Brain Functional Connectivity in MS: An EEG-NIRS Study

DTIC Science & Technology

2015-10-01

electrical (EEG) and blood volume and blood oxygen-based (NIRS and fMRI ) signals, and to use the results to help optimize blood oxygen level...dependent (BOLD) fMRI analyses of brain activity. Participants will be patients with MS (n=25) and healthy demographically matched controls (n=25) who will...undergo standardized evaluations and imaging using combined EEG-NIRS- fMRI . EEG-NIRS data will be used to construct maps of neurovascular coupling

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

PubMed

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.

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

PubMed Central

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

2018-01-01

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. PMID:28578130

Guidelines and Best Practices for Electrophysiological Data Collection, Analysis and Reporting in Autism

ERIC Educational Resources Information Center

Webb, Sara Jane; Bernier, Raphael; Henderson, Heather A.; Johnson, Mark H.; Jones, Emily J. H.; Lerner, Matthew D.; McPartland, James C.; Nelson, Charles A.; Rojas, Donald C.; Townsend, Jeanne; Westerfield, Marissa

2015-01-01

The EEG reflects the activation of large populations of neurons that act in synchrony and propagate to the scalp surface. This activity reflects both the brain's background electrical activity and when the brain is being challenged by a task. Despite strong theoretical and methodological arguments for the use of EEG in understanding the…

Design of a Wireless EEG System for Point-of-Care Applications.

PubMed

Jia, Wenyan; Bai, Yicheng; Sun, Mingui; Sclabassi, Robert J

2013-04-01

This study aims to develop a wireless EEG system to provide critical point-of-care information about brain electrical activity. A novel dry electrode, which can be installed rapidly, is used to acquire EEG from the scalp. A wireless data link between the electrode and a data port (i.e., a smartphone) is established based on the Bluetooth technology. A prototype of this system has been implemented and its performance in acquiring EEG has been evaluated.

Transcranial direct current stimulation and power spectral parameters: a tDCS/EEG co-registration study

PubMed Central

Mangia, Anna L.; Pirini, Marco; Cappello, Angelo

2014-01-01

Transcranial direct current stimulation (tDCS) delivers low electric currents to the brain through the scalp. Constant electric currents induce shifts in neuronal membrane excitability, resulting in secondary changes in cortical activity. Concomitant electroencephalography (EEG) monitoring during tDCS can provide valuable information on the tDCS mechanisms of action. This study examined the effects of anodal tDCS on spontaneous cortical activity in a resting brain to disclose possible modulation of spontaneous oscillatory brain activity. EEG activity was measured in ten healthy subjects during and after a session of anodal stimulation of the postero-parietal cortex to detect the tDCS-induced alterations. Changes in the theta, alpha, beta, and gamma power bands were investigated. Three main findings emerged: (1) an increase in theta band activity during the first minutes of stimulation; (2) an increase in alpha and beta power during and after stimulation; (3) a widespread activation in several brain regions. PMID:25147519

Transcranial Electrical Currents to Probe EEG Brain Rhythms and Memory Consolidation during Sleep in Humans

PubMed Central

Marshall, Lisa; Kirov, Roumen; Brade, Julian; Mölle, Matthias; Born, Jan

2011-01-01

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. PMID:21340034

Acute behavioral and EEG effects of NW-1015 on electrically-induced afterdischarge in conscious monkeys.

PubMed

Fariello, R G; Maj, R; Marrari, P; Beard, D; Algate, C; Salvati, P

2000-03-01

NW-1015 is a novel Na+ and Ca2+ channel blocker with broad spectrum anticonvulsant activity and an excellent safety margin. As the compound also shows sigma-1 receptor ligand properties it was deemed important to determine whether it possesses anticonvulsant properties in primates without causing behavioral and EEG abnormalities. Thus, the effects of NW-1015 on limbic electrically-induced afterdischarge (AD) were evaluated in four cynomolgus monkeys, and its activity compared to a single effective dose of phenytoin (PHT). The four male cynomolgus monkeys were chronically implanted for EEG recordings, from cortex and limbic structures. AD was induced in limbic areas by electrical stimulation. The effects of NW-1015 on the duration and the behavioral component of the AD were randomly tested at doses from 25 to 75 mg/kg and compared with the effects of PHT 50 mg/kg. Similarly to PHT, 50 mg/kg of NW-1015 significantly shortened the EEG AD and almost abolished AD elicited behavioral seizure. Only the behavioral effects of AD were reduced after administration of 25 mg/kg p.o. NW-1015 did not cause EEG or interictal behavioral alterations at doses up to 75 mg/kg p.o. These data further confirm the broad-spectrum anticonvulsant activity and a good safety profile of NW-1015 even in a primate model of complex partial seizures and suggest that its affinity for sigma-1 receptors is behaviorally irrelevant.

Intelligence Community Forum

DTIC Science & Technology

2008-11-05

Description Operationally Feasible? EEG ms ms cm Measures electrical activity in the brain. Practical tool for applications - real time monitoring or...Cognitive Systems Device Development & Processing Methods Brain activity can be monitored in real-time in operational environments with EEG Brain...biological and cognitive findings about the user to customize the learning environment Neurofeedback • Present the user with real-time feedback

[Temporary disappearance of EEG activity during reversible respiratory failure in rabbits and cats].

PubMed

Jurco, M; Tomori, Z; Tkácová, R; Calfa, J

1989-02-01

The dynamics of changes of EEG activity was studied on the model of reversible respiratory failure in rabbits and cats in pentobarbital anesthesia. During N2 inhalation, apnea of 60 second duration, and subsequent resuscitation the electrocorticogram in bifrontal and bioccipital connection was recorded. Evaluation of 19 episodes of apnea in 7 rabbits and of 25 episodes in 8 cats yielded the following results: 1. During hyperventilation induced by N2 inhalation a certain activation of the EEG was observed (spindles more pronounced, increased occurrence rate of discharges of the reticular activation system). 2. At the onset of apnea the EEG was still distinct, suggesting that primary apnea is presumably not caused by anoxia and the accompanying electric silence of the structures that control respiration. 3. Disappearance of EEG occurred within 50 seconds from the onset of apnea in rabbits and within 30 seconds in cats. 4. After repeated episodes of apnea lasting for 60 sec., artificial ventilation mostly resulted in normalization of EEG.

Developing an Adaptability Training Strategy and Policy for the DoD

DTIC Science & Technology

2008-10-01

might include monitoring of trainees using electroencephalogram ( EEG ) technology to gain neurofeedback during scenario performance. In order to...group & adequate sample; pre and post iii. Possibly including EEG monitoring (and even neurofeedback ) 4. Should seek to determine general...Dr. John Cowan has developed a system called the Peak Achievement Trainer (PAT) EEG , which traces electrical activity in the brain and provides

[Electrical activity and circulatory effects of nitrite in the rat cerebrum].

PubMed

Shumilova, T E; Smirnov, A G; Shereshkov, V I; Fedorova, M A; Nozdrachev, A D

2015-01-01

An association between the cerebrum electrical activity (CEA) in rats, blood supply of its cortex microregions (linear blood flow), and general cerebrum blood flow under acute nitrite hypoxia was studied. The phase character of the change in hemodynamic indices and the total capacity of electroencephalography (EEG) spectrum for 75 min after sodium nitrite introduction (30 mg/kg of body weight) was detected. The first phase (30 min) was associated with cerebrum adaptation to hypotension caused by nitrite and was completed by EEG normalization. The second phase was characterized by pathological EEG changes (in spite of restoration of hemodynamics in the cerebrum) caused by the growth of oxygen debt in the nervous tissue as a result of a decrease in the blood oxygen capacity by 60-75 min of the effect of nitrite.

Electric Field Encephalography as a tool for functional brain research: a modeling study.

PubMed

Petrov, Yury; Sridhar, Srinivas

2013-01-01

We introduce the notion of Electric Field Encephalography (EFEG) based on measuring electric fields of the brain and demonstrate, using computer modeling, that given the appropriate electric field sensors this technique may have significant advantages over the current EEG technique. Unlike EEG, EFEG can be used to measure brain activity in a contactless and reference-free manner at significant distances from the head surface. Principal component analysis using simulated cortical sources demonstrated that electric field sensors positioned 3 cm away from the scalp and characterized by the same signal-to-noise ratio as EEG sensors provided the same number of uncorrelated signals as scalp EEG. When positioned on the scalp, EFEG sensors provided 2-3 times more uncorrelated signals. This significant increase in the number of uncorrelated signals can be used for more accurate assessment of brain states for non-invasive brain-computer interfaces and neurofeedback applications. It also may lead to major improvements in source localization precision. Source localization simulations for the spherical and Boundary Element Method (BEM) head models demonstrated that the localization errors are reduced two-fold when using electric fields instead of electric potentials. We have identified several techniques that could be adapted for the measurement of the electric field vector required for EFEG and anticipate that this study will stimulate new experimental approaches to utilize this new tool for functional brain research.

Electrical activity of the cingulate cortex. II. Cholinergic modulation.

PubMed

Borst, J G; Leung, L W; MacFabe, D F

1987-03-24

The role of the cholinergic innervation in the modulation of cingulate electrical activity was studied by means of pharmacological manipulations and brain lesions. In the normal rat, an irregular slow activity (ISA) accompanied with EEG-spikes was recorded in the cingulate cortex during immobility as compared to walking. Atropine sulfate, but not atropine methyl nitrate, increased ISA and the frequency of cingulate EEG-spikes. Pilocarpine suppressed ISA and EEG-spikes during immobility, and induced a slow (4-7 Hz) theta rhythm. Unilateral or bilateral lesions of the substantia innominata and ventral globus pallidus area using kainic acid did not significantly change the cingulate EEG or its relation to behavior. Large electrolytic lesions of the medial septal nuclei and vertical limbs of the diagonal band generally decreased or abolished all theta activity in the cingulate cortex and the hippocampus. However, in 5 rats the cingulate theta rhythm increased while the hippocampal theta disappeared after a medial septal lesion. The large, postlesion cingulate theta, accompanied by sharp EEG-spikes during its negative phase, is an unequivocal demonstration of the existence of a theta rhythm in the cingulate cortex, independent of the hippocampal rhythm. Cholinergic afferents from the medial septum and diagonal band nuclei are inferred to be responsible for the behavioral suppression of cingulate EEG-spikes and ISA, and partially for the generation of a local cingulate theta rhythm. However, an atropine-resistant pathway and a theta-suppressing pathway, possibly coming from the medial septum or the hippocampus, may also be important in cingulate theta generation.

Corrected Four-Sphere Head Model for EEG Signals.

PubMed

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

2017-01-01

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

Corrected Four-Sphere Head Model for EEG Signals

PubMed Central

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. PMID:29093671

Epilepsy

MedlinePlus

... made great strides in detecting patterns of abnormal electrical activity in the brain that cause epileptic seizures. A technology to measure brain activity, called electroencephalography (EEG), became ...

Cognitive hearing aids? Insights and possibilities

NASA Astrophysics Data System (ADS)

Petersen, Eline Borch; Lunner, Thomas

2015-12-01

The working memory plays an important role in successfully overcoming adverse listening conditions and should consequently be considered when designing and testing hearing aids. A number of studies have established the relationship between hearing in noise and working memory involvement, but with the Sentence-final Word Identification and Recall (SWIRL) test, it is possible to show that working memory is also involved in listening under favorable conditions and that noise reduction has a positive influence in situation with very little noise. Although the capacity of the working memory is a finite individual size, its involvement can differ with fatigue and other factors and individualization of hearing aids should take this into account to obtain the best performance. A way of individually adapting hearing aids is based on changes in the electrical activity of the brain (EEG). Here we present the possibilities that arise from using EEG and show that ear-mounted electrodes is able to record useful EEG that can be explored for individualization of hearing aids. Such an adaptation could be done based on changes in the electrical activity of the brain (EEG). Here we present the possibilities that arise from using EEG and show that ear-mounted electrodes is able to record useful EEG that can be explored for individualization of hearing aids.

Do temperamentally shy children process emotion differently than nonshy children? Behavioral, psychophysiological, and gender differences in reticent preschoolers.

PubMed

Theall-Honey, Laura A; Schmidt, Louis A

2006-04-01

We examined regional brain electrical activity (EEG), heart rate, and subjective responses at rest and during the presentation of videoclips designed to elicit a range of emotions (e.g., sadness, anger, happiness, fear) among a sample of healthy 4-year-old children selected for temperamental shyness. We found that shy children exhibited significantly greater relative right central EEG activation at rest and during the presentation of the fear-eliciting videoclip than nonshy children. Shy females displayed greater relative right mid-frontal EEG activation during the sad, happy, and fear videoclips than shy males who displayed greater relative left mid-frontal EEG activation. These results (1) suggest that recent frontal EEG activation/emotion models might be gender-specific and (2) appear to provide the first empirical evidence for recent theoretical notions linking the origins and maintenance of temperamental shyness in children to difficulty in regulating fear responses. Copyright (c) 2006 Wiley Periodicals, Inc.

Patterns of Brain-Electrical Activity during Declarative Memory Performance in 10-Month-Old Infants

ERIC Educational Resources Information Center

Morasch, Katherine C.; Bell, Martha Ann

2009-01-01

This study of infant declarative memory concurrently examined brain-electrical activity and deferred imitation performance in 10-month-old infants. Continuous electroencephalogram (EEG) measures were collected throughout the activity-matched baseline, encoding (modeling) and retrieval (delayed test) phases of a within-subjects deferred imitation…

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

PubMed

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

2011-06-27

Dense array electroencephalography ((d)EEG), which provides a non-invasive window for measuring brain activity and a temporal resolution unsurpassed by any other current brain imaging technology¹, ² is being used increasingly in the study of social cognitive functioning in infants and adults. While (d)EEG is enabling researchers to examine brain activity patterns with unprecedented levels of sensitivity, conventional EEG recording systems continue to face certain limitations, including 1) poor spatial resolution and source localization³,⁴2) the physical discomfort for test subjects of enduring the individual application of numerous electrodes to the surface of the scalp, and 3) the complexity for researchers of learning to use multiple software packages to collect and process data. Here we present an overview of an established methodology that represents a significant improvement on conventional methodologies for studying EEG in infants and adults. Although several analytical software techniques can be used to establish indirect indices of source localization to improve the spatial resolution of (d)EEG, the HydroCel Geodesic Sensor Net (HCGSN) by Electrical Geodesics, Inc. (EGI), a dense sensory array that maintains equal distances among adjacent recording electrodes on all surfaces of the scalp, further enhances spatial resolution⁴,⁵(,)⁶ compared to standard (d)EEG systems. The sponge-based HCGSN can be applied rapidly and without scalp abrasion, making it ideal for use with adults⁷,⁸ children⁹,¹⁰, ¹¹,¹² and infants¹², in both research and clinical ⁴,⁵,⁶,¹³,¹⁴,¹⁵settings. This feature allows for considerable cost and time savings by decreasing the average net application time compared to other (d)EEG systems. Moreover, the HCGSN includes unified, seamless software applications for all phases of data, greatly simplifying the collection, processing, and analysis of (d)EEG data. The HCGSN features a low-profile electrode pedestal, which, when filled with electrolyte solution, creates a sealed microenvironment and an electrode-scalp interface. In all Geodesic (d;)EEG systems, EEG sensors detect changes in voltage originating from the participant's scalp, along with a small amount of electrical noise originating from the room environment. Electrical signals from all sensors of the Geodesic sensor net are received simultaneously by the amplifier, where they are automatically processed, packaged, and sent to the data-acquisition computer (DAC). Once received by the DAC, scalp electrical activity can be isolated from artifacts for analysis using the filtering and artifact detection tools included in the EGI software. Typically, the HCGSN can be used continuously for only up to two hours because the electrolyte solution dries out over time, gradually decreasing the quality of the scalp-electrode interface. In the Parent-Infant Research Lab at the University of Toronto, we are using (d)EEG to study social cognitive processes including memory, emotion, goals, intentionality, anticipation, and executive functioning in both adult and infant participants.

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

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

Individual differences in object permanence performance at 8 months: locomotor experience and brain electrical activity.

PubMed

Bell, M A; Fox, N A

1997-12-01

This work was designed to investigate individual differences in hands-and-knees crawling and frontal brain electrical activity with respect to object permanence performance in 76 eight-month-old infants. Four groups of infants (one prelocomotor and 3 with varying lengths of hands-and-knees crawling experience) were tested on an object permanence scale in a research design similar to that used by Kermoian and Campos (1988). In addition, baseline EEG was recorded and used as an indicator of brain development, as in the Bell and Fox (1992) longitudinal study. Individual differences in frontal and occipital EEG power and in locomotor experience were associated with performance on the object permanence task. Infants successful at A-not-B exhibited greater frontal EEG power and greater occipital EEG power than unsuccessful infants. In contrast to Kermoian and Campos (1988), who noted that long-term crawling experience was associated with higher performance on an object permanence scale, infants in this study with any amount of hands and knees crawling experience performed at a higher level on the object permanence scale than prelocomotor infants. There was no interaction among brain electrical activity, locomotor experience, and object permanence performance. These data highlight the value of electrophysiological research and the need for a brain-behavior model of object permanence performance that incorporates both electrophysiological and behavioral factors.

Topographic Brain Mapping: A Window on Brain Function?

ERIC Educational Resources Information Center

Karniski, Walt M.

1989-01-01

The article reviews the method of topographic mapping of the brain's electrical activity. Multiple electroencephalogram (EEG) electrodes and computerized analysis of the EEG signal are used to generate maps of frequency and voltage (evoked potential). This relatively new technique holds promise in the evaluation of children with behavioral and…

Differences of brain electrical activity between moderate and severe obstructive sleep apneic patients: a LORETA study.

PubMed

Toth, Marton; Kondakor, Istvan; Faludi, Bela

2016-10-01

The effects of initiation of continuous positive airway pressure (CPAP) therapy on electroencephalographic (EEG) background activity were investigated in patients exhibiting both moderate (n = 13) and severe (n = 12) obstructive sleep apnea syndromes in the testing of the potential differences of alterations of brain electrical activity caused by chronic hypoxia between these two groups. A normal control group (n = 14) was also examined. Two EEG examinations were achieved in each group: before and after first-time CPAP therapy. Low-resolution electromagnetic tomography (LORETA) was implemented towards localizing the generators of EEG activity in separate frequency bands. Prior to CPAP treatment, as a common direction of change, analysis with LORETA demonstrated increased activity in comparison with the patient and control groups. In the moderate group, significant changes were detected in the alpha2 band in the posterior cingulate cortex as well as in the beta1 band in the right posterior parietal cortex and the left supramarginal gyrus. In the severe group, significant changes were found in theta and alpha1 bands in the posterior cingulate cortex. Following CPAP treatment, these significant differences vanished in the severe group. In the moderate group, significantly decreased activity was seen in the beta3 band in the right fusiform gyrus. These findings potentially suggest a normalizing effect of CPAP therapy on EEG background activity in both groups of obstructive sleep apnea syndrome patients. Compensatory alterations of brain electrical activity in regions associated with influencing successful memory retrieval, emotional perception, default mode network, anorexia and fear network caused by chronic intermittent hypoxia could possibly be reversed with the use of CPAP therapy. © 2016 European Sleep Research Society.

The differential effects of halothane and isoflurane on electroencephalographic responses to electrical microstimulation of the reticular formation.

PubMed

Orth, Mashawn; Bravo, Emigdio; Barter, Linda; Carstens, Earl; Antognini, Joseph F

2006-06-01

Isoflurane and halothane cause electroencephalographic (EEG) depression and neuronal depression in the reticular formation, a site critical to consciousness. We hypothesized that isoflurane, more than halothane, would depress EEG activation elicited by electrical microstimulation of the reticular formation. Rats were anesthetized with either halothane or isoflurane and stimulating electrodes were positioned in the reticular formation. In a crossover design, anesthetic concentration was adjusted to 0.8 and 1.2 minimum alveolar concentration (MAC) of halothane or isoflurane and electrical microstimulation was performed and the EEG responses were recorded. Microstimulation increased the spectral edge and median edge frequencies 2-2.5 Hz at 0.8 MAC for halothane and isoflurane and 1.2 MAC halothane. At 1.2 MAC isoflurane, burst suppression occurred and microstimulation decreased the period of isoelectricity (24% +/- 19% to 8% +/- 7%; P < 0.05), whereas the spectral edge and median edge frequencies were unchanged. At anesthetic concentrations required to produce immobility, the cortex remains responsive to electrical microstimulation of the reticular formation, although the EEG response is depressed in the transition from 0.8 to 1.2 MAC. These data indicate that cortical neurons remain responsive to synaptic input during isoflurane and halothane anesthesia.

Electroencephalographic imaging of higher brain function

NASA Technical Reports Server (NTRS)

Gevins, A.; Smith, M. E.; McEvoy, L. K.; Leong, H.; Le, J.

1999-01-01

High temporal resolution is necessary to resolve the rapidly changing patterns of brain activity that underlie mental function. Electroencephalography (EEG) provides temporal resolution in the millisecond range. However, traditional EEG technology and practice provide insufficient spatial detail to identify relationships between brain electrical events and structures and functions visualized by magnetic resonance imaging or positron emission tomography. Recent advances help to overcome this problem by recording EEGs from more electrodes, by registering EEG data with anatomical images, and by correcting the distortion caused by volume conduction of EEG signals through the skull and scalp. In addition, statistical measurements of sub-second interdependences between EEG time-series recorded from different locations can help to generate hypotheses about the instantaneous functional networks that form between different cortical regions during perception, thought and action. Example applications are presented from studies of language, attention and working memory. Along with its unique ability to monitor brain function as people perform everyday activities in the real world, these advances make modern EEG an invaluable complement to other functional neuroimaging modalities.

[FREQUENCY-TEMPORAL STRUCTURE OF HUMAN ELECTROENCEPHALOGRAM IN THE CONDITION OF ARTIFICIAL HYPOGRAVITY: DRY IMMERSION MODEL].

PubMed

Kuznetsova, G D; Gabova, A V; Lazarev, I E; Obukhov, Iu V; Obukhov, K Iu; Morozov, A A; Kulikov, M A; Shchatskova, A B; Vasil'eva, O N; Tomilovskaia, E S

2015-01-01

Frequency-temporal electroencephalogram (EEG) reactions to hypogravity were studied in 7 male subjects at the age of 20 to 27 years. The experiment was conducted using dry immersion (DI) as the best known method of simulating the space microgravity effects on the Earth. This hypogravity model reproduces hypokinesia, i.e. the weight-bearing and mechanic load removal, which is typical of microgravity. EEG was recorded by Neuroscan-2 (Compumedics) before the experiment (baseline data) and at the end of day 2 in DI. Comparative analysis of the EEG frequency-temporal structure was performed with the use of 2 techniques: Fourier transform and modified wavelet analysis. The Fourier transform elicited that after 2 days in DI the main shifts occurring to the EEG spectral composition are a decline in the alpha power and a slight though reliable growth of theta power. Similar frequency shifts were detected in the same records analyzed using the wavelet transform. According to wavelet analysis, during DI shifts in EEG frequency spectrum are accompanied by frequency desorganization of the EEG dominant rhythm and gross impairment of total stability of the electrical activity with time. Wavelet transform provides an opportunity to quantify changes in the frequency-temporal structure of the electrical activity of the brain. Quantitative evidence of frequency desorganization and temporal instability of EEG wavelet spectrograms may be the key to the understanding of mechanisms that drive functional disorders in the brain cortex in the conditions of hypogravity.

Guidelines and best practices for electrophysiological data collection, analysis and reporting in autism

PubMed Central

Webb, S. J.; Bernier, R.; Henderson, H. A.; Johnson, M. H.; Jones, E. J. H.; Lerner, M. D.; McPartland, J. C.; Nelson, C. A.; Rojas, D. C.; Townsend, J.; Westerfield, M.

2014-01-01

The EEG reflects the activation of large populations of neurons that act in synchrony and propagate to the scalp surface. This activity reflects both the brain’s background electrical activity and when the brain is being challenged by a task. Despite strong theoretical and methodological arguments for the use of EEG in understanding the neural correlates of autism, the practice of collecting, processing and evaluating EEG data is complex. Scientists should take into consideration both the nature of development in autism given the life-long, pervasive course of the disorder and the disability of altered or atypical social, communicative, and motor behaviors, all of which require accommodations to traditional EEG environments and paradigms. This paper presents guidelines for the recording, analyzing, and interpreting of EEG data with participants with autism. The goal is to articulate a set of scientific standards as well as methodological considerations that will increase the general field’s understanding of EEG methods, provide support for collaborative projects, and contribute to the evaluation of results and conclusions. PMID:23975145

On analysis of electroencephalogram by multiresolution-based energetic approach

NASA Astrophysics Data System (ADS)

Sevindir, Hulya Kodal; Yazici, Cuneyt; Siddiqi, A. H.; Aslan, Zafer

2013-10-01

Epilepsy is a common brain disorder where the normal neuronal activity gets affected. Electroencephalography (EEG) is the recording of electrical activity along the scalp produced by the firing of neurons within the brain. The main application of EEG is in the case of epilepsy. On a standard EEG some abnormalities indicate epileptic activity. EEG signals like many biomedical signals are highly non-stationary by their nature. For the investigation of biomedical signals, in particular EEG signals, wavelet analysis have found prominent position in the study for their ability to analyze such signals. Wavelet transform is capable of separating the signal energy among different frequency scales and a good compromise between temporal and frequency resolution is obtained. The present study is an attempt for better understanding of the mechanism causing the epileptic disorder and accurate prediction of occurrence of seizures. In the present paper following Magosso's work [12], we identify typical patterns of energy redistribution before and during the seizure using multiresolution wavelet analysis on Kocaeli University's Medical School's data.

Quantitative modeling of multiscale neural activity

NASA Astrophysics Data System (ADS)

Robinson, Peter A.; Rennie, Christopher J.

2007-01-01

The electrical activity of the brain has been observed for over a century and is widely used to probe brain function and disorders, chiefly through the electroencephalogram (EEG) recorded by electrodes on the scalp. However, the connections between physiology and EEGs have been chiefly qualitative until recently, and most uses of the EEG have been based on phenomenological correlations. A quantitative mean-field model of brain electrical activity is described that spans the range of physiological and anatomical scales from microscopic synapses to the whole brain. Its parameters measure quantities such as synaptic strengths, signal delays, cellular time constants, and neural ranges, and are all constrained by independent physiological measurements. Application of standard techniques from wave physics allows successful predictions to be made of a wide range of EEG phenomena, including time series and spectra, evoked responses to stimuli, dependence on arousal state, seizure dynamics, and relationships to functional magnetic resonance imaging (fMRI). Fitting to experimental data also enables physiological parameters to be infered, giving a new noninvasive window into brain function, especially when referenced to a standardized database of subjects. Modifications of the core model to treat mm-scale patchy interconnections in the visual cortex are also described, and it is shown that resulting waves obey the Schroedinger equation. This opens the possibility of classical cortical analogs of quantum phenomena.

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

PubMed

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

2016-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

Event-Related Beta EEG Changes During Active, Passive Movement and Functional Electrical Stimulation of the Lower Limb.

PubMed

Qiu, Shuang; Yi, Weibo; Xu, Jiapeng; Qi, Hongzhi; Du, Jingang; Wang, Chunfang; He, Feng; Ming, Dong

2016-02-01

A number of electroencephalographic (EEG) studies have reported on event-related desynchronization/synchronization (ERD/ERS) during active movements, passive movements, and the movements induced by functional electrical stimulation (FES). However, the quantitative differences in ERD values and affected frequency bands associated with the lower limb have not been discussed. The goal of this paper was to quantitatively compare the ERD patterns during active movement, passive movement and FES-induced movement of the lower limb. 64-channel EEG signals were recorded to investigate the brain oscillatory patterns during active movement, passive movement and FES-induced movement of the lower limb in twelve healthy subjects. And passive movement and FES-induced movement were also performed in a hemiplegic stroke patient. For healthy subjects, FES-induced movement presented significantly higher characteristic frequency of central beta ERD while there was no significant difference in ERD values compared with active or passive movement. Meanwhile, beta ERD values of FES-induced movement were significantly correlated with those of active movement, and spatial distribution of beta ERD pattern for FES-induced movement was more correlated with that for active movement. In addition, the stroke patient presented central ERD patterns during FES-induced movement, while no ERD with similar frequencies could be found during passive movement. This work implies that the EEG oscillatory pattern under FES-induced movement tends more towards active movement instead of passive movement. The quantification of ERD patterns could be expected as a potential technique to evaluate the brain response during FES-induced movement.

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

PubMed Central

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 that modify the recorded traces and seek to minimize the impact of reference electrode activity upon functions of the original EEG recordings. New method We provide a novel, statistically robust procedure that adapts a robust maximum-likelihood type estimator to the problem of reference estimation, reduces the influence of neural activity from the re-referencing operation, and maintains good performance in a wide variety of empirical scenarios. Results The performance of the proposed and existing re-referencing procedures are validated in simulation and with examples of EEG recordings. To facilitate this comparison, channel-to-channel correlations are investigated theoretically and in simulation. Comparison with existing methods The proposed procedure avoids using data contaminated by neural signal and remains unbiased in recording scenarios where physical references, the common average reference (CAR) and the reference estimation standardization technique (REST) are not optimal. Conclusion The proposed procedure is simple, fast, and avoids the potential for substantial bias when analyzing low-density EEG data. PMID:24975291

Correlation between disease severity and brain electric LORETA tomography in Alzheimer's disease.

PubMed

Gianotti, Lorena R R; Künig, Gabriella; Lehmann, Dietrich; Faber, Pascal L; Pascual-Marqui, Roberto D; Kochi, Kieko; Schreiter-Gasser, Ursula

2007-01-01

To compare EEG power spectra and LORETA-computed intracortical activity between Alzheimer's disease (AD) patients and healthy controls, and to correlate the results with cognitive performance in the AD group. Nineteen channel resting EEG was recorded in 21 mild to moderate AD patients and in 23 controls. Power spectra and intracortical LORETA tomography were computed in seven frequency bands and compared between groups. In the AD patients, the EEG results were correlated with cognitive performance (Mini Mental State Examination, MMSE). AD patients showed increased power in EEG delta and theta frequency bands, and decreased power in alpha2, beta1, beta2 and beta3. LORETA specified that increases and decreases of power affected different cortical areas while largely sparing prefrontal cortex. Delta power correlated negatively and alpha1 power positively with the AD patients' MMSE scores; LORETA tomography localized these correlations in left temporo-parietal cortex. The non-invasive EEG method of LORETA localized pathological cortical activity in our mild to moderate AD patients in agreement with the literature, and yielded striking correlations between EEG delta and alpha1 activity and MMSE scores in left temporo-parietal cortex. The present data support the hypothesis of an asymmetrical progression of the Alzheimer's disease.

Hybrid ICA-Regression: Automatic Identification and Removal of Ocular Artifacts from Electroencephalographic Signals.

PubMed

Mannan, Malik M Naeem; Jeong, Myung Y; Kamran, Muhammad A

2016-01-01

Electroencephalography (EEG) is a portable brain-imaging technique with the advantage of high-temporal resolution that can be used to record electrical activity of the brain. However, it is difficult to analyze EEG signals due to the contamination of ocular artifacts, and which potentially results in misleading conclusions. Also, it is a proven fact that the contamination of ocular artifacts cause to reduce the classification accuracy of a brain-computer interface (BCI). It is therefore very important to remove/reduce these artifacts before the analysis of EEG signals for applications like BCI. In this paper, a hybrid framework that combines independent component analysis (ICA), regression and high-order statistics has been proposed to identify and eliminate artifactual activities from EEG data. We used simulated, experimental and standard EEG signals to evaluate and analyze the effectiveness of the proposed method. Results demonstrate that the proposed method can effectively remove ocular artifacts as well as it can preserve the neuronal signals present in EEG data. A comparison with four methods from literature namely ICA, regression analysis, wavelet-ICA (wICA), and regression-ICA (REGICA) confirms the significantly enhanced performance and effectiveness of the proposed method for removal of ocular activities from EEG, in terms of lower mean square error and mean absolute error values and higher mutual information between reconstructed and original EEG.

Hybrid ICA—Regression: Automatic Identification and Removal of Ocular Artifacts from Electroencephalographic Signals

PubMed Central

Mannan, Malik M. Naeem; Jeong, Myung Y.; Kamran, Muhammad A.

2016-01-01

Electroencephalography (EEG) is a portable brain-imaging technique with the advantage of high-temporal resolution that can be used to record electrical activity of the brain. However, it is difficult to analyze EEG signals due to the contamination of ocular artifacts, and which potentially results in misleading conclusions. Also, it is a proven fact that the contamination of ocular artifacts cause to reduce the classification accuracy of a brain-computer interface (BCI). It is therefore very important to remove/reduce these artifacts before the analysis of EEG signals for applications like BCI. In this paper, a hybrid framework that combines independent component analysis (ICA), regression and high-order statistics has been proposed to identify and eliminate artifactual activities from EEG data. We used simulated, experimental and standard EEG signals to evaluate and analyze the effectiveness of the proposed method. Results demonstrate that the proposed method can effectively remove ocular artifacts as well as it can preserve the neuronal signals present in EEG data. A comparison with four methods from literature namely ICA, regression analysis, wavelet-ICA (wICA), and regression-ICA (REGICA) confirms the significantly enhanced performance and effectiveness of the proposed method for removal of ocular activities from EEG, in terms of lower mean square error and mean absolute error values and higher mutual information between reconstructed and original EEG. PMID:27199714

Infraslow Electroencephalographic and Dynamic Resting State Network Activity.

PubMed

Grooms, Joshua K; Thompson, Garth J; Pan, Wen-Ju; Billings, Jacob; Schumacher, Eric H; Epstein, Charles M; Keilholz, Shella D

2017-06-01

A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (<1 Hz) has been little studied. Previously, work in rodents showed that infraslow local field potentials play a role in functional connectivity, particularly in the dynamic organization of large-scale networks. To examine the relationship between infraslow activity and network dynamics in humans, direct current (DC) EEG and resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies.

Infraslow Electroencephalographic and Dynamic Resting State Network Activity

PubMed Central

Grooms, Joshua K.; Thompson, Garth J.; Pan, Wen-Ju; Billings, Jacob; Schumacher, Eric H.; Epstein, Charles M.

2017-01-01

Abstract A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (<1 Hz) has been little studied. Previously, work in rodents showed that infraslow local field potentials play a role in functional connectivity, particularly in the dynamic organization of large-scale networks. To examine the relationship between infraslow activity and network dynamics in humans, direct current (DC) EEG and resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies. PMID:28462586

Electroencephalographic inverse localization of brain activity in acute traumatic brain injury as a guide to surgery, monitoring and treatment

PubMed Central

Irimia, Andrei; Goh, S.-Y. Matthew; Torgerson, Carinna M.; Stein, Nathan R.; Chambers, Micah C.; Vespa, Paul M.; Van Horn, John D.

2013-01-01

Objective To inverse-localize epileptiform cortical electrical activity recorded from severe traumatic brain injury (TBI) patients using electroencephalography (EEG). Methods Three acute TBI cases were imaged using computed tomography (CT) and multimodal magnetic resonance imaging (MRI). Semi-automatic segmentation was performed to partition the complete TBI head into 25 distinct tissue types, including 6 tissue types accounting for pathology. Segmentations were employed to generate a finite element method model of the head, and EEG activity generators were modeled as dipolar currents distributed over the cortical surface. Results We demonstrate anatomically faithful localization of EEG generators responsible for epileptiform discharges in severe TBI. By accounting for injury-related tissue conductivity changes, our work offers the most realistic implementation currently available for the inverse estimation of cortical activity in TBI. Conclusion Whereas standard localization techniques are available for electrical activity mapping in uninjured brains, they are rarely applied to acute TBI. Modern models of TBI-induced pathology can inform the localization of epileptogenic foci, improve surgical efficacy, contribute to the improvement of critical care monitoring and provide guidance for patient-tailored treatment. With approaches such as this, neurosurgeons and neurologists can study brain activity in acute TBI and obtain insights regarding injury effects upon brain metabolism and clinical outcome. PMID:24011495

Electroencephalographic inverse localization of brain activity in acute traumatic brain injury as a guide to surgery, monitoring and treatment.

PubMed

Irimia, Andrei; Goh, S-Y Matthew; Torgerson, Carinna M; Stein, Nathan R; Chambers, Micah C; Vespa, Paul M; Van Horn, John D

2013-10-01

To inverse-localize epileptiform cortical electrical activity recorded from severe traumatic brain injury (TBI) patients using electroencephalography (EEG). Three acute TBI cases were imaged using computed tomography (CT) and multimodal magnetic resonance imaging (MRI). Semi-automatic segmentation was performed to partition the complete TBI head into 25 distinct tissue types, including 6 tissue types accounting for pathology. Segmentations were employed to generate a finite element method model of the head, and EEG activity generators were modeled as dipolar currents distributed over the cortical surface. We demonstrate anatomically faithful localization of EEG generators responsible for epileptiform discharges in severe TBI. By accounting for injury-related tissue conductivity changes, our work offers the most realistic implementation currently available for the inverse estimation of cortical activity in TBI. Whereas standard localization techniques are available for electrical activity mapping in uninjured brains, they are rarely applied to acute TBI. Modern models of TBI-induced pathology can inform the localization of epileptogenic foci, improve surgical efficacy, contribute to the improvement of critical care monitoring and provide guidance for patient-tailored treatment. With approaches such as this, neurosurgeons and neurologists can study brain activity in acute TBI and obtain insights regarding injury effects upon brain metabolism and clinical outcome. Published by Elsevier B.V.

Brain electrical activity and subjective experience during altered states of consciousness: ganzfeld and hypnagogic states.

PubMed

Wackermann, Jiri; Pütz, Peter; Büchi, Simone; Strauch, Inge; Lehmann, Dietrich

2002-11-01

Manifestations of experimentally induced altered states of consciousness in the brain's electrical activity as well as in subjective experience were explored via the hypnagogic state at sleep onset, and the state induced by exposure to an unstructured perceptual field (ganzfeld). Twelve female paid volunteers participated in sessions involving sleep onset, ganzfeld, and eyes-closed relaxed waking, and were repeatedly prompted for recall of their momentary mentation, according to a predefined schedule. Nineteen channel EEG, two channels EOG and EMG were recorded simultaneously. The mentation reports were followed by the subjects' ratings of their experience on a number of ordinal scales. Two-hundred and forty-one mentation reports were collected. EEG epochs immediately preceding the mentation reports were FFT-analysed and the spectra compared between states. The ganzfeld EEG spectrum, showing no signs of decreased vigilance, was very similar to the EEG spectrum of waking states, even showed a minor acceleration of alpha activity. The subjective experience data were reduced to four principal components: Factor I represented the subjective vigilance dimension, as confirmed by correlations with EEG spectral indices. Only Factor IV, the 'absorption' dimension, differentiated between the ganzfeld state (more absorption) and other states. In waking states and in ganzfeld, the subjects estimated elapsed time periods significantly shorter than in states at sleep onset. The results did not support the assumption of a hypnagogic nature of the ganzfeld imagery. Dream-like imagery can occur in various global functional states of the brain; hypnagogic and ganzfeld-induced states should be conceived as special cases of a broader class of 'hypnagoid' phenomena.

EEG source imaging during two Qigong meditations.

PubMed

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.

Annotation: What Electrical Brain Activity Tells Us about Brain Function that Other Techniques Cannot Tell Us--A Child Psychiatric Perspective

ERIC Educational Resources Information Center

Banaschewski, Tobias; Brandeis, Daniel

2007-01-01

Background: Monitoring brain processes in real time requires genuine subsecond resolution to follow the typical timing and frequency of neural events. Non-invasive recordings of electric (EEG/ERP) and magnetic (MEG) fields provide this time resolution. They directly measure neural activations associated with a wide variety of brain states and…

Isolating gait-related movement artifacts in electroencephalography during human walking

PubMed Central

Kline, Julia E.; Huang, Helen J.; Snyder, Kristine L.; Ferris, Daniel P.

2016-01-01

Objective High-density electroencephelography (EEG) can provide insight into human brain function during real-world activities with walking. Some recent studies have used EEG to characterize brain activity during walking, but the relative contributions of movement artifact and electrocortical activity have been difficult to quantify. We aimed to characterize movement artifact recorded by EEG electrodes at a range of walking speeds and to test the efficacy of artifact removal methods. We also quantified the similarity between movement artifact recorded by EEG electrodes and a head-mounted accelerometer. Approach We used a novel experimental method to isolate and record movement artifact with EEG electrodes during walking. We blocked electrophysiological signals using a nonconductive layer (silicone swim cap) and simulated an electrically conductive scalp on top of the swim cap using a wig coated with conductive gel. We recorded motion artifact EEG data from nine young human subjects walking on a treadmill at speeds from 0.4–1.6 m/s. We then tested artifact removal methods including moving average and wavelet-based techniques. Main Results Movement artifact recorded with EEG electrodes varied considerably, across speed, subject, and electrode location. The movement artifact measured with EEG electrodes did not correlate well with head acceleration. All of the tested artifact removal methods attenuated low-frequency noise but did not completely remove movement artifact. The spectral power fluctuations in the movement artifact data resembled data from some previously published studies of EEG during walking. Significance Our results suggest that EEG data recorded during walking likely contains substantial movement artifact that: cannot be explained by head accelerations; varies across speed, subject, and channel; and cannot be removed using traditional signal processing methods. Future studies should focus on more sophisticated methods for removing of EEG movement artifact to advance the field. PMID:26083595

Isolating gait-related movement artifacts in electroencephalography during human walking.

PubMed

Kline, Julia E; Huang, Helen J; Snyder, Kristine L; Ferris, Daniel P

2015-08-01

High-density electroencephelography (EEG) can provide an insight into human brain function during real-world activities with walking. Some recent studies have used EEG to characterize brain activity during walking, but the relative contributions of movement artifact and electrocortical activity have been difficult to quantify. We aimed to characterize movement artifact recorded by EEG electrodes at a range of walking speeds and to test the efficacy of artifact removal methods. We also quantified the similarity between movement artifact recorded by EEG electrodes and a head-mounted accelerometer. We used a novel experimental method to isolate and record movement artifact with EEG electrodes during walking. We blocked electrophysiological signals using a nonconductive layer (silicone swim cap) and simulated an electrically conductive scalp on top of the swim cap using a wig coated with conductive gel. We recorded motion artifact EEG data from nine young human subjects walking on a treadmill at speeds from 0.4 to 1.6 m s(-1). We then tested artifact removal methods including moving average and wavelet-based techniques. Movement artifact recorded with EEG electrodes varied considerably, across speed, subject, and electrode location. The movement artifact measured with EEG electrodes did not correlate well with head acceleration. All of the tested artifact removal methods attenuated low-frequency noise but did not completely remove movement artifact. The spectral power fluctuations in the movement artifact data resembled data from some previously published studies of EEG during walking. Our results suggest that EEG data recorded during walking likely contains substantial movement artifact that: cannot be explained by head accelerations; varies across speed, subject, and channel; and cannot be removed using traditional signal processing methods. Future studies should focus on more sophisticated methods for removal of EEG movement artifact to advance the field.

Human Brain Activity Patterns beyond the Isoelectric Line of Extreme Deep Coma

PubMed Central

Kroeger, Daniel; Florea, Bogdan; Amzica, Florin

2013-01-01

The electroencephalogram (EEG) reflects brain electrical activity. A flat (isoelectric) EEG, which is usually recorded during very deep coma, is considered to be a turning point between a living brain and a deceased brain. Therefore the isoelectric EEG constitutes, together with evidence of irreversible structural brain damage, one of the criteria for the assessment of brain death. In this study we use EEG recordings for humans on the one hand, and on the other hand double simultaneous intracellular recordings in the cortex and hippocampus, combined with EEG, in cats. They serve to demonstrate that a novel brain phenomenon is observable in both humans and animals during coma that is deeper than the one reflected by the isoelectric EEG, and that this state is characterized by brain activity generated within the hippocampal formation. This new state was induced either by medication applied to postanoxic coma (in human) or by application of high doses of anesthesia (isoflurane in animals) leading to an EEG activity of quasi-rhythmic sharp waves which henceforth we propose to call ν-complexes (Nu-complexes). Using simultaneous intracellular recordings in vivo in the cortex and hippocampus (especially in the CA3 region) we demonstrate that ν-complexes arise in the hippocampus and are subsequently transmitted to the cortex. The genesis of a hippocampal ν-complex depends upon another hippocampal activity, known as ripple activity, which is not overtly detectable at the cortical level. Based on our observations, we propose a scenario of how self-oscillations in hippocampal neurons can lead to a whole brain phenomenon during coma. PMID:24058669

Unmasking local activity within local field potentials (LFPs) by removing distal electrical signals using independent component analysis.

PubMed

Whitmore, Nathan W; Lin, Shih-Chieh

2016-05-15

Local field potentials (LFPs) are commonly thought to reflect the aggregate dynamics in local neural circuits around recording electrodes. However, we show that when LFPs are recorded in awake behaving animals against a distal reference on the skull as commonly practiced, LFPs are significantly contaminated by non-local and non-neural sources arising from the reference electrode and from movement-related noise. In a data set with simultaneously recorded LFPs and electroencephalograms (EEGs) across multiple brain regions while rats perform an auditory oddball task, we used independent component analysis (ICA) to identify signals arising from electrical reference and from volume-conducted noise based on their distributed spatial pattern across multiple electrodes and distinct power spectral features. These sources of distal electrical signals collectively accounted for 23-77% of total variance in unprocessed LFPs, as well as most of the gamma oscillation responses to the target stimulus in EEGs. Gamma oscillation power was concentrated in volume-conducted noise and was tightly coupled with the onset of licking behavior, suggesting a likely origin of muscle activity associated with body movement or orofacial movement. The removal of distal signal contamination also selectively reduced correlations of LFP/EEG signals between distant brain regions but not within the same region. Finally, the removal of contamination from distal electrical signals preserved an event-related potential (ERP) response to auditory stimuli in the frontal cortex and also increased the coupling between the frontal ERP amplitude and neuronal activity in the basal forebrain, supporting the conclusion that removing distal electrical signals unmasked local activity within LFPs. Together, these results highlight the significant contamination of LFPs by distal electrical signals and caution against the straightforward interpretation of unprocessed LFPs. Our results provide a principled approach to identify and remove such contamination to unmask local LFPs. Published by Elsevier Inc.

Unmasking local activity within local field potentials (LFPs) by removing distal electrical signals using independent component analysis

PubMed Central

Whitmore, Nathan W.; Lin, Shih-Chieh

2016-01-01

Local field potentials (LFPs) are commonly thought to reflect the aggregate dynamics in local neural circuits around recording electrodes. However, we show that when LFPs are recorded in awake behaving animals against a distal reference on the skull as commonly practiced, LFPs are significantly contaminated by non-local and non-neural sources arising from the reference electrode and from movement-related noise. In a data set with simultaneously recorded LFPs and electroencephalograms (EEGs) across multiple brain regions while rats perform an auditory oddball task, we used independent component analysis (ICA) to identify signals arising from electrical reference and from volume-conducted noise based on their distributed spatial pattern across multiple electrodes and distinct power spectral features. These sources of distal electrical signals collectively accounted for 23–77% of total variance in unprocessed LFPs, as well as most of the gamma oscillation responses to the target stimulus in EEGs. Gamma oscillation power was concentrated in volume-conducted noise and was tightly coupled with the onset of licking behavior, suggesting a likely origin of muscle activity associated with body movement or orofacial movement. The removal of distal signal contamination also selectively reduced correlations of LFP/EEG signals between distant brain regions but not within the same region. Finally, the removal of contamination from distal electrical signals preserved an event-related potential (ERP) response to auditory stimuli in the frontal cortex and also increased the coupling between the frontal ERP amplitude and neuronal activity in the basal forebrain, supporting the conclusion that removing distal electrical signals unmasked local activity within LFPs. Together, these results highlight the significant contamination of LFPs by distal electrical signals and caution against the straightforward interpretation of unprocessed LFPs. Our results provide a principled approach to identify and remove such contamination to unmask local LFPs. PMID:26899209

High-Frequency EEG Variations in Children with Autism Spectrum Disorder during Human Faces Visualization

PubMed Central

Reategui, Camille; Costa, Bruna Karen de Sousa; da Fonseca, Caio Queiroz; da Silva, Luana; Morya, Edgard

2017-01-01

Autism spectrum disorder (ASD) is a neuropsychiatric disorder characterized by the impairment in the social reciprocity, interaction/language, and behavior, with stereotypes and signs of sensory function deficits. Electroencephalography (EEG) is a well-established and noninvasive tool for neurophysiological characterization and monitoring of the brain electrical activity, able to identify abnormalities related to frequency range, connectivity, and lateralization of brain functions. This research aims to evidence quantitative differences in the frequency spectrum pattern between EEG signals of children with and without ASD during visualization of human faces in three different expressions: neutral, happy, and angry. Quantitative clinical evaluations, neuropsychological evaluation, and EEG of children with and without ASD were analyzed paired by age and gender. The results showed stronger activation in higher frequencies (above 30 Hz) in frontal, central, parietal, and occipital regions in the ASD group. This pattern of activation may correlate with developmental characteristics in the children with ASD. PMID:29018811

Dynamical complexity in a mean-field model of human EEG

NASA Astrophysics Data System (ADS)

Frascoli, Federico; Dafilis, Mathew P.; van Veen, Lennaert; Bojak, Ingo; Liley, David T. J.

2008-12-01

A recently proposed mean-field theory of mammalian cortex rhythmogenesis describes the salient features of electrical activity in the cerebral macrocolumn, with the use of inhibitory and excitatory neuronal populations (Liley et al 2002). This model is capable of producing a range of important human EEG (electroencephalogram) features such as the alpha rhythm, the 40 Hz activity thought to be associated with conscious awareness (Bojak & Liley 2007) and the changes in EEG spectral power associated with general anesthetic effect (Bojak & Liley 2005). From the point of view of nonlinear dynamics, the model entails a vast parameter space within which multistability, pseudoperiodic regimes, various routes to chaos, fat fractals and rich bifurcation scenarios occur for physiologically relevant parameter values (van Veen & Liley 2006). The origin and the character of this complex behaviour, and its relevance for EEG activity will be illustrated. The existence of short-lived unstable brain states will also be discussed in terms of the available theoretical and experimental results. A perspective on future analysis will conclude the presentation.

Stability in Infant Frontal Asymmetry as a Predictor of Toddlerhood Internalizing and Externalizing Behaviors

PubMed Central

Smith, Cynthia L.; Bell, Martha Ann

2013-01-01

Stability in frontal brain electrical activity (i.e., electroencephalographic or EEG) asymmetry at 10 and 24 months was examined with respect to maternal ratings of internalizing and externalizing behaviors at 30 months in a sample of 48 children. Children with stable left frontal EEG asymmetry during infancy were rated higher in externalizing behaviors by their mothers, whereas children with stable right frontal EEG asymmetry were rated higher in internalizing behaviors. These findings highlight the need to focus on the early stability in physiological measures that may be implicated later in developing behavioral problems. PMID:20175143

Post-acute stroke patients use brain-computer interface to activate electrical stimulation.

PubMed

Tan, H G; Kong, K H; Shee, C Y; Wang, C C; Guan, C T; Ang, W T

2010-01-01

Through certain mental actions, our electroencephalogram (EEG) can be regulated to operate a brain-computer interface (BCI), which translates the EEG patterns into commands that can be used to operate devices such as prostheses. This allows paralyzed persons to gain direct brain control of the paretic limb, which could open up many possibilities for rehabilitative and assistive applications. When using a BCI neuroprosthesis in stroke, one question that has surfaced is whether stroke patients are able to produce a sufficient change in EEG that can be used as a control signal to operate a prosthesis.

The study of evolution and depression of the alpha-rhythm in the human brain EEG by means of wavelet-based methods

NASA Astrophysics Data System (ADS)

Runnova, A. E.; Zhuravlev, M. O.; Khramova, M. V.; Pysarchik, A. N.

2017-04-01

We study the appearance, development and depression of the alpha-rhythm in human EEG data during a psychophysiological experiment by stimulating cognitive activity with the perception of ambiguous object. The new method based on continuous wavelet transform allows to estimate the energy contribution of various components, including the alpha rhythm, in the general dynamics of the electrical activity of the projections of various areas of the brain. The decision-making process by observe ambiguous images is characterized by specific oscillatory alfa-rhytm patterns in the multi-channel EEG data. We have shown the repeatability of detected principles of the alpha-rhythm evolution in a data of group of 12 healthy male volunteers.

Quantitative complexity analysis in multi-channel intracranial EEG recordings form epilepsy brains

PubMed Central

Liu, Chang-Chia; Pardalos, Panos M.; Chaovalitwongse, W. Art; Shiau, Deng-Shan; Ghacibeh, Georges; Suharitdamrong, Wichai; Sackellares, J. Chris

2008-01-01

Epilepsy is a brain disorder characterized clinically by temporary but recurrent disturbances of brain function that may or may not be associated with destruction or loss of consciousness and abnormal behavior. Human brain is composed of more than 10 to the power 10 neurons, each of which receives electrical impulses known as action potentials from others neurons via synapses and sends electrical impulses via a sing output line to a similar (the axon) number of neurons. When neuronal networks are active, they produced a change in voltage potential, which can be captured by an electroencephalogram (EEG). The EEG recordings represent the time series that match up to neurological activity as a function of time. By analyzing the EEG recordings, we sought to evaluate the degree of underlining dynamical complexity prior to progression of seizure onset. Through the utilization of the dynamical measurements, it is possible to classify the state of the brain according to the underlying dynamical properties of EEG recordings. The results from two patients with temporal lobe epilepsy (TLE), the degree of complexity start converging to lower value prior to the epileptic seizures was observed from epileptic regions as well as non-epileptic regions. The dynamical measurements appear to reflect the changes of EEG’s dynamical structure. We suggest that the nonlinear dynamical analysis can provide a useful information for detecting relative changes in brain dynamics, which cannot be detected by conventional linear analysis. PMID:19079790

Application and Evaluation of Independent Component Analysis Methods to Generalized Seizure Disorder Activities Exhibited in the Brain.

PubMed

George, S Thomas; Balakrishnan, R; Johnson, J Stanly; Jayakumar, J

2017-07-01

EEG records the spontaneous electrical activity of the brain using multiple electrodes placed on the scalp, and it provides a wealth of information related to the functions of brain. Nevertheless, the signals from the electrodes cannot be directly applied to a diagnostic tool like brain mapping as they undergo a "mixing" process because of the volume conduction effect in the scalp. A pervasive problem in neuroscience is determining which regions of the brain are active, given voltage measurements at the scalp. Because of which, there has been a surge of interest among the biosignal processing community to investigate the process of mixing and unmixing to identify the underlying active sources. According to the assumptions of independent component analysis (ICA) algorithms, the resultant mixture obtained from the scalp can be closely approximated by a linear combination of the "actual" EEG signals emanating from the underlying sources of electrical activity in the brain. As a consequence, using these well-known ICA techniques in preprocessing of the EEG signals prior to clinical applications could result in development of diagnostic tool like quantitative EEG which in turn can assist the neurologists to gain noninvasive access to patient-specific cortical activity, which helps in treating neuropathologies like seizure disorders. The popular and proven ICA schemes mentioned in various literature and applications were selected (which includes Infomax, JADE, and SOBI) and applied on generalized seizure disorder samples using EEGLAB toolbox in MATLAB environment to see their usefulness in source separations; and they were validated by the expert neurologist for clinical relevance in terms of pathologies on brain functionalities. The performance of Infomax method was found to be superior when compared with other ICA schemes applied on EEG and it has been established based on the validations carried by expert neurologist for generalized seizure and its clinical correlation. The results are encouraging for furthering the studies in the direction of developing useful brain mapping tools using ICA methods.

Measurements of evoked electroencephalograph by transcranial magnetic stimulation applied to motor cortex and posterior parietal cortex

NASA Astrophysics Data System (ADS)

Iwahashi, Masakuni; Koyama, Yohei; Hyodo, Akira; Hayami, Takehito; Ueno, Shoogo; Iramina, Keiji

2009-04-01

To investigate the functional connectivity, the evoked potentials by stimulating at the motor cortex, the posterior parietal cortex, and the cerebellum by transcranial magnetic stimulation (TMS) were measured. It is difficult to measure the evoked electroencephalograph (EEG) by the magnetic stimulation because of the large artifact induced by the magnetic pulse. We used an EEG measurement system with sample-and-hold circuit and an independent component analysis to eliminate the electromagnetic interaction emitted from TMS. It was possible to measure EEG signals from all electrodes over the head within 10 ms after applying the TMS. When the motor area was stimulated by TMS, the spread of evoked electrical activity to the contralateral hemisphere was observed at 20 ms after stimulation. However, when the posterior parietal cortex was stimulated, the evoked electrical activity to the contralateral hemisphere was not observed. When the cerebellum was stimulated, the cortical activity propagated from the stimulated point to the frontal area and the contralateral hemisphere at around 20 ms after stimulation. These results suggest that the motor area has a strong interhemispheric connection and the posterior parietal cortex has no interhemispheric connection.

Entropy changes in brain function.

PubMed

Rosso, Osvaldo A

2007-04-01

The traditional way of analyzing brain electrical activity, on the basis of electroencephalography (EEG) records, relies mainly on visual inspection and years of training. Although it is quite useful, of course, one has to acknowledge its subjective nature that hardly allows for a systematic protocol. In the present work quantifiers based on information theory and wavelet transform are reviewed. The "relative wavelet energy" provides information about the relative energy associated with different frequency bands present in the EEG and their corresponding degree of importance. The "normalized total wavelet entropy" carries information about the degree of order-disorder associated with a multi-frequency signal response. Their application in the analysis and quantification of short duration EEG signals (event-related potentials) and epileptic EEG records are summarized.

Coherence and phase locking in the scalp EEG and between LORETA model sources, and microstates as putative mechanisms of brain temporo-spatial functional organization.

PubMed

Lehmann, Dietrich; Faber, Pascal L; Gianotti, Lorena R R; Kochi, Kieko; Pascual-Marqui, Roberto D

2006-01-01

Brain electric mechanisms of temporary, functional binding between brain regions are studied using computation of scalp EEG coherence and phase locking, sensitive to time differences of few milliseconds. However, such results if computed from scalp data are ambiguous since electric sources are spatially oriented. Non-ambiguous results can be obtained using calculated time series of strength of intracerebral model sources. This is illustrated applying LORETA modeling to EEG during resting and meditation. During meditation, time series of LORETA model sources revealed a tendency to decreased left-right intracerebral coherence in the delta band, and to increased anterior-posterior intracerebral coherence in the theta band. An alternate conceptualization of functional binding is based on the observation that brain electric activity is discontinuous, i.e., that it occurs in chunks of up to about 100 ms duration that are detectable as quasi-stable scalp field configurations of brain electric activity, called microstates. Their functional significance is illustrated in spontaneous and event-related paradigms, where microstates associated with imagery- versus abstract-type mentation, or while reading positive versus negative emotion words showed clearly different regions of cortical activation in LORETA tomography. These data support the concept that complete brain functions of higher order such as a momentary thought might be incorporated in temporal chunks of processing in the range of tens to about 100 ms as quasi-stable brain states; during these time windows, subprocesses would be accepted as members of the ongoing chunk of processing.

Comparison of simultaneously recorded [H2(15)O]-PET and LORETA during cognitive and pharmacological activation.

PubMed

Gamma, Alex; Lehmann, Dietrich; Frei, Edi; Iwata, Kazuki; Pascual-Marqui, Roberto D; Vollenweider, Franz X

2004-06-01

The complementary strengths and weaknesses of established functional brain imaging methods (high spatial, low temporal resolution) and EEG-based techniques (low spatial, high temporal resolution) make their combined use a promising avenue for studying brain processes at a more fine-grained level. However, this strategy requires a better understanding of the relationship between hemodynamic/metabolic and neuroelectric measures of brain activity. We investigated possible correspondences between cerebral blood flow (CBF) as measured by [H2O]-PET and intracerebral electric activity computed by Low Resolution Brain Electromagnetic Tomography (LORETA) from scalp-recorded multichannel EEG in healthy human subjects during cognitive and pharmacological stimulation. The two imaging modalities were compared by descriptive, correlational, and variance analyses, the latter carried out using statistical parametric mapping (SPM99). Descriptive visual comparison showed a partial overlap between the sets of active brain regions detected by the two modalities. A number of exclusively positive correlations of neuroelectric activity with regional CBF were found across the whole EEG frequency range, including slow wave activity, the latter finding being in contrast to most previous studies conducted in patients. Analysis of variance revealed an extensive lack of statistically significant correspondences between brain activity changes as measured by PET vs. EEG-LORETA. In general, correspondences, to the extent they were found, were dependent on experimental condition, brain region, and EEG frequency. Copyright 2004 Wiley-Liss, Inc.

Neuropharmacological Evaluation of Toxic Chemicals. Part 1. Behavioral and EEG Correlates of Immobilization in the Rhesus Monkey. Part 2. Operant Conditioning of 12-15 Hz Sensorimotor Cortex EEG Activity in the Rhesus Monkey

DTIC Science & Technology

1977-06-01

especially when procedures involving catheterization of the cardiovascular system or electrical stimulation or recording of brain were desired in awake ...immobilization. Most commonly, the greatest magnitude of SMR activity occurring in the awake condition appeared during immobilization or during immobiliz- ation...level of arousal in the awake animal. We were impressed by the fact that the immobilization response continued throughout the 15 minute observation

[Effect of alcohol on electrical organisation in the brain during a visuospatial working memory task and its relationship with the menstrual cycle].

PubMed

Sanz-Martin, Araceli; Hernández-González, Marisela; Guevara, Miguel Ángel; Santana, Gloria; Gumá-Díaz, Emilio

2014-02-01

The metabolism of alcohol and cognitive functions can vary during the menstrual cycle. Also, both alcohol ingestion and hormonal variations during menstruation have been associated with characteristic changes in electroencephalographic (EEG) activity. AIM. To determine whether EEG activity during a working memory task is affected by acute alcohol consumption, and if these EEG patterns vary in relation to different phases of the menstrual cycle. 24 women who drank a moderate dose of alcohol or placebo during the follicular and early luteal phases of the menstrual cycle. The EEG activity was recorded during performance of viso-spatial working memory task. Although the alcohol did not deteriorate the performance of working memory task, it caused in the EEG a decrease of relative theta power and lower right fronto-parietal correlation in theta and alpha2 bands. Only women who drank alcohol in the follicular phase had a higher relative potency of alpha1, which could indicate a lower level of arousal and attention. These results contribute to a better understanding of the brain mechanisms underlying cognitive changes with alcohol and its relationship to the menstrual cycle.

Real-Time EEG Signal Enhancement Using Canonical Correlation Analysis and Gaussian Mixture Clustering

PubMed Central

Huang, Chih-Sheng; Yang, Wen-Yu; Chuang, Chun-Hsiang; Wang, Yu-Kai

2018-01-01

Electroencephalogram (EEG) signals are usually contaminated with various artifacts, such as signal associated with muscle activity, eye movement, and body motion, which have a noncerebral origin. The amplitude of such artifacts is larger than that of the electrical activity of the brain, so they mask the cortical signals of interest, resulting in biased analysis and interpretation. Several blind source separation methods have been developed to remove artifacts from the EEG recordings. However, the iterative process for measuring separation within multichannel recordings is computationally intractable. Moreover, manually excluding the artifact components requires a time-consuming offline process. This work proposes a real-time artifact removal algorithm that is based on canonical correlation analysis (CCA), feature extraction, and the Gaussian mixture model (GMM) to improve the quality of EEG signals. The CCA was used to decompose EEG signals into components followed by feature extraction to extract representative features and GMM to cluster these features into groups to recognize and remove artifacts. The feasibility of the proposed algorithm was demonstrated by effectively removing artifacts caused by blinks, head/body movement, and chewing from EEG recordings while preserving the temporal and spectral characteristics of the signals that are important to cognitive research. PMID:29599950

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

PubMed Central

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

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

PubMed

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

2015-01-22

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

a Statistical Theory of the Epilepsies.

NASA Astrophysics Data System (ADS)

Thomas, Kuryan

1988-12-01

A new physical and mathematical model for the epilepsies is proposed, based on the theory of bond percolation on finite lattices. Within this model, the onset of seizures in the brain is identified with the appearance of spanning clusters of neurons engaged in the spurious and uncontrollable electrical activity characteristic of seizures. It is proposed that the fraction of excitatory to inhibitory synapses can be identified with a bond probability, and that the bond probability is a randomly varying quantity displaying Gaussian statistics. The consequences of the proposed model to the treatment of the epilepsies is explored. The nature of the data on the epilepsies which can be acquired in a clinical setting is described. It is shown that such data can be analyzed to provide preliminary support for the bond percolation hypothesis, and to quantify the efficacy of anti-epileptic drugs in a treatment program. The results of a battery of statistical tests on seizure distributions are discussed. The physical theory of the electroencephalogram (EEG) is described, and extant models of the electrical activity measured by the EEG are discussed, with an emphasis on their physical behavior. A proposal is made to explain the difference between the power spectra of electrical activity measured with cranial probes and with the EEG. Statistical tests on the characteristic EEG manifestations of epileptic activity are conducted, and their results described. Computer simulations of a correlated bond percolating system are constructed. It is shown that the statistical properties of the results of such a simulation are strongly suggestive of the statistical properties of clinical data. The study finds no contradictions between the predictions of the bond percolation model and the observed properties of the available data. Suggestions are made for further research and for techniques based on the proposed model which may be used for tuning the effects of anti -epileptic drugs.

Efficacy of brain-computer interface-driven neuromuscular electrical stimulation for chronic paresis after stroke.

PubMed

Mukaino, Masahiko; Ono, Takashi; Shindo, Keiichiro; Fujiwara, Toshiyuki; Ota, Tetsuo; Kimura, Akio; Liu, Meigen; Ushiba, Junichi

2014-04-01

Brain computer interface technology is of great interest to researchers as a potential therapeutic measure for people with severe neurological disorders. The aim of this study was to examine the efficacy of brain computer interface, by comparing conventional neuromuscular electrical stimulation and brain computer interface-driven neuromuscular electrical stimulation, using an A-B-A-B withdrawal single-subject design. A 38-year-old male with severe hemiplegia due to a putaminal haemorrhage participated in this study. The design involved 2 epochs. In epoch A, the patient attempted to open his fingers during the application of neuromuscular electrical stimulation, irrespective of his actual brain activity. In epoch B, neuromuscular electrical stimulation was applied only when a significant motor-related cortical potential was observed in the electroencephalogram. The subject initially showed diffuse functional magnetic resonance imaging activation and small electro-encephalogram responses while attempting finger movement. Epoch A was associated with few neurological or clinical signs of improvement. Epoch B, with a brain computer interface, was associated with marked lateralization of electroencephalogram (EEG) and blood oxygenation level dependent responses. Voluntary electromyogram (EMG) activity, with significant EEG-EMG coherence, was also prompted. Clinical improvement in upper-extremity function and muscle tone was observed. These results indicate that self-directed training with a brain computer interface may induce activity- dependent cortical plasticity and promote functional recovery. This preliminary clinical investigation encourages further research using a controlled design.

Your brain on bikes: P3, MMN/N2b, and baseline noise while pedaling a stationary bike.

PubMed

Scanlon, Joanna E M; Sieben, Alex J; Holyk, Kevin R; Mathewson, Kyle E

2017-06-01

Increasingly, there is a trend to measure brain activity in more ecologically realistic scenarios. Normally, the confines of the laboratory and sedentary tasks mitigate sources of electrical noise on EEG measurement. Moving EEG outside of the lab requires understanding of the impact of complex movements and activities on traditional EEG and ERP measures. Here, we recorded EEG with active electrodes while participants were either riding or sitting on a stationary bike in an electrical and sound-attenuated chamber in the lab. Participants performed an auditory oddball task, pressing a button when they detected rare target tones in a series of standard frequent tones. We quantified both the levels of spectral, single-trial baseline, and ERP baseline noise, as well as classic MMN/N2b and P3 ERP components measured during both biking and sitting still. We observed slight increases in posterior high frequency noise in the spectra, and increased noise in the baseline period during biking. However, morphologically and topographically similar MMN/N2b and P3 components were measured reliably while both biking and sitting. A quantification of the power to reliably measure ERPs as a function of the number of trials revealed slight increases in the number of trials needed during biking to achieve the same level of power. Taken in sum, our results confirm that classic ERPs can be measured reliably during biking activities in the lab. Future directions will employ these techniques outside the lab in ecologically valid situations. © 2017 Society for Psychophysiological Research.

Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals.

PubMed

Acharya, U Rajendra; Oh, Shu Lih; Hagiwara, Yuki; Tan, Jen Hong; Adeli, Hojjat

2017-09-27

An encephalogram (EEG) is a commonly used ancillary test to aide in the diagnosis of epilepsy. The EEG signal contains information about the electrical activity of the brain. Traditionally, neurologists employ direct visual inspection to identify epileptiform abnormalities. This technique can be time-consuming, limited by technical artifact, provides variable results secondary to reader expertise level, and is limited in identifying abnormalities. Therefore, it is essential to develop a computer-aided diagnosis (CAD) system to automatically distinguish the class of these EEG signals using machine learning techniques. This is the first study to employ the convolutional neural network (CNN) for analysis of EEG signals. In this work, a 13-layer deep convolutional neural network (CNN) algorithm is implemented to detect normal, preictal, and seizure classes. The proposed technique achieved an accuracy, specificity, and sensitivity of 88.67%, 90.00% and 95.00%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Graph Theory at the Service of Electroencephalograms.

PubMed

Iakovidou, Nantia D

2017-04-01

The brain is one of the largest and most complex organs in the human body and EEG is a noninvasive electrophysiological monitoring method that is used to record the electrical activity of the brain. Lately, the functional connectivity in human brain has been regarded and studied as a complex network using EEG signals. This means that the brain is studied as a connected system where nodes, or units, represent different specialized brain regions and links, or connections, represent communication pathways between the nodes. Graph theory and theory of complex networks provide a variety of measures, methods, and tools that can be useful to efficiently model, analyze, and study EEG networks. This article is addressed to computer scientists who wish to be acquainted and deal with the study of EEG data and also to neuroscientists who would like to become familiar with graph theoretic approaches and tools to analyze EEG data.

High-resolution EEG techniques for brain-computer interface applications.

PubMed

Cincotti, Febo; Mattia, Donatella; Aloise, Fabio; Bufalari, Simona; Astolfi, Laura; De Vico Fallani, Fabrizio; Tocci, Andrea; Bianchi, Luigi; Marciani, Maria Grazia; Gao, Shangkai; Millan, Jose; Babiloni, Fabio

2008-01-15

High-resolution electroencephalographic (HREEG) techniques allow estimation of cortical activity based on non-invasive scalp potential measurements, using appropriate models of volume conduction and of neuroelectrical sources. In this study we propose an application of this body of technologies, originally developed to obtain functional images of the brain's electrical activity, in the context of brain-computer interfaces (BCI). Our working hypothesis predicted that, since HREEG pre-processing removes spatial correlation introduced by current conduction in the head structures, by providing the BCI with waveforms that are mostly due to the unmixed activity of a small cortical region, a more reliable classification would be obtained, at least when the activity to detect has a limited generator, which is the case in motor related tasks. HREEG techniques employed in this study rely on (i) individual head models derived from anatomical magnetic resonance images, (ii) distributed source model, composed of a layer of current dipoles, geometrically constrained to the cortical mantle, (iii) depth-weighted minimum L(2)-norm constraint and Tikhonov regularization for linear inverse problem solution and (iv) estimation of electrical activity in cortical regions of interest corresponding to relevant Brodmann areas. Six subjects were trained to learn self modulation of sensorimotor EEG rhythms, related to the imagination of limb movements. Off-line EEG data was used to estimate waveforms of cortical activity (cortical current density, CCD) on selected regions of interest. CCD waveforms were fed into the BCI computational pipeline as an alternative to raw EEG signals; spectral features are evaluated through statistical tests (r(2) analysis), to quantify their reliability for BCI control. These results are compared, within subjects, to analogous results obtained without HREEG techniques. The processing procedure was designed in such a way that computations could be split into a setup phase (which includes most of the computational burden) and the actual EEG processing phase, which was limited to a single matrix multiplication. This separation allowed to make the procedure suitable for on-line utilization, and a pilot experiment was performed. Results show that lateralization of electrical activity, which is expected to be contralateral to the imagined movement, is more evident on the estimated CCDs than in the scalp potentials. CCDs produce a pattern of relevant spectral features that is more spatially focused, and has a higher statistical significance (EEG: 0.20+/-0.114 S.D.; CCD: 0.55+/-0.16 S.D.; p=10(-5)). A pilot experiment showed that a trained subject could utilize voluntary modulation of estimated CCDs for accurate (eight targets) on-line control of a cursor. This study showed that it is practically feasible to utilize HREEG techniques for on-line operation of a BCI system; off-line analysis suggests that accuracy of BCI control is enhanced by the proposed method.

