disorder (PTSD patients. However, its effectiveness on emotion processing in children with complex trauma has yet to be explored. High density Electroencephalography (hdEEG was used to investigate the effects of EMDR on brain responses to adults’ emotions on children with histories of early maltreatment. Ten school–aged children were examined before (T0 and within one month after the conclusion of EMDR (T1. hdEEGs were recorded while children passively viewed angry, afraid, happy, and neutral faces. Clinical scales were administered at the same time. Correlation analyses were performed to detect brain regions whose activity was linked to children’s traumatic symptom–related and emotional–adaptive problem scores. In all four conditions, hdEEG showed similar significantly higher activity on the right medial prefrontal and fronto–temporal limbic regions at T0, shifting towards the left medial and superior temporal regions at T1. Moreover, significant correlations were found between clinical scales and the same regions whose activity significantly differed between pre– and post–treatment. These preliminary results demonstrate that, after EMDR, children suffering from complex trauma show increased activity in areas implicated in high–order cognitive processing when passively viewing pictures of emotional expressions. These changes are associated with the decrease of depressive and traumatic symptoms, and with the improvement of emotional–adaptive functioning over time.

  13. Neural processing of emotions in traumatized children treated with Eye Movement Desensitization and Reprocessing therapy: a hdEEG study

    Science.gov (United States)

    Trentini, Cristina; Pagani, Marco; Fania, Piercarlo; Speranza, Anna Maria; Nicolais, Giampaolo; Sibilia, Alessandra; Inguscio, Lucio; Verardo, Anna Rita; Fernandez, Isabel; Ammaniti, Massimo

    2015-01-01

    Eye Movement Desensitization and Reprocessing (EMDR) therapy has been proven efficacious in restoring affective regulation in post-traumatic stress disorder (PTSD) patients. However, its effectiveness on emotion processing in children with complex trauma has yet to be explored. High density electroencephalography (hdEEG) was used to investigate the effects of EMDR on brain responses to adults’ emotions on children with histories of early maltreatment. Ten school-aged children were examined before (T0) and within one month after the conclusion of EMDR (T1). hdEEGs were recorded while children passively viewed angry, afraid, happy, and neutral faces. Clinical scales were administered at the same time. Correlation analyses were performed to detect brain regions whose activity was linked to children’s traumatic symptom-related and emotional-adaptive problem scores. In all four conditions, hdEEG showed similar significantly higher activity on the right medial prefrontal and fronto-temporal limbic regions at T0, shifting toward the left medial and superior temporal regions at T1. Moreover, significant correlations were found between clinical scales and the same regions whose activity significantly differed between pre- and post-treatment. These preliminary results demonstrate that, after EMDR, children suffering from complex trauma show increased activity in areas implicated in high-order cognitive processing when passively viewing pictures of emotional expressions. These changes are associated with the decrease of depressive and traumatic symptoms, and with the improvement of emotional-adaptive functioning over time. PMID:26594183

  14. Multifractal analysis of real and imaginary movements: EEG study

    Science.gov (United States)

    Pavlov, Alexey N.; Maksimenko, Vladimir A.; Runnova, Anastasiya E.; Khramova, Marina V.; Pisarchik, Alexander N.

    2018-04-01

    We study abilities of the wavelet-based multifractal analysis in recognition specific dynamics of electrical brain activity associated with real and imaginary movements. Based on the singularity spectra we analyze electroencephalograms (EEGs) acquired in untrained humans (operators) during imagination of hands movements, and show a possibility to distinguish between the related EEG patterns and the recordings performed during real movements or the background electrical brain activity. We discuss how such recognition depends on the selected brain region.

  15. Burst suppression in sleep in a routine outpatient EEG

    Directory of Open Access Journals (Sweden)

    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.

  16. Investigating dynamical information transfer in the brain following a TMS pulse: Insights from structural architecture.

    Science.gov (United States)

    Amico, Enrico; Van Mierlo, Pieter; Marinazzo, Daniele; Laureys, Steven

    2015-01-01

    Transcranial magnetic stimulation (TMS) has been used for more than 20 years to investigate connectivity and plasticity in the human cortex. By combining TMS with high-density electroencephalography (hd-EEG), one can stimulate any cortical area and measure the effects produced by this perturbation in the rest of the cerebral cortex. The purpose of this paper is to investigate changes of information flow in the brain after TMS from a functional and structural perspective, using multimodal modeling of source reconstructed TMS/hd-EEG recordings and DTI tractography. We prove how brain dynamics induced by TMS is constrained and driven by its structure, at different spatial and temporal scales, especially when considering cross-frequency interactions. These results shed light on the function-structure organization of the brain network at the global level, and on the huge variety of information contained in it.

  17. 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.

  18. A pilot randomized controlled trial using EEG-based brain-computer interface training for a Chinese-speaking group of healthy elderly.

    Science.gov (United States)

    Lee, Tih-Shih; Quek, Shin Yi; Goh, Siau Juinn Alexa; Phillips, Rachel; Guan, Cuntai; Cheung, Yin Bun; Feng, Lei; Wang, Chuan Chu; Chin, Zheng Yang; Zhang, Haihong; Lee, Jimmy; Ng, Tze Pin; Krishnan, K Ranga Rama

    2015-01-01

    There is growing evidence that cognitive training (CT) can improve the cognitive functioning of the elderly. CT may be influenced by cultural and linguistic factors, but research examining CT programs has mostly been conducted on Western populations. We have developed an innovative electroencephalography (EEG)-based brain-computer interface (BCI) CT program that has shown preliminary efficacy in improving cognition in 32 healthy English-speaking elderly adults in Singapore. In this second pilot trial, we examine the acceptability, safety, and preliminary efficacy of our BCI CT program in healthy Chinese-speaking Singaporean elderly. Thirty-nine elderly participants were randomized into intervention (n=21) and wait-list control (n=18) arms. Intervention consisted of 24 half-hour sessions with our BCI-based CT training system to be completed in 8 weeks; the control arm received the same intervention after an initial 8-week waiting period. At the end of the training, a usability and acceptability questionnaire was administered. Efficacy was measured using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), which was translated and culturally adapted for the Chinese-speaking local population. Users were asked about any adverse events experienced after each session as a safety measure. The training was deemed easily usable and acceptable by senior users. The median difference in the change scores pre- and post-training of the modified RBANS total score was 8.0 (95% confidence interval [CI]: 0.0-16.0, P=0.042) higher in the intervention arm than waitlist control, while the mean difference was 9.0 (95% CI: 1.7-16.2, P=0.017). Ten (30.3%) participants reported a total of 16 adverse events - all of which were graded "mild" except for one graded "moderate". Our BCI training system shows potential in improving cognition in both English- and Chinese-speaking elderly, and deserves further evaluation in a Phase III trial. Overall, participants

  19. Network Efficiency and Posterior Alpha Patterns Are Markers of Recovery from General Anesthesia: A High-Density Electroencephalography Study in Healthy Volunteers

    Directory of Open Access Journals (Sweden)

    Stefanie Blain-Moraes

    2017-06-01

    Full Text Available Recent studies have investigated local oscillations, long-range connectivity, and global network patterns to identify neural changes associated with anesthetic-induced unconsciousness. These studies typically employ anesthetic protocols that either just cross the threshold of unconsciousness, or induce deep unconsciousness for a brief period of time—neither of which models general anesthesia for major surgery. To study neural patterns of unconsciousness and recovery in a clinically-relevant context, we used a realistic anesthetic regimen to induce and maintain unconsciousness in eight healthy participants for 3 h. High-density electroencephalogram (EEG was acquired throughout and for another 3 h after emergence. Seven epochs of 5-min eyes-closed resting states were extracted from the data at baseline as well as 30, 60, 90, 120, 150, and 180-min post-emergence. Additionally, 5-min epochs were extracted during induction, unconsciousness, and immediately prior to recovery of consciousness, for a total of 10 analysis epochs. The EEG data in each epoch were analyzed using source-localized spectral analysis, phase-lag index, and graph theoretical techniques. Posterior alpha power was significantly depressed during unconsciousness, and gradually approached baseline levels over the 3 h recovery period. Phase-lag index did not distinguish between states of consciousness or stages of recovery. Network efficiency was significantly depressed and network clustering coefficient was significantly increased during unconsciousness; these graph theoretical measures returned to baseline during the 3 h recovery period. Posterior alpha power may be a potential biomarker for normal recovery of functional brain networks after general anesthesia.

  20. Brain rhythms alterations and their effect in functional networks: A simultaneous EEG/fMRI study in Fixation-off epilepsy

    OpenAIRE

    Solana Sánchez, Ana Beatriz; Hernández Tamames, J.A.; Molina, Elena; Martínez, Kenia; Alcalá, Juan José; Toledano, Rafael; San Antonio-Arce, Victoria; Garcia Morales, Irene; Gil Nagel, Antonio; Maestu Unturbe, Ceferino; Alvarez Linera, Juan; Alfayate, E.; Pozo Guerrero, Francisco del

    2012-01-01

    Fixation-off sensitivity (FOS) denotes the forms of EEG abnormalities, which are elicited by elimination of central vision or fixation. The phenomenon seems to depend on variables that modulate the alpha rhythm, however, the cerebral mechanisms underlying FOS remain unclear [1]. The scarce previous fMRI findings related to FOS have shown activation in extrastriate cortex [2] and also in frontal areas [3][4]. On the other hand, simultaneous EEG-fMRI technique has been used to assess the relati...

  1. Quantitative topographic differentiation of the neonatal EEG.

    Science.gov (United States)

    Paul, Karel; Krajca, Vladimír; Roth, Zdenek; Melichar, Jan; Petránek, Svojmil

    2006-09-01

    To test the discriminatory topographic potential of a new method of the automatic EEG analysis in neonates. A quantitative description of the neonatal EEG can contribute to the objective assessment of the functional state of the brain, and may improve the precision of diagnosing cerebral dysfunctions manifested by 'disorganization', 'dysrhythmia' or 'dysmaturity'. 21 healthy, full-term newborns were examined polygraphically during sleep (EEG-8 referential derivations, respiration, ECG, EOG, EMG). From each EEG record, two 5-min samples (one from the middle of quiet sleep, the other from the middle of active sleep) were subject to subsequent automatic analysis and were described by 13 variables: spectral features and features describing shape and variability of the signal. The data from individual infants were averaged and the number of variables was reduced by factor analysis. All factors identified by factor analysis were statistically significantly influenced by the location of derivation. A large number of statistically significant differences were also established when comparing the effects of individual derivations on each of the 13 measured variables. Both spectral features and features describing shape and variability of the signal are largely accountable for the topographic differentiation of the neonatal EEG. The presented method of the automatic EEG analysis is capable to assess the topographic characteristics of the neonatal EEG, and it is adequately sensitive and describes the neonatal electroencephalogram with sufficient precision. The discriminatory capability of the used method represents a promise for their application in the clinical practice.

  2. [The Influence of the Functional State of Brain Regulatory Structures on the Programming, Selective Regulation and Control of Cognitive Activity in Children. Report I: Neuropsychological and EEG Analysis of Age-Related Changes in Brain Regulatory Functions in Children Aged 9-12 Years].

    Science.gov (United States)

    Semenova, A; Machinskaya, R I; Lomakin, D I

    2015-01-01

    Age-related changes in brain regulatory functions in children aged from 9 to 12 years with typical development were studied by means of neuropsychological and EEG analysis. The participants of the study were 107 children without learning difficulties and behavior deviations; they were devided into three groups (9-10, 10-11 and 11-12 years). The neuropsychological tests revealed nonlinear age-related changes in different executive brain functions. The group of 10-11-year-old children showed better results in programming, in- hibition of impulsive reactions and in the perception of socially relevant information than the group of 9-10- year-old children. At the same time, these children had more difficulties with selective activity regulation as compared with the younger group. The difficulties were mainly caused by switching from one element of the program to another and by retention of learned sequence of actions. These children also showed a lower level of motivation for task performance. The children aged 11-12 years had less difficulties with selective activity regulation; however, impulsive behavior was more frequent; these children also had a higher level of task performance motivation than in children aged 10-11 years. The analysis of resting state EEG revealed age-related differences in deviated EEG patterns associated with non-optimal functioning of fronto-thalamic system and hypothalamic structures. The incidence of these two types of EEG patterns was significantly higher in children aged 10-11 years as compared with children aged 9-10 years. The EEG of the groups of 10-11 and 11-12-years-old children did not show any significant differences.

  3. 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...

  4. Usefulness of multi-plane dynamic subtraction CT (MPDS-CT) for intracranial high density lesions

    Energy Technology Data Exchange (ETDEWEB)

    Takagi, Ryo; Kumazaki, Tatsuo [Nippon Medical School, Tokyo (Japan)

    1996-02-01

    We present a new CT technique using the high speed CT scanner in detection and evaluation of temporal and spatial contrast enhancement of intracranial high density lesions. A multi-plane dynamic subtraction CT (MPDS-CT) was performed in 21 patients with intracranial high density lesions. These lesions consisted of 10 brain tumors, 7 intracerebral hemorrhages and 4 vascular malformations (2 untreated, 2 post-embolization). Baseline study was first performed, and 5 sequential planes of covering total high density lesions were selected. After obtaining the 5 sequential CT images as mask images, three series of multi-plane dynamic CT were performed for the same 5 planes with an intravenous bolus injection of contrast medium. MPDS-CT images were reconstructed by subtracting dynamic CT images from the mask ones. MPDS-CT were compared with conventional contrast-enhanced CT. MPDS-CT images showed the definite contrast enhancement of high density brain tumors and vascular malformations which were not clearly identified on conventional contrast-enhanced CT images because of calcified or hemorrhagic lesions and embolic materials, enabling us to eliminate enhanced abnormalities with non-enhanced areas such as unusual intracerebral hemorrhages. MPDS-CT will provide us further accurate and objective information and will be greatly helpful for interpreting pathophysiologic condition. (author).

  5. Improved GAMMA 10 tandem mirror confinement in high density plasma

    International Nuclear Information System (INIS)

    Yatsu, K.; Cho, T.; Higaki, H.; Hirata, M.; Hojo, H.; Ichimura, M.; Ishii, K.; Ishimoto, Y.; Itakura, A.; Katanuma, I.; Kohagura, J.; Minami, R.; Nakashima, Y.; Numakura, T.; Saito, T.; Saosaki, S.; Takemura, Y.; Tatematsu, Y.; Yoshida, M.; Yoshikawa, M.

