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.

Phase Synchronization in Electroencephalographic Recordings Prognosticates Outcome in Paediatric Coma

PubMed Central

Nenadovic, Vera; Perez Velazquez, Jose Luis; Hutchison, James Saunders

2014-01-01

Brain injury from trauma, cardiac arrest or stroke is the most important cause of death and acquired disability in the paediatric population. Due to the lifetime impact of brain injury, there is a need for methods to stratify patient risk and ultimately predict outcome. Early prognosis is fundamental to the implementation of interventions to improve recovery, but no clinical model as yet exists. Healthy physiology is associated with a relative high variability of physiologic signals in organ systems. This was first evaluated in heart rate variability research. Brain variability can be quantified through electroencephalographic (EEG) phase synchrony. We hypothesised that variability in brain signals from EEG recordings would correlate with patient outcome after brain injury. Lower variability in EEG phase synchronization, would be associated with poor patient prognosis. A retrospective study, spanning 10 years (2000–2010) analysed the scalp EEGs of children aged 1 month to 17 years in coma (Glasgow Coma Scale, GCS, <8) admitted to the paediatric critical care unit (PCCU) following brain injury from TBI, cardiac arrest or stroke. Phase synchrony of the EEGs was evaluated using the Hilbert transform and the variability of the phase synchrony calculated. Outcome was evaluated using the 6 point Paediatric Performance Category Score (PCPC) based on chart review at the time of hospital discharge. Outcome was dichotomized to good outcome (PCPC score 1 to 3) and poor outcome (PCPC score 4 to 6). Children who had a poor outcome following brain injury secondary to cardiac arrest, TBI or stroke, had a higher magnitude of synchrony (R index), a lower spatial complexity of the synchrony patterns and a lower temporal variability of the synchrony index values at 15 Hz when compared to those patients with a good outcome. PMID:24752289

On a Possible Relationship between Linguistic Expertise and EEG Gamma Band Phase Synchrony

PubMed Central

Reiterer, Susanne; Pereda, Ernesto; Bhattacharya, Joydeep

2011-01-01

Recent research has shown that extensive training in and exposure to a second language can modify the language organization in the brain by causing both structural and functional changes. However it is not yet known how these changes are manifested by the dynamic brain oscillations and synchronization patterns subserving the language networks. In search for synchronization correlates of proficiency and expertise in second language acquisition, multivariate EEG signals were recorded from 44 high and low proficiency bilinguals during processing of natural language in their first and second languages. Gamma band (30–45 Hz) phase synchronization (PS) was calculated mainly by two recently developed methods: coarse-graining of Markov chains (estimating global phase synchrony, measuring the degree of PS between one electrode and all other electrodes), and phase lag index (PLI; estimating bivariate phase synchrony, measuring the degree of PS between a pair of electrodes). On comparing second versus first language processing, global PS by coarse-graining Markov chains indicated that processing of the second language needs significantly higher synchronization strength than first language. On comparing the proficiency groups, bivariate PS measure (i.e., PLI) revealed that during second language processing the low proficiency group showed stronger and broader network patterns than the high proficiency group, with interconnectivities between a left fronto-parietal network. Mean phase coherence analysis also indicated that the network activity was globally stronger in the low proficiency group during second language processing. PMID:22125542

Hierarchical organization of brain functional networks during visual tasks.

PubMed

Zhuo, Zhao; Cai, Shi-Min; Fu, Zhong-Qian; Zhang, Jie

2011-09-01

The functional network of the brain is known to demonstrate modular structure over different hierarchical scales. In this paper, we systematically investigated the hierarchical modular organizations of the brain functional networks that are derived from the extent of phase synchronization among high-resolution EEG time series during a visual task. In particular, we compare the modular structure of the functional network from EEG channels with that of the anatomical parcellation of the brain cortex. Our results show that the modular architectures of brain functional networks correspond well to those from the anatomical structures over different levels of hierarchy. Most importantly, we find that the consistency between the modular structures of the functional network and the anatomical network becomes more pronounced in terms of vision, sensory, vision-temporal, motor cortices during the visual task, which implies that the strong modularity in these areas forms the functional basis for the visual task. The structure-function relationship further reveals that the phase synchronization of EEG time series in the same anatomical group is much stronger than that of EEG time series from different anatomical groups during the task and that the hierarchical organization of functional brain network may be a consequence of functional segmentation of the brain cortex.