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

PubMed

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

2014-10-01

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

Battery-Less Electroencephalogram System Architecture Optimization

DTIC Science & Technology

2016-12-01

disorders, especially in real-world situations, such as when a Soldier is in theater. There are several methods to study the electrical activity in the brain...to measure the electrical activity in the brain that can still be used to study brain activity. Currently, most EEGs are recorded in highly controlled...base to build a larger system as its power consumption would allow it to operate from a AA battery for more than 72 h. While this might be acceptable

A quantitative evaluation of dry-sensor electroencephalography

NASA Astrophysics Data System (ADS)

Uy, E. Timothy

Neurologists, neuroscientists, and experimental psychologists study electrical activity within the brain by recording voltage fluctuations at the scalp. This is electroencephalography (EEG). In conventional or "wet" EEG, scalp abrasion and use of electrolytic paste are required to insure good electrical connection between sensor and skin. Repeated abrasion quickly becomes irritating to subjects, severely limiting the number and frequency of sessions. Several groups have produced "dry" EEG sensors that do not require abrasion or conductive paste. These, in addition to sidestepping the issue of abrasion, promise to reduce setup time from about 30 minutes with a technician to less than 30 seconds without one. The availability of such an instrument would (1) reduce the cost of brain-related medical care, (2) lower the barrier of entry on brain experimentation, and (3) allow individual subjects to contribute substantially more data without fear of abrasion or fatigue. Accuracy of the EEG is paramount in the medical diagnosis of epilepsy, in experimental psychology and in the burgeoning field of brain-computer interface. Without a sufficiently accurate measurement, the advantages of dry sensors remain a moot point. However, even after nearly a decade, demonstrations of dry EEG accuracy with respect to wet have been limited to visual comparison of short snippets of spontaneous EEG, averaged event-related potentials or plots of power spectrum. In this dissertation, I propose a detailed methodology based on single-trial EEG classification for comparing dry EEG sensors to their wet counterparts. Applied to a set of commercially fabricated dry sensors, this work reveals that dry sensors can perform as well their wet counterparts with careful screening and attention to the bandwidth of interest.

Sedation for electroencephalography with dexmedetomidine or chloral hydrate: a comparative study on the qualitative and quantitative electroencephalogram pattern.

PubMed

Fernandes, Magda L; Oliveira, Welser Machado de; Santos, Maria do Carmo Vasconcellos; Gomez, Renato S

2015-01-01

Sedation for electroencephalography in uncooperative patients is a controversial issue because majority of sedatives, hypnotics, and general anesthetics interfere with the brain's electrical activity. Chloral hydrate (CH) is typically used for this sedation, and dexmedetomidine (DEX) was recently tested because preliminary data suggest that this drug does not affect the electroencephalogram (EEG). The aim of the present study was to compare the EEG pattern during DEX or CH sedation to test the hypothesis that both drugs exert similar effects on the EEG. A total of 17 patients underwent 2 EEGs on 2 separate occasions, one with DEX and the other with CH. The EEG qualitative variables included the phases of sleep and the background activity. The EEG quantitative analysis was performed during the first 2 minutes of the second stage of sleep. The EEG quantitative variables included density, duration, and amplitude of the sleep spindles and absolute spectral power. The results showed that the qualitative analysis, density, duration, and amplitude of sleep spindles did not differ between DEX and CH sedation. The power of the slow-frequency bands (δ and θ) was higher with DEX, but the power of the faster-frequency bands (α and β) was higher with CH. The total power was lower with DEX than with CH. The differences of DEX and CH in EEG power did not change the EEG qualitative interpretation, which was similar with the 2 drugs. Other studies comparing natural sleep and sleep induced by these drugs are needed to clarify the clinical relevance of the observed EEG quantitative differences.

Toward a fully integrated wireless wearable EEG-NIRS bimodal acquisition system.

PubMed

Safaie, J; Grebe, R; Abrishami Moghaddam, H; Wallois, F

2013-10-01

Interactions between neuronal electrical activity and regional changes in microcirculation are assumed to play a major role in physiological brain activity and the development of pathological disorders, but have been poorly elucidated to date. There is a need for advanced diagnostic tools to investigate the relationships between these two physiological processes. To meet these needs, a wireless wearable system has been developed, which combines a near infrared spectroscopy (NIRS) system using light emitting diodes (LEDs) as a light source and silicon photodiodes as a detector with an integrated electroencephalography (EEG) system. The main advantages over currently available devices are miniaturization and integration of a real-time electrical and hemodynamic activity monitor into one wearable device. For patient distributed monitoring and creating a body-area network, up to seven same devices can be connected to a single base station (PC) synchronously. Each node presents enhanced portability due to the wireless communication and highly integrated components resulting in a small, lightweight signal acquisition device. Further progress includes the individual control of LEDs output to automatically or interactively adjust emitted light to the actual local situation online, the use of silicon photodiodes with a safe low-voltage power supply, and an integrated three dimensional accelerometer for movement detection for the identification of motion artifacts. The device was tested and validated using our enhanced EEG-NIRS tissue mimicking fluid phantom for sensitivity mapping. Typical somatotopic electrical evoked potential experiments were performed to verify clinical applicability.

Hardware enhance of brain computer interfaces

NASA Astrophysics Data System (ADS)

Wu, Jerry; Szu, Harold; Chen, Yuechen; Guo, Ran; Gu, Xixi

2015-05-01

The history of brain-computer interfaces (BCIs) starts with Hans Berger's discovery of the electrical activity of the human brain and the development of electroencephalography (EEG). Recent years, BCI researches are focused on Invasive, Partially invasive, and Non-invasive BCI. Furthermore, EEG can be also applied to telepathic communication which could provide the basis for brain-based communication using imagined speech. It is possible to use EEG signals to discriminate the vowels and consonants embedded in spoken and in imagined words and apply to military product. In this report, we begin with an example of using high density EEG with high electrode density and analysis the results by using BCIs. The BCIs in this work is enhanced by A field-programmable gate array (FPGA) board with optimized two dimension (2D) image Fast Fourier Transform (FFT) analysis.

Frontal midline theta and the error-related negativity: neurophysiological mechanisms of action regulation.

PubMed

Luu, Phan; Tucker, Don M; Makeig, Scott

2004-08-01

The error-related negativity (ERN) is an event-related potential (ERP) peak occurring between 50 and 100 ms after the commission of a speeded motor response that the subject immediately realizes to be in error. The ERN is believed to index brain processes that monitor action outcomes. Our previous analyses of ERP and EEG data suggested that the ERN is dominated by partial phase-locking of intermittent theta-band EEG activity. In this paper, this possibility is further evaluated. The possibility that the ERN is produced by phase-locking of theta-band EEG activity was examined by analyzing the single-trial EEG traces from a forced-choice speeded response paradigm before and after applying theta-band (4-7 Hz) filtering and by comparing the averaged and single-trial phase-locked (ERP) and non-phase-locked (other) EEG data. Electrical source analyses were used to estimate the brain sources involved in the generation of the ERN. Beginning just before incorrect button presses in a speeded choice response paradigm, midfrontal theta-band activity increased in amplitude and became partially and transiently phase-locked to the subject's motor response, accounting for 57% of ERN peak amplitude. The portion of the theta-EEG activity increase remaining after subtracting the response-locked ERP from each trial was larger and longer lasting after error responses than after correct responses, extending on average 400 ms beyond the ERN peak. Multiple equivalent-dipole source analysis suggested 3 possible equivalent dipole sources of the theta-bandpassed ERN, while the scalp distribution of non-phase-locked theta amplitude suggested the presence of additional frontal theta-EEG sources. These results appear consistent with a body of research that demonstrates a relationship between limbic theta activity and action regulation, including error monitoring and learning.

Hybrid Weighted Minimum Norm Method A new method based LORETA to solve EEG inverse problem.

PubMed

Song, C; Zhuang, T; Wu, Q

2005-01-01

This Paper brings forward a new method to solve EEG inverse problem. Based on following physiological characteristic of neural electrical activity source: first, the neighboring neurons are prone to active synchronously; second, the distribution of source space is sparse; third, the active intensity of the sources are high centralized, we take these prior knowledge as prerequisite condition to develop the inverse solution of EEG, and not assume other characteristic of inverse solution to realize the most commonly 3D EEG reconstruction map. The proposed algorithm takes advantage of LORETA's low resolution method which emphasizes particularly on 'localization' and FOCUSS's high resolution method which emphasizes particularly on 'separability'. The method is still under the frame of the weighted minimum norm method. The keystone is to construct a weighted matrix which takes reference from the existing smoothness operator, competition mechanism and study algorithm. The basic processing is to obtain an initial solution's estimation firstly, then construct a new estimation using the initial solution's information, repeat this process until the solutions under last two estimate processing is keeping unchanged.

Using recurrence plot for determinism analysis of EEG recordings in genetic absence epilepsy rats.

PubMed

Ouyang, Gaoxiang; Li, Xiaoli; Dang, Chuangyin; Richards, Douglas A

2008-08-01

Understanding the transition of brain activity towards an absence seizure is a challenging task. In this paper, we use recurrence quantification analysis to indicate the deterministic dynamics of EEG series at the seizure-free, pre-seizure and seizure states in genetic absence epilepsy rats. The determinism measure, DET, based on recurrence plot, was applied to analyse these three EEG datasets, each dataset containing 300 single-channel EEG epochs of 5-s duration. Then, statistical analysis of the DET values in each dataset was carried out to determine whether their distributions over the three groups were significantly different. Furthermore, a surrogate technique was applied to calculate the significance level of determinism measures in EEG recordings. The mean (+/-SD) DET of EEG was 0.177+/-0.045 in pre-seizure intervals. The DET values of pre-seizure EEG data are significantly higher than those of seizure-free intervals, 0.123+/-0.023, (P<0.01), but lower than those of seizure intervals, 0.392+/-0.110, (P<0.01). Using surrogate data methods, the significance of determinism in EEG epochs was present in 25 of 300 (8.3%), 181 of 300 (60.3%) and 289 of 300 (96.3%) in seizure-free, pre-seizure and seizure intervals, respectively. Results provide some first indications that EEG epochs during pre-seizure intervals exhibit a higher degree of determinism than seizure-free EEG epochs, but lower than those in seizure EEG epochs in absence epilepsy. The proposed methods have the potential of detecting the transition between normal brain activity and the absence seizure state, thus opening up the possibility of intervention, whether electrical or pharmacological, to prevent the oncoming seizure.

Patterns recognition of electric brain activity using artificial neural networks

NASA Astrophysics Data System (ADS)

Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

2017-04-01

An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

Diurnal alterations of brain electrical activity in healthy adults: a LORETA study.

PubMed

Toth, Marton; Kiss, Attila; Kosztolanyi, Peter; Kondakor, Istvan

2007-01-01

EEG background activity was investigated by low resolution brain electromagnetic tomography (LORETA) to test the diurnal alterations of brain electrical activity in healthy adults. Fourteen right-handed healthy male postgraduate medical students were examined four times (8 a.m., 2 p.m., 8 p.m. and next day 2 p.m.). LORETA was computed to localize generators of EEG frequency components. Comparing the EEG activity between 2 p.m. and 8 a.m., increased activity was seen (1) in theta band (6.5-8 Hz) in the left prefrontal, bilateral mesial frontal and anterior cingulate cortex; (2) in alpha2 band (10.5-12 Hz) in the bilateral precuneus and posterior parietal cortex as well as in the right temporo-occipital cortex; (3) in beta1-2-3 band (12.5-30 Hz) in the right hippocampus and parieto-occipital cortex, left frontal and bilateral cingulate cortex. Comparing the brain activity between 8 p.m. and 8 a.m., (1) midline theta activity disappeared; (2) increased alpha2 band activity was seen in the left hemisphere (including the left hippocampus); and (3) increased beta bands activity was found over almost the whole cortex (including both of hippocampi) with the exception of left temporo-occipital region. There were no significant changes between the background activities of 2 p.m. and next day 2 p.m. Characteristic distribution of increased activity of cortex (no change in delta band, and massive changes in the upper frequency bands) may mirror increasing activation of reticular formation and thus evoked thalamocortical feedback mechanisms as a sign of maintenance of arousal.

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

PubMed

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

2017-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Source analysis of MEG activities during sleep (abstract)

NASA Astrophysics Data System (ADS)

Ueno, S.; Iramina, K.

1991-04-01

The present study focuses on magnetic fields of the brain activities during sleep, in particular on K-complexes, vertex waves, and sleep spindles in human subjects. We analyzed these waveforms based on both topographic EEG (electroencephalographic) maps and magnetic fields measurements, called MEGs (magnetoencephalograms). The components of magnetic fields perpendicular to the surface of the head were measured using a dc SQUID magnetometer with a second derivative gradiometer. In our computer simulation, the head is assumed to be a homogeneous spherical volume conductor, with electric sources of brain activity modeled as current dipoles. Comparison of computer simulations with the measured data, particularly the MEG, suggests that the source of K-complexes can be modeled by two current dipoles. A source for the vertex wave is modeled by a single current dipole which orients along the body axis out of the head. By again measuring the simultaneous MEG and EEG signals, it is possible to uniquely determine the orientation of this dipole, particularly when it is tilted slightly off-axis. In sleep stage 2, fast waves of magnetic fields consistently appeared, but EEG spindles appeared intermittently. The results suggest that there exist sources which are undetectable by electrical measurement but are detectable by magnetic-field measurement. Such source can be described by a pair of opposing dipoles of which directions are oppositely oriented.

Different quantitative EEG alterations induced by TBI among patients with different APOE genotypes.

PubMed

Jiang, Li; Yin, Xiaohong; Yin, Cheng; Zhou, Shuai; Dan, Wei; Sun, Xiaochuan

2011-11-14

Although several studies have revealed the EEG alterations in AD and TBI patients, the influence of APOE (apolipoprotein E) genotype in EEG at the early stage of TBI has not been reported yet. We have previously studied EEG alterations caused by TBI among different APOE genotype carriers. In this study, we firstly investigated the relationship between APOE polymorphisms and quantitative EEG (QEEG) changes after TBI. A total of 118 consecutive TBI patients with a Glasgow Coma Scale (GCS) of 9 or higher were recruited, and 40 normal adults were also included as a control group. APOE genotype was determined by PCR-RFLP for each subject, and QEEG recordings were performed in rest, relaxed, awake and with eyes closed in normal subjects and TBI patients during 1-3 days after TBI. In the normal control group, both APOEɛ4 carriers and non-carriers had normal EEG, and no significant difference of QEEG data was found between APOEɛ4 carriers and non-carriers. But in the TBI group, APOEɛ4 carriers had more focal or global irregular slow wave activities than APOEɛ4 non-carriers. APOE gene did not influence brain electrical activity under normal conditions, but TBI can induce different alterations among different APOE gene carriers, and APOEɛ4 allele enhances the EEG abnormalities at the early stage of TBI. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Regularized two-step brain activity reconstruction from spatiotemporal EEG data

NASA Astrophysics Data System (ADS)

Alecu, Teodor I.; Voloshynovskiy, Sviatoslav; Pun, Thierry

2004-10-01

We are aiming at using EEG source localization in the framework of a Brain Computer Interface project. We propose here a new reconstruction procedure, targeting source (or equivalently mental task) differentiation. EEG data can be thought of as a collection of time continuous streams from sparse locations. The measured electric potential on one electrode is the result of the superposition of synchronized synaptic activity from sources in all the brain volume. Consequently, the EEG inverse problem is a highly underdetermined (and ill-posed) problem. Moreover, each source contribution is linear with respect to its amplitude but non-linear with respect to its localization and orientation. In order to overcome these drawbacks we propose a novel two-step inversion procedure. The solution is based on a double scale division of the solution space. The first step uses a coarse discretization and has the sole purpose of globally identifying the active regions, via a sparse approximation algorithm. The second step is applied only on the retained regions and makes use of a fine discretization of the space, aiming at detailing the brain activity. The local configuration of sources is recovered using an iterative stochastic estimator with adaptive joint minimum energy and directional consistency constraints.

Modulation of the COMT Val(158)Met polymorphism on resting-state EEG power.

PubMed

Solís-Ortiz, Silvia; Pérez-Luque, Elva; Gutiérrez-Muñoz, Mayra

2015-01-01

The catechol-O-methyltransferase (COMT) Val(158)Met polymorphism impacts cortical dopamine (DA) levels and may influence cortical electrical activity in the human brain. This study investigated whether COMT genotype influences resting-state electroencephalogram (EEG) power in the frontal, parietal and midline regions in healthy volunteers. EEG recordings were conducted in the resting-state in 13 postmenopausal healthy woman carriers of the Val/Val genotype and 11 with the Met/Met genotype. The resting EEG spectral absolute power in the frontal (F3, F4, F7, F8, FC3 and FC4), parietal (CP3, CP4, P3 and P4) and midline (Fz, FCz, Cz, CPz, Pz and Oz) was analyzed during the eyes-open and eyes-closed conditions. The frequency bands considered were the delta, theta, alpha1, alpha2, beta1 and beta2. EEG data of the Val/Val and Met/Met genotypes, brain regions and conditions were analyzed using a general linear model analysis. In the individuals with the Met/Met genotype, delta activity was increased in the eyes-closed condition, theta activity was increased in the eyes-closed and in the eyes-open conditions, and alpha1 band, alpha2 band and beta1band activity was increased in the eyes-closed condition. A significant interaction between COMT genotypes and spectral bands was observed. Met homozygote individuals exhibited more delta, theta and beta1 activity than individuals with the Val/Val genotype. No significant interaction between COMT genotypes and the resting-state EEG regional power and conditions were observed for the three brain regions studied. Our findings indicate that the COMT Val(158)Met polymorphism does not directly impact resting-state EEG regional power, but instead suggest that COMT genotype can modulate resting-state EEG spectral power in postmenopausal healthy women.

Modulation of the COMT Val158Met polymorphism on resting-state EEG power

PubMed Central

Solís-Ortiz, Silvia; Pérez-Luque, Elva; Gutiérrez-Muñoz, Mayra

2015-01-01

The catechol-O-methyltransferase (COMT) Val158Met polymorphism impacts cortical dopamine (DA) levels and may influence cortical electrical activity in the human brain. This study investigated whether COMT genotype influences resting-state electroencephalogram (EEG) power in the frontal, parietal and midline regions in healthy volunteers. EEG recordings were conducted in the resting-state in 13 postmenopausal healthy woman carriers of the Val/Val genotype and 11 with the Met/Met genotype. The resting EEG spectral absolute power in the frontal (F3, F4, F7, F8, FC3 and FC4), parietal (CP3, CP4, P3 and P4) and midline (Fz, FCz, Cz, CPz, Pz and Oz) was analyzed during the eyes-open and eyes-closed conditions. The frequency bands considered were the delta, theta, alpha1, alpha2, beta1 and beta2. EEG data of the Val/Val and Met/Met genotypes, brain regions and conditions were analyzed using a general linear model analysis. In the individuals with the Met/Met genotype, delta activity was increased in the eyes-closed condition, theta activity was increased in the eyes-closed and in the eyes-open conditions, and alpha1 band, alpha2 band and beta1band activity was increased in the eyes-closed condition. A significant interaction between COMT genotypes and spectral bands was observed. Met homozygote individuals exhibited more delta, theta and beta1 activity than individuals with the Val/Val genotype. No significant interaction between COMT genotypes and the resting-state EEG regional power and conditions were observed for the three brain regions studied. Our findings indicate that the COMT Val158Met polymorphism does not directly impact resting-state EEG regional power, but instead suggest that COMT genotype can modulate resting-state EEG spectral power in postmenopausal healthy women. PMID:25883560

Electroencephalography as a Tool for Assessment of Brain Ischemic Alterations after Open Heart Operations

PubMed Central

Golukhova, Elena Z.; Polunina, Anna G.; Lefterova, Natalia P.; Begachev, Alexey V.

2011-01-01

Cardiac surgery is commonly associated with brain ischemia. Few studies addressed brain electric activity changes after on-pump operations. Eyes closed EEG was performed in 22 patients (mean age: 45.2 ± 11.2) before and two weeks after valve replacement. Spouses of patients were invited to participate as controls. Generalized increase of beta power most prominent in beta-1 band was an unambiguous pathological sign of postoperative cortex dysfunction, probably, manifesting due to gamma-activity slowing (“beta buzz” symptom). Generalized postoperative increase of delta-1 mean frequency along with increase of slow-wave activity in right posterior region may be hypothesized to be a consequence of intraoperative ischemia as well. At the same time, significant changes of alpha activity were observed in both patient and control groups, and, therefore, may be considered as physiological. Unexpectedly, controls showed prominent increase of electric activity in left temporal region whereas patients were deficient in left hemisphere activity in comparison with controls at postoperative followup. Further research is needed in order to determine the true neurological meaning of the EEG findings after on-pump operations. PMID:21776370

Frontal brain electrical activity (EEG) and heart rate in response to affective infant-directed (ID) speech in 9-month-old infants.

PubMed

Santesso, Diane L; Schmidt, Louis A; Trainor, Laurel J

2007-10-01

Many studies have shown that infants prefer infant-directed (ID) speech to adult-directed (AD) speech. ID speech functions to aid language learning, obtain and/or maintain an infant's attention, and create emotional communication between the infant and caregiver. We examined psychophysiological responses to ID speech that varied in affective content (i.e., love/comfort, surprise, fear) in a group of typically developing 9-month-old infants. Regional EEG and heart rate were collected continuously during stimulus presentation. We found the pattern of overall frontal EEG power was linearly related to affective intensity of the ID speech, such that EEG power was greatest in response to fear, than surprise than love/comfort; this linear pattern was specific to the frontal region. We also noted that heart rate decelerated to ID speech independent of affective content. As well, infants who were reported by their mothers as temperamentally distressed tended to exhibit greater relative right frontal EEG activity during baseline and in response to affective ID speech, consistent with previous work with visual stimuli and extending it to the auditory modality. Findings are discussed in terms of how increases in frontal EEG power in response to different affective intensity may reflect the cognitive aspects of emotional processing across sensory domains in infancy.

Intermittency in electric brain activity in the perception of ambiguous images

NASA Astrophysics Data System (ADS)

Kurovskaya, Maria K.; Runnova, Anastasiya E.; Zhuravlev, Maxim O.; Grubov, Vadim V.; Koronovskii, Alexey A.; Pavlov, Alexey N.; Pisarchik, Alexander N.

2017-04-01

Present paper is devoted to the study of intermittency during the perception of bistable Necker cube image being a good example of an ambiguous object, with simultaneous measurement of EEG. Distributions of time interval lengths corresponding to the left-oriented and right-oriented cube perception have been obtain. EEG data have been analyzed using continuous wavelet transform and it was shown that the destruction of alpha rhythm with accompanying generation of high frequency oscillations can serve as a marker of Necker cube recognition process.

Classification of epileptiform and wicket spike of EEG pattern using backpropagation neural network

NASA Astrophysics Data System (ADS)

Puspita, Juni Wijayanti; Jaya, Agus Indra; Gunadharma, Suryani

2017-03-01

Epilepsy is characterized by recurrent seizures that is resulted by permanent brain abnormalities. One of tools to support the diagnosis of epilepsy is Electroencephalograph (EEG), which describes the recording of brain electrical activity. Abnormal EEG patterns in epilepsy patients consist of Spike and Sharp waves. While both waves, there is a normal pattern that sometimes misinterpreted as epileptiform by electroenchepalographer (EEGer), namely Wicket Spike. The main difference of the three waves are on the time duration that related to the frequency. In this study, we proposed a method to classify a EEG wave into Sharp wave, Spike wave or Wicket spike group using Backpropagation Neural Network based on the frequency and amplitude of each wave. The results show that the proposed method can classifies the three group of waves with good accuracy.

Dynamics of large-scale brain activity in normal arousal states and epileptic seizures

NASA Astrophysics Data System (ADS)

Robinson, P. A.; Rennie, C. J.; Rowe, D. L.

2002-04-01

Links between electroencephalograms (EEGs) and underlying aspects of neurophysiology and anatomy are poorly understood. Here a nonlinear continuum model of large-scale brain electrical activity is used to analyze arousal states and their stability and nonlinear dynamics for physiologically realistic parameters. A simple ordered arousal sequence in a reduced parameter space is inferred and found to be consistent with experimentally determined parameters of waking states. Instabilities arise at spectral peaks of the major clinically observed EEG rhythms-mainly slow wave, delta, theta, alpha, and sleep spindle-with each instability zone lying near its most common experimental precursor arousal states in the reduced space. Theta, alpha, and spindle instabilities evolve toward low-dimensional nonlinear limit cycles that correspond closely to EEGs of petit mal seizures for theta instability, and grand mal seizures for the other types. Nonlinear stimulus-induced entrainment and seizures are also seen, EEG spectra and potentials evoked by stimuli are reproduced, and numerous other points of experimental agreement are found. Inverse modeling enables physiological parameters underlying observed EEGs to be determined by a new, noninvasive route. This model thus provides a single, powerful framework for quantitative understanding of a wide variety of brain phenomena.

Landau-Kleffner Syndrome, Electrical Status Epilepticus in Slow Wave Sleep, and Language Regression in Children

ERIC Educational Resources Information Center

McVicar, Kathryn A.; Shinnar, Shlomo

2004-01-01

The Landau-Kleffner syndrome (LKS) and electrical status epilepticus in slow wave sleep (ESES) are rare childhood-onset epileptic encephalopathies in which loss of language skills occurs in the context of an epileptiform EEG activated in sleep. Although in LKS the loss of function is limited to language, in ESES there is a wider spectrum of…

Reduction of EEG Theta Power and Changes in Motor Activity in Rats Treated with Ceftriaxone

PubMed Central

Bellesi, Michele; Vyazovskiy, Vladyslav V.; Tononi, Giulio; Cirelli, Chiara; Conti, Fiorenzo

2012-01-01

The glutamate transporter GLT-1 is responsible for the largest proportion of total glutamate transport. Recently, it has been demonstrated that ceftriaxone (CEF) robustly increases GLT-1 expression. In addition, physiological studies have shown that GLT-1 up-regulation strongly affects synaptic plasticity, and leads to an impairment of the prepulse inhibition, a simple form of information processing, thus suggesting that GLT-1 over-expression may lead to dysfunctions of large populations of neurons. To test this possibility, we assessed whether CEF affects cortical electrical activity by using chronic electroencephalographic (EEG) recordings in male WKY rats. Spectral analysis showed that 8 days of CEF treatment resulted in a delayed reduction in EEG theta power (7–9 Hz) in both frontal and parietal derivations. This decrease peaked at day 10, i.e., 2 days after the end of treatment, and disappeared by day 16. In addition, we found that the same CEF treatment increased motor activity, especially when EEG changes are more prominent. Taken together, these data indicate that GLT-1 up-regulation, by modulating glutamatergic transmission, impairs the activity of widespread neural circuits. In addition, the increased motor activity and prepulse inhibition alterations previously described suggest that neural circuits involved in sensorimotor control are particularly sensitive to GLT-1 up-regulation. PMID:22479544

Reduction of EEG theta power and changes in motor activity in rats treated with ceftriaxone.

PubMed

Bellesi, Michele; Vyazovskiy, Vladyslav V; Tononi, Giulio; Cirelli, Chiara; Conti, Fiorenzo

2012-01-01

The glutamate transporter GLT-1 is responsible for the largest proportion of total glutamate transport. Recently, it has been demonstrated that ceftriaxone (CEF) robustly increases GLT-1 expression. In addition, physiological studies have shown that GLT-1 up-regulation strongly affects synaptic plasticity, and leads to an impairment of the prepulse inhibition, a simple form of information processing, thus suggesting that GLT-1 over-expression may lead to dysfunctions of large populations of neurons. To test this possibility, we assessed whether CEF affects cortical electrical activity by using chronic electroencephalographic (EEG) recordings in male WKY rats. Spectral analysis showed that 8 days of CEF treatment resulted in a delayed reduction in EEG theta power (7-9 Hz) in both frontal and parietal derivations. This decrease peaked at day 10, i.e., 2 days after the end of treatment, and disappeared by day 16. In addition, we found that the same CEF treatment increased motor activity, especially when EEG changes are more prominent. Taken together, these data indicate that GLT-1 up-regulation, by modulating glutamatergic transmission, impairs the activity of widespread neural circuits. In addition, the increased motor activity and prepulse inhibition alterations previously described suggest that neural circuits involved in sensorimotor control are particularly sensitive to GLT-1 up-regulation.

[EEG correlates of geno-phenotypical features of the brain development in children of the native and newcomers' population of the Russian North-East].

PubMed

Soroko, S I; Bekshaev, S S; Rozhkov, V P

2012-01-01

Traditional and original methods of EEG analysis were used to study the brain electrical activity maturation in 156 children and adolescents from 7 to 17 years old who represented the native (Koryaks and Evenks) and newcomers' populations living in severe climatic and geographic conditions of the Russian North-East. New data revealing age-, sex- and ethnic-related features in quantitative EEG parameters are presented. Markers are obtained that characterize alterations in the structure of interaction between different EEG rhythms. The results demonstrate age-dependent transformation of this structure separated in time for both different cortical areas and different EEG frequency bands. These alterations show time lag from 2 to 3 years in children of native population compared to the newcomers. The revealed differences are assumed to reflect geno-phenotypical features of morpho-functional CNS development in children of the native and newcomers' population that depend on strong adaptation tension for extreme environmental conditions.

Seizures and electroencephalography findings in 61 patients with fetal alcohol spectrum disorders.

PubMed

Boronat, S; Vicente, M; Lainez, E; Sánchez-Montañez, A; Vázquez, E; Mangado, L; Martínez-Ribot, L; Del Campo, M

2017-01-01

Fetal alcohol spectrum disorders (FASD) cause neurodevelopmental abnormalities. However, publications about epilepsy and electroencephalographic features are scarce. In this study, we prospectively performed electroencephalography (EEG) and brain magnetic resonance (MR) imaging in 61 patients with diagnosis of FASD. One patient had multiple febrile seizures with normal EEGs. Fourteen children showed EEG anomalies, including slow background activity and interictal epileptiform discharges, focal and/or generalized, and 3 of them had epilepsy. In one patient, seizures were first detected during the EEG recording and one case had an encephalopathy with electrical status epilepticus during slow sleep (ESES). Focal interictal discharges in our patients did not imply the presence of underlying visible focal brain lesions in the neuroimaging studies, such as cortical dysplasia or polymicrogyria. However, they had nonspecific brain MR abnormalities, including corpus callosum hypoplasia, vermis hypoplasia or cavum septum pellucidum. The latter was significantly more frequent in the group with EEG abnormal findings (p < 0.01). Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Heart rate calculation from ensemble brain wave using wavelet and Teager-Kaiser energy operator.

PubMed

Srinivasan, Jayaraman; Adithya, V

2015-01-01

Electroencephalogram (EEG) signal artifacts are caused by various factors, such as, Electro-oculogram (EOG), Electromyogram (EMG), Electrocardiogram (ECG), movement artifact and line interference. The relatively high electrical energy cardiac activity causes EEG artifacts. In EEG signal processing the general approach is to remove the ECG signal. In this paper, we introduce an automated method to extract the ECG signal from EEG using wavelet and Teager-Kaiser energy operator for R-peak enhancement and detection. From the detected R-peaks the heart rate (HR) is calculated for clinical diagnosis. To check the efficiency of our method, we compare the HR calculated from ECG signal recorded in synchronous with EEG. The proposed method yields a mean error of 1.4% for the heart rate and 1.7% for mean R-R interval. The result illustrates that, proposed method can be used for ECG extraction from single channel EEG and used in clinical diagnosis like estimation for stress analysis, fatigue, and sleep stages classification studies as a multi-model system. In addition, this method eliminates the dependence of additional synchronous ECG in extraction of ECG from EEG signal process.

Beyond Epilepsy: How Can Quantitative Electroencephalography Improve Conventional Electroencephalography Findings? A Systematic Review of Comparative EEG Studies.

PubMed

Martins, Cassio Henrique Taques; Assunção, Catarina De Marchi

2018-01-01

It is a fundamental element in both research and clinical applications of electroencephalography to know the frequency composition of brain electrical activity. The quantitative analysis of brain electrical activity uses computer resources to evaluate the electroencephalography and allows quantification of the data. The contribution of the quantitative perspective is unique, since conventional electroencephalography based on the visual examination of the tracing is not as objective. A systematic review was performed on the MEDLINE database in October 2017. The authors independently analyzed the studies, by title and abstract, and selected articles that met the inclusion criteria: comparative studies, not older than 30 years, that compared the use of conventional electroencephalogram (EEG) with the use of quantitative electroencephalogram (QEEG) in the English language. One hundred twelve articles were automatically selected by the MEDLINE search engine, but only six met the above criteria. The review found that given a 95% confidence interval, QEEG had no statistically higher sensitivity than EEG in four of the six studies reviewed. However, these results must be viewed with appropriate caution, particularly as groups in between studies were not matched on important variables such as gender, age, type of illness, recovery stage, and treatment. The authors' findings in this systematic review are suggestive of the importance of QEEG as an auxiliary tool to traditional EEG, and as such, justifying further refinement, standardization, and eventually the future execution of a head-to-head prospective study on comparing the two methods.

EEG during pedaling: Evidence for cortical control of locomotor tasks

PubMed Central

Jain, Sanket; Gourab, Krishnaj; Schindler-Ivens, Sheila; Schmit, Brian D.

2014-01-01

Objective This study characterized the brain electrical activity during pedaling, a locomotor-like task, in humans. We postulated that phasic brain activity would be associated with active pedaling, consistent with a cortical role in locomotor tasks. Methods Sixty four channels of electroencephalogram (EEG) and 10 channels of electromyogram (EMG) data were recorded from 10 neurologically-intact volunteers while they performed active and passive (no effort) pedaling on a custom-designed stationary bicycle. Ensemble averaged waveforms, 2 dimensional topographic maps and amplitude of the β (13–35 Hz) frequency band were analyzed and compared between active and passive trials. Results The peak-to-peak amplitude (peak positive–peak negative) of the EEG waveform recorded at the Cz electrode was higher in the passive than the active trials (p < 0.01). β-band oscillations in electrodes overlying the leg representation area of the cortex were significantly desynchronized during active compared to the passive pedaling (p < 0.01). A significant negative correlation was observed between the average EEG waveform for active trials and the composite EMG (summated EMG from both limbs for each muscle) of the rectus femoris (r = −0.77, p < 0.01) the medial hamstrings (r = −0.85, p < 0.01) and the tibialis anterior (r = −0.70, p < 0.01) muscles. Conclusions These results demonstrated that substantial sensorimotor processing occurs in the brain during pedaling in humans. Further, cortical activity seemed to be greatest during recruitment of the muscles critical for transitioning the legs from flexion to extension and vice versa. Significance This is the first study demonstrating the feasibility of EEG recording during pedaling, and owing to similarities between pedaling and bipedal walking, may provide valuable insight into brain activity during locomotion in humans. PMID:23036179

Recognition and classification of oscillatory patterns of electric brain activity using artificial neural network approach

NASA Astrophysics Data System (ADS)

Pchelintseva, Svetlana V.; Runnova, Anastasia E.; Musatov, Vyacheslav Yu.; Hramov, Alexander E.

2017-03-01

In the paper we study the problem of recognition type of the observed object, depending on the generated pattern and the registered EEG data. EEG recorded at the time of displaying cube Necker characterizes appropriate state of brain activity. As an image we use bistable image Necker cube. Subject selects the type of cube and interpret it either as aleft cube or as the right cube. To solve the problem of recognition, we use artificial neural networks. In our paper to create a classifier we have considered a multilayer perceptron. We examine the structure of the artificial neural network and define cubes recognition accuracy.

Stretchable Conductive Elastomers for Soldier Biosensing Applications: Final Report

DTIC Science & Technology

2016-03-01

public release; distribution is unlimited. 7 the electrical impedance tunability that we required. Representative data for resistance versus volume...Technology Directorate’s (VTD) electric field mediated morphing wing research effort. Fig. 5 Resistance values of EEG electrodes as a function of...extend the resistance range of the developed polymer EEG electrodes to potentially provide insight into defining an optimum electrical performance for

Analysis of electrical and magnetic bio-signals associated with motor performance and fatigue

NASA Astrophysics Data System (ADS)

Yao, Bing

This dissertation reports findings centered principally on comprehensive research related to human bio-signals (EEG, MEG, EMG and fMRI) acquired during repetitive maximal voluntary contractions (MVC) that induced severe fatigue. Fatigue is a common experience that reduces productivity and quality of life and increases chances of injury. Although abundant information has been gained in the last several decades regarding muscular and spinal-level mechanisms of muscle fatigue, very little is known about how cortical centers control and respond to fatigue. The main purpose of this study was to examine the fatigue effects on the central nervous system by analyzing the bio-signals collected in the designed experiments. Healthy human subjects were asked to perform a series of repetitive handgrip MVCs with their dominant hand until exhaustion. Handgrip forces, electrical activity (EMG) from primary and non-primary muscles, and EEG, MEG, or fMRI signals from different locations of the brain were recorded simultaneously. The time series data were segmented into several physiologically meaningful epochs (time phases), from rest to preparation to movement execution/sustaining. A series of studies, including motor-related cortical potential (MRCP) analysis, power spectrum analysis, time-frequency (spectrogram) analysis of EEG, EEG source localization and nonlinear analysis (fractal dimension and largest Lyapunov exponent), and fMRI analysis, was applied to the data. We hypothesized that the fatigue effects would act differently on brain signals of different phases. The MRCP results showed that the negative potential (NP) related to motor task preparation only had minimal changes with fatigue. The power of all EEG frequencies did not alter significantly during the preparation phase but decreased significantly during the sustained phase of the contraction. The fractal dimension and the largest Lyapunov exponent decreased significantly during the sustained phase as fatigue progressed. On the other hand, the fMRI results only exhibited insignificant fatigue-related reductions of brain activation volume and no significant change of dipole strength derived from multi-channel EEG data. These results have been interpreted by a hypothetical neurophysiological model, in which two groups of cortical neurons (phasic and tonic) are preferentially activated in each physiological phase of the voluntary motor action.

Automatic Identification of Artifact-Related Independent Components for Artifact Removal in EEG Recordings.

PubMed

Zou, Yuan; Nathan, Viswam; Jafari, Roozbeh

2016-01-01

Electroencephalography (EEG) is the recording of electrical activity produced by the firing of neurons within the brain. These activities can be decoded by signal processing techniques. However, EEG recordings are always contaminated with artifacts which hinder the decoding process. Therefore, identifying and removing artifacts is an important step. Researchers often clean EEG recordings with assistance from independent component analysis (ICA), since it can decompose EEG recordings into a number of artifact-related and event-related potential (ERP)-related independent components. However, existing ICA-based artifact identification strategies mostly restrict themselves to a subset of artifacts, e.g., identifying eye movement artifacts only, and have not been shown to reliably identify artifacts caused by nonbiological origins like high-impedance electrodes. In this paper, we propose an automatic algorithm for the identification of general artifacts. The proposed algorithm consists of two parts: 1) an event-related feature-based clustering algorithm used to identify artifacts which have physiological origins; and 2) the electrode-scalp impedance information employed for identifying nonbiological artifacts. The results on EEG data collected from ten subjects show that our algorithm can effectively detect, separate, and remove both physiological and nonbiological artifacts. Qualitative evaluation of the reconstructed EEG signals demonstrates that our proposed method can effectively enhance the signal quality, especially the quality of ERPs, even for those that barely display ERPs in the raw EEG. The performance results also show that our proposed method can effectively identify artifacts and subsequently enhance the classification accuracies compared to four commonly used automatic artifact removal methods.

Automatic Identification of Artifact-related Independent Components for Artifact Removal in EEG Recordings

PubMed Central

Zou, Yuan; Nathan, Viswam; Jafari, Roozbeh

2017-01-01

Electroencephalography (EEG) is the recording of electrical activity produced by the firing of neurons within the brain. These activities can be decoded by signal processing techniques. However, EEG recordings are always contaminated with artifacts which hinder the decoding process. Therefore, identifying and removing artifacts is an important step. Researchers often clean EEG recordings with assistance from Independent Component Analysis (ICA), since it can decompose EEG recordings into a number of artifact-related and event related potential (ERP)-related independent components (ICs). However, existing ICA-based artifact identification strategies mostly restrict themselves to a subset of artifacts, e.g. identifying eye movement artifacts only, and have not been shown to reliably identify artifacts caused by non-biological origins like high-impedance electrodes. In this paper, we propose an automatic algorithm for the identification of general artifacts. The proposed algorithm consists of two parts: 1) an event-related feature based clustering algorithm used to identify artifacts which have physiological origins and 2) the electrode-scalp impedance information employed for identifying non-biological artifacts. The results on EEG data collected from 10 subjects show that our algorithm can effectively detect, separate, and remove both physiological and non-biological artifacts. Qualitative evaluation of the reconstructed EEG signals demonstrates that our proposed method can effectively enhance the signal quality, especially the quality of ERPs, even for those that barely display ERPs in the raw EEG. The performance results also show that our proposed method can effectively identify artifacts and subsequently enhance the classification accuracies compared to four commonly used automatic artifact removal methods. PMID:25415992

CORRELATION INDICES OF CEREBRAL HEMODYNAMICS AND ELECTRICAL ACTIVITY IN CHILDREN WITH IMPAIRED MOTOR SKILLS.

PubMed

Golovchenko, I V; Hayday, M I

The correlations between the indicators of cerebral hemodynamics and electrical activity in children with impaired motor skills of central origin (children with cerebral palsy) were investigated. There is established a high number of links between indicators of rheoencephalogram (REG) and electroencephalogram (EEG) in the left cerebral hemisphere than in the right. In frontomastoidal allocation 19 correlations and in occipitomastoidal - 59 links. We suppose that poor circulation in vertebroplasty-basilar system leads to the defeat of the brain stem, which, with afferent pathways of the reticular formation, connects the thalamus with the cortex. In the reticular formation there is an inhibition of ascending activators influences, which eland to decreasing of the cortex is tonus. You can talk about the functional immaturity of the system of nonspecific activation by the reticular formation of the brain stem. Children with violation of motor activity had significantly more negative and positive significant and high correlation among the existing indicators of electric brain activity and cerebral hemodynamics, in our opinion, is due to the development of interconnection compensation that is carried out by adjustment of the functional systems and the formation of new forms of adaptive responses in conditions of disontogenetik. Feature correlation pattern of the EEG, of children with disorders of motor activity, is associated with a significantly great number of high and significant correlations between measures of electrical brain activity in the δ- and q- rhythms, especially in the temporal areas of the cerebral cortex. According to visual analysis of EEG there is revealed a common manifestation of changes of bioelectric brain activity in children with disorders of motor activity. This is manifested in the development of paroxysmal activity of action potentials of θ- and δ-rhythms with the focus of activity in the anterior areas of the cerebral cortex; the formation of a mosaic representation of the θ-rhythms in temporal areas; the presence of hypersynchronous a-paroxysms in the posterior areas of the cerebral cortex. The given facts testify to activation of mechanisms of limbic-neocortical systems and synchronizing influences of the reticular formation of the stem and diencephalic structures. There is also detected greater number of correlations when occipitomastoidal registration was lone it reflects compensatory redistribution of cerebral blood flow over the affected structures of brain stem structures that are associated with the provision of cortical functions.

Wearable ear EEG for brain interfacing

NASA Astrophysics Data System (ADS)

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.

Automated Classification and Removal of EEG Artifacts With SVM and Wavelet-ICA.

PubMed

Sai, Chong Yeh; Mokhtar, Norrima; Arof, Hamzah; Cumming, Paul; Iwahashi, Masahiro

2018-05-01

Brain electrical activity recordings by electroencephalography (EEG) are often contaminated with signal artifacts. Procedures for automated removal of EEG artifacts are frequently sought for clinical diagnostics and brain-computer interface applications. In recent years, a combination of independent component analysis (ICA) and discrete wavelet transform has been introduced as standard technique for EEG artifact removal. However, in performing the wavelet-ICA procedure, visual inspection or arbitrary thresholding may be required for identifying artifactual components in the EEG signal. We now propose a novel approach for identifying artifactual components separated by wavelet-ICA using a pretrained support vector machine (SVM). Our method presents a robust and extendable system that enables fully automated identification and removal of artifacts from EEG signals, without applying any arbitrary thresholding. Using test data contaminated by eye blink artifacts, we show that our method performed better in identifying artifactual components than did existing thresholding methods. Furthermore, wavelet-ICA in conjunction with SVM successfully removed target artifacts, while largely retaining the EEG source signals of interest. We propose a set of features including kurtosis, variance, Shannon's entropy, and range of amplitude as training and test data of SVM to identify eye blink artifacts in EEG signals. This combinatorial method is also extendable to accommodate multiple types of artifacts present in multichannel EEG. We envision future research to explore other descriptive features corresponding to other types of artifactual components.

Effets des radiofréquences sur le système nerveux central chez lʼhomme : EEG, sommeil, cognition, vascularisation

NASA Astrophysics Data System (ADS)

Ghosn, Rania; Villégier, Anne-Sophie; Selmaoui, Brahim; Thuróczy, Georges; de Sèze, René

2013-05-01

Most of clinical studies on radiofrequency electromagnetic fields (RF) were directed at mobile phone-related exposures, usually at the level of the head, at their effect on some physiological functions including sleep, brain electrical activity (EEG), cognitive processes, brain vascularisation, and more generally on the cardiovascular and endocrine systems. They were frequently carried out on healthy adults. Effects on the amplitude of EEG alpha waves, mainly during sleep, look reproducible. It would however be important to define more precisely whether and how the absence of electromagnetic disturbance between RF exposure and the recording systems is checked. No consensus arises about cognitive effects. Some effects on cerebral vascularisation need complementary work.

No effects of a single 3G UMTS mobile phone exposure on spontaneous EEG activity, ERP correlates, and automatic deviance detection.

PubMed

Trunk, Attila; Stefanics, Gábor; Zentai, Norbert; Kovács-Bálint, Zsófia; Thuróczy, György; Hernádi, István

2013-01-01

Potential effects of a 30 min exposure to third generation (3G) Universal Mobile Telecommunications System (UMTS) mobile phone-like electromagnetic fields (EMFs) were investigated on human brain electrical activity in two experiments. In the first experiment, spontaneous electroencephalography (sEEG) was analyzed (n = 17); in the second experiment, auditory event-related potentials (ERPs) and automatic deviance detection processes reflected by mismatch negativity (MMN) were investigated in a passive oddball paradigm (n = 26). Both sEEG and ERP experiments followed a double-blind protocol where subjects were exposed to either genuine or sham irradiation in two separate sessions. In both experiments, electroencephalograms (EEG) were recorded at midline electrode sites before and after exposure while subjects were watching a silent documentary. Spectral power of sEEG data was analyzed in the delta, theta, alpha, and beta frequency bands. In the ERP experiment, subjects were presented with a random series of standard (90%) and frequency-deviant (10%) tones in a passive binaural oddball paradigm. The amplitude and latency of the P50, N100, P200, MMN, and P3a components were analyzed. We found no measurable effects of a 30 min 3G mobile phone irradiation on the EEG spectral power in any frequency band studied. Also, we found no significant effects of EMF irradiation on the amplitude and latency of any of the ERP components. In summary, the present results do not support the notion that a 30 min unilateral 3G EMF exposure interferes with human sEEG activity, auditory evoked potentials or automatic deviance detection indexed by MMN. Copyright © 2012 Wiley Periodicals, Inc.

Near infrared spectroscopy based brain-computer interface

NASA Astrophysics Data System (ADS)

Ranganatha, Sitaram; Hoshi, Yoko; Guan, Cuntai

2005-04-01

A brain-computer interface (BCI) provides users with an alternative output channel other than the normal output path of the brain. BCI is being given much attention recently as an alternate mode of communication and control for the disabled, such as patients suffering from Amyotrophic Lateral Sclerosis (ALS) or "locked-in". BCI may also find applications in military, education and entertainment. Most of the existing BCI systems which rely on the brain's electrical activity use scalp EEG signals. The scalp EEG is an inherently noisy and non-linear signal. The signal is detrimentally affected by various artifacts such as the EOG, EMG, ECG and so forth. EEG is cumbersome to use in practice, because of the need for applying conductive gel, and the need for the subject to be immobile. There is an urgent need for a more accessible interface that uses a more direct measure of cognitive function to control an output device. The optical response of Near Infrared Spectroscopy (NIRS) denoting brain activation can be used as an alternative to electrical signals, with the intention of developing a more practical and user-friendly BCI. In this paper, a new method of brain-computer interface (BCI) based on NIRS is proposed. Preliminary results of our experiments towards developing this system are reported.

Infant phantom head circuit board for EEG head phantom and pediatric brain simulation

NASA Astrophysics Data System (ADS)

Almohsen, Safa

The infant's skull differs from an adult skull because of the characteristic features of the human skull during early development. The fontanels and the conductivity of the infant skull influence surface currents, generated by neurons, which underlie electroencephalography (EEG) signals. An electric circuit was built to power a set of simulated neural sources for an infant brain activity simulator. Also, in the simulator, three phantom tissues were created using saline solution plus Agarose gel to mimic the conductivity of each layer in the head [scalp, skull brain]. The conductivity measurement was accomplished by two different techniques: using the four points' measurement technique, and a conductivity meter. Test results showed that the optimized phantom tissues had appropriate conductivities to simulate each tissue layer to fabricate a physical head phantom. In this case, the best results should be achieved by testing the electrical neural circuit with the sample physical model to generate simulated EEG data and use that to solve both the forward and the inverse problems for the purpose of localizing the neural sources in the head phantom.

Integrity of central nervous function in diabetes mellitus assessed by resting state EEG frequency analysis and source localization.

PubMed

Frøkjær, Jens B; Graversen, Carina; Brock, Christina; Khodayari-Rostamabad, Ahmad; Olesen, Søren S; Hansen, Tine M; Søfteland, Eirik; Simrén, Magnus; Drewes, Asbjørn M

2017-02-01

Diabetes mellitus (DM) is associated with structural and functional changes of the central nervous system. We used electroencephalography (EEG) to assess resting state cortical activity and explored associations to relevant clinical features. Multichannel resting state EEG was recorded in 27 healthy controls and 24 patients with longstanding DM and signs of autonomic dysfunction. The power distribution based on wavelet analysis was summarized into frequency bands with corresponding topographic mapping. Source localization analysis was applied to explore the electrical cortical sources underlying the EEG. Compared to controls, DM patients had an overall decreased EEG power in the delta (1-4Hz) and gamma (30-45Hz) bands. Topographic analysis revealed that these changes were confined to the frontal region for the delta band and to central cortical areas for the gamma band. Source localization analysis identified sources with reduced activity in the left postcentral gyrus for the gamma band and in right superior parietal lobule for the alpha1 (8-10Hz) band. DM patients with clinical signs of autonomic dysfunction and gastrointestinal symptoms had evidence of altered resting state cortical processing. This may reflect metabolic, vascular or neuronal changes associated with diabetes. Copyright © 2017 Elsevier Inc. All rights reserved.

Novel non-contact control system of electric bed for medical healthcare.

PubMed

Lo, Chi-Chun; Tsai, Shang-Ho; Lin, Bor-Shyh

2017-03-01

A novel non-contact controller of the electric bed for medical healthcare was proposed in this study. Nowadays, the electric beds are widely used for hospitals and home-care, and the conventional control method of the electric beds usually involves in the manual operation. However, it is more difficult for the disabled and bedridden patients, who might totally depend on others, to operate the conventional electric beds by themselves. Different from the current controlling method, the proposed system provides a new concept of controlling the electric bed via visual stimuli, without manual operation. The disabled patients could operate the electric bed by focusing on the control icons of a visual stimulus tablet in the proposed system. Besides, a wearable and wireless EEG acquisition module was also implemented to monitor the EEG signals of patients. The experimental results showed that the proposed system successfully measured and extracted the EEG features related to visual stimuli, and the disabled patients could operate the adjustable function of the electric bed by themselves to effectively reduce the long-term care burden.

Brain potentials evoked by intraepidermal electrical stimuli reflect the central sensitization of nociceptive pathways

PubMed Central

Lee, M. C.; O'Neill, J.; Dickenson, A. H.; Iannetti, G. D.

2016-01-01

Central sensitization (CS), the increased sensitivity of the central nervous system to somatosensory inputs, accounts for secondary hyperalgesia, a typical sign of several painful clinical conditions. Brain potentials elicited by mechanical punctate stimulation using flat-tip probes can provide neural correlates of CS, but their signal-to-noise ratio is limited by poor synchronization of the afferent nociceptive input. Additionally, mechanical punctate stimulation does not activate nociceptors exclusively. In contrast, low-intensity intraepidermal electrical stimulation (IES) allows selective activation of type II Aδ-mechano-heat nociceptors (II-AMHs) and elicits reproducible brain potentials. However, it is unclear whether hyperalgesia from IES occurs and coexists with secondary mechanical punctate hyperalgesia, and whether the magnitude of the electroencephalographic (EEG) responses evoked by IES within the hyperalgesic area is increased. To address these questions, we explored the modulation of the psychophysical and EEG responses to IES by intraepidermal injection of capsaicin in healthy human subjects. We obtained three main results. First, the intensity of the sensation elicited by IES was significantly increased in participants who developed robust mechanical punctate hyperalgesia after capsaicin injection (i.e., responders), indicating that hyperalgesia from IES coexists with punctate mechanical hyperalgesia. Second, the N2 peak magnitude of the EEG responses elicited by IES was significantly increased after the intraepidermal injection of capsaicin in responders only. Third, a receiver-operator characteristics analysis showed that the N2 peak amplitude is clearly predictive of the presence of CS. These findings suggest that the EEG responses elicited by IES reflect secondary hyperalgesia and therefore represent an objective correlate of CS. PMID:27098022

Double-blind, placebo-controlled, multiple-ascending-dose study on the pharmacodynamics of ABIO-08/01, a new CNS drug with potential anxiolytic activity. 2. EEG-tomography findings based on LORETA (low-resolution brain electromagnetic tomography).

PubMed

Saletu, Bernd; Anderer, Peter; Wolzt, Michael; Nosiska, Dorothea; Assandri, Alessandro; Noseda, Emanuele; Nannipieri, Fabrizio; Saletu-Zyhlarz, Gerda M

2009-01-01

Effects of ABIO-08/01, a new potentially anxiolytic isoxazoline, on regional electrical brain generators were investigated by 3-dimensional EEG tomography. In a double- blind, placebo-controlled, multiple-ascending-dose study, 16 healthy males (30.2 +/- 5.7 years) received 3 oral drug doses (10, 20, 40 mg) and placebo for 7 days (8-day wash-out) in a randomized non-balanced design for phase-1 studies. A 3-min vigilance-controlled (V) EEG, a 4-min resting (R) EEG with eyes closed, a 1-min eyes-open (EO) EEG and psychometric tests were performed 0, 1 and 6 h after taking the drug on days 1 and 5. Low-resolution brain electromagnetic tomography (LORETA) was computed from the spectrally analyzed EEG data, and differences between drug and placebo were displayed as statistical parametric maps. Data were registered to the Talairach-Tournoux Human Brain Atlas available as a digitized MRI. An overall omnibus significance test followed by a voxel-by-voxel t test demonstrated significant regional EEG changes after ABIO-08/01 versus placebo, dependent on recording condition, dose and time. While in the EO-EEG specifically the lowest dose of ABIO-08/01 induced pronounced sedative effects (delta/theta and beta increase) 1 h after acute and slightly less so after superimposed administration, in the 6th hour a decrease in alpha and beta activity signaled less sedative and more relaxant action. In the V-EEG these changes were less pronounced, in the R-EEG partly opposite. Hemisphere-specific changes were observed, suggesting increases in LORETA power over the left temporal, parietal, superior frontal regions and decreases over the right prefrontal, temporal pole and occipital regions. These LORETA changes are discussed in the light of neuroimaging findings on anxiety and anxiolytics. 2009 S. Karger AG, Basel.

A recursive algorithm for the three-dimensional imaging of brain electric activity: Shrinking LORETA-FOCUSS.

PubMed

Liu, Hesheng; Gao, Xiaorong; Schimpf, Paul H; Yang, Fusheng; Gao, Shangkai

2004-10-01

Estimation of intracranial electric activity from the scalp electroencephalogram (EEG) requires a solution to the EEG inverse problem, which is known as an ill-conditioned problem. In order to yield a unique solution, weighted minimum norm least square (MNLS) inverse methods are generally used. This paper proposes a recursive algorithm, termed Shrinking LORETA-FOCUSS, which combines and expands upon the central features of two well-known weighted MNLS methods: LORETA and FOCUSS. This recursive algorithm makes iterative adjustments to the solution space as well as the weighting matrix, thereby dramatically reducing the computation load, and increasing local source resolution. Simulations are conducted on a 3-shell spherical head model registered to the Talairach human brain atlas. A comparative study of four different inverse methods, standard Weighted Minimum Norm, L1-norm, LORETA-FOCUSS and Shrinking LORETA-FOCUSS are presented. The results demonstrate that Shrinking LORETA-FOCUSS is able to reconstruct a three-dimensional source distribution with smaller localization and energy errors compared to the other methods.

Spatio-temporal analysis of brain electrical activity in epilepsy based on cellular nonlinear networks

NASA Astrophysics Data System (ADS)

Gollas, Frank; Tetzlaff, Ronald

2009-05-01

Epilepsy is the most common chronic disorder of the nervous system. Generally, epileptic seizures appear without foregoing sign or warning. The problem of detecting a possible pre-seizure state in epilepsy from EEG signals has been addressed by many authors over the past decades. Different approaches of time series analysis of brain electrical activity already are providing valuable insights into the underlying complex dynamics. But the main goal the identification of an impending epileptic seizure with a sufficient specificity and reliability, has not been achieved up to now. An algorithm for a reliable, automated prediction of epileptic seizures would enable the realization of implantable seizure warning devices, which could provide valuable information to the patient and time/event specific drug delivery or possibly a direct electrical nerve stimulation. Cellular Nonlinear Networks (CNN) are promising candidates for future seizure warning devices. CNN are characterized by local couplings of comparatively simple dynamical systems. With this property these networks are well suited to be realized as highly parallel, analog computer chips. Today available CNN hardware realizations exhibit a processing speed in the range of TeraOps combined with low power consumption. In this contribution new algorithms based on the spatio-temporal dynamics of CNN are considered in order to analyze intracranial EEG signals and thus taking into account mutual dependencies between neighboring regions of the brain. In an identification procedure Reaction-Diffusion CNN (RD-CNN) are determined for short segments of brain electrical activity, by means of a supervised parameter optimization. RD-CNN are deduced from Reaction-Diffusion Systems, which usually are applied to investigate complex phenomena like nonlinear wave propagation or pattern formation. The Local Activity Theory provides a necessary condition for emergent behavior in RD-CNN. In comparison linear spatio-temporal autoregressive filter models are considered, for a prediction of EEG signal values. Thus Signal features values for successive, short, quasi stationary segments of brain electrical activity can be obtained, with the objective of detecting distinct changes prior to impending epileptic seizures. Furthermore long term recordings gained during presurgical diagnostics in temporal lobe epilepsy are analyzed and the predictive performance of the extracted features is evaluated statistically. Therefore a Receiver Operating Characteristic analysis is considered, assessing the distinguishability between distributions of supposed preictal and interictal periods.

Electrical stunning effectiveness with current levels lower than 1 A in lambs and kid goats.

PubMed

Llonch, P; Rodríguez, P; Casal, N; Carreras, R; Muñoz, I; Dalmau, A; Velarde, A

2015-02-01

An experiment with 360 lambs grouped into three Spanish commercial categories, (Pascual, 13-16 kg; Recental, 9-13 kg and Lechal <7 kg carcass weight) and kid goats (7 kg) was performed to assess stunning effectiveness after head-only (HO) and head-to-body (HB) electrical stunning with intensity currents of 0.3, 0.5 and 0.7 Amperes (A) compared to 1.0 A. After stunning, all animals showed tonic-clonic muscular activity and epileptiform EEG, absence of rhythmic breathing, corneal reflex, spontaneous blinking and pain sensibility. The quiescent EEG occurred earlier (P < 0.05) in HB compared to HO in all categories. More animals recovered corneal reflex and rhythmic breathing before onset of the quiescent activity after HO (from 15 to 50%) compared to HB (from 0 to 15%) (P < 0.05). Concluding, HO and HB electrical stunning with 0.3, 0.5 and 0.7 A induce effective stunning similar to 1.0 A in lambs and kid goats. After stunning and sticking, brain failure occurs earlier in HB than HO system. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Robust Current Pattern for the Detection of Intraventricular Hemorrhage in Neonates Using Electrical Impedance Tomography

PubMed Central

Tang, T.; Oh, Sungho; Sadleir, R. J.

2010-01-01

We compared two 16-electrode electrical impedance tomography (EIT) current patterns on their ability to reconstruct and quantify small amounts of bleeding inside a neonatal human head using both simulated and phantom data. The current patterns used were an adjacent injection RING pattern (with electrodes located equidistantly on the equator of a sphere) and an EEG current pattern based on the 10–20 EEG electrode layout. Structures mimicking electrically important structures in the infant skull were included in a spherical numerical forward model and their effects on reconstructions were determined. The EEG pattern was found to be a better topology to localize and quantify anomalies within lateral ventricular regions. The RING electrode pattern could not reconstruct anomaly location well, as it could not distinguish different axial positions. The quantification accuracy of the RING pattern was as good as the EEG pattern in noise-free environments. However, the EEG pattern showed better quantification ability than the RING pattern when noise was added. The performance of the EEG pattern improved further with respect to the RING pattern when a fontanel was included in forward models. Significantly better resolution and contrast of reconstructed anomalies was achieved when generated from a model containing such an opening and 50 dB added noise. The EEG method was further applied to reconstruct data from a realistic neonatal head model. Overall, acceptable reconstructions and quantification results were obtained using this model and the homogeneous spherical forward model. PMID:20238166

Motor learning processes: an electrophysiologic perspective.

PubMed

Velasques, Bruna; Ferreira, Camila; Teixeira, Silmar Silva; Furtado, Vernon; Mendes, Elizabeth; Basile, Luis; Cagy, Mauricio; Piedade, Roberto; Ribeiro, Pedro

2007-12-01

The goal of the present study was to investigate electrophysiologic, qEEG, changes when individuals were exposed to a motor task. Subjects brain electrical activity was analyzed before and after the typewriting training task. For the neurophysiological variable asymmetry, a paired t-test was performed to compare each moment, pre and post-task, in the beta bands. The findings showed a change for the qEEG variable in each scalp site, F3/F4; C3/C4 and P3/P4. These results suggest an adaptation of pre-frontal, sensory-motor and parietal cortex, as a consequence of the typewriting training.

On the Synchronization of EEG Spindle Waves

NASA Astrophysics Data System (ADS)

Long, Wen; Zhang, ChengFu; Zhao, SiLan; Shi, RuiHong

2000-06-01

Based on recently sleeping cellular substrates, a network model synaptically coupled by N three-cell circuits is provided. Simulation results show that: (i) the dynamic behavior of every circuit is chaotic; (ii) the synchronization of the network is incomplete; (iii) the incomplete synchronization can integrate burst firings of cortical cells into waxing-and-wanning EEG spindle waves. These results enlighten us that this kind of incomplete synchronization may integrate microscopic, electrical activities of neurons in billions into macroscopic, functional states in human brain. In addition, the effects of coupling strength, connectional mode and noise to the synchronization are discussed.

[Nootropics and antioxidants in the complex therapy of symptomatic posttraumatic epilepsy].

PubMed

Savenkov, A A; Badalian, O L; Avakian, G N

2013-01-01

To study the possibility of application of nootropics and antioxidants in the complex antiepileptic therapy, we examined 75 patients with symptomatic focal posttraumatic epilepsy. A statistically significant reduction in the number of epileptic seizures, improvement of cognitive function and quality of life of the patients as well as a decrease in the severity of depression and epileptic changes in the EEG were identified. The potentiation of antiepileptic activity of basic drugs, normalization of brain's electrical activity and reduction in EEG epileptiform activity, in particular coherent indicators of slow-wave activity, were noted after treatment with the antioxidant mexidol. A trend towards the improvement of neuropsychological performance and quality of life was observed. There was a lack of seizure aggravation typical of many nootropic drugs. Thus, phenotropil and mexidol can be recommended for complex treatment of symptomatic posttraumatic epilepsy.

Causal Neuro-immune Relationships at Patients with Chronic Pyelonephritis and Cholecystitis. Correlations between Parameters EEG, HRV and White Blood Cell Count.

PubMed

Kul'chyns'kyi, Andriy B; Kyjenko, Valeriy M; Zukow, Walery; Popovych, Igor L

2017-01-01

We aim to analyze in bounds KJ Tracey's immunological homunculus conception the relationships between parameters of electroencephalogram (EEG) and heart rate variability (HRV), on the one hand, and the parameters of bhite blood cell count, on the other hand. In basal conditions in 23 men, patients with chronic pyelonephritis and cholecystitis in remission, recorded EEG ("NeuroCom Standard", KhAI Medica, Ukraine) and HRV ("Cardiolab+VSR", KhAI Medica, Ukraine). In portion of blood counted up white blood cell count. Revealed that canonical correlation between constellation EEG and HRV parameters form with blood level of leukocytes 0.92 (p<10-5), with relative content in white blood cell count stubnuclear neutrophiles 0.93 (p<10-5), segmentonucleary neutrophiles 0.89 (p<10-3), eosinophiles 0.87 (p=0.003), lymphocytes 0.77 (p<10-3) and with monocytes 0.75 (p=0.003). Parameters of white blood cell count significantly modulated by electrical activity some structures of central and autonomic nervous systems.

Benign childhood epilepsy with centro-temporal spikes: quantitative EEG and the Wechsler intelligence scale for children (WISC-III).

PubMed

Tedrus, Gloria M A S; Fonseca, Lineu C; Tonelotto, Josiane M F; Costa, Rebeca M; Chiodi, Marcelo G

2006-07-01

Benign childhood epilepsy with centro-temporal spikes (BECTS) is a form of focal idiopathic epilepsy, with seizure remission by the age of 18. Recent studies have suggested that some children with BECTS can suffer from deficits of memory, attention and learning ability and in auditory-verbal and performance sub-tests. On the other hand, alterations in the baseline brain electrical activity determined by using the quantitative electroencephalogram (qEEG) have been described. The objective of this study was to evaluate the absolute and relative powers in the delta, theta, alpha and beta bands of the qEEG in children with BECTS, and their relation to IQ measurements (WISC-III). Twenty-six 8 to 11-year-old children with BECTS were studied, paired with a control group of healthy children according to age and gender. It was shown that the absolute delta and theta powers were statistically greater in the children with BECTS than in the control group, at almost all the electrodes. In the children with BECTS, a negative correlation (Pearson's correlation test) was observed at various electrodes between the absolute delta and theta powers and the performance IQ. These data indicate a possible relationship between maturational disturbance in the brain electrical activity development and the tendency for inferior cognitive performance in children with BECTS.

Deep learning for hybrid EEG-fNIRS brain-computer interface: application to motor imagery classification.

PubMed

Chiarelli, Antonio Maria; Croce, Pierpaolo; Merla, Arcangelo; Zappasodi, Filippo

2018-06-01

Brain-computer interface (BCI) refers to procedures that link the central nervous system to a device. BCI was historically performed using electroencephalography (EEG). In the last years, encouraging results were obtained by combining EEG with other neuroimaging technologies, such as functional near infrared spectroscopy (fNIRS). A crucial step of BCI is brain state classification from recorded signal features. Deep artificial neural networks (DNNs) recently reached unprecedented complex classification outcomes. These performances were achieved through increased computational power, efficient learning algorithms, valuable activation functions, and restricted or back-fed neurons connections. By expecting significant overall BCI performances, we investigated the capabilities of combining EEG and fNIRS recordings with state-of-the-art deep learning procedures. We performed a guided left and right hand motor imagery task on 15 subjects with a fixed classification response time of 1 s and overall experiment length of 10 min. Left versus right classification accuracy of a DNN in the multi-modal recording modality was estimated and it was compared to standalone EEG and fNIRS and other classifiers. At a group level we obtained significant increase in performance when considering multi-modal recordings and DNN classifier with synergistic effect. BCI performances can be significantly improved by employing multi-modal recordings that provide electrical and hemodynamic brain activity information, in combination with advanced non-linear deep learning classification procedures.

Deep learning for hybrid EEG-fNIRS brain–computer interface: application to motor imagery classification

NASA Astrophysics Data System (ADS)

Chiarelli, Antonio Maria; Croce, Pierpaolo; Merla, Arcangelo; Zappasodi, Filippo

2018-06-01

Objective. Brain–computer interface (BCI) refers to procedures that link the central nervous system to a device. BCI was historically performed using electroencephalography (EEG). In the last years, encouraging results were obtained by combining EEG with other neuroimaging technologies, such as functional near infrared spectroscopy (fNIRS). A crucial step of BCI is brain state classification from recorded signal features. Deep artificial neural networks (DNNs) recently reached unprecedented complex classification outcomes. These performances were achieved through increased computational power, efficient learning algorithms, valuable activation functions, and restricted or back-fed neurons connections. By expecting significant overall BCI performances, we investigated the capabilities of combining EEG and fNIRS recordings with state-of-the-art deep learning procedures. Approach. We performed a guided left and right hand motor imagery task on 15 subjects with a fixed classification response time of 1 s and overall experiment length of 10 min. Left versus right classification accuracy of a DNN in the multi-modal recording modality was estimated and it was compared to standalone EEG and fNIRS and other classifiers. Main results. At a group level we obtained significant increase in performance when considering multi-modal recordings and DNN classifier with synergistic effect. Significance. BCI performances can be significantly improved by employing multi-modal recordings that provide electrical and hemodynamic brain activity information, in combination with advanced non-linear deep learning classification procedures.

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

PubMed

Leite, Jorge; Morales-Quezada, Leon; Carvalho, Sandra; Thibaut, Aurore; Doruk, Deniz; Chen, Chiun-Fan; Schachter, Steven C; Rotenberg, Alexander; Fregni, Felipe

2017-09-01

Conventional transcranial direct current stimulation (tDCS) protocols rely on applying electrical current at a fixed intensity and duration without using surrogate markers to direct the interventions. This has led to some mixed results; especially because tDCS induced effects may vary depending on the ongoing level of brain activity. Therefore, the objective of this preliminary study was to assess the feasibility of an EEG-triggered tDCS system based on EEG online analysis of its frequency bands. Six healthy volunteers were randomized to participate in a double-blind sham-controlled crossover design to receive a single session of 10[Formula: see text]min 2[Formula: see text]mA cathodal and sham tDCS. tDCS trigger controller was based upon an algorithm designed to detect an increase in the relative beta power of more than 200%, accompanied by a decrease of 50% or more in the relative alpha power, based on baseline EEG recordings. EEG-tDCS closed-loop-system was able to detect the predefined EEG magnitude deviation and successfully triggered the stimulation in all participants. This preliminary study represents a proof-of-concept for the development of an EEG-tDCS closed-loop system in humans. We discuss and review here different methods of closed loop system that can be considered and potential clinical applications of such system.

Study of Sedative-Hypnotic Effects of Aloe vera L. Aqueous Extract through Behavioral Evaluations and EEG Recording in Rats

PubMed Central

Abdollahnejad, Fatemeh; Mosaddegh, Mahmoud; Nasoohi, Sanaz; Mirnajafi-Zadeh, Javad; Kamalinejad, Mohammad; Faizi, Mehrdad

2016-01-01

In this study, we investigated the sedative and hypnotic effects of the aqueous extract of Aloe vera on rats. In order to evaluate the overall hypnotic effects of the Aloe vera extract, open field and loss of righting reflex tests were primarily used. The sedative and hypnotic effects of the extract were then confirmed by detection of remarkable raise in the total sleeping time through analysis of electroencephalographic (EEG) recordings of animals. Analysis of the EEG recordings showed that there is concomitant change in Rapid Eye Movement (REM) and None Rapid Eye Movement (NREM) sleep in parallel with the prolonged total sleeping time. Results of the current research show that the extract has sedative-hypnotic effects on both functional and electrical activities of the brain. PMID:27610170

Brain potentials evoked by intraepidermal electrical stimuli reflect the central sensitization of nociceptive pathways.