    2003-01-01

    GAMMA 10 experiments have advanced in high density experiments after the last IAEA fusion energy conference in 2000 where we reported the production of the high density plasma through use of ion cyclotron range of frequency heating at a high harmonic frequency and neutral beam injection in the anchor cells. However, the diamagnetic signal of the plasma decreased when electron cyclotron resonance heating was applied for the potential formation. Recently a high density plasma has been obtained without degradation of the diamagnetic signal and with much improved reproducibility than before. The high density plasma was attained through adjustment of the spacing of the conducting plates installed in the anchor transition regions. The potential confinement of the plasma has been extensively studied. Dependences of the ion confinement time, ion-energy confinement time and plasma confining potential on plasma density were obtained for the first time in the high density region up to a density of 4x10 18 m -3 . (author)

  6. Mobile EEG in epilepsy

    NARCIS (Netherlands)

    Askamp, Jessica; van Putten, Michel Johannes Antonius Maria

    2014-01-01

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

  7. 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…

  8. 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...

  9. 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

  10. Subcortical vascular cognitive impairment, no dementia : EEG global power independently predicts vascular impairment and brain symmetry index reflects severity of cognitive decline

    NARCIS (Netherlands)

    Sheorajpanday, Rishi V.A.; Mariën, Peter; Nagels, Guy; Weeren, Arie J.T.M.; Saerens, Jos; Van Putten, Michel J.A.M.; de Deyn, Peter P.

    2014-01-01

    Background and Purpose: Vascular cognitive impairment, no dementia (vCIND) is a prevalent and potentially preventable disorder. Clinical presentation of the small-vessel subcortical subtype may be insidious, and differential difficulties can arise with mild cognitive impairment. We investigated EEG

  11. Subcortical Vascular Cognitive Impairment, No Dementia : EEG Global Power Independently Predicts Vascular Impairment and Brain Symmetry Index Reflects Severity of Cognitive Decline

    NARCIS (Netherlands)

    Sheorajpanday, Rishi V. A.; Marien, Peter; Nagels, Guy; Weeren, Arie J. T. M.; Saerens, Jos; van Putten, Michel J. A. M.; De Deyn, Peter P.

    2014-01-01

    Background and Purpose:Vascular cognitive impairment, no dementia (vCIND) is a prevalent and potentially preventable disorder. Clinical presentation of the small-vessel subcortical subtype may be insidious, and differential difficulties can arise with mild cognitive impairment. We investigated EEG

  12. A new ICA-based fingerprint method for the automatic removal of physiological artifacts from EEG recordings

    Science.gov (United States)

    Tamburro, Gabriella; Fiedler, Patrique; Stone, David; Haueisen, Jens

    2018-01-01

    Background EEG may be affected by artefacts hindering the analysis of brain signals. Data-driven methods like independent component analysis (ICA) are successful approaches to remove artefacts from the EEG. However, the ICA-based methods developed so far are often affected by limitations, such as: the need for visual inspection of the separated independent components (subjectivity problem) and, in some cases, for the independent and simultaneous recording of the inspected artefacts to identify the artefactual independent components; a potentially heavy manipulation of the EEG signals; the use of linear classification methods; the use of simulated artefacts to validate the methods; no testing in dry electrode or high-density EEG datasets; applications limited to specific conditions and electrode layouts. Methods Our fingerprint method automatically identifies EEG ICs containing eyeblinks, eye movements, myogenic artefacts and cardiac interference by evaluating 14 temporal, spatial, spectral, and statistical features composing the IC fingerprint. Sixty-two real EEG datasets containing cued artefacts are recorded with wet and dry electrodes (128 wet and 97 dry channels). For each artefact, 10 nonlinear SVM classifiers are trained on fingerprints of expert-classified ICs. Training groups include randomly chosen wet and dry datasets decomposed in 80 ICs. The classifiers are tested on the IC-fingerprints of different datasets decomposed into 20, 50, or 80 ICs. The SVM performance is assessed in terms of accuracy, False Omission Rate (FOR), Hit Rate (HR), False Alarm Rate (FAR), and sensitivity (p). For each artefact, the quality of the artefact-free EEG reconstructed using the classification of the best SVM is assessed by visual inspection and SNR. Results The best SVM classifier for each artefact type achieved average accuracy of 1 (eyeblink), 0.98 (cardiac interference), and 0.97 (eye movement and myogenic artefact). Average classification sensitivity (p) was 1

  13. Independent EEG sources are dipolar.

    Directory of Open Access Journals (Sweden)

    Arnaud Delorme

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

  14. Connectivity Measures in EEG Microstructural Sleep Elements.

    Science.gov (United States)

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

    2016-01-01

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

  15. Signal Quality Evaluation of Emerging EEG Devices

    Directory of Open Access Journals (Sweden)

    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.

  16. EEG simulation by 2D interconnected chaotic oscillators

    International Nuclear Information System (INIS)

    Kubany, Adam; Mhabary, Ziv; Gontar, Vladimir

    2011-01-01

    Research highlights: → ANN of 2D interconnected chaotic oscillators is explored for EEG simulation. → An inverse problem solution (PRCGA) is proposed. → Good matching between the simulated and experimental EEG signals has been achieved. - Abstract: An artificial neuronal network composed by 2D interconnected chaotic oscillators is explored for brain waves (EEG) simulation. For the inverse problem solution a parallel real-coded genetic algorithm (PRCGA) is proposed. In order to conduct thorough comparison between the simulated and target signal characteristics, a spectrum analysis of the signals is undertaken. A good matching between the theoretical and experimental EEG signals has been achieved. Numerical results of calculations are presented and discussed.

  17. EEG simulation by 2D interconnected chaotic oscillators

    Energy Technology Data Exchange (ETDEWEB)

    Kubany, Adam, E-mail: adamku@bgu.ac.i [Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, P.O. Box 653, Beer-Sheva 84105 (Israel); Mhabary, Ziv; Gontar, Vladimir [Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, P.O. Box 653, Beer-Sheva 84105 (Israel)

    2011-01-15

    Research highlights: ANN of 2D interconnected chaotic oscillators is explored for EEG simulation. An inverse problem solution (PRCGA) is proposed. Good matching between the simulated and experimental EEG signals has been achieved. - Abstract: An artificial neuronal network composed by 2D interconnected chaotic oscillators is explored for brain waves (EEG) simulation. For the inverse problem solution a parallel real-coded genetic algorithm (PRCGA) is proposed. In order to conduct thorough comparison between the simulated and target signal characteristics, a spectrum analysis of the signals is undertaken. A good matching between the theoretical and experimental EEG signals has been achieved. Numerical results of calculations are presented and discussed.

  18. Phenomenology of high density disruptions in the TFTR tokamak

    International Nuclear Information System (INIS)

    Fredrickson, E.D.; McGuire, K.M.; Bell, M.G.

    1993-01-01

    Studies of high density disruptions on TFTR, including a comparison of minor and major disruptions at high density, provide important new information regarding the nature of the disruption mechanism. Further, for the first time, an (m,n)=(1,1) 'cold bubble' precursor to high density disruptions has been experimentally observed in the electron temperature profile. The precursor to major disruptions resembles the 'vacuum bubble' model of disruptions first proposed by B.B. Kadomtsev and O.P. Pogutse (Sov. Phys. - JETP 38 (1974) 283). (author). Letter-to-the-editor. 25 refs, 3 figs

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

    Science.gov (United States)

    Antoniades, Andreas; Spyrou, Loukianos; Martin-Lopez, David; Valentin, Antonio; Alarcon, Gonzalo; Sanei, Saeid; Took, Clive Cheong

    2018-03-19

    Data is often plagued by noise which encumbers machine learning of clinically useful biomarkers and electroencephalogram (EEG) data is no exemption. Intracranial EEG (iEEG) data enhances the training of deep learning models of the human brain, yet is often prohibitive due to the invasive recording process. A more convenient alternative is to record brain activity using scalp electrodes. However, the inherent noise associated with scalp EEG data often impedes the learning process of neural models, achieving substandard performance. Here, an ensemble deep learning architecture for nonlinearly mapping scalp to iEEG data is proposed. The proposed architecture exploits the information from a limited number of joint scalp-intracranial recording to establish a novel methodology for detecting the epileptic discharges from the sEEG of a general population of subjects. Statistical tests and qualitative analysis have revealed that the generated pseudo-intracranial data are highly correlated with the true intracranial data. This facilitated the detection of IEDs from the scalp recordings where such waveforms are not often visible. As a real-world clinical application, these pseudo-iEEGs are then used by a convolutional neural network for the automated classification of intracranial epileptic discharges (IEDs) and non-IED of trials in the context of epilepsy analysis. Although the aim of this work was to circumvent the unavailability of iEEG and the limitations of sEEG, we have achieved a classification accuracy of 68% an increase of 6% over the previously proposed linear regression mapping.

  20. Effect of EEG biofeedback on improving brain function of children with comorbidity of ADHD and LD%脑电生物反馈对共患ADHD和LD患儿脑功能改善作用

    Institute of Scientific and Technical Information of China (English)

    翟杰; 仇新华; 薛波; 徐淑祝; 刘晓军

    2008-01-01

    目的 探讨脑电生物反馈对共患注意缺陷多动障碍(ADHD)和学习障碍(LD)患儿脑功能的改善作用.方法 应用脑电生物反馈治疗仪对48例共患ADHD和LD患儿进行治疗.采用脑电反馈仪检测脑电波功率比值,采用持续注意测验检测注意力,采用瑞文推理测验评价智力,采用酶联夹心免疫吸附测定法检测血清浓度.结果 治疗后患儿θ/β、θ/SMR值较前明显下降(P<0.01),漏报数、错误数、反应时间较前降低(P<0.01),智商较前改善(P<0.01),血清β-EP浓度[(180.29±32.38)pg/ml,(191.01±22.85)pg/ml]较前升高(P<0.01).结论 脑电反馈治疗能够显著改善共患ADHD和LD患儿的脑电异常、智力、注意力,且对脑电异常改善作用无左右脑半球特异性.%Objective To investigate the effect of EEG biofeedback treatment on improving brain func-tion of children with Comorbidity of attention deficit hyperactivity disorder(ADHD) and Learning disorder(LD).Methods Forty-eight children with Comorbidity of ADHD and LD diagnosed according to ICD-10 received 40 sessions of EEG biofeedback treatment. Feedback was contingent on enhancing beta activity and suppressing the-ta activity. All subjects were measured at pretreatment and at posttreatment on EEG activity, Raven's Standard Progressive Matrices, Continuous Performance Task (CPT). Serum levels were measured by enzyme linked immu-nosorbent assay. Results After treatment significante decreases were observed in the EEG ratio of the theta/be-ta and theta/SMR (P<0.01), in the errors commission and errors of omiss and reaction time of CPT (P<0.01). The mean concentration of Serum β-EP[(180.29±32.38) pg/ml and (191.01±22.85) pg/ml] in-creased significantly(P<0.01). IQ improve after treatment (P<0.01). Conclusion EEG biofeedback is highly effective in improving EEG spectrum,intelligence, attention of children with Comorbidity of ADHD and LD. The effect of EEG biofeedback is not hemispheric specific.

  1. 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.

  2. High regression rate, high density hybrid fuels, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — This SBIR program will investigate high energy density novel nanofuels combined with high density binders for use with an N2O oxidizer. Terves has developed...

  3. The Influence of Decreased Levels of High Density Lipoprotein ...

    African Journals Online (AJOL)

    very low density lipoprotein cholesterol, and triglyceride were assayed. ... Abiodun and Gwarzo: Association of high density lipoprotein cholesterol with haemolysis in sickle cell disease ... analyses were carried out to determine the correlation.

  4. 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

  5. High density UO2 powder preparation for HWR fuel

    International Nuclear Information System (INIS)

    Hwang, S. T.; Chang, I. S.; Choi, Y. D.; Cho, B. R.; Kwon, S. W.; Kim, B. H.; Moon, B. H.; Kim, S. D.; Phyu, K. M.; Lee, K. A.

    1992-01-01

    The objective of this project is to study on the preparation of method high density UO 2 powder for HWR Fuel. Accordingly, it is necessary to character ize the AUC processed UO 2 powder and to search method for the preparation of high density UO 2 powder for HWR Fuel. Therefore, it is expected that the results of this study can effect the producing of AUC processed UO 2 powder having sinterability. (Author)

  6. The high density effects in the Drell-Yan process

    International Nuclear Information System (INIS)

    Betemps, M.A.; Gay Ducati, M.B.; Ayala Filho, A.L.

    2003-01-01

    The high density effects in the Drell-Yan process (q q-bar → γ * →l + l - ) are investigated for pA collisions at RHIC and LHC energies. In particular, we use a set of nuclear parton distributions that describes the present nuclear eA and pA data in the DGLAP approach including the high density effects introduced in the perturbative Glauber-Mueller approach. (author)

  7. Widespread EEG changes precede focal seizures.

    Directory of Open Access Journals (Sweden)

    Piero Perucca

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

  8. 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.

  9. An overview of an amplitude integrated EEG

    Directory of Open Access Journals (Sweden)

    Setyo Handryastuti

    2007-05-01

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

  10. Alternating Dynamics of Segregation and Integration in Human EEG Functional Networks During Working-memory Task.

    Science.gov (United States)

    Zippo, Antonio G; Della Rosa, Pasquale A; Castiglioni, Isabella; Biella, Gabriele E M

    2018-02-10

    Brain functional networks show high variability in short time windows but mechanisms governing these transient dynamics remain unknown. In this work, we studied the temporal evolution of functional brain networks involved in a working memory (WM) task while recording high-density electroencephalography (EEG) in human normal subjects. We found that functional brain networks showed an initial phase characterized by an increase of the functional segregation index followed by a second phase where the functional segregation faded after the prevailing the functional integration. Notably, wrong trials were associated with different or disrupted sequences of the segregation-integration profiles and measures of network centrality and modularity were able to identify crucial aspects of the oscillatory network dynamics. Additionally, computational investigations further supported the experimental results. The brain functional organization may respond to the information processing demand of a WM task following a 2-step atomic scheme wherein segregation and integration alternately dominate the functional configurations. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  11. 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.

  12. Assessment of seizure liability of Org 306039, a 5-HT2c agonist, using hippocampal brain slice and rodent EEG telemetry.

    Science.gov (United States)

    Markgraf, Carrie G; DeBoer, Erik; Zhai, Jin; Cornelius, Lara; Zhou, Ying Ying; MacSweeney, Cliona

    2014-01-01

    Evaluation of the seizure potential for a CNS-targeted pharmaceutical compound before it is administered to humans is an important part of development. The current in vitro and in vivo studies were undertaken to characterize the seizure potential of the potent and selective 5-HT2c agonist Org 306039. Rat hippocampal slices (n=5) were prepared and Org 306039 was applied over a concentration range of 0-1000μM. Male Sprague-Dawley rats, implanted with telemetry EEG recording electrodes received either vehicle (n=4) or 100mg/kg Org 306039 (n=4) by oral gavage daily for 10days. EEG was recorded continuously for 22±1h post-dose each day. Post-dose behavior observations were conducted daily for 2h. Body temperature was measured at 1 and 2h post-dose. On Day 7, blood samples were drawn for pharmacokinetic analysis of Org 306039. In hippocampal slice, Org 306039 elicited a concentration-dependent increase in population spike area and number recorded from CA1 area, indicating seizure-genic potential. In telemetered rats, Org 306039 was associated with a decrease in body weight, a decrease in body temperature and the appearance of seizure-related behaviors and pre-seizure waveforms on EEG. One rat exhibited an overt seizure. Plasma concentrations of Org 306039 were similar among the 4 rats in the Org-treated group. Small group size made it difficult to determine a PK-PD relationship. These results indicate that the in vitro and in vivo models complement each other in the characterization of the seizure potential of CNS-targeted compounds such as the 5-HT2c agonist Org 306039. Copyright © 2014 Elsevier Inc. All rights reserved.