Heightened Background Cortical Synchrony in Patients With Epilepsy: EEG Phase Synchrony Analysis During Awake and Sleep Stages Using Novel Ensemble Measure.

PubMed

Nayak, Chetan S; Mariyappa, N; Majumdar, Kaushik K; Prasad, Pradeep D; Ravi, G S; Nagappa, M; Kandavel, Thennarasu; Taly, Arun B; Sinha, Sanjib

2018-05-01

Excessive cortical synchrony within neural ensembles has been implicated as an important mechanism driving epileptiform activity. The current study measures and compares background electroencephalographic (EEG) phase synchronization in patients having various types of epilepsies and healthy controls during awake and sleep stages. A total of 120 patients with epilepsy (PWE) subdivided into 3 groups (juvenile myoclonic epilepsy [JME], temporal lobe epilepsy [TLE], and extra-temporal lobe epilepsy [Ex-TLE]; n = 40 in each group) and 40 healthy controls were subjected to overnight polysomnography. EEG phase synchronization (SI) between the 8 EEG channels was assessed for delta, theta, alpha, sigma, and high beta frequency bands using ensemble measure on 10-second representative time windows and compared between patients and controls and also between awake and sleep stages. Mean ± SD of SI was compared using 2-way analysis of variance followed by pairwise comparison ( P ≤ .05). In both delta and theta bands, the SI was significantly higher in patients with JME, TLE, and Ex-TLE compared with controls, whereas in alpha, sigma, and high beta bands, SI was comparable between the groups. On comparison of SI between sleep stages, delta band: progressive increase in SI from wake ⇒ N1 ⇒ N2 ⇒ N3, whereas REM (rapid eye movement) was comparable to wake; theta band: decreased SI during N2 and increase during N3; alpha band: SI was highest in wake and lower in N1, N2, N3, and REM; and sigma and high beta bands: progressive increase in SI from wake ⇒ N1 ⇒ N2 ⇒ N3; however, sigma band showed lower SI during REM. This study found an increased background cortical synchronization in PWE compared with healthy controls in delta and theta bands during wake and sleep. This background hypersynchrony may be an important property of epileptogenic brain circuitry in PWE, which enables them to effortlessly generate a paroxysmal EEG depolarization shift.

Transient Cognitive Dynamics, Metastability, and Decision Making

DTIC Science & Technology

2008-05-02

imaging (fMRI) and EEG have opened new possibilities for understanding and modeling cognition [11–15]. Experimental recordings have revealed detailed...between different phase-synchronized states of alpha activity in spontaneous EEG . Alpha activity has been characterized as a series of globally...novel protocols of assisted neurofeedback [59– 62], which can open a wide variety of new medical and brain- machine applications. Methods Stable

Brain connectivity analysis from EEG signals using stable phase-synchronized states during face perception tasks

NASA Astrophysics Data System (ADS)

Jamal, Wasifa; Das, Saptarshi; Maharatna, Koushik; Pan, Indranil; Kuyucu, Doga

2015-09-01

Degree of phase synchronization between different Electroencephalogram (EEG) channels is known to be the manifestation of the underlying mechanism of information coupling between different brain regions. In this paper, we apply a continuous wavelet transform (CWT) based analysis technique on EEG data, captured during face perception tasks, to explore the temporal evolution of phase synchronization, from the onset of a stimulus. Our explorations show that there exists a small set (typically 3-5) of unique synchronized patterns or synchrostates, each of which are stable of the order of milliseconds. Particularly, in the beta (β) band, which has been reported to be associated with visual processing task, the number of such stable states has been found to be three consistently. During processing of the stimulus, the switching between these states occurs abruptly but the switching characteristic follows a well-behaved and repeatable sequence. This is observed in a single subject analysis as well as a multiple-subject group-analysis in adults during face perception. We also show that although these patterns remain topographically similar for the general category of face perception task, the sequence of their occurrence and their temporal stability varies markedly between different face perception scenarios (stimuli) indicating toward different dynamical characteristics for information processing, which is stimulus-specific in nature. Subsequently, we translated these stable states into brain complex networks and derived informative network measures for characterizing the degree of segregated processing and information integration in those synchrostates, leading to a new methodology for characterizing information processing in human brain. The proposed methodology of modeling the functional brain connectivity through the synchrostates may be viewed as a new way of quantitative characterization of the cognitive ability of the subject, stimuli and information integration/segregation capability.