PubMed

Liang, M; Lee, M C; O'Neill, J; Dickenson, A H; Iannetti, G D

2016-08-01

Central sensitization (CS), the increased sensitivity of the central nervous system to somatosensory inputs, accounts for secondary hyperalgesia, a typical sign of several painful clinical conditions. Brain potentials elicited by mechanical punctate stimulation using flat-tip probes can provide neural correlates of CS, but their signal-to-noise ratio is limited by poor synchronization of the afferent nociceptive input. Additionally, mechanical punctate stimulation does not activate nociceptors exclusively. In contrast, low-intensity intraepidermal electrical stimulation (IES) allows selective activation of type II Aδ-mechano-heat nociceptors (II-AMHs) and elicits reproducible brain potentials. However, it is unclear whether hyperalgesia from IES occurs and coexists with secondary mechanical punctate hyperalgesia, and whether the magnitude of the electroencephalographic (EEG) responses evoked by IES within the hyperalgesic area is increased. To address these questions, we explored the modulation of the psychophysical and EEG responses to IES by intraepidermal injection of capsaicin in healthy human subjects. We obtained three main results. First, the intensity of the sensation elicited by IES was significantly increased in participants who developed robust mechanical punctate hyperalgesia after capsaicin injection (i.e., responders), indicating that hyperalgesia from IES coexists with punctate mechanical hyperalgesia. Second, the N2 peak magnitude of the EEG responses elicited by IES was significantly increased after the intraepidermal injection of capsaicin in responders only. Third, a receiver-operator characteristics analysis showed that the N2 peak amplitude is clearly predictive of the presence of CS. These findings suggest that the EEG responses elicited by IES reflect secondary hyperalgesia and therefore represent an objective correlate of CS. Copyright © 2016 the American Physiological Society.

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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

2017-08-16

Visual spatial attention has been studied in humans with both electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) individually. However, due to the intrinsic limitations of each of these methods used alone, our understanding of the systems-level mechanisms underlying attentional control remains limited. Here, we examined trial-to-trial covariations of concurrently recorded EEG and fMRI in a cued visual spatial attention task in humans, which allowed delineation of both the generators and modulators of the cue-triggered event-related oscillatory brain activity underlying attentional control function. The fMRI activity in visual cortical regions contralateral to the cued direction of attention covaried positively with occipital gamma-band EEG, consistent with activation of cortical regions representing attended locations in space. In contrast, fMRI activity in ipsilateral visual cortical regions covaried inversely with occipital alpha-band oscillations, consistent with attention-related suppression of the irrelevant hemispace. Moreover, the pulvinar nucleus of the thalamus covaried with both of these spatially specific, attention-related, oscillatory EEG modulations. Because the pulvinar's neuroanatomical geometry makes it unlikely to be a direct generator of the scalp-recorded EEG, these covariational patterns appear to reflect the pulvinar's role as a regulatory control structure, sending spatially specific signals to modulate visual cortex excitability proactively. Together, these combined EEG/fMRI results illuminate the dynamically interacting cortical and subcortical processes underlying spatial attention, providing important insight not realizable using either method alone. SIGNIFICANCE STATEMENT Noninvasive recordings of changes in the brain's blood flow using functional magnetic resonance imaging and electrical activity using electroencephalography in humans have individually shown that shifting attention to a location in space produces spatially specific changes in visual cortex activity in anticipation of a stimulus. The mechanisms controlling these attention-related modulations of sensory cortex, however, are poorly understood. Here, we recorded these two complementary measures of brain activity simultaneously and examined their trial-to-trial covariations to gain insight into these attentional control mechanisms. This multi-methodological approach revealed the attention-related coordination of visual cortex modulation by the subcortical pulvinar nucleus of the thalamus while also disentangling the mechanisms underlying the attentional enhancement of relevant stimulus input and those underlying the concurrent suppression of irrelevant input. Copyright © 2017 the authors 0270-6474/17/377803-08$15.00/0.

Electrograms (ECG, EEG, EMG, EOG).

PubMed

Reilly, Richard B; Lee, T Clive

2010-01-01

There is a constant need in medicine to obtain objective measurements of physical and cognitive function as the basis for diagnosis and monitoring of health. The body can be considered as a chemical and electrical system supported by a mechanical structure. Measuring and quantifying such electrical activity provides a means for objective examination of heath status. The term electrogram, from the Greek electro meaning electricity and gram meaning write or record, is the broad definition given to the recording of electrical signal from the body. In order that comparisons of electrical activity can be made against normative data, certain methods and procedures have been defined for different electrograms. This paper reviews these methods and procedures for the more typical electrograms associated with some of the major organs in the body, providing a first point of reference for the reader.

II.3. Electrograms (ECG, EEG, EMG, EOG).

PubMed

Reilly, Richard B; Lee, T Clive

2010-01-01

There is a constant need in medicine to obtain objective measurements of physical and cognitive function as the basis for diagnosis and monitoring of health. The body can be considered as a chemical and electrical system supported by a mechanical structure. Measuring and quantifying such electrical activity provides a means for objective examination of heath status. The term electrogram, from the Greek electro meaning electricity and gram meaning write or record, is the broad definition given to the recording of electrical signal from the body. In order that comparisons of electrical activity can be made against normative data, certain methods and procedures have been defined for different electrograms. This paper reviews these methods and procedures for the more typical electrograms associated with some of the major organs in the body, providing a first point of reference for the reader.

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

PubMed Central

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

2015-01-01

We performed a comparative study to select the efficient mother wavelet (MWT) basis functions that optimally represent the signal characteristics of the electrical activity of the human brain during a working memory (WM) task recorded through electro-encephalography (EEG). Nineteen EEG electrodes were placed on the scalp following the 10–20 system. These electrodes were then grouped into five recording regions corresponding to the scalp area of the cerebral cortex. Sixty-second WM task data were recorded from ten control subjects. Forty-five MWT basis functions from orthogonal families were investigated. These functions included Daubechies (db1–db20), Symlets (sym1–sym20), and Coiflets (coif1–coif5). Using ANOVA, we determined the MWT basis functions with the most significant differences in the ability of the five scalp regions to maximize their cross-correlation with the EEG signals. The best results were obtained using “sym9” across the five scalp regions. Therefore, the most compatible MWT with the EEG signals should be selected to achieve wavelet denoising, decomposition, reconstruction, and sub-band feature extraction. This study provides a reference of the selection of efficient MWT basis functions. PMID:26593918

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

PubMed

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

2015-11-17

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

[Effect of oxysophoridine on electric activities and its power spectrum of reticular formation in rats].

PubMed

Yu, Jianqiang; Li, Yuxiang; Zhao, Chengjun; Gong, Xin; Liu, Jianping; Wang, Feng; Jiang, Yuanxu

2010-05-01

To observe the effect of oxysophoridine (OSR) on the EEG and its power spectrum of reticulum formation in mesencephalon of anaesthetized rat. Utilizing the technique of brain stereotactic apparatus, electrodes were implanted into reticulum formation of mesencephalon. Monopolar lead and computerized FFT technique were employed to record and analyse the index of EEG, power spectrum and frequency distribution in order to study the effect of oxysophoridine on the bioelectricity change of mesencephalon reticulum formation in rats. After administrating(icy) with oxysophoridine at the dose of 2.5,5, 10 mg/rat, the EEG of mesencephalon reticulum formation mainly characterized with low amplitude and slow waves accompanied by spindle-formed sleeping waves with a significant decrease of total power of EEG (P < 0.05) while the ratio of theta, alpha waves increased in total frequency of rats (P < 0.05). Oxysophoridine possesses central inhibitory effects and its inhibitory mechanism may associate with the reduction of bioelectricity in mesencephalon reticulum formation. Mesencephalon reticulum formation may serve as one part of the structure serving as the circuit conducting the central inhibitory effect of oxysophoridine. [Key words] oxysophoridine; reticulum formation; electroencephalogram (EEG) ; rats

QEEG and LORETA in Teenagers With Conduct Disorder and Psychopathic Traits.

PubMed

Calzada-Reyes, Ana; Alvarez-Amador, Alfredo; Galán-García, Lídice; Valdés-Sosa, Mitchell

2017-05-01

Few studies have investigated the impact of the psychopathic traits on the EEG of teenagers with conduct disorder (CD). To date, there is no other research studying low-resolution brain electromagnetic tomography (LORETA) technique using quantitative EEG (QEEG) analysis in adolescents with CD and psychopathic traits. To find electrophysiological differences specifically related to the psychopathic traits. The current investigation compares the QEEG and the current source density measures between adolescents with CD and psychopathic traits and adolescents with CD without psychopathic traits. The resting EEG activity and LORETA for the EEG fast spectral bands were evaluated in 42 teenagers with CD, 25 with and 17 without psychopathic traits according to the Antisocial Process Screening Device. All adolescents were assessed using the DSM-IV-TR criteria. The EEG visual inspection characteristics and the use of frequency domain quantitative analysis techniques (narrow band spectral parameters) are described. QEEG analysis showed a pattern of beta activity excess on the bilateral frontal-temporal regions and decreases of alpha band power on the left central-temporal and right frontal-central-temporal regions in the psychopathic traits group. Current source density calculated at 17.18 Hz showed an increase within fronto-temporo-striatal regions in the psychopathic relative to the nonpsychopathic traits group. These findings indicate that QEEG analysis and techniques of source localization may reveal differences in brain electrical activity among teenagers with CD and psychopathic traits, which was not obvious to visual inspection. Taken together, these results suggest that abnormalities in a fronto-temporo-striatal network play a relevant role in the neurobiological basis of psychopathic behavior.

Electroencephalograph (EEG) study on self-contemplating image formation

NASA Astrophysics Data System (ADS)

Meng, Qinglei; Hong, Elliot; Choa, Fow-Sen

2016-05-01

Electroencephalography (EEG) is one of the most widely used electrophysiological monitoring methods and plays a significant role in studies of human brain electrical activities. Default mode network (DMN), is a functional connection of brain regions that are activated while subjects are not in task positive state or not focused on the outside world. In this study, EEG was used for human brain signals recording while all subjects were asked to sit down quietly on a chair with eyes closed and thinking about some parts of their own body, such as left and right hands, left and right ears, lips, nose, and the images of faces that they were familiar with as well as doing some simple mathematical calculation. The time is marker when the image is formed in the subject's mind. By analyzing brain activity maps 300ms right before the time marked instant for each of the 4 wave bands, Delta, Theta, Alpha and Beta waves. We found that for most EEG datasets during this 300ms, Delta wave activity would mostly locate at the frontal lobe or the visual cortex, and the change and movement of activities are slow. Theta wave activity tended to rotate along the edge of cortex either clockwise or counterclockwise. Beta wave behaved like inquiry types of oscillations between any two regions spread over the cortex. Alpha wave activity looks like a mix of the Theta and Beta activities but more close to Theta activity. From the observation we feel that Beta and high Alpha are playing utility role for information inquiry. Theta and low Alpha are likely playing the role of binding and imagination formation in DMN operations.

Simultaneous recording of eeg and direct current (DC) potential makes it possible to assess functional and metabolic state of nervous tissue.

PubMed

Murik, S E; Shapkin, A G

2004-08-01

It has been proposed to assess functional and metabolic state of the brain nervous tissue in terms of bioelectrical parameters. Simultaneous recording of the DC potential level and total slow electrical activity of the nervous tissue was performed in the object of study by nonpolarizable Ag/AgCl electrodes with a DC amplifier. The functional and metabolic state of the brain was determined in terms of enhancement or reduction in the total slow electrical activity and positive or negative shifts in the DC potential level.

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

PubMed

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.

Combined process automation for large-scale EEG analysis.

PubMed

Sfondouris, John L; Quebedeaux, Tabitha M; Holdgraf, Chris; Musto, Alberto E

2012-01-01

Epileptogenesis is a dynamic process producing increased seizure susceptibility. Electroencephalography (EEG) data provides information critical in understanding the evolution of epileptiform changes throughout epileptic foci. We designed an algorithm to facilitate efficient large-scale EEG analysis via linked automation of multiple data processing steps. Using EEG recordings obtained from electrical stimulation studies, the following steps of EEG analysis were automated: (1) alignment and isolation of pre- and post-stimulation intervals, (2) generation of user-defined band frequency waveforms, (3) spike-sorting, (4) quantification of spike and burst data and (5) power spectral density analysis. This algorithm allows for quicker, more efficient EEG analysis. Copyright © 2011 Elsevier Ltd. All rights reserved.

Toward Automated Cochlear Implant Fitting Procedures Based on Event-Related Potentials.

PubMed

Finke, Mareike; Billinger, Martin; Büchner, Andreas

Cochlear implants (CIs) restore hearing to the profoundly deaf by direct electrical stimulation of the auditory nerve. To provide an optimal electrical stimulation pattern the CI must be individually fitted to each CI user. To date, CI fitting is primarily based on subjective feedback from the user. However, not all CI users are able to provide such feedback, for example, small children. This study explores the possibility of using the electroencephalogram (EEG) to objectively determine if CI users are able to hear differences in tones presented to them, which has potential applications in CI fitting or closed loop systems. Deviant and standard stimuli were presented to 12 CI users in an active auditory oddball paradigm. The EEG was recorded in two sessions and classification of the EEG data was performed with shrinkage linear discriminant analysis. Also, the impact of CI artifact removal on classification performance and the possibility to reuse a trained classifier in future sessions were evaluated. Overall, classification performance was above chance level for all participants although performance varied considerably between participants. Also, artifacts were successfully removed from the EEG without impairing classification performance. Finally, reuse of the classifier causes only a small loss in classification performance. Our data provide first evidence that EEG can be automatically classified on single-trial basis in CI users. Despite the slightly poorer classification performance over sessions, classifier and CI artifact correction appear stable over successive sessions. Thus, classifier and artifact correction weights can be reused without repeating the set-up procedure in every session, which makes the technique easier applicable. With our present data, we can show successful classification of event-related cortical potential patterns in CI users. In the future, this has the potential to objectify and automate parts of CI fitting procedures.

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

PubMed Central

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

2013-01-01

Background. Auditory event-related potentials (ERPs) have proved useful in investigating the role of auditory processing in cognitive disorders such as developmental dyslexia, specific language impairment (SLI), attention deficit hyperactivity disorder (ADHD), schizophrenia, and autism. However, laboratory recordings of auditory ERPs can be lengthy, uncomfortable, or threatening for some participants – particularly children. Recently, a commercial gaming electroencephalography (EEG) system has been developed that is portable, inexpensive, and easy to set up. In this study we tested if auditory ERPs measured using a gaming EEG system (Emotiv EPOC®, www.emotiv.com) were equivalent to those measured by a widely-used, laboratory-based, research EEG system (Neuroscan). Methods. We simultaneously recorded EEGs with the research and gaming EEG systems, whilst presenting 21 adults with 566 standard (1000 Hz) and 100 deviant (1200 Hz) tones under passive (non-attended) and active (attended) conditions. The onset of each tone was marked in the EEGs using a parallel port pulse (Neuroscan) or a stimulus-generated electrical pulse injected into the O1 and O2 channels (Emotiv EPOC®). These markers were used to calculate research and gaming EEG system late auditory ERPs (P1, N1, P2, N2, and P3 peaks) and the mismatch negativity (MMN) in active and passive listening conditions for each participant. Results. Analyses were restricted to frontal sites as these are most commonly reported in auditory ERP research. Intra-class correlations (ICCs) indicated that the morphology of the research and gaming EEG system late auditory ERP waveforms were similar across all participants, but that the research and gaming EEG system MMN waveforms were only similar for participants with non-noisy MMN waveforms (N = 11 out of 21). Peak amplitude and latency measures revealed no significant differences between the size or the timing of the auditory P1, N1, P2, N2, P3, and MMN peaks. Conclusions. Our findings suggest that the gaming EEG system may prove a valid alternative to laboratory ERP systems for recording reliable late auditory ERPs (P1, N1, P2, N2, and the P3) over the frontal cortices. In the future, the gaming EEG system may also prove useful for measuring less reliable ERPs, such as the MMN, if the reliability of such ERPs can be boosted to the same level as late auditory ERPs. PMID:23638374

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

PubMed

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

2013-01-01

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

Statistical geometric affinity in human brain electric activity

NASA Astrophysics Data System (ADS)

Chornet-Lurbe, A.; Oteo, J. A.; Ros, J.

2007-05-01

The representation of the human electroencephalogram (EEG) records by neurophysiologists demands standardized time-amplitude scales for their correct conventional interpretation. In a suite of graphical experiments involving scaling affine transformations we have been able to convert electroencephalogram samples corresponding to any particular sleep phase and relaxed wakefulness into each other. We propound a statistical explanation for that finding in terms of data collapse. As a sequel, we determine characteristic time and amplitude scales and outline a possible physical interpretation. An analysis for characteristic times based on lacunarity is also carried out as well as a study of the synchrony between left and right EEG channels.

Coregistration of Eye Movements and EEG in Natural Reading: Analyses and Review

ERIC Educational Resources Information Center

Dimigen, Olaf; Sommer, Werner; Hohlfeld, Annette; Jacobs, Arthur M.; Kliegl, Reinhold

2011-01-01

Brain-electric correlates of reading have traditionally been studied with word-by-word presentation, a condition that eliminates important aspects of the normal reading process and precludes direct comparisons between neural activity and oculomotor behavior. In the present study, we investigated effects of word predictability on eye movements (EM)…

Physiological processes non-linearly affect electrophysiological recordings during transcranial electric stimulation.

PubMed

Noury, Nima; Hipp, Joerg F; Siegel, Markus

2016-10-15

Transcranial electric stimulation (tES) is a promising tool to non-invasively manipulate neuronal activity in the human brain. Several studies have shown behavioral effects of tES, but stimulation artifacts complicate the simultaneous investigation of neural activity with EEG or MEG. Here, we first show for EEG and MEG, that contrary to previous assumptions, artifacts do not simply reflect stimulation currents, but that heartbeat and respiration non-linearly modulate stimulation artifacts. These modulations occur irrespective of the stimulation frequency, i.e. during both transcranial alternating and direct current stimulations (tACS and tDCS). Second, we show that, although at first sight previously employed artifact rejection methods may seem to remove artifacts, data are still contaminated by non-linear stimulation artifacts. Because of their complex nature and dependence on the subjects' physiological state, these artifacts are prone to be mistaken as neural entrainment. In sum, our results uncover non-linear tES artifacts, show that current techniques fail to fully remove them, and pave the way for new artifact rejection methods. Copyright © 2016 Elsevier Inc. All rights reserved.

Information-Theoretical Analysis of EEG Microstate Sequences in Python.

PubMed

von Wegner, Frederic; Laufs, Helmut

2018-01-01

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.

A stretchable electrode array for non-invasive, skin-mounted measurement of electrocardiography (ECG), electromyography (EMG) and electroencephalography (EEG).

PubMed

Ma, Rui; Kim, Dae-Hyeong; McCormick, Martin; Coleman, Todd; Rogers, John

2010-01-01

This paper reports a class of stretchable electrode array capable of intimate, conformal integration onto the curvilinear surfaces of skin on the human body. The designs employ conventional metallic conductors but in optimized mechanical layouts, on soft, thin elastomeric substrates. These devices exhibit an ability to record spontaneous EEG activity even without conductive electrolyte gels, with recorded alpha rhythm responses that are 40% stronger than those collected using conventional tin electrodes and gels under otherwise similar conditions. The same type of device can also measure high quality ECG and EMG signals. The results suggest broad utility for skin-mounted measurements of electrical activity in the body, with advantages in signal levels, wearability and modes of integration compared to alternatives.

Simultaneous head tissue conductivity and EEG source location estimation.

PubMed

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.

Simultaneous head tissue conductivity and EEG source location estimation

PubMed Central

Acar, Can E.; Makeig, Scott

2015-01-01

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 3 cm. 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 15 cm2-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-cm2-scale accurate 3-D functional cortical imaging modality. PMID:26302675

Applying support vector machine on hybrid fNIRS/EEG signal to classify driver's conditions (Conference Presentation)

NASA Astrophysics Data System (ADS)

Nguyen, Thien; Ahn, Sangtae; Jang, Hyojung; Jun, Sung C.; Kim, Jae G.

2016-03-01

Driver's condition plays a critical role in driving safety. The fact that about 20 percent of automobile accidents occurred due to driver fatigue leads to a demand for developing a method to monitor driver's status. In this study, we acquired brain signals such as oxy- and deoxyhemoglobin and neuronal electrical activity by a hybrid fNIRS/EEG system. Experiments were conducted with 11 subjects under two conditions: Normal condition, when subjects had enough sleep, and sleep deprivation condition, when subject did not sleep previous night. During experiment, subject performed a driving task with a car simulation system for 30 minutes. After experiment, oxy-hemoglobin and deoxy-hemoglobin changes were derived from fNIRS data, while beta and alpha band relative power were calculated from EEG data. Decrement of oxy-hemoglobin, beta band power, and increment of alpha band power were found in sleep deprivation condition compare to normal condition. These features were then applied to classify two conditions by Fisher's linear discriminant analysis (FLDA). The ratio of alpha-beta relative power showed classification accuracy with a range between 62% and 99% depending on a subject. However, utilization of both EEG and fNIRS features increased accuracy in the range between 68% and 100%. The highest increase of accuracy is from 63% using EEG to 99% using both EEG and fNIRS features. In conclusion, the enhancement of classification accuracy is shown by adding a feature from fNIRS to the feature from EEG using FLDA which provides the need of developing a hybrid fNIRS/EEG system.

Classification and evaluation of the pharmacodynamics of psychotropic drugs by single-lead pharmaco-EEG, EEG mapping and tomography (LORETA).

PubMed

Saletu, B; Anderer, P; Saletu-Zyhlarz, G M; Arnold, O; Pascual-Marqui, R D

2002-01-01

Utilizing computer-assisted quantitative analyses of human scalp-recorded electroencephalogram (EEG) in combination with certain statistical procedures (quantitative pharmaco-EEG) and mapping techniques (pharmaco-EEG mapping), it is possible to classify psychotropic substances and objectively evaluate their bioavailability at the target organ: the human brain. Specifically, one may determine at an early stage of drug development whether a drug is effective on the central nervous system (CNS) compared with placebo, what its clinical efficacy will be like, at which dosage it acts, when it acts and the equipotent dosages of different galenic formulations. Pharmaco-EEG profiles and maps of neuroleptics, antidepressants, tranquilizers, hypnotics, psychostimulants and nootropics/cognition-enhancing drugs will be described in this paper. Methodological problems, as well as the relationships between acute and chronic drug effects, alterations in normal subjects and patients, CNS effects, therapeutic efficacy and pharmacokinetic and pharmacodynamic data will be discussed. In recent times, imaging of drug effects on the regional brain electrical activity of healthy subjects by means of EEG tomography such as low-resolution electromagnetic tomography (LORETA) has been used for identifying brain areas predominantly involved in psychopharmacological action. This will be demonstrated for the representative drugs of the four main psychopharmacological classes, such as 3 mg haloperidol for neuroleptics, 20 mg citalopram for antidepressants, 2 mg lorazepam for tranquilizers and 20 mg methylphenidate for psychostimulants. LORETA demonstrates that these psychopharmacological classes affect brain structures differently.

The effect of hypobaric hypoxia on multichannel EEG signal complexity.

PubMed

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

2007-01-01

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

Functional brain microstate predicts the outcome in a visuospatial working memory task.

PubMed

Muthukrishnan, Suriya-Prakash; Ahuja, Navdeep; Mehta, Nalin; Sharma, Ratna

2016-11-01

Humans have limited capacity of processing just up to 4 integrated items of information in the working memory. Thus, it is inevitable to commit more errors when challenged with high memory loads. However, the neural mechanisms that determine the accuracy of response at high memory loads still remain unclear. High temporal resolution of Electroencephalography (EEG) technique makes it the best tool to resolve the temporal dynamics of brain networks. EEG-defined microstate is the quasi-stable scalp electrical potential topography that represents the momentary functional state of brain. Thus, it has been possible to assess the information processing currently performed by the brain using EEG microstate analysis. We hypothesize that the EEG microstate preceding the trial could determine its outcome in a visuospatial working memory (VSWM) task. Twenty-four healthy participants performed a high memory load VSWM task, while their brain activity was recorded using EEG. Four microstate maps were found to represent the functional brain state prior to the trials in the VSWM task. One pre-trial microstate map was found to determine the accuracy of subsequent behavioural response. The intracranial generators of the pre-trial microstate map that determined the response accuracy were localized to the visuospatial processing areas at bilateral occipital, right temporal and limbic cortices. Our results imply that the behavioural outcome in a VSWM task could be determined by the intensity of activation of memory representations in the visuospatial processing brain regions prior to the trial. Copyright © 2016 Elsevier B.V. All rights reserved.

The role of blood vessels in high-resolution volume conductor head modeling of EEG.

PubMed

Fiederer, L D J; Vorwerk, J; Lucka, F; Dannhauer, M; Yang, S; Dümpelmann, M; Schulze-Bonhage, A; Aertsen, A; Speck, O; Wolters, C H; Ball, T

2016-03-01

Reconstruction of the electrical sources of human EEG activity at high spatio-temporal accuracy is an important aim in neuroscience and neurological diagnostics. Over the last decades, numerous studies have demonstrated that realistic modeling of head anatomy improves the accuracy of source reconstruction of EEG signals. For example, including a cerebro-spinal fluid compartment and the anisotropy of white matter electrical conductivity were both shown to significantly reduce modeling errors. Here, we for the first time quantify the role of detailed reconstructions of the cerebral blood vessels in volume conductor head modeling for EEG. To study the role of the highly arborized cerebral blood vessels, we created a submillimeter head model based on ultra-high-field-strength (7T) structural MRI datasets. Blood vessels (arteries and emissary/intraosseous veins) were segmented using Frangi multi-scale vesselness filtering. The final head model consisted of a geometry-adapted cubic mesh with over 17×10(6) nodes. We solved the forward model using a finite-element-method (FEM) transfer matrix approach, which allowed reducing computation times substantially and quantified the importance of the blood vessel compartment by computing forward and inverse errors resulting from ignoring the blood vessels. Our results show that ignoring emissary veins piercing the skull leads to focal localization errors of approx. 5 to 15mm. Large errors (>2cm) were observed due to the carotid arteries and the dense arterial vasculature in areas such as in the insula or in the medial temporal lobe. Thus, in such predisposed areas, errors caused by neglecting blood vessels can reach similar magnitudes as those previously reported for neglecting white matter anisotropy, the CSF or the dura - structures which are generally considered important components of realistic EEG head models. Our findings thus imply that including a realistic blood vessel compartment in EEG head models will be helpful to improve the accuracy of EEG source analyses particularly when high accuracies in brain areas with dense vasculature are required. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Zazen meditation and no-task resting EEG compared with LORETA intracortical source localization.

PubMed

Faber, Pascal L; Lehmann, Dietrich; Gianotti, Lorena R R; Milz, Patricia; Pascual-Marqui, Roberto D; Held, Marlene; Kochi, Kieko

2015-02-01

Meditation is a self-induced and willfully initiated practice that alters the state of consciousness. The meditation practice of Zazen, like many other meditation practices, aims at disregarding intrusive thoughts while controlling body posture. It is an open monitoring meditation characterized by detached moment-to-moment awareness and reduced conceptual thinking and self-reference. Which brain areas differ in electric activity during Zazen compared to task-free resting? Since scalp electroencephalography (EEG) waveforms are reference-dependent, conclusions about the localization of active brain areas are ambiguous. Computing intracerebral source models from the scalp EEG data solves this problem. In the present study, we applied source modeling using low resolution brain electromagnetic tomography (LORETA) to 58-channel scalp EEG data recorded from 15 experienced Zen meditators during Zazen and no-task resting. Zazen compared to no-task resting showed increased alpha-1 and alpha-2 frequency activity in an exclusively right-lateralized cluster extending from prefrontal areas including the insula to parts of the somatosensory and motor cortices and temporal areas. Zazen also showed decreased alpha and beta-2 activity in the left angular gyrus and decreased beta-1 and beta-2 activity in a large bilateral posterior cluster comprising the visual cortex, the posterior cingulate cortex and the parietal cortex. The results include parts of the default mode network and suggest enhanced automatic memory and emotion processing, reduced conceptual thinking and self-reference on a less judgmental, i.e., more detached moment-to-moment basis during Zazen compared to no-task resting.

Simultaneous EEG and diffuse optical imaging of seizure-related hemodynamic activity in the newborn infant brain

NASA Astrophysics Data System (ADS)

Hebden, Jeremy C.; Cooper, Robert J.; Gibson, Adam; Everdell, Nick; Austin, Topun

2012-06-01

An optical imaging system has been developed which uses measurements of diffusely reflected near-infrared light to produce maps of changes in blood flow and oxygenation occurring within the cerebral cortex. Optical sources and detectors are coupled to the head via an array of optical fibers, on a probe held in contact with the scalp, and data is collected at a rate of 10 Hz. A clinical electroencephalography (EEG) system has been integrated with the optical system to enable simultaneous observation of electrical and hemodynamic activity in the cortex of neurologically compromised newborn infants diagnosed with seizures. Studies have made a potentially critically important discovery of previously unknown transient hemodynamic events in infants treated with anticonvulsant medication. We observed repeated episodes of small increases in cortical oxyhemoglobin concentration followed by a profound decrease in 3 of 4 infants studied, each with cerebral injury who presented with neonatal seizures. This was not accompanied by clinical or EEG seizure activity and was not present in nineteen matched controls. The underlying cause of these changes is currently unknown. We tentatively suggest that our results may be associated with a phenomenon known as cortical spreading depolarization, not previously observed in the infant brain.

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

NASA Astrophysics Data System (ADS)

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.

[Non-linear research of alertness levels under sleep deprivation].

PubMed

Xue, Ranting; Zhou, Peng; Gao, Xiang; Dong, Xinming; Wang, Xiaolu; Ming, Dong; Qi, Hongzhi; Wang, Xuemin

2014-06-01

We applied Lempel-Ziv complexity (LZC) combined with brain electrical activity mapping (BEAM) to study the change of alertness under sleep deprivation in our research. Ten subjects were involved in 36 hours sleep deprivation (SD), during which spontaneous electroencephalogram (EEG) experiments and auditory evoked EEG experiments-Oddball were recorded once every 6 hours. Spontaneous and evoked EEG data were calculated and BEAMs were structured. Results showed that during the 36 hours of SD, alertness could be divided into three stages, i. e. the first 12 hours as the high stage, the middle 12 hours as the rapid decline stage and the last 12 hours as the low stage. During the period SD, LZC of Spontaneous EEG decreased over the whole brain to some extent, but remained consistent with the subjective scales. By BEAMs of event related potential, LZC on frontal cortex decreased, but kept consistent with the behavioral responses. Therefore, LZC can be effective to reflect the change of brain alertness. At the same time LZC could be used as a practical index to monitor real-time alertness because of its simple computation and fast calculation.

Causal Neuro-immune Relationships at Patients with Chronic Pyelonephritis and Cholecystitis. Correlations between Parameters EEG, HRV and White Blood Cell Count

PubMed Central

Kul’chyns’kyi, Andriy B; Kyjenko, Valeriy M; Zukow, Walery; Popovych, Igor L

2017-01-01

Abstract We aim to analyze in bounds KJ Tracey’s immunological homunculus conception the relationships between parameters of electroencephalogram (EEG) and heart rate variability (HRV), on the one hand, and the parameters of bhite blood cell count, on the other hand. Methods In basal conditions in 23 men, patients with chronic pyelonephritis and cholecystitis in remission, recorded EEG (“NeuroCom Standard”, KhAI Medica, Ukraine) and HRV (“Cardiolab+VSR”, KhAI Medica, Ukraine). In portion of blood counted up white blood cell count. Results Revealed that canonical correlation between constellation EEG and HRV parameters form with blood level of leukocytes 0.92 (p<10-5), with relative content in white blood cell count stubnuclear neutrophiles 0.93 (p<10-5), segmentonucleary neutrophiles 0.89 (p<10-3), eosinophiles 0.87 (p=0.003), lymphocytes 0.77 (p<10-3) and with monocytes 0.75 (p=0.003). Conclusion Parameters of white blood cell count significantly modulated by electrical activity some structures of central and autonomic nervous systems. PMID:28730179

EEG-based recognition of video-induced emotions: selecting subject-independent feature set.

PubMed

Kortelainen, Jukka; Seppänen, Tapio

2013-01-01

Emotions are fundamental for everyday life affecting our communication, learning, perception, and decision making. Including emotions into the human-computer interaction (HCI) could be seen as a significant step forward offering a great potential for developing advanced future technologies. While the electrical activity of the brain is affected by emotions, offers electroencephalogram (EEG) an interesting channel to improve the HCI. In this paper, the selection of subject-independent feature set for EEG-based emotion recognition is studied. We investigate the effect of different feature sets in classifying person's arousal and valence while watching videos with emotional content. The classification performance is optimized by applying a sequential forward floating search algorithm for feature selection. The best classification rate (65.1% for arousal and 63.0% for valence) is obtained with a feature set containing power spectral features from the frequency band of 1-32 Hz. The proposed approach substantially improves the classification rate reported in the literature. In future, further analysis of the video-induced EEG changes including the topographical differences in the spectral features is needed.

A simple method for EEG guided transcranial electrical stimulation without models.

PubMed

Cancelli, Andrea; Cottone, Carlo; Tecchio, Franca; Truong, Dennis Q; Dmochowski, Jacek; Bikson, Marom

2016-06-01

There is longstanding interest in using EEG measurements to inform transcranial Electrical Stimulation (tES) but adoption is lacking because users need a simple and adaptable recipe. The conventional approach is to use anatomical head-models for both source localization (the EEG inverse problem) and current flow modeling (the tES forward model), but this approach is computationally demanding, requires an anatomical MRI, and strict assumptions about the target brain regions. We evaluate techniques whereby tES dose is derived from EEG without the need for an anatomical head model, target assumptions, difficult case-by-case conjecture, or many stimulation electrodes. We developed a simple two-step approach to EEG-guided tES that based on the topography of the EEG: (1) selects locations to be used for stimulation; (2) determines current applied to each electrode. Each step is performed based solely on the EEG with no need for head models or source localization. Cortical dipoles represent idealized brain targets. EEG-guided tES strategies are verified using a finite element method simulation of the EEG generated by a dipole, oriented either tangential or radial to the scalp surface, and then simulating the tES-generated electric field produced by each model-free technique. These model-free approaches are compared to a 'gold standard' numerically optimized dose of tES that assumes perfect understanding of the dipole location and head anatomy. We vary the number of electrodes from a few to over three hundred, with focality or intensity as optimization criterion. Model-free approaches evaluated include (1) voltage-to-voltage, (2) voltage-to-current; (3) Laplacian; and two Ad-Hoc techniques (4) dipole sink-to-sink; and (5) sink to concentric. Our results demonstrate that simple ad hoc approaches can achieve reasonable targeting for the case of a cortical dipole, remarkably with only 2-8 electrodes and no need for a model of the head. Our approach is verified directly only for a theoretically localized source, but may be potentially applied to an arbitrary EEG topography. For its simplicity and linearity, our recipe for model-free EEG guided tES lends itself to broad adoption and can be applied to static (tDCS), time-variant (e.g., tACS, tRNS, tPCS), or closed-loop tES.

A simple method for EEG guided transcranial electrical stimulation without models

NASA Astrophysics Data System (ADS)

Cancelli, Andrea; Cottone, Carlo; Tecchio, Franca; Truong, Dennis Q.; Dmochowski, Jacek; Bikson, Marom

2016-06-01

Objective. There is longstanding interest in using EEG measurements to inform transcranial Electrical Stimulation (tES) but adoption is lacking because users need a simple and adaptable recipe. The conventional approach is to use anatomical head-models for both source localization (the EEG inverse problem) and current flow modeling (the tES forward model), but this approach is computationally demanding, requires an anatomical MRI, and strict assumptions about the target brain regions. We evaluate techniques whereby tES dose is derived from EEG without the need for an anatomical head model, target assumptions, difficult case-by-case conjecture, or many stimulation electrodes. Approach. We developed a simple two-step approach to EEG-guided tES that based on the topography of the EEG: (1) selects locations to be used for stimulation; (2) determines current applied to each electrode. Each step is performed based solely on the EEG with no need for head models or source localization. Cortical dipoles represent idealized brain targets. EEG-guided tES strategies are verified using a finite element method simulation of the EEG generated by a dipole, oriented either tangential or radial to the scalp surface, and then simulating the tES-generated electric field produced by each model-free technique. These model-free approaches are compared to a ‘gold standard’ numerically optimized dose of tES that assumes perfect understanding of the dipole location and head anatomy. We vary the number of electrodes from a few to over three hundred, with focality or intensity as optimization criterion. Main results. Model-free approaches evaluated include (1) voltage-to-voltage, (2) voltage-to-current; (3) Laplacian; and two Ad-Hoc techniques (4) dipole sink-to-sink; and (5) sink to concentric. Our results demonstrate that simple ad hoc approaches can achieve reasonable targeting for the case of a cortical dipole, remarkably with only 2-8 electrodes and no need for a model of the head. Significance. Our approach is verified directly only for a theoretically localized source, but may be potentially applied to an arbitrary EEG topography. For its simplicity and linearity, our recipe for model-free EEG guided tES lends itself to broad adoption and can be applied to static (tDCS), time-variant (e.g., tACS, tRNS, tPCS), or closed-loop tES.

Microstates in resting-state EEG: current status and future directions.

PubMed

Khanna, Arjun; Pascual-Leone, Alvaro; Michel, Christoph M; Farzan, Faranak

2015-02-01

Electroencephalography (EEG) is a powerful method of studying the electrophysiology of the brain with high temporal resolution. Several analytical approaches to extract information from the EEG signal have been proposed. One method, termed microstate analysis, considers the multichannel EEG recording as a series of quasi-stable "microstates" that are each characterized by a unique topography of electric potentials over the entire channel array. Because this technique simultaneously considers signals recorded from all areas of the cortex, it is capable of assessing the function of large-scale brain networks whose disruption is associated with several neuropsychiatric disorders. In this review, we first introduce the method of EEG microstate analysis. We then review studies that have discovered significant changes in the resting-state microstate series in a variety of neuropsychiatric disorders and behavioral states. We discuss the potential utility of this method in detecting neurophysiological impairments in disease and monitoring neurophysiological changes in response to an intervention. Finally, we discuss how the resting-state microstate series may reflect rapid switching among neural networks while the brain is at rest, which could represent activity of resting-state networks described by other neuroimaging modalities. We conclude by commenting on the current and future status of microstate analysis, and suggest that EEG microstates represent a promising neurophysiological tool for understanding and assessing brain network dynamics on a millisecond timescale in health and disease. Copyright © 2014 Elsevier Ltd. All rights reserved.

Microstates in Resting-State EEG: Current Status and Future Directions

PubMed Central

Khanna, Arjun; Pascual-Leone, Alvaro; Michel, Christoph M.; Farzan, Faranak

2015-01-01

Electroencephalography (EEG) is a powerful method of studying the electrophysiology of the brain with high temporal resolution. Several analytical approaches to extract information from the EEG signal have been proposed. One method, termed microstate analysis, considers the multichannel EEG recording as a series of quasi-stable “microstates” that are each characterized by a unique topography of electric potentials over the entire channel array. Because this technique simultaneously considers signals recorded from all areas of the cortex, it is capable of assessing the function of large-scale brain networks whose disruption is associated with several neuropsychiatric disorders. In this review, we first introduce the method of EEG microstate analysis. We then review studies that have discovered significant changes in the resting-state microstate series in a variety of neuropsychiatric disorders and behavioral states. We discuss the potential utility of this method in detecting neurophysiological impairments in disease and monitoring neurophysiological changes in response to an intervention. Finally, we discuss how the resting-state microstate series may reflect rapid switching among neural networks while the brain is at rest, which could represent activity of resting-state networks described by other neuroimaging modalities. We conclude by commenting on the current and future status of microstate analysis, and suggest that EEG microstates represent a promising neurophysiological tool for understanding and assessing brain network dynamics on a millisecond timescale in health and disease. PMID:25526823

A low-noise low-power EEG acquisition node for scalable brain-machine interfaces

NASA Astrophysics Data System (ADS)

Sullivan, Thomas J.; Deiss, Stephen R.; Cauwenberghs, Gert; Jung, Tzyy-Ping

2007-05-01

Electroencephalograph (EEG) recording systems offer a versatile, noninvasive window on the brain's spatio-temporal activity for many neuroscience and clinical applications. Our research aims at improving the spatial resolution and mobility of EEG recording by reducing the form factor, power drain and signal fanout of the EEG acquisition node in a scalable sensor array architecture. We present such a node integrated onto a dimesized circuit board that contains a sensor's complete signal processing front-end, including amplifier, filters, and analog-to-digital conversion. A daisy-chain configuration between boards with bit-serial output reduces the wiring needed. The circuit's low power consumption of 423 μW supports EEG systems with hundreds of electrodes to operate from small batteries for many hours. Coupling between the bit-serial output and the highly sensitive analog input due to dense integration of analog and digital functions on the circuit board results in a deterministic noise component in the output, larger than the intrinsic sensor and circuit noise. With software correction of this noise contribution, the system achieves an input-referred noise of 0.277 μVrms in the signal band of 1 to 100 Hz, comparable to the best medical-grade systems in use. A chain of seven nodes using EEG dry electrodes created in micro-electrical-mechanical system (MEMS) technology is demonstrated in a real-world setting.

Removal of BCG artifacts using a non-Kirchhoffian overcomplete representation.

PubMed

Dyrholm, Mads; Goldman, Robin; Sajda, Paul; Brown, Truman R

2009-02-01

We present a nonlinear unmixing approach for extracting the ballistocardiogram (BCG) from EEG recorded in an MR scanner during simultaneous acquisition of functional MRI (fMRI). First, an overcomplete basis is identified in the EEG based on a custom multipath EEG electrode cap. Next, the overcomplete basis is used to infer non-Kirchhoffian latent variables that are not consistent with a conservative electric field. Neural activity is strictly Kirchhoffian while the BCG artifact is not, and the representation can hence be used to remove the artifacts from the data in a way that does not attenuate the neural signals needed for optimal single-trial classification performance. We compare our method to more standard methods for BCG removal, namely independent component analysis and optimal basis sets, by looking at single-trial classification performance for an auditory oddball experiment. We show that our overcomplete representation method for removing BCG artifacts results in better single-trial classification performance compared to the conventional approaches, indicating that the derived neural activity in this representation retains the complex information in the trial-to-trial variability.

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

PubMed

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

2018-02-15

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

Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics.

PubMed

He, Bin; Sohrabpour, Abbas; Brown, Emery; Liu, Zhongming

2018-06-04

Brain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications.

[Electroconvulsive therapy and level of evidence: From causality to dose-effect relationship].

PubMed

Micoulaud-Franchi, J-A; Quilès, C; Cermolacce, M; Belzeaux, R; Adida, M; Fakra, E; Azorin, J-M

2016-12-01

The first objective of this article is to summarize the history of electroconvulsive therapy (ECT) in psychiatry in order to highlight the transition from clinical level of evidence based on phenomenological descriptions to controlled trial establishing causal relationship. The second objective is to apply the criteria of causation for ECT, to focus on the dose-effect relationship criteria, and thus to analyze the conditions of application of these criteria for ECT. A literature review exploring the use of electricity, ECT and electroencephalography (EEG) in psychiatry was conducted. The publications were identified from the Pubmed and GoogleScholar electronic databases. The scientific literature search of international articles was performed in July 2016. In 1784, a Royal commission established in France by King Louis XVI tested Mesmer's claims concerning animal magnetism. By doing that, the commission, including such prominent scientists as the chemist Anton Lavoisier and the scientist and researcher on electricity and therapeutics Benjamin Franklin, played a central role in establishing the criteria needed to assess the level of evidence of electrical therapeutics in psychiatry. Surprisingly, it is possible to identify the classical Bradford Hill criteria of causation in the report of the commission, except the dose-effect relationship criteria. Since then, it has been conducted blinded randomized controlled trials that confirmed the effectiveness of ECT against ECT placebos for the treatment of psychiatric disorders. At present, the dose-effect relationship criteria can be analyzed through an EEG quality assessment of ECT-induced seizures. EEG quality assessment includes several indices: TSLOW (time to onset of seizure activity ≤5Hz, seconds), peak mid-ictal amplitude (mm), regularity (intensity or morphology of the seizure (0-6)), stereotypy (global seizure patterning, 0-3) and post-ictal suppression (0-3). A manual rating sheet is needed to score theses indices. Such manual rating with example of EEG segments recording is proposed in this article. Additional studies are needed to validate this manual, to better establish the dose-response relationship for the ECT, and thus strengthen the position of the EEG as a central element for clinical good practice for ECT. © L’Encéphale, Paris, 2016.

[Functional asymmetry of electric processes in the rabbit brain cortex at formation of the hunger dominant].

PubMed

Rusinova, E V

2011-01-01

The motivational condition of hunger and formation of the hunger dominant after daily food deprivation was studied in the conditions of chronic experiments on rabbits. It was shown, that the hunger condition was accompanied by left sided interhemispher asymmetry on indicators of spectral capacity of EEG frontal and right-hand asymmetry sensorimotor areas of the cortex. A hunger dominant was accompanied by falling of spectral capacity of EEG of areas of both hemispheres. The condition of hunger and a hunger dominant were characterized by right-hand asymmetry on average level of EEG coherence of frontal and sensorimotor areas. At transition of a condition of hunger in a hunger dominant there was an average level of EEG coherence decrease in areas of the right hemisphere. Electric processes of the cortex of the brain at a motivational condition of hunger and a hunger dominant were different.

Correlations between the Signal Complexity of Cerebral and Cardiac Electrical Activity: A Multiscale Entropy Analysis

PubMed Central

Lin, Pei-Feng; Lo, Men-Tzung; Tsao, Jenho; Chang, Yi-Chung; Lin, Chen; Ho, Yi-Lwun

2014-01-01

The heart begins to beat before the brain is formed. Whether conventional hierarchical central commands sent by the brain to the heart alone explain all the interplay between these two organs should be reconsidered. Here, we demonstrate correlations between the signal complexity of brain and cardiac activity. Eighty-seven geriatric outpatients with healthy hearts and varied cognitive abilities each provided a 24-hour electrocardiography (ECG) and a 19-channel eye-closed routine electroencephalography (EEG). Multiscale entropy (MSE) analysis was applied to three epochs (resting-awake state, photic stimulation of fast frequencies (fast-PS), and photic stimulation of slow frequencies (slow-PS)) of EEG in the 1–58 Hz frequency range, and three RR interval (RRI) time series (awake-state, sleep and that concomitant with the EEG) for each subject. The low-to-high frequency power (LF/HF) ratio of RRI was calculated to represent sympatho-vagal balance. With statistics after Bonferroni corrections, we found that: (a) the summed MSE value on coarse scales of the awake RRI (scales 11–20, RRI-MSE-coarse) were inversely correlated with the summed MSE value on coarse scales of the resting-awake EEG (scales 6–20, EEG-MSE-coarse) at Fp2, C4, T6 and T4; (b) the awake RRI-MSE-coarse was inversely correlated with the fast-PS EEG-MSE-coarse at O1, O2 and C4; (c) the sleep RRI-MSE-coarse was inversely correlated with the slow-PS EEG-MSE-coarse at Fp2; (d) the RRI-MSE-coarse and LF/HF ratio of the awake RRI were correlated positively to each other; (e) the EEG-MSE-coarse at F8 was proportional to the cognitive test score; (f) the results conform to the cholinergic hypothesis which states that cognitive impairment causes reduction in vagal cardiac modulation; (g) fast-PS significantly lowered the EEG-MSE-coarse globally. Whether these heart-brain correlations could be fully explained by the central autonomic network is unknown and needs further exploration. PMID:24498375

Combined electroencephalography-functional magnetic resonance imaging and electrical source imaging improves localization of pediatric focal epilepsy.

PubMed

Centeno, Maria; Tierney, Tim M; Perani, Suejen; Shamshiri, Elhum A; St Pier, Kelly; Wilkinson, Charlotte; Konn, Daniel; Vulliemoz, Serge; Grouiller, Frédéric; Lemieux, Louis; Pressler, Ronit M; Clark, Christopher A; Cross, J Helen; Carmichael, David W

2017-08-01

Surgical treatment in epilepsy is effective if the epileptogenic zone (EZ) can be correctly localized and characterized. Here we use simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) data to derive EEG-fMRI and electrical source imaging (ESI) maps. Their yield and their individual and combined ability to (1) localize the EZ and (2) predict seizure outcome were then evaluated. Fifty-three children with drug-resistant epilepsy underwent EEG-fMRI. Interictal discharges were mapped using both EEG-fMRI hemodynamic responses and ESI. A single localization was derived from each individual test (EEG-fMRI global maxima [GM]/ESI maximum) and from the combination of both maps (EEG-fMRI/ESI spatial intersection). To determine the localization accuracy and its predictive performance, the individual and combined test localizations were compared to the presumed EZ and to the postsurgical outcome. Fifty-two of 53 patients had significant maps: 47 of 53 for EEG-fMRI, 44 of 53 for ESI, and 34 of 53 for both. The EZ was well characterized in 29 patients; 26 had an EEG-fMRI GM localization that was correct in 11, 22 patients had ESI localization that was correct in 17, and 12 patients had combined EEG-fMRI and ESI that was correct in 11. Seizure outcome following resection was correctly predicted by EEG-fMRI GM in 8 of 20 patients, and by the ESI maximum in 13 of 16. The combined EEG-fMRI/ESI region entirely predicted outcome in 9 of 9 patients, including 3 with no lesion visible on MRI. EEG-fMRI combined with ESI provides a simple unbiased localization that may predict surgery better than each individual test, including in MRI-negative patients. Ann Neurol 2017;82:278-287. © 2017 American Neurological Association.

Investigating the Effects of Peripheral Electrical Stimulation on Corticomuscular Functional Connectivity Stroke Survivors.

PubMed

Lai, Meei-I; Pan, Li-Ling; Tsai, Mei-Wun; Shih, Yi-Fen; Wei, Shun-Hwa; Chou, Li-Wei

2016-06-01

Electrical stimulation (ES) in the periphery can induce brain plasticity and has been used clinically to promote motor recovery in patients with central nervous system lesion. Electroencephalogram (EEG) and electromyogram (EMG) are readily applicable in clinical settings and can detect real-time functional connectivity between motor cortex and muscles with EEG-EMG (corticomuscular) coherence. The purpose of this study was to determine whether EEG-EMG coherence can detect changes in corticomuscular control induced by peripheral ES. Fifteen healthy young adults and 15 stroke survivors received 40-min electrical stimulation session on median nerve. The stimulation (1-ms rectangular pulse, 100 Hz) was delivered with a 20-s on-20-s off cycle, and the intensity was set at the subjects' highest tolerable level without muscle contraction or pain. Both before and after the stimulation session, subjects performed a 20-s steady-hold thumb flexion at 50% maximal voluntary contraction (MVC) while EEG and EMG were collected. Our results demonstrated that after ES, EEG-EMG coherence in gamma band increased significantly for 22.1 and 48.6% in healthy adults and stroke survivors, respectively. In addition, after ES, force steadiness was also improved in both groups, as indicated by the decrease in force fluctuation during steady-hold contraction (-1.7% MVC and -3.9%MVC for healthy and stroke individuals, respectively). Our results demonstrated that EEG-EMG coherence can detect ES-induced changes in the neuromuscular system. Also, because gamma coherence is linked to afferent inputs encoding, improvement in motor performance is likely related to ES-elicited strong sensory input and enhanced sensorimotor integration.

Wavelet entropy: a new tool for analysis of short duration brain electrical signals.

PubMed

Rosso, O A; Blanco, S; Yordanova, J; Kolev, V; Figliola, A; Schürmann, M; Başar, E

2001-01-30

Since traditional electrical brain signal analysis is mostly qualitative, the development of new quantitative methods is crucial for restricting the subjectivity in the study of brain signals. These methods are particularly fruitful when they are strongly correlated with intuitive physical concepts that allow a better understanding of brain dynamics. Here, new method based on orthogonal discrete wavelet transform (ODWT) is applied. It takes as a basic element the ODWT of the EEG signal, and defines the relative wavelet energy, the wavelet entropy (WE) and the relative wavelet entropy (RWE). The relative wavelet energy provides information about the relative energy associated with different frequency bands present in the EEG and their corresponding degree of importance. The WE carries information about the degree of order/disorder associated with a multi-frequency signal response, and the RWE measures the degree of similarity between different segments of the signal. In addition, the time evolution of the WE is calculated to give information about the dynamics in the EEG records. Within this framework, the major objective of the present work was to characterize in a quantitative way functional dynamics of order/disorder microstates in short duration EEG signals. For that aim, spontaneous EEG signals under different physiological conditions were analyzed. Further, specific quantifiers were derived to characterize how stimulus affects electrical events in terms of frequency synchronization (tuning) in the event related potentials.

Effects of neurofeedback therapy in healthy young subjects.

PubMed

Altan, Sümeyra; Berberoglu, Bercim; Canan, Sinan; Dane, Şenol

2016-12-01

Neurofeedback refers to a form of operant conditioning of electrical brain activity, in which desirable brain activity is rewarded and undesirable brain activity is inhibited. The research team aimed to examine the efficacy of neurofeedback therapy on electroencephalogram (EEG) for heart rate, electrocardiogram (ECG) and galvanic skin resistance (GSR) parameters in a healthy young male population. Forty healthy young male subjects aged between 18 to 30 years participated in this study. Neurofeedback application of one session was made with bipolar electrodes placed on T3 and T4 (temporal 3 and 4) regions and with reference electrode placed on PF1 (prefrontal 1). Electroencephalogram (EEG), electrocardiogram (ECG) and galvanic skin resistance (GSR) were assessed during Othmer neurofeedback application of one session to regulate slow wave activity for forty minutes thorough the session. Data assessed before neurofeedback application for 5 minutes and during neurofeedback application of 30 minutes and after neurofeedback application for 5 minutes throughout the session of 40 minutes. Means for each 5 minutes, that is to say, a total 8 data points for each subjects over 40 minutes, were assessed. Galvanic skin resistance increased and heart rate decreased after neurofeedback therapy. Beta activity in EEG increased and alfa activity decreased after neurofeedback therapy. These results suggest that neurofeedback can be used to restore sympathovagal imbalances. Also, it may be accepted as a preventive therapy for psychological and neurological problems.

Spectral feature extraction of EEG signals and pattern recognition during mental tasks of 2-D cursor movements for BCI using SVM and ANN.

PubMed

Bascil, M Serdar; Tesneli, Ahmet Y; Temurtas, Feyzullah

2016-09-01

Brain computer interface (BCI) is a new communication way between man and machine. It identifies mental task patterns stored in electroencephalogram (EEG). So, it extracts brain electrical activities recorded by EEG and transforms them machine control commands. The main goal of BCI is to make available assistive environmental devices for paralyzed people such as computers and makes their life easier. This study deals with feature extraction and mental task pattern recognition on 2-D cursor control from EEG as offline analysis approach. The hemispherical power density changes are computed and compared on alpha-beta frequency bands with only mental imagination of cursor movements. First of all, power spectral density (PSD) features of EEG signals are extracted and high dimensional data reduced by principle component analysis (PCA) and independent component analysis (ICA) which are statistical algorithms. In the last stage, all features are classified with two types of support vector machine (SVM) which are linear and least squares (LS-SVM) and three different artificial neural network (ANN) structures which are learning vector quantization (LVQ), multilayer neural network (MLNN) and probabilistic neural network (PNN) and mental task patterns are successfully identified via k-fold cross validation technique.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Effect of the 5-HT(1A) partial agonist buspirone on regional brain electrical activity in man: a functional neuroimaging study using low-resolution electromagnetic tomography (LORETA).

PubMed

Anderer, P; Saletu, B; Pascual-Marqui, R D

2000-12-04

In a double-blind, placebo-controlled study, the effects of 20 mg buspirone - a 5-HT(1A) partial agonist - on regional electrical generators within the human brain were investigated utilizing three-dimensional EEG tomography. Nineteen-channel vigilance-controlled EEG recordings were carried out in 20 healthy subjects before and 1, 2, 4, 6 and 8 h after drug intake. Low-resolution electromagnetic tomography (LORETA; Key Institute for Brain-Mind Research, software: http://www.keyinst.unizh.ch) was computed from spectrally analyzed EEG data, and differences between drug- and placebo-induced changes were displayed as statistical parametric maps. Data were registered to the Talairach-Tournoux human brain atlas available as a digitized MRI (McConnell Brain Imaging Centre: http://www.bic.mni.mcgill.ca). At the pharmacodynamic peak (1st hour), buspirone increased theta and decreased fast alpha and beta sources. Areas of theta increase were mainly the left temporo-occipito-parietal and left prefrontal cortices, which is consistent with PET studies on buspirone-induced decreases in regional cerebral blood flow and fenfluramine-induced serotonin activation demonstrated by changes in regional cerebral glucose metabolism. In later hours (8th hour) with lower buspirone plasma levels, delta, theta, slow alpha and fast beta decreased, predominantly in the prefrontal and anterior limbic lobe. Whereas the results of the 1st hour speak for a slight CNS sedation (more in the sense of relaxation), those obtained in the 8th hour indicate activation. Thus, LORETA may provide useful and direct information on drug-induced changes in central nervous system function in man.

Evaluation of cortical local field potential diffusion in stereotactic electro-encephalography recordings: A glimpse on white matter signal.

PubMed

Mercier, Manuel R; Bickel, Stephan; Megevand, Pierre; Groppe, David M; Schroeder, Charles E; Mehta, Ashesh D; Lado, Fred A

2017-02-15

While there is a strong interest in meso-scale field potential recording using intracranial electroencephalography with penetrating depth electrodes (i.e. stereotactic EEG or S-EEG) in humans, the signal recorded in the white matter remains ignored. White matter is generally considered electrically neutral and often included in the reference montage. Moreover, re-referencing electrophysiological data is a critical preprocessing choice that could drastically impact signal content and consequently the results of any given analysis. In the present stereotactic electroencephalography study, we first illustrate empirically the consequences of commonly used references (subdermal, white matter, global average, local montage) on inter-electrode signal correlation. Since most of these reference montages incorporate white matter signal, we next consider the difference between signals recorded in cortical gray matter and white matter. Our results reveal that electrode contacts located in the white matter record a mixture of activity, with part arising from the volume conduction (zero time delay) of activity from nearby gray matter. Furthermore, our analysis shows that white matter signal may be correlated with distant gray matter signal. While residual passive electrical spread from nearby matter may account for this relationship, our results suggest the possibility that this long distance correlation arises from the white matter fiber tracts themselves (i.e. activity from distant gray matter traveling along axonal fibers with time lag larger than zero); yet definitive conclusions about the origin of the white matter signal would require further experimental substantiation. By characterizing the properties of signals recorded in white matter and in gray matter, this study illustrates the importance of including anatomical prior knowledge when analyzing S-EEG data. Copyright © 2017 Elsevier Inc. All rights reserved.

The functional significance of EEG microstates--Associations with modalities of thinking.

PubMed

Milz, P; Faber, P L; Lehmann, D; Koenig, T; Kochi, K; Pascual-Marqui, R D

2016-01-15

The momentary, global functional state of the brain is reflected by its electric field configuration. Cluster analytical approaches consistently extracted four head-surface brain electric field configurations that optimally explain the variance of their changes across time in spontaneous EEG recordings. These four configurations are referred to as EEG microstate classes A, B, C, and D and have been associated with verbal/phonological, visual, subjective interoceptive-autonomic processing, and attention reorientation, respectively. The present study tested these associations via an intra-individual and inter-individual analysis approach. The intra-individual approach tested the effect of task-induced increased modality-specific processing on EEG microstate parameters. The inter-individual approach tested the effect of personal modality-specific parameters on EEG microstate parameters. We obtained multichannel EEG from 61 healthy, right-handed, male students during four eyes-closed conditions: object-visualization, spatial-visualization, verbalization (6 runs each), and resting (7 runs). After each run, we assessed participants' degrees of object-visual, spatial-visual, and verbal thinking using subjective reports. Before and after the recording, we assessed modality-specific cognitive abilities and styles using nine cognitive tests and two questionnaires. The EEG of all participants, conditions, and runs was clustered into four classes of EEG microstates (A, B, C, and D). RMANOVAs, ANOVAs and post-hoc paired t-tests compared microstate parameters between conditions. TANOVAs compared microstate class topographies between conditions. Differences were localized using eLORETA. Pearson correlations assessed interrelationships between personal modality-specific parameters and EEG microstate parameters during no-task resting. As hypothesized, verbal as opposed to visual conditions consistently affected the duration, occurrence, and coverage of microstate classes A and B. Contrary to associations suggested by previous reports, parameters were increased for class A during visualization, and class B during verbalization. In line with previous reports, microstate D parameters were increased during no-task resting compared to the three internal, goal-directed tasks. Topographic differences between conditions included particular sub-regions of components of the metabolic default mode network. Modality-specific personal parameters did not consistently correlate with microstate parameters except verbal cognitive style which correlated negatively with microstate class A duration and positively with class C occurrence. This is the first study that aimed to induce EEG microstate class parameter changes based on their hypothesized functional significance. Beyond the associations of microstate classes A and B with visual and verbal processing, respectively, our results suggest that a finely-tuned interplay between all four EEG microstate classes is necessary for the continuous formation of visual and verbal thoughts. Our results point to the possibility that the EEG microstate classes may represent the head-surface measured activity of intra-cortical sources primarily exhibiting inhibitory functions. However, additional studies are needed to verify and elaborate on this hypothesis. Copyright © 2015 Elsevier Inc. All rights reserved.

Novel bifunctional cap for simultaneous electroencephalography and transcranial electrical stimulation.

PubMed

Wunder, Sophia; Hunold, Alexander; Fiedler, Patrique; Schlegelmilch, Falk; Schellhorn, Klaus; Haueisen, Jens

2018-05-08

Neuromodulation induced by transcranial electric stimulation (TES) exhibited promising potential for clinical practice. However, the underlying mechanisms remain subject of research. The combination of TES and electroencephalography (EEG) offers great potential for investigating these mechanisms and brain function in general, especially when performed simultaneously. In conventional applications, the combination of EEG and TES suffers from limitations on the electrode level (gel for electrode-skin interface) and the usability level (preparation time, reproducibility of positioning). To overcome these limitations, we designed a bifunctional cap for simultaneous TES-EEG applications. We used novel electrode materials, namely textile stimulation electrodes and dry EEG electrodes integrated in a flexible textile cap. We verified the functionality of this cap by analysing the effect of TES on visual evoked potentials (VEPs). In accordance with previous reports using standard TES, the amplitude of the N75 component was significantly decreased post-stimulation, indicating the feasibility of using this novel flexible cap for simultaneous TES and EEG. Further, we found a significant reduction of the P100 component only during TES, indicating a different brain modulation effect during and after TES. In conclusion, the novel bifunctional cap offers a novel tool for simultaneous TES-EEG applications in clinical research, therapy monitoring and closed-loop stimulation.

Increased determinism in brain electrical activity occurs in association with multiple sclerosis.

PubMed

Carrubba, Simona; Minagar, Alireza; Chesson, Andrew L; Frilot, Clifton; Marino, Andrew A

2012-04-01

Increased determinism (decreased complexity) of brain electrical activity has been associated with some brain diseases. Our objective was to determine whether a similar association occurred for multiple sclerosis (MS). Ten subjects with a relapsing-remitting course of MS who were in remission were studied; the controls were age- and gender-matched clinically normal subjects. Recurrence plots were calculated using representative electroencephalogram (EEG) epochs (1-7 seconds) from six derivations; the plots were quantified using the nonlinear variables percent recurrence (%R) and percent determinism (%D). The results were averaged over all derivations for each participant, and the means were compared between the groups. As a linear control procedure the groups were also compared using spectral analysis. The mean±SD of %R for the MS subjects was 6·6±1·3%, compared with 5·1±1·3% in the normal group (P = 0·017), indicating that brain activity in the subjects with MS was less complex, as hypothesized. The groups were not distinguishable using %D or spectral analysis. Taken together with our earlier report that %R could be used to discriminate between MS and normal subjects based on the ability to exhibit evoked potentials, the evidence suggests that complexity analysis of the EEG has potential for development as a diagnostic test for MS.

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

PubMed

Nasrallah, Fatima A; Lew, Si Kang; Low, Amanda Si-Min; Chuang, Kai-Hsiang

2014-01-01

Correlative fluctuations in functional MRI (fMRI) signals across the brain at rest have been taken as a measure of functional connectivity, but the neural basis of this resting-state MRI (rsMRI) signal is not clear. Previously, we found that the α2 adrenergic agonist, medetomidine, suppressed the rsMRI correlation dose-dependently but not the stimulus evoked activation. To understand the underlying electrophysiology and neurovascular coupling, which might be altered due to the vasoconstrictive nature of medetomidine, somatosensory evoked potential (SEP) and resting electroencephalography (EEG) were measured and correlated with corresponding BOLD signals in rat brains under three dosages of medetomidine. The SEP elicited by electrical stimulation to both forepaws was unchanged regardless of medetomidine dosage, which was consistent with the BOLD activation. Identical relationship between the SEP and BOLD signal under different medetomidine dosages indicates that the neurovascular coupling was not affected. Under resting state, EEG power was the same but a depression of inter-hemispheric EEG coherence in the gamma band was observed at higher medetomidine dosage. Different from medetomidine, both resting EEG power and BOLD power and coherence were significantly suppressed with increased isoflurane level. Such reduction was likely due to suppressed neural activity as shown by diminished SEP and BOLD activation under isoflurane, suggesting different mechanisms of losing synchrony at resting-state. Even though, similarity between electrophysiology and BOLD under stimulation and resting-state implicates a tight neurovascular coupling in both medetomidine and isoflurane. Our results confirm that medetomidine does not suppress neural activity but dissociates connectivity in the somatosensory cortex. The differential effect of medetomidine and its receptor specific action supports the neuronal origin of functional connectivity and implicates the mechanism of its sedative effect. © 2013. Published by Elsevier Inc. All rights reserved.

Investigation of the electric field distribution in the human brain based on MRI and EEG data

NASA Astrophysics Data System (ADS)

Kistenev, Yu. V.; Borisov, A. V.; Knyazkova, A. I.; Shapovalova, A. V.; Ilyasova, E. E.; Sandykova, E. A.

2018-04-01

This work is devoted to the development of the approach to restoration of the spatial-temporal distribution of electric field in the human brain. This field was estimated from the model derived from the Maxwell's equations with boundary conditions corresponding to electric potentials at the EEG electrodes, which are located on the surface of the head according to the standard "10-20" scheme. The MRI data were used for calculation of the spatial distribution of the electrical conductivity of biotissues in the human brain. The study of the electric field distribution using our approach was carried out for the healthy child and the child with autism. The research was carried out using the equipment of the Tomsk Regional Common Use Center of Tomsk State University.

Review of devices used in neuromuscular electrical stimulation for stroke rehabilitation.

PubMed

Takeda, Kotaro; Tanino, Genichi; Miyasaka, Hiroyuki

2017-01-01

Neuromuscular electrical stimulation (NMES), specifically functional electrical stimulation (FES) that compensates for voluntary motion, and therapeutic electrical stimulation (TES) aimed at muscle strengthening and recovery from paralysis are widely used in stroke rehabilitation. The electrical stimulation of muscle contraction should be synchronized with intended motion to restore paralysis. Therefore, NMES devices, which monitor electromyogram (EMG) or electroencephalogram (EEG) changes with motor intention and use them as a trigger, have been developed. Devices that modify the current intensity of NMES, based on EMG or EEG, have also been proposed. Given the diversity in devices and stimulation methods of NMES, the aim of the current review was to introduce some commercial FES and TES devices and application methods, which depend on the condition of the patient with stroke, including the degree of paralysis.

[INDIVIDUAL EVALUATION OF LORETA ABNORMALITIES IN IDIOPATHIC GENERALIZED EPILEPSY].

PubMed

Clemens, Béla; Puskás, Szilvia; Besenyei, Mónika; Kondákor, István; Hollódy, Katalin; Fogarasi, Andrós; Bense, Katalin; Emri, Miklós; Opposits Gábor; Kovács, Noémi Zsuzsanna; Fekete, István

2016-03-30

Contemporary neuroimaging methods disclosed structural and functional cerebral abnormalities in idiopathic generalized epilepsies (IGEs). However, individual electrical (EEG) abnormalities have not been evaluated yet in IGE patients. IGE patients were investigated in the drug-free condition and after 3-6 month of antiepileptic treatment. To estimate the reproducibility of qEEG variables a retrospective recruited cohort of IGE patients was investigated. 19-channel resting state EEG activity was recorded. For each patient a total of 2 minutes EEG activity was analyzed by LORETA (Low Resolution Electromagnetic Tomography). Raw LORETA values were Z-transformed and projected to a MRI template. Z-values outside within the [+3Z] to [-3Z] range were labelled as statistically abnormal. 1. In drug-free condition, 41-50% of IGE patients showed abnormal LORETA values. 2. Abnormal LORETA findings showed great inter-individual variability. 3. Most abnormal LORETA-findings were symmetrical. 4. Most maximum Z-values were localized to frontal or temporal cortex. 5. Succesfull treatment was mostly coupled with disappearence of LORETA-abnormality, persistent seizures were accompanied by persistent LORETA abnormality. 1. LORETA abnormalities detected in the untreated condition reflect seizure-generating property of the cortex in IGE patients. 2. Maximum LORETA-Z abnormalities were topographically congruent with structural abnormalities reported by other research groups. 3. LORETA might help to investigate drug effects at the whole-brain level.

Frontal Brain Electrical Activity (EEG) and Heart Rate in Response to Affective Infant-Directed (ID) Speech in 9-Month-Old Infants

ERIC Educational Resources Information Center

Santesso, Diane L.; Schmidt, Louis A.; Trainor, Laurel J.

2007-01-01

Many studies have shown that infants prefer infant-directed (ID) speech to adult-directed (AD) speech. ID speech functions to aid language learning, obtain and/or maintain an infant's attention, and create emotional communication between the infant and caregiver. We examined psychophysiological responses to ID speech that varied in affective…

Improvement of Information Transfer Rates Using a Hybrid EEG-NIRS Brain-Computer Interface with a Short Trial Length: Offline and Pseudo-Online Analyses.

PubMed

Shin, Jaeyoung; Kim, Do-Won; Müller, Klaus-Robert; Hwang, Han-Jeong

2018-06-05

Electroencephalography (EEG) and near-infrared spectroscopy (NIRS) are non-invasive neuroimaging methods that record the electrical and metabolic activity of the brain, respectively. Hybrid EEG-NIRS brain-computer interfaces (hBCIs) that use complementary EEG and NIRS information to enhance BCI performance have recently emerged to overcome the limitations of existing unimodal BCIs, such as vulnerability to motion artifacts for EEG-BCI or low temporal resolution for NIRS-BCI. However, with respect to NIRS-BCI, in order to fully induce a task-related brain activation, a relatively long trial length (≥10 s) is selected owing to the inherent hemodynamic delay that lowers the information transfer rate (ITR; bits/min). To alleviate the ITR degradation, we propose a more practical hBCI operated by intuitive mental tasks, such as mental arithmetic (MA) and word chain (WC) tasks, performed within a short trial length (5 s). In addition, the suitability of the WC as a BCI task was assessed, which has so far rarely been used in the BCI field. In this experiment, EEG and NIRS data were simultaneously recorded while participants performed MA and WC tasks without preliminary training and remained relaxed (baseline; BL). Each task was performed for 5 s, which was a shorter time than previous hBCI studies. Subsequently, a classification was performed to discriminate MA-related or WC-related brain activations from BL-related activations. By using hBCI in the offline/pseudo-online analyses, average classification accuracies of 90.0 ± 7.1/85.5 ± 8.1% and 85.8 ± 8.6/79.5 ± 13.4% for MA vs. BL and WC vs. BL, respectively, were achieved. These were significantly higher than those of the unimodal EEG- or NIRS-BCI in most cases. Given the short trial length and improved classification accuracy, the average ITRs were improved by more than 96.6% for MA vs. BL and 87.1% for WC vs. BL, respectively, compared to those reported in previous studies. The suitability of implementing a more practical hBCI based on intuitive mental tasks without preliminary training and with a shorter trial length was validated when compared to previous studies.

Constructing Carbon Fiber Motion-Detection Loops for Simultaneous EEG–fMRI

PubMed Central

Abbott, David F.; Masterton, Richard A. J.; Archer, John S.; Fleming, Steven W.; Warren, Aaron E. L.; Jackson, Graeme D.

2015-01-01

One of the most significant impediments to high-quality EEG recorded in an MRI scanner is subject motion. Availability of motion artifact sensors can substantially improve the quality of the recorded EEG. In the study of epilepsy, it can also dramatically increase the confidence that one has in discriminating true epileptiform activity from artifact. This is due both to the reduction in artifact and the ability to visually inspect the motion sensor signals when reading the EEG, revealing whether or not head motion is present. We have previously described the use of carbon fiber loops for detecting and correcting artifact in EEG acquired simultaneously with MRI. The loops, attached to the subject’s head, are electrically insulated from the scalp. They provide a simple and direct measure of specific artifact that is contaminating the EEG, including both subject motion and residual artifact arising from magnetic field gradients applied during MRI. Our previous implementation was used together with a custom-built EEG–fMRI system that differs substantially from current commercially available EEG–fMRI systems. The present technical note extends this work, describing in more detail how to construct the carbon fiber motion-detection loops, and how to interface them with a commercially available simultaneous EEG–fMRI system. We hope that the information provided may help those wishing to utilize a motion-detection/correction solution to improve the quality of EEG recorded within an MRI scanner. PMID:25601852

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

PubMed

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

2015-05-01

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

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

PubMed

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

2018-05-17

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

Decoding of Ankle Flexion and Extension from Cortical Current Sources Estimated from Non-invasive Brain Activity Recording Methods.