  13. High-density-plasma diagnostics in magnetic-confinement fusion

    International Nuclear Information System (INIS)

    Jahoda, F.C.

    1982-01-01

    The lectures will begin by defining high density in the context of magnetic confinement fusion research and listing some alternative reactor concepts, ranging from n/sub e/ approx. 2 x 10 14 cm -3 to several orders of magnitude greater, that offer potential advantages over the main-line, n/sub e/ approx. 1 x 10 14 cm -3 , Tokamak reactor designs. The high density scalings of several major diagnostic techniques, some favorable and some disadvantageous, will be discussed. Special emphasis will be given to interferometric methods, both electronic and photographic, for which integral n/sub e/dl measurements and associated techniques are accessible with low wavelength lasers. Reactor relevant experience from higher density, smaller dimension devices exists. High density implies high β, which implies economies of scale. The specialized features of high β diagnostics will be discussed

  14. A Smartphone Interface for a Wireless EEG Headset with Real-Time 3D Reconstruction

    DEFF Research Database (Denmark)

    Stopczynski, Arkadiusz; Larsen, Jakob Eg; Stahlhut, Carsten

    2011-01-01

    We demonstrate a fully functional handheld brain scanner consisting of a low-cost 14-channel EEG headset with a wireless connec- tion to a smartphone, enabling minimally invasive EEG monitoring in naturalistic settings. The smartphone provides a touch-based interface with real-time brain state...

  15. 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.

  16. EEG UPPER/LOW ALPHA FREQUENCY POWER RATIO RELATES TO TEMPORO-PARIETAL BRAIN ATROPHY AND MEMORY PERFORMANCES IN MILD COGNITIVE IMPAIRMENT

    Directory of Open Access Journals (Sweden)

    Davide Vito Moretti

    2013-10-01

    Full Text Available Objective: temporo-parietal cortex thinning is associated to mild cognitive impairment (MCI due to Alzheimer disease (AD. The increase of EEG upper/low alpha power ratio has been associated with AD-converter MCI subjects. We investigated the association of alpha3/alpha2 ratio with patterns of cortical thickness in MCI.Methods: 74 adult subjects with MCI underwent clinical and neuropsychological evaluation, electroencephalogram (EEG recording and high resolution 3D magnetic resonance imaging (MRI. Alpha3/alpha2 power ratio as well as cortical thickness was computed for each subject. Three MCI groups were detected according to increasing tertile values of upper/low alpha power ratio . Difference of cortical thikness among the groups was estimated. Pearson’s r was used to assess the topography of the correlation between cortical thinning and memory impairment.Results: High upper/low alpha power ratio group had total cortical grey matter (CGM volume reduction of 471 mm2 than low upper/low alpha power ratio group (p

  17. EEG-guided meditation: A personalized approach.

    Science.gov (United States)

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

    2015-12-01

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

  18. BCS Theory of Hadronic Matter at High Densities

    DEFF Research Database (Denmark)

    Bohr, Henrik; Panda, Prafulla K.; Providencia, Constanca

    2012-01-01

    The equilibrium between the so-called 2SC and CFL phases of strange quark matter at high densities is investigated in the framework of a simple schematic model of the NJL type. Equal densities are assumed for quarks u, d and s. The 2SC phase is here described by a color-flavor symmetric state, in...

  19. Antioxidant activity of high-density lipoprotein (HDL) using different ...

    African Journals Online (AJOL)

    HDL is a potent antioxidant in terms of inhibition of lipid peroxidation, ROS production and LDL oxidation. These may to some extent add to the antiatherogenic beyond reverse-cholesterol transport properties of HDL. Keywords: high-density lipoprotein; reverse cholesterol transport; apolipoprotein A1; antioxidant; in vitro.

  20. Morphodynamics of supercritical high-density turbidity currents

    NARCIS (Netherlands)

    Cartigny, M.

    2012-01-01

    Seafloor and outcrop observations combined with numerical and physical experiments show that turbidity currents are likely 1) to be in a supercritical flow state and 2) to carry high sediment concentrations (being of high-density). The thesis starts with an experimental study of bedforms

  1. Fluorescent Fe K Emission from High Density Accretion Disks

    Science.gov (United States)

    Bautista, Manuel; Mendoza, Claudio; Garcia, Javier; Kallman, Timothy R.; Palmeri, Patrick; Deprince, Jerome; Quinet, Pascal

    2018-06-01

    Iron K-shell lines emitted by gas closely orbiting black holes are observed to be grossly broadened and skewed by Doppler effects and gravitational redshift. Accordingly, models for line profiles are widely used to measure the spin (i.e., the angular momentum) of astrophysical black holes. The accuracy of these spin estimates is called into question because fitting the data requires very high iron abundances, several times the solar value. Meanwhile, no plausible physical explanation has been proffered for why these black hole systems should be so iron rich. The most likely explanation for the super-solar iron abundances is a deficiency in the models, and the leading candidate cause is that current models are inapplicable at densities above 1018 cm-3. We study the effects of high densities on the atomic parameters and on the spectral models for iron ions. At high densities, Debye plasma can affect the effective atomic potential of the ions, leading to observable changes in energy levels and atomic rates with respect to the low density case. High densities also have the effec of lowering energy the atomic continuum and reducing the recombination rate coefficients. On the spectral modeling side, high densities drive level populations toward a Boltzman distribution and very large numbers of excited atomic levels, typically accounted for in theoretical spectral models, may contribute to the K-shell spectrum.

  2. Sputtered thin films for high density tape recording

    NARCIS (Netherlands)

    Nguyen, L.T.

    This thesis describes the investigation of sputtered thin film media for high density tape recording. As discussed in Chapter 1, to meet the tremendous demand of data storage, the density of recording tape has to be increased continuously. For further increasing the bit density the key factors are:

  3. Ultra-stretchable Interconnects for high-density stretchable electronics

    NARCIS (Netherlands)

    Shafqat, S.; Hoefnagels, J.P.M.; Savov, A.; Joshi, S.; Dekker, R.; Geers, M.G.D.

    2017-01-01

    The exciting field of stretchable electronics (SE) promises numerous novel applications, particularly in-body and medical diagnostics devices. However, future advanced SE miniature devices will require high-density, extremely stretchable interconnects with micron-scale footprints, which calls for

  4. Positron camera with high-density avalanche chambers

    International Nuclear Information System (INIS)

    Manfrass, D.; Enghardt, W.; Fromm, W.D.; Wohlfarth, D.; Hennig, K.

    1988-01-01

    The results of an extensive investigation of the properties of high-density avalanche chambers (HIDAC) are presented. This study has been performed in order to optimize the layout of HIDAC detectors, since they are intended to be applied as position sensitive detectors for annihilation radiation in a positron emission tomograph being under construction. (author)

  5. Role of Lipids in Spheroidal High Density Lipoproteins

    NARCIS (Netherlands)

    Vuorela, Timo; Catte, Andrea; Niemela, Perttu S.; Hall, Anette; Hyvonen, Marja T.; Marrink, Siewert-Jan; Karttunen, Mikko; Vattulainen, Ilpo

    2010-01-01

    We study the structure and dynamics of spherical high density lipoprotein (HDL) particles through coarse-grained multi-microsecond molecular dynamics simulations. We simulate both a lipid droplet without the apolipoprotein A-I (apoA-I) and the full HDL particle including two apoA-I molecules

  6. Role of lipids in spheroidal high density lipoproteins

    NARCIS (Netherlands)

    Vuorela, T.A.; Catte, A.; Niemelä, P.S.; Hall, A.; Hyvönen, M.T.; Marrink, S.J.; Karttunen, M.E.J.; Vattulainen, I.

    2010-01-01

    We study the structure and dynamics of spherical high density lipoprotein (HDL) particles through coarse-grained multi-microsecond molecular dynamics simulations. We simulate both a lipid droplet without the apolipoprotein A-I (apoA-I) and the full HDL particle including two apoA-I molecules

  7. Interfacial stick–slip transition in hydroxyapatite filled high density ...

    Indian Academy of Sciences (India)

    Unknown

    flow curves of composites and that of unfilled system remain identical. Filler addition lowers the .... Injection moulding grade high density polyethylene,. HD6070EA, was ... rheometer (Rosand Precision Ltd., UK) using version. 6⋅10 software. .... Bagley E B, Cabbot I M and West D C 1958 J. Appl. Phys. 29. 109. Blyler L L and ...

  8. Spontaneous magnetization in high-density quark matter

    DEFF Research Database (Denmark)

    Tsue, Yasuhiko; da Providência, João; Providência, Constanca

    2015-01-01

    It is shown that spontaneous magnetization occurs due to the anomalous magnetic moments of quarks in high-density quark matter under the tensor-type four-point interaction. The spin polarized condensate for each flavor of quark appears at high baryon density, which leads to the spontaneous magnet...

  9. The Influence of Decreased Levels of High Density Lipoprotein ...

    African Journals Online (AJOL)

    Background: Changes in lipoproteins levels in sickle cell disease (SCD) patients are well.known, but the physiological ramifications of the low levels observed have not been entirely resolved. Aim: The aim of this study is to evaluate the impact of decreased levels of high density lipoprotein cholesterol (HDL.c) on ...

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2015-01-01

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

  12. Monitoring alert and drowsy states by modeling EEG source nonstationarity

    Science.gov (United States)

    Hsu, Sheng-Hsiou; Jung, Tzyy-Ping

    2017-10-01

    Objective. As a human brain performs various cognitive functions within ever-changing environments, states of the brain characterized by recorded brain activities such as electroencephalogram (EEG) are inevitably nonstationary. The challenges of analyzing the nonstationary EEG signals include finding neurocognitive sources that underlie different brain states and using EEG data to quantitatively assess the state changes. Approach. This study hypothesizes that brain activities under different states, e.g. levels of alertness, can be modeled as distinct compositions of statistically independent sources using independent component analysis (ICA). This study presents a framework to quantitatively assess the EEG source nonstationarity and estimate levels of alertness. The framework was tested against EEG data collected from 10 subjects performing a sustained-attention task in a driving simulator. Main results. Empirical results illustrate that EEG signals under alert versus drowsy states, indexed by reaction speeds to driving challenges, can be characterized by distinct ICA models. By quantifying the goodness-of-fit of each ICA model to the EEG data using the model deviation index (MDI), we found that MDIs were significantly correlated with the reaction speeds (r  =  -0.390 with alertness models and r  =  0.449 with drowsiness models) and the opposite correlations indicated that the two models accounted for sources in the alert and drowsy states, respectively. Based on the observed source nonstationarity, this study also proposes an online framework using a subject-specific ICA model trained with an initial (alert) state to track the level of alertness. For classification of alert against drowsy states, the proposed online framework achieved an averaged area-under-curve of 0.745 and compared favorably with a classic power-based approach. Significance. This ICA-based framework provides a new way to study changes of brain states and can be applied to

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

    Directory of Open Access Journals (Sweden)

    Pedro eReis

    2014-03-01

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

  14. High density plasmas formation in Inertial Confinement Fusion and Astrophysics

    International Nuclear Information System (INIS)

    Martinez-Val, J. M.; Minguez, E.; Velarde, P.; Perlado, J. M.; Velarde, G.; Bravo, E.; Eliezer, S.; Florido, R.; Garcia Rubiano, J.; Garcia-Senz, D.; Gil de la Fe, J. M.; Leon, P. T.; Martel, P.; Ogando, F.; Piera, M.; Relano, A.; Rodriguez, R.; Garcia, C.; Gonzalez, E.; Lachaise, M.; Oliva, E.

    2005-01-01

    In inertially confined fusion (ICF), high densities are required to obtain high gains. In Fast Ignition, a high density, low temperature plasma can be obtained during the compression. If the final temperature reached is low enough, the electrons of the plasma can be degenerate. In degenerate plasmas. Bremsstrahlung emission is strongly suppressed an ignition temperature becomes lower than in classical plasmas, which offers a new design window for ICF. The main difficulty of degenerate plasmas in the compression energy needed for high densities. Besides that, the low specific heat of degenerate electrons (as compared to classical values) is also a problem because of the rapid heating of the plasma. Fluid dynamic evolution of supernovae remnants is a very interesting problem in order to predict the thermodynamical conditions achieved in their collision regions. Those conditions have a strong influence in the emission of light and therefore the detection of such events. A laboratory scale system has been designed reproducing the fluid dynamic field in high energy experiments. The evolution of the laboratory system has been calculated with ARWEN code, 2D Radiation CFD that works with Adaptive Mesh Refinement. Results are compared with simulations on the original system obtained with a 3D SPH astrophysical code. New phenomena at the collision plane and scaling of the laboratory magnitudes will be described. Atomic physics for high density plasmas has been studied with participation in experiments to obtain laser produced high density plasmas under NLTE conditions, carried out at LULI. A code, ATOM3R, has been developed which solves rate equations for optically thin plasmas as well as for homogeneous optically thick plasmas making use of escape factors. New improvements in ATOM3R are been done to calculate level populations and opacities for non homogeneous thick plasmas in NLTE, with emphasis in He and H lines for high density plasma diagnosis. Analytical expression

  15. Illumination influences working memory: an EEG study.

    Science.gov (United States)

    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.

  16. 3D Printed Dry EEG Electrodes.

    Science.gov (United States)

    Krachunov, Sammy; Casson, Alexander J

    2016-10-02

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

  17. 3D Printed Dry EEG Electrodes

    Directory of Open Access Journals (Sweden)

    Sammy Krachunov

    2016-10-01

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

  18. High density data storage principle, technology, and materials

    CERN Document Server

    Zhu, Daoben

    2009-01-01

    The explosive increase in information and the miniaturization of electronic devices demand new recording technologies and materials that combine high density, fast response, long retention time and rewriting capability. As predicted, the current silicon-based computer circuits are reaching their physical limits. Further miniaturization of the electronic components and increase in data storage density are vital for the next generation of IT equipment such as ultra high-speed mobile computing, communication devices and sophisticated sensors. This original book presents a comprehensive introduction to the significant research achievements on high-density data storage from the aspects of recording mechanisms, materials and fabrication technologies, which are promising for overcoming the physical limits of current data storage systems. The book serves as an useful guide for the development of optimized materials, technologies and device structures for future information storage, and will lead readers to the fascin...