Sleep-related modifications of EEG connectivity in the sensory-motor networks in Huntington Disease: An eLORETA study and review of the literature.

PubMed

Piano, Carla; Imperatori, Claudio; Losurdo, Anna; Bentivoglio, Anna Rita; Cortelli, Pietro; Della Marca, Giacomo

2017-07-01

To evaluate EEG functional connectivity in the sensory-motor network, during wake and sleep, in patients with Huntington Disease (HD). 23 patients with HD and 23 age- and sex-matched healthy controls were enrolled. EEG connectivity analysis was performed by means of exact Low Resolution Electric Tomography (eLORETA). In wake, HD patients showed an increase of delta lagged phase synchronization (T=3.60; p<0.05) among Broadman's Areas (BA) 6-8 bilaterally; right BA 6-8 and right BA 1-2-3; left BA 1-2-3 and left BA 4. In NREM, HD patients showed an increase of delta lagged phase synchronization (T=3.56; p<0.05) among left BA 1-2-3 and right BA 6-8. In REM, HD patients showed an increase of lagged phase synchronization (T=3.60; p<0.05) among the BA 6-8 bilaterally (delta band); left BA 1-2-3 and right BA 1-2-3 (theta); left BA 1-2-3 and right BA 4 (theta); left BA 1-2-3 and right BA 1-2-3 (alpha). Our results may reflect an abnormal function of the motor areas or an effort to counterbalance the pathological motor output. Our results may help to understand the pathophysiology of sleep-related movement disorders in Huntington's Disease, and to define therapeutically strategies. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Brain network dynamics characterization in epileptic seizures. Joint directed graph and pairwise synchronization measures

NASA Astrophysics Data System (ADS)

Rodrigues, A. C.; Machado, B. S.; Florence, G.; Hamad, A. P.; Sakamoto, A. C.; Fujita, A.; Baccalá, L. A.; Amaro, E.; Sameshima, K.

2014-12-01

Here we propose and evaluate a new approach to analyse multichannel mesial temporal lobe epilepsy EEG data from eight patients through complex network and synchronization theories. The method employs a Granger causality test to infer the directed connectivity graphs and a wavelet transform based phase synchronization measure whose characteristics allow studying dynamical transitions during epileptic seizures. We present a new combined graph measure that quantifies the level of network hub formation, called network hub out-degree, which closely reflects the level of synchronization observed during the ictus.

Beta phase synchronization in the frontal-temporal-cerebellar network during auditory-to-motor rhythm learning.

PubMed

Edagawa, Kouki; Kawasaki, Masahiro

2017-02-22

Rhythm is an essential element of dancing and music. To investigate the neural mechanisms underlying how rhythm is learned, we recorded electroencephalographic (EEG) data during a rhythm-reproducing task that asked participants to memorize an auditory stimulus and reproduce it via tapping. Based on the behavioral results, we divided the participants into Learning and No-learning groups. EEG analysis showed that error-related negativity (ERN) in the Learning group was larger than in the No-learning group. Time-frequency analysis of the EEG data showed that the beta power in right and left temporal area at the late learning stage was smaller than at the early learning stage in the Learning group. Additionally, the beta power in the temporal and cerebellar areas in the Learning group when learning to reproduce the rhythm were larger than in the No Learning group. Moreover, phase synchronization between frontal and temporal regions and between temporal and cerebellar regions at late stages of learning were larger than at early stages. These results indicate that the frontal-temporal-cerebellar beta neural circuits might be related to auditory-motor rhythm learning.