PubMed

Mejia Tobar, Alejandra; Hyoudou, Rikiya; Kita, Kahori; Nakamura, Tatsuhiro; Kambara, Hiroyuki; Ogata, Yousuke; Hanakawa, Takashi; Koike, Yasuharu; Yoshimura, Natsue

2017-01-01

The classification of ankle movements from non-invasive brain recordings can be applied to a brain-computer interface (BCI) to control exoskeletons, prosthesis, and functional electrical stimulators for the benefit of patients with walking impairments. In this research, ankle flexion and extension tasks at two force levels in both legs, were classified from cortical current sources estimated by a hierarchical variational Bayesian method, using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings. The hierarchical prior for the current source estimation from EEG was obtained from activated brain areas and their intensities from an fMRI group (second-level) analysis. The fMRI group analysis was performed on regions of interest defined over the primary motor cortex, the supplementary motor area, and the somatosensory area, which are well-known to contribute to movement control. A sparse logistic regression method was applied for a nine-class classification (eight active tasks and a resting control task) obtaining a mean accuracy of 65.64% for time series of current sources, estimated from the EEG and the fMRI signals using a variational Bayesian method, and a mean accuracy of 22.19% for the classification of the pre-processed of EEG sensor signals, with a chance level of 11.11%. The higher classification accuracy of current sources, when compared to EEG classification accuracy, was attributed to the high number of sources and the different signal patterns obtained in the same vertex for different motor tasks. Since the inverse filter estimation for current sources can be done offline with the present method, the present method is applicable to real-time BCIs. Finally, due to the highly enhanced spatial distribution of current sources over the brain cortex, this method has the potential to identify activation patterns to design BCIs for the control of an affected limb in patients with stroke, or BCIs from motor imagery in patients with spinal cord injury.

[French guidelines on electroencephalogram].

PubMed

André-Obadia, N; Sauleau, P; Cheliout-Heraut, F; Convers, P; Debs, R; Eisermann, M; Gavaret, M; Isnard, J; Jung, J; Kaminska, A; Kubis, N; Lemesle, M; Maillard, L; Mazzola, L; Michel, V; Montavont, A; N'Guyen, S; Navarro, V; Parain, D; Perin, B; Rosenberg, S D; Sediri, H; Soufflet, C; Szurhaj, W; Taussig, D; Touzery-de Villepin, A; Vercueil, L; Lamblin, M D

2014-12-01

Electroencephalography allows the functional analysis of electrical brain cortical activity and is the gold standard for analyzing electrophysiological processes involved in epilepsy but also in several other dysfunctions of the central nervous system. Morphological imaging yields complementary data, yet it cannot replace the essential functional analysis tool that is EEG. Furthermore, EEG has the great advantage of being non-invasive, easy to perform and allows control tests when follow-up is necessary, even at the patient's bedside. Faced with the advances in knowledge, techniques and indications, the Société de Neurophysiologie Clinique de Langue Française (SNCLF) and the Ligue Française Contre l'Épilepsie (LFCE) found it necessary to provide an update on EEG recommendations. This article will review the methodology applied to this work, refine the various topics detailed in the following chapters. It will go over the summary of recommendations for each of these chapters and underline proposals for writing an EEG report. Some questions could not be answered by the review of the literature; in those cases, an expert advice was given by the working and reading groups in addition to the guidelines. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Evaluation of cerebral function after carotid endarterectomy.

PubMed

Uclés, P; Almárcegui, C; Lorente, S; Romero, F; Marco, M

1997-05-01

Neuroimaging methods have failed to disclose correlation between degree of cerebral atrophy and blood flow in carotid artery stenosis patients. Moreover, intellectual improvement after carotid endarterectomy does not correlate fully with neuroimaging data in such patients. We performed brain electrical activity mapping and psychological testing before and 4 weeks after operation in 28 patients with symptomatic, high-grade, carotid stenosis. Postoperatively, electroencephalographic (EEG) mean frequency and absolute theta power improved significantly (p < 0.01). Mean frequency increased >1 Hz in most areas while power decreased dramatically, mainly because of resolution of high-voltage foci in 8 patients. Differences were conspicuous in both frontal lobes irrespective of the operated side, which suggests changes in perfusion affecting the whole brain. This is a positive effect of endarterectomy. Mini-Mental test and Set Test for verbal fluency had a positive correlation with the qEEG changes. Quantitative EEG as a measure of cerebral function has disclosed discriminative improvement in the early postoperative period. Our results support the thesis of improvement subsequent to endarterectomy.

Hypoglycemia-Induced Changes in the Electroencephalogram

PubMed Central

Blaabjerg, Lykke; Juhl, Claus B.

2016-01-01

Hypoglycemia is defined by an abnormally low blood glucose level. The condition develops when rates of glucose entry into the systematic circulation are reduced relative to the glucose uptake by the tissues. A cardinal manifestation of hypoglycemia arises from inadequate supply of glucose to the brain, where glucose is the primary metabolic fuel. The brain is one of the first organs to be affected by hypoglycemia. Shortage of glucose in the brain, or neuroglycopenia, results in a gradual loss of cognitive functions causing slower reaction time, blurred speech, loss of consciousness, seizures, and ultimately death, as the hypoglycemia progresses. The electrical activity in the brain represents the metabolic state of the brain cells and can be measured by electroencephalography (EEG). An association between hypoglycemia and changes in the EEG has been demonstrated, although blood glucose levels alone do not seem to predict neuroglycopenia. This review provides an overview of the current literature regarding changes in the EEG during episodes of low blood glucose. PMID:27464753

Phase-Locked Loop for Precisely Timed Acoustic Stimulation during Sleep

PubMed Central

Santostasi, Giovanni; Malkani, Roneil; Riedner, Brady; Bellesi, Michele; Tononi, Giulio; Paller, Ken A.; Zee, Phyllis C.

2016-01-01

Background A Brain-Computer Interface could potentially enhance the various benefits of sleep. New Method We describe a strategy for enhancing slow-wave sleep (SWS) by stimulating the sleeping brain with periodic acoustic stimuli that produce resonance in the form of enhanced slow-wave activity in the electroencephalogram (EEG). The system delivers each acoustic stimulus at a particular phase of an electrophysiological rhythm using a Phase-Locked Loop (PLL). Results The PLL is computationally economical and well suited to follow and predict the temporal behavior of the EEG during slow-wave sleep. Comparison with Existing Methods Acoustic stimulation methods may be able to enhance SWS without the risks inherent in electrical stimulation or pharmacological methods. The PLL method differs from other acoustic stimulation methods that are based on detecting a single slow wave rather than modeling slow-wave activity over an extended period of time. Conclusions By providing real-time estimates of the phase of ongoing EEG oscillations, the PLL can rapidly adjust to physiological changes, thus opening up new possibilities to study brain dynamics during sleep. Future application of these methods hold promise for enhancing sleep quality and associated daytime behavior and improving physiologic function. PMID:26617321

Write, read and answer emails with a dry 'n' wireless brain-computer interface system.

PubMed

Pinegger, Andreas; Deckert, Lisa; Halder, Sebastian; Barry, Norbert; Faller, Josef; Käthner, Ivo; Hintermüller, Christoph; Wriessnegger, Selina C; Kübler, Andrea; Müller-Putz, Gernot R

2014-01-01

Brain-computer interface (BCI) users can control very complex applications such as multimedia players or even web browsers. Therefore, different biosignal acquisition systems are available to noninvasively measure the electrical activity of the brain, the electroencephalogram (EEG). To make BCIs more practical, hardware and software are nowadays designed more user centered and user friendly. In this paper we evaluated one of the latest innovations in the area of BCI: A wireless EEG amplifier with dry electrode technology combined with a web browser which enables BCI users to use standard webmail. With this system ten volunteers performed a daily life task: Write, read and answer an email. Experimental results of this study demonstrate the power of the introduced BCI system.

Review of devices used in neuromuscular electrical stimulation for stroke rehabilitation

PubMed Central

Takeda, Kotaro; Tanino, Genichi; Miyasaka, Hiroyuki

2017-01-01

Neuromuscular electrical stimulation (NMES), specifically functional electrical stimulation (FES) that compensates for voluntary motion, and therapeutic electrical stimulation (TES) aimed at muscle strengthening and recovery from paralysis are widely used in stroke rehabilitation. The electrical stimulation of muscle contraction should be synchronized with intended motion to restore paralysis. Therefore, NMES devices, which monitor electromyogram (EMG) or electroencephalogram (EEG) changes with motor intention and use them as a trigger, have been developed. Devices that modify the current intensity of NMES, based on EMG or EEG, have also been proposed. Given the diversity in devices and stimulation methods of NMES, the aim of the current review was to introduce some commercial FES and TES devices and application methods, which depend on the condition of the patient with stroke, including the degree of paralysis. PMID:28883745

Electrical source localization by LORETA in patients with epilepsy: Confirmation by postoperative MRI

PubMed Central

Akdeniz, Gülsüm

2016-01-01

Background: Few studies have been conducted that have compared electrical source localization (ESL) results obtained by analyzing ictal patterns in scalp electroencephalogram (EEG) with the brain areas that are found to be responsible for seizures using other brain imaging techniques. Additionally, adequate studies have not been performed to confirm the accuracy of ESL methods. Materials and Methods: In this study, ESL was conducted using LORETA (Low Resolution Brain Electromagnetic Tomography) in 9 patients with lesions apparent on magnetic resonance imaging (MRI) and in 6 patients who did not exhibit lesions on their MRIs. EEGs of patients who underwent surgery for epilepsy and had follow-ups for at least 1 year after operations were analyzed for ictal spike, rhythmic, paroxysmal fast, and obscured EEG activities. Epileptogenic zones identified in postoperative MRIs were then compared with localizations obtained by LORETA model we employed. Results: We found that brain areas determined via ESL were in concordance with resected brain areas for 13 of the 15 patients evaluated, and those 13 patients were post-operatively determined as being seizure-free. Conclusion: ESL, which is a noninvasive technique, may contribute to the correct delineation of epileptogenic zones in patients who will eventually undergo surgery to treat epilepsy, (regardless of neuroimaging status). Moreover, ESL may aid in deciding on the number and localization of intracranial electrodes to be used in patients who are candidates for invasive recording. PMID:27011626

Electrical source localization by LORETA in patients with epilepsy: Confirmation by postoperative MRI.

PubMed

Akdeniz, Gülsüm

2016-01-01

Few studies have been conducted that have compared electrical source localization (ESL) results obtained by analyzing ictal patterns in scalp electroencephalogram (EEG) with the brain areas that are found to be responsible for seizures using other brain imaging techniques. Additionally, adequate studies have not been performed to confirm the accuracy of ESL methods. In this study, ESL was conducted using LORETA (Low Resolution Brain Electromagnetic Tomography) in 9 patients with lesions apparent on magnetic resonance imaging (MRI) and in 6 patients who did not exhibit lesions on their MRIs. EEGs of patients who underwent surgery for epilepsy and had follow-ups for at least 1 year after operations were analyzed for ictal spike, rhythmic, paroxysmal fast, and obscured EEG activities. Epileptogenic zones identified in postoperative MRIs were then compared with localizations obtained by LORETA model we employed. We found that brain areas determined via ESL were in concordance with resected brain areas for 13 of the 15 patients evaluated, and those 13 patients were post-operatively determined as being seizure-free. ESL, which is a noninvasive technique, may contribute to the correct delineation of epileptogenic zones in patients who will eventually undergo surgery to treat epilepsy, (regardless of neuroimaging status). Moreover, ESL may aid in deciding on the number and localization of intracranial electrodes to be used in patients who are candidates for invasive recording.

Spontaneous pre-stimulus fluctuations in the activity of right fronto-parietal areas influence inhibitory control performance

PubMed Central

Chavan, Camille F.; Manuel, Aurelie L.; Mouthon, Michael; Spierer, Lucas

2013-01-01

Inhibitory control refers to the ability to suppress planned or ongoing cognitive or motor processes. Electrophysiological indices of inhibitory control failure have been found to manifest even before the presentation of the stimuli triggering the inhibition, suggesting that pre-stimulus brain-states modulate inhibition performance. However, previous electrophysiological investigations on the state-dependency of inhibitory control were based on averaged event-related potentials (ERPs), a method eliminating the variability in the ongoing brain activity not time-locked to the event of interest. These studies thus left unresolved whether spontaneous variations in the brain-state immediately preceding unpredictable inhibition-triggering stimuli also influence inhibitory control performance. To address this question, we applied single-trial EEG topographic analyses on the time interval immediately preceding NoGo stimuli in conditions where the responses to NoGo trials were correctly inhibited [correct rejection (CR)] vs. committed [false alarms (FAs)] during an auditory spatial Go/NoGo task. We found a specific configuration of the EEG voltage field manifesting more frequently before correctly inhibited responses to NoGo stimuli than before FAs. There was no evidence for an EEG topography occurring more frequently before FAs than before CR. The visualization of distributed electrical source estimations of the EEG topography preceding successful response inhibition suggested that it resulted from the activity of a right fronto-parietal brain network. Our results suggest that the fluctuations in the ongoing brain activity immediately preceding stimulus presentation contribute to the behavioral outcomes during an inhibitory control task. Our results further suggest that the state-dependency of sensory-cognitive processing might not only concern perceptual processes, but also high-order, top-down inhibitory control mechanisms. PMID:23761747

EEG source analysis of data from paralysed subjects

NASA Astrophysics Data System (ADS)

Carabali, Carmen A.; Willoughby, John O.; Fitzgibbon, Sean P.; Grummett, Tyler; Lewis, Trent; DeLosAngeles, Dylan; Pope, Kenneth J.

2015-12-01

One of the limitations of Encephalography (EEG) data is its quality, as it is usually contaminated with electric signal from muscle. This research intends to study results of two EEG source analysis methods applied to scalp recordings taken in paralysis and in normal conditions during the performance of a cognitive task. The aim is to determinate which types of analysis are appropriate for dealing with EEG data containing myogenic components. The data used are the scalp recordings of six subjects in normal conditions and during paralysis while performing different cognitive tasks including the oddball task which is the object of this research. The data were pre-processed by filtering it and correcting artefact, then, epochs of one second long for targets and distractors were extracted. Distributed source analysis was performed in BESA Research 6.0, using its results and information from the literature, 9 ideal locations for source dipoles were identified. The nine dipoles were used to perform discrete source analysis, fitting them to the averaged epochs for obtaining source waveforms. The results were statistically analysed comparing the outcomes before and after the subjects were paralysed. Finally, frequency analysis was performed for better explain the results. The findings were that distributed source analysis could produce confounded results for EEG contaminated with myogenic signals, conversely, statistical analysis of the results from discrete source analysis showed that this method could help for dealing with EEG data contaminated with muscle electrical signal.

A capacitive, biocompatible and adhesive electrode for long-term and cap-free monitoring of EEG signals.

PubMed

Lee, Seung Min; Kim, Jeong Hun; Byeon, Hang Jin; Choi, Yoon Young; Park, Kwang Suk; Lee, Sang-Hoon

2013-06-01

Long-term electroencephalogram (EEG) monitoring broadens EEG applications to various areas, but it requires cap-free recording of EEG signals. Our objective here is to develop a capacitive, small-sized, adhesive and biocompatible electrode for the cap-free and long-term EEG monitoring. We have developed an electrode made of polydimethylsiloxane (PDMS) and adhesive PDMS for EEG monitoring. This electrode can be attached to a hairy scalp and be completely hidden by the hair. We tested its electrical and mechanical (adhesive) properties by measuring voltage gain to frequency and adhesive force using 30 repeat cycles of the attachment and detachment test. Electrode performance on EEG was evaluated by alpha rhythm detection and measuring steady state visually evoked potential and N100 auditory evoked potential. We observed the successful recording of alpha rhythm and evoked signals to diverse stimuli with high signal quality. The biocompatibility of the electrode was verified and a survey found that the electrode was comfortable and convenient to wear. These results indicate that the proposed EEG electrode is suitable and convenient for long term EEG monitoring.

Detection of Intracranial Signatures of Interictal Epileptiform Discharges from Concurrent Scalp EEG.

PubMed

Spyrou, Loukianos; Martín-Lopez, David; Valentín, Antonio; Alarcón, Gonzalo; Sanei, Saeid

2016-06-01

Interictal epileptiform discharges (IEDs) are transient neural electrical activities that occur in the brain of patients with epilepsy. A problem with the inspection of IEDs from the scalp electroencephalogram (sEEG) is that for a subset of epileptic patients, there are no visually discernible IEDs on the scalp, rendering the above procedures ineffective, both for detection purposes and algorithm evaluation. On the other hand, intracranially placed electrodes yield a much higher incidence of visible IEDs as compared to concurrent scalp electrodes. In this work, we utilize concurrent scalp and intracranial EEG (iEEG) from a group of temporal lobe epilepsy (TLE) patients with low number of scalp-visible IEDs. The aim is to determine whether by considering the timing information of the IEDs from iEEG, the resulting concurrent sEEG contains enough information for the IEDs to be reliably distinguished from non-IED segments. We develop an automatic detection algorithm which is tested in a leave-subject-out fashion, where each test subject's detection algorithm is based on the other patients' data. The algorithm obtained a [Formula: see text] accuracy in recognizing scalp IED from non-IED segments with [Formula: see text] accuracy when trained and tested on the same subject. Also, it was able to identify nonscalp-visible IED events for most patients with a low number of false positive detections. Our results represent a proof of concept that IED information for TLE patients is contained in scalp EEG even if they are not visually identifiable and also that between subject differences in the IED topology and shape are small enough such that a generic algorithm can be used.

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

PubMed

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

2016-01-01

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

Electric field encephalography for brain activity monitoring.

PubMed

Versek, Craig William; Frasca, Tyler; Zhou, Jianlin; Chowdhury, Kaushik; Sridhar, Srinivas

2018-05-11

Objective - We describe an early-stage prototype of a new wireless electrophysiological sensor system, called NeuroDot, which can measure neuroelectric potentials and fields at the scalp in a new modality called Electric Field Encephalography (EFEG). We aim to establish the physical validity of the EFEG modality, and examine some of its properties and relative merits compared to EEG. Approach - We designed a wireless neuroelectric measurement device based on the Texas Instrument ADS1299 Analog Front End platform and a sensor montage, using custom electrodes, to simultaneously measure EFEG and spatially averaged EEG over a localized patch of the scalp (2cm x 2cm). The signal properties of each modality were compared across tests of noise floor, Berger effect, steady-state Visually Evoked Potential (ssVEP), signal-to-noise ratio (SNR), and others. In order to compare EFEG to EEG modalities in the frequency domain, we use a novel technique to compute spectral power densities and derive narrow-band SNR estimates for ssVEP signals. A simple binary choice brain-computer-interface (BCI) concept based on ssVEP is evaluated. Also, we present examples of high quality recording of transient Visually Evoked Potentials and Fields (tVEPF) that could be used for neurological studies. Main results - We demonstrate the capability of the NeuroDot system to record high quality EEG signals comparable to some recent clinical and research grade systems on the market. We show that the locally-referenced EFEG metric is resistant to certain types of movement artifacts. In some ssVEP based measurements, the EFEG modality shows promising results, demonstrating superior signal to noise ratios than the same recording processed as an analogous EEG signal. We show that by using EFEG based ssVEP SNR estimates to perform a binary classification in a model BCI, the optimal information transfer rate (ITR) can be raised from 15 to 30 bits per minute - though these preliminary results are likely sensitive to inter-subject variations and choice of scalp locations, so require further investigation. Significance - Enhancement of ssVEP SNR using EFEG has the potential to improve visually based BCIs and diagnostic paradigms. The time domain analysis of tVEPF signals shows robust features in the electric field components that might have clinical relevance beyond classical VEP approaches. . © 2018 IOP Publishing Ltd.

Neurofeedback Training for BCI Control

NASA Astrophysics Data System (ADS)

Neuper, Christa; Pfurtscheller, Gert

Brain-computer interface (BCI) systems detect changes in brain signals that reflect human intention, then translate these signals to control monitors or external devices (for a comprehensive review, see [1]). BCIs typically measure electrical signals resulting from neural firing (i.e. neuronal action potentials, Electroencephalogram (ECoG), or Electroencephalogram (EEG)). Sophisticated pattern recognition and classification algorithms convert neural activity into the required control signals. BCI research has focused heavily on developing powerful signal processing and machine learning techniques to accurately classify neural activity [2-4].

Reversing pathologically increased EEG power by acoustic coordinated reset neuromodulation

PubMed Central

Adamchic, Ilya; Toth, Timea; Hauptmann, Christian; Tass, Peter Alexander

2014-01-01

Acoustic Coordinated Reset (CR) neuromodulation is a patterned stimulation with tones adjusted to the patient's dominant tinnitus frequency, which aims at desynchronizing pathological neuronal synchronization. In a recent proof-of-concept study, CR therapy, delivered 4–6 h/day more than 12 weeks, induced a significant clinical improvement along with a significant long-lasting decrease of pathological oscillatory power in the low frequency as well as γ band and an increase of the α power in a network of tinnitus-related brain areas. As yet, it remains unclear whether CR shifts the brain activity toward physiological levels or whether it induces clinically beneficial, but nonetheless abnormal electroencephalographic (EEG) patterns, for example excessively decreased δ and/or γ. Here, we compared the patients' spontaneous EEG data at baseline as well as after 12 weeks of CR therapy with the spontaneous EEG of healthy controls by means of Brain Electrical Source Analysis source montage and standardized low-resolution brain electromagnetic tomography techniques. The relationship between changes in EEG power and clinical scores was investigated using a partial least squares approach. In this way, we show that acoustic CR neuromodulation leads to a normalization of the oscillatory power in the tinnitus-related network of brain areas, most prominently in temporal regions. A positive association was found between the changes in tinnitus severity and the normalization of δ and γ power in the temporal, parietal, and cingulate cortical regions. Our findings demonstrate a widespread CR-induced normalization of EEG power, significantly associated with a reduction of tinnitus severity. PMID:23907785

A Pharmacokinetics-Neural Mass Model (PK-NMM) for the Simulation of EEG Activity during Propofol Anesthesia

PubMed Central

Liang, Zhenhu; Duan, Xuejing; Su, Cui; Voss, Logan; Sleigh, Jamie; Li, Xiaoli

2015-01-01

Modeling the effects of anesthetic drugs on brain activity is very helpful in understanding anesthesia mechanisms. The aim of this study was to set up a combined model to relate actual drug levels to EEG dynamics and behavioral states during propofol-induced anesthesia. We proposed a new combined theoretical model based on a pharmacokinetics (PK) model and a neural mass model (NMM), which we termed PK-NMM—with the aim of simulating electroencephalogram (EEG) activity during propofol-induced general anesthesia. The PK model was used to derive propofol effect-site drug concentrations (C eff) based on the actual drug infusion regimen. The NMM model took C eff as the control parameter to produce simulated EEG-like (sEEG) data. For comparison, we used real prefrontal EEG (rEEG) data of nine volunteers undergoing propofol anesthesia from a previous experiment. To see how well the sEEG could describe the dynamic changes of neural activity during anesthesia, the rEEG data and the sEEG data were compared with respect to: power-frequency plots; nonlinear exponent (permutation entropy (PE)); and bispectral SynchFastSlow (SFS) parameters. We found that the PK-NMM model was able to reproduce anesthesia EEG-like signals based on the estimated drug concentration and patients’ condition. The frequency spectrum indicated that the frequency power peak of the sEEG moved towards the low frequency band as anesthesia deepened. Different anesthetic states could be differentiated by the PE index. The correlation coefficient of PE was 0.80±0.13 (mean±standard deviation) between rEEG and sEEG for all subjects. Additionally, SFS could track the depth of anesthesia and the SFS of rEEG and sEEG were highly correlated with a correlation coefficient of 0.77±0.13. The PK-NMM model could simulate EEG activity and might be a useful tool for understanding the action of propofol on brain activity. PMID:26720495

Topographic mapping of electroencephalography coherence in hypnagogic state.

PubMed

Tanaka, H; Hayashi, M; Hori, T

1998-04-01

The present study examined the topographic characteristics of hypnagogic electroencephalography (EEG), using topographic mapping of EEG power and coherence corresponding to nine EEG stages (Hori's hypnagogic EEG stages). EEG stages 1 and 2, the EEG stages 3-8, and the EEG stage 9 each correspond with standard sleep stage W, 1 and 2, respectively. The dominant topographic components of delta and theta activities increased clearly from the vertex sharp-wave stage (the EEG stages 6 and 7) in the anterior-central areas. The dominant topographic component of alpha 3 activities increased clearly from the EEG stage 9 in the anterior-central areas. The dominant topographic component of sigma activities increased clearly from the EEG stage 8 in the central-parietal area. These results suggested basic sleep process might start before the onset of sleep stage 2 or of the manually scored spindles.

Visual brain activity patterns classification with simultaneous EEG-fMRI: A multimodal approach.

PubMed

Ahmad, Rana Fayyaz; Malik, Aamir Saeed; Kamel, Nidal; Reza, Faruque; Amin, Hafeez Ullah; Hussain, Muhammad

2017-01-01

Classification of the visual information from the brain activity data is a challenging task. Many studies reported in the literature are based on the brain activity patterns using either fMRI or EEG/MEG only. EEG and fMRI considered as two complementary neuroimaging modalities in terms of their temporal and spatial resolution to map the brain activity. For getting a high spatial and temporal resolution of the brain at the same time, simultaneous EEG-fMRI seems to be fruitful. In this article, we propose a new method based on simultaneous EEG-fMRI data and machine learning approach to classify the visual brain activity patterns. We acquired EEG-fMRI data simultaneously on the ten healthy human participants by showing them visual stimuli. Data fusion approach is used to merge EEG and fMRI data. Machine learning classifier is used for the classification purposes. Results showed that superior classification performance has been achieved with simultaneous EEG-fMRI data as compared to the EEG and fMRI data standalone. This shows that multimodal approach improved the classification accuracy results as compared with other approaches reported in the literature. The proposed simultaneous EEG-fMRI approach for classifying the brain activity patterns can be helpful to predict or fully decode the brain activity patterns.

Technical and clinical analysis of microEEG: a miniature wireless EEG device designed to record high-quality EEG in the emergency department

PubMed Central

2012-01-01

Background We describe and characterize the performance of microEEG compared to that of a commercially available and widely used clinical EEG machine. microEEG is a portable, battery-operated, wireless EEG device, developed by Bio-Signal Group to overcome the obstacles to routine use of EEG in emergency departments (EDs). Methods The microEEG was used to obtain EEGs from healthy volunteers in the EEG laboratory and ED. The standard system was used to obtain EEGs from healthy volunteers in the EEG laboratory, and studies recorded from patients in the ED or ICU were also used for comparison. In one experiment, a signal splitter was used to record simultaneous microEEG and standard EEG from the same electrodes. Results EEG signal analysis techniques indicated good agreement between microEEG and the standard system in 66 EEGs recorded in the EEG laboratory and the ED. In the simultaneous recording the microEEG and standard system signals differed only in a smaller amount of 60 Hz noise in the microEEG signal. In a blinded review by a board-certified clinical neurophysiologist, differences in technical quality or interpretability were insignificant between standard recordings in the EEG laboratory and microEEG recordings from standard or electrode cap electrodes in the ED or EEG laboratory. The microEEG data recording characteristics such as analog-to-digital conversion resolution (16 bits), input impedance (>100MΩ), and common-mode rejection ratio (85 dB) are similar to those of commercially available systems, although the microEEG is many times smaller (88 g and 9.4 × 4.4 × 3.8 cm). Conclusions Our results suggest that the technical qualities of microEEG are non-inferior to a standard commercially available EEG recording device. EEG in the ED is an unmet medical need due to space and time constraints, high levels of ambient electrical noise, and the cost of 24/7 EEG technologist availability. This study suggests that using microEEG with an electrode cap that can be applied easily and quickly can surmount these obstacles without compromising technical quality. PMID:23006616

Ultra-slow mechanical stimulation of olfactory epithelium modulates consciousness by slowing cerebral rhythms in humans.

PubMed

Piarulli, A; Zaccaro, A; Laurino, M; Menicucci, D; De Vito, A; Bruschini, L; Berrettini, S; Bergamasco, M; Laureys, S; Gemignani, A

2018-04-26

The coupling between respiration and neural activity within olfactory areas and hippocampus has recently been unambiguously demonstrated, its neurophysiological basis sustained by the well-assessed mechanical sensitivity of the olfactory epithelium. We herein hypothesize that this coupling reverberates to the whole brain, possibly modulating the subject's behavior and state of consciousness. The olfactory epithelium of 12 healthy subjects was stimulated with periodical odorless air-delivery (frequency 0.05 Hz, 8 s on, 12 off). Cortical electrical activity (High Density-EEG) and perceived state of consciousness have been studied. The stimulation induced i) an enhancement of delta-theta EEG activity over the whole cortex mainly involving the Limbic System and Default Mode Network structures, ii) a reversal of the overall information flow directionality from wake-like postero-anterior to NREM sleep-like antero-posterior, iii) the perception of having experienced an Altered State of Consciousness. These findings could shed further light via a neurophenomenological approach on the links between respiration, cerebral activity and subjective experience, suggesting a plausible neurophysiological basis for interpreting altered states of consciousness induced by respiration-based meditative practices.

Reduced Cortical Activity Impairs Development and Plasticity after Neonatal Hypoxia Ischemia

PubMed Central

Ranasinghe, Sumudu; Or, Grace; Wang, Eric Y.; Ievins, Aiva; McLean, Merritt A.; Niell, Cristopher M.; Chau, Vann; Wong, Peter K. H.; Glass, Hannah C.; Sullivan, Joseph

2015-01-01

Survivors of preterm birth are at high risk of pervasive cognitive and learning impairments, suggesting disrupted early brain development. The limits of viability for preterm birth encompass the third trimester of pregnancy, a “precritical period” of activity-dependent development characterized by the onset of spontaneous and evoked patterned electrical activity that drives neuronal maturation and formation of cortical circuits. Reduced background activity on electroencephalogram (EEG) is a sensitive marker of brain injury in human preterm infants that predicts poor neurodevelopmental outcome. We studied a rodent model of very early hypoxic–ischemic brain injury to investigate effects of injury on both general background and specific patterns of cortical activity measured with EEG. EEG background activity is depressed transiently after moderate hypoxia–ischemia with associated loss of spindle bursts. Depressed activity, in turn, is associated with delayed expression of glutamate receptor subunits and transporters. Cortical pyramidal neurons show reduced dendrite development and spine formation. Complementing previous observations in this model of impaired visual cortical plasticity, we find reduced somatosensory whisker barrel plasticity. Finally, EEG recordings from human premature newborns with brain injury demonstrate similar depressed background activity and loss of bursts in the spindle frequency band. Together, these findings suggest that abnormal development after early brain injury may result in part from disruption of specific forms of brain activity necessary for activity-dependent circuit development. SIGNIFICANCE STATEMENT Preterm birth and term birth asphyxia result in brain injury from inadequate oxygen delivery and constitute a major and growing worldwide health problem. Poor outcomes are noted in a majority of very premature (<25 weeks gestation) newborns, resulting in death or life-long morbidity with motor, sensory, learning, behavioral, and language disabilities that limit academic achievement and well-being. Limited progress has been made to develop therapies that improve neurologic outcomes. The overall objective of this study is to understand the effect of early brain injury on activity-dependent brain development and cortical plasticity to develop new treatments that will optimize repair and recovery after brain injury. PMID:26311776

Differences in quantitative EEG between frontotemporal dementia and Alzheimer's disease as revealed by LORETA.

PubMed

Nishida, K; Yoshimura, M; Isotani, T; Yoshida, T; Kitaura, Y; Saito, A; Mii, H; Kato, M; Takekita, Y; Suwa, A; Morita, S; Kinoshita, T

2011-09-01

To determine the electrophysiological characteristics of frontotemporal dementia (FTD) and the distinction with Alzheimer's disease (AD). We performed analyses of global field power (GFP) which is a measure of whole brain electric field strength, and EEG neuroimaging analyses with sLORETA (standardized low resolution electromagnetic tomography), in the mild stages of FTD (n = 19; mean age = 68.11 ± 7.77) and AD (n = 19; mean age = 69.42 ± 9.57) patients, and normal control (NC) subjects (n = 22; mean age = 66.13 ± 6.02). In the GFP analysis, significant group effects were observed in the delta (1.5-6.0 Hz), alpha1 (8.5-10.0 Hz), and beta1 (12.5-18.0 Hz) bands. In sLORETA analysis, differences in activity were observed in the alpha1 band (NC > FTD) in the orbital frontal and temporal lobe, in the delta band (AD>NC) in widespread areas including the frontal lobe, and in the beta1 band (FTD > AD) in the parietal lobe and sensorimotor area. Differential patterns of brain regions and EEG frequency bands were observed between the FTD and AD groups in terms of pathological activity. FTD and AD patients in the early stages displayed different patterns in the cortical localization of oscillatory activity across different frequency bands. Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

A novel approach for the elimination of artefacts from EEG signals employing an improved Artificial Immune System algorithm

NASA Astrophysics Data System (ADS)

Suja Priyadharsini, S.; Edward Rajan, S.; Femilin Sheniha, S.

2016-03-01

Electroencephalogram (EEG) is the recording of electrical activities of the brain. It is contaminated by other biological signals, such as cardiac signal (electrocardiogram), signals generated by eye movement/eye blinks (electrooculogram) and muscular artefact signal (electromyogram), called artefacts. Optimisation is an important tool for solving many real-world problems. In the proposed work, artefact removal, based on the adaptive neuro-fuzzy inference system (ANFIS) is employed, by optimising the parameters of ANFIS. Artificial Immune System (AIS) algorithm is used to optimise the parameters of ANFIS (ANFIS-AIS). Implementation results depict that ANFIS-AIS is effective in removing artefacts from EEG signal than ANFIS. Furthermore, in the proposed work, improved AIS (IAIS) is developed by including suitable selection processes in the AIS algorithm. The performance of the proposed method IAIS is compared with AIS and with genetic algorithm (GA). Measures such as signal-to-noise ratio, mean square error (MSE) value, correlation coefficient, power spectrum density plot and convergence time are used for analysing the performance of the proposed method. From the results, it is found that the IAIS algorithm converges faster than the AIS and performs better than the AIS and GA. Hence, IAIS tuned ANFIS (ANFIS-IAIS) is effective in removing artefacts from EEG signals.

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

PubMed

Ueda, Jun; Kawamoto, Michi; Hikiami, Ryota; Ishii, Junko; Yoshimura, Hajime; Matsumoto, Riki; Kohara, Nobuo

2017-12-01

Anti-NMDA receptor encephalitis is a paraneoplastic encephalitis characterised by psychiatric features, involuntary movement, and autonomic instability. Various EEG findings in patients with anti-NMDA receptor encephalitis have been reported, however, the correlation between the EEG findings and clinical course of anti-NMDA receptor encephalitis remains unclear. We describe a patient with anti-NMDA receptor encephalitis with a focus on EEG findings, which included: status epilepticus, generalised rhythmic delta activity, excess beta activity, extreme delta brush, and paroxysmal alpha activity upon arousal from sleep, which we term"arousal alpha pattern". Initially, status epilepticus was observed on the EEG when the patient was comatose with conjugate deviation. The EEG then indicated excess beta activity, followed by the emergence of continuous slow activity, including generalised rhythmic delta activity and extreme delta brush, in the most severe phase. Slow activity gradually faded in parallel with clinical amelioration. Excess beta activity persisted, even after the patient became almost independent in daily activities, and finally disappeared with full recovery. In summary, our patient with anti-NMDA receptor encephalitis demonstrated slow activity on the EEG, including extreme delta brush during the most severe phase, which gradually faded in parallel with clinical amelioration, with excess beta activity persisting into the recovery phase.

Electrical Stimulation Modulates High γ Activity and Human Memory Performance

PubMed Central

Berry, Brent M.; Miller, Laura R.; Khadjevand, Fatemeh; Ezzyat, Youssef; Wanda, Paul; Sperling, Michael R.; Lega, Bradley; Stead, S. Matt

2018-01-01

Direct electrical stimulation of the brain has emerged as a powerful treatment for multiple neurological diseases, and as a potential technique to enhance human cognition. Despite its application in a range of brain disorders, it remains unclear how stimulation of discrete brain areas affects memory performance and the underlying electrophysiological activities. Here, we investigated the effect of direct electrical stimulation in four brain regions known to support declarative memory: hippocampus (HP), parahippocampal region (PH) neocortex, prefrontal cortex (PF), and lateral temporal cortex (TC). Intracranial EEG recordings with stimulation were collected from 22 patients during performance of verbal memory tasks. We found that high γ (62–118 Hz) activity induced by word presentation was modulated by electrical stimulation. This modulatory effect was greatest for trials with “poor” memory encoding. The high γ modulation correlated with the behavioral effect of stimulation in a given brain region: it was negative, i.e., the induced high γ activity was decreased, in the regions where stimulation decreased memory performance, and positive in the lateral TC where memory enhancement was observed. Our results suggest that the effect of electrical stimulation on high γ activity induced by word presentation may be a useful biomarker for mapping memory networks and guiding therapeutic brain stimulation. PMID:29404403

EEG activity during estral cycle in the rat.

PubMed

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

1992-10-01

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

Back-Projection Cortical Potential Imaging: Theory and Results.

PubMed

Haor, Dror; Shavit, Reuven; Shapiro, Moshe; Geva, Amir B

2017-07-01

Electroencephalography (EEG) is the single brain monitoring technique that is non-invasive, portable, passive, exhibits high-temporal resolution, and gives a directmeasurement of the scalp electrical potential. Amajor disadvantage of the EEG is its low-spatial resolution, which is the result of the low-conductive skull that "smears" the currents coming from within the brain. Recording brain activity with both high temporal and spatial resolution is crucial for the localization of confined brain activations and the study of brainmechanismfunctionality, whichis then followed by diagnosis of brain-related diseases. In this paper, a new cortical potential imaging (CPI) method is presented. The new method gives an estimation of the electrical activity on the cortex surface and thus removes the "smearing effect" caused by the skull. The scalp potentials are back-projected CPI (BP-CPI) onto the cortex surface by building a well-posed problem to the Laplace equation that is solved by means of the finite elements method on a realistic head model. A unique solution to the CPI problem is obtained by introducing a cortical normal current estimation technique. The technique is based on the same mechanism used in the well-known surface Laplacian calculation, followed by a scalp-cortex back-projection routine. The BP-CPI passed four stages of validation, including validation on spherical and realistic head models, probabilistic analysis (Monte Carlo simulation), and noise sensitivity tests. In addition, the BP-CPI was compared with the minimum norm estimate CPI approach and found superior for multi-source cortical potential distributions with very good estimation results (CC >0.97) on a realistic head model in the regions of interest, for two representative cases. The BP-CPI can be easily incorporated in different monitoring tools and help researchers by maintaining an accurate estimation for the cortical potential of ongoing or event-related potentials in order to have better neurological inferences from the EEG.

Understanding the impact of TV commercials: electrical neuroimaging.

PubMed

Vecchiato, Giovanni; Kong, Wanzeng; Maglione, Anton Giulio; Wei, Daming

2012-01-01

Today, there is a greater interest in the marketing world in using neuroimaging tools to evaluate the efficacy of TV commercials. This field of research is known as neuromarketing. In this article, we illustrate some applications of electrical neuroimaging, a discipline that uses electroencephalography (EEG) and intensive signal processing techniques for the evaluation of marketing stimuli. We also show how the proper usage of these methodologies can provide information related to memorization and attention while people are watching marketing-relevant stimuli. We note that temporal and frequency patterns of EEG signals are able to provide possible descriptors that convey information about the cognitive process in subjects observing commercial advertisements (ads). Such information could be unobtainable through common tools used in standard marketing research. Evidence of this research shows how EEG methodologies could be employed to better design new products that marketers are going to promote and to analyze the global impact of video commercials already broadcast on TV.

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

PubMed Central

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 understanding of the goal of object-directed motor acts (mirror mechanism). The successive right hemisphere activation indicates that this hemisphere plays an important role in understanding the intention of others. PMID:20730095

Study of emotion-based neurocardiology through wearable systems

NASA Astrophysics Data System (ADS)

Ramasamy, Mouli; Varadan, Vijay

2016-04-01

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 phenomena. 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 modalities 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.

[Bioelectric brain activity in patients with neurotic disorders].

PubMed

Golubev, V L; Korabel'nikova, E A; Kudriavtseva, E P

2006-01-01

Seventy-three patients with neurotic disorders, aged 14-35 years, and 33 healthy controls have been examined using electroencephalographic method with spectral analysis of EEG, which has been conducted on the Brain Surfing system by the algorithm of direct Fourier transformation. The patients had changes of brain electric activity manifesting as insufficiency of thalamo-cortical synchronizing systems that caused an excessive activating effect of reticular formation on the cortex realized through extrathalamic reticular cortical and septo-hippocampal activation paths. Determinative in electrophysiological brain organization was the theta-rhythm, a marker of excessive emotional and autonomic activation, which directly correlated with an extent of personality accentuation and severity of neurotic state.

Quality improvement in home life based on EEG signal

NASA Astrophysics Data System (ADS)

Wang, Xiaolong; Wu, Shan; Wang, Sen; Liang, Jinhu

2017-06-01

The purpose of this research is based on the EEG and environmental signals, which are collected by different sensors and uploaded to the same server wirelessly. On the one hand, it is convenient for the data storage and data calls at any time; on the other hand, the system can provide a health advice with adjusting to the environment spontaneously, or to use EEG for the control part of the electrical equipment. The people, objects, and the environment will be organically combined to create a more comfortable, more suitable environment for their living.

[EFFECTS OF ELECTRICAL STIMULATION OF NUCLEUS RETICULARIS PONTIS ORALIS ON THE SLEEP-WAKING STATES IN KRUSHINSKII-MOLODKINA STRAIN RATS].

PubMed

Vataev, S I; Malgina, N A; Oganesyan, G A

2015-07-01

The effects of electrical stimulation of nucleus reticularis pontis oralis on the behavior and brain electrical activity during all phases of the sleep-waking cycle was studied in Krushinskii-Molodkina strain rats, which have an inherited predisposition to audiogenic seizures. Electrical stimulation with 7 Hz frequency in the deep stage of slow-wave sleep cause appearance the fast-wave sleep. Similar stimulation during fast-wave sleep periods did not effects on the electrographic patterns and EEG spectral characteristics of hippocampus, visual, auditory and somatocnen nrnrenc nf the cnrtey ThPe sfimul1stinns did nnt break a fast-wave sleenhut increased almost twice due the duration of these sleep episodes. After electrical stimulation by same frequency during the wakeftlness and superficial slow-wave sleep states, the patterns and spectral characteristics of brain electrical activity in rats showed no significant changes as compared with controls. The results of this study indicate that the state of the animals sleep-waking cycle at the time of stimulation is a critical variable that influences the responses which are induced by electrical stimulation of the nucleus reticularis pontis oralis.

EEG-fMRI evaluation of patients with mesial temporal lobe sclerosis.

PubMed

Avesani, Mirko; Giacopuzzi, Silvia; Bongiovanni, Luigi Giuseppe; Borelli, Paolo; Cerini, Roberto; Pozzi Mucelli, Roberto; Fiaschi, Antonio

2014-02-01

This preliminary study sought more information on blood oxygen level dependent (BOLD) activation, especially contralateral temporal/extratemporal spread, during continuous EEG-fMRI recordings in four patients with mesial temporal sclerosis (MTS). In two patients, EEG showed unilateral focal activity during the EEG-fMRI session concordant with the interictal focus previously identified with standard and video-poly EEG. In the other two patients EEG demonstrated a contralateral diffusion of the irritative focus. In the third patient (with the most drug-resistant form and also extratemporal clinical signs), there was an extratemporal diffusion over frontal regions, ipsilateral to the irritative focus. fMRI analysis confirmed a single activation in the mesial temporal region in two patients whose EEG showed unilateral focal activity, while it demonstrated a bilateral activation in the mesial temporal regions in the other two patients. In the third patient, fMRI demonstrated an activation in the supplementary motxor area. This study confirms the most significant activation with a high firing rate of the irritative focus, but also suggests the importance of using new techniques (such as EEG-fMRI to examine cerebral blood flow) to identify the controlateral limbic activation, and any other extratemporal activations, possible causes of drug resistance in MTS that may require a more precise pre-surgical evaluation with invasive techniques.

EEG-fMRI Evaluation of Patients with Mesial Temporal Lobe Sclerosis

PubMed Central

Avesani, Mirko; Giacopuzzi, Silvia; Bongiovanni, Luigi Giuseppe; Borelli, Paolo; Cerini, Roberto; Pozzi Mucelli, Roberto; Fiaschi, Antonio

2014-01-01

Summary This preliminary study sought more information on blood oxygen level dependent (BOLD) activation, especially contralateral temporal/extratemporal spread, during continuous EEG-fMRI recordings in four patients with mesial temporal sclerosis (MTS). In two patients, EEG showed unilateral focal activity during the EEG-fMRI session concordant with the interictal focus previously identified with standard and video-poly EEG. In the other two patients EEG demonstrated a contralateral diffusion of the irritative focus. In the third patient (with the most drug-resistant form and also extratemporal clinical signs), there was an extratemporal diffusion over frontal regions, ipsilateral to the irritative focus. fMRI analysis confirmed a single activation in the mesial temporal region in two patients whose EEG showed unilateral focal activity, while it demonstrated a bilateral activation in the mesial temporal regions in the other two patients. In the third patient, fMRI demonstrated an activation in the supplementary motxor area. This study confirms the most significant activation with a high firing rate of the irritative focus, but also suggests the importance of using new techniques (such as EEG-fMRI to examine cerebral blood flow) to identify the controlateral limbic activation, and any other extratemporal activations, possible causes of drug resistance in MTS that may require a more precise pre-surgical evaluation with invasive techniques. PMID:24571833

The human brain pacemaker: Synchronized infra-slow neurovascular coupling in patients undergoing non-pulsatile cardiopulmonary bypass.

PubMed

Zanatta, Paolo; Toffolo, Gianna Maria; Sartori, Elisa; Bet, Anna; Baldanzi, Fabrizio; Agarwal, Nivedita; Golanov, Eugene

2013-05-15

In non-pulsatile cardiopulmonary bypass surgery, middle cerebral artery blood flow velocity (BFV) is characterized by infra-slow oscillations of approximately 0.06Hz, which are paralleled by changes in total EEG power variability (EEG-PV), measured in 2s intervals. Since the origin of these BFV oscillations is not known, we explored their possible causative relationships with oscillations in EEG-PV at around 0.06Hz. We monitored 28 patients undergoing non-pulsatile cardiopulmonary bypass using transcranial Doppler sonography and scalp electroencephalography at two levels of anesthesia, deep (prevalence of burst suppression rhythm) and moderate (prevalence of theta rhythm). Under deep anesthesia, the EEG bursts suppression pattern was highly correlative with BFV oscillations. Hence, a detailed quantitative picture of the coupling between electrical brain activity and BFV was derived, both in deep and moderate anesthesia, via linear and non linear processing of EEG-PV and BFV signals, resorting to widely used measures of signal coupling such as frequency of oscillations, coherence, Granger causality and cross-approximate entropy. Results strongly suggest the existence of coupling between EEG-PV and BFV. In moderate anesthesia EEG-PV mean dominant frequency is similar to frequency of BFV oscillations (0.065±0.010Hz vs 0.045±0.019Hz); coherence between the two signals was significant in about 55% of subjects, and the Granger causality suggested an EEG-PV→BFV causal effect direction. The strength of the coupling increased with deepening anesthesia, as EEG-PV oscillations mean dominant frequency virtually coincided with the BFV peak frequency (0.062±0.017Hz vs 0.060±0.024Hz), and coherence became significant in a larger number (65%) of subjects. Cross-approximate entropy decreased significantly from moderate to deep anesthesia, indicating a higher level of synchrony between the two signals. Presence of a subcortical brain pacemaker that drives vascular infra-slow oscillations in the brain is proposed. These findings allow to suggest an original hypothesis explaining the mechanism underlying infra-slow neurovascular coupling. Copyright © 2013 Elsevier Inc. All rights reserved.

EEG topography and tomography (LORETA) in the classification and evaluation of the pharmacodynamics of psychotropic drugs.

PubMed

Saletu, Bernd; Anderer, Peter; Saletu-Zyhlarz, Gerda M

2006-04-01

By multi-lead computer-assisted quantitative analyses of human scalp-recorded electroencephalogram (QEEG) in combination with certain statistical procedures (quantitative pharmaco-EEG) and mapping techniques (pharmaco-EEG mapping or topography), it is possible to classify psychotropic substances and objectively evaluate their bioavailability at the target organ, the human brain. Specifically, one may determine at an early stage of drug development whether a drug is effective on the central nervous system (CNS) compared with placebo, what its clinical efficacy will be like, at which dosage it acts, when it acts and the equipotent dosages of different galenic formulations. Pharmaco-EEG maps of neuroleptics, antidepressants, tranquilizers, hypnotics, psychostimulants and nootropics/cognition-enhancing drugs will be described. Methodological problems, as well as the relationships between acute and chronic drug effects, alterations in normal subjects and patients, CNS effects and therapeutic efficacy will be discussed. Imaging of drug effects on the regional brain electrical activity of healthy subjects by means of EEG tomography such as low-resolution electromagnetic tomography (LORETA) has been used for identifying brain areas predominantly involved in psychopharmacological action. This will be shown for the representative drugs of the four main psychopharmacological classes, such as 3 mg haloperidol for neuroleptics, 20 mg citalopram for antidepressants, 2 mg lorazepam for tranquilizers and 20 mg methylphenidate for psychostimulants. LORETA demonstrates that these psychopharmacological classes affect brain structures differently. By considering these differences between psychotropic drugs and placebo in normal subjects, as well as between mental disorder patients and normal controls, it may be possible to choose the optimum drug for a specific patient according to a key-lock principle, since the drug should normalize the deviant brain function. Thus, pharmaco-EEG topography and tomography are valuable methods in human neuropsychopharmacology, clinical psychiatry and neurology.

Improvements in Concentration, Working Memory, and Sustained Attention Following Consumption of a Natural Citicoline-Caffeine Beverage

PubMed Central

Bruce, Steven E.; Werner, Kimberly B.; Preston, Brittany F.; Baker, Laurie M.

2015-01-01

The present study examined the neurocognitive and electrophysiological effects of a citicoline-caffeine-based beverage in 60 healthy adult participants enrolled in a randomized, double-blind, placebo-controlled trial. Measures of electrical brain activity using electroencephalogram (EEG) and neuropsychological measures examining attention, concentration, and reaction time were administered. Compared to placebo, participants receiving the citicoline-caffeine beverage exhibited significantly faster maze learning times and reaction times on a continuous performance test, fewer errors in a Go No-Go task, and better accuracy on a measure of information processing speed. EEG results examining P450 event related potentials (ERP) revealed that participants receiving the citicoline-caffeine beverage exhibited higher P450 amplitudes than controls, suggesting an increase in sustained attention. Overall, these findings suggest that the beverage significantly improved sustained attention, cognitive effort, and reaction times in healthy adults. Evidence of improved P450 amplitude indicates a general improvement in the ability to accommodate new and relevant information within working memory and overall enhanced brain activation. PMID:25046515

Effects of Cable Sway, Electrode Surface Area, and Electrode Mass on Electroencephalography Signal Quality during Motion.

PubMed

Symeonidou, Evangelia-Regkina; Nordin, Andrew D; Hairston, W David; Ferris, Daniel P

2018-04-03

More neuroscience researchers are using scalp electroencephalography (EEG) to measure electrocortical dynamics during human locomotion and other types of movement. Motion artifacts corrupt the EEG and mask underlying neural signals of interest. The cause of motion artifacts in EEG is often attributed to electrode motion relative to the skin, but few studies have examined EEG signals under head motion. In the current study, we tested how motion artifacts are affected by the overall mass and surface area of commercially available electrodes, as well as how cable sway contributes to motion artifacts. To provide a ground-truth signal, we used a gelatin head phantom with embedded antennas broadcasting electrical signals, and recorded EEG with a commercially available electrode system. A robotic platform moved the phantom head through sinusoidal displacements at different frequencies (0-2 Hz). Results showed that a larger electrode surface area can have a small but significant effect on improving EEG signal quality during motion and that cable sway is a major contributor to motion artifacts. These results have implications in the development of future hardware for mobile brain imaging with EEG.

Visualizing Simulated Electrical Fields from Electroencephalography and Transcranial Electric Brain Stimulation: A Comparative Evaluation

PubMed Central

Eichelbaum, Sebastian; Dannhauer, Moritz; Hlawitschka, Mario; Brooks, Dana; Knösche, Thomas R.; Scheuermann, Gerik

2014-01-01

Electrical activity of neuronal populations is a crucial aspect of brain activity. This activity is not measured directly but recorded as electrical potential changes using head surface electrodes (electroencephalogram - EEG). Head surface electrodes can also be deployed to inject electrical currents in order to modulate brain activity (transcranial electric stimulation techniques) for therapeutic and neuroscientific purposes. In electroencephalography and noninvasive electric brain stimulation, electrical fields mediate between electrical signal sources and regions of interest (ROI). These fields can be very complicated in structure, and are influenced in a complex way by the conductivity profile of the human head. Visualization techniques play a central role to grasp the nature of those fields because such techniques allow for an effective conveyance of complex data and enable quick qualitative and quantitative assessments. The examination of volume conduction effects of particular head model parameterizations (e.g., skull thickness and layering), of brain anomalies (e.g., holes in the skull, tumors), location and extent of active brain areas (e.g., high concentrations of current densities) and around current injecting electrodes can be investigated using visualization. Here, we evaluate a number of widely used visualization techniques, based on either the potential distribution or on the current-flow. In particular, we focus on the extractability of quantitative and qualitative information from the obtained images, their effective integration of anatomical context information, and their interaction. We present illustrative examples from clinically and neuroscientifically relevant cases and discuss the pros and cons of the various visualization techniques. PMID:24821532

Estimation of the EEG power spectrum using MRI T(2) relaxation time in traumatic brain injury.

PubMed

Thatcher, R W; Biver, C; Gomez, J F; North, D; Curtin, R; Walker, R A; Salazar, A

2001-09-01

To study the relationship between magnetic resonance imaging (MRI) T(2) relaxation time and the power spectrum of the electroencephalogram (EEG) in long-term follow up of traumatic brain injury. Nineteen channel quantitative electroencephalograms or qEEG, tests of cognitive function and quantitative MRI T(2) relaxation times (qMRI) were measured in 18 mild to severe closed head injured outpatients 2 months to 4.6 years after injury and 11 normal controls. MRI T(2) and the Laplacian of T(2) were then correlated with the power spectrum of the scalp electrical potentials and current source densities of the qEEG. qEEG and qMRI T(2) were related by a frequency tuning with maxima in the alpha (8-12Hz) and the lower EEG frequencies (0.5-5Hz), which varied as a function of spatial location. The Laplacian of T(2) acted like a spatial-temporal "lens" by increasing the spatial-temporal resolution of correlation between 3-dimensional T(2) and the ear referenced alert but resting spontaneous qEEG. The severity of traumatic brain injury can be modeled by a linear transfer function that relates the molecular qMRI to qEEG resonant frequencies.

Correlation between electrical and hemodynamic responses during visual stimulation with graded contrasts

NASA Astrophysics Data System (ADS)

Si, Juanning; Zhang, Xin; Li, Yuejun; Zhang, Yujin; Zuo, Nianming; Jiang, Tianzi

2016-09-01

Brain functional activity involves complex cellular, metabolic, and vascular chain reactions, making it difficult to comprehend. Electroencephalography (EEG) and functional near infrared spectroscopy (fNIRS) have been combined into a multimodal neuroimaging method that captures both electrophysiological and hemodynamic information to explore the spatiotemporal characteristics of brain activity. Because of the significance of visually evoked functional activity in clinical applications, numerous studies have explored the amplitude of the visual evoked potential (VEP) to clarify its relationship with the hemodynamic response. However, relatively few studies have investigated the influence of latency, which has been frequently used to diagnose visual diseases, on the hemodynamic response. Moreover, because the latency and the amplitude of VEPs have different roles in coding visual information, investigating the relationship between latency and the hemodynamic response should be helpful. In this study, checkerboard reversal tasks with graded contrasts were used to evoke visual functional activity. Both EEG and fNIRS were employed to investigate the relationship between neuronal electrophysiological activities and the hemodynamic responses. The VEP amplitudes were linearly correlated with the hemodynamic response, but the VEP latency showed a negative linear correlation with the hemodynamic response.

Age-Related Changes in Electroencephalographic Signal Complexity

PubMed Central

Zappasodi, Filippo; Marzetti, Laura; Olejarczyk, Elzbieta; Tecchio, Franca; Pizzella, Vittorio

2015-01-01

The study of active and healthy aging is a primary focus for social and neuroscientific communities. Here, we move a step forward in assessing electrophysiological neuronal activity changes in the brain with healthy aging. To this end, electroencephalographic (EEG) resting state activity was acquired in 40 healthy subjects (age 16–85). We evaluated Fractal Dimension (FD) according to the Higuchi algorithm, a measure which quantifies the presence of statistical similarity at different scales in temporal fluctuations of EEG signals. Our results showed that FD increases from age twenty to age fifty and then decreases. The curve that best fits the changes in FD values across age over the whole sample is a parabola, with the vertex located around age fifty. Moreover, FD changes are site specific, with interhemispheric FD asymmetry being pronounced in elderly individuals in the frontal and central regions. The present results indicate that fractal dimension well describes the modulations of brain activity with age. Since fractal dimension has been proposed to be related to the complexity of the signal dynamics, our data demonstrate that the complexity of neuronal electric activity changes across the life span of an individual, with a steady increase during young adulthood and a decrease in the elderly population. PMID:26536036

What can be found in scalp EEG spectrum beyond common frequency bands. EEG-fMRI study

NASA Astrophysics Data System (ADS)

Marecek, R.; Lamos, M.; Mikl, M.; Barton, M.; Fajkus, J.; I, Rektor; Brazdil, M.

2016-08-01

Objective. The scalp EEG spectrum is a frequently used marker of neural activity. Commonly, the preprocessing of EEG utilizes constraints, e.g. dealing with a predefined subset of electrodes or a predefined frequency band of interest. Such treatment of the EEG spectrum neglects the fact that particular neural processes may be reflected in several frequency bands and/or several electrodes concurrently, and can overlook the complexity of the structure of the EEG spectrum. Approach. We showed that the EEG spectrum structure can be described by parallel factor analysis (PARAFAC), a method which blindly uncovers the spatial-temporal-spectral patterns of EEG. We used an algorithm based on variational Bayesian statistics to reveal nine patterns from the EEG of 38 healthy subjects, acquired during a semantic decision task. The patterns reflected neural activity synchronized across theta, alpha, beta and gamma bands and spread over many electrodes, as well as various EEG artifacts. Main results. Specifically, one of the patterns showed significant correlation with the stimuli timing. The correlation was higher when compared to commonly used models of neural activity (power fluctuations in distinct frequency band averaged across a subset of electrodes) and we found significantly correlated hemodynamic fluctuations in simultaneously acquired fMRI data in regions known to be involved in speech processing. Further, we show that the pattern also occurs in EEG data which were acquired outside the MR machine. Two other patterns reflected brain rhythms linked to the attentional and basal ganglia large scale networks. The other patterns were related to various EEG artifacts. Significance. These results show that PARAFAC blindly identifies neural activity in the EEG spectrum and that it naturally handles the correlations among frequency bands and electrodes. We conclude that PARAFAC seems to be a powerful tool for analysis of the EEG spectrum and might bring novel insight to the relationships between EEG activity and brain hemodynamics.

Time course of EEG background activity level before spontaneous awakening in infants.

PubMed

Zampi, Chiara; Fagioli, Igino; Salzarulo, Piero

2002-12-01

This research aimed to investigate the time course of the cortical activity level preceding spontaneous awakening as a function of age and state. Two groups of infants (1-4 and 9-14 weeks of age) were continuously monitored by polygraphic recording and behavioural observation during the night. The electroencephalographic (EEG) activity recorded by the C3-O1 lead was analysed through an automatic analysis method which provides, for each 30-s epoch, a single measure, time domain based, of the EEG synchronization. The EEG parameter values were computed in the 6 min preceding each awakening out of non-rapid eye movement (NREM) sleep and out of rapid eye movement (REM) sleep. The EEG background activity level did not change in the minutes preceding awakening out of REM sleep. Awakening out of NREM sleep was preceded by a change of EEG activity level in the direction of higher activation with different time course according to the age. Both REM and NREM sleep results suggest that a high level of EEG activity is a prerequisite for the occurrence of a spontaneous awakening.

Imaging the cortical effect of lamotrigine in patients with idiopathic generalized epilepsy: a low-resolution electromagnetic tomography (LORETA) study.

PubMed

Clemens, Béla; Piros, Pálma; Bessenyei, Mónika; Tóth, Márton; Hollódy, Katalin; Kondákor, István

2008-10-01

Anatomical localization of the cortical effect of lamotrigine (LTG) in patients with idiopathic generalized epilepsy (IGE). 19 patients with untreated IGE were investigated. EEG was recorded in the untreated condition and 3 months later when LTG treatment abolished the seizures. 19-channel EEG was recorded, and a total of 2min artifact-free, waking EEG was processed to low-resolution electromagnetic tomography (LORETA) analysis. Activity (that is, current source density, A/m(2)) was computed in four frequency bands (delta, theta, alpha, and beta), for 2394 voxels that represented the cortical gray matter and the hippocampi. Group differences between the untreated and treated conditions were computed for the four bands and all voxels by multiple t-tests for interdependent datasets. The results were presented in terms of anatomical distribution and statistical significance. p<0.01 (uncorrected) changes (decrease of activity) emerged in the theta and the alpha bands. Theta activity decreased in a large cluster of voxels including parts of the temporal, parietal, occipital cortex bilaterally, and in the transverse temporal gyri, insula, hippocampus, and uncus on the right side. Alpha activity decreased in a relatively smaller cortical area involving the right temporo-parietal junction and surrounding parts of the cortex, and part of the insula on the right side. LTG decreased theta activity in several cortical areas where abnormally increased theta activity had been found in a prior study in another cohort of untreated IGE patients [Clemens, B., Bessenyei, M., Piros, P., Tóth, M., Seress, L., Kondákor, I., 2007b. Characteristic distribution of interictal brain electrical activity in idiopathic generalized epilepsy. Epilepsia 48, 941-949]. These LTG-related changes might be related to the decrease of seizure propensity in IGE.

Biofield Physiology: A Framework for an Emerging Discipline

PubMed Central

Levin, Michael; McCraty, Rollin; Bat, Namuun; Ives, John A.; Lutgendorf, Susan K.; Oschman, James L.

2015-01-01

Biofield physiology is proposed as an overarching descriptor for the electromagnetic, biophotonic, and other types of spatially-distributed fields that living systems generate and respond to as integral aspects of cellular, tissue, and whole organism self-regulation and organization. Medical physiology, cell biology, and biophysics provide the framework within which evidence for biofields, their proposed receptors, and functions is presented. As such, biofields can be viewed as affecting physiological regulatory systems in a manner that complements the more familiar molecular-based mechanisms. Examples of clinically relevant biofields are the electrical and magnetic fields generated by arrays of heart cells and neurons that are detected, respectively, as electrocardiograms (ECGs) or magnetocardiograms (MCGs) and electroencephalograms (EEGs) or magnetoencephalograms (MEGs). At a basic physiology level, electromagnetic activity of neural assemblies appears to modulate neuronal synchronization and circadian rhythmicity. Numerous nonneural electrical fields have been detected and analyzed, including those arising from patterns of resting membrane potentials that guide development and regeneration, and from slowly-varying transepithelial direct current fields that initiate cellular responses to tissue damage. Another biofield phenomenon is the coherent, ultraweak photon emissions (UPE), detected from cell cultures and from the body surface. A physiological role for biophotons is consistent with observations that fluctuations in UPE correlate with cerebral blood flow, cerebral energy metabolism, and EEG activity. Biofield receptors are reviewed in 3 categories: molecular-level receptors, charge flux sites, and endogenously generated electric or electromagnetic fields. In summary, sufficient evidence has accrued to consider biofield physiology as a viable scientific discipline. Directions for future research are proposed. PMID:26665040

Biofield Physiology: A Framework for an Emerging Discipline.

PubMed

Hammerschlag, Richard; Levin, Michael; McCraty, Rollin; Bat, Namuun; Ives, John A; Lutgendorf, Susan K; Oschman, James L

2015-11-01

Biofield physiology is proposed as an overarching descriptor for the electromagnetic, biophotonic, and other types of spatially-distributed fields that living systems generate and respond to as integral aspects of cellular, tissue, and whole organism self-regulation and organization. Medical physiology, cell biology, and biophysics provide the framework within which evidence for biofields, their proposed receptors, and functions is presented. As such, biofields can be viewed as affecting physiological regulatory systems in a manner that complements the more familiar molecular-based mechanisms. Examples of clinically relevant biofields are the electrical and magnetic fields generated by arrays of heart cells and neurons that are detected, respectively, as electrocardiograms (ECGs) or magnetocardiograms (MCGs) and electroencephalograms (EEGs) or magnetoencephalograms (MEGs). At a basic physiology level, electromagnetic activity of neural assemblies appears to modulate neuronal synchronization and circadian rhythmicity. Numerous nonneural electrical fields have been detected and analyzed, including those arising from patterns of resting membrane potentials that guide development and regeneration, and from slowly-varying transepithelial direct current fields that initiate cellular responses to tissue damage. Another biofield phenomenon is the coherent, ultraweak photon emissions (UPE), detected from cell cultures and from the body surface. A physiological role for biophotons is consistent with observations that fluctuations in UPE correlate with cerebral blood flow, cerebral energy metabolism, and EEG activity. Biofield receptors are reviewed in 3 categories: molecular-level receptors, charge flux sites, and endogenously generated electric or electromagnetic fields. In summary, sufficient evidence has accrued to consider biofield physiology as a viable scientific discipline. Directions for future research are proposed.

EEG controlled neuromuscular electrical stimulation of the upper limb for stroke patients

NASA Astrophysics Data System (ADS)

Tan, Hock Guan; Shee, Cheng Yap; Kong, Keng He; Guan, Cuntai; Ang, Wei Tech

2011-03-01

This paper describes the Brain Computer Interface (BCI) system and the experiments to allow post-acute (<3 months) stroke patients to use electroencephalogram (EEG) to trigger neuromuscular electrical stimulation (NMES)-assisted extension of the wrist/fingers, which are essential pre-requisites for useful hand function. EEG was recorded while subjects performed motor imagery of their paretic limb, and then analyzed to determine the optimal frequency range within the mu-rhythm, with the greatest attenuation. Aided by visual feedback, subjects then trained to regulate their mu-rhythm EEG to operate the BCI to trigger NMES of the wrist/finger. 6 post-acute stroke patients successfully completed the training, with 4 able to learn to control and use the BCI to initiate NMES. This result is consistent with the reported BCI literacy rate of healthy subjects. Thereafter, without the loss of generality, the controller of the NMES is developed and is based on a model of the upper limb muscle (biceps/triceps) groups to determine the intensity of NMES required to flex or extend the forearm by a specific angle. The muscle model is based on a phenomenological approach, with parameters that are easily measured and conveniently implemented.

Comment on the Nanoparticle Conclusions in Crüts et al. (2008), "Exposure to diesel exhaust induces changes in EEG in human volunteers"

PubMed Central

Valberg, Peter A; Long, Christopher M; Hesterberg, Thomas W

2008-01-01

A recent publication in this journal reported interesting changes in electroencephalographic (EEG) waves that occurred in 10 young, male volunteers following inhalation for one hour of elevated levels of diesel-engine exhaust fumes [1]. The authors then proposed a chain of causal events that they hypothesized underlay their observed EEG changes. Their reasoning linked the observed results to nanoparticles in diesel-engine exhaust (DEE), and went on to suggest that associations between changes in ambient particulate matter (PM) levels and changes in health statistics might be due to the effects of diesel-engine exhaust (DEE) nanoparticles on EEG. We suggest that the extrapolations of the Crüts et al. EEG findings to casual mechanisms about how ambient levels of DEE particulate might affect electrical signals in the brain, and subsequently to how DEE particulate might alter disease risk, are premature. PMID:18652692

Hypnagogic imagery and EEG activity.

PubMed

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.

The joint use of the tangential electric field and surface Laplacian in EEG classification.

PubMed

Carvalhaes, C G; de Barros, J Acacio; Perreau-Guimaraes, M; Suppes, P

2014-01-01

We investigate the joint use of the tangential electric field (EF) and the surface Laplacian (SL) derivation as a method to improve the classification of EEG signals. We considered five classification tasks to test the validity of such approach. In all five tasks, the joint use of the components of the EF and the SL outperformed the scalar potential. The smallest effect occurred in the classification of a mental task, wherein the average classification rate was improved by 0.5 standard deviations. The largest effect was obtained in the classification of visual stimuli and corresponded to an improvement of 2.1 standard deviations.

Neurophysiological responses to unpleasant stimuli (acute electrical stimulations and emotional pictures) are increased in patients with schizophrenia

PubMed Central

Duval, Céline Z.; Goumon, Yannick; Kemmel, Véronique; Kornmeier, Jürgen; Dufour, André; Andlauer, Olivier; Vidailhet, Pierre; Poisbeau, Pierrick; Salvat, Eric; Muller, André; Mensah-Nyagan, Ayikoé G.; Schmidt-Mutter, Catherine; Giersch, Anne

2016-01-01

Patients with schizophrenia have often been described as insensitive to nociceptive signals, but objective evidence is sparse. We address this question by combining subjective behavioral and objective neurochemical and neurophysiological measures. The present study involved 21 stabilized and mildly symptomatic patients with schizophrenia and 21 control subjects. We applied electrical stimulations below the pain threshold and assessed sensations of pain and unpleasantness with rating scales, and Somatosensory Evoked Potentials (SEPs/EEG). We also measured attention, two neurochemical stress indices (ACTH/cortisol), and subjective VEPs/EEG responses to visual emotional stimuli. Our results revealed that, subjectively, patients’ evaluations do not differ from controls. However, the amplitude of EEG evoked potentials was greater in patients than controls as early as 50 ms after electrical stimulations and beyond one second after visual processing of emotional pictures. Such responses could not be linked to the stress induced by the stimulations, since stress hormone levels were stable. Nor was there a difference between patients and controls in respect of attention performance and tactile sensitivity. Taken together, all indices measured in patients in our study were either heightened or equivalent relative to healthy volunteers. PMID:26935652

Evidence of Neurotoxicity of Ecstasy: Sustained Effects on Electroencephalographic Activity in Polydrug Users

PubMed Central

Adamaszek, Michael; Khaw, Alexander V.; Buck, Ulrike; Andresen, Burghard; Thomasius, Rainer

2010-01-01

Objective According to previous EEG reports of indicative disturbances in Alpha and Beta activities, a systematic search for distinct EEG abnormalities in a broader population of Ecstasy users may especially corroborate the presumed specific neurotoxicity of Ecstasy in humans. Methods 105 poly-drug consumers with former Ecstasy use and 41 persons with comparable drug history without Ecstasy use, and 11 drug naives were investigated for EEG features. Conventional EEG derivations of 19 electrodes according to the 10-20-system were conducted. Besides standard EEG bands, quantitative EEG analyses of 1-Hz-subdivided power ranges of Alpha, Theta and Beta bands have been considered. Results Ecstasy users with medium and high cumulative Ecstasy doses revealed an increase in Theta and lower Alpha activities, significant increases in Beta activities, and a reduction of background activity. Ecstasy users with low cumulative Ecstasy doses showed a significant Alpha activity at 11 Hz. Interestingly, the spectral power of low frequencies in medium and high Ecstasy users was already significantly increased in the early phase of EEG recording. Statistical analyses suggested the main effect of Ecstasy to EEG results. Conclusions Our data from a major sample of Ecstasy users support previous data revealing alterations of EEG frequency spectrum due rather to neurotoxic effects of Ecstasy on serotonergic systems in more detail. Accordingly, our data may be in line with the observation of attentional and memory impairments in Ecstasy users with moderate to high misuse. Despite the methodological problem of polydrug use also in our approach, our EEG results may be indicative of the neuropathophysiological background of the reported memory and attentional deficits in Ecstasy abusers. Overall, our findings may suggest the usefulness of EEG in diagnostic approaches in assessing neurotoxic sequela of this common drug abuse. PMID:21124854

[The electroencephalographic correlates of neurological disorders in the late periods of exposure to ionizing radiation (the aftereffects of the accident at the Chernobyl Atomic Electric Power Station)].