  19. Noise reduction in muon tomography for detecting high density objects

    International Nuclear Information System (INIS)

    Benettoni, M; Checchia, P; Cossutta, L; Furlan, M; Gonella, F; Pegoraro, M; Garola, A Rigoni; Ronchese, P; Vanini, S; Viesti, G; Bettella, G; Bonomi, G; Donzella, A; Subieta, M; Zenoni, A; Calvagno, G; Cortelazzo, G; Zanuttigh, P; Calvini, P; Squarcia, S

    2013-01-01

    The muon tomography technique, based on multiple Coulomb scattering of cosmic ray muons, has been proposed as a tool to detect the presence of high density objects inside closed volumes. In this paper a new and innovative method is presented to handle the density fluctuations (noise) of reconstructed images, a well known problem of this technique. The effectiveness of our method is evaluated using experimental data obtained with a muon tomography prototype located at the Legnaro National Laboratories (LNL) of the Istituto Nazionale di Fisica Nucleare (INFN). The results reported in this paper, obtained with real cosmic ray data, show that with appropriate image filtering and muon momentum classification, the muon tomography technique can detect high density materials, such as lead, albeit surrounded by light or medium density material, in short times. A comparison with algorithms published in literature is also presented

  20. 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 ...

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

    Science.gov (United States)

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

    2015-12-01

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

  2. Wireless and wearable EEG system for evaluating driver vigilance.

    Science.gov (United States)

    Lin, Chin-Teng; Chuang, Chun-Hsiang; Huang, Chih-Sheng; Tsai, Shu-Fang; Lu, Shao-Wei; Chen, Yen-Hsuan; Ko, Li-Wei

    2014-04-01

    Brain activity associated with attention sustained on the task of safe driving has received considerable attention recently in many neurophysiological studies. Those investigations have also accurately estimated shifts in drivers' levels of arousal, fatigue, and vigilance, as evidenced by variations in their task performance, by evaluating electroencephalographic (EEG) changes. However, monitoring the neurophysiological activities of automobile drivers poses a major measurement challenge when using a laboratory-oriented biosensor technology. This work presents a novel dry EEG sensor based mobile wireless EEG system (referred to herein as Mindo) to monitor in real time a driver's vigilance status in order to link the fluctuation of driving performance with changes in brain activities. The proposed Mindo system incorporates the use of a wireless and wearable EEG device to record EEG signals from hairy regions of the driver conveniently. Additionally, the proposed system can process EEG recordings and translate them into the vigilance level. The study compares the system performance between different regression models. Moreover, the proposed system is implemented using JAVA programming language as a mobile application for online analysis. A case study involving 15 study participants assigned a 90 min sustained-attention driving task in an immersive virtual driving environment demonstrates the reliability of the proposed system. Consistent with previous studies, power spectral analysis results confirm that the EEG activities correlate well with the variations in vigilance. Furthermore, the proposed system demonstrated the feasibility of predicting the driver's vigilance in real time.

  3. The standardized EEG electrode array of the IFCN.

    Science.gov (United States)

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

    2017-10-01

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

  4. Operation and control of high density tokamak reactors

    International Nuclear Information System (INIS)

    Attenberger, S.E.; McAlees, D.G.

    1976-01-01

    The incentive for high density operation of a tokamak reactor is discussed. The plasma size required to attain ignition is determined. Ignition is found to be possible in a relatively small system provided other design criteria are met. These criteria are described and the technology developments and operating procedures required by them are outlined. The parameters for such a system and its dynamic behavior during the operating cycle are also discussed

  5. Volume generation of negative ions in high density hydrogen discharges

    International Nuclear Information System (INIS)

    Hiskes, J.R.; Karo, A.M.

    1983-01-01

    A parametric survey is made of a high-density tandem two-chamber hydrogen negative ion system. The optimum extracted negative ion current densities are sensitive to the atom concentration in the discharge and to the system scale length. For scale lengths ranging from 10 cm to 0.1 cm optimum current densities range from of order 1 to 100 mA cm -2 , respectively

  6. Apparatus and method for generating high density pulses of electrons

    International Nuclear Information System (INIS)

    Lee, C.; Oettinger, P.E.

    1981-01-01

    An apparatus and method are described for the production of high density pulses of electrons using a laser energized emitter. Caesium atoms from a low pressure vapour atmosphere are absorbed on and migrate from a metallic target rapidly heated by a laser to a high temperature. Due to this heating time being short compared with the residence time of the caesium atoms adsorbed on the target surface, copious electrons are emitted which form a high current density pulse. (U.K.)

  7. Relativistic many-body theory of high density matter

    International Nuclear Information System (INIS)

    Chin, S.A.

    1977-01-01

    A fully relativistic quantum many-body theory is applied to the study of high-density matter. The latter is identified with the zero-temperature ground state of a system of interacting baryons. In accordance with the observed short-range repulsive and long-range attractive character of the nucleon--nucleon force, baryons are described as interacting with each other via a massive scalar and a massive vector meson exchange. In the Hartree approximation, the theory yields the same result as the mean-field theory, but with additional vacuum fluctuation corrections. The resultant equation of state for neutron matter is used to determine properties of neutron stars. The relativistic exchange energy, its corresponding single-particle excitation spectrum, and its effect on the neutron matter equation of state, are calculated. The correlation energy from summing the set of ring diagrams is derived directly from the energy-momentum tensor, with renormalization carried out by adding counterterms to the original Lagrangian and subtracting purely vacuum expectation values. Terms of order g 4 lng 2 are explicitly given. Effects of scalar-vector mixing are discussed. Collective modes corresponding to macroscopic density fluctuation are investigated. Two basic modes are found, a plasma-like mode and zero sound, with the latter dominant at high density. The stability and damping of these modes are studied. Last, the effect of vacuum polarization in high-density matter is examined

  8. Operation and control of high density tokamak reactors

    International Nuclear Information System (INIS)

    Attenberger, S.E.; McAlees, D.G.

    1976-01-01

    The incentive for high density operation of a tokamak reactor was discussed. It is found that high density permits ignition in a relatively small, moderately elongated plasma with a moderate magnetic field strength. Under these conditions, neutron wall loadings approximately 4 MW/m 2 must be tolerated. The sensitivity analysis with respect to impurity effects shows that impurity control will most likely be necessary to achieve the desired plasma conditions. The charge exchange sputtered impurities are found to have an important effect so that maintaining a low neutral density in the plasma is critical. If it is assumed that neutral beams will be used to heat the plasma to ignition, high energy injection is required (approximately 250 keV) when heating is accompished at full density. A scenario is outlined where the ignition temperature is established at low density and then the fueling rate is increased to attain ignition. This approach may permit beams with energies being developed for use in TFTR to be successfully used to heat a high density device of the type described here to ignition

  9. Evaporation of carbon using electrons of a high density plasma

    International Nuclear Information System (INIS)

    Muhl, S.; Camps, E.; Escobar A, L.; Garcia E, J.L.; Olea, O.

    1999-01-01

    The high density plasmas are used frequently in the preparation of thin films or surface modification, for example to nitridation. In these processes, are used mainly the ions and the neutrals which compose the plasma. However, the electrons present in the plasma are not used, except in the case of chemical reactions induced by collisions, although the electron bombardment usually get hot the work piece. Through the adequate polarization of a conductor material, it is possible to extract electrons from a high density plasma at low pressure, that could be gotten the evaporation of this material. As result of the interaction between the plasma and the electron flux with the vapor produced, this last will be ionized. In this work, it is reported the use of this novelty arrangement to prepare carbon thin films using a high density argon plasma and a high purity graphite bar as material to evaporate. It has been used substrates outside plasma and immersed in the plasma. Also it has been reported the plasma characteristics (temperature and electron density, energy and ions flux), parameters of the deposit process (deposit rate and ion/neutral rate) as well as the properties of the films obtained (IR absorption spectra and UV/Vis, elemental analysis, hardness and refractive index. (Author)

  10. 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...

  11. High-density cervical ureaplasma urealyticum colonization in pregnant women

    Directory of Open Access Journals (Sweden)

    Ranđelović Gordana

    2006-01-01

    Full Text Available Background/aim: Ureaplasma urealyticum, a common commensal of the female lower genital tract, has been observed as an important opportunistic pathogen during pregnancy. The aims of this study were to determine the degree of cervical colonization with U. urealyticum in pregnant women with risk pregnancy and in pregnant women with normal term delivery and to evaluate the correlation between high-density cervical U. urealyticum colonization and premature rupture of membranes (PROM as well. Methods. This research was conducted on the samples comprising 130 hospitalized pregnant women with threatening preterm delivery and premature rupture of membranes. The control group consisted of 39 pregnant women with term delivery without PROM. In addition to standard bacteriological examination and performing direct immunofluorescence test to detect Chlamydia trachomatis, cervical swabs were also examined for the presence of U. urealyticum and Mycoplasma hominis by commercially available Mycofast Evolution 2 test (International Microbio, France. Results. The number of findings with isolated high-density U. urealyticum in the target group was 69 (53.08%, while in the control group was 14 (35.90%. Premature rupture of membranes (PROM occurred in 43 (33.08% examinees: 29 were pPROM, and 14 were PROM. The finding of U.urealyticum ≥104 was determined in 25 (58.14% pregnant women with rupture, 17 were pPROM, and 8 were PROM. There was statistically significant difference in the finding of high-density U. urealyticum between the pregnant women with PROM and the control group (χ² = 4.06, p < 0.05. U. urealyticum was predominant bacterial species found in 62.79% of isolates in the PROM cases, while in 32.56% it was isolated alone. Among the 49 pregnant women with preterm delivery, pPROM occurred in 29 (59.18% examinees, and in 70.83% of pregnant women with findings of high-density U. urealyticum pPROM was observed. Conclusion. Cervical colonization with U

  12. Characterization of the high density plasma etching process of CCTO thin films for the fabrication of very high density capacitors

    International Nuclear Information System (INIS)

    Altamore, C; Tringali, C; Sparta', N; Marco, S Di; Grasso, A; Ravesi, S

    2010-01-01

    In this work the feasibility of CCTO (Calcium Copper Titanate) patterning by etching process is demonstrated and fully characterized in a hard to etch materials etcher. CCTO sintered in powder shows a giant relative dielectric constant (10 5 ) measured at 1 MHz at room temperature. This feature is furthermore coupled with stability from 10 1 Hz to 10 6 Hz in a wide temperature range (100K - 600K). In principle, this property can allow to fabricate very high capacitance density condenser. Due to its perovskite multi-component structure, CCTO can be considered a hard to etch material. For high density capacitor fabrication, CCTO anisotropic etching is requested by using high density plasma. The behavior of etched CCTO was studied in a HRe- (High Density Reflected electron) plasma etcher using Cl 2 /Ar chemistry. The relationship between the etch rate and the Cl 2 /Ar ratio was also studied. The effects of RF MHz, KHz Power and pressure variation, the impact of HBr addiction to the Cl 2 /Ar chemistry on the CCTO etch rate and on its selectivity to Pt and photo resist was investigated.

  13. Characterization of the high density plasma etching process of CCTO thin films for the fabrication of very high density capacitors

    Energy Technology Data Exchange (ETDEWEB)

    Altamore, C; Tringali, C; Sparta' , N; Marco, S Di; Grasso, A; Ravesi, S [STMicroelectronics, Industial and Multi-segment Sector R and D, Catania (Italy)

    2010-02-15

    In this work the feasibility of CCTO (Calcium Copper Titanate) patterning by etching process is demonstrated and fully characterized in a hard to etch materials etcher. CCTO sintered in powder shows a giant relative dielectric constant (10{sup 5}) measured at 1 MHz at room temperature. This feature is furthermore coupled with stability from 10{sup 1} Hz to 10{sup 6} Hz in a wide temperature range (100K - 600K). In principle, this property can allow to fabricate very high capacitance density condenser. Due to its perovskite multi-component structure, CCTO can be considered a hard to etch material. For high density capacitor fabrication, CCTO anisotropic etching is requested by using high density plasma. The behavior of etched CCTO was studied in a HRe- (High Density Reflected electron) plasma etcher using Cl{sub 2}/Ar chemistry. The relationship between the etch rate and the Cl{sub 2}/Ar ratio was also studied. The effects of RF MHz, KHz Power and pressure variation, the impact of HBr addiction to the Cl{sub 2}/Ar chemistry on the CCTO etch rate and on its selectivity to Pt and photo resist was investigated.

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

    Science.gov (United States)

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

    2016-07-01

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

  15. Development of grouped icEEG for the study of cognitive processing

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    Zachary B. Loris

    2017-07-01

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

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

    Directory of Open Access Journals (Sweden)

    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.

  18. Biomimetic High Density Lipoprotein Nanoparticles For Nucleic Acid Delivery

    Science.gov (United States)

    McMahon, Kaylin M.; Mutharasan, R. Kannan; Tripathy, Sushant; Veliceasa, Dorina; Bobeica, Mariana; Shumaker, Dale K.; Luthi, Andrea J.; Helfand, Brian T.; Ardehali, Hossein; Mirkin, Chad A.; Volpert, Olga; Thaxton, C. Shad

    2014-01-01

    We report a gold nanoparticle-templated high density lipoprotein (HDL AuNP) platform for gene therapy which combines lipid-based nucleic acid transfection strategies with HDL biomimicry. For proof-of-concept, HDL AuNPs are shown to adsorb antisense cholesterylated DNA. The conjugates are internalized by human cells, can be tracked within cells using transmission electron microscopy (TEM), and regulate target gene expression. Overall, the ability to directly image the AuNP core within cells, the chemical tailorability of the HDL AuNP platform, and the potential for cell-specific targeting afforded by HDL biomimicry make this platform appealing for nucleic acid delivery. PMID:21319839

  19. High Density Thermal Energy Storage with Supercritical Fluids

    Science.gov (United States)

    Ganapathi, Gani B.; Wirz, Richard

    2012-01-01

    A novel approach to storing thermal energy with supercritical fluids is being investigated, which if successful, promises to transform the way thermal energy is captured and utilized. The use of supercritical fluids allows cost-affordable high-density storage with a combination of latent heat and sensible heat in the two-phase as well as the supercritical state. This technology will enhance penetration of several thermal power generation applications and high temperature water for commercial use if the overall cost of the technology can be demonstrated to be lower than the current state-of-the-art molten salt using sodium nitrate and potassium nitrate eutectic mixtures.