Analysis of cross-correlations in electroencephalogram signals as an approach to proactive diagnosis of schizophrenia

NASA Astrophysics Data System (ADS)

Timashev, Serge F.; Panischev, Oleg Yu.; Polyakov, Yuriy S.; Demin, Sergey A.; Kaplan, Alexander Ya.

2012-02-01

We apply flicker-noise spectroscopy (FNS), a time series analysis method operating on structure functions and power spectrum estimates, to study the clinical electroencephalogram (EEG) signals recorded in children/adolescents (11 to 14 years of age) with diagnosed schizophrenia-spectrum symptoms at the National Center for Psychiatric Health (NCPH) of the Russian Academy of Medical Sciences. The EEG signals for these subjects were compared with the signals for a control sample of chronically depressed children/adolescents. The purpose of the study is to look for diagnostic signs of subjects' susceptibility to schizophrenia in the FNS parameters for specific electrodes and cross-correlations between the signals simultaneously measured at different points on the scalp. Our analysis of EEG signals from scalp-mounted electrodes at locations F3 and F4, which are symmetrically positioned in the left and right frontal areas of cerebral cortex, respectively, demonstrates an essential role of frequency-phase synchronization, a phenomenon representing specific correlations between the characteristic frequencies and phases of excitations in the brain. We introduce quantitative measures of frequency-phase synchronization and systematize the values of FNS parameters for the EEG data. The comparison of our results with the medical diagnoses for 84 subjects performed at NCPH makes it possible to group the EEG signals into 4 categories corresponding to different risk levels of subjects' susceptibility to schizophrenia. We suggest that the introduced quantitative characteristics and classification of cross-correlations may be used for the diagnosis of schizophrenia at the early stages of its development.

Slower EEG alpha generation, synchronization and "flow"-possible biomarkers of cognitive impairment and neuropathology of minor stroke.

PubMed

Petrovic, Jelena; Milosevic, Vuk; Zivkovic, Miroslava; Stojanov, Dragan; Milojkovic, Olga; Kalauzi, Aleksandar; Saponjic, Jasna

2017-01-01

We investigated EEG rhythms, particularly alpha activity, and their relationship to post-stroke neuropathology and cognitive functions in the subacute and chronic stages of minor strokes. We included 10 patients with right middle cerebral artery (MCA) ischemic strokes and 11 healthy controls. All the assessments of stroke patients were done both in the subacute and chronic stages. Neurological impairment was measured using the National Institute of Health Stroke Scale (NIHSS), whereas cognitive functions were assessed using the Montreal Cognitive Assessment (MoCA) and MoCA memory index (MoCA-MIS). The EEG was recorded using a 19 channel EEG system with standard EEG electrode placement. In particular, we analyzed the EEGs derived from the four lateral frontal (F3, F7, F4, F8), and corresponding lateral posterior (P3, P4, T5, T6) electrodes. Quantitative EEG analysis included: the group FFT spectra, the weighted average of alpha frequency (αAVG), the group probability density distributions of all conventional EEG frequency band relative amplitudes (EEG microstructure), the inter- and intra-hemispheric coherences, and the topographic distribution of alpha carrier frequency phase potentials (PPs). Statistical analysis was done using a Kruskal-Wallis ANOVA with a post-hoc Mann-Whitney U two-tailed test, and Spearman's correlation. We demonstrated transient cognitive impairment alongside a slower alpha frequency ( α AVG) in the subacute right MCA stroke patients vs. the controls. This slower alpha frequency showed no amplitude change, but was highly synchronized intra-hemispherically, overlying the ipsi-lesional hemisphere, and inter-hemispherically, overlying the frontal cortex. In addition, the disturbances in EEG alpha activity in subacute stroke patients were expressed as a decrease in alpha PPs over the frontal cortex and an altered "alpha flow", indicating the sustained augmentation of inter-hemispheric interactions. Although the stroke induced slower alpha was a transient phenomenon, the increased alpha intra-hemispheric synchronization, overlying the ipsi-lesional hemisphere, the increased alpha F3-F4 inter-hemispheric synchronization, the delayed alpha waves, and the newly established inter-hemispheric "alpha flow" within the frontal cortex, remained as a permanent consequence of the minor stroke. This newly established frontal inter-hemispheric "alpha flow" represented a permanent consequence of the "hidden" stroke neuropathology, despite the fact that cognitive impairment has been returned to the control values. All the detected permanent changes at the EEG level with no cognitive impairment after a minor stroke could be a way for the brain to compensate for the lesion and restore the lost function. Our study indicates slower EEG alpha generation, synchronization and "flow" as potential biomarkers of cognitive impairment onset and/or compensatory post-stroke re-organizational processes.