PubMed

Zhavoronkova, L A; Kholodova, N B; Zubovskiĭ, G A; Smirnov, Iu N; Koptelov, Iu M; Ryzhov, N I

1994-01-01

EEG mapping and three-dimensional localization of epileptic activity sources together with a neurological analysis were carried out in subjects having taken part in 1986-1987 in the liquidation of consequences of the Chernobyl accident. Experimental group included 40 right-handed 25-45 years-old men having received a radiation dose of 15-51 Ber stated officially. Control group consisted of 20 healthy men. Neurological examination of the patients revealed vegetative-vascular and endocrine dysfunctions as well as diffuse neurological symptoms. EEG of one group of patients (25 persons) was characterized by slow alpha- and theta-band foci and epileptic waves in the central-frontal regions; epileptic sources were localized at the diencephalic level mainly in the midline being shifted to the right hemisphere. In the EEG of another group (15 persons) delta-waves were recorded in the frontal regions at the background of diffuse beta-activity. The sources of epileptic activity of a diffuse character were localized at the basal level of the brain and in the cortex (predominantly) in the left hemisphere. The results obtained together with SPECT mapping and CT data permit to suppose the organic damage of different brain structures (at the cortical and the midline levels) in the patients, with participation of diencephalic structures in the pathological process hypothalamic-hypophysial system being probably connected with adaptive processes in the CNS.

A brain-machine interface for control of medically-induced coma.

PubMed

Shanechi, Maryam M; Chemali, Jessica J; Liberman, Max; Solt, Ken; Brown, Emery N

2013-10-01

Medically-induced coma is a drug-induced state of profound brain inactivation and unconsciousness used to treat refractory intracranial hypertension and to manage treatment-resistant epilepsy. The state of coma is achieved by continually monitoring the patient's brain activity with an electroencephalogram (EEG) and manually titrating the anesthetic infusion rate to maintain a specified level of burst suppression, an EEG marker of profound brain inactivation in which bursts of electrical activity alternate with periods of quiescence or suppression. The medical coma is often required for several days. A more rational approach would be to implement a brain-machine interface (BMI) that monitors the EEG and adjusts the anesthetic infusion rate in real time to maintain the specified target level of burst suppression. We used a stochastic control framework to develop a BMI to control medically-induced coma in a rodent model. The BMI controlled an EEG-guided closed-loop infusion of the anesthetic propofol to maintain precisely specified dynamic target levels of burst suppression. We used as the control signal the burst suppression probability (BSP), the brain's instantaneous probability of being in the suppressed state. We characterized the EEG response to propofol using a two-dimensional linear compartment model and estimated the model parameters specific to each animal prior to initiating control. We derived a recursive Bayesian binary filter algorithm to compute the BSP from the EEG and controllers using a linear-quadratic-regulator and a model-predictive control strategy. Both controllers used the estimated BSP as feedback. The BMI accurately controlled burst suppression in individual rodents across dynamic target trajectories, and enabled prompt transitions between target levels while avoiding both undershoot and overshoot. The median performance error for the BMI was 3.6%, the median bias was -1.4% and the overall posterior probability of reliable control was 1 (95% Bayesian credibility interval of [0.87, 1.0]). A BMI can maintain reliable and accurate real-time control of medically-induced coma in a rodent model suggesting this strategy could be applied in patient care.

Dynamics of the EEG of human brain in the gradient magnetic fields of geological faults in different geographical and climatic zones

NASA Astrophysics Data System (ADS)

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.

Long term impairment of cognitive functions and alterations of NMDAR subunits after continuous microwave exposure.

PubMed

Wang, Hui; Tan, Shengzhi; Xu, Xinping; Zhao, Li; Zhang, Jing; Yao, Binwei; Gao, Yabing; Zhou, Hongmei; Peng, Ruiyun

2017-11-01

The long term effects of continuous microwave exposure cannot be ignored for the simulation of the real environment and increasing concerns about the negative cognitive effects of microwave exposure. In this study, 220 male Wistar rats were exposed by a 2.856GHz radiation source with the average power density of 0, 2.5, 5 and 10mW/cm 2 for 6min/day, 5days/week and up to 6weeks. The MWM task, the EEG analysis, the hippocampus structure observation and the western blot were applied until the 12months after microwave exposure to detect the spatial learning and memory abilities, the cortical electrical activity, changes of hippocampal structure and the NMDAR subunits expressions. Results found that the rats in the 10mW/cm 2 group showed the decline of spatial learning and memory abilities and EEG disorders (the decrease of EEG frequencies, and increase of EEG amplitudes and delta wave powers). Moreover, changes of basic structure and ultrastructure of hippocampus also found in the 10 and 5mW/cm 2 groups. The decrease of NR 2A, 2B and p-NR2B might contribute to the impairment of cognitive functions. Our findings suggested that the continuous microwave exposure could cause the dose-dependent long term impairment of spatial learning and memory, the abnormalities of EEG and the hippocampal structure injuries. The decrease of NMDAR key subunits and phosphorylation of NR 2B might contribute to the cognitive impairment. Copyright © 2017 Elsevier Inc. All rights reserved.

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

PubMed

Engelbregt, H J; Keeser, D; van Eijk, L; Suiker, E M; Eichhorn, D; Karch, S; Deijen, J B; Pogarell, O

2016-04-01

In this study we evaluated long-term effects of frontal beta EEG-neurofeedback training (E-NFT) on healthy subjects. We hypothesized that E-NFT can change frontal beta activity in the long-term and that changes in frontal beta EEG activity are accompanied by altered cognitive performance. 25 healthy subjects were included and randomly assigned to active or sham E-NFT. On average the subjects underwent 15 E-NFT training sessions with a training duration of 45 min. Resting-state EEG was recorded prior to E-NFT training (t1) and in a 3-year follow-up (t3). Compared to sham E-NFT, which was used for the control group, real E-NFT increased beta activity in a predictable way. This increase was maintained over a period of three years post training. However, E-NFT did not result in significantly improved cognitive performance. Based on our results, we conclude that EEG-NFT can selectively modify EEG beta activity both in short and long-term. This is a sham controlled EEG neurofeedback study demonstrating long-term effects in resting state EEG. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Is EEG-biofeedback an effective treatment in autism spectrum disorders? A randomized controlled trial.

PubMed

Kouijzer, Mirjam E J; van Schie, Hein T; Gerrits, Berrie J L; Buitelaar, Jan K; de Moor, Jan M H

2013-03-01

EEG-biofeedback has been reported to reduce symptoms of autism spectrum disorders (ASD) in several studies. However, these studies did not control for nonspecific effects of EEG-biofeedback and did not distinguish between participants who succeeded in influencing their own EEG activity and participants who did not. To overcome these methodological shortcomings, this study evaluated the effects of EEG-biofeedback in ASD in a randomized pretest-posttest control group design with blinded active comparator and six months follow-up. Thirty-eight participants were randomly allocated to the EEG-biofeedback, skin conductance (SC)-biofeedback or waiting list group. EEG- and SC-biofeedback sessions were similar and participants were blinded to the type of feedback they received. Assessments pre-treatment, post-treatment, and after 6 months included parent ratings of symptoms of ASD, executive function tasks, and 19-channel EEG recordings. Fifty-four percent of the participants significantly reduced delta and/or theta power during EEG-biofeedback sessions and were identified as EEG-regulators. In these EEG-regulators, no statistically significant reductions of symptoms of ASD were observed, but they showed significant improvement in cognitive flexibility as compared to participants who managed to regulate SC. EEG-biofeedback seems to be an applicable tool to regulate EEG activity and has specific effects on cognitive flexibility, but it did not result in significant reductions in symptoms of ASD. An important finding was that no nonspecific effects of EEG-biofeedback were demonstrated.

The effects of increased fluid viscosity on stationary characteristics of EEG signal in healthy adults

PubMed Central

Jestrović, I.; Coyle, J. L.

2014-01-01

Electroencephalography (EEG) systems can enable us to study cerebral activation patterns during performance of swallowing tasks and possibly infer about the nature of abnormal neurological conditions causing swallowing difficulties. While it is well known that EEG signals are non-stationary, there are still open questions regarding the stationarity of EEG during swallowing activities and how the EEG stationarity is affected by different viscosities of the fluids that are swallowed by subjects during these swallowing activities. In the present study, we investigated the EEG signal collected during swallowing tasks by collecting data from 55 healthy adults (ages 18–65). Each task involved the deliberate swallowing of boluses of fluids of different viscosities. Using time-frequency tests with surrogates, we showed that the EEG during swallowing tasks could be considered non-stationary. Furthermore, the statistical tests and linear regression showed that the parameters of fluid viscosity, sex, and different brain regions significantly influenced the index of non-stationarity values. Therefore, these parameters should be considered in future investigations which use EEG during swallowing activities. PMID:25245522

Comparative analysis of the electroencephalogram in patients with Alzheimer's disease, diffuse axonal injury patients and healthy controls using LORETA analysis.

PubMed

Ianof, Jéssica Natuline; Fraga, Francisco José; Ferreira, Leonardo Alves; Ramos, Renato Teodoro; Demario, José Luiz Carlos; Baratho, Regina; Basile, Luís Fernando Hindi; Nitrini, Ricardo; Anghinah, Renato

2017-01-01

Alzheimer's disease (AD) is a dementia that affects a large contingent of the elderly population characterized by the presence of neurofibrillary tangles and senile plaques. Traumatic brain injury (TBI) is a non-degenerative injury caused by an external mechanical force. One of the main causes of TBI is diffuse axonal injury (DAI), promoted by acceleration-deceleration mechanisms. To understand the electroencephalographic differences in functional mechanisms between AD and DAI groups. The study included 20 subjects with AD, 19 with DAI and 17 healthy adults submitted to high resolution EEG with 128 channels. Cortical sources of EEG rhythms were estimated by exact low-resolution electromagnetic tomography (eLORETA) analysis. The eLORETA analysis showed that, in comparison to the control (CTL) group, the AD group had increased theta activity in the parietal and frontal lobes and decreased alpha 2 activity in the parietal, frontal, limbic and occipital lobes. In comparison to the CTL group, the DAI group had increased theta activity in the limbic, occipital sublobar and temporal areas. The results suggest that individuals with AD and DAI have impairment of electrical activity in areas important for memory and learning.

Impaired brainstem and thalamic high-frequency oscillatory EEG activity in migraine between attacks.

PubMed

Porcaro, Camillo; Di Lorenzo, Giorgio; Seri, Stefano; Pierelli, Francesco; Tecchio, Franca; Coppola, Gianluca

2017-09-01

Introduction We investigated whether interictal thalamic dysfunction in migraine without aura (MO) patients is a primary determinant or the expression of its functional disconnection from proximal or distal areas along the somatosensory pathway. Methods Twenty MO patients and twenty healthy volunteers (HVs) underwent an electroencephalographic (EEG) recording during electrical stimulation of the median nerve at the wrist. We used the functional source separation algorithm to extract four functionally constrained nodes (brainstem, thalamus, primary sensory radial, and primary sensory motor tangential parietal sources) along the somatosensory pathway. Two digital filters (1-400 Hz and 450-750 Hz) were applied in order to extract low- (LFO) and high- frequency (HFO) oscillatory activity from the broadband signal. Results Compared to HVs, patients presented significantly lower brainstem (BS) and thalamic (Th) HFO activation bilaterally. No difference between the two cortical HFO as well as in LFO peak activations between the two groups was seen. The age of onset of the headache was positively correlated with HFO power in the right brainstem and thalamus. Conclusions This study provides evidence for complex dysfunction of brainstem and thalamocortical networks under the control of genetic factors that might act by modulating the severity of migraine phenotype.

A brain-computer interface to support functional recovery.

PubMed

Kjaer, Troels W; Sørensen, Helge B

2013-01-01

Brain-computer interfaces (BCI) register changes in brain activity and utilize this to control computers. The most widely used method is based on registration of electrical signals from the cerebral cortex using extracranially placed electrodes also called electroencephalography (EEG). The features extracted from the EEG may, besides controlling the computer, also be fed back to the patient for instance as visual input. This facilitates a learning process. BCI allow us to utilize brain activity in the rehabilitation of patients after stroke. The activity of the cerebral cortex varies with the type of movement we imagine, and by letting the patient know the type of brain activity best associated with the intended movement the rehabilitation process may be faster and more efficient. The focus of BCI utilization in medicine has changed in recent years. While we previously focused on devices facilitating communication in the rather few patients with locked-in syndrome, much interest is now devoted to the therapeutic use of BCI in rehabilitation. For this latter group of patients, the device is not intended to be a lifelong assistive companion but rather a 'teacher' during the rehabilitation period. Copyright © 2013 S. Karger AG, Basel.

A variational Bayes spatiotemporal model for electromagnetic brain mapping.

PubMed

Nathoo, F S; Babul, A; Moiseev, A; Virji-Babul, N; Beg, M F

2014-03-01

In this article, we present a new variational Bayes approach for solving the neuroelectromagnetic inverse problem arising in studies involving electroencephalography (EEG) and magnetoencephalography (MEG). This high-dimensional spatiotemporal estimation problem involves the recovery of time-varying neural activity at a large number of locations within the brain, from electromagnetic signals recorded at a relatively small number of external locations on or near the scalp. Framing this problem within the context of spatial variable selection for an underdetermined functional linear model, we propose a spatial mixture formulation where the profile of electrical activity within the brain is represented through location-specific spike-and-slab priors based on a spatial logistic specification. The prior specification accommodates spatial clustering in brain activation, while also allowing for the inclusion of auxiliary information derived from alternative imaging modalities, such as functional magnetic resonance imaging (fMRI). We develop a variational Bayes approach for computing estimates of neural source activity, and incorporate a nonparametric bootstrap for interval estimation. The proposed methodology is compared with several alternative approaches through simulation studies, and is applied to the analysis of a multimodal neuroimaging study examining the neural response to face perception using EEG, MEG, and fMRI. © 2013, The International Biometric Society.

EEG activity during the spatial span task in young men: Differences between short-term and working memory.

PubMed

Guevara, Miguel Angel; Cruz Paniagua, Edwin Iván; Hernández González, Marisela; Sandoval Carrillo, Ivett Karina; Almanza Sepúlveda, Mayra Linné; Hevia Orozco, Jorge Carlos; Amezcua Gutiérrez, Claudia

2018-03-15

Short-term memory and working memory are two closely-related concepts that involve the prefrontal and parietal areas. These two types of memory have been evaluated by means of the spatial span task in its forward and backward conditions, respectively. To determine possible neurofunctional differences between them, this study recorded electroencephalographic activity (EEG) in the frontopolar (Fp1, Fp2), dorsolateral (F3, F4), and parietal (P3 and P4) areas during performance of the forward and backward conditions of this task in young men. The backward condition (an indicator of working memory) was characterized by fewer correct answers, higher absolute power (AP) of the delta band in dorsolateral areas, and a lower correlation between frontopolar and dorsolateral regions in the fast bands (alpha, beta and gamma), mainly in the right hemisphere. The prefrontal EEG changes during backward performance may be associated with the higher attentional demands and inhibition processes required to invert the order of reproduction of a sequence. These data provide evidence that the forward and backward conditions of the spatial span task can be distinguished on the basis of neurofunctional activity and performance, and that each one is associated with a distinct pattern of electrical activity and synchronization between prefrontal areas. The higher AP of the delta band and lower correlation of the fast bands, particularly between right prefrontal areas during the backward condition of this visuospatial task, suggest greater participation by the right prefrontal areas in working memory. Copyright © 2018 Elsevier B.V. All rights reserved.

Neural complexity in patients with poststroke depression: A resting EEG study.

PubMed

Zhang, Ying; Wang, Chunfang; Sun, Changcheng; Zhang, Xi; Wang, Yongjun; Qi, Hongzhi; He, Feng; Zhao, Xin; Wan, Baikun; Du, Jingang; Ming, Dong

2015-12-01

Poststroke depression (PSD) is one of the most common emotional disorders affecting post-stroke patients. However, the neurophysiological mechanism remains elusive. This study was aimed to study the relationship between complexity of neural electrical activity and PSD. Resting state eye-closed electroencephalogram (EEG) signals of 16 electrodes were recorded in 21 ischemic poststroke depression (PSD) patients, 22 ischemic poststroke non-depression (PSND) patients and 15 healthy controls (CONT). Lempel-Ziv Complexity (LZC) was used to evaluate changes in EEG complexity in PSD patients. Statistical analysis was performed to explore difference among different groups and electrodes. Correlation between the severity of depression (HDRS) and EEG complexity was determined with pearson correlation coefficients. Receiver operating characteristic (ROC) and binary logistic regression analysis were conducted to estimate the discriminating ability of LZC for PSD in specificity, sensitivity and accuracy. PSD patients showed lower neural complexity compared with PSND and CONT subjects in the whole brain regions. There was no significant difference among different brain regions, and no interactions between group and electrodes. None of the LZC significantly correlated with overall depression severity or differentiated symptom severity of 7 items in PSD patients, but in stroke patients, significant correlation was found between HDRS and LZC in the whole brain regions, especially in frontal and temporal. LZC parameters used for PSD recognition possessed more than 85% in specificity, sensitivity and accuracy, suggesting the feasibility of LZC to serve as screening indicators for PSD. Increased slow wave rhythms were found in PSD patients and clearly correlation was confirmed between neuronal complexity and spectral power of the four EEG rhythms. Lesion location of stroke patients in the study distributed in different brain regions, and most of the PSD patients were mild or moderate in depressive severity. Compared with conventional spectral analysis, complexity of neural activity using LZC was more sensitive and stationary in the measurement of abnormal brain activity in PSD patients and may offer a potential approach to facilitate clinical screening of this disease. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Brain-computer interface controlled functional electrical stimulation device for foot drop due to stroke.

PubMed

Do, An H; Wang, Po T; King, Christine E; Schombs, Andrew; Cramer, Steven C; Nenadic, Zoran

2012-01-01

Gait impairment due to foot drop is a common outcome of stroke, and current physiotherapy provides only limited restoration of gait function. Gait function can also be aided by orthoses, but these devices may be cumbersome and their benefits disappear upon removal. Hence, new neuro-rehabilitative therapies are being sought to generate permanent improvements in motor function beyond those of conventional physiotherapies through positive neural plasticity processes. Here, the authors describe an electroencephalogram (EEG) based brain-computer interface (BCI) controlled functional electrical stimulation (FES) system that enabled a stroke subject with foot drop to re-establish foot dorsiflexion. To this end, a prediction model was generated from EEG data collected as the subject alternated between periods of idling and attempted foot dorsiflexion. This prediction model was then used to classify online EEG data into either "idling" or "dorsiflexion" states, and this information was subsequently used to control an FES device to elicit effective foot dorsiflexion. The performance of the system was assessed in online sessions, where the subject was prompted by a computer to alternate between periods of idling and dorsiflexion. The subject demonstrated purposeful operation of the BCI-FES system, with an average cross-correlation between instructional cues and BCI-FES response of 0.60 over 3 sessions. In addition, analysis of the prediction model indicated that non-classical brain areas were activated in the process, suggesting post-stroke cortical re-organization. In the future, these systems may be explored as a potential therapeutic tool that can help promote positive plasticity and neural repair in chronic stroke patients.

Early Oxygen-Utilization and Brain Activity in Preterm Infants

PubMed Central

de Vries, Linda S.; Groenendaal, Floris; Toet, Mona C.; Lemmers, Petra M. A.; Vosse van de, Renè E.; van Bel, Frank; Benders, Manon J. N. L.

2015-01-01

The combined monitoring of oxygen supply and delivery using Near-InfraRed spectroscopy (NIRS) and cerebral activity using amplitude-integrated EEG (aEEG) could yield new insights into brain metabolism and detect potentially vulnerable conditions soon after birth. The relationship between NIRS and quantitative aEEG/EEG parameters has not yet been investigated. Our aim was to study the association between oxygen utilization during the first 6 h after birth and simultaneously continuously monitored brain activity measured by aEEG/EEG. Forty-four hemodynamically stable babies with a GA < 28 weeks, with good quality NIRS and aEEG/EEG data available and who did not receive morphine were included in the study. aEEG and NIRS monitoring started at NICU admission. The relation between regional cerebral oxygen saturation (rScO2) and cerebral fractional tissue oxygen extraction (cFTOE), and quantitative measurements of brain activity such as number of spontaneous activity transients (SAT) per minute (SAT rate), the interval in seconds (i.e. time) between SATs (ISI) and the minimum amplitude of the EEG in μV (min aEEG) were evaluated. rScO2 was negatively associated with SAT rate (β=-3.45 [CI=-5.76- -1.15], p=0.004) and positively associated with ISI (β=1.45 [CI=0.44-2.45], p=0.006). cFTOE was positively associated with SAT rate (β=0.034 [CI=0.009-0.059], p=0.008) and negatively associated with ISI (β=-0.015 [CI=-0.026- -0.004], p=0.007). Oxygen delivery and utilization, as indicated by rScO2 and cFTOE, are directly related to functional brain activity, expressed by SAT rate and ISI during the first hours after birth, showing an increase in oxygen extraction in preterm infants with increased early electro-cerebral activity. NIRS monitored oxygenation may be a useful biomarker of brain vulnerability in high-risk infants. PMID:25965343

Prolonged activation EEG differentiates dementia with and without delirium in frail elderly patients.

PubMed

Thomas, C; Hestermann, U; Walther, S; Pfueller, U; Hack, M; Oster, P; Mundt, C; Weisbrod, M

2008-02-01

Delirium in the elderly results in increased morbidity, mortality and functional decline. Delirium is underdiagnosed, particularly in dementia. To increase diagnostic accuracy, we investigated whether maintenance of activation assessed by EEG discriminates delirium in association with dementia (D+D) from dementia without delirium (DP) and cognitively unimpaired elderly subjects (CU). Routine and quantitative EEG (rEEG/qEEG) with additional prolonged activation (3 min eyes open period) were evaluated in hospitalised elderly patients with acute geriatric disease. Patients were assigned post hoc to three comparable groups (D+D/DP/CU) by expert consensus based on DSM-IV criteria. Dementia diagnosis was confirmed using cognitive and functional tests and caregiver rating (IQCODE, Informed Questionnaire of Cognitive Decline in the Elderly). While rEEG at rest showed low accuracy for a diagnosis of delirium, qEEG in DP and CU revealed a specific activation pattern of high significance found to be absent in the D+D group. Stepwise logistic regression confirmed that differentiation of D+D from DP was best resolved using activated upper alpha and delta power density which, compared with rEEG, enabled an 11% increase in diagnostic correctness to 83%, resulting in 67% sensitivity and 91% specificity. Among frail CU and D+D subjects, almost 90% were correctly classified. Dementia associated with delirium can be discriminated reliably from dementia alone in a meaningful clinical setting. Thus EEG evaluation in chronic encephalopathy should be optimised by a simple activation task and spectral analysis, particularly in the elderly with dementia.

Nonlinear analysis of EEG in major depression with fractal dimensions.

PubMed

Akar, Saime A; Kara, Sadik; Agambayev, Sumeyra; Bilgic, Vedat

2015-01-01

Major depressive disorder (MDD) is a psychiatric mood disorder characterized by cognitive and functional impairments in attention, concentration, learning and memory. In order to investigate and understand its underlying neural activities and pathophysiology, EEG methodologies can be used. In this study, we estimated the nonlinearity features of EEG in MDD patients to assess the dynamical properties underlying the frontal and parietal brain activity. EEG data were obtained from 16 patients and 15 matched healthy controls. A wavelet-chaos methodology was used for data analysis. First, EEGs of subjects were decomposed into 5 EEG sub-bands by discrete wavelet transform. Then, both the Katz's and Higuchi's fractal dimensions (KFD and HFD) were calculated as complexity measures for full-band and sub-bands EEGs. Last, two-way analyses of variances were used to test EEG complexity differences on each fractality measures. As a result, a significantly increased complexity was found in both parietal and frontal regions of MDD patients. This significantly increased complexity was observed not only in full-band activity but also in beta and gamma sub-bands of EEG. The findings of the present study indicate the possibility of using the wavelet-chaos methodology to discriminate the EEGs of MDD patients from healthy controls.

EEG in children with spelling disabilities.

PubMed

Byring, R F; Salmi, T K; Sainio, K O; Orn, H P

1991-10-01

A total of 23 13-year-old boys with spelling disabilities and 21 matched controls were studied. EEG was recorded for visual and quantitative analysis, including FFT band powers and normalized slope descriptors (NSD). Visual analysis showed general excess of slow activity, as well as an excess of temporal slow wave activity in the index group. Quantitative analysis showed low alpha and beta powers, and low "activity" and high "complexity" (NSD) in parieto-occipital derivations in the index group. Quantitative EEG (qEEG) parameter ratios between temporal and parieto-occipital derivations were increased in the index group, implying a lack of spatial differentiation in these EEGs. In covariance analysis the qEEG parameter differences between the index group and controls were partly explained by the neurotic traits made evident in psychological tests. This implies that psychopathological artifacts should be considered in qEEG examinations of children with cognitive handicaps. Differences in anterior/posterior qEEG ratios were, however, little affected by any confounding factors. Thus these qEEG ratios seem potentially useful in clinical assessments of children with learning disabilities.

Fuzzy topological digital space and digital fuzzy spline of electroencephalography during epileptic seizures

NASA Astrophysics Data System (ADS)

Shah, Mazlina Muzafar; Wahab, Abdul Fatah

2017-08-01

Epilepsy disease occurs because of there is a temporary electrical disturbance in a group of brain cells (nurons). The recording of electrical signals come from the human brain which can be collected from the scalp of the head is called Electroencephalography (EEG). EEG then considered in digital format and in fuzzy form makes it a fuzzy digital space data form. The purpose of research is to identify the area (curve and surface) in fuzzy digital space affected by inside epilepsy seizure in epileptic patient's brain. The main focus for this research is to generalize fuzzy topological digital space, definition and basic operation also the properties by using digital fuzzy set and the operations. By using fuzzy digital space, the theory of digital fuzzy spline can be introduced to replace grid data that has been use previously to get better result. As a result, the flat of EEG can be fuzzy topological digital space and this type of data can be use to interpolate the digital fuzzy spline.

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

NASA Astrophysics Data System (ADS)

Croce, Pierpaolo; Basti, Alessio; Marzetti, Laura; Zappasodi, Filippo; Del Gratta, Cosimo

2016-12-01

Objective. Due to the complementary nature of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), and given the possibility of simultaneous acquisition, the joint data analysis can afford a better understanding of the underlying neural activity estimation. In this simulation study we want to show the benefit of the joint EEG-fMRI neural activity estimation in a Bayesian framework. Approach. We built a dynamic Bayesian framework in order to perform joint EEG-fMRI neural activity time course estimation. The neural activity is originated by a given brain area and detected by means of both measurement techniques. We have chosen a resting state neural activity situation to address the worst case in terms of the signal-to-noise ratio. To infer information by EEG and fMRI concurrently we used a tool belonging to the sequential Monte Carlo (SMC) methods: the particle filter (PF). Main results. First, despite a high computational cost, we showed the feasibility of such an approach. Second, we obtained an improvement in neural activity reconstruction when using both EEG and fMRI measurements. Significance. The proposed simulation shows the improvements in neural activity reconstruction with EEG-fMRI simultaneous data. The application of such an approach to real data allows a better comprehension of the neural dynamics.

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

PubMed

Croce, Pierpaolo; Basti, Alessio; Marzetti, Laura; Zappasodi, Filippo; Gratta, Cosimo Del

2016-12-01

Due to the complementary nature of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), and given the possibility of simultaneous acquisition, the joint data analysis can afford a better understanding of the underlying neural activity estimation. In this simulation study we want to show the benefit of the joint EEG-fMRI neural activity estimation in a Bayesian framework. We built a dynamic Bayesian framework in order to perform joint EEG-fMRI neural activity time course estimation. The neural activity is originated by a given brain area and detected by means of both measurement techniques. We have chosen a resting state neural activity situation to address the worst case in terms of the signal-to-noise ratio. To infer information by EEG and fMRI concurrently we used a tool belonging to the sequential Monte Carlo (SMC) methods: the particle filter (PF). First, despite a high computational cost, we showed the feasibility of such an approach. Second, we obtained an improvement in neural activity reconstruction when using both EEG and fMRI measurements. The proposed simulation shows the improvements in neural activity reconstruction with EEG-fMRI simultaneous data. The application of such an approach to real data allows a better comprehension of the neural dynamics.

Effects of Cable Sway, Electrode Surface Area, and Electrode Mass on Electroencephalography Signal Quality during Motion

PubMed Central

Symeonidou, Evangelia-Regkina; Nordin, Andrew D.; Hairston, W. David

2018-01-01

More neuroscience researchers are using scalp electroencephalography (EEG) to measure electrocortical dynamics during human locomotion and other types of movement. Motion artifacts corrupt the EEG and mask underlying neural signals of interest. The cause of motion artifacts in EEG is often attributed to electrode motion relative to the skin, but few studies have examined EEG signals under head motion. In the current study, we tested how motion artifacts are affected by the overall mass and surface area of commercially available electrodes, as well as how cable sway contributes to motion artifacts. To provide a ground-truth signal, we used a gelatin head phantom with embedded antennas broadcasting electrical signals, and recorded EEG with a commercially available electrode system. A robotic platform moved the phantom head through sinusoidal displacements at different frequencies (0–2 Hz). Results showed that a larger electrode surface area can have a small but significant effect on improving EEG signal quality during motion and that cable sway is a major contributor to motion artifacts. These results have implications in the development of future hardware for mobile brain imaging with EEG. PMID:29614020

Meanings of Waves: Electroencephalography and Society in Mexico City, 1940-1950.

PubMed

Pérez, Nuria Valverde

2016-12-01

Argument This paper focuses on the uses of electroencephalograms (EEGs) in Mexico during their introductory decade from 1940 to 1950. Following Borck (2006), I argue that EEGs adapted to fit local circumstances and that this adjustment led to the consolidation of different ways of making science and the emergence of new objects of study and social types. I also maintain that the way EEGs were introduced into the institutional networks of Mexico entangled them in discussions about the objective and juridical definitions of social groups, thereby preempting concerns about their technical and epistemic limitations. This ultimately enabled the use of EEGs as normative machines and dispositifs. To this end, the paper follows the arrival of EEGs and the creation of institutional networks then analyzes the extent to which the styles of thinking behind the uses of EEGs and attempts to reify a notion of normal electrical brain behavior-particularly by applying EEGs to a community of Otomí Indians-correlated with the difficulties of defining the socio-anthropological notions that articulated legal and disciplinary projects of the time. Finally, it unveils the shortcomings of alternative attempts to define a brain model and to resist the production of ontological determinations.

[Individual Types Reactivity of EEG Oscillations in Effective Heart Rhythm Biofeedback Parameters in Adolescents and Young People in the North].

PubMed

Krivonogova, E V; Poskotinova, L V; Demin, D B

2015-01-01

A single session of heart rate variability (HRV) biofeedback in apparently healthy young people and adolescents aged 14-17 years in order to increase vagal effects on heart rhythm and also electroencephalograms were carried out. Different variants of EEG spectral power during the successful HRV biofeedback session were identified. In the case of I variant of EEG activity the increase of power spectrum of alpha-, betal-, theta-components takes place in all parts of the brain. In the case of II variant of EEG activity the reduction of power spectrum of alpha-, betal-, theta-activity in all parts of the brain was observed. I and II variants of EEG activity cause more intensive regime of cortical-subcortical interactions. During the III variant of EEG activity the successful biofeedback is accompanied by increase of alpha activity in the central, front and anteriofrontal brain parts and so indicates the formation of thalamocortical relations of neural network in order to optimize the vegetal regulation of heart function. There was an increase in alpha- and beta1-activity in the parietal, central, frontal and temporal brain parts during the IV variant of EEG activity and so that it provides the relief of neural networks communication for information processing. As a result of V variance of EEG activity there was the increase of power spectrum of theta activity in the central and frontal parts of both cerebral hemispheres, so it was associated with the cortical-hippocampal interactions to achieve a successful biofeedback.

Reproducibility of EEG-fMRI results in a patient with fixation-off sensitivity.

PubMed

Formaggio, Emanuela; Storti, Silvia Francesca; Galazzo, Ilaria Boscolo; Bongiovanni, Luigi Giuseppe; Cerini, Roberto; Fiaschi, Antonio; Manganotti, Paolo

2014-07-01

Blood oxygenation level-dependent (BOLD) activation associated with interictal epileptiform discharges in a patient with fixation-off sensitivity (FOS) was studied using a combined electroencephalography-functional magnetic resonance imaging (EEG-fMRI) technique. An automatic approach for combined EEG-fMRI analysis and a subject-specific hemodynamic response function was used to improve general linear model analysis of the fMRI data. The EEG showed the typical features of FOS, with continuous epileptiform discharges during elimination of central vision by eye opening and closing and fixation; modification of this pattern was clearly visible and recognizable. During all 3 recording sessions EEG-fMRI activations indicated a BOLD signal decrease related to epileptiform activity in the parietal areas. This study can further our understanding of this EEG phenomenon and can provide some insight into the reliability of the EEG-fMRI technique in localizing the irritative zone.

Neural activity based biofeedback therapy for Autism spectrum disorder through wearable wireless textile EEG monitoring system

NASA Astrophysics Data System (ADS)

Sahi, Ahna; Rai, Pratyush; Oh, Sechang; Ramasamy, Mouli; Harbaugh, Robert E.; Varadan, Vijay K.

2014-04-01

Mu waves, also known as mu rhythms, comb or wicket rhythms are synchronized patterns of electrical activity involving large numbers of neurons, in the part of the brain that controls voluntary functions. Controlling, manipulating, or gaining greater awareness of these functions can be done through the process of Biofeedback. Biofeedback is a process that enables an individual to learn how to change voluntary movements for purposes of improving health and performance through the means of instruments such as EEG which rapidly and accurately 'feedback' information to the user. Biofeedback is used for therapeutic purpose for Autism Spectrum Disorder (ASD) by focusing on Mu waves for detecting anomalies in brain wave patterns of mirror neurons. Conventional EEG measurement systems use gel based gold cup electrodes, attached to the scalp with adhesive. It is obtrusive and wires sticking out of the electrodes to signal acquisition system make them impractical for use in sensitive subjects like infants and children with ASD. To remedy this, sensors can be incorporated with skull cap and baseball cap that are commonly used for infants and children. Feasibility of Textile based Sensor system has been investigated here. Textile based multi-electrode EEG, EOG and EMG monitoring system with embedded electronics for data acquisition and wireless transmission has been seamlessly integrated into fabric of these items for continuous detection of Mu waves. Textile electrodes were placed on positions C3, CZ, C4 according to 10-20 international system and their capability to detect Mu waves was tested. The system is ergonomic and can potentially be used for early diagnosis in infants and planning therapy for ASD patients.

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

PubMed

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

2001-08-01

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

New Flexible Silicone-Based EEG Dry Sensor Material Compositions Exhibiting Improvements in Lifespan, Conductivity, and Reliability

PubMed Central

Yu, Yi-Hsin; Chen, Shih-Hsun; Chang, Che-Lun; Lin, Chin-Teng; Hairston, W. David; Mrozek, Randy A.

2016-01-01

This study investigates alternative material compositions for flexible silicone-based dry electroencephalography (EEG) electrodes to improve the performance lifespan while maintaining high-fidelity transmission of EEG signals. Electrode materials were fabricated with varying concentrations of silver-coated silica and silver flakes to evaluate their electrical, mechanical, and EEG transmission performance. Scanning electron microscope (SEM) analysis of the initial electrode development identified some weak points in the sensors’ construction, including particle pull-out and ablation of the silver coating on the silica filler. The newly-developed sensor materials achieved significant improvement in EEG measurements while maintaining the advantages of previous silicone-based electrodes, including flexibility and non-toxicity. The experimental results indicated that the proposed electrodes maintained suitable performance even after exposure to temperature fluctuations, 85% relative humidity, and enhanced corrosion conditions demonstrating improvements in the environmental stability. Fabricated flat (forehead) and acicular (hairy sites) electrodes composed of the optimum identified formulation exhibited low impedance and reliable EEG measurement; some initial human experiments demonstrate the feasibility of using these silicone-based electrodes for typical lab data collection applications. PMID:27809260

New Flexible Silicone-Based EEG Dry Sensor Material Compositions Exhibiting Improvements in Lifespan, Conductivity, and Reliability.

PubMed

Yu, Yi-Hsin; Chen, Shih-Hsun; Chang, Che-Lun; Lin, Chin-Teng; Hairston, W David; Mrozek, Randy A

2016-10-31

This study investigates alternative material compositions for flexible silicone-based dry electroencephalography (EEG) electrodes to improve the performance lifespan while maintaining high-fidelity transmission of EEG signals. Electrode materials were fabricated with varying concentrations of silver-coated silica and silver flakes to evaluate their electrical, mechanical, and EEG transmission performance. Scanning electron microscope (SEM) analysis of the initial electrode development identified some weak points in the sensors' construction, including particle pull-out and ablation of the silver coating on the silica filler. The newly-developed sensor materials achieved significant improvement in EEG measurements while maintaining the advantages of previous silicone-based electrodes, including flexibility and non-toxicity. The experimental results indicated that the proposed electrodes maintained suitable performance even after exposure to temperature fluctuations, 85% relative humidity, and enhanced corrosion conditions demonstrating improvements in the environmental stability. Fabricated flat (forehead) and acicular (hairy sites) electrodes composed of the optimum identified formulation exhibited low impedance and reliable EEG measurement; some initial human experiments demonstrate the feasibility of using these silicone-based electrodes for typical lab data collection applications.

[Electroencephalographic effects of chlorphenesin carbamate, a new central muscle relaxant, in rabbits (author's transl)].

PubMed

Watanabe, S; Araki, H; Kawasaki, H; Ueki, S

1977-05-01

Electroencephalographic (EEG) effects of chlorphenesin carbamate were investigated in rabbits with chronic electrode implants, and compared with those of chlormezanone and methocarbamol. Chlorphenesin carbamate (50 mg/kg i.v., 100 mg/kg i.d.) induced a drowsy pattern of spontaneous EEG consisting of high voltage slow waves in the cortex and amygdala, and desynchronization of hippocampal theta waves. Chlormezanone also elicited similar EEG changes but such were much more potent than chlorphenesin carbamate. Methocarbamol showed no effect on spontaneous EEG. Chlorphenesin carbamate caused sedation in this period and muscle relaxation was more potent than that of chlormezanone. The EEG arousal response to auditory stimulation and to electric stimulation of the posterior hypothalamus, centromedian thalamus and mesencephalic reticular formation was slightly depressed by chlorphenesin carbamate. Chlorphenesin carbamate, as with chlormezanone, markedly depressed the limbic afterdischarges elicited by hippocampal stimulation. These EEG effects of chlorphenesin carbamate were qualitatively similar to but much weaker than those of chlormezanone, whereas the muscle relaxant effect of chlorphenesin carbamate was more potent than that of chlormezanone.

A longitudinal study of emotion regulation and anxiety in middle childhood: Associations with frontal EEG asymmetry in early childhood.

PubMed

Hannesdóttir, Dagmar Kr; Doxie, Jacquelyn; Bell, Martha Ann; Ollendick, Thomas H; Wolfe, Christy D

2010-03-01

We investigated whether brain electrical activity during early childhood was associated with anxiety symptoms and emotion regulation during a stressful situation during middle childhood. Frontal electroencephalogram (EEG) asymmetries were measured during baseline and during a cognitive control task at 4 1/2 years. Anxiety and emotion regulation were assessed during a stressful situation at age 9 (speech task), along with measures of heart rate (HR) and heart rate variability (HRV). Questionnaires were also used to assess anxiety and emotion regulation at age 9. Results from this longitudinal study indicated that children who exhibited right frontal asymmetry in early childhood experienced more physiological arousal (increased HR, decreased HRV) during the speech task at age 9 and less ability to regulate their emotions as reported by their parents. Findings are discussed in light of the associations between temperament and development of anxiety disorders.

Computation of Surface Laplacian for tri-polar ring electrodes on high-density realistic geometry head model.

PubMed

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.

EEG microstates during resting represent personality differences.

PubMed

Schlegel, Felix; Lehmann, Dietrich; Faber, Pascal L; Milz, Patricia; Gianotti, Lorena R R

2012-01-01

We investigated the spontaneous brain electric activity of 13 skeptics and 16 believers in paranormal phenomena; they were university students assessed with a self-report scale about paranormal beliefs. 33-channel EEG recordings during no-task resting were processed as sequences of momentary potential distribution maps. Based on the maps at peak times of Global Field Power, the sequences were parsed into segments of quasi-stable potential distribution, the 'microstates'. The microstates were clustered into four classes of map topographies (A-D). Analysis of the microstate parameters time coverage, occurrence frequency and duration as well as the temporal sequence (syntax) of the microstate classes revealed significant differences: Believers had a higher coverage and occurrence of class B, tended to decreased coverage and occurrence of class C, and showed a predominant sequence of microstate concatenations from A to C to B to A that was reversed in skeptics (A to B to C to A). Microstates of different topographies, putative "atoms of thought", are hypothesized to represent different types of information processing.The study demonstrates that personality differences can be detected in resting EEG microstate parameters and microstate syntax. Microstate analysis yielded no conclusive evidence for the hypothesized relation between paranormal belief and schizophrenia.

Analyzing EEG and MEG signals recorded during tES, a reply.

PubMed

Noury, Nima; Siegel, Markus

2018-02-15

Transcranial Electric Stimulation (tES) is a widely used non-invasive brain stimulation technique. However, strong stimulation artifacts complicate the investigation of neural activity with EEG or MEG during tES. Thus, studying brain signals during tES requires detailed knowledge about the properties of these artifacts. Recently, we characterized the phase- and amplitude-relationship between tES stimulation currents and tES artifacts in EEG and MEG and provided a mathematical model of these artifacts (Noury and Siegel, 2017, and Noury et al., 2016, respectively). Among several other features, we showed that, independent of the stimulation current, the amplitude of tES artifacts is modulated time locked to heartbeat and respiration. In response to our work, a recent paper (Neuling et al., 2017) raised several points concerning the employed stimulation device and methodology. Here, we discuss these points, explain potential misunderstandings, and show that none of the raised concerns are applicable to our results. Furthermore, we explain in detail the physics underlying tES artifacts, and discuss several approaches how to study brain function during tES in the presence of residual artifacts. Copyright © 2017 Elsevier Inc. All rights reserved.

Compact continuum brain model for human electroencephalogram

NASA Astrophysics Data System (ADS)

Kim, J. W.; Shin, H.-B.; Robinson, P. A.

2007-12-01

A low-dimensional, compact brain model has recently been developed based on physiologically based mean-field continuum formulation of electric activity of the brain. The essential feature of the new compact model is a second order time-delayed differential equation that has physiologically plausible terms, such as rapid corticocortical feedback and delayed feedback via extracortical pathways. Due to its compact form, the model facilitates insight into complex brain dynamics via standard linear and nonlinear techniques. The model successfully reproduces many features of previous models and experiments. For example, experimentally observed typical rhythms of electroencephalogram (EEG) signals are reproduced in a physiologically plausible parameter region. In the nonlinear regime, onsets of seizures, which often develop into limit cycles, are illustrated by modulating model parameters. It is also shown that a hysteresis can occur when the system has multiple attractors. As a further illustration of this approach, power spectra of the model are fitted to those of sleep EEGs of two subjects (one with apnea, the other with narcolepsy). The model parameters obtained from the fittings show good matches with previous literature. Our results suggest that the compact model can provide a theoretical basis for analyzing complex EEG signals.

Automatic detection of ischemic stroke based on scaling exponent electroencephalogram using extreme learning machine

NASA Astrophysics Data System (ADS)

Adhi, H. A.; Wijaya, S. K.; Prawito; Badri, C.; Rezal, M.

2017-03-01

Stroke is one of cerebrovascular diseases caused by the obstruction of blood flow to the brain. Stroke becomes the leading cause of death in Indonesia and the second in the world. Stroke also causes of the disability. Ischemic stroke accounts for most of all stroke cases. Obstruction of blood flow can cause tissue damage which results the electrical changes in the brain that can be observed through the electroencephalogram (EEG). In this study, we presented the results of automatic detection of ischemic stroke and normal subjects based on the scaling exponent EEG obtained through detrended fluctuation analysis (DFA) using extreme learning machine (ELM) as the classifier. The signal processing was performed with 18 channels of EEG in the range of 0-30 Hz. Scaling exponents of the subjects were used as the input for ELM to classify the ischemic stroke. The performance of detection was observed by the value of accuracy, sensitivity and specificity. The result showed, performance of the proposed method to classify the ischemic stroke was 84 % for accuracy, 82 % for sensitivity and 87 % for specificity with 120 hidden neurons and sine as the activation function of ELM.

Real-time monitoring of human blood-brain barrier disruption

PubMed Central

Kiviniemi, Vesa; Korhonen, Vesa; Kortelainen, Jukka; Rytky, Seppo; Keinänen, Tuija; Tuovinen, Timo; Isokangas, Matti; Sonkajärvi, Eila; Siniluoto, Topi; Nikkinen, Juha; Alahuhta, Seppo; Tervonen, Osmo; Turpeenniemi-Hujanen, Taina; Myllylä, Teemu; Kuittinen, Outi; Voipio, Juha

2017-01-01

Chemotherapy aided by opening of the blood-brain barrier with intra-arterial infusion of hyperosmolar mannitol improves the outcome in primary central nervous system lymphoma. Proper opening of the blood-brain barrier is crucial for the treatment, yet there are no means available for its real-time monitoring. The intact blood-brain barrier maintains a mV-level electrical potential difference between blood and brain tissue, giving rise to a measurable electrical signal at the scalp. Therefore, we used direct-current electroencephalography (DC-EEG) to characterize the spatiotemporal behavior of scalp-recorded slow electrical signals during blood-brain barrier opening. Nine anesthetized patients receiving chemotherapy were monitored continuously during 47 blood-brain barrier openings induced by carotid or vertebral artery mannitol infusion. Left or right carotid artery mannitol infusion generated a strongly lateralized DC-EEG response that began with a 2 min negative shift of up to 2000 μV followed by a positive shift lasting up to 20 min above the infused carotid artery territory, whereas contralateral responses were of opposite polarity. Vertebral artery mannitol infusion gave rise to a minimally lateralized and more uniformly distributed slow negative response with a posterior-frontal gradient. Simultaneously performed near-infrared spectroscopy detected a multiphasic response beginning with mannitol-bolus induced dilution of blood and ending in a prolonged increase in the oxy/deoxyhemoglobin ratio. The pronounced DC-EEG shifts are readily accounted for by opening and sealing of the blood-brain barrier. These data show that DC-EEG is a promising real-time monitoring tool for blood-brain barrier disruption augmented drug delivery. PMID:28319185

Topographic pharmaco-EEG mapping of the effects of the South American psychoactive beverage ayahuasca in healthy volunteers

PubMed Central

Riba, Jordi; Anderer, Peter; Morte, Adelaida; Urbano, Gloria; Jané, Francesc; Saletu, Bernd; Barbanoj, Manel J

2002-01-01

Aims Ayahuasca is a traditional South American psychoactive beverage used in Amazonian shamanism, and in the religious ceremonies of Brazilian-based syncretic religious groups with followers in the US and several European countries. This tea contains measurable amounts of the psychotropic indole N,N-dimethyltryptamine (DMT), and β-carboline alkaloids with MAO-inhibiting properties. In a previous report we described a profile of stimulant and psychedelic effects for ayahuasca as measured by subjective report self-assessment instruments. In the present study the cerebral bioavailability and time-course of effects of ayahuasca were assessed in humans by means of topographic quantitative-electroencephalography (q-EEG), a noninvasive method measuring drug-induced variations in brain electrical activity. Methods Two doses (one low and one high) of encapsulated freeze-dried ayahuasca, equivalent to 0.6 and 0.85 mg DMT kg−1 body weight, were administered to 18 healthy volunteers with previous experience in psychedelic drug use in a double-blind crossover placebo-controlled clinical trial. Nineteen-lead recordings were undertaken from baseline to 8 h after administration. Subjective effects were measured by means of the Hallucinogen Rating Scale (HRS). Results Ayahuasca induced a pattern of psychoactive effects which resulted in significant dose-dependent increases in all subscales of the HRS, and in significant and dose-dependent modifications of brain electrical activity. Absolute power decreased in all frequency bands, most prominently in the theta band. Mean absolute power decreases (95% CI) at a representative lead (P3) 90 min after the high dose were −20.20±15.23 µV2 and −2.70±2.21 µV2 for total power and theta power, respectively. Relative power decreased in the delta (−1.20±1.31% after 120 min at P3) and theta (−3.30±2.59% after 120 min at P3) bands, and increased in the beta band, most prominently in the faster beta-3 (1.00±0.88% after 90 min at P3) and beta-4 (0.30±0.24% after 90 min at P3) subbands. Finally, an increase was also seen for the centroid of the total activity and its deviation. EEG modifications began as early as 15–30 min, reached a peak between 45 and 120 min and decreased thereafter to return to baseline levels at 4–6 h after administration. Conclusions The central effects of ayahuasca could be objectively measured by means of q-EEG, showing a time pattern which closely paralleled that of previously reported subjective effects. The modifications seen for the individual q-EEG variables were in line with those previously described for other serotonergic psychedelics and share some features with the profile of effects shown by pro-serotonergic and pro-dopaminergic drugs. The q-EEG profile supports the role of 5-HT2 and dopamine D2-receptor agonism in mediating the effects of ayahuasca on the central nervous system. PMID:12047486

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

Gatzke-Kopp, L M; Raine, A; Buchsbaum, M; LaCasse, L

2001-01-01

This study evaluates electroencephalography (EEG) and positron emission tomography (PET) in the same subjects. Fourteen murderers were assessed by using both PET (while they were performing the continuous performance task) and EEG during a resting state. EEG revealed significant increases in slow-wave activity in the temporal, but not frontal, lobe in murderers, in contrast to prior PET findings that showed reduced prefrontal, but not temporal, glucose metabolism. Results suggest that resting EEG shows empirical utility distinct from PET activation findings.

Deficient "sensory" beta synchronization in Parkinson's disease.

PubMed

Degardin, A; Houdayer, E; Bourriez, J-L; Destée, A; Defebvre, L; Derambure, P; Devos, D

2009-03-01

Beta rhythm movement-related synchronization (beta synchronization) reflects motor cortex deactivation and sensory afference processing. In Parkinson's disease (PD), decreased beta synchronization after active movement reflects abnormal motor cortex idling and may be involved in the pathophysiology of akinesia. The objectives of the present study were to (i) compare event-related synchronization after active and passive movement and electrical nerve stimulation in PD patients and healthy, age-matched volunteers and (ii) evaluate the effect of levodopa. Using a 128-electrode EEG system, we studied beta synchronization after active and passive index finger movement and electrical median nerve stimulation in 13 patients and 12 control subjects. Patients were recorded before and after 150% of their usual morning dose of levodopa. The peak beta synchronization magnitude in the contralateral primary sensorimotor (PSM) cortex was significantly lower in PD patients after active movement, passive movement and electrical median nerve stimulation, compared with controls. Levodopa partially reversed the drop in beta synchronization after active movement but not after passive movement or electrical median nerve stimulation. If one considers that beta synchronization reflects sensory processing, our results suggest that integration of somaesthetic afferences in the PSM cortex is abnormal in PD during active and passive movement execution and after simple electrical median nerve stimulation. Better understanding of the mechanisms involved in the deficient beta synchronization observed here could prompt the development of new therapeutic approaches aimed at strengthening defective processes. The lack of full beta synchronization restoration by levodopa might be related to the involvement of non-dopaminergic pathways.

Synchronization of EEG activity in patients with bipolar disorder

NASA Astrophysics Data System (ADS)

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

2015-12-01

In paper we apply the method based on the Flicker-Noise Spectroscopy (FNS) to determine the differences in frequency-phase synchronization of the cortical electroencephalographic (EEG) activities in patients with bipolar disorder (BD). We found that for healthy subjects the frequency-phase synchronization of EEGs from long-range electrodes was significantly better for BD patients. In BD patients a high synchronization of EEGs was observed only for short-range electrodes. Thus, the FNS is a simple graphical method for qualitative analysis can be applied to identify the synchronization effects in EEG activity and, probably, may be used for the diagnosis of this syndrome.

Integrating EEG and fMRI in epilepsy.

PubMed

Formaggio, Emanuela; Storti, Silvia Francesca; Bertoldo, Alessandra; Manganotti, Paolo; Fiaschi, Antonio; Toffolo, Gianna Maria

2011-02-14

Integrating electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) studies enables to non-invasively investigate human brain function and to find the direct correlation of these two important measures of brain activity. Presurgical evaluation of patients with epilepsy is one of the areas where EEG and fMRI integration has considerable clinical relevance for localizing the brain regions generating interictal epileptiform activity. The conventional analysis of EEG-fMRI data is based on the visual identification of the interictal epileptiform discharges (IEDs) on scalp EEG. The convolution of these EEG events, represented as stick functions, with a model of the fMRI response, i.e. the hemodynamic response function, provides the regressor for general linear model (GLM) analysis of fMRI data. However, the conventional analysis is not automatic and suffers of some subjectivity in IEDs classification. Here, we present an easy-to-use and automatic approach for combined EEG-fMRI analysis able to improve IEDs identification based on Independent Component Analysis and wavelet analysis. EEG signal due to IED is reconstructed and its wavelet power is used as a regressor in GLM. The method was validated on simulated data and then applied on real data set consisting of 2 normal subjects and 5 patients with partial epilepsy. In all continuous EEG-fMRI recording sessions a good quality EEG was obtained allowing the detection of spontaneous IEDs and the analysis of the related BOLD activation. The main clinical finding in EEG-fMRI studies of patients with partial epilepsy is that focal interictal slow-wave activity was invariably associated with increased focal BOLD responses in a spatially related brain area. Our study extends current knowledge on epileptic foci localization and confirms previous reports suggesting that BOLD activation associated with slow activity might have a role in localizing the epileptogenic region even in the absence of clear interictal spikes. Copyright © 2010 Elsevier Inc. All rights reserved.

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy

PubMed Central

Shafi, Mouhsin M.; Whitfield-Gabrieli, Susan; Chu, Catherine J.; Pascual-Leone, Alvaro; Chang, Bernard S.

2017-01-01

Resting-state functional connectivity MRI (rs-fcMRI) is a technique that identifies connectivity between different brain regions based on correlations over time in the blood-oxygenation level dependent signal. rs-fcMRI has been applied extensively to identify abnormalities in brain connectivity in different neurologic and psychiatric diseases. However, the relationship among rs-fcMRI connectivity abnormalities, brain electrophysiology and disease state is unknown, in part because the causal significance of alterations in functional connectivity in disease pathophysiology has not been established. Transcranial Magnetic Stimulation (TMS) is a technique that uses electromagnetic induction to noninvasively produce focal changes in cortical activity. When combined with electroencephalography (EEG), TMS can be used to assess the brain's response to external perturbations. Here we provide a protocol for combining rs-fcMRI, TMS and EEG to assess the physiologic significance of alterations in functional connectivity in patients with neuropsychiatric disease. We provide representative results from a previously published study in which rs-fcMRI was used to identify regions with abnormal connectivity in patients with epilepsy due to a malformation of cortical development, periventricular nodular heterotopia (PNH). Stimulation in patients with epilepsy resulted in abnormal TMS-evoked EEG activity relative to stimulation of the same sites in matched healthy control patients, with an abnormal increase in the late component of the TMS-evoked potential, consistent with cortical hyperexcitability. This abnormality was specific to regions with abnormal resting-state functional connectivity. Electrical source analysis in a subject with previously recorded seizures demonstrated that the origin of the abnormal TMS-evoked activity co-localized with the seizure-onset zone, suggesting the presence of an epileptogenic circuit. These results demonstrate how rs-fcMRI, TMS and EEG can be utilized together to identify and understand the physiological significance of abnormal brain connectivity in human diseases. PMID:27911366

Ongoing slow oscillatory phase modulates speech intelligibility in cooperation with motor cortical activity.

PubMed

Onojima, Takayuki; Kitajo, Keiichi; Mizuhara, Hiroaki

2017-01-01

Neural oscillation is attracting attention as an underlying mechanism for speech recognition. Speech intelligibility is enhanced by the synchronization of speech rhythms and slow neural oscillation, which is typically observed as human scalp electroencephalography (EEG). In addition to the effect of neural oscillation, it has been proposed that speech recognition is enhanced by the identification of a speaker's motor signals, which are used for speech production. To verify the relationship between the effect of neural oscillation and motor cortical activity, we measured scalp EEG, and simultaneous EEG and functional magnetic resonance imaging (fMRI) during a speech recognition task in which participants were required to recognize spoken words embedded in noise sound. We proposed an index to quantitatively evaluate the EEG phase effect on behavioral performance. The results showed that the delta and theta EEG phase before speech inputs modulated the participant's response time when conducting speech recognition tasks. The simultaneous EEG-fMRI experiment showed that slow EEG activity was correlated with motor cortical activity. These results suggested that the effect of the slow oscillatory phase was associated with the activity of the motor cortex during speech recognition.

Emergency Department Triage of Traumatic Head Injury Using a Brain Electrical Activity Biomarker: A Multisite Prospective Observational Validation Trial.

PubMed

Hanley, Daniel; Prichep, Leslie S; Bazarian, Jeffrey; Huff, J Stephen; Naunheim, Rosanne; Garrett, John; Jones, Elizabeth B; Wright, David W; O'Neill, John; Badjatia, Neeraj; Gandhi, Dheeraj; Curley, Kenneth C; Chiacchierini, Richard; O'Neil, Brian; Hack, Dallas C

2017-05-01

A brain electrical activity biomarker for identifying traumatic brain injury (TBI) in emergency department (ED) patients presenting with high Glasgow Coma Scale (GCS) after sustaining a head injury has shown promise for objective, rapid triage. The main objective of this study was to prospectively evaluate the efficacy of an automated classification algorithm to determine the likelihood of being computed tomography (CT) positive, in high-functioning TBI patients in the acute state. Adult patients admitted to the ED for evaluation within 72 hours of sustaining a closed head injury with GCS 12 to 15 were candidates for study. A total of 720 patients (18-85 years) meeting inclusion/exclusion criteria were enrolled in this observational, prospective validation trial, at 11 U.S. EDs. GCS was 15 in 97%, with the first and third quartiles being 15 (interquartile range = 0) in the study population at the time of the evaluation. Standard clinical evaluations were conducted and 5 to 10 minutes of electroencephalogram (EEG) was acquired from frontal and frontal-temporal scalp locations. Using an a priori derived EEG-based classification algorithm developed on an independent population and applied to this validation population prospectively, the likelihood of each subject being CT+ was determined, and performance metrics were computed relative to adjudicated CT findings. Sensitivity of the binary classifier (likely CT+ or CT-) was 92.3% (95% confidence interval [CI] = 87.8%-95.5%) for detection of any intracranial injury visible on CT (CT+), with specificity of 51.6% (95% CI = 48.1%-55.1%) and negative predictive value (NPV) of 96.0% (95% CI = 93.2%-97.9%). Using ternary classification (likely CT+, equivocal, likely CT-) demonstrated enhanced sensitivity to traumatic hematomas (≥1 mL of blood), 98.6% (95% CI = 92.6%-100.0%), and NPV of 98.2% (95% CI = 95.5%-99.5%). Using an EEG-based biomarker high accuracy of predicting the likelihood of being CT+ was obtained, with high NPV and sensitivity to any traumatic bleeding and to hematomas. Specificity was significantly higher than standard CT decision rules. The short time to acquire results and the ease of use in the ED environment suggests that EEG-based classifier algorithms have potential to impact triage and clinical management of head-injured patients. © 2017 by the Society for Academic Emergency Medicine.

A system for automatic artifact removal in ictal scalp EEG based on independent component analysis and Bayesian classification.

PubMed

LeVan, P; Urrestarazu, E; Gotman, J

2006-04-01

To devise an automated system to remove artifacts from ictal scalp EEG, using independent component analysis (ICA). A Bayesian classifier was used to determine the probability that 2s epochs of seizure segments decomposed by ICA represented EEG activity, as opposed to artifact. The classifier was trained using numerous statistical, spectral, and spatial features. The system's performance was then assessed using separate validation data. The classifier identified epochs representing EEG activity in the validation dataset with a sensitivity of 82.4% and a specificity of 83.3%. An ICA component was considered to represent EEG activity if the sum of the probabilities that its epochs represented EEG exceeded a threshold predetermined using the training data. Otherwise, the component represented artifact. Using this threshold on the validation set, the identification of EEG components was performed with a sensitivity of 87.6% and a specificity of 70.2%. Most misclassified components were a mixture of EEG and artifactual activity. The automated system successfully rejected a good proportion of artifactual components extracted by ICA, while preserving almost all EEG components. The misclassification rate was comparable to the variability observed in human classification. Current ICA methods of artifact removal require a tedious visual classification of the components. The proposed system automates this process and removes simultaneously multiple types of artifacts.

Detection of epileptiform activity in EEG signals based on time-frequency and non-linear analysis

PubMed Central

Gajic, Dragoljub; Djurovic, Zeljko; Gligorijevic, Jovan; Di Gennaro, Stefano; Savic-Gajic, Ivana

2015-01-01

We present a new technique for detection of epileptiform activity in EEG signals. After preprocessing of EEG signals we extract representative features in time, frequency and time-frequency domain as well as using non-linear analysis. The features are extracted in a few frequency sub-bands of clinical interest since these sub-bands showed much better discriminatory characteristics compared with the whole frequency band. Then we optimally reduce the dimension of feature space to two using scatter matrices. A decision about the presence of epileptiform activity in EEG signals is made by quadratic classifiers designed in the reduced two-dimensional feature space. The accuracy of the technique was tested on three sets of electroencephalographic (EEG) signals recorded at the University Hospital Bonn: surface EEG signals from healthy volunteers, intracranial EEG signals from the epilepsy patients during the seizure free interval from within the seizure focus and intracranial EEG signals of epileptic seizures also from within the seizure focus. An overall detection accuracy of 98.7% was achieved. PMID:25852534

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

PubMed

Pizzagalli, D; Koenig, T; Regard, M; Lehmann, D

1999-01-01

We investigated whether different, personality-related affective attitudes are associated with different brain electric field (EEG) sources before any emotional challenge (stimulus exposure). A 27-channel EEG was recorded in 15 subjects during eyes-closed resting. After recording, subjects rated 32 images of human faces for affective appeal. The subjects in the first (i.e., most negative) and fourth (i.e., most positive) quartile of general affective attitude were further analyzed. The EEG data (mean=25+/-4. 8 s/subject) were subjected to frequency-domain model dipole source analysis (FFT-Dipole-Approximation), resulting in 3-dimensional intracerebral source locations and strengths for the delta-theta, alpha, and beta EEG frequency band, and for the full range (1.5-30 Hz) band. Subjects with negative attitude (compared to those with positive attitude) showed the following source locations: more inferior for all frequency bands, more anterior for the delta-theta band, more posterior and more right for the alpha, beta and 1.5-30 Hz bands. One year later, the subjects were asked to rate the face images again. The rating scores for the same face images were highly correlated for all subjects, and original and retest affective mean attitude was highly correlated across subjects. The present results show that subjects with different affective attitudes to face images had different active, cerebral, neural populations in a task-free condition prior to viewing the images. We conclude that the brain functional state which implements affective attitude towards face images as a personality feature exists without elicitors, as a continuously present, dynamic feature of brain functioning. Copyright 1999 Elsevier Science B.V.

Detecting large-scale networks in the human brain using high-density electroencephalography.

PubMed

Liu, Quanying; Farahibozorg, Seyedehrezvan; Porcaro, Camillo; Wenderoth, Nicole; Mantini, Dante

2017-09-01

High-density electroencephalography (hdEEG) is an emerging brain imaging technique that can be used to investigate fast dynamics of electrical activity in the healthy and the diseased human brain. Its applications are however currently limited by a number of methodological issues, among which the difficulty in obtaining accurate source localizations. In particular, these issues have so far prevented EEG studies from reporting brain networks similar to those previously detected by functional magnetic resonance imaging (fMRI). Here, we report for the first time a robust detection of brain networks from resting state (256-channel) hdEEG recordings. Specifically, we obtained 14 networks previously described in fMRI studies by means of realistic 12-layer head models and exact low-resolution brain electromagnetic tomography (eLORETA) source localization, together with independent component analysis (ICA) for functional connectivity analysis. Our analyses revealed three important methodological aspects. First, brain network reconstruction can be improved by performing source localization using the gray matter as source space, instead of the whole brain. Second, conducting EEG connectivity analyses in individual space rather than on concatenated datasets may be preferable, as it permits to incorporate realistic information on head modeling and electrode positioning. Third, the use of a wide frequency band leads to an unbiased and generally accurate reconstruction of several network maps, whereas filtering data in a narrow frequency band may enhance the detection of specific networks and penalize that of others. We hope that our methodological work will contribute to rise of hdEEG as a powerful tool for brain research. Hum Brain Mapp 38:4631-4643, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Intracranial electroencephalography power and phase synchronization changes during monaural and binaural beat stimulation.

PubMed

Becher, Ann-Katrin; Höhne, Marlene; Axmacher, Nikolai; Chaieb, Leila; Elger, Christian E; Fell, Juergen

2015-01-01

Auditory stimulation with monaural or binaural auditory beats (i.e. sine waves with nearby frequencies presented either to both ears or to each ear separately) represents a non-invasive approach to influence electrical brain activity. It is still unclear exactly which brain sites are affected by beat stimulation. In particular, an impact of beat stimulation on mediotemporal brain areas could possibly provide new options for memory enhancement or seizure control. Therefore, we examined how electroencephalography (EEG) power and phase synchronization are modulated by auditory stimulation with beat frequencies corresponding to dominant EEG rhythms based on intracranial recordings in presurgical epilepsy patients. Monaural and binaural beat stimuli with beat frequencies of 5, 10, 40 and 80 Hz and non-superposed control signals were administered with low amplitudes (60 dB SPL) and for short durations (5 s). EEG power was intracranially recorded from mediotemporal, temporo-basal and temporo-lateral and surface sites. Evoked and total EEG power and phase synchronization during beat vs. control stimulation were compared by the use of Bonferroni-corrected non-parametric label-permutation tests. We found that power and phase synchronization were significantly modulated by beat stimulation not only at temporo-basal, temporo-lateral and surface sites, but also at mediotemporal sites. Generally, more significant decreases than increases were observed. The most prominent power increases were seen after stimulation with monaural 40-Hz beats. The most pronounced power and synchronization decreases resulted from stimulation with monaural 5-Hz and binaural 80-Hz beats. Our results suggest that beat stimulation offers a non-invasive approach for the modulation of intracranial EEG characteristics. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Automatic classification of background EEG activity in healthy and sick neonates

NASA Astrophysics Data System (ADS)

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

2010-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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

PubMed Central

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

2017-01-01

Subcortical structures play a critical role in brain function. However, options for assessing electrophysiological activity in these structures are limited. Electromagnetic fields generated by neuronal activity in subcortical structures can be recorded noninvasively, using magnetoencephalography (MEG) and electroencephalography (EEG). However, these subcortical signals are much weaker than those generated by cortical activity. In addition, we show here that it is difficult to resolve subcortical sources because distributed cortical activity can explain the MEG and EEG patterns generated by deep sources. We then demonstrate that if the cortical activity is spatially sparse, both cortical and subcortical sources can be resolved with M/EEG. Building on this insight, we develop a hierarchical sparse inverse solution for M/EEG. We assess the performance of this algorithm on realistic simulations and auditory evoked response data, and show that thalamic and brainstem sources can be correctly estimated in the presence of cortical activity. Our work provides alternative perspectives and tools for characterizing electrophysiological activity in subcortical structures in the human brain. PMID:29138310

Spatio-temporal dynamics of multimodal EEG-fNIRS signals in the loss and recovery of consciousness under sedation using midazolam and propofol.

PubMed

Yeom, Seul-Ki; Won, Dong-Ok; Chi, Seong In; Seo, Kwang-Suk; Kim, Hyun Jeong; Müller, Klaus-Robert; Lee, Seong-Whan

2017-01-01

On sedation motivated by the clinical needs for safety and reliability, recent studies have attempted to identify brain-specific signatures for tracking patient transition into and out of consciousness, but the differences in neurophysiological effects between 1) the sedative types and 2) the presence/absence of surgical stimulations still remain unclear. Here we used multimodal electroencephalography-functional near-infrared spectroscopy (EEG-fNIRS) measurements to observe electrical and hemodynamic responses during sedation simultaneously. Forty healthy volunteers were instructed to push the button to administer sedatives in response to auditory stimuli every 9-11 s. To generally illustrate brain activity at repetitive transition points at the loss of consciousness (LOC) and the recovery of consciousness (ROC), patient-controlled sedation was performed using two different sedatives (midazolam (MDZ) and propofol (PPF)) under two surgical conditions. Once consciousness was lost via sedatives, we observed gradually increasing EEG power at lower frequencies (<15 Hz) and decreasing power at higher frequencies (>15 Hz), as well as spatially increased EEG powers in the delta and lower alpha bands, and particularly also in the upper alpha rhythm, at the frontal and parieto-occipital areas over time. During ROC from unconsciousness, these spatio-temporal changes were reversed. Interestingly, the level of consciousness was switched on/off at significantly higher effect-site concentrations of sedatives in the brain according to the use of surgical stimuli, but the spatio-temporal EEG patterns were similar, regardless of the sedative used. We also observed sudden phase shifts in fronto-parietal connectivity at the LOC and the ROC as critical points. fNIRS measurement also revealed mild hemodynamic fluctuations. Compared with general anesthesia, our results provide insights into critical hallmarks of sedative-induced (un)consciousness, which have similar spatio-temporal EEG-fNIRS patterns regardless of the stage and the sedative used.

3D source localization of interictal spikes in epilepsy patients with MRI lesions

NASA Astrophysics Data System (ADS)

Ding, Lei; Worrell, Gregory A.; Lagerlund, Terrence D.; He, Bin

2006-08-01

The present study aims to accurately localize epileptogenic regions which are responsible for epileptic activities in epilepsy patients by means of a new subspace source localization approach, i.e. first principle vectors (FINE), using scalp EEG recordings. Computer simulations were first performed to assess source localization accuracy of FINE in the clinical electrode set-up. The source localization results from FINE were compared with the results from a classic subspace source localization approach, i.e. MUSIC, and their differences were tested statistically using the paired t-test. Other factors influencing the source localization accuracy were assessed statistically by ANOVA. The interictal epileptiform spike data from three adult epilepsy patients with medically intractable partial epilepsy and well-defined symptomatic MRI lesions were then studied using both FINE and MUSIC. The comparison between the electrical sources estimated by the subspace source localization approaches and MRI lesions was made through the coregistration between the EEG recordings and MRI scans. The accuracy of estimations made by FINE and MUSIC was also evaluated and compared by R2 statistic, which was used to indicate the goodness-of-fit of the estimated sources to the scalp EEG recordings. The three-concentric-spheres head volume conductor model was built for each patient with three spheres of different radii which takes the individual head size and skull thickness into consideration. The results from computer simulations indicate that the improvement of source spatial resolvability and localization accuracy of FINE as compared with MUSIC is significant when simulated sources are closely spaced, deep, or signal-to-noise ratio is low in a clinical electrode set-up. The interictal electrical generators estimated by FINE and MUSIC are in concordance with the patients' structural abnormality, i.e. MRI lesions, in all three patients. The higher R2 values achieved by FINE than MUSIC indicate that FINE provides a more satisfactory fitting of the scalp potential measurements than MUSIC in all patients. The present results suggest that FINE provides a useful brain source imaging technique, from clinical EEG recordings, for identifying and localizing epileptogenic regions in epilepsy patients with focal partial seizures. The present study may lead to the establishment of a high-resolution source localization technique from scalp-recorded EEGs for aiding presurgical planning in epilepsy patients.

An EEG Finger-Print of fMRI deep regional activation.