  20. Optically Addressed Nanostructures for High Density Data Storage

    Science.gov (United States)

    2005-10-14

    beam to sub-wavelength resolutions. X. Refereed Journal Publications I. M. D. Stenner , D. J. Gauthier, and M. A. Neifeld, "The speed of information in a...profiles for high-density optical data storage," Optics Communications, Vol.253, pp.56-69, 2005. 5. M. D. Stenner , D. J. Gauthier, and M. A. Neifeld, "Fast...causal information transmission in a medium with a slow group velocity," Physical Review Letters, Vol.94, February 2005. 6. M. D. Stenner , M. A

  1. Viscosity and attenuation of sound wave in high density deuterium

    International Nuclear Information System (INIS)

    Inoue, Kazuko; Ariyasu, Tomio

    1985-01-01

    The penetration of low frequency sound wave into the fuel deuterium is discussed as for laser fusion. The sound velocity and the attenuation constant due to viscosity are calculated for high density (n = 10 24 -- 10 27 cm -3 , T = 10 -1 -- 10 4 eV) deuterium. The shear viscosity of free electron gas and the bulk viscosity due to ion-ion interaction mainly contribute to the attenuation of sound wave. The sound wave of the frequency below 10 10 Hz can easily penetrate through the compressed fuel deuterium of diameter 1 -- 10 3 μm. (author)

  2. Low-frequency oscillations at high density in JFT-2

    International Nuclear Information System (INIS)

    Maeno, Masaki; Katagiri, Masaki; Suzuki, Norio; Fujisawa, Noboru

    1977-12-01

    Low-frequency oscillations in a plasma were measured with magnetic probes and Si surface-barrier detectors, and behaviour of the high density plasmas was studied. The plasma current profile in the phase of decreasing density after the interruption of gas input is more peaked than during gas input. The introduction of hydrogen during a discharge results in a reduction of the impurities flux. The increase of density by fast gas input is limited with a negative voltage spike. Immediately before a negative voltage spike, oscillations of m=1,2 grow, leading to the spike. (auth.)

  3. Possible new form of matter at high density

    International Nuclear Information System (INIS)

    Lee, T.D.

    1974-01-01

    As a preliminary to discussion of the possibility of new forms of matter at high density, questions relating to the vacuum and vacuum excitation are considered. A quasi-classical approach to the development of abnormal nuclear states is undertaken using a Fermi gas of nucleons of uniform density. Discontinuous transitions are considered in the sigma model (tree approximation) followed by brief consideration of higher order loop diagrams. Production and detection of abnormal nuclear states are discussed in the context of high energy heavy ion collisions. Remarks are made on motivation for such research. 8 figures

  4. Characterization of composite high density polyethylene and layered zirconium phosphate

    International Nuclear Information System (INIS)

    Lino, Adan S.; Silva, Daniela F.; Mendes, Luis C.

    2011-01-01

    Zirconium phosphate (ZrP) (2 w%), synthesized by direct precipitation method, was used in the preparation of composite with high density polyethylene (HDPE), through extrusion processing in the molten state. Wide angle x-ray diffraction (WAXD), stress-strain mechanical analysis and scanning electron microscopy (SEM) techniques were used for ZrP, neat polymer and composite mechanical and morphologic characterization. Although there was a slight increase in the Young modulus, WAXD and SEM analysis showed that the intercalation of the HDPE matrix in the filler galleries did not occur, probably due to the insufficient lamellae spacing to intercalate the polymer chains. Then, a microcomposite was achieved. (author)

  5. Structure of high-density amorphous ice under pressure

    International Nuclear Information System (INIS)

    Klotz, S.; Hamel, G.; Loveday, J.S.; Nelmes, R.J.; Guthrie, M.; Soper, A.K.

    2002-01-01

    We report in situ neutron diffraction studies of high-density amorphous ice (HDA) at 100 K at pressures up to 2.2 GPa. We find that the compression is achieved by a strong contraction (∼20%) of the second neighbor coordination shell, so that at 2.2 GPa it closely approaches the first coordination shell, which itself remains intact in both structure and size. The hydrogen bond orientations suggest an absence of hydrogen bonding between first and second shells and that HDA has increasingly interpenetrating hydrogen bond networks under pressure

  6. Behavior of high-density spent-fuel storage racks

    International Nuclear Information System (INIS)

    Bailey, W.J.

    1986-08-01

    Included in this report is a summary of information on neutron-absorbing materials such as B 4 C in an aluminum matrix or organic binder material, stainless steel-boron and aluminum-boron alloys, and stainless steetl-clad cadmium that are used in high-density spent fuel storage racks. A list of the types of neutron-absorbing materials being used in spent fuel storage racks at domestic commercial plants is provided. Recent cases at several domestic plants where swelling of rack side plates (where the B 4 C in an aluminum matrix and B 4 C in an organic binder material were located) occurred are reviewed

  7. 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.

  8. 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.

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

    OpenAIRE

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

    2014-01-01

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

  10. Dynamics of the EEG of human brain in the gradient magnetic fields of geological faults in different geographical and climatic zones

    Science.gov (United States)

    Pobachenko, S. V.; Sokolov, M. V.; Grigoriev, P. E.; Vasilieva, I. V.

    2017-11-01

    There are presented the results of experimental studies of the dynamics of indices of the functional state of a person located within the zones characterized by anomalous parameters of spatial distribution of magnetic field vector values. It is shown that these geophysical modifications have a pronounced effect on the dynamics of electrical activity indices of the human brain, regardless of geographic and climatic conditions.

  11. Combined EEG-fNIRS Decoding of Motor Attempt and Imagery for Brain Switch Control: An Offline Study in Patients With Tetraplegia

    NARCIS (Netherlands)

    Blokland, Y.M.; Spyrou, L.; Thijssen, D.H.J.; Eijsvogels, T.M.; Colier, W.N.; Floor-Westerdijk, M.; Vlek, R.; Bruhn, J.; Farquhar, J.D.R.

    2014-01-01

    Combining electrophysiological and hemodynamic features is a novel approach for improving current performance of brain switches based on sensorimotor rhythms (SMR). This study was conducted with a dual purpose: to test the feasibility of using a combined electroencephalogram/functional near-infrared

  12. Combined EEG-fNIRS decoding of motor attempt and imagery for brain switch control: an offline study in patients with tetraplegia

    NARCIS (Netherlands)

    Blokland, Y.M.; Spyrou, L.; Thijssen, D.H.J.; Eijsvogels, T.M.H.; Colier, W.N.J.M.; Floor-Westerdijk, M.J.; Vlek, R.J.; Bruhn, J.; Farquhar, J.D.R.

    2014-01-01

    Combining electrophysiological and hemodynamic features is a novel approach for improving current performance of brain switches based on sensorimotor rhythms (SMR). This study was conducted with a dual purpose: to test the feasibility of using a combined electroencephalogram/functional near-infrared

  13. Multiplexed, high density electrophysiology with nanofabricated neural probes.

    Directory of Open Access Journals (Sweden)

    Jiangang Du

    Full Text Available Extracellular electrode arrays can reveal the neuronal network correlates of behavior with single-cell, single-spike, and sub-millisecond resolution. However, implantable electrodes are inherently invasive, and efforts to scale up the number and density of recording sites must compromise on device size in order to connect the electrodes. Here, we report on silicon-based neural probes employing nanofabricated, high-density electrical leads. Furthermore, we address the challenge of reading out multichannel data with an application-specific integrated circuit (ASIC performing signal amplification, band-pass filtering, and multiplexing functions. We demonstrate high spatial resolution extracellular measurements with a fully integrated, low noise 64-channel system weighing just 330 mg. The on-chip multiplexers make possible recordings with substantially fewer external wires than the number of input channels. By combining nanofabricated probes with ASICs we have implemented a system for performing large-scale, high-density electrophysiology in small, freely behaving animals that is both minimally invasive and highly scalable.

  14. Mixing of high density solution in vertical upward flow

    International Nuclear Information System (INIS)

    Kumamaru, Hiroshige; Hosogi, Nobuyoshi; Komada, Toshiaki; Fujiwara, Yoshiki

    1999-01-01

    Experimental and analytical studies have been performed in order to provide fundamental data and a numerical calculation model on the mixing of boric acid solution, injected from the standby liquid control system (SLCS), under a low natural circulation flow during an ATWS in a BWR. First, fundamental experiments on the mixing of high-density solution in vertically-upward water flow have been performed by using a small apparatus. Mixing patterns observed in the experiments have been classified to two groups, i.e. complete mixing (entrainment) and incomplete mixing (entrainment). In the complete mixing, the injected high-density solution is mixed (entrained) completely into the vertically-upward water flow. From the experiments, the minimum water flow rates in which the complete mixing (entrainment) is achieved have been obtained for various solution densities and solution injection rates. Secondly, two-dimensional numerical calculations have been performed. A continuity equation for total fluid, momentum equations in two directions and a continuity equation for solute are solved by using the finite difference method for discretization method and by following the MAC method for solution procedure. The calculations have predicted nearly the minimum water flow rate in which the complete mixing is achieved, while the calculations have been performed only for one combination of the solution density and solution injection rate until now. (author)

  15. Ultra-Stretchable Interconnects for High-Density Stretchable Electronics

    Directory of Open Access Journals (Sweden)

    Salman Shafqat

    2017-09-01

    Full Text Available The exciting field of stretchable electronics (SE promises numerous novel applications, particularly in-body and medical diagnostics devices. However, future advanced SE miniature devices will require high-density, extremely stretchable interconnects with micron-scale footprints, which calls for proven standardized (complementary metal-oxide semiconductor (CMOS-type process recipes using bulk integrated circuit (IC microfabrication tools and fine-pitch photolithography patterning. Here, we address this combined challenge of microfabrication with extreme stretchability for high-density SE devices by introducing CMOS-enabled, free-standing, miniaturized interconnect structures that fully exploit their 3D kinematic freedom through an interplay of buckling, torsion, and bending to maximize stretchability. Integration with standard CMOS-type batch processing is assured by utilizing the Flex-to-Rigid (F2R post-processing technology to make the back-end-of-line interconnect structures free-standing, thus enabling the routine microfabrication of highly-stretchable interconnects. The performance and reproducibility of these free-standing structures is promising: an elastic stretch beyond 2000% and ultimate (plastic stretch beyond 3000%, with <0.3% resistance change, and >10 million cycles at 1000% stretch with <1% resistance change. This generic technology provides a new route to exciting highly-stretchable miniature devices.

  16. Manufacture of sintered bricks of high density from beryllium oxide

    International Nuclear Information System (INIS)

    Pointud, R.; Rispal, Ch.; Le Garec, M.

    1959-01-01

    Beryllium oxide bricks of nuclear purity 100 x 100 x 50 and 100 x 100 x 100 mm of very high density (between 2.85 and 3.00) are manufactured by sintering under pressure in graphite moulds at temperatures between 1,750 and 1,850 deg. C, and under a pressure of 150 kg/cm 2 . The physico-chemical state of the saw material is of considerable importance with regard to the success of the sintering operation. In addition, a study of the sintering of a BeO mixture with 3 to 5 per cent of boron introduced in the form of boric acid, boron carbide or elementary boron shows that high densities can only be obtained by sintering under pressure. For technical reasons of manufacture, only the mixture based on boron carbide is used. The sintering is carried out in graphite moulds at 1500 deg. C under 150 kg/cm 2 pressure, and bricks can be obtained with density between 2,85 and 2,90. Laboratory studies and the industrial manufacture of various sinters are described in detail. (author) [fr

  17. Development of technology of high density LEU dispersion fuel fabrication

    International Nuclear Information System (INIS)

    Wiencek, T.; Totev, T.

    2007-01-01

    Advanced Materials Fabrication Facilities at Argonne National Laboratory have been involved in development of LEU dispersion fuel for research and test reactors from the beginning of RERTR program. This paper presents development of technology of high density LEU dispersion fuel fabrication for full size plate type fuel elements. A brief description of Advanced Materials Fabrication Facilities where development of the technology was carried out is given. A flow diagram of the manufacturing process is presented. U-Mo powder was manufactured by the rotating electrode process. The atomization produced a U-Mo alloy powder with a relatively uniform size distribution and a nearly spherical shape. Test plates were fabricated using tungsten and depleted U-7 wt.% Mo alloy, 4043 Al and Al-2 wt% Si matrices with Al 6061 aluminum alloy for the cladding. During the development of the technology of manufacturing of full size high density LEU dispersion fuel plates special attention was paid to meet the required homogeneity, bonding, dimensions, fuel out of zone and other mechanical characteristics of the plates.

  18. Presurgical EEG-fMRI in a complex clinical case with seizure recurrence after epilepsy surgery

    Science.gov (United States)

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

    2013-01-01

    Epilepsy surgery has improved over the last decade, but non-seizure-free outcome remains at 10%–40% in temporal lobe epilepsy (TLE) and 40%–60% in extratemporal lobe epilepsy (ETLE). This paper reports a complex multifocal case. With a normal magnetic resonance imaging (MRI) result and nonlocalizing electroencephalography (EEG) findings (bilateral TLE and ETLE, with more interictal epileptiform discharges [IEDs] in the right frontal and temporal regions), a presurgical EEG-functional MRI (fMRI) was performed before the intraoperative intracranial EEG (icEEG) monitoring (icEEG with right hemispheric coverage). Our previous EEG-fMRI analysis results (IEDs in the left hemisphere alone) were contradictory to the EEG and icEEG findings (IEDs in the right frontal and temporal regions). Thus, the EEG-fMRI data were reanalyzed with newly identified IED onsets and different fMRI model options. The reanalyzed EEG-fMRI findings were largely concordant with those of EEG and icEEG, and the failure of our previous EEG-fMRI analysis may lie in the inaccurate identification of IEDs and wrong usage of model options. The right frontal and temporal regions were resected in surgery, and dual pathology (hippocampus sclerosis and focal cortical dysplasia in the extrahippocampal region) was found. The patient became seizure-free for 3 months, but his seizures restarted after antiepileptic drugs (AEDs) were stopped. The seizures were not well controlled after resuming AEDs. Postsurgical EEGs indicated that ictal spikes in the right frontal and temporal regions reduced, while those in the left hemisphere became prominent. This case suggested that (1) EEG-fMRI is valuable in presurgical evaluation, but requires caution; and (2) the intact seizure focus in the remaining brain may cause the non-seizure-free outcome. PMID:23926432

  19. EEG source imaging during two Qigong meditations.

    Science.gov (United States)

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

    2012-08-01

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

  20. Computation of Surface Laplacian for tri-polar ring electrodes on high-density realistic geometry head model.

    Science.gov (United States)

    Junwei Ma; Han Yuan; Sunderam, Sridhar; Besio, Walter; Lei Ding

    2017-07-01

    Neural activity inside the human brain generate electrical signals that can be detected on the scalp. Electroencephalograph (EEG) is one of the most widely utilized techniques helping physicians and researchers to diagnose and understand various brain diseases. Due to its nature, EEG signals have very high temporal resolution but poor spatial resolution. To achieve higher spatial resolution, a novel tri-polar concentric ring electrode (TCRE) has been developed to directly measure Surface Laplacian (SL). The objective of the present study is to accurately calculate SL for TCRE based on a realistic geometry head model. A locally dense mesh was proposed to represent the head surface, where the local dense parts were to match the small structural components in TCRE. Other areas without dense mesh were used for the purpose of reducing computational load. We conducted computer simulations to evaluate the performance of the proposed mesh and evaluated possible numerical errors as compared with a low-density model. Finally, with achieved accuracy, we presented the computed forward lead field of SL for TCRE for the first time in a realistic geometry head model and demonstrated that it has better spatial resolution than computed SL from classic EEG recordings.