Phase and amplitude analysis in time-frequency space--application to voluntary finger movement.

PubMed

Ginter, J; Blinowska, K J; Kamiński, M; Durka, P J

2001-09-30

Two methods operating in time-frequency space were applied to analysis of EEG activity accompanying voluntary finger movements. The first one, based on matching pursuit approach provided high-resolution distributions of power in time-frequency space. The phenomena of event related desynchronization (ERD) and synchronization (ERS) were investigated without the need of band-pass filtering. Time evolution of mu- and beta-components was observed in a detailed way. The second method was based on a multichannel autoregressive model (MVAR) adapted for investigation of short-time changes in EEG signal. The direction and spectral content of the EEG activity propagation was estimated by means of short-time directed transfer function (SDTF). The evidence of 'cross-talk' between different areas of motor and sensory cortex was found. The earlier known phenomena, connected with voluntary movements, were confirmed and a new evidence concerning focal ERD/surround ERS and beta activity post-movement synchronization was found.

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…

Fast entrainment of human electroencephalogram to a theta-band photic flicker during successful memory encoding.

PubMed

Sato, Naoyuki

2013-01-01

Theta band power (4-8 Hz) in the scalp electroencephalogram (EEG) is thought to be stronger during memory encoding for subsequently remembered items than for forgotten items. According to simultaneous EEG-functional magnetic resonance imaging (fMRI) measurements, the memory-dependent EEG theta is associated with multiple regions of the brain. This suggests that the multiple regions cooperate with EEG theta synchronization during successful memory encoding. However, a question still remains: What kind of neural dynamic organizes such a memory-dependent global network? In this study, the modulation of the EEG theta entrainment property during successful encoding was hypothesized to lead to EEG theta synchronization among a distributed network. Then, a transient response of EEG theta to a theta-band photic flicker with a short duration was evaluated during memory encoding. In the results, flicker-induced EEG power increased and decreased with a time constant of several hundred milliseconds following the onset and the offset of the flicker, respectively. Importantly, the offset response of EEG power was found to be significantly decreased during successful encoding. Moreover, the offset response of the phase locking index was also found to associate with memory performance. According to computational simulations, the results are interpreted as a smaller time constant (i.e., faster response) of a driven harmonic oscillator rather than a change in the spontaneous oscillatory input. This suggests that the fast response of EEG theta forms a global EEG theta network among memory-related regions during successful encoding, and it contributes to a flexible formation of the network along the time course.

Graph properties of synchronized cortical networks during visual working memory maintenance.

PubMed

Palva, Satu; Monto, Simo; Palva, J Matias

2010-02-15

Oscillatory synchronization facilitates communication in neuronal networks and is intimately associated with human cognition. Neuronal activity in the human brain can be non-invasively imaged with magneto- (MEG) and electroencephalography (EEG), but the large-scale structure of synchronized cortical networks supporting cognitive processing has remained uncharacterized. We combined simultaneous MEG and EEG (MEEG) recordings with minimum-norm-estimate-based inverse modeling to investigate the structure of oscillatory phase synchronized networks that were active during visual working memory (VWM) maintenance. Inter-areal phase-synchrony was quantified as a function of time and frequency by single-trial phase-difference estimates of cortical patches covering the entire cortical surfaces. The resulting networks were characterized with a number of network metrics that were then compared between delta/theta- (3-6 Hz), alpha- (7-13 Hz), beta- (16-25 Hz), and gamma- (30-80 Hz) frequency bands. We found several salient differences between frequency bands. Alpha- and beta-band networks were more clustered and small-world like but had smaller global efficiency than the networks in the delta/theta and gamma bands. Alpha- and beta-band networks also had truncated-power-law degree distributions and high k-core numbers. The data converge on showing that during the VWM-retention period, human cortical alpha- and beta-band networks have a memory-load dependent, scale-free small-world structure with densely connected core-like structures. These data further show that synchronized dynamic networks underlying a specific cognitive state can exhibit distinct frequency-dependent network structures that could support distinct functional roles. Copyright 2009 Elsevier Inc. All rights reserved.