PubMed

Meir-Hasson, Yehudit; Kinreich, Sivan; Podlipsky, Ilana; Hendler, Talma; Intrator, Nathan

2014-11-15

This work introduces a general framework for producing an EEG Finger-Print (EFP) which can be used to predict specific brain activity as measured by fMRI at a given deep region. This new approach allows for improved EEG spatial resolution based on simultaneous fMRI activity measurements. Advanced signal processing and machine learning methods were applied on EEG data acquired simultaneously with fMRI during relaxation training guided by on-line continuous feedback on changing alpha/theta EEG measure. We focused on demonstrating improved EEG prediction of activation in sub-cortical regions such as the amygdala. Our analysis shows that a ridge regression model that is based on time/frequency representation of EEG data from a single electrode, can predict the amygdala related activity significantly better than a traditional theta/alpha activity sampled from the best electrode and about 1/3 of the times, significantly better than a linear combination of frequencies with a pre-defined delay. The far-reaching goal of our approach is to be able to reduce the need for fMRI scanning for probing specific sub-cortical regions such as the amygdala as the basis for brain-training procedures. On the other hand, activity in those regions can be characterized with higher temporal resolution than is obtained by fMRI alone thus revealing additional information about their processing mode. Copyright © 2013 Elsevier Inc. All rights reserved.

Imagined Hand Clenching Force and Speed Modulate Brain Activity and Are Classified by NIRS Combined With EEG.

PubMed

Fu, Yunfa; Xiong, Xin; Jiang, Changhao; Xu, Baolei; Li, Yongcheng; Li, Hongyi

2017-09-01

Simultaneous acquisition of brain activity signals from the sensorimotor area using NIRS combined with EEG, imagined hand clenching force and speed modulation of brain activity, as well as 6-class classification of these imagined motor parameters by NIRS-EEG were explored. Near infrared probes were aligned with C3 and C4, and EEG electrodes were placed midway between the NIRS probes. NIRS and EEG signals were acquired from six healthy subjects during six imagined hand clenching force and speed tasks involving the right hand. The results showed that NIRS combined with EEG is effective for simultaneously measuring brain activity of the sensorimotor area. The study also showed that in the duration of (0, 10) s for imagined force and speed of hand clenching, HbO first exhibited a negative variation trend, which was followed by a negative peak. After the negative peak, it exhibited a positive variation trend with a positive peak about 6-8 s after termination of imagined movement. During (-2, 1) s, the EEG may have indicated neural processing during the preparation, execution, and monitoring of a given imagined force and speed of hand clenching. The instantaneous phase, frequency, and amplitude feature of the EEG were calculated by Hilbert transform; HbO and the difference between HbO and Hb concentrations were extracted. The features of NIRS and EEG were combined to classify three levels of imagined force [at 20/50/80% MVGF (maximum voluntary grip force)] and speed (at 0.5/1/2 Hz) of hand clenching by SVM. The average classification accuracy of the NIRS-EEG fusion feature was 0.74 ± 0.02. These results may provide increased control commands of force and speed for a brain-controlled robot based on NIRS-EEG.

Understanding the pathophysiology of reflex epilepsy using simultaneous EEG-fMRI.

PubMed

Sandhya, Manglore; Bharath, Rose Dawn; Panda, Rajanikant; Chandra, S R; Kumar, Naveen; George, Lija; Thamodharan, A; Gupta, Arun Kumar; Satishchandra, P

2014-03-01

Measuring neuro-haemodynamic correlates in the brain of epilepsy patients using EEG-fMRI has opened new avenues in clinical neuroscience, as these are two complementary methods for understanding brain function. In this study, we investigated three patients with drug-resistant reflex epilepsy using EEG-fMRI. Different types of reflex epilepsy such as eating, startle myoclonus, and hot water epilepsy were included in the study. The analysis of EEG-fMRI data was based on the visual identification of interictal epileptiform discharges on scalp EEG. The convolution of onset time and duration of these epilepsy spikes was estimated, and using these condition-specific effects in a general linear model approach, we evaluated activation of fMRI. Patients with startle myoclonus epilepsy experienced epilepsy in response to sudden sound or touch, in association with increased delta and theta activity with a spike-and-slow-wave pattern of interictal epileptiform discharges on EEG and fronto-parietal network activation pattern on SPECT and EEG-fMRI. Eating epilepsy was triggered by sight or smell of food and fronto-temporal discharges were noted on video-EEG (VEEG). Similarly, fronto-temporo-parietal involvement was noted on SPECT and EEG-fMRI. Hot water epilepsy was triggered by contact with hot water either in the bath or by hand immersion, and VEEG showed fronto-parietal involvement. SPECT and EEG fMRI revealed a similar fronto-parietal-occipital involvement. From these results, we conclude that continuous EEG recording can improve the modelling of BOLD changes related to interictal epileptic activity and this can thus be used to understand the neuro-haemodynamic substrates involved in reflex epilepsy.

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

PubMed

Grin-Yatsenko, Vera A; Ponomarev, Valery A; Pronina, Marina V; Poliakov, Yury I; Plotnikova, Irina V; Kropotov, Juri D

2017-09-01

We evaluated EEG frequency abnormalities in resting state (eyes closed and eyes open) EEG in a group of chronic schizophrenia patients as compared with healthy subjects. The study included 3 methods of analysis of deviation of EEG characteristics: genuine EEG, current source density (CSD), and group independent component (gIC). All 3 methods have shown that the EEG in schizophrenia patients is characterized by enhanced low-frequency (delta and theta) and high-frequency (beta) activity in comparison with the control group. However, the spatial pattern of differences was dependent on the type of method used. Comparative analysis has shown that increased EEG power in schizophrenia patients apparently concerns both widely spatially distributed components and local components of signal. Furthermore, the observed differences in the delta and theta range can be described mainly by the local components, and those in the beta range mostly by spatially widely distributed ones. The possible nature of the widely distributed activity is discussed.

Neurophysiological correlates of eye movement desensitization and reprocessing sessions: preliminary evidence for traumatic memories integration.

PubMed

Farina, Benedetto; Imperatori, Claudio; Quintiliani, Maria I; Castelli Gattinara, Paola; Onofri, Antonio; Lepore, Marta; Brunetti, Riccardo; Losurdo, Anna; Testani, Elisa; Della Marca, Giacomo

2015-11-01

We have investigated the potential role of eye movement desensitization and reprocessing (EMDR) in enhancing the integration of traumatic memories by measuring EEG coherence, power spectra and autonomic variables before (pre-EMDR) and after (post-EMDR) EMDR sessions during the recall of patient's traumatic memory. Thirteen EMDR sessions of six patients with post-traumatic stress disorder were recorded. EEG analyses were conducted by means of the standardized Low Resolution Electric Tomography (sLORETA) software. Power spectra, EEG coherence and heart rate variability (HRV) were compared between pre- and post-EMDR sessions. After EMDR, we observed a significant increase of alpha power in the left inferior temporal gyrus (T = 3.879; P = 0.041) and an increased EEG coherence in beta band between C3 and T5 electrodes (T = 6.358; P < 0.001). Furthermore, a significant increase of HRV in the post-EMDR sessions was also observed (pre-EMDR: 6.38 ± 6.83; post-EMDR: 2.46 ± 2.95; U-Test = 45, P = 0.043). Finally, the values of lagged coherence were negatively associated with subjective units of disturbance (r(24) = -0.44, P < 0.05) and positively associated with parasympathetic activity (r(24) = 0.40, P < 0.05). Our results suggest that EMDR leads to an integration of dissociated aspects of traumatic memories and, consequently, a decrease of hyperarousal symptoms [Correction made here after initial publication]. © 2014 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.

Single-trial EEG-informed fMRI analysis of emotional decision problems in hot executive function.

PubMed

Guo, Qian; Zhou, Tiantong; Li, Wenjie; Dong, Li; Wang, Suhong; Zou, Ling

2017-07-01

Executive function refers to conscious control in psychological process which relates to thinking and action. Emotional decision is a part of hot executive function and contains emotion and logic elements. As a kind of important social adaptation ability, more and more attention has been paid in recent years. Gambling task can be well performed in the study of emotional decision. As fMRI researches focused on gambling task show not completely consistent brain activation regions, this study adopted EEG-fMRI fusion technology to reveal brain neural activity related with feedback stimuli. In this study, an EEG-informed fMRI analysis was applied to process simultaneous EEG-fMRI data. First, relative power-spectrum analysis and K-means clustering method were performed separately to extract EEG-fMRI features. Then, Generalized linear models were structured using fMRI data and using different EEG features as regressors. The results showed that in the win versus loss stimuli, the activated regions almost covered the caudate, the ventral striatum (VS), the orbital frontal cortex (OFC), and the cingulate. Wide activation areas associated with reward and punishment were revealed by the EEG-fMRI integration analysis than the conventional fMRI results, such as the posterior cingulate and the OFC. The VS and the medial prefrontal cortex (mPFC) were found when EEG power features were performed as regressors of GLM compared with results entering the amplitudes of feedback-related negativity (FRN) as regressors. Furthermore, the brain region activation intensity was the strongest when theta-band power was used as a regressor compared with the other two fusion results. The EEG-based fMRI analysis can more accurately depict the whole-brain activation map and analyze emotional decision problems.

k-Nearest neighbour local linear prediction of scalp EEG activity during intermittent photic stimulation.

PubMed

Erla, Silvia; Faes, Luca; Tranquillini, Enzo; Orrico, Daniele; Nollo, Giandomenico

2011-05-01

The characterization of the EEG response to photic stimulation (PS) is an important issue with significant clinical relevance. This study aims to quantify and map the complexity of the EEG during PS, where complexity is measured as the degree of unpredictability resulting from local linear prediction. EEG activity was recorded with eyes closed (EC) and eyes open (EO) during resting and PS at 5, 10, and 15 Hz in a group of 30 healthy subjects and in a case-report of a patient suffering from cerebral ischemia. The mean squared prediction error (MSPE) resulting from k-nearest neighbour local linear prediction was calculated in each condition as an index of EEG unpredictability. The linear or nonlinear nature of the system underlying EEG activity was evaluated quantifying MSPE as a function of the neighbourhood size during local linear prediction, and by surrogate data analysis as well. Unpredictability maps were obtained for each subject interpolating MSPE values over a schematic head representation. Results on healthy subjects evidenced: (i) the prevalence of linear mechanisms in the generation of EEG dynamics, (ii) the lower predictability of EO EEG, (iii) the desynchronization of oscillatory mechanisms during PS leading to increased EEG complexity, (iv) the entrainment of alpha rhythm during EC obtained by 10 Hz PS, and (v) differences of EEG predictability among different scalp regions. Ischemic patient showed different MSPE values in healthy and damaged regions. The EEG predictability decreased moving from the early acute stage to a stage of partial recovery. These results suggest that nonlinear prediction can be a useful tool to characterize EEG dynamics during PS protocols, and may consequently constitute a complement of quantitative EEG analysis in clinical applications. Copyright © 2010 IPEM. Published by Elsevier Ltd. All rights reserved.

Effects of oral amines on the EEG.

PubMed

Scott, D F; Moffett, A M; Swash, M

1977-02-01

Oral tyramine activated pre-existing episodic EEG abnormalities--namely, sharp waves, spike and wave, and localised theta activity--in epileptic patients. Little change was found in the EEGs of migrainous subjects after chocolate or beta-phenylethylamine. The implications of the findings with tyramine are discussed.

[The role of ambulatory electroencephalogram monitoring: experience and results in 264 records].

PubMed

González de la Aleja, J; Saiz Díaz, R A; Martín García, H; Juntas, R; Pérez-Martínez, D; de la Peña, P

2008-11-01

Ambulatory electroencephalogram (EEG) monitoring allows for long-term, mobile electroencephalographic recordings of patients. This study aims to describe and analyze the results obtained with ambulatory EEG in our clinical practice. We have analyzed the results of 264 ambulatory EEG records, grouped according to the reason for the request: a) group 1: diagnostic evaluation of episodes of epileptic nature; b) group 2: diagnostic evaluation of paroxysmal episodes, and c) group 3: evaluation of the risk of relapse during anti-seizure treatment withdrawal in certain epileptic patients. a) Group 1 (n=137): normal results were found in 54 records (39.4%). There was generalized epileptic activity in 20 (14.6%) of them (5 with ictal activity) and focal epileptic activity was detected in 57 cases (42%) (8 with ictal activity). No EEG diagnosis could be reached in 6 (4%) recordings due to the presence of artefacts; b) group 2 (n=99): in 47 records (47.5 %), there were no episodes and the Holter-EEG was normal. There was a clinically documented episode without anomalies during Holter-EEG registration in 14 cases (14.2%). In 29 records (29.3%), focal epileptic activity was recorded (ictal 4) and generalized epileptic activity (ictal in 1) was recorded in 4 patients (4%). No EEG diagnosis could be reached in 5 cases (5%), and c) group 3 (n=28): the study was normal in 15 cases (53.6%) and showed focal interictal epileptic activity in 8 (28.6 %) and generalized interictal epileptic activity in 5 of them (17.8%). We believe that the ambulatory EEG recordings in correctly selected cases can provide important additional information regarding global assessment of patients with epilepsy.

Change in Mean Frequency of Resting-State Electroencephalography after Transcranial Direct Current Stimulation

PubMed Central

Boonstra, Tjeerd W.; Nikolin, Stevan; Meisener, Ann-Christin; Martin, Donel M.; Loo, Colleen K.

2016-01-01

Transcranial direct current stimulation (tDCS) is proposed as a tool to investigate cognitive functioning in healthy people and as a treatment for various neuropathological disorders. However, the underlying cortical mechanisms remain poorly understood. We aim to investigate whether resting-state electroencephalography (EEG) can be used to monitor the effects of tDCS on cortical activity. To this end we tested whether the spectral content of ongoing EEG activity is significantly different after a single session of active tDCS compared to sham stimulation. Twenty participants were tested in a sham-controlled, randomized, crossover design. Resting-state EEG was acquired before, during and after active tDCS to the left dorsolateral prefrontal cortex (15 min of 2 mA tDCS) and sham stimulation. Electrodes with a diameter of 3.14 cm2 were used for EEG and tDCS. Partial least squares (PLS) analysis was used to examine differences in power spectral density (PSD) and the EEG mean frequency to quantify the slowing of EEG activity after stimulation. PLS revealed a significant increase in spectral power at frequencies below 15 Hz and a decrease at frequencies above 15 Hz after active tDCS (P = 0.001). The EEG mean frequency was significantly reduced after both active tDCS (P < 0.0005) and sham tDCS (P = 0.001), though the decrease in mean frequency was smaller after sham tDCS than after active tDCS (P = 0.073). Anodal tDCS of the left DLPFC using a high current density bi-frontal electrode montage resulted in general slowing of resting-state EEG. The similar findings observed following sham stimulation question whether the standard sham protocol is an appropriate control condition for tDCS. PMID:27375462

Unimodal Versus Bimodal EEG-fMRI Neurofeedback of a Motor Imagery Task.

PubMed

Perronnet, Lorraine; Lécuyer, Anatole; Mano, Marsel; Bannier, Elise; Lotte, Fabien; Clerc, Maureen; Barillot, Christian

2017-01-01

Neurofeedback is a promising tool for brain rehabilitation and peak performance training. Neurofeedback approaches usually rely on a single brain imaging modality such as EEG or fMRI. Combining these modalities for neurofeedback training could allow to provide richer information to the subject and could thus enable him/her to achieve faster and more specific self-regulation. Yet unimodal and multimodal neurofeedback have never been compared before. In the present work, we introduce a simultaneous EEG-fMRI experimental protocol in which participants performed a motor-imagery task in unimodal and bimodal NF conditions. With this protocol we were able to compare for the first time the effects of unimodal EEG-neurofeedback and fMRI-neurofeedback versus bimodal EEG-fMRI-neurofeedback by looking both at EEG and fMRI activations. We also propose a new feedback metaphor for bimodal EEG-fMRI-neurofeedback that integrates both EEG and fMRI signal in a single bi-dimensional feedback (a ball moving in 2D). Such a feedback is intended to relieve the cognitive load of the subject by presenting the bimodal neurofeedback task as a single regulation task instead of two. Additionally, this integrated feedback metaphor gives flexibility on defining a bimodal neurofeedback target. Participants were able to regulate activity in their motor regions in all NF conditions. Moreover, motor activations as revealed by offline fMRI analysis were stronger during EEG-fMRI-neurofeedback than during EEG-neurofeedback. This result suggests that EEG-fMRI-neurofeedback could be more specific or more engaging than EEG-neurofeedback. Our results also suggest that during EEG-fMRI-neurofeedback, participants tended to regulate more the modality that was harder to control. Taken together our results shed first light on the specific mechanisms of bimodal EEG-fMRI-neurofeedback and on its added-value as compared to unimodal EEG-neurofeedback and fMRI-neurofeedback.

Unimodal Versus Bimodal EEG-fMRI Neurofeedback of a Motor Imagery Task

PubMed Central

Perronnet, Lorraine; Lécuyer, Anatole; Mano, Marsel; Bannier, Elise; Lotte, Fabien; Clerc, Maureen; Barillot, Christian

2017-01-01

Neurofeedback is a promising tool for brain rehabilitation and peak performance training. Neurofeedback approaches usually rely on a single brain imaging modality such as EEG or fMRI. Combining these modalities for neurofeedback training could allow to provide richer information to the subject and could thus enable him/her to achieve faster and more specific self-regulation. Yet unimodal and multimodal neurofeedback have never been compared before. In the present work, we introduce a simultaneous EEG-fMRI experimental protocol in which participants performed a motor-imagery task in unimodal and bimodal NF conditions. With this protocol we were able to compare for the first time the effects of unimodal EEG-neurofeedback and fMRI-neurofeedback versus bimodal EEG-fMRI-neurofeedback by looking both at EEG and fMRI activations. We also propose a new feedback metaphor for bimodal EEG-fMRI-neurofeedback that integrates both EEG and fMRI signal in a single bi-dimensional feedback (a ball moving in 2D). Such a feedback is intended to relieve the cognitive load of the subject by presenting the bimodal neurofeedback task as a single regulation task instead of two. Additionally, this integrated feedback metaphor gives flexibility on defining a bimodal neurofeedback target. Participants were able to regulate activity in their motor regions in all NF conditions. Moreover, motor activations as revealed by offline fMRI analysis were stronger during EEG-fMRI-neurofeedback than during EEG-neurofeedback. This result suggests that EEG-fMRI-neurofeedback could be more specific or more engaging than EEG-neurofeedback. Our results also suggest that during EEG-fMRI-neurofeedback, participants tended to regulate more the modality that was harder to control. Taken together our results shed first light on the specific mechanisms of bimodal EEG-fMRI-neurofeedback and on its added-value as compared to unimodal EEG-neurofeedback and fMRI-neurofeedback. PMID:28473762

Frontal EEG and emotion regulation: electrocortical activity in response to emotional film clips is associated with reduced mood induction and attention interference effects.

PubMed

Dennis, Tracy A; Solomon, Beylul

2010-12-01

Frontal EEG activity is thought to reflect affective dispositions, but may also reflect the emotional demands of a specific context combined with the capability to regulate emotions in that context. The present study examined this hypothesis by testing whether frontal EEG activity during mood inductions versus a resting baseline predicted emotion regulation. EEG was recorded while participants (N=66, 40 females) received a fearful, sad, or neutral mood induction. Emotion regulation was measured following the mood inductions as self-reported change in negative mood and as attention interference in a task with mood-congruent emotional distracters. Greater frontal EEG activity during the mood inductions versus baseline was associated with more effective emotion regulation: less post-induction sadness and anxiety and reduced mood-congruent attention interference effects. Effects did not differ between the left and right hemispheres. Results support the hypothesis that frontal EEG activity reflects both emotional context and emotion-regulatory capabilities. Copyright © 2010 Elsevier B.V. All rights reserved.

Effects of adaptive refinement on the inverse EEG solution

NASA Astrophysics Data System (ADS)

Weinstein, David M.; Johnson, Christopher R.; Schmidt, John A.

1995-10-01

One of the fundamental problems in electroencephalography can be characterized by an inverse problem. Given a subset of electrostatic potentials measured on the surface of the scalp and the geometry and conductivity properties within the head, calculate the current vectors and potential fields within the cerebrum. Mathematically the generalized EEG problem can be stated as solving Poisson's equation of electrical conduction for the primary current sources. The resulting problem is mathematically ill-posed i.e., the solution does not depend continuously on the data, such that small errors in the measurement of the voltages on the scalp can yield unbounded errors in the solution, and, for the general treatment of a solution of Poisson's equation, the solution is non-unique. However, if accurate solutions the general treatment of a solution of Poisson's equation, the solution is non-unique. However, if accurate solutions to such problems could be obtained, neurologists would gain noninvasive accesss to patient-specific cortical activity. Access to such data would ultimately increase the number of patients who could be effectively treated for pathological cortical conditions such as temporal lobe epilepsy. In this paper, we present the effects of spatial adaptive refinement on the inverse EEG problem and show that the use of adaptive methods allow for significantly better estimates of electric and potential fileds within the brain through an inverse procedure. To test these methods, we have constructed several finite element head models from magneteic resonance images of a patient. The finite element meshes ranged in size from 2724 nodes and 12,812 elements to 5224 nodes and 29,135 tetrahedral elements, depending on the level of discretization. We show that an adaptive meshing algorithm minimizes the error in the forward problem due to spatial discretization and thus increases the accuracy of the inverse solution.

A wearable neuro-feedback system with EEG-based mental status monitoring and transcranial electrical stimulation.

PubMed

Roh, Taehwan; Song, Kiseok; Cho, Hyunwoo; Shin, Dongjoo; Yoo, Hoi-Jun

2014-12-01

A wearable neuro-feedback system is proposed with a low-power neuro-feedback SoC (NFS), which supports mental status monitoring with encephalography (EEG) and transcranial electrical stimulation (tES) for neuro-modulation. Self-configured independent component analysis (ICA) is implemented to accelerate source separation at low power. Moreover, an embedded support vector machine (SVM) enables online source classification, configuring the ICA accelerator adaptively depending on the types of the decomposed components. Owing to the hardwired accelerating functions, the NFS dissipates only 4.45 mW to yield 16 independent components. For non-invasive neuro-modulation, tES stimulation up to 2 mA is implemented on the SoC. The NFS is fabricated in 130-nm CMOS technology.

Emission of mitochondrial biophotons and their effect on electrical activity of membrane via microtubules.

PubMed

Rahnama, Majid; Tuszynski, Jack A; Bókkon, István; Cifra, Michal; Sardar, Peyman; Salari, Vahid

2011-03-01

In this paper we argue that, in addition to electrical and chemical signals propagating in the neurons of the brain, signal propagation takes place in the form of biophoton production. This statement is supported by recent experimental confirmation of photon guiding properties of a single neuron. We have investigated the interaction of mitochondrial biophotons with microtubules from a quantum mechanical point of view. Our theoretical analysis indicates that the interaction of biophotons and microtubules causes transitions/fluctuations of microtubules between coherent and incoherent states. A significant relationship between the fluctuation function of microtubules and alpha-EEG diagrams is elaborated on in this paper. We argue that the role of biophotons in the brain merits special attention. © Imperial College Press

Brain-computer interface for alertness estimation and improving

NASA Astrophysics Data System (ADS)

Hramov, Alexander; Maksimenko, Vladimir; Hramova, Marina

2018-02-01

Using wavelet analysis of the signals of electrical brain activity (EEG), we study the processes of neural activity, associated with perception of visual stimuli. We demonstrate that the brain can process visual stimuli in two scenarios: (i) perception is characterized by destruction of the alpha-waves and increase in the high-frequency (beta) activity, (ii) the beta-rhythm is not well pronounced, while the alpha-wave energy remains unchanged. The special experiments show that the motivation factor initiates the first scenario, explained by the increasing alertness. Based on the obtained results we build the brain-computer interface and demonstrate how the degree of the alertness can be estimated and controlled in real experiment.

Recording human cortical population spikes non-invasively--An EEG tutorial.

PubMed

Waterstraat, Gunnar; Fedele, Tommaso; Burghoff, Martin; Scheer, Hans-Jürgen; Curio, Gabriel

2015-07-30

Non-invasively recorded somatosensory high-frequency oscillations (sHFOs) evoked by electric nerve stimulation are markers of human cortical population spikes. Previously, their analysis was based on massive averaging of EEG responses. Advanced neurotechnology and optimized off-line analysis can enhance the signal-to-noise ratio of sHFOs, eventually enabling single-trial analysis. The rationale for developing dedicated low-noise EEG technology for sHFOs is unfolded. Detailed recording procedures and tailored analysis principles are explained step-by-step. Source codes in Matlab and Python are provided as supplementary material online. Combining synergistic hardware and analysis improvements, evoked sHFOs at around 600 Hz ('σ-bursts') can be studied in single-trials. Additionally, optimized spatial filters increase the signal-to-noise ratio of components at about 1 kHz ('κ-bursts') enabling their detection in non-invasive surface EEG. sHFOs offer a unique possibility to record evoked human cortical population spikes non-invasively. The experimental approaches and algorithms presented here enable also non-specialized EEG laboratories to combine measurements of conventional low-frequency EEG with the analysis of concomitant cortical population spike responses. Copyright © 2014 Elsevier B.V. All rights reserved.

Effects of oral amines on the EEG.

PubMed Central

Scott, D F; Moffett, A M; Swash, M

1977-01-01

Oral tyramine activated pre-existing episodic EEG abnormalities--namely, sharp waves, spike and wave, and localised theta activity--in epileptic patients. Little change was found in the EEGs of migrainous subjects after chocolate or beta-phenylethylamine. The implications of the findings with tyramine are discussed. Images PMID:864482

Correlation between amygdala BOLD activity and frontal EEG asymmetry during real-time fMRI neurofeedback training in patients with depression

PubMed Central

Zotev, Vadim; Yuan, Han; Misaki, Masaya; Phillips, Raquel; Young, Kymberly D.; Feldner, Matthew T.; Bodurka, Jerzy

2016-01-01

Real-time fMRI neurofeedback (rtfMRI-nf) is an emerging approach for studies and novel treatments of major depressive disorder (MDD). EEG performed simultaneously with an rtfMRI-nf procedure allows an independent evaluation of rtfMRI-nf brain modulation effects. Frontal EEG asymmetry in the alpha band is a widely used measure of emotion and motivation that shows profound changes in depression. However, it has never been directly related to simultaneously acquired fMRI data. We report the first study investigating electrophysiological correlates of the rtfMRI-nf procedure, by combining the rtfMRI-nf with simultaneous and passive EEG recordings. In this pilot study, MDD patients in the experimental group (n = 13) learned to upregulate BOLD activity of the left amygdala using an rtfMRI-nf during a happy emotion induction task. MDD patients in the control group (n = 11) were provided with a sham rtfMRI-nf. Correlations between frontal EEG asymmetry in the upper alpha band and BOLD activity across the brain were examined. Average individual changes in frontal EEG asymmetry during the rtfMRI-nf task for the experimental group showed a significant positive correlation with the MDD patients' depression severity ratings, consistent with an inverse correlation between the depression severity and frontal EEG asymmetry at rest. The average asymmetry changes also significantly correlated with the amygdala BOLD laterality. Temporal correlations between frontal EEG asymmetry and BOLD activity were significantly enhanced, during the rtfMRI-nf task, for the amygdala and many regions associated with emotion regulation. Our findings demonstrate an important link between amygdala BOLD activity and frontal EEG asymmetry during emotion regulation. Our EEG asymmetry results indicate that the rtfMRI-nf training targeting the amygdala is beneficial to MDD patients. They further suggest that EEG-nf based on frontal EEG asymmetry in the alpha band would be compatible with the amygdala-based rtfMRI-nf. Combination of the two could enhance emotion regulation training and benefit MDD patients. PMID:26958462

[Changes in cortical power distribution produced by memory consolidation as a function of a typewriting skill].

PubMed

Cunha, Marlo; Bastos, Victor Hugo; Veiga, Heloisa; Cagy, Maurício; McDowell, Kaleb; Furtado, Vernon; Piedade, Roberto; Ribeiro, Pedro

2004-09-01

The present study aimed to investigate alterations in EEG patterns in normal, right-handed individuals, during the process of learning a specific motor skill (typewriting). Recent studies have shown that the cerebral cortex is susceptible to several changes during a learning process and that alterations in the brain's electrical patterns take place as a result of the acquisition of a motor skill and memory consolidation. In this context, subjects' brain electrical activity was analyzed before and after the motor task. EEG data were collected by a Braintech 3000 and analyzed by Neurometrics. For the statistical analysis, the behavioral variables "time" and "number of errors" were assessed by a one-way ANOVA. For the neurophysiological variable "Absolute Power", a paired t-Test was performed for each pair of electrodes CZ-C3/CZ-C4, in the theta and alpha frequency bands. The main results demonstrated a change in performance, through both behavioral variables ("time" and "number of errors"). At the same time, no changes were observed for the neurophysiological variable ("Absolute Power") in the theta band. On the other hand, a significant increase was observed in the alpha band in central areas (CZ-C3/CZ-C4). These results suggest an adaptation of the sensory-motor cortex, as a consequence of the typewriting training.

Multimodal EEG Recordings, Psychometrics and Behavioural Analysis.

PubMed

Boeijinga, Peter H

2015-01-01

High spatial and temporal resolution measurements of neuronal activity are preferably combined. In an overview on how this approach can take shape, multimodal electroencephalography (EEG) is treated in 2 main parts: by experiments without a task and in the experimentally cued working brain. It concentrates first on the alpha rhythm properties and next on data-driven search for patterns such as the default mode network. The high-resolution volumic distributions of neuronal metabolic indices result in distributed cortical regions and possibly relate to numerous nuclei, observable in a non-invasive manner in the central nervous system of humans. The second part deals with paradigms in which nowadays assessment of target-related networks can align level-dependent blood oxygenation, electrical responses and behaviour, taking the temporal resolution advantages of event-related potentials. Evidence-based electrical propagation in serial tasks during performance is now to a large extent attributed to interconnected pathways, particularly chronometry-dependent ones, throughout a chain including a dorsal stream, next ventral cortical areas taking the flow of information towards inferior temporal domains. The influence of aging is documented, and results of the first multimodal studies in neuropharmacology are consistent. Finally a scope on implementation of advanced clinical applications and personalized marker strategies in neuropsychiatry is indicated. © 2016 S. Karger AG, Basel.

Pharmacokinetic and pharmacodynamic effects of clonazepam in children with epilepsy treated with valproate: a preliminary study.

PubMed

Wang, Li; Wang, Xiao-Dong

2002-08-01

The authors report the use of the quantitative pharmaco-EEG (QPEEG) technique to study the pharmacokinetics (PK) and pharmacodynamics (PD) of clonazepam (CZP) in four epileptic children who suffered uncontrolled seizures despite long-term valproate (VPA) therapy. After a single dose of CZP (0.05 mg/kg, PO), blood samples were collected at 0, 0.5, 1.0, 1.5, 2.0, 3.0, 4.0, 8.0, 12.0, and 24.0 hours. CZP and VPA concentrations were measured by HPLC or GC assay, respectively. At each blood collection time point, EEG signals (60 s) were recorded for brain electrical activity mapping, and the power percentage average (PPA) of each frequency band was calculated. The relationship between drug concentrations and their corresponding PPA of each frequency band was analyzed. VPA steady-state drug concentrations (Css) were within the therapeutic range and not affected by CZP. The peak concentration (Cmax) of CZP and the time intervals from dosing to Cmax (Tmax) were 20.9 ng/mL to 113.8 ng/mL and 1 hour to 1.5 hours, respectively. There was no significant correlation between VPA concentrations and the PPA of any of the EEG frequency bands. CZP blood concentrations showed significant correlation with PPA in 3 of the 4 patients. Our results suggested CZP could affect fast wave activities in proportion to CZP blood concentrations. We propose that QPEEG is a promising technique to study the PK and PD of selected anti-epileptic drugs.

The inverse electroencephalography pipeline

NASA Astrophysics Data System (ADS)

Weinstein, David Michael

The inverse electroencephalography (EEG) problem is defined as determining which regions of the brain are active based on remote measurements recorded with scalp EEG electrodes. An accurate solution to this problem would benefit both fundamental neuroscience research and clinical neuroscience applications. However, constructing accurate patient-specific inverse EEG solutions requires complex modeling, simulation, and visualization algorithms, and to date only a few systems have been developed that provide such capabilities. In this dissertation, a computational system for generating and investigating patient-specific inverse EEG solutions is introduced, and the requirements for each stage of this Inverse EEG Pipeline are defined and discussed. While the requirements of many of the stages are satisfied with existing algorithms, others have motivated research into novel modeling and simulation methods. The principal technical results of this work include novel surface-based volume modeling techniques, an efficient construction for the EEG lead field, and the Open Source release of the Inverse EEG Pipeline software for use by the bioelectric field research community. In this work, the Inverse EEG Pipeline is applied to three research problems in neurology: comparing focal and distributed source imaging algorithms; separating measurements into independent activation components for multifocal epilepsy; and localizing the cortical activity that produces the P300 effect in schizophrenia.

Stimulus-dependent spiking relationships with the EEG

PubMed Central

Snyder, Adam C.

2015-01-01

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

EEG Subspace Analysis and Classification Using Principal Angles for Brain-Computer Interfaces

NASA Astrophysics Data System (ADS)

Ashari, Rehab Bahaaddin

Brain-Computer Interfaces (BCIs) help paralyzed people who have lost some or all of their ability to communicate and control the outside environment from loss of voluntary muscle control. Most BCIs are based on the classification of multichannel electroencephalography (EEG) signals recorded from users as they respond to external stimuli or perform various mental activities. The classification process is fraught with difficulties caused by electrical noise, signal artifacts, and nonstationarity. One approach to reducing the effects of similar difficulties in other domains is the use of principal angles between subspaces, which has been applied mostly to video sequences. This dissertation studies and examines different ideas using principal angles and subspaces concepts. It introduces a novel mathematical approach for comparing sets of EEG signals for use in new BCI technology. The success of the presented results show that principal angles are also a useful approach to the classification of EEG signals that are recorded during a BCI typing application. In this application, the appearance of a subject's desired letter is detected by identifying a P300-wave within a one-second window of EEG following the flash of a letter. Smoothing the signals before using them is the only preprocessing step that was implemented in this study. The smoothing process based on minimizing the second derivative in time is implemented to increase the classification accuracy instead of using the bandpass filter that relies on assumptions on the frequency content of EEG. This study examines four different ways of removing outliers that are based on the principal angles and shows that the outlier removal methods did not help in the presented situations. One of the concepts that this dissertation focused on is the effect of the number of trials on the classification accuracies. The achievement of the good classification results by using a small number of trials starting from two trials only, should make this approach more appropriate for online BCI applications. In order to understand and test how EEG signals are different from one subject to another, different users are tested in this dissertation, some with motor impairments. Furthermore, the concept of transferring information between subjects is examined by training the approach on one subject and testing it on the other subject using the training subject's EEG subspaces to classify the testing subject's trials.

Frequency domain beamforming of magnetoencephalographic beta band activity in epilepsy patients with focal cortical dysplasia.

PubMed

Heers, Marcel; Hirschmann, Jan; Jacobs, Julia; Dümpelmann, Matthias; Butz, Markus; von Lehe, Marec; Elger, Christian E; Schnitzler, Alfons; Wellmer, Jörg

2014-09-01

Spike-based magnetoencephalography (MEG) source localization is an established method in the presurgical evaluation of epilepsy patients. Focal cortical dysplasias (FCDs) are associated with focal epileptic discharges of variable morphologies in the beta frequency band in addition to single epileptic spikes. Therefore, we investigated the potential diagnostic value of MEG-based localization of spike-independent beta band (12-30Hz) activity generated by epileptogenic lesions. Five patients with FCD IIB underwent MEG. In one patient, invasive EEG (iEEG) was recorded simultaneously with MEG. In two patients, iEEG succeeded MEG, and two patients had MEG only. MEG and iEEG were evaluated for epileptic spikes. Two minutes of iEEG data and MEG epochs with no spikes as well as MEG epochs with epileptic spikes were analyzed in the frequency domain. MEG oscillatory beta band activity was localized using Dynamic Imaging of Coherent Sources. Intralesional beta band activity was coherent between simultaneous MEG and iEEG recordings. Continuous 14Hz beta band power correlated with the rate of interictal epileptic discharges detected in iEEG. In cases where visual MEG evaluation revealed epileptic spikes, the sources of beta band activity localized within <2cm of the epileptogenic lesion as shown on magnetic resonance imaging. This result held even when visually marked epileptic spikes were deselected. When epileptic spikes were detectable in iEEG but not MEG, MEG beta band activity source localization failed. Source localization of beta band activity has the potential to contribute to the identification of epileptic foci in addition to source localization of visually marked epileptic spikes. Thus, this technique may assist in the localization of epileptic foci in patients with suspected FCD. Copyright © 2014 Elsevier B.V. All rights reserved.

Vector tomography for reconstructing electric fields with non-zero divergence in bounded domains

NASA Astrophysics Data System (ADS)

Koulouri, Alexandra; Brookes, Mike; Rimpiläinen, Ville

2017-01-01

In vector tomography (VT), the aim is to reconstruct an unknown multi-dimensional vector field using line integral data. In the case of a 2-dimensional VT, two types of line integral data are usually required. These data correspond to integration of the parallel and perpendicular projection of the vector field along the integration lines and are called the longitudinal and transverse measurements, respectively. In most cases, however, the transverse measurements cannot be physically acquired. Therefore, the VT methods are typically used to reconstruct divergence-free (or source-free) velocity and flow fields that can be reconstructed solely from the longitudinal measurements. In this paper, we show how vector fields with non-zero divergence in a bounded domain can also be reconstructed from the longitudinal measurements without the need of explicitly evaluating the transverse measurements. To the best of our knowledge, VT has not previously been used for this purpose. In particular, we study low-frequency, time-harmonic electric fields generated by dipole sources in convex bounded domains which arise, for example, in electroencephalography (EEG) source imaging. We explain in detail the theoretical background, the derivation of the electric field inverse problem and the numerical approximation of the line integrals. We show that fields with non-zero divergence can be reconstructed from the longitudinal measurements with the help of two sparsity constraints that are constructed from the transverse measurements and the vector Laplace operator. As a comparison to EEG source imaging, we note that VT does not require mathematical modeling of the sources. By numerical simulations, we show that the pattern of the electric field can be correctly estimated using VT and the location of the source activity can be determined accurately from the reconstructed magnitudes of the field.

The role of resting-state EEG localized activation and central nervous system arousal in executive function performance in children with Attention-Deficit/Hyperactivity Disorder.

PubMed

Zhang, Da-Wei; Johnstone, Stuart J; Roodenrys, Steven; Luo, Xiangsheng; Li, Hui; Wang, Encong; Zhao, Qihua; Song, Yan; Liu, Lu; Qian, Qiujin; Wang, Yufeng; Sun, Li

2018-06-01

This study explored the relationships between resting-state electroencephalogram (RS-EEG) localized activation and two important types of executive functions (EF) to extend the prognostic utilization of RS-EEG in children with Attention-Deficit/Hyperactivity Disorder (AD/HD). Also, the role of central nervous system (CNS) arousal in the relationships was examined. Fifty-eight children with AD/HD participated in the study. RS-EEG localized activation was derived from spectral power differences between EEG in eyes-closed and eyes-open conditions. CNS arousal was measured based on alpha band power. Common and everyday EF scores were obtained as EF outcomes. Frontal delta activation predicted common EF ability and posterior alpha activation predicted everyday EF. A serial mediation analysis found that lower CNS baseline arousal was related to greater arousal and delta activation in series, which in turn related to worse common EF. A follow-up study found that baseline arousal was related to larger interference cost. RS-EEG is indicative of individual differences in two important types of EF in children with AD/HD. Lower CNS arousal may be a driving force for the poorer common EF performance. The current study supports prognostic utilization of RS-EEG and AD/HD models that take resting brain activity into consideration in children with AD/HD. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Continuous EEG source imaging enhances analysis of EEG-fMRI in focal epilepsy.

PubMed

Vulliemoz, S; Rodionov, R; Carmichael, D W; Thornton, R; Guye, M; Lhatoo, S D; Michel, C M; Duncan, J S; Lemieux, L

2010-02-15

EEG-correlated fMRI (EEG-fMRI) studies can reveal haemodynamic changes associated with Interictal Epileptic Discharges (IED). Methodological improvements are needed to increase sensitivity and specificity for localising the epileptogenic zone. We investigated whether the estimated EEG source activity improved models of the BOLD changes in EEG-fMRI data, compared to conventional < event-related > designs based solely on the visual identification of IED. Ten patients with pharmaco-resistant focal epilepsy underwent EEG-fMRI. EEG Source Imaging (ESI) was performed on intra-fMRI averaged IED to identify the irritative zone. The continuous activity of this estimated IED source (cESI) over the entire recording was used for fMRI analysis (cESI model). The maps of BOLD signal changes explained by cESI were compared to results of the conventional IED-related model. ESI was concordant with non-invasive data in 13/15 different types of IED. The cESI model explained significant additional BOLD variance in regions concordant with video-EEG, structural MRI or, when available, intracranial EEG in 10/15 IED. The cESI model allowed better detection of the BOLD cluster, concordant with intracranial EEG in 4/7 IED, compared to the IED model. In 4 IED types, cESI-related BOLD signal changes were diffuse with a pattern suggestive of contamination of the source signal by artefacts, notably incompletely corrected motion and pulse artefact. In one IED type, there was no significant BOLD change with either model. Continuous EEG source imaging can improve the modelling of BOLD changes related to interictal epileptic activity and this may enhance the localisation of the irritative zone. Copyright 2009 Elsevier Inc. All rights reserved.

Preterm EEG: a multimodal neurophysiological protocol.

PubMed

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.

EEG and MEG: sensitivity to epileptic spike activity as function of source orientation and depth.

PubMed

Hunold, A; Funke, M E; Eichardt, R; Stenroos, M; Haueisen, J

2016-07-01

Simultaneous electroencephalography (EEG) and magnetoencephalography (MEG) recordings of neuronal activity from epileptic patients reveal situations in which either EEG or MEG or both modalities show visible interictal spikes. While different signal-to-noise ratios (SNRs) of the spikes in EEG and MEG have been reported, a quantitative relation of spike source orientation and depth as well as the background brain activity to the SNR has not been established. We investigated this quantitative relationship for both dipole and patch sources in an anatomically realistic cortex model. Altogether, 5600 dipole and 3300 patch sources were distributed on the segmented cortical surfaces of two volunteers. The sources were classified according to their quantified depths and orientations, ranging from 20 mm to 60 mm below the skin surface and radial and tangential, respectively. The source time-courses mimicked an interictal spike, and the simulated background activity emulated resting activity. Simulations were conducted with individual three-compartment boundary element models. The SNR was evaluated for 128 EEG, 102 MEG magnetometer, and 204 MEG gradiometer channels. For superficial dipole and superficial patch sources, EEG showed higher SNRs for dominantly radial orientations, and MEG showed higher values for dominantly tangential orientations. Gradiometers provided higher SNR than magnetometers for superficial sources, particularly for those with dominantly tangential orientations. The orientation dependent difference in SNR in EEG and MEG gradually changed as the sources were located deeper, where the interictal spikes generated higher SNRs in EEG compared to those in MEG for all source orientations. With deep sources, the SNRs in gradiometers and magnetometers were of the same order. To better detect spikes, both EEG and MEG should be used.

Topographical characteristics and principal component structure of the hypnagogic EEG.

PubMed

Tanaka, H; Hayashi, M; Hori, T

1997-07-01

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

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

PubMed

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

2014-08-01

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

Electroencephalogram associations to cognitive performance in clinically active nurses.

PubMed

Lees, Ty; Khushaba, Rami; Lal, Sara

2016-07-01

Cognitive impairment is traditionally identified via cognitive screening tools that have limited ability in detecting early or transitional stages of impairment. The dynamic nature of physiological variables such as the electroencephalogram (EEG) may provide alternate means for detecting these transitions. However, previous research examining EEG and cognitive performance is largely confined to samples with diagnosed cognitive impairments, and research examining non-impaired, and occupation specific samples, is limited. The present study aimed to investigate the associations between frontal pole and central EEG and cognitive performance in a sample of male and female nurses, and to determine the significance of these associations. Fifty seven nurses participated in the study, in which two lead bipolar EEG was recorded at positions Fp1 (frontal polar), Fp2, C3 (central) and C4 during a baseline and an active phase involving the common neuropsychological Stroop test. Participants' cognitive performance was assessed using the mini-mental state exam (MMSE) and Cognistat screening tools. Significant correlations between EEG beta activity and the outcome of MMSE and Cognistat were revealed, where an increased beta activity was associated to an increased global cognitive performance. Additionally, domain specific cognitive performance was also significantly associated to various EEG variables. The study identified potential EEG biomarkers for global and domain specific cognitive performance, and provides initial groundwork for the development of future EEG based biomarkers for detection of cognitive pathologies.

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

PubMed Central

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

2016-01-01

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

Multimodal effective connectivity analysis reveals seizure focus and propagation in musicogenic epilepsy.

PubMed

Klamer, Silke; Rona, Sabine; Elshahabi, Adham; Lerche, Holger; Braun, Christoph; Honegger, Jürgen; Erb, Michael; Focke, Niels K

2015-06-01

Dynamic causal modeling (DCM) is a method to non-invasively assess effective connectivity between brain regions. 'Musicogenic epilepsy' is a rare reflex epilepsy syndrome in which seizures can be elicited by musical stimuli and thus represents a unique possibility to investigate complex human brain networks and test connectivity analysis tools. We investigated effective connectivity in a case of musicogenic epilepsy using DCM for fMRI, high-density (hd-) EEG and MEG and validated results with intracranial EEG recordings. A patient with musicogenic seizures was examined using hd-EEG/fMRI and simultaneous '256-channel hd-EEG'/'whole head MEG' to characterize the epileptogenic focus and propagation effects using source analysis techniques and DCM. Results were validated with invasive EEG recordings. We recorded one seizure with hd-EEG/fMRI and four auras with hd-EEG/MEG. During the seizures, increases of activity could be observed in the right mesial temporal region as well as bilateral mesial frontal regions. Effective connectivity analysis of fMRI and hd-EEG/MEG indicated that right mesial temporal neuronal activity drives changes in the frontal areas consistently in all three modalities, which was confirmed by the results of invasive EEG recordings. Seizures thus seem to originate in the right mesial temporal lobe and propagate to mesial frontal regions. Using DCM for fMRI, hd-EEG and MEG we were able to correctly localize focus and propagation of epileptic activity and thereby characterize the underlying epileptic network in a patient with musicogenic epilepsy. The concordance between all three functional modalities validated by invasive monitoring is noteworthy, both for epileptic activity spread as well as for effective connectivity analysis in general. Copyright © 2015 Elsevier Inc. All rights reserved.

Electrophysiological correlates of the BOLD signal for EEG-informed fMRI

PubMed Central

Murta, Teresa; Leite, Marco; Carmichael, David W; Figueiredo, Patrícia; Lemieux, Louis

2015-01-01

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are important tools in cognitive and clinical neuroscience. Combined EEG–fMRI has been shown to help to characterise brain networks involved in epileptic activity, as well as in different sensory, motor and cognitive functions. A good understanding of the electrophysiological correlates of the blood oxygen level-dependent (BOLD) signal is necessary to interpret fMRI maps, particularly when obtained in combination with EEG. We review the current understanding of electrophysiological–haemodynamic correlates, during different types of brain activity. We start by describing the basic mechanisms underlying EEG and BOLD signals and proceed by reviewing EEG-informed fMRI studies using fMRI to map specific EEG phenomena over the entire brain (EEG–fMRI mapping), or exploring a range of EEG-derived quantities to determine which best explain colocalised BOLD fluctuations (local EEG–fMRI coupling). While reviewing studies of different forms of brain activity (epileptic and nonepileptic spontaneous activity; cognitive, sensory and motor functions), a significant attention is given to epilepsy because the investigation of its haemodynamic correlates is the most common application of EEG-informed fMRI. Our review is focused on EEG-informed fMRI, an asymmetric approach of data integration. We give special attention to the invasiveness of electrophysiological measurements and the simultaneity of multimodal acquisitions because these methodological aspects determine the nature of the conclusions that can be drawn from EEG-informed fMRI studies. We emphasise the advantages of, and need for, simultaneous intracranial EEG–fMRI studies in humans, which recently became available and hold great potential to improve our understanding of the electrophysiological correlates of BOLD fluctuations. PMID:25277370

Suitable Adaptation Mechanisms for Intelligent Tutoring Technologies

DTIC Science & Technology

2010-12-01

the Acoustic Society of America, 93(2), pp. 1097-1108. Neurofeedback equipment - Wireless Brainquiry PET EEG and ActivEEG. (n.d.). Retrieved from...27 5.2 Electroencephalogram ( EEG ...electroencephalogram ( EEG ), heart rate variability (HRV- a measure involving the electrocardiogram [ECG]), and galvanic skin response (GSR) either

Automatic interpretation and writing report of the adult waking electroencephalogram.

PubMed

Shibasaki, Hiroshi; Nakamura, Masatoshi; Sugi, Takenao; Nishida, Shigeto; Nagamine, Takashi; Ikeda, Akio

2014-06-01

Automatic interpretation of the EEG has so far been faced with significant difficulties because of a large amount of spatial as well as temporal information contained in the EEG, continuous fluctuation of the background activity depending on changes in the subject's vigilance and attention level, the occurrence of paroxysmal activities such as spikes and spike-and-slow-waves, contamination of the EEG with a variety of artefacts and the use of different recording electrodes and montages. Therefore, previous attempts of automatic EEG interpretation have been focussed only on a specific EEG feature such as paroxysmal abnormalities, delta waves, sleep stages and artefact detection. As a result of a long-standing cooperation between clinical neurophysiologists and system engineers, we report for the first time on a comprehensive, computer-assisted, automatic interpretation of the adult waking EEG. This system analyses the background activity, intermittent abnormalities, artefacts and the level of vigilance and attention of the subject, and automatically presents its report in written form. Besides, it also detects paroxysmal abnormalities and evaluates the effects of intermittent photic stimulation and hyperventilation on the EEG. This system of automatic EEG interpretation was formed by adopting the strategy that the qualified EEGers employ for the systematic visual inspection. This system can be used as a supplementary tool for the EEGer's visual inspection, and for educating EEG trainees and EEG technicians. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

``Seeing'' electroencephalogram through the skull: imaging prefrontal cortex with fast optical signal

NASA Astrophysics Data System (ADS)

Medvedev, Andrei V.; Kainerstorfer, Jana M.; Borisov, Sergey V.; Gandjbakhche, Amir H.; Vanmeter, John

2010-11-01

Near-infrared spectroscopy is a novel imaging technique potentially sensitive to both brain hemodynamics (slow signal) and neuronal activity (fast optical signal, FOS). The big challenge of measuring FOS noninvasively lies in the presumably low signal-to-noise ratio. Thus, detectability of the FOS has been controversially discussed. We present reliable detection of FOS from 11 individuals concurrently with electroencephalogram (EEG) during a Go-NoGo task. Probes were placed bilaterally over prefrontal cortex. Independent component analysis (ICA) was used for artifact removal. Correlation coefficient in the best correlated FOS-EEG ICA pairs was highly significant (p < 10-8), and event-related optical signal (EROS) was found in all subjects. Several EROS components were similar to the event-related potential (ERP) components. The most robust ``optical N200'' at t = 225 ms coincided with the N200 ERP; both signals showed significant difference between targets and nontargets, and their timing correlated with subject's reaction time. Correlation between FOS and EEG even in single trials provides further evidence that at least some FOS components ``reflect'' electrical brain processes directly. The data provide evidence for the early involvement of prefrontal cortex in rapid object recognition. EROS is highly localized and can provide cost-effective imaging tools for cortical mapping of cognitive processes.

Equivalent charge source model based iterative maximum neighbor weight for sparse EEG source localization.

PubMed

Xu, Peng; Tian, Yin; Lei, Xu; Hu, Xiao; Yao, Dezhong

2008-12-01

How to localize the neural electric activities within brain effectively and precisely from the scalp electroencephalogram (EEG) recordings is a critical issue for current study in clinical neurology and cognitive neuroscience. In this paper, based on the charge source model and the iterative re-weighted strategy, proposed is a new maximum neighbor weight based iterative sparse source imaging method, termed as CMOSS (Charge source model based Maximum neighbOr weight Sparse Solution). Different from the weight used in focal underdetermined system solver (FOCUSS) where the weight for each point in the discrete solution space is independently updated in iterations, the new designed weight for each point in each iteration is determined by the source solution of the last iteration at both the point and its neighbors. Using such a new weight, the next iteration may have a bigger chance to rectify the local source location bias existed in the previous iteration solution. The simulation studies with comparison to FOCUSS and LORETA for various source configurations were conducted on a realistic 3-shell head model, and the results confirmed the validation of CMOSS for sparse EEG source localization. Finally, CMOSS was applied to localize sources elicited in a visual stimuli experiment, and the result was consistent with those source areas involved in visual processing reported in previous studies.

“Seeing” electroencephalogram through the skull: imaging prefrontal cortex with fast optical signal

PubMed Central

Medvedev, Andrei V.; Kainerstorfer, Jana M.; Borisov, Sergey V.; Gandjbakhche, Amir H.; VanMeter, John

2010-01-01

Near-infrared spectroscopy is a novel imaging technique potentially sensitive to both brain hemodynamics (slow signal) and neuronal activity (fast optical signal, FOS). The big challenge of measuring FOS noninvasively lies in the presumably low signal-to-noise ratio. Thus, detectability of the FOS has been controversially discussed. We present reliable detection of FOS from 11 individuals concurrently with electroencephalogram (EEG) during a Go-NoGo task. Probes were placed bilaterally over prefrontal cortex. Independent component analysis (ICA) was used for artifact removal. Correlation coefficient in the best correlated FOS–EEG ICA pairs was highly significant (p < 10−8), and event-related optical signal (EROS) was found in all subjects. Several EROS components were similar to the event-related potential (ERP) components. The most robust “optical N200” at t = 225 ms coincided with the N200 ERP; both signals showed significant difference between targets and nontargets, and their timing correlated with subject’s reaction time. Correlation between FOS and EEG even in single trials provides further evidence that at least some FOS components “reflect” electrical brain processes directly. The data provide evidence for the early involvement of prefrontal cortex in rapid object recognition. EROS is highly localized and can provide cost-effective imaging tools for cortical mapping of cognitive processes. PMID:21198150

Characteristics analysis of acupuncture electroencephalograph based on mutual information Lempel—Ziv complexity

NASA Astrophysics Data System (ADS)

Luo, Xi-Liu; Wang, Jiang; Han, Chun-Xiao; Deng, Bin; Wei, Xi-Le; Bian, Hong-Rui

2012-02-01

As a convenient approach to the characterization of cerebral cortex electrical information, electroencephalograph (EEG) has potential clinical application in monitoring the acupuncture effects. In this paper, a method composed of the mutual information method and Lempel—Ziv complexity method (MILZC) is proposed to investigate the effects of acupuncture on the complexity of information exchanges between different brain regions based on EEGs. In the experiments, eight subjects are manually acupunctured at ‘Zusanli’ acupuncture point (ST-36) with different frequencies (i.e., 50, 100, 150, and 200 times/min) and the EEGs are recorded simultaneously. First, MILZC values are compared in general. Then average brain connections are used to quantify the effectiveness of acupuncture under the above four frequencies. Finally, significance index P values are used to study the spatiality of the acupuncture effect on the brain. Three main findings are obtained: (i) MILZC values increase during the acupuncture; (ii) manual acupunctures (MAs) with 100 times/min and 150 times/min are more effective than with 50 times/min and 200 times/min; (iii) contralateral hemisphere activation is more prominent than ipsilateral hemisphere's. All these findings suggest that acupuncture contributes to the increase of brain information exchange complexity and the MILZC method can successfully describe these changes.

Audio-Visual and Autogenic Relaxation Alter Amplitude of Alpha EEG Band, Causing Improvements in Mental Work Performance in Athletes.

PubMed

Mikicin, Mirosław; Kowalczyk, Marek

2015-09-01

The aim of the present study was to investigate the effect of regular audio-visual relaxation combined with Schultz's autogenic training on: (1) the results of behavioral tests that evaluate work performance during burdensome cognitive tasks (Kraepelin test), (2) changes in classical EEG alpha frequency band, neocortex (frontal, temporal, occipital, parietal), hemisphere (left, right) versus condition (only relaxation 7-12 Hz). Both experimental (EG) and age-and skill-matched control group (CG) consisted of eighteen athletes (ten males and eight females). After 7-month training EG demonstrated changes in the amplitude of mean electrical activity of the EEG alpha bend at rest and an improvement was significantly changing and an improvement in almost all components of Kraepelin test. The same examined variables in CG were unchanged following the period without the intervention. Summing up, combining audio-visual relaxation with autogenic training significantly improves athlete's ability to perform a prolonged mental effort. These changes are accompanied by greater amplitude of waves in alpha band in the state of relax. The results suggest usefulness of relaxation techniques during performance of mentally difficult sports tasks (sports based on speed and stamina, sports games, combat sports) and during relax of athletes.

Multivariate pattern analysis of MEG and EEG: A comparison of representational structure in time and space.

PubMed

Cichy, Radoslaw Martin; Pantazis, Dimitrios

2017-09-01

Multivariate pattern analysis of magnetoencephalography (MEG) and electroencephalography (EEG) data can reveal the rapid neural dynamics underlying cognition. However, MEG and EEG have systematic differences in sampling neural activity. This poses the question to which degree such measurement differences consistently bias the results of multivariate analysis applied to MEG and EEG activation patterns. To investigate, we conducted a concurrent MEG/EEG study while participants viewed images of everyday objects. We applied multivariate classification analyses to MEG and EEG data, and compared the resulting time courses to each other, and to fMRI data for an independent evaluation in space. We found that both MEG and EEG revealed the millisecond spatio-temporal dynamics of visual processing with largely equivalent results. Beyond yielding convergent results, we found that MEG and EEG also captured partly unique aspects of visual representations. Those unique components emerged earlier in time for MEG than for EEG. Identifying the sources of those unique components with fMRI, we found the locus for both MEG and EEG in high-level visual cortex, and in addition for MEG in low-level visual cortex. Together, our results show that multivariate analyses of MEG and EEG data offer a convergent and complimentary view on neural processing, and motivate the wider adoption of these methods in both MEG and EEG research. Copyright © 2017 Elsevier Inc. All rights reserved.

A close look at EEG in subacute sclerosing panencephalitis.

PubMed

Demir, Nurhak; Cokar, Ozlem; Bolukbasi, Feray; Demirbilek, Veysi; Yapici, Zuhal; Yalcinkaya, Cengiz; Direskeneli, Guher Saruhan; Yentur, Sibel; Onal, Emel; Yilmaz, Gulden; Dervent, Aysin

2013-08-01

To define atypical clinical and EEG features of patients with subacute sclerosing panencephalitis that may require an overview of differential diagnosis. A total of 66 EEGs belonging to 53 (17 females and 36 males) consecutive patients with serologically confirmed subacute sclerosing panencephalitis were included in this study. Patient files and EEG data were evaluated retrospectively. EEGs included in the study were sleep-waking EEGs and/or sleep-waking video-EEG records with at least 2 hours duration. Cranial MRIs of the patients taken 2 months before or after the EEG records were included. Age range at the onset of the disease was 15 to 192 months (mean age: 80.02 months). Epilepsy was diagnosed in 21 (43%) patients. Among epileptic seizures excluding myoclonic jerks, generalized tonic-clonic type constituted the majority (58%). Tonic seizures were documented during the video-EEG recordings in four patients. Epileptogenic activities were found in 56 (83%) EEG recordings. They were localized mainly in frontal (58%), posterior temporal, parietal, occipital (26%), and centrotemporal (8%) regions. Multiple foci were detected in 26 recordings (39%). Epileptiform activities in the 39 (59%) EEGs appeared as unilateral or bilateral diffuse paroxysmal discharges. Recognition of uncommon clinical and EEG findings of subacute sclerosing panencephalitis, especially in countries where subacute sclerosing panencephalitis has not been eliminated yet, could be helpful in prevention of misdiagnosis and delay in the management of improvable conditions.

EEG alpha activity and hallucinatory experience during sensory deprivation.

PubMed

Hayashi, M; Morikawa, T; Hori, T

1992-10-01

The relationship between hallucinatory experiences under sensory deprivation and EEG alpha activities was studied. Each of seven male students lived alone in an air conditioned, soundproof dark room for 72 hours. When hallucinatory experiences occurred, the students pressed a button at once. If they could not press the button during the experience, they were required to press it two times when the hallucinatory experience was finished. Spectral analysis was performed on the consecutive EEG samples from just before button-presses to 10 min. before them, and the average alpha band amplitudes were obtained for the four epochs (0-.5, .5-2, 2-5, 5-10 min.). For the single button-presses, the amplitude of alpha band increased 2 min. before the button-presses. Right-hemisphere EEG activation was observed in the occipital area for the double button-presses. The results suggest an association between the hallucinatory experiences under sensory deprivation and the amount of EEG alpha activity.

Assistance to NASA in biomedical areas of the technology utilization program

NASA Technical Reports Server (NTRS)

Culclasure, D. F.; Eckhardt, L.

1972-01-01

The applications of aerospace technology to biomedical research are reported. The medical institutions participating in the Biomedical Applications Program are listed along with the institutions currently utilizing the services of the Southwest Research Institute Biomedical Applications Team. Significant accomplishments during this period include: ultra-low bandpass amplifier for gastro-intestinal electric potentials; non-encumbering EEG electrode assembly suitable for long term sleep research; accurate cardiac telemetry system for active subjects; warning system for the deaf; tracking cane for the blind; and an improved control mechanism to expand the self-sufficiency of quadriplegics.

Experimental validation of the influence of white matter anisotropy on the intracranial EEG forward solution.

PubMed

Bangera, Nitin B; Schomer, Donald L; Dehghani, Nima; Ulbert, Istvan; Cash, Sydney; Papavasiliou, Steve; Eisenberg, Solomon R; Dale, Anders M; Halgren, Eric

2010-12-01

Forward solutions with different levels of complexity are employed for localization of current generators, which are responsible for the electric and magnetic fields measured from the human brain. The influence of brain anisotropy on the forward solution is poorly understood. The goal of this study is to validate an anisotropic model for the intracranial electric forward solution by comparing with the directly measured 'gold standard'. Dipolar sources are created at known locations in the brain and intracranial electroencephalogram (EEG) is recorded simultaneously. Isotropic models with increasing level of complexity are generated along with anisotropic models based on Diffusion tensor imaging (DTI). A Finite Element Method based forward solution is calculated and validated using the measured data. Major findings are (1) An anisotropic model with a linear scaling between the eigenvalues of the electrical conductivity tensor and water self-diffusion tensor in brain tissue is validated. The greatest improvement was obtained when the stimulation site is close to a region of high anisotropy. The model with a global anisotropic ratio of 10:1 between the eigenvalues (parallel: tangential to the fiber direction) has the worst performance of all the anisotropic models. (2) Inclusion of cerebrospinal fluid as well as brain anisotropy in the forward model is necessary for an accurate description of the electric field inside the skull. The results indicate that an anisotropic model based on the DTI can be constructed non-invasively and shows an improved performance when compared to the isotropic models for the calculation of the intracranial EEG forward solution.

Exploring differences between left and right hand motor imagery via spatio-temporal EEG microstate.

PubMed

Liu, Weifeng; Liu, Xiaoming; Dai, Ruomeng; Tang, Xiaoying

2017-12-01

EEG-based motor imagery is very useful in brain-computer interface. How to identify the imaging movement is still being researched. Electroencephalography (EEG) microstates reflect the spatial configuration of quasi-stable electrical potential topographies. Different microstates represent different brain functions. In this paper, microstate method was used to process the EEG-based motor imagery to obtain microstate. The single-trial EEG microstate sequences differences between two motor imagery tasks - imagination of left and right hand movement were investigated. The microstate parameters - duration, time coverage and occurrence per second as well as the transition probability of the microstate sequences were obtained with spatio-temporal microstate analysis. The results were shown significant differences (P < 0.05) with paired t-test between the two tasks. Then these microstate parameters were used as features and a linear support vector machine (SVM) was utilized to classify the two tasks with mean accuracy 89.17%, superior performance compared to the other methods. These indicate that the microstate can be a promising feature to improve the performance of the brain-computer interface classification.

A comparison of continuous video-EEG monitoring and 30-minute EEG in an ICU.

PubMed

Khan, Omar I; Azevedo, Christina J; Hartshorn, Alendia L; Montanye, Justin T; Gonzalez, Juan C; Natola, Mark A; Surgenor, Stephen D; Morse, Richard P; Nordgren, Richard E; Bujarski, Krzysztof A; Holmes, Gregory L; Jobst, Barbara C; Scott, Rod C; Thadani, Vijay M

2014-12-01

To determine whether there is added benefit in detecting electrographic abnormalities from 16-24 hours of continuous video-EEG in adult medical/surgical ICU patients, compared to a 30-minute EEG. This was a prospectively enroled non-randomized study of 130 consecutive ICU patients for whom EEG was requested. For 117 patients, a 30-minute EEG was requested for altered mental state and/or suspected seizures; 83 patients continued with continuous video-EEG for 16-24 hours and 34 patients had only the 30-minute EEG. For 13 patients with prior seizures, continuous video-EEG was requested and was carried out for 16-24 hours. We gathered EEG data prospectively, and reviewed the medical records retrospectively to assess the impact of continuous video-EEG. A total of 83 continuous video-EEG recordings were performed for 16-24 hours beyond 30 minutes of routine EEG. All were slow, and 34% showed epileptiform findings in the first 30 minutes, including 2% with seizures. Over 16-24 hours, 14% developed new or additional epileptiform abnormalities, including 6% with seizures. In 8%, treatment was changed based on continuous video-EEG. Among the 34 EEGs limited to 30 minutes, almost all were slow and 18% showed epileptiform activity, including 3% with seizures. Among the 13 patients with known seizures, continuous video-EEG was slow in all and 69% had epileptiform abnormalities in the first 30 minutes, including 31% with seizures. An additional 8% developed epileptiform abnormalities over 16-24 hours. In 46%, treatment was changed based on continuous video-EEG. This study indicates that if continuous video-EEG is not available, a 30-minute EEG in the ICU has a substantial diagnostic yield and will lead to the detection of the majority of epileptiform abnormalities. In a small percentage of patients, continuous video-EEG will lead to the detection of additional epileptiform abnormalities. In a sub-population, with a history of seizures prior to the initiation of EEG recording, the benefits of continuous video-EEG in monitoring seizure activity and influencing treatment may be greater.

Task complexity modulates pilot electroencephalographic activity during real flights.

PubMed

Di Stasi, Leandro L; Diaz-Piedra, Carolina; Suárez, Juan; McCamy, Michael B; Martinez-Conde, Susana; Roca-Dorda, Joaquín; Catena, Andrés

2015-07-01

Most research connecting task performance and neural activity to date has been conducted in laboratory conditions. Thus, field studies remain scarce, especially in extreme conditions such as during real flights. Here, we investigated the effects of flight procedures of varied complexity on the in-flight EEG activity of military helicopter pilots. Flight procedural complexity modulated the EEG power spectrum: highly demanding procedures (i.e., takeoff and landing) were associated with higher EEG power in the higher frequency bands, whereas less demanding procedures (i.e., flight exercises) were associated with lower EEG power over the same frequency bands. These results suggest that EEG recordings may help to evaluate an operator's cognitive performance in challenging real-life scenarios, and thus could aid in the prevention of catastrophic events. © 2015 Society for Psychophysiological Research.

EEG and ocular correlates of circadian melatonin phase and human performance decrements during sleep loss

NASA Technical Reports Server (NTRS)

Cajochen, C.; Khalsa, S. B.; Wyatt, J. K.; Czeisler, C. A.; Dijk, D. J.

1999-01-01

The aim of this study was to quantify the associations between slow eye movements (SEMs), eye blink rate, waking electroencephalogram (EEG) power density, neurobehavioral performance, and the circadian rhythm of plasma melatonin in a cohort of 10 healthy men during up to 32 h of sustained wakefulness. The time course of neurobehavioral performance was characterized by fairly stable levels throughout the first 16 h of wakefulness followed by deterioration during the phase of melatonin secretion. This deterioration was closely associated with an increase in SEMs. Frontal low-frequency EEG activity (1-7 Hz) exhibited a prominent increase with time awake and little circadian modulation. EEG alpha activity exhibited circadian modulation. The dynamics of SEMs and EEG activity were phase locked to changes in neurobehavioral performance and lagged the plasma melatonin rhythm. The data indicate that frontal areas of the brain are more susceptible to sleep loss than occipital areas. Frontal EEG activity and ocular parameters may be used to monitor and predict changes in neurobehavioral performance associated with sleep loss and circadian misalignment.

A Within-subjects Experimental Protocol to Assess the Effects of Social Input on Infant EEG.

PubMed

St John, Ashley M; Kao, Katie; Chita-Tegmark, Meia; Liederman, Jacqueline; Grieve, Philip G; Tarullo, Amanda R

2017-05-03

Despite the importance of social interactions for infant brain development, little research has assessed functional neural activation while infants socially interact. Electroencephalography (EEG) power is an advantageous technique to assess infant functional neural activation. However, many studies record infant EEG only during one baseline condition. This protocol describes a paradigm that is designed to comprehensively assess infant EEG activity in both social and nonsocial contexts as well as tease apart how different types of social inputs differentially relate to infant EEG. The within-subjects paradigm includes four controlled conditions. In the nonsocial condition, infants view objects on computer screens. The joint attention condition involves an experimenter directing the infant's attention to pictures. The joint attention condition includes three types of social input: language, face-to-face interaction, and the presence of joint attention. Differences in infant EEG between the nonsocial and joint attention conditions could be due to any of these three types of input. Therefore, two additional conditions (one with language input while the experimenter is hidden behind a screen and one with face-to-face interaction) were included to assess the driving contextual factors in patterns of infant neural activation. Representative results demonstrate that infant EEG power varied by condition, both overall and differentially by brain region, supporting the functional nature of infant EEG power. This technique is advantageous in that it includes conditions that are clearly social or nonsocial and allows for examination of how specific types of social input relate to EEG power. This paradigm can be used to assess how individual differences in age, affect, socioeconomic status, and parent-infant interaction quality relate to the development of the social brain. Based on the demonstrated functional nature of infant EEG power, future studies should consider the role of EEG recording context and design conditions that are clearly social or nonsocial.

On-going electroencephalographic rhythms related to cortical arousal in wild-type mice: the effect of aging.

PubMed

Del Percio, Claudio; Drinkenburg, Wilhelmus; Lopez, Susanna; Infarinato, Francesco; Bastlund, Jesper Frank; Laursen, Bettina; Pedersen, Jan T; Christensen, Ditte Zerlang; Forloni, Gianluigi; Frasca, Angelisa; Noè, Francesco M; Bentivoglio, Marina; Fabene, Paolo Francesco; Bertini, Giuseppe; Colavito, Valeria; Kelley, Jonathan; Dix, Sophie; Richardson, Jill C; Babiloni, Claudio

2017-01-01

Resting state electroencephalographic (EEG) rhythms reflect the fluctuation of cortical arousal and vigilance in a typical clinical setting, namely the EEG recording for few minutes with eyes closed (i.e., passive condition) and eyes open (i.e., active condition). Can this procedure be back-translated to C57 (wild type) mice for aging studies? On-going EEG rhythms were recorded from a frontoparietal bipolar channel in 85 (19 females) C57 mice. Male mice were subdivided into 3 groups: 25 young (4.5-6 months), 18 middle-aged (12-15 months), and 23 old (20-24 months) mice to test the effect of aging. EEG power density was compared between short periods (about 5 minutes) of awake quiet behavior (passive) and dynamic exploration of the cage (active). Compared with the passive condition, the active condition induced decreased EEG power at 1-2 Hz and increased EEG power at 6-10 Hz in the group of 85 mice. Concerning the aging effects, the passive condition showed higher EEG power at 1-2 Hz in the old group than that in the others. Furthermore, the active condition exhibited a maximum EEG power at 6-8 Hz in the former group and 8-10 Hz in the latter. In the present conditions, delta and theta EEG rhythms reflected changes in cortical arousal and vigilance in freely behaving C57 mice across aging. These changes resemble the so-called slowing of resting state EEG rhythms observed in humans across physiological and pathological aging. The present EEG procedures may be used to enhance preclinical phases of drug discovery in mice for understanding the neurophysiological effects of new compounds against brain aging. Copyright © 2016 Elsevier Inc. All rights reserved.

Validation of a low-cost EEG device for mood induction studies.

PubMed

Rodríguez, Alejandro; Rey, Beatriz; Alcañiz, Mariano

2013-01-01

New electroencephalography (EEG) devices, more portable and cheaper, are appearing on the market. Studying the reliability of these EEG devices for emotional studies would be interesting, as these devices could be more economical and compatible with Virtual Reality (VR) settings. Therefore, the aim in this work was to validate a low-cost EEG device (Emotiv Epoc) to monitor brain activity during a positive emotional induction procedure. Emotional pictures (IAPS) were used to induce a positive mood in sixteen participants. Changes in the brain activity of subjects were compared between positive induction and neutral conditions. Obtained results were in accordance with previous scientific literature regarding frontal EEG asymmetry, which supports the possibility of using this low-cost EEG device in future mood induction studies combined with VR.