  1. FFT transformed quantitative EEG analysis of short term memory load.

    Science.gov (United States)

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

    2015-07-01

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

  2. Higher-Order Spectrum in Understanding Nonlinearity in EEG Rhythms

    Directory of Open Access Journals (Sweden)

    Cauchy Pradhan

    2012-01-01

    Full Text Available The fundamental nature of the brain's electrical activities recorded as electroencephalogram (EEG remains unknown. Linear stochastic models and spectral estimates are the most common methods for the analysis of EEG because of their robustness, simplicity of interpretation, and apparent association with rhythmic behavioral patterns in nature. In this paper, we extend the use of higher-order spectrum in order to indicate the hidden characteristics of EEG signals that simply do not arise from random processes. The higher-order spectrum is an extension Fourier spectrum that uses higher moments for spectral estimates. This essentially nullifies all Gaussian random effects, therefore, can reveal non-Gaussian and nonlinear characteristics in the complex patterns of EEG time series. The paper demonstrates the distinguishing features of bispectral analysis for chaotic systems, filtered noises, and normal background EEG activity. The bispectrum analysis detects nonlinear interactions; however, it does not quantify the coupling strength. The squared bicoherence in the nonredundant region has been estimated to demonstrate nonlinear coupling. The bicoherence values are minimal for white Gaussian noises (WGNs and filtered noises. Higher bicoherence values in chaotic time series and normal background EEG activities are indicative of nonlinear coupling in these systems. The paper shows utility of bispectral methods as an analytical tool in understanding neural process underlying human EEG patterns.

  3. Discovering EEG resting state alterations of semantic dementia.

    Science.gov (United States)

    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.

  4. Seizure classification in EEG signals utilizing Hilbert-Huang transform

    OpenAIRE

    Oweis, Rami J; Abdulhay, Enas W

    2011-01-01

    Abstract Background Classification method capable of recognizing abnormal activities of the brain functionality are either brain imaging or brain signal analysis. The abnormal activity of interest in this study is characterized by a disturbance caused by changes in neuronal electrochemical activity that results in abnormal synchronous discharges. The method aims at helping physicians discriminate between healthy and seizure electroencephalographic (EEG) signals. Method Discrimination in this ...

  5. Novel Methods for Measuring Depth of Anesthesia by Quantifying Dominant Information Flow in Multichannel EEGs

    Directory of Open Access Journals (Sweden)

    Kab-Mun Cha

    2017-01-01

    Full Text Available In this paper, we propose novel methods for measuring depth of anesthesia (DOA by quantifying dominant information flow in multichannel EEGs. Conventional methods mainly use few EEG channels independently and most of multichannel EEG based studies are limited to specific regions of the brain. Therefore the function of the cerebral cortex over wide brain regions is hardly reflected in DOA measurement. Here, DOA is measured by the quantification of dominant information flow obtained from principle bipartition. Three bipartitioning methods are used to detect the dominant information flow in entire EEG channels and the dominant information flow is quantified by calculating information entropy. High correlation between the proposed measures and the plasma concentration of propofol is confirmed from the experimental results of clinical data in 39 subjects. To illustrate the performance of the proposed methods more easily we present the results for multichannel EEG on a two-dimensional (2D brain map.

  6. Driver-response relationships between frontal EEG and respiration during affective audiovisual stimuli.

    Science.gov (United States)

    Kroupi, Eleni; Vesin, Jean-Marc; Ebrahimi, Touradj

    2013-01-01

    The complementary nature and the coordinative tendencies of brain and body are essential to the way humans function. Although static features from brain and body signals have been shown to reflect emotions, the dynamic interrelation of the two systems during emotional processes is still in its infancy. This study aims at investigating the way brain signals captured by Electroencephalography (EEG) and bodily responses reflected in respiration interact when watching music clips. A non-linear measure is applied to frontal EEG and respiration to determine the driver/driven relationship between these two modalities. The results reveal a unidirectional dependence from respiration to EEG which adds evidence to the bodily-feedback theory.

  7. Corrected Four-Sphere Head Model for EEG Signals.

    Science.gov (United States)

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

    2017-01-01

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

  8. Corrected Four-Sphere Head Model for EEG Signals

    Directory of Open Access Journals (Sweden)

    Solveig Næss

    2017-10-01

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

  9. 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.

  10. 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.

  11. 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.

  12. EEG feature selection method based on decision tree.

    Science.gov (United States)

    Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

    2015-01-01

    This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

  13. An Evaluation of EEG Scanner’s Dependence on the Imaging Technique, Forward Model Computation Method, and Array Dimensionality

    DEFF Research Database (Denmark)

    Stahlhut, Carsten; Attias, Hagai Thomas; Stopczynski, Arkadiusz

    2012-01-01

    EEG source reconstruction involves solving an inverse problem that is highly ill-posed and dependent on a generally fixed forward propagation model. In this contribution we compare a low and high density EEG setup’s dependence on correct forward modeling. Specifically, we examine how different...... forward models affect the source estimates obtained using four inverse solvers Minimum-Norm, LORETA, Minimum-Variance Adaptive Beamformer, and Sparse Bayesian Learning....

  14. Validation of a smartphone-based EEG among people with epilepsy: A prospective study

    DEFF Research Database (Denmark)

    Mckenzie, Erica D.; Lim, Andrew S P; Leung, Edward C W

    2017-01-01

    Our objective was to assess the ability of a smartphone-based electroencephalography (EEG) application, the Smartphone Brain Scanner-2 (SBS2), to detect epileptiform abnormalities compared to standard clinical EEG. The SBS2 system consists of an Android tablet wirelessly connected to a 14-electrode...

  15. 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

  16. Effects of magnesium sulphate on amplitude-integrated continuous EEG in asphyxiated term neonates

    NARCIS (Netherlands)

    Groenendaal, F; Rademaker, CMA; Toet, MC; de Vries, LS

    2002-01-01

    In this study it is hypothesized that magnesium sulphate in asphyxiated full-term neonates could lead to a gradual improvement in background pattern of the amplitude integrated EEG (aEEG), an early marker of hypoxic-ischaemic brain injury. In a double-blind, randomized, controlled pilot study of 22

  17. A distributed current stimulator ASIC for high density neural stimulation.

    Science.gov (United States)

    Jeong Hoan Park; Chaebin Kim; Seung-Hee Ahn; Tae Mok Gwon; Joonsoo Jeong; Sang Beom Jun; Sung June Kim

    2016-08-01

    This paper presents a novel distributed neural stimulator scheme. Instead of a single stimulator ASIC in the package, multiple ASICs are embedded at each electrode site for stimulation with a high density electrode array. This distributed architecture enables the simplification of wiring between electrodes and stimulator ASIC that otherwise could become too complex as the number of electrode increases. The individual ASIC chip is designed to have a shared data bus that independently controls multiple stimulating channels. Therefore, the number of metal lines is determined by the distributed ASICs, not by the channel number. The function of current steering is also implemented within each ASIC in order to increase the effective number of channels via pseudo channel stimulation. Therefore, the chip area can be used more efficiently. The designed chip was fabricated with area of 0.3 mm2 using 0.18 μm BCDMOS process, and the bench-top test was also conducted to validate chip performance.

  18. Automatic Calibration of High Density Electric Muscle Stimulation

    DEFF Research Database (Denmark)

    Knibbe, Jarrod; Strohmeier, Paul; Boring, Sebastian

    2017-01-01

    . (2) EMS requires time consuming, expert calibration -- confining these interaction techniques to the lab. EMS arrays have been shown to increase stimulation resolution, but as calibration complexity increases exponentially as more electrodes are used, we require heuristics or automated procedures......Electric muscle stimulation (EMS) can enable mobile force feedback, support pedestrian navigation, or confer object affordances. To date, however, EMS is limited by two interlinked problems. (1) EMS is low resolution -- achieving only coarse movements and constraining opportunities for exploration...... for successful calibration. We explore the feasibility of using electromyography (EMG) to auto-calibrate high density EMS arrays. We determine regions of muscle activity during human-performed gestures, to inform stimulation patterns for EMS-performed gestures. We report on a study which shows that auto...

  19. A high-density lipoprotein-mediated drug delivery system.

    Science.gov (United States)

    Mo, Zhong-Cheng; Ren, Kun; Liu, Xing; Tang, Zhen-Li; Yi, Guang-Hui

    2016-11-15

    High-density lipoprotein (HDL) is a comparatively dense and small lipoprotein that can carry lipids as a multifunctional aggregate in plasma. Several studies have shown that increasing the levels or improving the functionality of HDL is a promising target for treating a wide variety of diseases. Among lipoproteins, HDL particles possess unique physicochemical properties, including naturally synthesized physiological components, amphipathic apolipoproteins, lipid-loading and hydrophobic agent-incorporating characteristics, specific protein-protein interactions, heterogeneity, nanoparticles, and smaller size. Recently, the feasibility and superiority of using HDL particles as drug delivery vehicles have been of great interest. In this review, we summarize the structure, constituents, biogenesis, remodeling, and reconstitution of HDL drug delivery systems, focusing on their delivery capability, characteristics, applications, manufacturing, and drug-loading and drug-targeting characteristics. Finally, the future prospects are presented regarding the clinical application and challenges of using HDL as a pharmacodelivery carrier. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Single-Readout High-Density Memristor Crossbar

    KAUST Repository

    Zidan, M. A.

    2016-01-07

    High-density memristor-crossbar architecture is a very promising technology for future computing systems. The simplicity of the gateless-crossbar structure is both its principal advantage and the source of undesired sneak-paths of current. This parasitic current could consume an enormous amount of energy and ruin the readout process. We introduce new adaptive-threshold readout techniques that utilize the locality and hierarchy properties of the computer-memory system to address the sneak-paths problem. The proposed methods require a single memory access per pixel for an array readout. Besides, the memristive crossbar consumes an order of magnitude less power than state-of-the-art readout techniques.

  1. High-Density Lipoproteins and the Immune System

    Directory of Open Access Journals (Sweden)

    Hidesuke Kaji

    2013-01-01

    Full Text Available High-density lipoprotein (HDL plays a major role in vasodilation and in the reduction of low-density lipoprotein (LDL oxidation, inflammation, apoptosis, thrombosis, and infection; however, HDL is now less functional in these roles under certain conditions. This paper focuses on HDL, its anti-inflammation behavior, and the mechanisms by which HDL interacts with components of the innate and adaptive immune systems. Genome-wide association studies (GWAS and proteomic studies have elucidated important molecules involved in the interaction between HDL and the immune system. An understanding of these mechanisms is expected to be useful for the prevention and treatment of chronic inflammation due to metabolic syndrome, atherosclerosis, or various autoimmune diseases.

  2. Reaction of unirradiated high-density fuel with aluminum

    International Nuclear Information System (INIS)

    Wiencek, T.C.; Meyer, M.K.; Prokofiev, I.G.; Keiser, D.D.

    1997-01-01

    Excellent dispersion fuel performance requires that fuel particles remain stable and do not react significantly with the surrounding aluminum matrix. A series of high-density fuels, which contain uranium densities >12 g/cm 3 , have been fabricated into plates. As part of standard processing, all of these fuels were subjected to a blister anneal of 1 h at 485 deg. C. Changes in plate thickness were measured and evaluated. From these results, suppositions about the probable irradiation properties of these fuels have been proposed. In addition, two fuels, U-10 wt% Mo and U 2 Mo, were subjected to various heat treatments and were found to be very stable in an aluminum matrix. On the basis of the experimental data, hypotheses of the irradiation behavior of these fuels are presented. (author)

  3. High-current discharge channel contraction in high density gas

    International Nuclear Information System (INIS)

    Rutberg, Ph. G.; Bogomaz, A. A.; Pinchuk, M. E.; Budin, A. V.; Leks, A. G.; Pozubenkov, A. A.

    2011-01-01

    Research results for discharges at current amplitudes of 0.5-1.6 MA and current rise rate of ∼10 10 A/s are presented. The discharge is performed in the hydrogen environment at the initial pressure of 5-35 MPa. Initiation is implemented by a wire explosion. The time length of the first half-period of the discharge current is 70-150 μs. Under such conditions, discharge channel contraction is observed; the contraction is followed by soft x-ray radiation. The phenomena are discussed, which are determined by high density of the gas surrounding the discharge channel. These phenomena are increase of the current critical value, where the channel contraction begins and growth of temperature in the axis region of the channel, where the initial density of the gas increases.

  4. Diquark Bose Condensates in High Density Matter and Instantons

    International Nuclear Information System (INIS)

    Rapp, R.; Shuryak, E.; Schaefer, T.; Velkovsky, M.

    1998-01-01

    Instantons lead to strong correlations between up and down quarks with spin zero and antisymmetric color wave functions. In cold and dense matter, n b >n c ≅1 fm -3 and T c ∼50 thinspthinspMeV, these pairs Bose condense, replacing the usual left-angle bar qq right-angle condensate and restoring chiral symmetry. At high density, the ground state is a color superconductor in which diquarks play the role of Cooper pairs. An interesting toy model is provided by QCD with two colors: it has a particle-antiparticle symmetry which relates left-angle bar qq right-angle and left-angle qq right-angle condensates. copyright 1998 The American Physical Society

  5. High-Density Near-Field Optical Disc Recording

    Science.gov (United States)

    Shinoda, Masataka; Saito, Kimihiro; Ishimoto, Tsutomu; Kondo, Takao; Nakaoki, Ariyoshi; Ide, Naoki; Furuki, Motohiro; Takeda, Minoru; Akiyama, Yuji; Shimouma, Takashi; Yamamoto, Masanobu

    2005-05-01

    We developed a high-density near-field optical recording disc system using a solid immersion lens. The near-field optical pick-up consists of a solid immersion lens with a numerical aperture of 1.84. The laser wavelength for recording is 405 nm. In order to realize the near-field optical recording disc, we used a phase-change recording media and a molded polycarbonate substrate. A clear eye pattern of 112 GB capacity with 160 nm track pitch and 50 nm bit length was observed. The equivalent areal density is 80.6 Gbit/in2. The bottom bit error rate of 3 tracks-write was 4.5× 10-5. The readout power margin and the recording power margin were ± 30.4% and ± 11.2%, respectively.