Global field synchronization in gamma range of the sleep EEG tracks sleep depth: Artifact introduced by a rectangular analysis window.

PubMed

Rusterholz, Thomas; Achermann, Peter; Dürr, Roland; Koenig, Thomas; Tarokh, Leila

2017-06-01

Investigating functional connectivity between brain networks has become an area of interest in neuroscience. Several methods for investigating connectivity have recently been developed, however, these techniques need to be applied with care. We demonstrate that global field synchronization (GFS), a global measure of phase alignment in the EEG as a function of frequency, must be applied considering signal processing principles in order to yield valid results. Multichannel EEG (27 derivations) was analyzed for GFS based on the complex spectrum derived by the fast Fourier transform (FFT). We examined the effect of window functions on GFS, in particular of non-rectangular windows. Applying a rectangular window when calculating the FFT revealed high GFS values for high frequencies (>15Hz) that were highly correlated (r=0.9) with spectral power in the lower frequency range (0.75-4.5Hz) and tracked the depth of sleep. This turned out to be spurious synchronization. With a non-rectangular window (Tukey or Hanning window) these high frequency synchronization vanished. Both, GFS and power density spectra significantly differed for rectangular and non-rectangular windows. Previous papers using GFS typically did not specify the applied window and may have used a rectangular window function. However, the demonstrated impact of the window function raises the question of the validity of some previous findings at higher frequencies. We demonstrated that it is crucial to apply an appropriate window function for determining synchronization measures based on a spectral approach to avoid spurious synchronization in the beta/gamma range. Copyright © 2017 Elsevier B.V. All rights reserved.

Brain functional connectivity and the pathophysiology of schizophrenia.