Real-time fMRI neurofeedback of the mediodorsal and anterior thalamus enhances correlation between thalamic BOLD activity and alpha EEG rhythm.

PubMed

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

2018-02-01

Real-time fMRI neurofeedback (rtfMRI-nf) with simultaneous EEG allows volitional modulation of BOLD activity of target brain regions and investigation of related electrophysiological activity. We applied this approach to study correlations between thalamic BOLD activity and alpha EEG rhythm. Healthy volunteers in the experimental group (EG, n = 15) learned to upregulate BOLD activity of the target region consisting of the mediodorsal (MD) and anterior (AN) thalamic nuclei using rtfMRI-nf during retrieval of happy autobiographical memories. Healthy subjects in the control group (CG, n = 14) were provided with a sham feedback. The EG participants were able to significantly increase BOLD activities of the MD and AN. Functional connectivity between the MD and the inferior precuneus was significantly enhanced during the rtfMRI-nf task. Average individual changes in the occipital alpha EEG power significantly correlated with the average MD BOLD activity levels for the EG. Temporal correlations between the occipital alpha EEG power and BOLD activities of the MD and AN were significantly enhanced, during the rtfMRI-nf task, for the EG compared to the CG. Temporal correlations with the alpha power were also significantly enhanced for the posterior nodes of the default mode network, including the precuneus/posterior cingulate, and for the dorsal striatum. Our findings suggest that the temporal correlation between the MD BOLD activity and posterior alpha EEG power is modulated by the interaction between the MD and the inferior precuneus, reflected in their functional connectivity. Our results demonstrate the potential of the rtfMRI-nf with simultaneous EEG for noninvasive neuromodulation studies of human brain function. © 2017 Wiley Periodicals, Inc.

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

PubMed

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

2017-03-01

To compare amplitude-integrated EEG (aEEG) and conventional EEG (EEG) activity in premature neonates. Biweekly aEEG and EEG were simultaneously recorded in a cohort of infants born less than 34 weeks gestation. aEEG recordings were visually assessed for lower and upper border amplitude and bandwidth. EEG recordings were compressed for visual evaluation of continuity and assessed using a signal processing software for interburst intervals (IBI) and frequencies' amplitude. Ten-minute segments of aEEG and EEG indices were compared using regression analysis. A total of 189 recordings from 67 infants were made, from which 1697 aEEG/EEG pairs of 10-minute segments were assessed. Good concordance was found for visual assessment of continuity between the 2 methods. EEG IBI, alpha and theta frequencies' amplitudes were negatively correlated to the aEEG lower border while conceptional age (CA) was positively correlated to aEEG lower border ( P < .001). IBI and all frequencies' amplitude were positively correlated to the upper aEEG border ( P ≤ .001). CA was negatively correlated to aEEG span while IBI, alpha, beta, and theta frequencies' amplitude were positively correlated to the aEEG span. Important information is retained and integrated in the transformation of premature neonatal EEG to aEEG. aEEG recordings in high-risk premature neonates reflect reliably EEG background information related to continuity and amplitude.

Brain-wave Dynamics Related to Cognitive Tasks and Neurofeedback Information Flow

NASA Astrophysics Data System (ADS)

Pop-Jordanova, Nada; Pop-Jordanov, Jordan; Dimitrovski, Darko; Markovska, Natasa

2003-08-01

Synchronization of oscillating neuronal discharges has been recently correlated to the moment of perception and the ensuing motor response, with transition between these two cognitive acts "through cellular mechanisms that remain to be established"[1]. Last year, using genetic strategies, it was found that the switching off persistent electric activity in the brain blocks memory recall [2]. On the other hand, analyzing mental-neural information flow, the nobelist Eccles has formulated a fundamental hypotheses that mental events may change the probability of quantum vesicular emissions of transmitters analogously to probability functions of quantum mechanics [3]. Applying the advanced quantum modeling to molecular rotational states exposed to electric activity in brain cells, we found that the probability of transitions does not depend on the field amplitude, suggesting the electric field frequency as the possible information-bearing physical quantity [4]. In this paper, an attempt is made to inter-correlate the above results on frequency aspects of neural transitions induced by cognitive tasks. Furthermore, considering the consecutive steps of mental-neural information flow during the biofeedback training to normalize EEG frequencies, the rationales for neurofeedback efficiency have been deduced.

Understanding perception of active noise control system through multichannel EEG analysis.

PubMed

Bagha, Sangeeta; Tripathy, R K; Nanda, Pranati; Preetam, C; Das, Debi Prasad

2018-06-01

In this Letter, a method is proposed to investigate the effect of noise with and without active noise control (ANC) on multichannel electroencephalogram (EEG) signal. The multichannel EEG signal is recorded during different listening conditions such as silent, music, noise, ANC with background noise and ANC with both background noise and music. The multiscale analysis of EEG signal of each channel is performed using the discrete wavelet transform. The multivariate multiscale matrices are formulated based on the sub-band signals of each EEG channel. The singular value decomposition is applied to the multivariate matrices of multichannel EEG at significant scales. The singular value features at significant scales and the extreme learning machine classifier with three different activation functions are used for classification of multichannel EEG signal. The experimental results demonstrate that, for ANC with noise and ANC with noise and music classes, the proposed method has sensitivity values of 75.831% ( p < 0.001 ) and 99.31% ( p < 0.001 ), respectively. The method has an accuracy value of 83.22% for the classification of EEG signal with music and ANC with music as stimuli. The important finding of this study is that by the introduction of ANC, music can be better perceived by the human brain.

Open Ephys electroencephalography (Open Ephys  +  EEG): a modular, low-cost, open-source solution to human neural recording

NASA Astrophysics Data System (ADS)

Black, Christopher; Voigts, Jakob; Agrawal, Uday; Ladow, Max; Santoyo, Juan; Moore, Christopher; Jones, Stephanie

2017-06-01

Objective. Electroencephalography (EEG) offers a unique opportunity to study human neural activity non-invasively with millisecond resolution using minimal equipment in or outside of a lab setting. EEG can be combined with a number of techniques for closed-loop experiments, where external devices are driven by specific neural signals. However, reliable, commercially available EEG systems are expensive, often making them impractical for individual use and research development. Moreover, by design, a majority of these systems cannot be easily altered to the specification needed by the end user. We focused on mitigating these issues by implementing open-source tools to develop a new EEG platform to drive down research costs and promote collaboration and innovation. Approach. Here, we present methods to expand the open-source electrophysiology system, Open Ephys (www.openephys.org), to include human EEG recordings. We describe the equipment and protocol necessary to interface various EEG caps with the Open Ephys acquisition board, and detail methods for processing data. We present applications of Open Ephys  +  EEG as a research tool and discuss how this innovative EEG technology lays a framework for improved closed-loop paradigms and novel brain-computer interface experiments. Main results. The Open Ephys  +  EEG system can record reliable human EEG data, as well as human EMG data. A side-by-side comparison of eyes closed 8-14 Hz activity between the Open Ephys  +  EEG system and the Brainvision ActiCHamp EEG system showed similar average power and signal to noise. Significance. Open Ephys  +  EEG enables users to acquire high-quality human EEG data comparable to that of commercially available systems, while maintaining the price point and extensibility inherent to open-source systems.

Open Ephys electroencephalography (Open Ephys  +  EEG): a modular, low-cost, open-source solution to human neural recording.

PubMed

Black, Christopher; Voigts, Jakob; Agrawal, Uday; Ladow, Max; Santoyo, Juan; Moore, Christopher; Jones, Stephanie

2017-06-01

Electroencephalography (EEG) offers a unique opportunity to study human neural activity non-invasively with millisecond resolution using minimal equipment in or outside of a lab setting. EEG can be combined with a number of techniques for closed-loop experiments, where external devices are driven by specific neural signals. However, reliable, commercially available EEG systems are expensive, often making them impractical for individual use and research development. Moreover, by design, a majority of these systems cannot be easily altered to the specification needed by the end user. We focused on mitigating these issues by implementing open-source tools to develop a new EEG platform to drive down research costs and promote collaboration and innovation. Here, we present methods to expand the open-source electrophysiology system, Open Ephys (www.openephys.org), to include human EEG recordings. We describe the equipment and protocol necessary to interface various EEG caps with the Open Ephys acquisition board, and detail methods for processing data. We present applications of Open Ephys  +  EEG as a research tool and discuss how this innovative EEG technology lays a framework for improved closed-loop paradigms and novel brain-computer interface experiments. The Open Ephys  +  EEG system can record reliable human EEG data, as well as human EMG data. A side-by-side comparison of eyes closed 8-14 Hz activity between the Open Ephys  +  EEG system and the Brainvision ActiCHamp EEG system showed similar average power and signal to noise. Open Ephys  +  EEG enables users to acquire high-quality human EEG data comparable to that of commercially available systems, while maintaining the price point and extensibility inherent to open-source systems.

Simultaneous EEG and MEG source reconstruction in sparse electromagnetic source imaging.

PubMed

Ding, Lei; Yuan, Han

2013-04-01

Electroencephalography (EEG) and magnetoencephalography (MEG) have different sensitivities to differently configured brain activations, making them complimentary in providing independent information for better detection and inverse reconstruction of brain sources. In the present study, we developed an integrative approach, which integrates a novel sparse electromagnetic source imaging method, i.e., variation-based cortical current density (VB-SCCD), together with the combined use of EEG and MEG data in reconstructing complex brain activity. To perform simultaneous analysis of multimodal data, we proposed to normalize EEG and MEG signals according to their individual noise levels to create unit-free measures. Our Monte Carlo simulations demonstrated that this integrative approach is capable of reconstructing complex cortical brain activations (up to 10 simultaneously activated and randomly located sources). Results from experimental data showed that complex brain activations evoked in a face recognition task were successfully reconstructed using the integrative approach, which were consistent with other research findings and validated by independent data from functional magnetic resonance imaging using the same stimulus protocol. Reconstructed cortical brain activations from both simulations and experimental data provided precise source localizations as well as accurate spatial extents of localized sources. In comparison with studies using EEG or MEG alone, the performance of cortical source reconstructions using combined EEG and MEG was significantly improved. We demonstrated that this new sparse ESI methodology with integrated analysis of EEG and MEG data could accurately probe spatiotemporal processes of complex human brain activations. This is promising for noninvasively studying large-scale brain networks of high clinical and scientific significance. Copyright © 2011 Wiley Periodicals, Inc.

Presleep relaxed 7-8 Hz EEG from left frontal region: marker of localised neuropsychological performance?

PubMed

Anderson, Clare; Horne, James A

2004-06-01

Others have shown that frontally dominant EEG activity of around 7-8 Hz is linked to ongoing cognitive performance. Interestingly, we have found that this EEG activity is particularly evident during the relatively artefact-free period following "lights out" at bedtime when people report "thinking" when lying relaxed in their own beds prior to the appearance of EEG-determined sleepiness. Here, we explore the extent to which this localised activity is indicative of 'trait' performance on left frontal neuropsychological tasks, as well as with less localised, more general tasks. Twelve right-handed young adults (mean age: 21.3 years) and 12 right-handed older adults (mean age: 67.2 years) underwent (i) morning, laboratory-based, waking EEGs comprising (eyes closed) contrived thinking tasks, and (ii) a home-based wake EEG at bedtime. EEGs divided the cortex into the four comparable quadrants: Fp1-F3; Fp2-F4; O1-P3; and O2-P4. From a wide frequency band of 3-10 Hz analysed in 1-Hz bins, only 7-8 Hz was associated with the neuropsychological performance (nonverbal planning, verbal fluency) for both younger and older participants. This was most evident during relaxed waking after 'lights out,' and from the left frontal EEG. Such associations were not apparent for the other EEG channels or for the nonspecific tasks. Laboratory-based daytime, frontal EEG recordings are problematic because of eye movement artefact and when participants are not fully relaxed. In contrast, the nighttime data are almost artefact-free and from fully relaxed participants. This particular EEG is useful for assessing cortically localised behaviour and indicates that a more traditional approach of using large bandwidths (e.g., the whole of "alpha" or "theta" ranges) may mask subfrequencies of functional importance.

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

PubMed

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

2011-01-01

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

LIMO EEG: A Toolbox for Hierarchical LInear MOdeling of ElectroEncephaloGraphic Data

PubMed Central

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

2011-01-01

Magnetic- and electric-evoked brain responses have traditionally been analyzed by comparing the peaks or mean amplitudes of signals from selected channels and averaged across trials. More recently, tools have been developed to investigate single trial response variability (e.g., EEGLAB) and to test differences between averaged evoked responses over the entire scalp and time dimensions (e.g., SPM, Fieldtrip). LIMO EEG is a Matlab toolbox (EEGLAB compatible) to analyse evoked responses over all space and time dimensions, while accounting for single trial variability using a simple hierarchical linear modelling of the data. In addition, LIMO EEG provides robust parametric tests, therefore providing a new and complementary tool in the analysis of neural evoked responses. PMID:21403915

Analysis of Brain Recurrence

NASA Astrophysics Data System (ADS)

Frilot, Clifton; Kim, Paul Y.; Carrubba, Simona; McCarty, David E.; Chesson, Andrew L.; Marino, Andrew A.

Analysis of Brain Recurrence (ABR) is a method for extracting physiologically significant information from the electroencephalogram (EEG), a non-stationary electrical output of the brain, the ultimate complex dynamical system. ABR permits quantification of temporal patterns in the EEG produced by the non-autonomous differential laws that govern brain metabolism. In the context of appropriate experimental and statistical designs, ABR is ideally suited to the task of interpreting the EEG. Present applications of ABR include discovery of a human magnetic sense, increased mechanistic understanding of neuronal membrane processes, diagnosis of degenerative neurological disease, detection of changes in brain metabolism caused by weak environmental electromagnetic fields, objective characterization of the quality of human sleep, and evaluation of sleep disorders. ABR has important beneficial implications for the development of clinical and experimental neuroscience.

Prediction of Treatment Outcome in Patients with Obsessive-Compulsive Disorder with Low-Resolution Brain Electromagnetic Tomography: A Prospective EEG Study.

PubMed

Krause, Daniela; Folkerts, Malte; Karch, Susanne; Keeser, Daniel; Chrobok, Agnieszka I; Zaudig, Michael; Hegerl, Ulrich; Juckel, Georg; Pogarell, Oliver

2015-01-01

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 10 weeks of standardized treatment with sertraline and behavioral therapy. LORETA was used to localize the sources of brain electrical activity. At week 10, 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 measuring brain activity with LORETA could be an efficient and applicable technique to prospectively identify treatment responders in OCD.

Prediction of Treatment Outcome in Patients with Obsessive-Compulsive Disorder with Low-Resolution Brain Electromagnetic Tomography: A Prospective EEG Study

PubMed Central

Krause, Daniela; Folkerts, Malte; Karch, Susanne; Keeser, Daniel; Chrobok, Agnieszka I.; Zaudig, Michael; Hegerl, Ulrich; Juckel, Georg; Pogarell, Oliver

2016-01-01

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 10 weeks of standardized treatment with sertraline and behavioral therapy. LORETA was used to localize the sources of brain electrical activity. At week 10, 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 measuring brain activity with LORETA could be an efficient and applicable technique to prospectively identify treatment responders in OCD. PMID:26834658

Ambulatory Seizure Monitoring: From Concept to Prototype Device.

PubMed

Myers, Mark H; Threatt, Madeline; Solies, Karsten M; McFerrin, Brent M; Hopf, Lindsey B; Birdwell, J Douglas; Sillay, Karl A

2016-07-01

The brain, made up of billions of neurons and synapses, is the marvelous core of human thought, action and memory. However, if neuronal activity manifests into abnormal electrical activity across the brain, neural behavior may exhibit synchronous neural firings known as seizures. If unprovoked seizures occur repeatedly, a patient may be diagnosed with epilepsy. The scope of this project is to develop an ambulatory seizure monitoring system that can be used away from a hospital, making it possible for the user to stay at home, and primary care personnel to monitor a patient's seizure activity in order to provide deeper analysis of the patient's condition and apply personalized intervention techniques. The ambulatory seizure monitoring device is a research device that has been developed with the objective of acquiring a portable, clean electroencephalography (EEG) signal and transmitting it wirelessly to a handheld device for processing and notification. This device is comprised of 4 phases: acquisition, transmission, processing and notification. During the acquisition stage, the EEG signal is detected using EEG electrodes; these signals are filtered and amplified before being transmitted in the second stage. The processing stage encompasses the signal processing and seizure prediction. A notification is sent to the patient and designated contacts, given an impending seizure. Each of these phases is comprised of various design components, hardware and software. The experimental findings illustrate that there may be a triggering mechanism through the phase lock value method that enables seizure prediction. The device addresses the need for long-term monitoring of the patient's seizure condition in order to provide the clinician a better understanding of the seizure's duration and frequency and ultimately provide the best remedy for the patient.

Ambulatory Seizure Monitoring: From Concept to Prototype Device

PubMed Central

Myers, Mark H.; Threatt, Madeline; Solies, Karsten M.; McFerrin, Brent M.; Hopf, Lindsey B.; Birdwell, J. Douglas; Sillay, Karl A.

2016-01-01

Background The brain, made up of billions of neurons and synapses, is the marvelous core of human thought, action and memory. However, if neuronal activity manifests into abnormal electrical activity across the brain, neural behavior may exhibit synchronous neural firings known as seizures. If unprovoked seizures occur repeatedly, a patient may be diagnosed with epilepsy. Purpose The scope of this project is to develop an ambulatory seizure monitoring system that can be used away from a hospital, making it possible for the user to stay at home, and primary care personnel to monitor a patient's seizure activity in order to provide deeper analysis of the patient's condition and apply personalized intervention techniques. Methods The ambulatory seizure monitoring device is a research device that has been developed with the objective of acquiring a portable, clean electroencephalography (EEG) signal and transmitting it wirelessly to a handheld device for processing and notification. Result This device is comprised of 4 phases: acquisition, transmission, processing and notification. During the acquisition stage, the EEG signal is detected using EEG electrodes; these signals are filtered and amplified before being transmitted in the second stage. The processing stage encompasses the signal processing and seizure prediction. A notification is sent to the patient and designated contacts, given an impending seizure. Each of these phases is comprised of various design components, hardware and software. The experimental findings illustrate that there may be a triggering mechanism through the phase lock value method that enables seizure prediction. Conclusion The device addresses the need for long-term monitoring of the patient's seizure condition in order to provide the clinician a better understanding of the seizure's duration and frequency and ultimately provide the best remedy for the patient. PMID:27647960

Semantic memory retrieval circuit: role of pre-SMA, caudate, and thalamus.

PubMed

Hart, John; Maguire, Mandy J; Motes, Michael; Mudar, Raksha Anand; Chiang, Hsueh-Sheng; Womack, Kyle B; Kraut, Michael A

2013-07-01

We propose that pre-supplementary motor area (pre-SMA)-thalamic interactions govern processes fundamental to semantic retrieval of an integrated object memory. At the onset of semantic retrieval, pre-SMA initiates electrical interactions between multiple cortical regions associated with semantic memory subsystems encodings as indexed by an increase in theta-band EEG power. This starts between 100-150 ms after stimulus presentation and is sustained throughout the task. We posit that this activity represents initiation of the object memory search, which continues in searching for an object memory. When the correct memory is retrieved, there is a high beta-band EEG power increase, which reflects communication between pre-SMA and thalamus, designates the end of the search process and resultant in object retrieval from multiple semantic memory subsystems. This high beta signal is also detected in cortical regions. This circuit is modulated by the caudate nuclei to facilitate correct and suppress incorrect target memories. Copyright © 2012 Elsevier Inc. All rights reserved.

Wireless and wearable EEG system for evaluating driver vigilance.

PubMed

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.

Effects of noxious stimuli on the electroencephalogram of anaesthetised chickens (Gallus gallus domesticus).

PubMed

McIlhone, Amanda E; Beausoleil, Ngaio J; Kells, Nikki J; Mellor, David J; Johnson, Craig B

2018-01-01

The reliable assessment and management of avian pain is important in the context of animal welfare. Overtly expressed signs of pain vary substantially between and within species, strains and individuals, limiting the use of behaviour in pain studies. Similarly, physiological indices of pain can also vary and may be confounded by influence from non-painful stimuli. In mammals, changes in the frequency spectrum of the electroencephalogram (EEG) recorded under light anaesthesia (the minimal anaesthesia model; MAM) have been shown to reliably indicate cerebral responses to noxious stimuli in a range of species. The aim of the current study was to determine whether the MAM can be applied to the study of nociception in birds. Ten chickens were lightly anaesthetised with halothane and their EEG recorded using surface electrodes during the application of supramaximal mechanical, thermal and electrical noxious stimuli. Spectral analysis revealed no EEG responses to any of these stimuli. Given that birds possess the neural apparatus to detect and process pain, and that the applied noxious stimuli elicit behavioural signs of pain in conscious chickens, this lack of response probably relates to methodological limitations. Anatomical differences between the avian and mammalian brains, along with a paucity of knowledge regarding specific sites of pain processing in the avian brain, could mean that EEG recorded from the head surface is insensitive to changes in neural activity in the pain processing regions of the avian brain. Future investigations should examine alternative electrode placement sites, based on avian homologues of the mammalian brain regions involved in pain processing.

Effects of noxious stimuli on the electroencephalogram of anaesthetised chickens (Gallus gallus domesticus)

PubMed Central

McIlhone, Amanda E.; Beausoleil, Ngaio J.; Mellor, David J.; Johnson, Craig B.

2018-01-01

The reliable assessment and management of avian pain is important in the context of animal welfare. Overtly expressed signs of pain vary substantially between and within species, strains and individuals, limiting the use of behaviour in pain studies. Similarly, physiological indices of pain can also vary and may be confounded by influence from non-painful stimuli. In mammals, changes in the frequency spectrum of the electroencephalogram (EEG) recorded under light anaesthesia (the minimal anaesthesia model; MAM) have been shown to reliably indicate cerebral responses to noxious stimuli in a range of species. The aim of the current study was to determine whether the MAM can be applied to the study of nociception in birds. Ten chickens were lightly anaesthetised with halothane and their EEG recorded using surface electrodes during the application of supramaximal mechanical, thermal and electrical noxious stimuli. Spectral analysis revealed no EEG responses to any of these stimuli. Given that birds possess the neural apparatus to detect and process pain, and that the applied noxious stimuli elicit behavioural signs of pain in conscious chickens, this lack of response probably relates to methodological limitations. Anatomical differences between the avian and mammalian brains, along with a paucity of knowledge regarding specific sites of pain processing in the avian brain, could mean that EEG recorded from the head surface is insensitive to changes in neural activity in the pain processing regions of the avian brain. Future investigations should examine alternative electrode placement sites, based on avian homologues of the mammalian brain regions involved in pain processing. PMID:29698446

COMPARISON OF EEG CHANGES PRODUCED BY CARBARYL (CARBAMATE), PERMETHRIN (TYPE I PYRETHROID), AND DELTAMETHRIN (TYPE II PYRETHROID)

EPA Science Inventory

We have reported that treatment with carbaryl may alter Theta activity in the EEG (Lyke et al., Toxicologist, 108(S-1):441, 2009). In this study, we examined the ability to detect changes in EEG activity produced by pesticides with different modes of action. Long Evans rats were ...

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

ERIC Educational Resources Information Center

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

2011-01-01

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

Patient prognosis based on feature extraction, selection and classification of EEG periodic activity.

PubMed

Sánchez-González, Alain; García-Zapirain, Begoña; Maestro Saiz, Iratxe; Yurrebaso Santamaría, Izaskun

2015-01-01

Periodic activity in electroencephalography (PA-EEG) is shown as comprising a series of repetitive wave patterns that may appear in different cerebral regions and are due to many different pathologies. The diagnosis based on PA-EEG is an arduous task for experts in Clinical Neurophysiology, being mainly based on other clinical features of patients. Considering this difficulty in the diagnosis it is also very complicated to establish the prognosis of patients who present PA-EEG. The goal of this paper is to propose a method capable of determining patient prognosis based on characteristics of the PA-EEG activity. The approach, based on a parallel classification architecture and a majority vote system has proven successful by obtaining a success rate of 81.94% in the classification of patient prognosis of our database.

Assessing the depth of hypnosis of xenon anaesthesia with the EEG.

PubMed

Stuttmann, Ralph; Schultz, Arthur; Kneif, Thomas; Krauss, Terence; Schultz, Barbara

2010-04-01

Xenon was approved as an inhaled anaesthetic in Germany in 2005 and in other countries of the European Union in 2007. Owing to its low blood/gas partition coefficient, xenons effects on the central nervous system show a fast onset and offset and, even after long xenon anaesthetics, the wake-up times are very short. The aim of this study was to examine which electroencephalogram (EEG) stages are reached during xenon application and whether these stages can be identified by an automatic EEG classification. Therefore, EEG recordings were performed during xenon anaesthetics (EEG monitor: Narcotrend®). A total of 300 EEG epochs were assessed visually with regard to the EEG stages. These epochs were also classified automatically by the EEG monitor Narcotrend® using multivariate algorithms. There was a high correlation between visual and automatic classification (Spearman's rank correlation coefficient r=0.957, prediction probability Pk=0.949). Furthermore, it was observed that very deep stages of hypnosis were reached which are characterised by EEG activity in the low frequency range (delta waves). The burst suppression pattern was not seen. In deep hypnosis, in contrast to the xenon EEG, the propofol EEG was characterised by a marked superimposed higher frequency activity. To ensure an optimised dosage for the single patient, anaesthetic machines for xenon should be combined with EEG monitoring. To date, only a few anaesthetic machines for xenon are available. Because of the high price of xenon, new and further developments of machines focus on optimizing xenon consumption.

Recording EEG in immature rats with a novel miniature telemetry system

PubMed Central

Zayachkivsky, A.; Lehmkuhle, M. J.; Fisher, J. H.; Ekstrand, J. J.

2013-01-01

Serial EEG recordings from immature rat pups are extremely difficult to obtain but important for analyzing animal models of neonatal seizures and other pediatric neurological conditions as well as normal physiology. In this report, we describe the features and applications of a novel miniature telemetry system designed to record EEG in rat pups as young as postnatal day 6 (P6). First, we have recorded electrographic seizure activity in two animal models of neonatal seizures, hypoxia- and kainate-induced seizures at P7. Second, we describe a viable approach for long-term continuous EEG monitoring of naturally reared rat pups implanted with EEG at P6. Third, we have used serial EEG recordings to record age-dependent changes in the background EEG signal as the animals matured from P7 to P11. The important advantages of using miniature wireless EEG technology are: 1) minimally invasive surgical implantation; 2) a device form-factor that is compatible with housing of rat pups with the dam and littermates; 3) serial recordings of EEG activity; and 4) low power consumption of the unit, theoretically allowing continuous monitoring for up to 2 yr without surgical reimplantation. The miniature EEG telemetry system provides a technical advance that allows researchers to record continuous and serial EEG recordings in neonatal rodent models of human neurological disorders, study the progression of the disease, and then assess possible therapies using quantitative EEG as an outcome measure. This new technical approach should improve animal models of human conditions that rely on EEG monitoring for diagnosis and therapy. PMID:23114207

Statistical features of hypnagogic EEG measured by a new scoring system.

PubMed

Tanaka, H; Hayashi, M; Hori, T

1996-11-01

The purpose of this study was to examine the durations of individual occurrences of each of nine hypnagogic electroencephalographic (EEG) stages and the interchange relationship among these stages. Most of the alpha patterns (stages 1, 2, and 3), ripples (stage 5), and spindles (stage 9) tended to last > 2 minutes. On the other hand, histograms of the durations of time in EEG flattening (stage 4) and vertex sharp wave (stages 6, 7, and 8) patterns had peaks that lasted < 30 seconds. Analysis of the sequences of EEG stage changes demonstrated that shifts to adjacent stages were most common for all stages. A smooth change in EEG stage occurred in the downward or upward direction in the hypnagogic state. This was especially true for the first five stages. EEG stages with vertex sharp waves (stages 6, 7, and 8), however, showed less-smooth changes, with approximately 20% of all changes involving a jump of more than one stage. These results show that the basic EEG activities in the sleep onset period are the alpha, theta, and sleep spindles activities, whereas the activities of vertex sharp waves seem to have a secondary or enhancing role, instead of independent characteristics.

Trans3D: a free tool for dynamical visualization of EEG activity transmission in the brain.

PubMed

Blinowski, Grzegorz; Kamiński, Maciej; Wawer, Dariusz

2014-08-01

The problem of functional connectivity in the brain is in the focus of attention nowadays, since it is crucial for understanding information processing in the brain. A large repertoire of measures of connectivity have been devised, some of them being capable of estimating time-varying directed connectivity. Hence, there is a need for a dedicated software tool for visualizing the propagation of electrical activity in the brain. To this aim, the Trans3D application was developed. It is an open access tool based on widely available libraries and supporting both Windows XP/Vista/7(™), Linux and Mac environments. Trans3D can create animations of activity propagation between electrodes/sensors, which can be placed by the user on the scalp/cortex of a 3D model of the head. Various interactive graphic functions for manipulating and visualizing components of the 3D model and input data are available. An application of the Trans3D tool has helped to elucidate the dynamics of the phenomena of information processing in motor and cognitive tasks, which otherwise would have been very difficult to observe. Trans3D is available at: http://www.eeg.pl/. Copyright © 2014 Elsevier Ltd. All rights reserved.

Electrophysiological Evidence for Ventral Stream Deficits in Schizophrenia Patients

PubMed Central

Plomp, Gijs; Roinishvili, Maya; Chkonia, Eka; Kapanadze, George; Kereselidze, Maia; Brand, Andreas; Herzog, Michael H.

2013-01-01

Schizophrenic patients suffer from many deficits including visual, attentional, and cognitive ones. Visual deficits are of particular interest because they are at the fore-end of information processing and can provide clear examples of interactions between sensory, perceptual, and higher cognitive functions. Visual deficits in schizophrenic patients are often attributed to impairments in the dorsal (where) rather than the ventral (what) stream of visual processing. We used a visual-masking paradigm in which patients and matched controls discriminated small vernier offsets. We analyzed the evoked electroencephalography (EEG) responses and applied distributed electrical source imaging techniques to estimate activity differences between conditions and groups throughout the brain. Compared with controls, patients showed strongly reduced discrimination accuracy, confirming previous work. The behavioral deficits corresponded to pronounced decreases in the evoked EEG response at around 200 ms after stimulus onset. At this latency, patients showed decreased activity for targets in left parietal cortex (dorsal stream), but the decrease was most pronounced in lateral occipital cortex (in the ventral stream). These deficiencies occurred at latencies that reflect object processing and fine shape discriminations. We relate the reduced ventral stream activity to deficient top-down processing of target stimuli and provide a framework for relating the commonly observed dorsal stream deficiencies with the currently observed ventral stream deficiencies. PMID:22258884

Electrophysiological evidence for ventral stream deficits in schizophrenia patients.

PubMed

Plomp, Gijs; Roinishvili, Maya; Chkonia, Eka; Kapanadze, George; Kereselidze, Maia; Brand, Andreas; Herzog, Michael H

2013-05-01

Schizophrenic patients suffer from many deficits including visual, attentional, and cognitive ones. Visual deficits are of particular interest because they are at the fore-end of information processing and can provide clear examples of interactions between sensory, perceptual, and higher cognitive functions. Visual deficits in schizophrenic patients are often attributed to impairments in the dorsal (where) rather than the ventral (what) stream of visual processing. We used a visual-masking paradigm in which patients and matched controls discriminated small vernier offsets. We analyzed the evoked electroencephalography (EEG) responses and applied distributed electrical source imaging techniques to estimate activity differences between conditions and groups throughout the brain. Compared with controls, patients showed strongly reduced discrimination accuracy, confirming previous work. The behavioral deficits corresponded to pronounced decreases in the evoked EEG response at around 200 ms after stimulus onset. At this latency, patients showed decreased activity for targets in left parietal cortex (dorsal stream), but the decrease was most pronounced in lateral occipital cortex (in the ventral stream). These deficiencies occurred at latencies that reflect object processing and fine shape discriminations. We relate the reduced ventral stream activity to deficient top-down processing of target stimuli and provide a framework for relating the commonly observed dorsal stream deficiencies with the currently observed ventral stream deficiencies.

Comparison of quantitative EEG characteristics of quiet and active sleep in newborns.

PubMed

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

2003-11-01

The aim of the present study was to verify whether the proposed method of computer-supported EEG analysis is able to differentiate the EEG activity in quiet sleep (QS) from that in active sleep (AS) in newborns. A quantitative description of the neonatal EEG may contribute to a more exact evaluation of the functional state of the brain, as well as to a refinement of diagnostics of brain dysfunction manifesting itself frequently as 'dysrhythmia' or 'dysmaturity'. Twenty-one healthy newborns (10 full-term and 11 pre-term) were examined polygraphically (EEG-eight channels, respiration, ECG, EOG and EMG) in the course of sleep. From each EEG record, two 5-min samples (one from QS and one from AS) were subject to an off-line computerized analysis. The obtained data were averaged with respect to the sleep state and to the conceptional age. The number of variables was reduced by means of factor analysis. All factors identified by factor analysis were highly significantly influenced by sleep states in both developmental periods. Likewise, a comparison of the measured variables between QS and AS revealed many statistically significant differences. The variables describing (a) the number and length of quasi-stationary segments, (b) voltage and (c) power in delta and theta bands contributed to the greatest degree to the differentiation of EEGs between both sleep states. The presented method of the computerized EEG analysis which has good discriminative potential is adequately sensitive and describes the neonatal EEG with convenient accuracy.

Amplitude-Integrated EEG and Range-EEG Modulation Associated with Pneumatic Orocutaneous Stimulation in Preterm Infants

PubMed Central

Barlow, Steven M; Jegatheesan, Priya; Weiss, Sunshine; Govindaswami, Balaji; Wang, Jingyan; Lee, Jaehoon; Oder, Austin; Song, Dongli

2013-01-01

Background Controlled somatosensory stimulation strategies have demonstrated merit in developing oral feeding skills in premature infants who lack a functional suck, however, the effects of orosensory entrainment stimulation on electrocortical dynamics is unknown. Objective To determine the effects of servo-controlled pneumatic orocutaneous stimulation presented during gavage feedings on the modulation of aEEG and rEEG activity. Methods Two-channel EEG recordings were collected during 180 sessions that included orocutaneous stimulation and non-stimulation epochs among 22 preterm infants (mean gestational age = 28.56 weeks) who were randomized to treatment and control ‘sham’ conditions. The study was initiated at around 32 weeks post-menstrual age (PMA). The raw EEG was transformed into amplitude-integrated EEG (aEEG) margins, and range-EEG (rEEG) amplitude bands measured at 1-minute intervals and subjected to a mixed models statistical analysis. Results Multiple significant effects were observed in the processed EEG during and immediately following 3-minute periods of orocutaneous stimulation, including modulation of the upper and lower margins of the aEEG, and a reorganization of rEEG with an apparent shift from amplitude bands D and E to band C throughout the 23-minute recording period that followed the first stimulus block when compared to the sham condition. Cortical asymmetry also was apparent in both EEG measures. Conclusions Orocutaneous stimulation represents a salient trigeminal input which has both short- and long-term effects in modulating electrocortical activity, and thus, is hypothesized to represent a form of neural adaptation or plasticity that may benefit the preterm infant during this critical period of brain maturation. PMID:24310443

Detection of EEG-patterns associated with real and imaginary movements using detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Pavlov, Alexey N.; Runnova, Anastasiya E.; Maksimenko, Vladimir A.; Grishina, Daria S.; Hramov, Alexander E.

2018-02-01

Authentic recognition of specific patterns of electroencephalograms (EEGs) associated with real and imagi- nary movements is an important stage for the development of brain-computer interfaces. In experiments with untrained participants, the ability to detect the motor-related brain activity based on the multichannel EEG processing is demonstrated. Using the detrended fluctuation analysis, changes in the EEG patterns during the imagination of hand movements are reported. It is discussed how the ability to recognize brain activity related to motor executions depends on the electrode position.

Auditory and audio-visual processing in patients with cochlear, auditory brainstem, and auditory midbrain implants: An EEG study.

PubMed

Schierholz, Irina; Finke, Mareike; Kral, Andrej; Büchner, Andreas; Rach, Stefan; Lenarz, Thomas; Dengler, Reinhard; Sandmann, Pascale

2017-04-01

There is substantial variability in speech recognition ability across patients with cochlear implants (CIs), auditory brainstem implants (ABIs), and auditory midbrain implants (AMIs). To better understand how this variability is related to central processing differences, the current electroencephalography (EEG) study compared hearing abilities and auditory-cortex activation in patients with electrical stimulation at different sites of the auditory pathway. Three different groups of patients with auditory implants (Hannover Medical School; ABI: n = 6, CI: n = 6; AMI: n = 2) performed a speeded response task and a speech recognition test with auditory, visual, and audio-visual stimuli. Behavioral performance and cortical processing of auditory and audio-visual stimuli were compared between groups. ABI and AMI patients showed prolonged response times on auditory and audio-visual stimuli compared with NH listeners and CI patients. This was confirmed by prolonged N1 latencies and reduced N1 amplitudes in ABI and AMI patients. However, patients with central auditory implants showed a remarkable gain in performance when visual and auditory input was combined, in both speech and non-speech conditions, which was reflected by a strong visual modulation of auditory-cortex activation in these individuals. In sum, the results suggest that the behavioral improvement for audio-visual conditions in central auditory implant patients is based on enhanced audio-visual interactions in the auditory cortex. Their findings may provide important implications for the optimization of electrical stimulation and rehabilitation strategies in patients with central auditory prostheses. Hum Brain Mapp 38:2206-2225, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Correlates of a single cortical action potential in the epidural EEG

PubMed Central

Teleńczuk, Bartosz; Baker, Stuart N; Kempter, Richard; Curio, Gabriel

2015-01-01

To identify the correlates of a single cortical action potential in surface EEG, we recorded simultaneously epidural EEG and single-unit activity in the primary somatosensory cortex of awake macaque monkeys. By averaging over EEG segments coincident with more than hundred thousand single spikes, we found short-lived (≈ 0.5 ms) triphasic EEG deflections dominated by high-frequency components > 800 Hz. The peak-to-peak amplitude of the grand-averaged spike correlate was 80 nV, which matched theoretical predictions, while single-neuron amplitudes ranged from 12 to 966 nV. Combining these estimates with post-stimulus-time histograms of single-unit responses to median-nerve stimulation allowed us to predict the shape of the evoked epidural EEG response and to estimate the number of contributing neurons. These findings establish spiking activity of cortical neurons as a primary building block of high-frequency epidural EEG, which thus can serve as a quantitative macroscopic marker of neuronal spikes. PMID:25554430

Value of electrical stimulation and high frequency oscillations (80–500 Hz) in identifying epileptogenic areas during intracranial EEG recordings

PubMed Central

Jacobs, Julia; Zijlmans, Maeike; Zelmann, Rina; Olivier, André; Hall, Jeffery; Gotman, Jean; Dubeau, François

2013-01-01

Summary Purpose Electrical stimulation (ES) is used during intracranial electroencephalography (EEG) investigations to delineate epileptogenic areas and seizure-onset zones (SOZs) by provoking afterdischarges (ADs) or patients’ typical seizure. High frequency oscillations (HFOs—ripples, 80–250 Hz; fast ripples, 250–500 Hz) are linked to seizure onset. This study investigates whether interictal HFOs are more frequent in areas with a low threshold to provoke ADs or seizures. Methods Intracranial EEG studies were filtered at 500 Hz and sampled at 2,000 Hz. HFOs were visually identified. Twenty patients underwent ES, with gradually increasing currents. Results were interpreted as agreeing or disagreeing with the intracranial study (clinical-EEG seizure onset defined the SOZ). Current thresholds provoking an AD or seizure were correlated with the rate of HFOs of each channel. Results ES provoked a seizure in 12 and ADs in 19 patients. Sixteen patients showed an ES response inside the SOZ, and 10 had additional areas with ADs. The response was more specific for mesiotemporal than for neocortical channels. HFO rates were negatively correlated with thresholds for ES responses; especially in neo-cortical regions; areas with low threshold and high HFO rate were colocalized even outside the SOZ. Discussion Areas showing epileptic HFOs colocalize with those reacting to ES. HFOs may represent a pathologic correlate of regions showing an ES response; both phenomena suggest a more widespread epileptogenicity. PMID:19845730

The Brain Computer Interface Future: Time for a Strategy

DTIC Science & Technology

2013-02-14

electrophysiological activity can be measured by electroencepholography ( EEG ), electrocorticography (ECoG), magnetoencephalography (MEG), or signal activity...magnetic resonance imaging (MRI) or near infrared spectroscopy. Currently EEG is most the most widely used BCI interface due to high temporal...resolution, less user risk, and lower costs.12 EEG technology has been widely available for many decades but has significantly expanded as researchers

Wireless system for long-term EEG monitoring of absence epilepsy

NASA Astrophysics Data System (ADS)

Whitchurch, Ashwin K.; Ashok, B. H.; Kumaar, R. V.; Saurkesi, K.; Varadan, Vijay K.

2002-11-01

Absence epilepsy is a form of epilepsy common mostly in children. The most common manifestations of Absence epilepsy are staring and transient loss of responsiveness. Also, subtle motor activities may occur. Due to the subtle nature of these symptoms, episodes of absence epilepsy may often go unrecognized for long periods of time or be mistakenly attributed to attention deficit disorder or daydreaming. Spells of absence epilepsy may last about 10 seconds and occur hundreds of times each day. Patients have no recollections of the events that occurred during those seizures and will resume normal activity without any postictal symptoms. The EEG during such episodes of Absence epilepsy shows intermittent activity of 3 Hz generalized spike and wave complexes. As EEG is the only way of detecting such symptoms, it is required to monitor the EEG of the patient for a long time and thus remain only in bed. So, effectively the EEG is being monitored only when the patient is stationary. The wireless monitoring sys tem described in this paper aims at eliminating this constraint and enables the physicial to monitor the EEG when the patient resumes his normal activities. This approach could even help the doctor identify possible triggers of absence epilepsy.

Analysis and visualization of single-trial event-related potentials

NASA Technical Reports Server (NTRS)

Jung, T. P.; Makeig, S.; Westerfield, M.; Townsend, J.; Courchesne, E.; Sejnowski, T. J.

2001-01-01

In this study, a linear decomposition technique, independent component analysis (ICA), is applied to single-trial multichannel EEG data from event-related potential (ERP) experiments. Spatial filters derived by ICA blindly separate the input data into a sum of temporally independent and spatially fixed components arising from distinct or overlapping brain or extra-brain sources. Both the data and their decomposition are displayed using a new visualization tool, the "ERP image," that can clearly characterize single-trial variations in the amplitudes and latencies of evoked responses, particularly when sorted by a relevant behavioral or physiological variable. These tools were used to analyze data from a visual selective attention experiment on 28 control subjects plus 22 neurological patients whose EEG records were heavily contaminated with blink and other eye-movement artifacts. Results show that ICA can separate artifactual, stimulus-locked, response-locked, and non-event-related background EEG activities into separate components, a taxonomy not obtained from conventional signal averaging approaches. This method allows: (1) removal of pervasive artifacts of all types from single-trial EEG records, (2) identification and segregation of stimulus- and response-locked EEG components, (3) examination of differences in single-trial responses, and (4) separation of temporally distinct but spatially overlapping EEG oscillatory activities with distinct relationships to task events. The proposed methods also allow the interaction between ERPs and the ongoing EEG to be investigated directly. We studied the between-subject component stability of ICA decomposition of single-trial EEG epochs by clustering components with similar scalp maps and activation power spectra. Components accounting for blinks, eye movements, temporal muscle activity, event-related potentials, and event-modulated alpha activities were largely replicated across subjects. Applying ICA and ERP image visualization to the analysis of sets of single trials from event-related EEG (or MEG) experiments can increase the information available from ERP (or ERF) data. Copyright 2001 Wiley-Liss, Inc.

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

PubMed

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

2014-01-01

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

Towards deep brain monitoring with superficial EEG sensors plus neuromodulatory focused ultrasound

PubMed Central

Darvas, F; Mehić, E; Caler, CJ; Ojemann, JG; Mourad, PD

2017-01-01

Noninvasive recordings of electrophysiological activity have limited anatomical specificity and depth. We hypothesized that spatially tagging a small volume of brain with a unique electroencephalogram (EEG) signal induced by pulsed focused ultrasound (pFU) could overcome those limitations. As a first step towards testing this hypothesis, we applied transcranial ultrasound (2 MHz, 200 microsecond-long pulses applied at 1050 Hz for one second at a spatial peak temporal average intensity of 1.4 W/cm2) to the brains of anesthetized rats while simultaneously recording EEG signals. We observed a significant 1050 Hz electrophysiological signal only when ultrasound was applied to living brain. Moreover, amplitude demodulation of the EEG signal at 1050 Hz yielded measurement of gamma band (>30 Hz) brain activity consistent with direct measurements of that activity. These results represent preliminary support for use of pFU as a spatial tagging mechanism for non-invasive EEG-based mapping of deep brain activity with high spatial resolution. PMID:27181686

Trait anxiety impact on posterior activation asymmetries at rest and during evoked negative emotions: EEG investigation.

PubMed

Aftanas, Ljubomir I; Pavlov, Sergey V

2005-01-01

The main objective of the present investigation was to examine how high trait anxiety would influence cortical EEG asymmetries under non-emotional conditions and while experiencing negative emotions. The 62-channel EEG was recorded in control (n=21) and high anxiety (HA, n=18) non-patient individuals. Results showed that in HA subjects, the lowest level of arousal (eyes closed) was associated with stronger right-sided parieto-temporal theta-1 (4-6 Hz) and beta-1 (12-18 Hz) activity, whereas increased non-emotional arousal (eyes open, viewing neutral movie clip) was marked by persisting favored right hemisphere beta-1 activity. In turn, viewing aversive movie clip by the HA group led to significant lateralized decrease of the right parieto-temporal beta-1 power, which was initially higher in the emotionally neutral conditions. The EEG data suggests that asymmetrical parieto-temporal theta-1 and beta-1 EEG activity might be better interpreted in terms of Gray's BAS and BIS theory.

Analysis of spontaneous EEG activity in Alzheimer's disease using cross-sample entropy and graph theory.

PubMed

Gomez, Carlos; Poza, Jesus; Gomez-Pilar, Javier; Bachiller, Alejandro; Juan-Cruz, Celia; Tola-Arribas, Miguel A; Carreres, Alicia; Cano, Monica; Hornero, Roberto

2016-08-01

The aim of this pilot study was to analyze spontaneous electroencephalography (EEG) activity in Alzheimer's disease (AD) by means of Cross-Sample Entropy (Cross-SampEn) and two local measures derived from graph theory: clustering coefficient (CC) and characteristic path length (PL). Five minutes of EEG activity were recorded from 37 patients with dementia due to AD and 29 elderly controls. Our results showed that Cross-SampEn values were lower in the AD group than in the control one for all the interactions among EEG channels. This finding indicates that EEG activity in AD is characterized by a lower statistical dissimilarity among channels. Significant differences were found mainly for fronto-central interactions (p <; 0.01, permutation test). Additionally, the application of graph theory measures revealed diverse neural network changes, i.e. lower CC and higher PL values in AD group, leading to a less efficient brain organization. This study suggests the usefulness of our approach to provide further insights into the underlying brain dynamics associated with AD.

Memory-Augmented Active Deep Learning for Identifying Relations Between Distant Medical Concepts in Electroencephalography Reports.

PubMed

Maldonado, Ramon; Goodwin, Travis R; Harabagiu, Sanda M

2018-01-01

The automatic identification of relations between medical concepts in a large corpus of Electroencephalography (EEG) reports is an important step in the development of an EEG-specific patient cohort retrieval system as well as in the acquisition of EEG-specific knowledge from this corpus. EEG-specific relations involve medical concepts that are not typically mentioned in the same sentence or even the same section of a report, thus requiring extraction techniques that can handle such long-distance dependencies. To address this challenge, we present a novel frame work which combines the advantages of a deep learning framework employing Dynamic Relational Memory (DRM) with active learning. While DRM enables the prediction of long-distance relations, active learning provides a mechanism for accurately identifying relations with minimal training data, obtaining an 5-fold cross validationF1 score of 0.7475 on a set of 140 EEG reports selected with active learning. The results obtained with our novel framework show great promise.

Effect of low-level laser stimulation on EEG.

PubMed

Wu, Jih-Huah; Chang, Wen-Dien; Hsieh, Chang-Wei; Jiang, Joe-Air; Fang, Wei; Shan, Yi-Chia; Chang, Yang-Chyuan

2012-01-01

Conventional laser stimulation at the acupoint can induce significant brain activation, and the activation is theoretically conveyed by the sensory afferents. Whether the insensible low-level Laser stimulation outside the acupoint could also evoke electroencephalographic (EEG) changes is not known. We designed a low-level laser array stimulator (6 pcs laser diode, wavelength 830 nm, output power 7 mW, and operation frequency 10 Hz) to deliver insensible laser stimulations to the palm. EEG activities before, during, and after the laser stimulation were collected. The amplitude powers of each EEG frequency band were analyzed. We found that the low-level laser stimulation was able to increase the power of alpha rhythms and theta waves, mainly in the posterior head regions. These effects lasted at least 15 minutes after cessation of the laser stimulation. The amplitude power of beta activities in the anterior head regions decreased after laser stimulation. We thought these EEG changes comparable to those in meditation.

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

PubMed

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.

Separation of circadian and wake duration-dependent modulation of EEG activation during wakefulness

NASA Technical Reports Server (NTRS)

Cajochen, C.; Wyatt, J. K.; Czeisler, C. A.; Dijk, D. J.

2002-01-01

The separate contribution of circadian rhythmicity and elapsed time awake on electroencephalographic (EEG) activity during wakefulness was assessed. Seven men lived in an environmental scheduling facility for 4 weeks and completed fourteen 42.85-h 'days', each consisting of an extended (28.57-h) wake episode and a 14.28-h sleep opportunity. The circadian rhythm of plasma melatonin desynchronized from the 42.85-h day. This allowed quantification of the separate contribution of circadian phase and elapsed time awake to variation in EEG power spectra (1-32 Hz). EEG activity during standardized behavioral conditions was markedly affected by both circadian phase and elapsed time awake in an EEG frequency- and derivation-specific manner. The nadir of the circadian rhythm in alpha (8-12 Hz) activity in both fronto-central and occipito-parietal derivations occurred during the biological night, close to the crest of the melatonin rhythm. The nadir of the circadian rhythm of theta (4.5-8 Hz) and beta (20-32 Hz) activity in the fronto-central derivation was located close to the onset of melatonin secretion, i.e. during the wake maintenance zone. As time awake progressed, delta frequency (1-4.5 Hz) and beta (20-32 Hz) activity rose monotonically in frontal derivations. The interaction between the circadian and wake-dependent increase in frontal delta was such that the intrusion of delta was minimal when sustained wakefulness coincided with the biological day, but pronounced during the biological night. Our data imply that the circadian pacemaker facilitates frontal EEG activation during the wake maintenance zone, by generating an arousal signal that prevents the intrusion of low-frequency EEG components, the propensity for which increases progressively during wakefulness.

Quantitative Electroencephalography Analysis (qEEG) of Neuro-Electro-Adaptive Therapy 12™ [NEAT12] Up-Regulates Cortical Potentials in an Alcoholic during Protracted Abstinence: Putative Anti-Craving Implications

PubMed Central

Waite, Roger L; Oscar-Berman, Marlene; RBraverman, Eric; Barh, Debmalya; Blum, Kenneth

2015-01-01

Introduction Cranial electrotherapy stimulation (CES) is a noninvasive therapy that has been used for decades in the United States to treat anxiety, depression, and insomnia in the general population. The effectiveness of CES has been questioned by many and its use is considered controversial. In this study we are presenting data on one alcoholic patient using a newly engineered device we call Neuro-Electro-Adaptive Therapy 12™ [NEAT12]. This hybrid device utilizes TENS current characteristics yielding CES effects. This device has been found to primarily target the excitation of the Cingulate Gyrus region of the brain. Case presentation This is a 42 year old male who has been abstinent from alcohol for approximately two months. The data presented herein represents the pre to post qEEG differences of an alcoholic in protracted abstinence. This subject was evaluated both before and after using the NEAT-12 device. The pre to post comparisons suggest that the cortical potentials especially at the Cingulate Gyrus are up regulated after using the device. The absolute power changes obtained shows a decrease of more than 2 SD as noted in the delta wave spectrum. Also noted is an overall cortical increase in the alpha spectrum. The resting alert state of a neuro typical population is most prominently marked by a regulation of 7.5-11 Hz alpha throughout the cortex. The decreased in delta and theta suggests an up regulation of the prefrontal cortex and the anterior Cingulate Gyrus a site involved in substance use disorder (SUD). Conclusion A presence of dominant slow waves through the prefrontal cortex and the anterior Cingulate Gyrus is often associated with OCD, anxiety, impulsivity and cravings in addicted populations. It is conceivable that our initial finding of altered electrical activity of the brain using qEEG analysis suggests the NEAT-12 may induce a “normalization” of aberrant electrical activity of the cortical region of the brain known to occur during protracted abstinence of alcoholics. It may have utility as a putative anti-craving CES device and therefore warrants intensive investigation. PMID:25927012

Quantitative EEG during REM and NREM sleep in combat-exposed veterans with and without Posttraumatic Stress Disorder

PubMed Central

Cohen, Daniel J.; Begley, Amy; Alman, Jennie J.; Cashmere, J. David; Pietrone, Regina N.; Seres, Robert J.; Germain, Anne

2012-01-01

Summary Sleep disturbances are a hallmark feature of posttraumatic stress disorder (PTSD), and associated with poor clinical outcomes. Few studies have examined sleep quantitative electroencephalography (qEEG), a technique able to detect subtle differences polysomnography does not capture. We hypothesized greater high-frequency qEEG would reflect “hyperarousal” in in combat veterans with PTSD (n=16) compared to veterans without PTSD (n=13). EEG power in traditional EEG frequency bands was computed for artifact-free sleep epochs across an entire night. Correlations were performed between qEEG and ratings of PTSD symptoms and combat exposure. The groups did not differ significantly in whole night qEEG measures for either REM or NREM. Non-significant medium effect sizes suggest less REM beta (opposite to our hypothesis), less REM and NREM sigma, and more NREM gamma in combat veterans with PTSD. Positive correlations were found between combat exposure and NREM beta (PTSD group only), and REM and NREM sigma (non-PTSD group only). Results did not support global hyperarousal in PTSD as indexed by increased beta qEEG activity. The correlation of sigma activity with combat exposure in those without PTSD, and the non-significant trend towards less sigma activity during both REM and NREM sleep in combat veterans with PTSD suggests that differential information processing during sleep may characterize combat-exposed military veterans with and without PTSD. PMID:22845675

Using EEG To Detect and Monitor Mental Fatigue

NASA Technical Reports Server (NTRS)

Montgomery, Leslie; Luna, Bernadette; Trejo, Leonard J.; Montgomery, Richard

2001-01-01

This project aims to develop EEG-based methods for detecting and monitoring mental fatigue. Mental fatigue poses a serious risk, even when performance is not apparently degraded. When such fatigue is associated with sustained performance of a single type of cognitive task it may be related to the metabolic energy required for sustained activation of cortical areas specialized for that task. The objective of this study was to adapt EEG to monitor cortical energy over a long period of performance of a cognitive task. Multielectrode event related potentials (ERPs) were collected every 15 minutes in nine subjects who performed a mental arithmetic task (algebraic sum of four randomly generated negative or positive digits). A new problem was presented on a computer screen 0.5 seconds after each response; some subjects endured for as long as three hours. ERPs were transformed to a quantitative measure of scalp electrical field energy. The average energy level at electrode P3 (near the left angular gyrus), 100-300 msec latency, was compared over the series of ERPs. For most subjects, scalp energy density at P3 gradually fell over the period of task performance and dramatically increased just before the subject was unable to continue the task. This neural response can be simulated for individual subjects using, a differential equation model in which it is assumed that the mental arithmetic task requires a commitment of metabolic energy that would otherwise be used for brain activities that are temporarily neglected. Their cumulative neglect eventually requires a reallocation of energy away from the mental arithmetic task.

"Epileptosis"--a syndrome or useless speculation?

PubMed

Faber, J; Vladyka, V; Dufková, D; Faltus, F; Jirák, R; Pavlovský, P; Smídová, E; Zvolský, P; Zukov, I; Klár, I; Posmurová, M; Srutová, L

1996-01-01

102 patients were divided into 3 groups: epileptics, psychotics and epileptics with psychotic symptoms. All had long been monitored for a number of clinical and laboratory parameters. Though different in many respects, all share states of sudden dysphoria, cacophoria, panic anxiety, horror, and EEG (stereo-EEG, too) signs of epileptic or other gross anomalies, often correlated to those affective disorders. Attacks of dysphoria, epilepsy, and psychosis come spontaneously and in response to biological (hypoglycemia, sleep deprivation, alcohol, menses) or psychosocial stimulation (agitation, quarrels, fear of redundancy, psychic trauma). These states (attacks, dysphoria, "neurotic" or even psychotic episodes) often provoke one another. -Calling this syndrome epileptosis, we believe its mechanism is due to lesions of the limbic and brainstem modulation systems. At the start of the process there is an epileptic focus in the amygdalo-hippocampal complex (AHC) which in itself can trigger simple or complex partial paroxysm but also-by means of electric stimulation of the AHC-states of dysphoria, anxiety, and psychotic hallucinations. Besides, a form of pathological learning develops in premorbid "hypersensitive" personality which can be put down to associative learning and to Overton's phenomenon of "state-dependent retention of learned responses". This may give rise to mutual stimulation where epileptic focal activity in AHC can provoke dysphoria while an external psychosocial situation can trigger epileptic activity there, too (AHC). Since there need not always be mydriasis (though other vegetative signs such as tachycardia, tachypnoea, nausea, blush and others are frequent) or unconsciousness, and some psychomotor manifestations may be out of the ordinary, and scalp EEG may be normal, such patients are often regarded as "hysterics" or malingerers.

An exploratory data analysis of electroencephalograms using the functional boxplots approach

PubMed Central

Ngo, Duy; Sun, Ying; Genton, Marc G.; Wu, Jennifer; Srinivasan, Ramesh; Cramer, Steven C.; Ombao, Hernando

2015-01-01

Many model-based methods have been developed over the last several decades for analysis of electroencephalograms (EEGs) in order to understand electrical neural data. In this work, we propose to use the functional boxplot (FBP) to analyze log periodograms of EEG time series data in the spectral domain. The functional bloxplot approach produces a median curve—which is not equivalent to connecting medians obtained from frequency-specific boxplots. In addition, this approach identifies a functional median, summarizes variability, and detects potential outliers. By extending FBPs analysis from one-dimensional curves to surfaces, surface boxplots are also used to explore the variation of the spectral power for the alpha (8–12 Hz) and beta (16–32 Hz) frequency bands across the brain cortical surface. By using rank-based nonparametric tests, we also investigate the stationarity of EEG traces across an exam acquired during resting-state by comparing the spectrum during the early vs. late phases of a single resting-state EEG exam. PMID:26347598

EMG parameters and EEG α Index change at fatigue period during different types of muscle contraction

NASA Astrophysics Data System (ADS)

Zhang, Li; Zhou, Bin; Song, Gaoqing

2010-10-01

The purpose of this study is to measure and analyze the characteristics in change of EMG and EEG parameters at muscle fatigue period in participants with different exercise capacity. Twenty participants took part in the tests. They were divided into two groups, Group A (constant exerciser) and Group B (seldom-exerciser). MVC dynamic and 1/3 isometric exercises were performed; EMG and EEG signals were recorded synchronously during different type of muscle contraction. Results indicated that values of MVC, RMS and IEMG in Group A were greater than Group B, but isometric exercise time was shorter than the time of dynamic exercise although its intensity was light. Turning point of IEMG and α Index occurred synchronously during constant muscle contraction of isometric or dynamic exercise. It is concluded that IEMG turning point may be an indication to justify muscle fatigue. Synchronization of EEG and EMG reflects its common characteristics on its bio-electric change.

EMG parameters and EEG α Index change at fatigue period during different types of muscle contraction

NASA Astrophysics Data System (ADS)

Zhang, Li; Zhou, Bin; Song, Gaoqing

2011-03-01

The purpose of this study is to measure and analyze the characteristics in change of EMG and EEG parameters at muscle fatigue period in participants with different exercise capacity. Twenty participants took part in the tests. They were divided into two groups, Group A (constant exerciser) and Group B (seldom-exerciser). MVC dynamic and 1/3 isometric exercises were performed; EMG and EEG signals were recorded synchronously during different type of muscle contraction. Results indicated that values of MVC, RMS and IEMG in Group A were greater than Group B, but isometric exercise time was shorter than the time of dynamic exercise although its intensity was light. Turning point of IEMG and α Index occurred synchronously during constant muscle contraction of isometric or dynamic exercise. It is concluded that IEMG turning point may be an indication to justify muscle fatigue. Synchronization of EEG and EMG reflects its common characteristics on its bio-electric change.

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

PubMed

Ng, Kwun Kei; Penney, Trevor B

2014-01-01

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

Relationship between prolonged neural suppression and cerebral hemodynamic dysfunction during hypothermia in asphyxiated piglets.

PubMed

Jinnai, Wataru; Nakamura, Shinji; Koyano, Kosuke; Yamato, Satoshi; Wakabayashi, Takayuki; Htun, Yinmon; Nakao, Yasuhiro; Iwase, Takashi; Nakamura, Makoto; Yasuda, Saneyuki; Ueno, Masaki; Miki, Takanori; Kusaka, Takashi

2018-05-19

Hypothermia (HT) improves the outcome of neonatal hypoxic-ischemic encephalopathy. Here, we investigated changes during HT in cortical electrical activity using amplitude-integrated electroencephalography (aEEG) and in cerebral blood volume (CBV) and cerebral hemoglobin oxygen saturation using near-infrared time-resolved spectroscopy (TRS) and compared the results with those obtained during normothermia (NT) after a hypoxic-ischemic (HI) insult in a piglet model of asphyxia. We previously reported that a greater increase in CBV can indicate greater pressure-passive cerebral perfusion due to more severe brain injury and correlates with prolonged neural suppression during NT. We hypothesized that when energy metabolism is suppressed during HT, the cerebral hemodynamics of brains with severe injury would be suppressed to a greater extent, resulting in a greater decrease in CBV during HT that would correlate with prolonged neural suppression after insult. Twenty-six piglets were divided into four groups: control with NT (C-NT, n = 3), control with HT (C-HT, n = 3), HI insult with NT (HI-NT, n = 10), and HI insult with HT (HI-HT, n = 10). TRS and aEEG were performed in all groups until 24 h after the insult. Piglets in the HI-HT group were maintained in a hypothermic state for 24 h after the insult. There was a positive linear correlation between changes in CBV at 1, 3, 6, and 12 h after the insult and low-amplitude aEEG (<5 µV) duration after insult in the HI-NT group, but a negative linear correlation between these two parameters at 6 and 12 h after the insult in the HI-HT group. The aEEG background score and low-amplitude EEG duration after the insult did not differ between these two groups. A longer low-amplitude EEG duration after insult was associated with a greater CBV decrease during HT in the HI-HT group, suggesting that brains with more severe neural suppression could be more prone to HT-induced suppression of cerebral metabolism and circulation. Copyright © 2018 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Nonlinear Recurrent Dynamics and Long-Term Nonstationarities in EEG Alpha Cortical Activity: Implications for Choosing Adequate Segment Length in Nonlinear EEG Analyses.

PubMed

Cerquera, Alexander; Vollebregt, Madelon A; Arns, Martijn

2018-03-01

Nonlinear analysis of EEG recordings allows detection of characteristics that would probably be neglected by linear methods. This study aimed to determine a suitable epoch length for nonlinear analysis of EEG data based on its recurrence rate in EEG alpha activity (electrodes Fz, Oz, and Pz) from 28 healthy and 64 major depressive disorder subjects. Two nonlinear metrics, Lempel-Ziv complexity and scaling index, were applied in sliding windows of 20 seconds shifted every 1 second and in nonoverlapping windows of 1 minute. In addition, linear spectral analysis was carried out for comparison with the nonlinear results. The analysis with sliding windows showed that the cortical dynamics underlying alpha activity had a recurrence period of around 40 seconds in both groups. In the analysis with nonoverlapping windows, long-term nonstationarities entailed changes over time in the nonlinear dynamics that became significantly different between epochs across time, which was not detected with the linear spectral analysis. Findings suggest that epoch lengths shorter than 40 seconds neglect information in EEG nonlinear studies. In turn, linear analysis did not detect characteristics from long-term nonstationarities in EEG alpha waves of control subjects and patients with major depressive disorder patients. We recommend that application of nonlinear metrics in EEG time series, particularly of alpha activity, should be carried out with epochs around 60 seconds. In addition, this study aimed to demonstrate that long-term nonlinearities are inherent to the cortical brain dynamics regardless of the presence or absence of a mental disorder.

Experimental validation of the influence of white matter anisotropy on the intracranial EEG forward solution

PubMed Central

Schomer, Donald L.; Dehghani, Nima; Ulbert, Istvan; Cash, Sydney; Papavasiliou, Steve; Eisenberg, Solomon R.; Dale, Anders M.; Halgren, Eric

2010-01-01

Forward solutions with different levels of complexity are employed for localization of current generators, which are responsible for the electric and magnetic fields measured from the human brain. The influence of brain anisotropy on the forward solution is poorly understood. The goal of this study is to validate an anisotropic model for the intracranial electric forward solution by comparing with the directly measured ‘gold standard’. Dipolar sources are created at known locations in the brain and intracranial electroencephalogram (EEG) is recorded simultaneously. Isotropic models with increasing level of complexity are generated along with anisotropic models based on Diffusion tensor imaging (DTI). A Finite Element Method based forward solution is calculated and validated using the measured data. Major findings are (1) An anisotropic model with a linear scaling between the eigenvalues of the electrical conductivity tensor and water self-diffusion tensor in brain tissue is validated. The greatest improvement was obtained when the stimulation site is close to a region of high anisotropy. The model with a global anisotropic ratio of 10:1 between the eigenvalues (parallel: tangential to the fiber direction) has the worst performance of all the anisotropic models. (2) Inclusion of cerebrospinal fluid as well as brain anisotropy in the forward model is necessary for an accurate description of the electric field inside the skull. The results indicate that an anisotropic model based on the DTI can be constructed non-invasively and shows an improved performance when compared to the isotropic models for the calculation of the intracranial EEG forward solution. Electronic supplementary material The online version of this article (doi:10.1007/s10827-009-0205-z) contains supplementary material, which is available to authorized users. PMID:20063051

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

PubMed

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

2016-01-01

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

Performance and brain electrical activity during prolonged confinement.

PubMed

Lorenz, B; Lorenz, J; Manzey, D

1996-01-01

A subset of the AGARD-STRES battery including memory search, unstable tracking, and a combination of both tasks (dual-task), was applied repeatedly to the four chamber crew members before, during, and after the 60-day isolation period of EXEMSI. Five ground control group members served as a control group. A subjective state questionnaire was also included. The results were subjected to a quantitative single-subject analysis. Electroencephalograms (EEG) were recorded to permit correlation of changes in task performance with changes in the physiological state. Evaluation of the EEG focused on spectral parameters of spontaneous EEG waves. No physiological data were collected from the control group. Significant decrements in tracking ability were observed in the chamber crew. The time course of these effects followed a triphasic pattern with initial deterioration, intermediate recovery to pre-isolation baseline scores after the first half of the isolation period, and a second deterioration towards the end. None of the control group subjects displayed such an effect. Memory search (speed and accuracy) was only occasionally impaired during isolation, but the control group displayed a similar pattern of changes. It is suggested that a state of decreased alertness causes tracking deterioration, which leads to a reduced efficiency of sustained cue utilization. The assumption of low alertness was further substantiated by higher fatigue ratings by the chamber crew compared to those of the control group. Analysis of the continuous EEG recordings revealed that only two subjects produced reliable alpha wave activity (8-12 Hz) over Pz and, to a much smaller extent, Fz-theta wave activity (5-7 Hz) during task performance. In both subjects Pz-alpha power decreased consistently under task conditions involving single-task and dual-task tracking. Fz-theta activity was increased more by single-task and dual-task memory search than by single-task tracking. The alpha attenuation appears to be associated with an increasing demand on perceptual cue utilization required by the tracking performance. In one subject marked attenuation of alpha power occurred during the first half of the confinement period, where he also scored the highest fatigue ratings. A striking increase in fronto-central theta activity was observed in the same subject after six weeks of isolation. The change was associated with an efficient rather than a degraded task performance, and a high rating of the item "concentrated" and a low rating of the item "fatigued." This finding supports the hypothesis that the activation state associated with increased fronto-central theta activity accompanies efficient performance of demanding mental tasks. The usefulness of standardized laboratory tasks as monitoring instruments is demonstrated by the direct comparability with results of studies obtained from other relevant research applications using the same tasks. The feasibility of a self-administered integrated psychophysiological assessment of the individual state was illustrated by the nearly complete collection of data. The large number of individual data collected over the entire period permitted application of quantitative single-subject analysis, allowing reliable determination of changes in the individual state in the course of time. It thus appears that this assessment technique can be adapted for in-flight monitoring of astronauts during prolonged spaceflights. Parallel EEG recording can provide relevant supplementary information for diagnosing the individual activation state associated with task performance. The existence of large individual differences in the generation of task-sensitive EEG rhythms forms an important issue for further studies.

Electroencephalography in the Diagnosis of Genetic Generalized Epilepsy Syndromes

PubMed Central

Seneviratne, Udaya; Cook, Mark J.; D’Souza, Wendyl Jude

2017-01-01

Genetic generalized epilepsy (GGE) consists of several syndromes diagnosed and classified on the basis of clinical features and electroencephalographic (EEG) abnormalities. The main EEG feature of GGE is bilateral, synchronous, symmetric, and generalized spike-wave complex. Other classic EEG abnormalities are polyspikes, epileptiform K-complexes and sleep spindles, polyspike-wave discharges, occipital intermittent rhythmic delta activity, eye-closure sensitivity, fixation-off sensitivity, and photoparoxysmal response. However, admixed with typical changes, atypical epileptiform discharges are also commonly seen in GGE. There are circadian variations of generalized epileptiform discharges. Sleep, sleep deprivation, hyperventilation, intermittent photic stimulation, eye closure, and fixation-off are often used as activation techniques to increase the diagnostic yield of EEG recordings. Reflex seizure-related EEG abnormalities can be elicited by the use of triggers such as cognitive tasks and pattern stimulation during the EEG recording in selected patients. Distinct electrographic abnormalities to help classification can be identified among different electroclinical syndromes. PMID:28993753

Two Different Populations within the Healthy Elderly: Lack of Conflict Detection in Those at Risk of Cognitive Decline

PubMed Central

Sánchez-Moguel, Sergio M.; Alatorre-Cruz, Graciela C.; Silva-Pereyra, Juan; González-Salinas, Sofía; Sanchez-Lopez, Javier; Otero-Ojeda, Gloria A.; Fernández, Thalía

2018-01-01

During healthy aging, inhibitory processing is affected at the sensorial, perceptual, and cognitive levels. The assessment of event-related potentials (ERPs) during the Stroop task has been used to study age-related decline in the efficiency of inhibitory processes. Studies using ERPs have found that the P300 amplitude increases and the N500 amplitude is attenuated in healthy elderly adults compared to those in young adults. On the other hand, it has been reported that theta excess in resting EEG with eyes closed is a good predictor of cognitive decline during aging 7 years later, while a normal EEG increases the probability of not developing cognitive decline. The behavioral and ERP responses during a Counting-Stroop task were compared between 22 healthy elderly subjects with normal EEG (Normal-EEG group) and 22 healthy elderly subjects with an excess of EEG theta activity (Theta-EEG group). Behaviorally, the Normal-EEG group showed a higher behavioral interference effect than the Theta-EEG group. ERP patterns were different between the groups, and two facts are highlighted: (a) the P300 amplitude was higher in the Theta-EEG group, with both groups showing a P300 effect in almost all electrodes, and (b) the Theta-EEG group did not show an N500 effect. These results suggest that the diminishment in inhibitory control observed in the Theta-EEG group may be compensated by different processes in earlier stages, which would allow them to perform the task with similar efficiency to that of participants with a normal EEG. This study is the first to show that healthy elderly subjects with an excess of theta EEG activity not only are at risk of developing cognitive decline but already have a cognitive impairment. PMID:29375352

Two Different Populations within the Healthy Elderly: Lack of Conflict Detection in Those at Risk of Cognitive Decline.