  6. EVALUATION OF SOME PLUM CULTIVARS IN A HIGH DENSITY SYSTEM

    Directory of Open Access Journals (Sweden)

    Madalina Butac

    2014-12-01

    Full Text Available Three plum cultivars bred in Romania (‘Carpatin’, ‘Centenar’ and ‘Tita’ were tested together with several standards (‘Cacanska Rodna’ and ‘Stanley’ in a high density experimental orchard established at Pitesti - Maracineni in the spring of 2009, with spacing 4 x 2.25 m. Trees were trained as spindles, grafted on ‘Saint Julian’ rootstock. In the orchard the following characteristics were evaluated: tree vigour based upon measuring of trunk-diameter, yields in kg/tree, time of fruit ripening and basic parameters of fruit quality. All Romanian varieties were characterized by earliness and large fruit, but production was relatively small. Instead, foreign varieties were characterized by high productivity in the 4th year after planting.

  7. High density thermite mixture for shaped charge ordnance disposal

    Directory of Open Access Journals (Sweden)

    Tamer Elshenawy

    2017-10-01

    Full Text Available The effect of thermite mixture based on aluminum and ferric oxides for ammunition neutralization has been studied and tested. Thermochemical calculations have been carried out for different percentage of Al using Chemical Equilibrium Code to expect the highest performance thermite mixture used for shaped charge ordnance disposal. Densities and enthalpy of different formulations have been calculated and demonstrated. The optimized thermite formulation has been prepared experimentally using cold iso-static pressing technique, which exhibited relatively high density and high burning rate thermite mixture. The produced green product compacted powder mixture was tested against small caliber shaped charge bomblet for neutralization. Theoretical and experimental results showed that the prepared thermite mixture containing 33% of aluminum as a fuel with ferric oxide can be successfully used for shaped charge ordnance disposal.

  8. The stability of the High-Density Z-Pinch

    International Nuclear Information System (INIS)

    Glasser, A.H.; Nebel, R.A.

    1989-01-01

    Fiber-initiated High Density Z-Pinches at Los Alamos, NRL, and Karlsruhe have shown anomalously good stability. Kink modes are never seen, and sausage modes are at least delayed until late in the discharge. The success of these devices in reaching fusion conditions may depend on maintaining and understanding this anomalous stability. We have developed two numerical methods to study the stability in the regime where fluid theory is valid. While our methods are applicable to all modes, we will describe them only for the m = 0 sausage mode. The appearance of sausage modes late in the discharge and the total absence of kink modes suggest that an understanding of sausage modes is more urgent, and it is also simpler. 14 refs., 8 figs

  9. The stability of the high-density z-pinch

    International Nuclear Information System (INIS)

    Glasser, A.H.; Nebel, R.A.

    1989-01-01

    Fiber-initiated High Density Z-Pinches at Los Alamos, NRL, and Karlsruhe have shown anomalously good stability. Kink modes are never seen, and sausage modes are at least delayed until late in the discharge. The success of these devices in reaching fusion conditions may depend on maintaining and understanding this anomalous stability. We have developed two numerical methods to study the stability in the regime where fluid theory is valid. While our methods are applicable to all modes, we will describe them only for the m=0 sausage mode. The appearance of sausage modes late in the discharge and the total absence of kink modes suggest that an understanding of sausage modes is more urgent, and it is also simpler

  10. Corrosion of high-density sintered tungsten alloys. Part 2

    International Nuclear Information System (INIS)

    Batten, J.J.; Moore, B.T.

    1988-12-01

    The behaviour of four high-density sintered tungsten alloys has been evluated and compared with that of pure tungsten. Rates of corrosion during the cyclic humidity and the salt mist tests were ascertained from weight loss measurements. Insight into the corrosion mechanism was gained from the nature of the corrosion products and an examination of the corroded surfaces. In the tests, the alloy 95% W, 2.5% Ni, 1.5% Fe was the most corrosion resistant. The data showed that copper as an alloying element accelerates corrosion of tungsten alloys. Both attack on the tungsten particles and the binder phase were observed together with tungsten grain loss. 6 refs., 3 tabs.,

  11. High density high-TC ceramic superconductors by hot pressing

    International Nuclear Information System (INIS)

    Mak, S.; Chaklader, A.C.D.

    1989-01-01

    High density and high T C superconductor specimens, YBa 2 Cu 3 O x , have been produced by hot-pressing. The factors studied are the effect of hot pressing on the density, the oxygen stoichiometry, the crystal structure, and the critical temperature. Hot pressing followed by heat treatment increased the density of the specimen to 93%. The hot pressing itself did not significantly affect the oxygen content in the specimen, and although the crystal structure appeared to be orthorhombic, the specimens were not superconducting above liquid nitrogen temperature. The superconductivity was restored after head treatment in oxygen. The highest critical temperature (T C ) of the hot pressed pellets was 82K, which was slightly lower than the T C that could be obtained with the cold pressed/sintered pellets. (6 refs., 5 figs., tab.)

  12. Evaluation of the radiation resistance of high-density polyethylene

    International Nuclear Information System (INIS)

    Dougherty, D.R.; Adams, J.W.; Barletta, R.R.

    1984-03-01

    Mechanical tests following gamma irradiation and creep tests during irradiation have been conducted on high-density polyethylene (HDPE) to provide data to help assess the adequacy of this material for use in high integrity containers (HICs). Two types of HDPE, a highly cross-linked rotationally molded material and a non-cross-linked blow molded material, were used in these tests. Gamma-ray irradiations were performed at several dose rates in environments of air, Barnwell and Hanford backfill soils, and ion-exchange resins. The results of tensile and bend tests on these materials following irradiation are presented along with results on creep during irradiation. 8 references, 9 figures, 2 tables

  13. The Pulsed High Density Experiment (PHDX) Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Slough, John P. [Univ. of Washington, Seattle, WA (United States); Andreason, Samuel [Univ. of Washington, Seattle, WA (United States)

    2017-04-27

    The purpose of this paper is to present the conclusions that can be drawn from the Field Reversed Configuration (FRC) formation experiments conducted on the Pulsed High Density experiment (PHD) at the University of Washington. The experiment is ongoing. The experimental goal for this first stage of PHD was to generate a stable, high flux (>10 mWb), high energy (>10 KJ) target FRC. Such results would be adequate as a starting point for several later experiments. This work focuses on experimental implementation and the results of the first four month run. Difficulties were encountered due to the initial on-axis plasma ionization source. Flux trapping with this ionization source acting alone was insufficient to accomplish experimental objectives. Additional ionization methods were utilized to overcome this difficulty. A more ideal plasma source layout is suggested and will be explored during a forthcoming work.

  14. High-Density Stacked Ru Nanocrystals for Nonvolatile Memory Application

    International Nuclear Information System (INIS)

    Ping, Mao; Zhi-Gang, Zhang; Li-Yang, Pan; Jun, Xu; Pei-Yi, Chen

    2009-01-01

    Stacked ruthenium (Ru) nanocrystals (NCs) are formed by rapid thermal annealing for the whole gate stacks and embedded in memory structure, which is compatible with conventional CMOS technology. Ru NCs with high density (3 × 10 12 cm −2 ), small size (2–4 nm) and good uniformity both in aerial distribution and morphology are formed. Attributed to the higher surface trap density, a memory window of 5.2 V is obtained with stacked Ru NCs in comparison to that of 3.5 V with single-layer samples. The stacked Ru NCs device also exhibits much better retention performance because of Coulomb blockade and vertical uniformity between stacked Ru NCs

  15. Single-Readout High-Density Memristor Crossbar

    KAUST Repository

    Zidan, M. A.; Omran, Hesham; Naous, Rawan; Salem, Ahmed Sultan; Fahmy, H. A. H.; Lu, W. D.; Salama, Khaled N.

    2016-01-01

    High-density memristor-crossbar architecture is a very promising technology for future computing systems. The simplicity of the gateless-crossbar structure is both its principal advantage and the source of undesired sneak-paths of current. This parasitic current could consume an enormous amount of energy and ruin the readout process. We introduce new adaptive-threshold readout techniques that utilize the locality and hierarchy properties of the computer-memory system to address the sneak-paths problem. The proposed methods require a single memory access per pixel for an array readout. Besides, the memristive crossbar consumes an order of magnitude less power than state-of-the-art readout techniques.

  16. High density submicron magnetoresistive random access memory (invited)

    Science.gov (United States)

    Tehrani, S.; Chen, E.; Durlam, M.; DeHerrera, M.; Slaughter, J. M.; Shi, J.; Kerszykowski, G.

    1999-04-01

    Various giant magnetoresistance material structures were patterned and studied for their potential as memory elements. The preferred memory element, based on pseudo-spin valve structures, was designed with two magnetic stacks (NiFeCo/CoFe) of different thickness with Cu as an interlayer. The difference in thickness results in dissimilar switching fields due to the shape anisotropy at deep submicron dimensions. It was found that a lower switching current can be achieved when the bits have a word line that wraps around the bit 1.5 times. Submicron memory elements integrated with complementary metal-oxide-semiconductor (CMOS) transistors maintained their characteristics and no degradation to the CMOS devices was observed. Selectivity between memory elements in high-density arrays was demonstrated.

  17. The alterations in high density polyethylene properties with gamma irradiation

    Science.gov (United States)

    Zaki, M. F.; Elshaer, Y. H.; Taha, Doaa. H.

    2017-10-01

    In the present investigation, high density polyethylene (HDPE) polymer has been used to study the alterations in its properties under gamma-irradiation. Physico-chemical properties have been investigated with different spectroscopy techniques, Fourier Transform Infrared spectroscopy (FTIR), X-ray diffraction (XRD), biocompatibility properties, as well as, mechanical properties change. The FT-IR analysis shows the formation of new band at 1716 cm-1 that is attributed to the oxidation of irradiated polymer chains, which is due to the formation of carbonyl groups (C˭O). XRD patterns show that a decrease in the crystallite size and increase in the Full Width at Half Maximum (FWHM). This means that the crystallinity of irradiated samples is decreased with increase in gamma dose. The contact angle measurements show an increase in the surface free energy as the gamma irradiation increases. The measurements of mechanical properties of irradiated HDPE samples were discussed.

  18. Relaxation Time of High-Density Amorphous Ice

    Science.gov (United States)

    Handle, Philip H.; Seidl, Markus; Loerting, Thomas

    2012-06-01

    Amorphous water plays a fundamental role in astrophysics, cryoelectron microscopy, hydration of matter, and our understanding of anomalous liquid water properties. Yet, the characteristics of the relaxation processes taking place in high-density amorphous ice (HDA) are unknown. We here reveal that the relaxation processes in HDA at 110-135 K at 0.1-0.2 GPa are of collective and global nature, resembling the alpha relaxation in glassy material. Measured relaxation times suggest liquid-like relaxation characteristics in the vicinity of the crystallization temperature at 145 K. By carefully relaxing pressurized HDA for several hours at 135 K, we produce a state that is closer to the ideal glass state than all HDA states discussed so far in literature.

  19. High-density amorphous ice: A path-integral simulation

    Science.gov (United States)

    Herrero, Carlos P.; Ramírez, Rafael

    2012-09-01

    Structural and thermodynamic properties of high-density amorphous (HDA) ice have been studied by path-integral molecular dynamics simulations in the isothermal-isobaric ensemble. Interatomic interactions were modeled by using the effective q-TIP4P/F potential for flexible water. Quantum nuclear motion is found to affect several observable properties of the amorphous solid. At low temperature (T = 50 K) the molar volume of HDA ice is found to increase by 6%, and the intramolecular O-H distance rises by 1.4% due to quantum motion. Peaks in the radial distribution function of HDA ice are broadened with respect to their classical expectancy. The bulk modulus, B, is found to rise linearly with the pressure, with a slope ∂B/∂P = 7.1. Our results are compared with those derived earlier from classical and path-integral simulations of HDA ice. We discuss similarities and discrepancies with those earlier simulations.

  20. Characterization of High Density Concrete by Ultrasonic Goniometer

    International Nuclear Information System (INIS)

    Suhairy Sani; Mohamad Pauzi Ismail; Noor Azreen Masenwat; Nasharuddin Isa; Mohamad Haniza Mahmud

    2014-01-01

    This paper described the results of ultrasonic goniometer measurements on concrete containing hematite. Local hematite stones were used as aggregates to produce high density concrete for application in X-and gamma shielding. Concrete cube samples (150 mm x 150 mm x 150 mm) containing hematite as coarse aggregates were prepared by changing mix ratio, water to cement ratio (w/ c) and types of fine aggregate. All samples were cured in water for 7 days. After 28 days of casting, the concrete cubes were then cut into small size of about 10 mm x 20 mm x 30 mm so that it can be fitted into goniometer specimen holder. From this measurement, longitudinal, shear and surface Rayleigh waves in the concrete can be determined. The measurement results are explained and discussed. (author)

  1. Microelectromechanical high-density energy storage/rapid release system

    Science.gov (United States)

    Rodgers, M. Steven; Allen, James J.; Meeks, Kent D.; Jensen, Brian D.; Miller, Samuel L.

    1999-08-01

    One highly desirable characteristic of electrostatically driven microelectromechanical systems (MEMS) is that they consume very little power. The corresponding drawback is that the force they produce may be inadequate for many applications. It has previously been demonstrated that gear reduction units or microtransmissions can substantially increase the torque generated by microengines. Operating speed, however, is also reduced by the transmission gear ratio. Some applications require both high speed and high force. If this output is only required for a limited period of time, then energy could be stored in a mechanical system and rapidly released upon demand. We have designed, fabricated, and demonstrated a high-density energy storage/rapid release system that accomplishes this task. Built using a 5-level surface micromachining technology, the assembly closely resembles a medieval crossbow. Energy releases on the order of tens of nanojoules have already been demonstrated, and significantly higher energy systems are under development.

  2. Preparations of high density (Th,U)O2 pellets

    International Nuclear Information System (INIS)

    Akabori, Mitsuo; Ikawa, Katsuichi

    1986-07-01

    Preparations of high density and homogeneous (Th,U)O 2 pellets by a powder metallurgy method were examined. (Th,U)O 2 powders were prepared by calcining coprecipitates of ammonium uranate and thorium hydroxide derived from nitrates and mixed sols, and by calcining mixed oxalates precipitated from nitrates. (Th,U)O 2 pellets were characterized with respect to sinterability, lattice parameter, microstructure, homogeneity and stoichiometry. Sintering atmospheres had a significant effect upon all the properties of the derived pellets. The sinterability of (Th,U)O 2 was most favourable in oxidizing and reducing atmospheres for ThO 2 -rich and UO 2 -rich compositions, respectively, and can be enhanced by presence of water vapour in sintering atmospheres. In addition, highly homogeneous (Th,U)O 2 pellets with 99 % in theoretical density were derived from the sol powders. (author)

  3. Neutron shielding properties of a borated high-density glass

    Directory of Open Access Journals (Sweden)

    Saeed Aly Abdallah

    2017-01-01

    Full Text Available The neutron shielding properties of a borated high density glass system was characterized experimentally. The total removal macroscopic cross-section of fast neutrons, slow neutrons as well as the linear attenuation coefficient of total gamma rays, primary in addition to secondary, were measured experimentally under good geometric condition to characterize the attenuation properties of (75-x B2O3-1Li2O-5MgO-5ZnO-14Na2O-xBaO glassy system. Slabs of different thicknesses from the investigated glass system were exposed to a collimated beam of neutrons emitted from 252Cf and 241Am-Be neutron sources in order to measure the attenuation properties of fast and slow neutrons as well as total gamma rays. Results confirmed that barium borate glass was suitable for practical use in the field of radiation shielding.

  4. Biominetic High Density Lipoproteins for the Delivery of Therapeutic Oligonucleotides

    Science.gov (United States)

    Tripathy, Sushant

    Advances in nanotechnology have brought about novel inorganic and hybrid nanoparticles with unique physico-chemical properties that make them suitable for a broad range of applications---from nano-circuitry to drug delivery. A significant part of those advancements have led to ground-breaking discoveries that have changed the approaches to formulation of therapeutics against diseases, such as cancer. Now-a-days the focus does not lie solely on finding a candidate small-molecule therapeutic with minimal adverse effects, but researchers are looking up to nanoparticles to improve biodistribution and biocompatibility profile of clinically proven therapeutics. The plethora of conjugation chemistries offered by currently extant inorganic nanoparticles have, in recent years, led to great leaps in the field of biomimicry---a modality that promises high biocompatibility. Further, in the pursuit of highly specific therapeutic molecules, researchers have turned to silencing oligonucleotides and some have already brought together the strengths of nanoparticles and silencing oligonucleotides in search of an efficacious therapy for cancer with minimal adverse effects. This dissertation work focuses on such a biomimetic platform---a gold nanoparticle based high density lipoprotein biomimetic (HDL NP), for the delivery of therapeutic oligonucleotides. The first chapter of this body of work introduces the molecular target of the silencing oligonucleotides---VEGFR2, and its role in the progression of solid tumor cancers. The background information also covers important aspects of natural high density lipoproteins (HDL), especially their innate capacity to bind and deliver exogenous and endogenous silencing oligonucleotides to tissues that express their high affinity receptor SRB1. We subsequently describe the synthesis of the biomimetic HDL NP and its oligonucleotide conjugates, and establish their biocompatibility. Further on, experimental data demonstrate the efficacy of silencing

  5. Rethinking reverse cholesterol transport and dysfunctional high-density lipoproteins.

    Science.gov (United States)

    Gillard, Baiba K; Rosales, Corina; Xu, Bingqing; Gotto, Antonio M; Pownall, Henry J

    2018-04-12

    Human plasma high-density lipoprotein cholesterol concentrations are a negative risk factor for atherosclerosis-linked cardiovascular disease. Pharmacological attempts to reduce atherosclerotic cardiovascular disease by increasing plasma high-density lipoprotein cholesterol have been disappointing so that recent research has shifted from HDL quantity to HDL quality, that is, functional vs dysfunctional HDL. HDL has varying degrees of dysfunction reflected in impaired reverse cholesterol transport (RCT). In the context of atheroprotection, RCT occurs by 2 mechanisms: one is the well-known trans-hepatic pathway comprising macrophage free cholesterol (FC) efflux, which produces early forms of FC-rich nascent HDL (nHDL). Lecithin:cholesterol acyltransferase converts HDL-FC to HDL-cholesteryl ester while converting nHDL from a disc to a mature spherical HDL, which transfers its cholesteryl ester to the hepatic HDL receptor, scavenger receptor B1 for uptake, conversion to bile salts, or transfer to the intestine for excretion. Although widely cited, current evidence suggests that this is a minor pathway and that most HDL-FC and nHDL-FC rapidly transfer directly to the liver independent of lecithin:cholesterol acyltransferase activity. A small fraction of plasma HDL-FC enters the trans-intestinal efflux pathway comprising direct FC transfer to the intestine. SR-B1 -/- mice, which have impaired trans-hepatic FC transport, are characterized by high plasma levels of a dysfunctional FC-rich HDL that increases plasma FC bioavailability in a way that produces whole-body hypercholesterolemia and multiple pathologies. The design of future therapeutic strategies to improve RCT will have to be formulated in the context of these dual RCT mechanisms and the role of FC bioavailability. Copyright © 2018 National Lipid Association. Published by Elsevier Inc. All rights reserved.

  6. Properties of matter at ultra-high densities

    International Nuclear Information System (INIS)

    Banerjee, B.; Chitre, S.M.

    1975-01-01

    The recent discovery of pulsars and their subsequent identification with neutron stars has given a great impetus to the study of the behaviour of matter at ultra high densities. The object of these studies is to calculate the equation of state as a function of density. In this paper, the properties of electrically neutral, cold (T=0) matter at unusually high densities has been reviewed. The physics of the equation of state of such matter divides quite naturally in four density ranges. (i) At the very lowest densities the state of minimum energy is a lattice of 56 Fe atoms. This state persists upto 10 7 g/cm 3 . (ii) In the next density region the nuclei at the lattice sites become neutron rich because the high electron Fermi energy makes inverse beta decay possible. (iii) At a density 4.3 x 10 11 the nuclei become so neutron rich that the neutrons start 'dripping' out of the nuclei and form a gas. This density range is characterised by large, neutron-rich nuclei immersed in a neutron gas. (iv) At a density 2.4 x 10 14 g/cm 3 , the nuclei disappear and a fluid of uniform neutron matter with a small percentage of protons and electrons results. The above four density ranges have been discussed in detail as the equation of state is now well established upto the nuclear density 3 x 10 14 g/cm 3 . The problems of extending the equation of state beyond this density are also touched upon. (author)

  7. Pulsed high-density plasmas for advanced dry etching processes

    International Nuclear Information System (INIS)

    Banna, Samer; Agarwal, Ankur; Cunge, Gilles; Darnon, Maxime; Pargon, Erwine; Joubert, Olivier

    2012-01-01

    Plasma etching processes at the 22 nm technology node and below will have to satisfy multiple stringent scaling requirements of microelectronics fabrication. To satisfy these requirements simultaneously, significant improvements in controlling key plasma parameters are essential. Pulsed plasmas exhibit considerable potential to meet the majority of the scaling challenges, while leveraging the broad expertise developed over the years in conventional continuous wave plasma processing. Comprehending the underlying physics and etching mechanisms in pulsed plasma operation is, however, a complex undertaking; hence the full potential of this strategy has not yet been realized. In this review paper, we first address the general potential of pulsed plasmas for plasma etching processes followed by the dynamics of pulsed plasmas in conventional high-density plasma reactors. The authors reviewed more than 30 years of academic research on pulsed plasmas for microelectronics processing, primarily for silicon and conductor etch applications, highlighting the potential benefits to date and challenges in extending the technology for mass-production. Schemes such as source pulsing, bias pulsing, synchronous pulsing, and others in conventional high-density plasma reactors used in the semiconductor industry have demonstrated greater flexibility in controlling critical plasma parameters such as ion and radical densities, ion energies, and electron temperature. Specifically, plasma pulsing allows for independent control of ion flux and neutral radicals flux to the wafer, which is key to eliminating several feature profile distortions at the nanometer scale. However, such flexibility might also introduce some difficulty in developing new etching processes based on pulsed plasmas. Therefore, the main characteristics of continuous wave plasmas and different pulsing schemes are compared to provide guidelines for implementing different schemes in advanced plasma etching processes based on

  8. The glass transition in high-density amorphous ice.

    Science.gov (United States)

    Loerting, Thomas; Fuentes-Landete, Violeta; Handle, Philip H; Seidl, Markus; Amann-Winkel, Katrin; Gainaru, Catalin; Böhmer, Roland

    2015-01-01

    There has been a long controversy regarding the glass transition in low-density amorphous ice (LDA). The central question is whether or not it transforms to an ultraviscous liquid state above 136 K at ambient pressure prior to crystallization. Currently, the most widespread interpretation of the experimental findings is in terms of a transformation to a superstrong liquid above 136 K. In the last decade some work has also been devoted to the study of the glass transition in high-density amorphous ice (HDA) which is in the focus of the present review. At ambient pressure HDA is metastable against both ice I and LDA, whereas at > 0.2 GPa HDA is no longer metastable against LDA, but merely against high-pressure forms of crystalline ice. The first experimental observation interpreted as the glass transition of HDA was made using in situ methods by Mishima, who reported a glass transition temperature T g of 160 K at 0.40 GPa. Soon thereafter Andersson and Inaba reported a much lower glass transition temperature of 122 K at 1.0 GPa. Based on the pressure dependence of HDA's T g measured in Innsbruck, we suggest that they were in fact probing the distinct glass transition of very high-density amorphous ice (VHDA). Very recently the glass transition in HDA was also observed at ambient pressure at 116 K. That is, LDA and HDA show two distinct glass transitions, clearly separated by about 20 K at ambient pressure. In summary, this suggests that three glass transition lines can be defined in the p-T plane for LDA, HDA, and VHDA.

  9. 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

  10. EEG-fMRI correlation patterns in the presurgical evaluation of focal epilepsy: A comparison with electrocorticographic data and surgical outcome measures

    NARCIS (Netherlands)

    van Houdt, P.J.; de Munck, J.C.; Leijten, F.S.S.; Huiskamp, G.J.M.; Colon, A.J.; Boon, P.A.J.M.; Ossenblok, P.P.W.

    2013-01-01

    EEG-correlated functional MRI (EEG-fMRI) visualizes brain regions associated with interictal epileptiform discharges (IEDs). This technique images the epileptiform network, including multifocal, superficial and deeply situated cortical areas. To understand the role of EEG-fMRI in presurgical

  11. Boxers--computed tomography, EEG, and neurological evaluation

    International Nuclear Information System (INIS)

    Ross, R.J.; Cole, M.; Thompson, J.S.; Kim, K.H.

    1983-01-01

    During the last three years, 40 ex-boxers were examined to determine the effects of boxing in regard to their neurological status and the computed tomographic (CT) appearance of the brain. Thirty-eight of these patients had a CT scan of the brain, and 24 had a complete neurological examination including an EEG. The results demonstrate a significant relationship between the number of bouts fought and CT changes indicating cerebral atrophy. Positive neurological findings were not significantly correlated with the number of bouts. Electroencephalographic abnormalities were significantly correlated with the number of bouts fought. Computed tomography and EEG of the brain should be considered as part of a regular neurological examination for active boxers and, if possible, before and after each match, to detect not only the effects of acute life-threatening brain trauma such as subdural hematomas and brain hemorrhages, but the more subtle and debilitating long-term changes of cerebral atrophy

  12. Effects of gamma irradiation on polypropylene, polypropylene + high density polyethylene and polypropylene + high density polyethylene + wood flour

    Energy Technology Data Exchange (ETDEWEB)

    Reyes, J.; Albano, C.; Davidson, E.; Poleo, R. [Universidad Central de Venezuela, Caracas (Venezuela). Escuela de Quimica; Gonzalez, J.; Ichazo, M. [Universidad Simon Bolivar, Dept. de Mecanica, Caracas (Venezuela); Chipara, M. [Research Institute for Electrotechnics, Bucharest (Romania)

    2001-04-01

    The effect of the gamma-irradiation on the mechanical properties of the composites, Polypropylene (PP), PP+high density Polyethylene (HDPE), PP+ HDPE+wood flour, where HDPE is virgin and recycled, was studied. This paper discusses the behavior of the composites after exposure to various doses of gamma irradiation (1-7 MRads) in the presence of oxygen. The dependence of mechanical properties on the integral dose for a constant dose rate of 0.48 MRads/h confirms the influence of the irradiation. Strong effects on the elongation at break and break strength is noticed. The mathematical analysis suggests for the PP+r-HDPE a bimolecular process of the elongation at break. On the order hand, for the PP+HDPE a complex process is represented for a three exponential equation. (orig.)

  13. Effects of gamma irradiation on polypropylene, polypropylene + high density polyethylene and polypropylene + high density polyethylene + wood flour

    International Nuclear Information System (INIS)

    Reyes, J.; Albano, C.; Davidson, E.; Poleo, R.; Chipara, M.

    2001-01-01

    The effect of the gamma-irradiation on the mechanical properties of the composites, Polypropylene (PP), PP+high density Polyethylene (HDPE), PP+ HDPE+wood flour, where HDPE is virgin and recycled, was studied. This paper discusses the behavior of the composites after exposure to various doses of gamma irradiation (1-7 MRads) in the presence of oxygen. The dependence of mechanical properties on the integral dose for a constant dose rate of 0.48 MRads/h confirms the influence of the irradiation. Strong effects on the elongation at break and break strength is noticed. The mathematical analysis suggests for the PP+r-HDPE a bimolecular process of the elongation at break. On the order hand, for the PP+HDPE a complex process is represented for a three exponential equation. (orig.)

  14. Adaptive Automation Triggered by EEG-Based Mental Workload Index: A Passive Brain-Computer Interface Application in Realistic Air Traffic Control Environment.

    Science.gov (United States)

    Aricò, Pietro; Borghini, Gianluca; Di Flumeri, Gianluca; Colosimo, Alfredo; Bonelli, Stefano; Golfetti, Alessia; Pozzi, Simone; Imbert, Jean-Paul; Granger, Géraud; Benhacene, Raïlane; Babiloni, Fabio

    2016-01-01

    Adaptive Automation (AA) is a promising approach to keep the task workload demand within appropriate levels in order to avoid both the under - and over-load conditions, hence enhancing the overall performance and safety of the human-machine system. The main issue on the use of AA is how to trigger the AA solutions without affecting the operative task. In this regard, passive Brain-Computer Interface (pBCI) systems are a good candidate to activate automation, since they are able to gather information about the covert behavior (e.g., mental workload) of a subject by analyzing its neurophysiological signals (i.e., brain activity), and without interfering with the ongoing operational activity. We proposed a pBCI system able to trigger AA solutions integrated in a realistic Air Traffic Management (ATM) research simulator developed and hosted at ENAC (É cole Nationale de l'Aviation Civile of Toulouse, France). Twelve Air Traffic Controller (ATCO) students have been involved in the experiment and they have been asked to perform ATM scenarios with and without the support of the AA solutions. Results demonstrated the effectiveness of the proposed pBCI system, since it enabled the AA mostly during the high-demanding conditions (i.e., overload situations) inducing a reduction of the mental workload under which the ATCOs were operating. On the contrary, as desired, the AA was not activated when workload level was under the threshold, to prevent too low demanding conditions that could bring the operator's workload level toward potentially dangerous conditions of underload.

  15. 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