PubMed

Sánchez-Moguel, Sergio M; Alatorre-Cruz, Graciela C; Silva-Pereyra, Juan; González-Salinas, Sofía; Sanchez-Lopez, Javier; Otero-Ojeda, Gloria A; Fernández, Thalía

2017-01-01

During healthy aging, inhibitory processing is affected at the sensorial, perceptual, and cognitive levels. The assessment of event-related potentials (ERPs) during the Stroop task has been used to study age-related decline in the efficiency of inhibitory processes. Studies using ERPs have found that the P300 amplitude increases and the N500 amplitude is attenuated in healthy elderly adults compared to those in young adults. On the other hand, it has been reported that theta excess in resting EEG with eyes closed is a good predictor of cognitive decline during aging 7 years later, while a normal EEG increases the probability of not developing cognitive decline. The behavioral and ERP responses during a Counting-Stroop task were compared between 22 healthy elderly subjects with normal EEG (Normal-EEG group) and 22 healthy elderly subjects with an excess of EEG theta activity (Theta-EEG group). Behaviorally, the Normal-EEG group showed a higher behavioral interference effect than the Theta-EEG group. ERP patterns were different between the groups, and two facts are highlighted: (a) the P300 amplitude was higher in the Theta-EEG group, with both groups showing a P300 effect in almost all electrodes, and (b) the Theta-EEG group did not show an N500 effect. These results suggest that the diminishment in inhibitory control observed in the Theta-EEG group may be compensated by different processes in earlier stages, which would allow them to perform the task with similar efficiency to that of participants with a normal EEG. This study is the first to show that healthy elderly subjects with an excess of theta EEG activity not only are at risk of developing cognitive decline but already have a cognitive impairment.

Spatio-temporal dynamics of multimodal EEG-fNIRS signals in the loss and recovery of consciousness under sedation using midazolam and propofol

PubMed Central

Won, Dong-Ok; Chi, Seong In; Seo, Kwang-Suk; Kim, Hyun Jeong; Müller, Klaus-Robert; Lee, Seong-Whan

2017-01-01

On sedation motivated by the clinical needs for safety and reliability, recent studies have attempted to identify brain-specific signatures for tracking patient transition into and out of consciousness, but the differences in neurophysiological effects between 1) the sedative types and 2) the presence/absence of surgical stimulations still remain unclear. Here we used multimodal electroencephalography–functional near-infrared spectroscopy (EEG–fNIRS) measurements to observe electrical and hemodynamic responses during sedation simultaneously. Forty healthy volunteers were instructed to push the button to administer sedatives in response to auditory stimuli every 9–11 s. To generally illustrate brain activity at repetitive transition points at the loss of consciousness (LOC) and the recovery of consciousness (ROC), patient-controlled sedation was performed using two different sedatives (midazolam (MDZ) and propofol (PPF)) under two surgical conditions. Once consciousness was lost via sedatives, we observed gradually increasing EEG power at lower frequencies (<15 Hz) and decreasing power at higher frequencies (>15 Hz), as well as spatially increased EEG powers in the delta and lower alpha bands, and particularly also in the upper alpha rhythm, at the frontal and parieto-occipital areas over time. During ROC from unconsciousness, these spatio-temporal changes were reversed. Interestingly, the level of consciousness was switched on/off at significantly higher effect-site concentrations of sedatives in the brain according to the use of surgical stimuli, but the spatio-temporal EEG patterns were similar, regardless of the sedative used. We also observed sudden phase shifts in fronto-parietal connectivity at the LOC and the ROC as critical points. fNIRS measurement also revealed mild hemodynamic fluctuations. Compared with general anesthesia, our results provide insights into critical hallmarks of sedative-induced (un)consciousness, which have similar spatio-temporal EEG-fNIRS patterns regardless of the stage and the sedative used. PMID:29121108

Feasibility of imaging epileptic seizure onset with EIT and depth electrodes.

PubMed

Witkowska-Wrobel, Anna; Aristovich, Kirill; Faulkner, Mayo; Avery, James; Holder, David

2018-06-01

Imaging ictal and interictal activity with Electrical Impedance Tomography (EIT) using intracranial electrode mats has been demonstrated in animal models of epilepsy. In human epilepsy subjects undergoing presurgical evaluation, depth electrodes are often preferred. The purpose of this work was to evaluate the feasibility of using EIT to localise epileptogenic areas with intracranial electrodes in humans. The accuracy of localisation of the ictal onset zone was evaluated in computer simulations using 9M element FEM models derived from three subjects. 5 mm radius perturbations imitating a single seizure onset event were placed in several locations forming two groups: under depth electrode coverage and in the contralateral hemisphere. Simulations were made for impedance changes of 1% expected for neuronal depolarisation over milliseconds and 10% for cell swelling over seconds. Reconstructions were compared with EEG source modelling for a radially orientated dipole with respect to the closest EEG recording contact. The best accuracy of EIT was obtained using all depth and 32 scalp electrodes, greater than the equivalent accuracy with EEG inverse source modelling. The localisation error was 5.2 ± 1.8, 4.3 ± 0 and 46.2 ± 25.8 mm for perturbations within the volume enclosed by depth electrodes and 29.6 ± 38.7, 26.1 ± 36.2, 54.0 ± 26.2 mm for those without (EIT 1%, 10% change, EEG source modelling, n = 15 in 3 subjects, p < 0.01). As EIT was insensitive to source dipole orientation, all 15 perturbations within the volume enclosed by depth electrodes were localised, whereas the standard clinical method of visual inspection of EEG voltages, only localised 8 out of 15 cases. This suggests that adding EIT to SEEG measurements could be beneficial in localising the onset of seizures. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Human EEG responses to controlled alterations of the Earth's magnetic field.

PubMed

Sastre, Antonio; Graham, Charles; Cook, Mary R; Gerkovich, Mary M; Gailey, Paul

2002-09-01

Examine the effects of controlled changes in the Earth's magnetic field on electroencephalogram (EEG) and subjective report. Fifty volunteers were exposed double-blind to changes in field magnitude, angle of inclination, and angle of deviation. Volunteers were also exposed to magnetic field conditions found near the North and South Pole. EEG recorded over temporal and occipital sites was compared across 4s baseline, field exposure, and no-change control trials. No EEG spectral differences as a function of gender or recording site were found. Geomagnetic field alterations had no effect on total energy (0.5-42 Hz), energy within traditional EEG analysis bands, or on the 95% spectral edge. Most volunteers reported no sensations; others reported non-specific symptoms unrelated to type of field change. Three hypothesized field detection mechanisms were not supported: (1) mechanical reception through torque exerted on the ferromagnetic material magnetite; (2) movement-induced induction of an electric field in the body; and (3) enhanced sensitivity due to alterations in the rates of chemical reactions involving electron spin states. Humans have little ability to detect brief alterations in the geomagnetic field, even if these alteration are of a large magnitude.

Biomarkers for visceral hypersensitivity identified by classification of electroencephalographic frequency alterations

NASA Astrophysics Data System (ADS)

Graversen, Carina; Brock, Christina; Mohr Drewes, Asbjørn; Farina, Dario

2011-10-01

Abdominal pain is frequently related to visceral hypersensitivity. This is associated with increased neuronal excitability in the central nervous system (CNS), which can be manifested as discrete electroencephalographic (EEG) alterations. In the current placebo-controlled study, visceral hypersensitivity was evoked by chemical irritation of the esophagus with acid and capsaicin perfusion. The resulting hyperexcitability of the CNS was evaluated by evoked brain potentials following painful electrical stimulations of a remote organ—the rectosigmoid colon. Alterations in individual EEG power distributions between baseline and after perfusion were quantified by extracting features from the evoked brain potentials using an optimized discrete wavelet transform. Visceral hypersensitivity was identified as increased EEG power in the delta, theta and alpha frequency bands. By applying a support vector machine in regression mode, the individual baseline corrected alterations after sensitization were discriminated from alterations caused by placebo perfusions. An accuracy of 91.7% was obtained (P < 0.01). The regression value representing the overall alteration of the EEG correlated with the degree of hyperalgesia (P = 0.03). In conclusion, this study showed that classification of EEG can be used to detect biomarkers reflecting central neuronal changes. In the future, this may be used in studies of pain physiology and pharmacological interventions.

EEG-neurofeedback training of beta band (12-22Hz) affects alpha and beta frequencies - A controlled study of a healthy population.

PubMed

Jurewicz, Katarzyna; Paluch, Katarzyna; Kublik, Ewa; Rogala, Jacek; Mikicin, Mirosław; Wróbel, Andrzej

2018-01-08

The frequency-function relation of various EEG bands has inspired EEG-neurofeedback procedures intending to improve cognitive abilities in numerous clinical groups. In this study, we administered EEG-neurofeedback (EEG-NFB) to a healthy population to determine the efficacy of this procedure. We evaluated feedback manipulation in the beta band (12-22Hz), known to be involved in visual attention processing. Two groups of healthy adults were trained to either up- or down-regulate beta band activity, thus providing mutual control. Up-regulation training induced increases in beta and alpha band (8-12Hz) amplitudes during the first three sessions. Group-independent increases in the activity of both bands were observed in the later phase of training. EEG changes were not matched by measured behavioural indices of attention. Parallel changes in the two bands challenge the idea of frequency-specific EEG-NFB protocols and suggest their interdependence. Our study exposes the possibility (i) that the alpha band is more prone to manipulation, and (ii) that changes in the bands' amplitudes are independent from specified training. We therefore encourage a more comprehensive approach to EEG-neurofeedback training embracing physiological and/or operational relations among various EEG bands. Copyright © 2017 Elsevier Ltd. All rights reserved.

Magnetic Stimulation and Epilepsy

DTIC Science & Technology

2013-10-14

the seizure-induced groups exhibited varying degrees of EEG activity reduction. Figure 2. The effects of TMS on penicillin-induced seizures...the EEG recording including (a) baseline (pre-penicillin injection), (b) 30-min post-penicillin injection (30min-PI), (c) 10-min post- TMS stimulation...stable conditions 55% faster, and the 5 pps TMS -treated group 78% faster. Figure 3. Maximum frequency relationships in EEG activity among the

Inflammatory and vascular placental lesions are associated with neonatal amplitude integrated EEG recording in early premature neonates

PubMed Central

Goshen, Sharon; Richardson, Justin; Drunov, VIadimir; Staretz Chacham, Orna; Shany, Eilon

2017-01-01

Introduction Placental histologic examination can assist in revealing the mechanism leading to preterm birth. Accumulating evidence suggests an association between intrauterine pathological processes, morbidity and mortality of premature infants, and their long term outcome. Neonatal brain activity is increasingly monitored in neonatal intensive care units by amplitude integrated EEG (aEEG) and indices of background activity and sleep cycling patterns were correlated with long term outcome. We hypothesized an association between types of placental lesions and abnormal neonatal aEEG patterns. Objective To determine the association between the placental lesions observed in extreme preterm deliveries, and their neonatal aEEG patterns and survival. Patients and methods This prospective cohort study included extreme premature infants, who were born ≤ 28 weeks of gestation, their placentas were available for histologic examination, and had a continues aEEG, soon after birth)n = 34). Infants and maternal clinical data were collected. aEEG data was assessed for percentage of depressed daily activity in the first 3 days of life and for sleep cycling. Associations of placental histology with clinical findings and aEEG activity were explored using parametric and non-parametric statistics. Results Twenty two out of the 34 newborns survived to discharge. Preterm prelabor rupture of membranes (PPROM) or chorioamnionitis were associated with placental lesions consistent with fetal amniotic fluid infection (AFI) or maternal under perfusion (MUP) (P < 0.05). Lesions consistent with fetal response to AFI were associated with absence of SWC pattern during the 1st day of life. Fetal-vascular-thrombo-occlusive lesions of inflammatory type were negatively associated with depressed cerebral activity during the 1st day of life, and with aEEG cycling during the 2nd day of life (P<0.05). Placental lesions associated with MUP were associated with depressed neonatal cerebral activity during the first 3 days of life (P = 0.007). Conclusions Depressed neonatal aEEG patterns are associated with placental lesions consistent with maternal under perfusion, and amniotic fluid infection of fetal type, but not with fetal thrombo-oclusive vascular disease of inflammatory type. Our findings highlight the association between the intrauterine mechanisms leading to preterm parturition and subsequent depressed neonatal cerebral function early after birth, which eventually may put premature infants at risk for abnormal neurodevelopmental outcome. PMID:28644831

Approach and withdrawal motivation in schizophrenia: an examination of frontal brain asymmetric activity.

PubMed

Horan, William P; Wynn, Jonathan K; Mathis, Ian; Miller, Gregory A; Green, Michael F

2014-01-01

Although motivational disturbances are common in schizophrenia, their neurophysiological and psychological basis is poorly understood. This electroencephalography (EEG) study examined the well-established motivational direction model of asymmetric frontal brain activity in schizophrenia. According to this model, relative left frontal activity in the resting EEG reflects enhanced approach motivation tendencies, whereas relative right frontal activity reflects enhanced withdrawal motivation tendencies. Twenty-five schizophrenia outpatients and 25 healthy controls completed resting EEG assessments of frontal asymmetry in the alpha frequency band (8-12 Hz), as well as a self-report measure of behavioral activation and inhibition system (BIS/BAS) sensitivity. Patients showed an atypical pattern of differences from controls. On the EEG measure patients failed to show the left lateralized activity that was present in controls, suggesting diminished approach motivation. On the self-report measure, patients reported higher BIS sensitivity than controls, which is typically interpreted as heightened withdrawal motivation. EEG asymmetry scores did not significantly correlate with BIS/BAS scores or with clinical symptom ratings among patients. The overall pattern suggests a motivational disturbance in schizophrenia characterized by elements of both diminished approach and elevated withdrawal tendencies.

High-resolution EEG (HR-EEG) and magnetoencephalography (MEG).

PubMed

Gavaret, M; Maillard, L; Jung, J

2015-03-01

High-resolution EEG (HR-EEG) and magnetoencephalography (MEG) allow the recording of spontaneous or evoked electromagnetic brain activity with excellent temporal resolution. Data must be recorded with high temporal resolution (sampling rate) and high spatial resolution (number of channels). Data analyses are based on several steps with selection of electromagnetic signals, elaboration of a head model and use of algorithms in order to solve the inverse problem. Due to considerable technical advances in spatial resolution, these tools now represent real methods of ElectroMagnetic Source Imaging. HR-EEG and MEG constitute non-invasive and complementary examinations, characterized by distinct sensitivities according to the location and orientation of intracerebral generators. In the presurgical assessment of drug-resistant partial epilepsies, HR-EEG and MEG can characterize and localize interictal activities and thus the irritative zone. HR-EEG and MEG often yield significant additional data that are complementary to other presurgical investigations and particularly relevant in MRI-negative cases. Currently, the determination of the epileptogenic zone and functional brain mapping remain rather less well-validated indications. In France, in 2014, HR-EEG is now part of standard clinical investigation of epilepsy, while MEG remains a research technique. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Analysis of bioelectric records and fabrication of phototype sleep analysis equipment

NASA Technical Reports Server (NTRS)

Kellaway, P.

1972-01-01

A computer-analysis technique was used to evaluate the changes in the waking EEGs of 5 normal subjects which occurred during the oral administration of flurazepam hydrochloride (Dalmane). While the subjects were receiving the drug, there was an increase in the amount of beta (14-38 c/sec) activity in fronto-central EEG leads in all 5 subjects. This increase in beta activity was characterized by a highly consistent increase in the number of waves that occurred during an EEG recording interval of fixed duration and by a less consistent increase in average wave amplitude. There was no detectable change in mean EEG wavelength (frequency) within the beta frequency range. The EEG patterns reverted to their baseline condition during 2-3 weeks after withdrawal of the drug. Analysis of the alpha, theta and delta components of the EEG indicated no changes during or following administration of the drug. This study clearly illustrates the usefulness of specific computer-analysis techniques in the characterization and quantification of sleep-promoting drugs upon the EEG of the normal young adults in the waking state. Two preamplifiers and 150 EEG monitoring caps with electrodes were delivered to MSC.

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

PubMed

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

2014-06-01

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

Artifact removal from EEG data with empirical mode decomposition

NASA Astrophysics Data System (ADS)

Grubov, Vadim V.; Runnova, Anastasiya E.; Efremova, Tatyana Yu.; Hramov, Alexander E.

2017-03-01

In the paper we propose the novel method for dealing with the physiological artifacts caused by intensive activity of facial and neck muscles and other movements in experimental human EEG recordings. The method is based on analysis of EEG signals with empirical mode decomposition (Hilbert-Huang transform). We introduce the mathematical algorithm of the method with following steps: empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing empirical modes with artifacts, reconstruction of the initial EEG signal. We test the method on filtration of experimental human EEG signals from movement artifacts and show high efficiency of the method.

Adolescent Changes in Homeostatic Regulation of EEG Activity in the Delta and Theta Frequency Bands during NREM Sleep

PubMed Central

Campbell, Ian G.; Darchia, Nato; Higgins, Lisa M.; Dykan, Igor V.; Davis, Nicole M.; de Bie, Evan; Feinberg, Irwin

2011-01-01

Study Objectives: Slow wave EEG activity in NREM sleep decreases by more than 60% between ages 10 and 20 years. Slow wave EEG activity also declines across NREM periods (NREMPs) within a night, and this decline is thought to represent the dynamics of sleep homeostasis. We used longitudinal data to determine whether these homeostatic dynamics change across adolescence. Design: All-night sleep EEG was recorded semiannually for 6 years. Setting: EEG was recorded with ambulatory recorders in the subjects' homes. Participants: Sixty-seven subjects in 2 cohorts, one starting at age 9 and one starting at age 12 years. Measurements and Results: For NREM delta (1-4 Hz) and theta (4-8 Hz) EEG, we tested whether the proportion of spectral energy contained in the first NREMP changes with age. We also tested for age changes in the parameters of the process S exponential decline. For both delta and theta, the proportion of energy in the first NREMP declined significantly across ages 9 to 18 years. Process S parameters SWA0 and TWA0, respectively, represent slow wave (delta) activity and theta wave activity at the beginning of the night. SWA0 and TWA0 declined significantly (P < 0.0001) across ages 9 to 18. Conclusions: These declines indicate that the intensity of the homeostatic or restorative processes at the beginning of sleep diminished across adolescence. We propose that this change in sleep regulation is caused by the synaptic pruning that occurs during adolescent brain maturation. Citation: Campbell IG; Darchia N; Higgins LM; Dykan IV; Davis NM; de Bie E; Feinberg I. Adolescent changes in homeostatic regulation of EEG activity in the delta and theta frequency bands during NREM sleep. SLEEP 2011;34(1):83-91. PMID:21203377

Effect of the Anti-depressant Sertraline, the Novel Anti-seizure Drug Vinpocetine and Several Conventional Antiepileptic Drugs on the Epileptiform EEG Activity Induced by 4-Aminopyridine.

PubMed

Sitges, Maria; Aldana, Blanca Irene; Reed, Ronald Charles

2016-06-01

Seizures are accompanied by an exacerbated activation of cerebral ion channels. 4-aminopyridine (4-AP) is a pro-convulsive agent which mechanism of action involves activation of Na(+) and Ca(2+) channels, and several antiepileptic drugs control seizures by reducing these channels permeability. The antidepressant, sertraline, and the anti-seizure drug vinpocetine are effective inhibitors of cerebral presynaptic Na(+) channels. Here the effectiveness of these compounds to prevent the epileptiform EEG activity induced by 4-AP was compared with the effectiveness of seven conventional antiepileptic drugs. For this purpose, EEG recordings before and at three intervals within the next 30 min following 4-AP (2.5 mg/kg, i.p.) were taken in anesthetized animals; and the EEG-highest peak amplitude values (HPAV) calculated. In control animals, the marked increase in the EEG-HPAV observed near 20 min following 4-AP reached its maximum at 30 min. Results show that this epileptiform EEG activity induced by 4-AP is prevented by sertraline and vinpocetine at a dose of 2.5 mg/kg, and by carbamazepine, phenytoin, lamotrigine and oxcarbazepine at a higher dose (25 mg/kg). In contrast, topiramate (25 mg/kg), valproate (100 mg/kg) and levetiracetam (100 mg/kg) failed to prevent the epileptiform EEG activity induced by 4-AP. It is concluded that 4-AP is a useful tool to elicit the mechanism of action of anti-seizure drugs at clinical meaningful doses. The particular efficacy of sertraline and vinpocetine to prevent seizures induced by 4-AP is explained by their high effectiveness to reduce brain presynaptic Na(+) and Ca(2+) channels permeability.

Analyzing large data sets acquired through telemetry from rats exposed to organophosphorous compounds: an EEG study.

PubMed

de Araujo Furtado, Marcio; Zheng, Andy; Sedigh-Sarvestani, Madineh; Lumley, Lucille; Lichtenstein, Spencer; Yourick, Debra

2009-10-30

The organophosphorous compound soman is an acetylcholinesterase inhibitor that causes damage to the brain. Exposure to soman causes neuropathology as a result of prolonged and recurrent seizures. In the present study, long-term recordings of cortical EEG were used to develop an unbiased means to quantify measures of seizure activity in a large data set while excluding other signal types. Rats were implanted with telemetry transmitters and exposed to soman followed by treatment with therapeutics similar to those administered in the field after nerve agent exposure. EEG, activity and temperature were recorded continuously for a minimum of 2 days pre-exposure and 15 days post-exposure. A set of automatic MATLAB algorithms have been developed to remove artifacts and measure the characteristics of long-term EEG recordings. The algorithms use short-time Fourier transforms to compute the power spectrum of the signal for 2-s intervals. The spectrum is then divided into the delta, theta, alpha, and beta frequency bands. A linear fit to the power spectrum is used to distinguish normal EEG activity from artifacts and high amplitude spike wave activity. Changes in time spent in seizure over a prolonged period are a powerful indicator of the effects of novel therapeutics against seizures. A graphical user interface has been created that simultaneously plots the raw EEG in the time domain, the power spectrum, and the wavelet transform. Motor activity and temperature are associated with EEG changes. The accuracy of this algorithm is also verified against visual inspection of video recordings up to 3 days after exposure.

Evolution of genuine cross-correlation strength of focal onset seizures.

PubMed

Müller, Markus F; Baier, Gerold; Jiménez, Yurytzy López; Marín García, Arlex O; Rummel, Christian; Schindler, Kaspar

2011-10-01

To quantify the evolution of genuine zero-lag cross-correlations of focal onset seizures, we apply a recently introduced multivariate measure to broad band and to narrow-band EEG data. For frequency components below 12.5 Hz, the strength of genuine cross-correlations decreases significantly during the seizure and the immediate postseizure period, while higher frequency bands show a tendency of elevated cross-correlations during the same period. We conclude that in terms of genuine zero-lag cross-correlations, the electrical brain activity as assessed by scalp electrodes shows a significant spatial fragmentation, which might promote seizure offset.

Vector tomography for reconstructing electric fields with non-zero divergence in bounded domains

DOE Office of Scientific and Technical Information (OSTI.GOV)

Koulouri, Alexandra, E-mail: koulouri@uni-muenster.de; Department of Electrical and Electronic Engineering, Imperial College London, Exhibition Road, London SW7 2BT; Brookes, Mike

In vector tomography (VT), the aim is to reconstruct an unknown multi-dimensional vector field using line integral data. In the case of a 2-dimensional VT, two types of line integral data are usually required. These data correspond to integration of the parallel and perpendicular projection of the vector field along the integration lines and are called the longitudinal and transverse measurements, respectively. In most cases, however, the transverse measurements cannot be physically acquired. Therefore, the VT methods are typically used to reconstruct divergence-free (or source-free) velocity and flow fields that can be reconstructed solely from the longitudinal measurements. In thismore » paper, we show how vector fields with non-zero divergence in a bounded domain can also be reconstructed from the longitudinal measurements without the need of explicitly evaluating the transverse measurements. To the best of our knowledge, VT has not previously been used for this purpose. In particular, we study low-frequency, time-harmonic electric fields generated by dipole sources in convex bounded domains which arise, for example, in electroencephalography (EEG) source imaging. We explain in detail the theoretical background, the derivation of the electric field inverse problem and the numerical approximation of the line integrals. We show that fields with non-zero divergence can be reconstructed from the longitudinal measurements with the help of two sparsity constraints that are constructed from the transverse measurements and the vector Laplace operator. As a comparison to EEG source imaging, we note that VT does not require mathematical modeling of the sources. By numerical simulations, we show that the pattern of the electric field can be correctly estimated using VT and the location of the source activity can be determined accurately from the reconstructed magnitudes of the field. - Highlights: • Vector tomography is used to reconstruct electric fields generated by dipole sources. • Inverse solutions are based on longitudinal and transverse line integral measurements. • Transverse line integral measurements are used as a sparsity constraint. • Numerical procedure to approximate the line integrals is described in detail. • Patterns of the studied electric fields are correctly estimated.« less

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

PubMed

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

2017-01-01

Concurrent EEG and fMRI is increasingly used to characterize the spatial-temporal dynamics of brain activity. However, most studies to date have been limited to conventional echo-planar imaging (EPI). There is considerable interest in integrating recently developed high-speed fMRI methods with high-density EEG to increase temporal resolution and sensitivity for task-based and resting state fMRI, and for detecting interictal spikes in epilepsy. In the present study using concurrent high-density EEG and recently developed high-speed fMRI methods, we investigate safety of radiofrequency (RF) related heating, the effect of EEG on cortical signal-to-noise ratio (SNR) in fMRI, and assess EEG data quality. The study compared EPI, multi-echo EPI, multi-band EPI and multi-slab echo-volumar imaging pulse sequences, using clinical 3 Tesla MR scanners from two different vendors that were equipped with 64- and 256-channel MR-compatible EEG systems, respectively, and receive only array head coils. Data were collected in 11 healthy controls (3 males, age range 18-70 years) and 13 patients with epilepsy (8 males, age range 21-67 years). Three of the healthy controls were scanned with the 256-channel EEG system, the other subjects were scanned with the 64-channel EEG system. Scalp surface temperature, SNR in occipital cortex and head movement were measured with and without the EEG cap. The degree of artifacts and the ability to identify background activity was assessed by visual analysis by a trained expert in the 64 channel EEG data (7 healthy controls, 13 patients). RF induced heating at the surface of the EEG electrodes during a 30-minute scan period with stable temperature prior to scanning did not exceed 1.0° C with either EEG system and any of the pulse sequences used in this study. There was no significant decrease in cortical SNR due to the presence of the EEG cap (p > 0.05). No significant differences in the visually analyzed EEG data quality were found between EEG recorded during high-speed fMRI and during conventional EPI (p = 0.78). Residual ballistocardiographic artifacts resulted in 58% of EEG data being rated as poor quality. This study demonstrates that high-density EEG can be safely implemented in conjunction with high-speed fMRI and that high-speed fMRI does not adversely affect EEG data quality. However, the deterioration of the EEG quality due to residual ballistocardiographic artifacts remains a significant constraint for routine clinical applications of concurrent EEG-fMRI.

Video-EEG study of psychogenic nonepileptic seizures: differential characteristics in patients with and without epilepsy.

PubMed

Mari, Francesco; Di Bonaventura, Carlo; Vanacore, Nicola; Fattouch, Jinane; Vaudano, Anna Elisabetta; Egeo, Gabriella; Berardelli, Alfredo; Manfredi, Mario; Prencipe, Massimiliano; Giallonardo, Anna Teresa

2006-01-01

Psychogenic nonepileptic seizures (PNES) are episodes that may resemble epileptic seizures (ES) but are not associated with abnormal electrical discharges in the brain. Video-EEG recording of a typical episode is considered the best diagnostic tool available. PNES are, however, also documented in patients with epilepsy (PNES/ES). The purpose of this study was to assess this comorbid population, focusing on the differences between patients with PNES/ES and patients with PNES alone. We reviewed 110 PNES episodes, occurring spontaneously or induced by means of suggestion techniques, recorded in our video-EEG laboratory over a period of eight years. We identified two subgroups of patients, consisting of 85 PNES cases and 25 PNES/ES cases, and assessed any differences in their characteristics by reviewing a number of variables (age, sex, clinical features, antiepileptic therapy, age of onset, time to diagnosis, pathological history, and length of follow-up). The comparison between the two subgroups revealed that PNES/ES patients displayed some statistically significant differences when compared with PNES alone patients, i.e., younger age, a higher percentage of spontaneously activated events, a shorter disease duration, a longer time to PNES diagnosis, and a lower percentage lost at follow-up. This study confirms that PNES is a common, though probably underestimated, occurrence in epilepsy services. Our results shed light on some different characteristics between PNES and PNES/ES patients.

Dynamic Responses in Brain Networks to Social Feedback: A Dual EEG Acquisition Study in Adolescent Couples

PubMed Central

Kuo, Ching-Chang; Ha, Thao; Ebbert, Ashley M.; Tucker, Don M.; Dishion, Thomas J.

2017-01-01

Adolescence is a sensitive period for the development of romantic relationships. During this period the maturation of frontolimbic networks is particularly important for the capacity to regulate emotional experiences. In previous research, both functional magnetic resonance imaging (fMRI) and dense array electroencephalography (dEEG) measures have suggested that responses in limbic regions are enhanced in adolescents experiencing social rejection. In the present research, we examined social acceptance and rejection from romantic partners as they engaged in a Chatroom Interact Task. Dual 128-channel dEEG systems were used to record neural responses to acceptance and rejection from both adolescent romantic partners and unfamiliar peers (N = 75). We employed a two-step temporal principal component analysis (PCA) and spatial independent component analysis (ICA) approach to statistically identify the neural components related to social feedback. Results revealed that the early (288 ms) discrimination between acceptance and rejection reflected by the P3a component was significant for the romantic partner but not the unfamiliar peer. In contrast, the later (364 ms) P3b component discriminated between acceptance and rejection for both partners and peers. The two-step approach (PCA then ICA) was better able than either PCA or ICA alone in separating these components of the brain's electrical activity that reflected both temporal and spatial phases of the brain's processing of social feedback. PMID:28620292

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

PubMed Central

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

2017-01-01

Non-invasive transcranial brain stimulation (NTBS) techniques have a wide range of applications but also suffer from a number of limitations mainly related to poor specificity of intervention and variable effect size. These limitations motivated recent efforts to focus on the temporal dimension of NTBS with respect to the ongoing brain activity. Temporal patterns of ongoing neuronal activity, in particular brain oscillations and their fluctuations, can be traced with electro- or magnetoencephalography (EEG/MEG), to guide the timing as well as the stimulation settings of NTBS. These novel, online and offline EEG/MEG-guided NTBS-approaches are tailored to specifically interact with the underlying brain activity. Online EEG/MEG has been used to guide the timing of NTBS (i.e., when to stimulate): by taking into account instantaneous phase or power of oscillatory brain activity, NTBS can be aligned to fluctuations in excitability states. Moreover, offline EEG/MEG recordings prior to interventions can inform researchers and clinicians how to stimulate: by frequency-tuning NTBS to the oscillation of interest, intrinsic brain oscillations can be up- or down-regulated. In this paper, we provide an overview of existing approaches and ideas of EEG/MEG-guided interventions, and their promises and caveats. We point out potential future lines of research to address challenges. PMID:28233641

Cerebral mechanisms underlying the effects of music during a fatiguing isometric ankle-dorsiflexion task.

PubMed

Bigliassi, Marcelo; Karageorghis, Costas I; Nowicky, Alexander V; Orgs, Guido; Wright, Michael J

2016-10-01

The brain mechanisms by which music-related interventions ameliorate fatigue-related symptoms during the execution of fatiguing motor tasks are hitherto under-researched. The objective of the present study was to investigate the effects of music on brain electrical activity and psychophysiological measures during the execution of an isometric fatiguing ankle-dorsiflexion task performed until the point of volitional exhaustion. Nineteen healthy participants performed two fatigue tests at 40% of maximal voluntary contraction while listening to music or in silence. Electrical activity in the brain was assessed by use of a 64-channel EEG. The results indicated that music downregulated theta waves in the frontal, central, and parietal regions of the brain during exercise. Music also induced a partial attentional switching from associative thoughts to task-unrelated factors (dissociative thoughts) during exercise, which led to improvements in task performance. Moreover, participants experienced a more positive affective state while performing the isometric task under the influence of music. © 2016 Society for Psychophysiological Research.

EEGgui: a program used to detect electroencephalogram anomalies after traumatic brain injury.

PubMed

Sick, Justin; Bray, Eric; Bregy, Amade; Dietrich, W Dalton; Bramlett, Helen M; Sick, Thomas

2013-05-21

Identifying and quantifying pathological changes in brain electrical activity is important for investigations of brain injury and neurological disease. An example is the development of epilepsy, a secondary consequence of traumatic brain injury. While certain epileptiform events can be identified visually from electroencephalographic (EEG) or electrocorticographic (ECoG) records, quantification of these pathological events has proved to be more difficult. In this study we developed MATLAB-based software that would assist detection of pathological brain electrical activity following traumatic brain injury (TBI) and present our MATLAB code used for the analysis of the ECoG. Software was developed using MATLAB(™) and features of the open access EEGLAB. EEGgui is a graphical user interface in the MATLAB programming platform that allows scientists who are not proficient in computer programming to perform a number of elaborate analyses on ECoG signals. The different analyses include Power Spectral Density (PSD), Short Time Fourier analysis and Spectral Entropy (SE). ECoG records used for demonstration of this software were derived from rats that had undergone traumatic brain injury one year earlier. The software provided in this report provides a graphical user interface for displaying ECoG activity and calculating normalized power density using fast fourier transform of the major brain wave frequencies (Delta, Theta, Alpha, Beta1, Beta2 and Gamma). The software further detects events in which power density for these frequency bands exceeds normal ECoG by more than 4 standard deviations. We found that epileptic events could be identified and distinguished from a variety of ECoG phenomena associated with normal changes in behavior. We further found that analysis of spectral entropy was less effective in distinguishing epileptic from normal changes in ECoG activity. The software presented here was a successful modification of EEGLAB in the Matlab environment that allows detection of epileptiform ECoG signals in animals after TBI. The code allows import of large EEG or ECoG data records as standard text files and uses fast fourier transform as a basis for detection of abnormal events. The software can also be used to monitor injury-induced changes in spectral entropy if required. We hope that the software will be useful for other investigators in the field of traumatic brain injury and will stimulate future advances of quantitative analysis of brain electrical activity after neurological injury or disease.

Spatial and Temporal EEG-fMRI Changes During Preictal and Postictal Phases in a Patient With Posttraumatic Epilepsy.

PubMed

Storti, Silvia F; Del Felice, Alessandra; Formaggio, Emanuela; Boscolo Galazzo, Ilaria; Bongiovanni, Luigi G; Cerini, Roberto; Fiaschi, Antonio; Manganotti, Paolo

2015-07-01

The combined use of electroencephalography (EEG) and functional magnetic resonance imaging (EEG-fMRI) in epilepsy allows the noninvasive hemodynamic characterization of epileptic discharge-related neuronal activations. The aim of this study was to investigate pathophysiologic mechanisms underlying epileptic activity by exploring the spatial and temporal distribution of fMRI signal modifications during seizure in a single patient with posttraumatic epilepsy. EEG and fMRI data were acquired during two scanning sessions: a spontaneous critical episode was observed during the first, and interictal events were recorded during the second. The EEG-fMRI data were analyzed using the general linear model (GLM). Blood oxygenation level-dependent (BOLD) localization derived from the preictal and artifact-free postictal phase was concordant with the BOLD localization of the interictal epileptiform discharges identified in the second session, pointing to a left perilesional mesiofrontal area. Of note, BOLD signal modifications were already visible several seconds before seizure onset. In brief, BOLD activations from the preictal, postictal, and interictal epileptiform discharge analysis appear to be concordant with the clinically driven localization hypothesis, whereas a widespread network of activations is detected during the ictal phase in a partial seizure. © EEG and Clinical Neuroscience Society (ECNS) 2014.

EEG datasets for motor imagery brain-computer interface.

PubMed

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.

Content-specific coordination of listeners' to speakers' EEG during communication.

PubMed

Kuhlen, Anna K; Allefeld, Carsten; Haynes, John-Dylan

2012-01-01

Cognitive neuroscience has recently begun to extend its focus from the isolated individual mind to two or more individuals coordinating with each other. In this study we uncover a coordination of neural activity between the ongoing electroencephalogram (EEG) of two people-a person speaking and a person listening. The EEG of one set of twelve participants ("speakers") was recorded while they were narrating short stories. The EEG of another set of twelve participants ("listeners") was recorded while watching audiovisual recordings of these stories. Specifically, listeners watched the superimposed videos of two speakers simultaneously and were instructed to attend either to one or the other speaker. This allowed us to isolate neural coordination due to processing the communicated content from the effects of sensory input. We find several neural signatures of communication: First, the EEG is more similar among listeners attending to the same speaker than among listeners attending to different speakers, indicating that listeners' EEG reflects content-specific information. Secondly, listeners' EEG activity correlates with the attended speakers' EEG, peaking at a time delay of about 12.5 s. This correlation takes place not only between homologous, but also between non-homologous brain areas in speakers and listeners. A semantic analysis of the stories suggests that listeners coordinate with speakers at the level of complex semantic representations, so-called "situation models". With this study we link a coordination of neural activity between individuals directly to verbally communicated information.

Content-specific coordination of listeners' to speakers' EEG during communication

PubMed Central

Kuhlen, Anna K.; Allefeld, Carsten; Haynes, John-Dylan

2012-01-01

Cognitive neuroscience has recently begun to extend its focus from the isolated individual mind to two or more individuals coordinating with each other. In this study we uncover a coordination of neural activity between the ongoing electroencephalogram (EEG) of two people—a person speaking and a person listening. The EEG of one set of twelve participants (“speakers”) was recorded while they were narrating short stories. The EEG of another set of twelve participants (“listeners”) was recorded while watching audiovisual recordings of these stories. Specifically, listeners watched the superimposed videos of two speakers simultaneously and were instructed to attend either to one or the other speaker. This allowed us to isolate neural coordination due to processing the communicated content from the effects of sensory input. We find several neural signatures of communication: First, the EEG is more similar among listeners attending to the same speaker than among listeners attending to different speakers, indicating that listeners' EEG reflects content-specific information. Secondly, listeners' EEG activity correlates with the attended speakers' EEG, peaking at a time delay of about 12.5 s. This correlation takes place not only between homologous, but also between non-homologous brain areas in speakers and listeners. A semantic analysis of the stories suggests that listeners coordinate with speakers at the level of complex semantic representations, so-called “situation models”. With this study we link a coordination of neural activity between individuals directly to verbally communicated information. PMID:23060770

Frontal EEG Asymmetry and Temperament Across Infancy and Early Childhood: An Exploration of Stability and Bidirectional Relations

PubMed Central

Howarth, Grace Z.; Fettig, Nicole B.; Curby, Timothy W.; Bell, Martha Ann

2015-01-01

The stability of frontal electroencephalogram (EEG) asymmetry, temperamental activity level and fear, as well as bidirectional relations between asymmetry and temperament across the first four years of life were examined in a sample of 183 children. Children participated in annual lab visits through 48 months, providing EEG and maternal report of temperament. EEG asymmetry showed moderate stability between 10 and 24 months. Analyses revealed that more left asymmetry predicted later activity level across the first three years. Conversely, asymmetry did not predict fear. Rather, fear at 36 months predicted more right asymmetry at 48 months. Results highlight the need for additional longitudinal research of infants and children to increase understanding of bidirectional relations between EEG and temperament in typically developing populations. PMID:26659466

Monitoring task loading with multivariate EEG measures during complex forms of human-computer interaction

NASA Technical Reports Server (NTRS)

Smith, M. E.; Gevins, A.; Brown, H.; Karnik, A.; Du, R.

2001-01-01

Electroencephalographic (EEG) recordings were made while 16 participants performed versions of a personal-computer-based flight simulation task of low, moderate, or high difficulty. As task difficulty increased, frontal midline theta EEG activity increased and alpha band activity decreased. A participant-specific function that combined multiple EEG features to create a single load index was derived from a sample of each participant's data and then applied to new test data from that participant. Index values were computed for every 4 s of task data. Across participants, mean task load index values increased systematically with increasing task difficulty and differed significantly between the different task versions. Actual or potential applications of this research include the use of multivariate EEG-based methods to monitor task loading during naturalistic computer-based work.

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

PubMed Central

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

2015-01-01

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

Pulse Wave Amplitude Drops during Sleep are Reliable Surrogate Markers of Changes in Cortical Activity

PubMed Central

Delessert, Alexandre; Espa, Fabrice; Rossetti, Andrea; Lavigne, Gilles; Tafti, Mehdi; Heinzer, Raphael

2010-01-01

Background: During sleep, sudden drops in pulse wave amplitude (PWA) measured by pulse oximetry are commonly associated with simultaneous arousals and are thought to result from autonomic vasoconstriction. In the present study, we determine whether PWA drops were associated with changes in cortical activity as determined by EEG spectral analysis. Methods: A 20% decrease in PWA was chosen as a minimum for a drop. A total of 1085 PWA drops from 10 consecutive sleep recordings were analyzed. EEG spectral analysis was performed over 5 consecutive epochs of 5 seconds: 2 before, 1 during, and 2 after the PWA drop. EEG spectral analysis was performed over delta, theta, alpha, sigma, and beta frequency bands. Within each frequency band, power density was compared across the five 5-sec epochs. Presence or absence of visually scored EEG arousals were adjudicated by an investigator blinded to the PWA signal and considered associated with PWA drop if concomitant. Results: A significant increase in EEG power density in all EEG frequency bands was found during PWA drops (P < 0.001) compared to before and after drop. Even in the absence of visually scored arousals, PWA drops were associated with a significant increase in EEG power density (P < 0.001) in most frequency bands. Conclusions: Drops in PWA are associated with a significant increase in EEG power density, suggesting that these events can be used as a surrogate for changes in cortical activity during sleep. This approach may prove of value in scoring respiratory events on limited-channel (type III) portable monitors. Citation: Delessert A; Espa F; Rossetti A; Lavigne G; Tafti M; Heinzer R. Pulse wave amplitude drops during sleep are reliable surrogate markers of changes in cortical activity. SLEEP 2010;33(12):1687-1692. PMID:21120131

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

PubMed

Zhang, Shao-jie; Ke, Zheng; Li, Le; Yip, Shea-ping; Tong, Kai-yu

2013-04-01

Monitoring the neural activities from the ischemic penumbra provides critical information on neurological recovery after stroke. The purpose of this study is to evaluate the temporal alterations of neural activities using electroencephalography (EEG) from the acute phase to the chronic phase, and to compare EEG with the degree of post-stroke motor function recovery in a rat model of focal ischemic stroke. Male Sprague-Dawley rats were subjected to 90 min transient middle cerebral artery occlusion surgery followed by reperfusion for seven days (n = 58). The EEG signals were recorded at the pre-stroke phase (0 h), acute phase (3, 6 h), subacute phase (12, 24, 48, 72 h) and chronic phase (96, 120, 144, 168 h) (n = 8). This study analyzed post-stroke seizures and polymorphic delta activities (PDAs) and calculated quantitative EEG parameters such as the alpha-to-delta ratio (ADR). The ADR represented the ratio between alpha power and delta power, which indicated how fast the EEG activities were. Forelimb and hindlimb motor functions were measured by De Ryck's test and the beam walking test, respectively. In the acute phase, delta power increased fourfold with the occurrence of PDAs, and the histological staining showed that the infarct was limited to the striatum and secondary sensory cortex. In the subacute phase, the alpha power reduced to 50% of the baseline, and the infarct progressed to the forelimb cortical region. ADRs reduced from 0.23 ± 0.09 to 0.04 ± 0.01 at 3 h in the acute phase and gradually recovered to 0.22 ± 0.08 at 168 h in the chronic phase. In the comparison of correlations between the EEG parameters and the limb motor function from the acute phase to the chronic phase, ADRs were found to have the highest correlation coefficients with the beam walking test (r = 0.9524, p < 0.05) and De Ryck's test (r = 0.8077, p < 0.05). This study measured EEG activities after focal cerebral ischemia and showed that functional recovery was closely correlated with the neural activities in the penumbra. Longitudinal EEG monitoring at different phases after a stroke can provide information on the neural activities, which are well correlated with the motor function recovery.

Standards for data acquisition and software-based analysis of in vivo electroencephalography recordings from animals. A TASK1-WG5 report of the AES/ILAE Translational Task Force of the ILAE.

PubMed

Moyer, Jason T; Gnatkovsky, Vadym; Ono, Tomonori; Otáhal, Jakub; Wagenaar, Joost; Stacey, William C; Noebels, Jeffrey; Ikeda, Akio; Staley, Kevin; de Curtis, Marco; Litt, Brian; Galanopoulou, Aristea S

2017-11-01

Electroencephalography (EEG)-the direct recording of the electrical activity of populations of neurons-is a tremendously important tool for diagnosing, treating, and researching epilepsy. Although standard procedures for recording and analyzing human EEG exist and are broadly accepted, there are no such standards for research in animal models of seizures and epilepsy-recording montages, acquisition systems, and processing algorithms may differ substantially among investigators and laboratories. The lack of standard procedures for acquiring and analyzing EEG from animal models of epilepsy hinders the interpretation of experimental results and reduces the ability of the scientific community to efficiently translate new experimental findings into clinical practice. Accordingly, the intention of this report is twofold: (1) to review current techniques for the collection and software-based analysis of neural field recordings in animal models of epilepsy, and (2) to offer pertinent standards and reporting guidelines for this research. Specifically, we review current techniques for signal acquisition, signal conditioning, signal processing, data storage, and data sharing, and include applicable recommendations to standardize collection and reporting. We close with a discussion of challenges and future opportunities, and include a supplemental report of currently available acquisition systems and analysis tools. This work represents a collaboration on behalf of the American Epilepsy Society/International League Against Epilepsy (AES/ILAE) Translational Task Force (TASK1-Workgroup 5), and is part of a larger effort to harmonize video-EEG interpretation and analysis methods across studies using in vivo and in vitro seizure and epilepsy models. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Spatio-temporal coupling of EEG signals in epilepsy

NASA Astrophysics Data System (ADS)

Senger, Vanessa; Müller, Jens; Tetzlaff, Ronald

2011-05-01

Approximately 1% of the world's population suffer from epileptic seizures throughout their lives that mostly come without sign or warning. Thus, epilepsy is the most common chronical disorder of the neurological system. In the past decades, the problem of detecting a pre-seizure state in epilepsy using EEG signals has been addressed in many contributions by various authors over the past two decades. Up to now, the goal of identifying an impending epileptic seizure with sufficient specificity and reliability has not yet been achieved. Cellular Nonlinear Networks (CNN) are characterized by local couplings of dynamical systems of comparably low complexity. Thus, they are well suited for an implementation as highly parallel analogue processors. Programmable sensor-processor realizations of CNN combine high computational power comparable to tera ops of digital processors with low power consumption. An algorithm allowing an automated and reliable detection of epileptic seizure precursors would be a"huge step" towards the vision of an implantable seizure warning device that could provide information to patients and for a time/event specific treatment directly in the brain. Recent contributions have shown that modeling of brain electrical activity by solutions of Reaction-Diffusion-CNN as well as the application of a CNN predictor taking into account values of neighboring electrodes may contribute to the realization of a seizure warning device. In this paper, a CNN based predictor corresponding to a spatio-temporal filter is applied to multi channel EEG data in order to identify mutual couplings for different channels which lead to a enhanced prediction quality. Long term EEG recordings of different patients are considered. Results calculated for these recordings with inter-ictal phases as well as phases with seizures will be discussed in detail.

Specificity of spontaneous EEG associated with different levels of cognitive and communicative dysfunctions in children.

PubMed

Kozhushko, Nadezhda Ju; Nagornova, Zhanna V; Evdokimov, Sergey A; Shemyakina, Natalia V; Ponomarev, Valery A; Tereshchenko, Ekaterina P; Kropotov, Jury D

2018-06-01

This study aimed to reveal electrophysiological markers of communicative and cognitive dysfunctions of different severity in children with autism spectrum disorder (ASD). Eyes-opened electroencephalograms (EEGs) of 42 children with ASD, divided into two groups according to the severity of their communicative and cognitive dysfunctions (24 with severe and 18 children with less severe ASD), and 70 age-matched controls aged 4-9 years were examined by means of spectral and group independent component (gIC) analyses. A predominance of theta and beta EEG activity in both groups of children with ASD compared to the activity in the control group was found in the global gIC together with a predominance of beta EEG activity in the right occipital region. The quantity of local gICs with enhanced slow and high-frequency EEG activity (within the frontal, temporal, and parietal cortex areas) in children 4-9 years of age might be considered a marker of cognitive and communicative dysfunction severity. Copyright © 2018 Elsevier B.V. All rights reserved.

Prognostic value of electroencephalography (EEG) after out-of-hospital cardiac arrest in successfully resuscitated patients used in daily clinical practice.

PubMed

Søholm, Helle; Kjær, Troels Wesenberg; Kjaergaard, Jesper; Cronberg, Tobias; Bro-Jeppesen, John; Lippert, Freddy K; Køber, Lars; Wanscher, Michael; Hassager, Christian

2014-11-01

Out-of-hospital cardiac arrest (OHCA) is associated with a poor prognosis and predicting outcome is complex with neurophysiological testing and repeated clinical neurological examinations as key components of the assessment. In this study we examine the association between different electroencephalography (EEG) patterns and mortality in a clinical cohort of OHCA-patients. From 2002 to 2011 consecutive patients were admitted to an intensive-care-unit after resuscitation from OHCA. Utstein-criteria for pre-hospital data and review of individual patients' charts for post-resuscitation care were used. EEG reports were analysed according to the 2012 American Clinical Neurophysiology Society's guidelines. A total of 1076 patients were included, and EEG was performed in 20% (n=219) with a median of 3(IQR 2-4) days after OHCA. Rhythmic Delta Activity (RDA) was found in 71 patients (36%) and Periodic Discharges (PD) in 100 patients (45%). Background EEG frequency of Alpha+ or Theta was noted in 107 patients (49%), and change in cerebral EEG activity to stimulation (reactivity) was found in 38 patients (17%). Suppression (all activity <10 μV) was found in 26 (12%) and burst-suppression in 17 (8%) patients. A favourable EEG pattern (reactivity, favourable background frequency and RDA) was independently associated with reduced mortality with hazard ratio (HR) 0.43 (95%CI: 0.24-0.76), p=0.004 (false positive rate: 31%) and a non-favourable EEG pattern (no reactivity, unfavourable background frequency, and PD, suppressed voltage or burst-suppression) was associated with higher mortality (HR=1.62(1.09-2.41), p=0.02) after adjustment for known prognostic factors (false positive rate: 9%). EEG may be useful in work-up in prognostication of patients with OHCA. Findings such as Rhythmic Delta Activity (RDA) seem to be associated with a better prognosis, whereas suppressed voltage and burst-suppression patterns were associated with poor prognosis. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Effect of bright light on EEG activities and subjective sleepiness to mental task during nocturnal sleep deprivation.

PubMed

Yokoi, Mari; Aoki, Ken; Shimomura, Yoshihiro; Iwanaga, Koichi; Katsuura, Tetsuo; Shiomura, Yoshihiro

2003-11-01

The purpose of this study was to investigate the effect of the exposure to bright light on EEG activity and subjective sleepiness at rest and at the mental task during nocturnal sleep deprivation. Eight male subjects lay awake in semi-supine in a reclining seat from 21:00 to 04:30 under the bright (BL; >2500 lux) or the dim (DL; <150 lux) light conditions. During the sleep deprivation, the mental task (Stroop color-word conflict test: CWT) was performed each 15 min in one hour. EEG, subjective sleepiness, rectal and mean skin temperatures and urinary melatonin concentrations were measured. The subjective sleepiness increased with time of sleep deprivation during both rest and CWT under the DL condition. The exposure to bright light delayed for 2 hours the increase in subjective sleepiness at rest and suppressed the increase in that during CWT. The bright light exposure also delayed the increase in the theta and alpha wave activities in EEG at rest. In contrast, the effect of the bright light exposure on the theta and alpha wave activities disappeared by CWT. Additionally, under the BL condition, the entire theta activity during CWT throughout nocturnal sleep deprivation increased significantly from that in a rest condition. Our results suggest that the exposure to bright light throughout nocturnal sleep deprivation influences the subjective sleepiness during the mental task and the EEG activity, as well as the subjective sleepiness at rest. However, the effect of the bright light exposure on the EEG activity at the mental task diminishes throughout nocturnal sleep deprivation.

Emotion and resilience: a multilevel investigation of hemispheric electroencephalogram asymmetry and emotion regulation in maltreated and nonmaltreated children.

PubMed

Curtis, W John; Cicchetti, Dante

2007-01-01

The current study was a multilevel investigation of resilience, emotion regulation, and hemispheric electroencephalogram (EEG) asymmetry in a sample of maltreated and nonmaltreated school age children. It was predicted that the positive emotionality and increased emotion regulatory ability associated with resilient functioning would be associated with relatively greater left frontal EEG activity. The study also investigated differences in pathways to resilience between maltreated and nonmaltreated children. The findings indicated that EEG asymmetry across central cortical regions distinguished between resilient and nonresilient children, with greater left hemisphere activity characterizing those who were resilient. In addition, nonmaltreated children showed greater left hemisphere EEG activity across parietal cortical regions. There was also a significant interaction between resilience, maltreatment status, and gender for asymmetry at anterior frontal electrodes, where nonmaltreated resilient females had greater relative left frontal activity compared to more right frontal activity exhibited by resilient maltreated females. An observational measure of emotion regulation significantly contributed to the prediction of resilience in the maltreated and nonmaltreated children, but EEG asymmetry in central cortical regions independently predicted resilience only in the maltreated group. The findings are discussed in terms of their meaning for the development of resilient functioning.

Brain electric microstates and momentary conscious mind states as building blocks of spontaneous thinking: I. Visual imagery and abstract thoughts.

PubMed

Lehmann, D; Strik, W K; Henggeler, B; Koenig, T; Koukkou, M

1998-06-01

Prompted reports of recall of spontaneous, conscious experiences were collected in a no-input, no-task, no-response paradigm (30 random prompts to each of 13 healthy volunteers). The mentation reports were classified into visual imagery and abstract thought. Spontaneous 19-channel brain electric activity (EEG) was continuously recorded, viewed as series of momentary spatial distributions (maps) of the brain electric field and segmented into microstates, i.e. into time segments characterized by quasi-stable landscapes of potential distribution maps which showed varying durations in the sub-second range. Microstate segmentation used a data-driven strategy. Different microstates, i.e. different brain electric landscapes must have been generated by activity of different neural assemblies and therefore are hypothesized to constitute different functions. The two types of reported experiences were associated with significantly different microstates (mean duration 121 ms) immediately preceding the prompts; these microstates showed, across subjects, for abstract thought (compared to visual imagery) a shift of the electric gravity center to the left and a clockwise rotation of the field axis. Contrariwise, the microstates 2 s before the prompt did not differ between the two types of experiences. The results support the hypothesis that different microstates of the brain as recognized in its electric field implement different conscious, reportable mind states, i.e. different classes (types) of thoughts (mentations); thus, the microstates might be candidates for the 'atoms of thought'.

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

PubMed

Zebende, Gilney Figueira; Oliveira Filho, Florêncio Mendes; Leyva Cruz, Juan Alberto

2017-01-01

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

Cerebral cortical neurons with activity linked to central neurogenic spontaneous and evoked elevations in cerebral blood flow

NASA Technical Reports Server (NTRS)

Golanov, E. V.; Reis, D. J.

1996-01-01

We recorded neurons in rat cerebral cortex with activity relating to the neurogenic elevations in regional cerebral blood flow (rCBF) coupled to stereotyped bursts of EEG activity, burst-cerebrovascular wave complexes, appearing spontaneously or evoked by electrical stimulation of rostral ventrolateral medulla (RVL) or fastigial nucleus (FN). Of 333 spontaneously active neurons only 15 (5%), in layers 5-6, consistently (P < 0.05, chi-square) increased their activity during the earliest potential of the complex, approximately 1.3 s before the rise of rCBF, and during the minutes-long elevation of rCBF elicited by 10 s of stimulation of RVL or FN. The results indicate the presence of a small population of neurons in deep cortical laminae whose activity correlates with neurogenic elevations of rCBF. These neurons may function to transduce afferent neuronal signals into vasodilation.

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

PubMed

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.

Willing to wait: Elevated reward-processing EEG activity associated with a greater preference for larger-but-delayed rewards.

PubMed

Pornpattananangkul, Narun; Nusslock, Robin

2016-10-01

While almost everyone discounts the value of future rewards over immediate rewards, people differ in their so-called delay-discounting. One of the several factors that may explain individual differences in delay-discounting is reward-processing. To study individual-differences in reward-processing, however, one needs to consider the heterogeneity of neural-activity at each reward-processing stage. Here using EEG, we separated reward-related neural activity into distinct reward-anticipation and reward-outcome stages using time-frequency characteristics. Thirty-seven individuals first completed a behavioral delay-discounting task. Then reward-processing EEG activity was assessed using a separate reward-learning task, called a reward time-estimation task. During this EEG task, participants were instructed to estimate time duration and were provided performance feedback on a trial-by-trial basis. Participants received monetary-reward for accurate-performance on Reward trials, but not on No-Reward trials. Reward trials, relative to No-Reward trials, enhanced EEG activity during both reward-anticipation (including, cued-locked delta power during cue-evaluation and pre-feedback alpha suppression during feedback-anticipation) and reward-outcome (including, feedback-locked delta, theta and beta power) stages. Moreover, all of these EEG indices correlated with behavioral performance in the time-estimation task, suggesting their essential roles in learning and adjusting performance to maximize winnings in a reward-learning situation. Importantly, enhanced EEG power during Reward trials, as reflected by stronger 1) pre-feedback alpha suppression, 2) feedback-locked theta and 3) feedback-locked beta, was associated with a greater preference for larger-but-delayed rewards in a separate, behavioral delay-discounting task. Results highlight the association between a stronger preference toward larger-but-delayed rewards and enhanced reward-processing. Moreover, our reward-processing EEG indices detail the specific stages of reward-processing where these associations occur. Copyright © 2016 Elsevier Ltd. All rights reserved.

Does power mobility training impact a child's mastery motivation and spectrum of EEG activity? An exploratory project.

PubMed

Kenyon, Lisa K; Farris, John P; Aldrich, Naomi J; Rhodes, Samhita

2017-08-30

The purposes of this exploratory project were: (1) to evaluate the impact of power mobility training with a child who has multiple, severe impairments and (2) to determine if the child's spectrum of electroencephalography (EEG) activity changed during power mobility training. A single-subject A-B-A-B research design was conducted with a four-week duration for each phase. Two target behaviours were explored: (1) mastery motivation assessed via the dimensions of mastery questionnaire (DMQ) and (2) EEG data collected under various conditions. Power mobility skills were also assessed. The participant was a three-year, two-month-old girl with spastic quadriplegic cerebral palsy, gross motor function classification system level V. Each target behaviour was measured weekly. During intervention phases, power mobility training was provided. Improvements were noted in subscale scores of the DMQ. Short-term and long-term EEG changes were also noted. Improvements were noted in power mobility skills. The participant in this exploratory project demonstrated improvements in power mobility skill and function. EEG data collection procedures and variability in an individual's EEG activity make it difficult to determine if the participant's spectrum of EEG activity actually changed in response to power mobility training. Additional studies are needed to investigate the impact of power mobility training on the spectrum of EEG activity in children who have multiple, severe impairments. Implications for Rehabilitation Power mobility training appeared to be beneficial for a child with multiple, severe impairments though the child may never become an independent, community-based power wheelchair user. Electroencephalography may be a valuable addition to the study of power mobility use in children with multiple, severe impairments. Power mobility training appeared to impact mastery motivation (the internal drive to solve complex problems and master new skills) in a child who has multiple, severe impairments.

A Vehicle Active Safety Model: Vehicle Speed Control Based on Driver Vigilance Detection Using Wearable EEG and Sparse Representation.

PubMed

Zhang, Zutao; Luo, Dianyuan; Rasim, Yagubov; Li, Yanjun; Meng, Guanjun; Xu, Jian; Wang, Chunbai

2016-02-19

In this paper, we present a vehicle active safety model for vehicle speed control based on driver vigilance detection using low-cost, comfortable, wearable electroencephalographic (EEG) sensors and sparse representation. The proposed system consists of three main steps, namely wireless wearable EEG collection, driver vigilance detection, and vehicle speed control strategy. First of all, a homemade low-cost comfortable wearable brain-computer interface (BCI) system with eight channels is designed for collecting the driver's EEG signal. Second, wavelet de-noising and down-sample algorithms are utilized to enhance the quality of EEG data, and Fast Fourier Transformation (FFT) is adopted to extract the EEG power spectrum density (PSD). In this step, sparse representation classification combined with k-singular value decomposition (KSVD) is firstly introduced in PSD to estimate the driver's vigilance level. Finally, a novel safety strategy of vehicle speed control, which controls the electronic throttle opening and automatic braking after driver fatigue detection using the above method, is presented to avoid serious collisions and traffic accidents. The simulation and practical testing results demonstrate the feasibility of the vehicle active safety model.

A Vehicle Active Safety Model: Vehicle Speed Control Based on Driver Vigilance Detection Using Wearable EEG and Sparse Representation

PubMed Central

Zhang, Zutao; Luo, Dianyuan; Rasim, Yagubov; Li, Yanjun; Meng, Guanjun; Xu, Jian; Wang, Chunbai

2016-01-01

In this paper, we present a vehicle active safety model for vehicle speed control based on driver vigilance detection using low-cost, comfortable, wearable electroencephalographic (EEG) sensors and sparse representation. The proposed system consists of three main steps, namely wireless wearable EEG collection, driver vigilance detection, and vehicle speed control strategy. First of all, a homemade low-cost comfortable wearable brain-computer interface (BCI) system with eight channels is designed for collecting the driver’s EEG signal. Second, wavelet de-noising and down-sample algorithms are utilized to enhance the quality of EEG data, and Fast Fourier Transformation (FFT) is adopted to extract the EEG power spectrum density (PSD). In this step, sparse representation classification combined with k-singular value decomposition (KSVD) is firstly introduced in PSD to estimate the driver’s vigilance level . Finally, a novel safety strategy of vehicle speed control, which controls the electronic throttle opening and automatic braking after driver fatigue detection using the above method, is presented to avoid serious collisions and traffic accidents. The simulation and practical testing results demonstrate the feasibility of the vehicle active safety model. PMID:26907278

Hybrid EEG--Eye Tracker: Automatic Identification and Removal of Eye Movement and Blink Artifacts from Electroencephalographic Signal.

PubMed

Mannan, Malik M Naeem; Kim, Shinjung; Jeong, Myung Yung; Kamran, M Ahmad

2016-02-19

Contamination of eye movement and blink artifacts in Electroencephalogram (EEG) recording makes the analysis of EEG data more difficult and could result in mislead findings. Efficient removal of these artifacts from EEG data is an essential step in improving classification accuracy to develop the brain-computer interface (BCI). In this paper, we proposed an automatic framework based on independent component analysis (ICA) and system identification to identify and remove ocular artifacts from EEG data by using hybrid EEG and eye tracker system. The performance of the proposed algorithm is illustrated using experimental and standard EEG datasets. The proposed algorithm not only removes the ocular artifacts from artifactual zone but also preserves the neuronal activity related EEG signals in non-artifactual zone. The comparison with the two state-of-the-art techniques namely ADJUST based ICA and REGICA reveals the significant improved performance of the proposed algorithm for removing eye movement and blink artifacts from EEG data. Additionally, results demonstrate that the proposed algorithm can achieve lower relative error and higher mutual information values between corrected EEG and artifact-free EEG data.

Evaluation of Dry Sensors for Neonatal EEG Recordings.

PubMed

Fridman, Igor; Cordeiro, Malaika; Rais-Bahrami, Khodayar; McDonald, Neil J; Reese, James J; Massaro, An N; Conry, Joan A; Chang, Taeun; Soussou, Walid; Tsuchida, Tammy N

2016-04-01

Neonatal seizures are a common neurologic diagnosis in neonatal intensive care units, occurring in approximately 14,000 newborns annually in the United States. Although the only reliable means of detecting and treating neonatal seizures is with an electroencephalography (EEG) recording, many neonates do not receive an EEG or experience delays in getting them. Barriers to obtaining neonatal EEGs include (1) lack of skilled EEG technologists to apply conventional wet electrodes to delicate neonatal skin, (2) poor signal quality because of improper skin preparation and artifact, and (3) extensive time needed to apply electrodes. Dry sensors have the potential to overcome these obstacles but have not previously been evaluated on neonates. Sequential and simultaneous recordings with wet and dry sensors were performed for 1 hour on 27 neonates from 35 to 42.5 weeks postmenstrual age. Recordings were analyzed for correlation and amplitude and were reviewed by neurophysiologists. Performance of dry sensors on simulated vernix was examined. Analysis of dry and wet signals showed good time-domain correlation (reaching >0.8), given the nonsuperimposed sensor positions and similar power spectral density curves. Neurophysiologist reviews showed no statistically significant difference between dry and wet data on most clinically relevant EEG background and seizure patterns. There was no skin injury after 1 hour of dry sensor recordings. In contrast to wet electrodes, impedance and electrical artifact of dry sensors were largely unaffected by simulated vernix. Dry sensors evaluated in this study have the potential to provide high-quality, timely EEG recordings on neonates with less risk of skin injury.

Evaluation of Dry Sensors for Neonatal EEG recordings

PubMed Central

Fridman, Igor; Cordeiro, Malaika; Rais-Bahrami, Khodayar; McDonald, Neil J.; Reese, James J.; Massaro, An N.; Conry, Joan A.; Chang, Taeun; Soussou, Walid; Tsuchida, Tammy N.

2015-01-01

Introduction Neonatal seizures are a common neurologic diagnosis in Neonatal Intensive Care Units (NICUs), occurring in approximately 14,000 newborns annually in the US. While the only reliable means of detecting and treating neonatal seizures is with an EEG recording, many neonates do not get an EEG or experience delays in getting them. Barriers to obtaining neonatal EEGs include: 1) lack of skilled EEG technologists to apply conventional wet electrodes to delicate neonatal skin, 2) poor signal quality due to improper skin preparation and artifact, 3) extensive time needed to apply electrodes. Dry sensors have the potential to overcome these obstacles but have not been previously evaluated on neonates. Methods Sequential and simultaneous recordings with wet and dry sensors were performed for one hour on 27 neonates from 35-42.5 weeks postmenstrual age. Recordings were analyzed for correlation and amplitude, and were reviewed by neurophysiologists. Performance of dry sensors on simulated vernix was examined. Results Analysis of dry and wet signals showed good time-domain correlation (reaching >0.8) given the non-superimposed sensor positions, and similar power spectral density curves. Neurophysiologist reviews showed no statistically significant difference between dry and wet data on most clinically-relevant EEG background and seizure patterns. There was no skin injury after 1 hr of dry sensor recordings. In contrast to wet electrodes, impedance and electrical artifact of dry sensors were largely unaffected by simulated vernix. Conclusions Dry sensors evaluated in this study have the potential to provide high-quality, timely EEG recordings on neonates with less risk of skin injury. PMID:26562208

EEG-based emotion recognition in music listening.

PubMed

Lin, Yuan-Pin; Wang, Chi-Hong; Jung, Tzyy-Ping; Wu, Tien-Lin; Jeng, Shyh-Kang; Duann, Jeng-Ren; Chen, Jyh-Horng

2010-07-01

Ongoing brain activity can be recorded as electroencephalograph (EEG) to discover the links between emotional states and brain activity. This study applied machine-learning algorithms to categorize EEG dynamics according to subject self-reported emotional states during music listening. A framework was proposed to optimize EEG-based emotion recognition by systematically 1) seeking emotion-specific EEG features and 2) exploring the efficacy of the classifiers. Support vector machine was employed to classify four emotional states (joy, anger, sadness, and pleasure) and obtained an averaged classification accuracy of 82.29% +/- 3.06% across 26 subjects. Further, this study identified 30 subject-independent features that were most relevant to emotional processing across subjects and explored the feasibility of using fewer electrodes to characterize the EEG dynamics during music listening. The identified features were primarily derived from electrodes placed near the frontal and the parietal lobes, consistent with many of the findings in the literature. This study might lead to a practical system for noninvasive assessment of the emotional states in practical or clinical applications.

Quantitative EEG analysis of the maturational changes associated with childhood absence epilepsy

NASA Astrophysics Data System (ADS)

Rosso, O. A.; Hyslop, W.; Gerlach, R.; Smith, R. L. L.; Rostas, J. A. P.; Hunter, M.

2005-10-01

This study aimed to examine the background electroencephalography (EEG) in children with childhood absence epilepsy, a condition whose presentation has strong developmental links. EEG hallmarks of absence seizure activity are widely accepted and there is recognition that the bulk of inter-ictal EEG in this group is normal to the naked eye. This multidisciplinary study aimed to use the normalized total wavelet entropy (NTWS) (Signal Processing 83 (2003) 1275) to examine the background EEG of those patients demonstrating absence seizure activity, and compare it with children without absence epilepsy. This calculation can be used to define the degree of order in a system, with higher levels of entropy indicating a more disordered (chaotic) system. Results were subjected to further statistical analyses of significance. Entropy values were calculated for patients versus controls. For all channels combined, patients with absence epilepsy showed (statistically significant) lower entropy values than controls. The size of the difference in entropy values was not uniform, with certain EEG electrodes consistently showing greater differences than others.

Role of EEG background activity, seizure burden and MRI in predicting neurodevelopmental outcome in full-term infants with hypoxic-ischaemic encephalopathy in the era of therapeutic hypothermia.

PubMed

Weeke, Lauren C; Boylan, Geraldine B; Pressler, Ronit M; Hallberg, Boubou; Blennow, Mats; Toet, Mona C; Groenendaal, Floris; de Vries, Linda S

2016-11-01

To investigate the role of EEG background activity, electrographic seizure burden, and MRI in predicting neurodevelopmental outcome in infants with hypoxic-ischaemic encephalopathy (HIE) in the era of therapeutic hypothermia. Twenty-six full-term infants with HIE (September 2011-September 2012), who had video-EEG monitoring during the first 72 h, an MRI performed within the first two weeks and neurodevelopmental assessment at two years were evaluated. EEG background activity at age 24, 36 and 48 h, seizure burden, and severity of brain injury on MRI, were compared and related to neurodevelopmental outcome. EEG background activity was significantly associated with neurodevelopmental outcome at 36 h (p = 0.009) and 48 h after birth (p = 0.029) and with severity of brain injury on MRI at 36 h (p = 0.002) and 48 h (p = 0.018). All infants with a high seizure burden and moderate-severe injury on MRI had an abnormal outcome. The positive predictive value (PPV) of EEG for abnormal outcome was 100% at 36 h and 48 h and the negative predictive value (NPV) was 75% at 36 h and 69% at 48 h. The PPV of MRI was 100% and the NPV 85%. The PPV of seizure burden was 78% and the NPV 71%. Severely abnormal EEG background activity at 36 h and 48 h after birth was associated with severe injury on MRI and abnormal neurodevelopmental outcome. High seizure burden was only associated with abnormal outcome in combination with moderate-severe injury on MRI. Copyright © 2016 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.

Willing to Wait: Elevated Reward-Processing EEG Activity Associated with a Greater Preference for Larger-But-Delayed Rewards

PubMed Central

Pornpattananangkul, Narun; Nusslock, Robin

2016-01-01

While almost everyone discounts the value of future rewards over immediate rewards, people differ in their so-called delay-discounting. One of the several factors that may explain individual differences in delay-discounting is reward-processing. To study individual-differences in reward-processing, however, one needs to consider the heterogeneity of neural-activity at each reward-processing stage. Here using EEG, we separated reward-related neural activity into distinct reward-anticipation and reward-outcome stages using time-frequency characteristics. Thirty-seven individuals completed a behavioral delay-discounting task. Reward-processing EEG activity was assessed using a separate reward-learning task, called a reward time-estimation task. During this task, participants were instructed to estimate time duration and were provided performance feedback on a trial-by-trial basis. Participants received monetary-reward for accurate-performance on Reward trials, but not on No-Reward trials. Reward trials, relative to No-Reward trials, enhanced EEG activity during both reward-anticipation stage (including, cued-locked delta power during cue-evaluation and pre-feedback alpha suppression during feedback-anticipation) and at the reward-outcome stage (including, feedback-locked delta, theta and beta power). Moreover, all of these EEG indices correlated with behavioral performance in the time-estimation task, suggesting their essential roles in learning and adjusting performance to maximize winnings in a reward-learning situation. Importantly, enhanced EEG power during Reward trials for 1) pre-feedback alpha suppression, 2) feedback-locked theta and 3) feedback-locked beta was associated with a greater preference for larger-but-delayed rewards. Results highlight the association between a stronger preference toward larger-but-delayed rewards and enhanced reward-processing. Moreover, our reward-processing EEG indices detail the specific stages of reward-processing where these associations occur. PMID:27477630