PubMed

Angelopoulos, E

2014-01-01

In the last decade there is extensive evidence to suggest that cognitive functions depending on coordination of distributed neuronal responses are associated with synchronized oscillatory activity in various frequency ranges suggesting a functional mechanism of neural oscillations in cortical networks. In addition to their role in normal brain functioning, there is increasing evidence that altered oscillatory activity may be associated with certain neuropsychiatric disorders, such as schizophrenia. Consequently, disturbances in neural synchronization may represent the functional relationship of disordered connectivity of cortical networks underlying the characteristic fragmentation of mind and behavior in schizophrenia. In recent studies the synchronization of oscillatory activity in the experience of characteristic symptoms such as auditory verbal hallucinations and thought blocks have been studied in patients with schizophrenia. Studies involving analysis of EEG activity obtained from individuals in resting state (in cage Faraday, isolated from external influences and with eyes closed). In patients with schizophrenia and persistent auditory verbal hallucinations (AVHs) observed a temporary increase in the synchronization phase of α and high θ oscillations of the electroencephalogram (EEG) compared with those of healthy controls and patients without AVHs . This functional hyper-connection manifested in time windows corresponding to experience AVHs, as noted by the patients during the recording of EEG and observed in speech related cortical areas. In another study an interaction of theta and gamma oscillations engages in the production and experience of AVHs. The results showed increased phase coupling between theta and gamma EEG rhythms in the left temporal cortex during AVHs experiences. A more recent study, approaches the thought blocking experience in terms of functional brain connectivity. Thought blocks (TBs) are characterized by regular interruptions of the flow of thought. Outward signs are abrupt and repeated interruptions in the flow of conversation or actions while subjective experience is that of a total and uncontrollable emptying of the mind. In the very limited bibliography regarding TB, the phenomenon is thought to be conceptualized as a disturbance of consciousness that can be attributed to stoppages of continuous information processing due to an increase in the volume of information to be processed. In an attempt to investigate potential expression of the phenomenon on the functional properties of electroencephalographic (EEG) activity, an EEG study was contacted in schizophrenic patients with persisting auditory verbal hallucinations (AVHs) who additionally exhibited TBs. Phase synchronization analyses performed on EEG segments during the experience of TBs showed that synchrony values exhibited a long-range common mode of coupling (grouped behavior) among the left temporal area and the remaining central and frontal brain areas. These common synchrony-fluctuation schemes were observed for 0.5 to 2 s and were detected in a 4-s window following the estimated initiation of the phenomenon. The observation was frequency specific and detected in the broad alpha band region (6-12 Hz). The introduction of synchrony entropy (SE) analysis applied on the cumulative synchrony distribution showed that TB states were characterized by an explicit preference of the system to be functioned at low values of synchrony, while the synchrony values are broadly distributed during the recovery state. The results indicate that during TB states, the phase locking of several brain areas were converged uniformly in a narrow band of low synchrony values and in a distinct time window, impeding thus the ability of the system to recruit and to process information during this time window. The results of this study seem to have greater importance on neuronal correlation of consciousness. The brain is a highly distributed system in which numerous operations are executed in parallel and that lacks a single coordinating center. This raises the question of how the computations occurring simultaneously in spatially segregated processing areas are coordinated and bound together to give rise to coherent percepts and actions. One of the coordinating mechanisms appears to be the synchronization of neuronal activity by phase locking of self-generated network oscillations. This led to the hypothesis that the cerebral cortex might exploit the option to synchronize the discharges of neurons with millisecond ` theoretical formulations of the binding-by-synchrony hypothesis were proposed earlier by Milner (1974), but the Singer lab in the 1990s was the first to obtain experimental evidence supporting the potential role of synchrony as a relational code. The results concerning the functional connectivity of the brain during TBs further support the hypothesis of phase synchronization as a key mechanism for neuronal assemblies underlying mental representations in the human brain.

Analysis of Synchronization Phenomena in Broadband Signals with Nonlinear Excitable Media

NASA Astrophysics Data System (ADS)

Chernihovskyi, Anton; Elger, Christian E.; Lehnertz, Klaus

2009-12-01

We apply the method of frequency-selective excitation waves in excitable media to characterize synchronization phenomena in interacting complex dynamical systems by measuring coincidence rates of induced excitations. We relax the frequency-selectivity of excitable media and demonstrate two applications of the method to signals with broadband spectra. Findings obtained from analyzing time series of coupled chaotic oscillators as well as electroencephalographic (EEG) recordings from an epilepsy patient indicate that this method can provide an alternative and complementary way to estimate the degree of phase synchronization in noisy signals.

Classifying Different Emotional States by Means of EEG-Based Functional Connectivity Patterns

PubMed Central

Lee, You-Yun; Hsieh, Shulan

2014-01-01

This study aimed to classify different emotional states by means of EEG-based functional connectivity patterns. Forty young participants viewed film clips that evoked the following emotional states: neutral, positive, or negative. Three connectivity indices, including correlation, coherence, and phase synchronization, were used to estimate brain functional connectivity in EEG signals. Following each film clip, participants were asked to report on their subjective affect. The results indicated that the EEG-based functional connectivity change was significantly different among emotional states. Furthermore, the connectivity pattern was detected by pattern classification analysis using Quadratic Discriminant Analysis. The results indicated that the classification rate was better than chance. We conclude that estimating EEG-based functional connectivity provides a useful tool for studying the relationship between brain activity and emotional states. PMID:24743695

Music training is associated with cortical synchronization reflected in EEG coherence during verbal memory encoding.

PubMed

Cheung, Mei-Chun; Chan, Agnes S; Liu, Ying; Law, Derry; Wong, Christina W Y

2017-01-01

Music training can improve cognitive functions. Previous studies have shown that children and adults with music training demonstrate better verbal learning and memory performance than those without such training. Although prior studies have shown an association between music training and changes in the structural and functional organization of the brain, there is no concrete evidence of the underlying neural correlates of the verbal memory encoding phase involved in such enhanced memory performance. Therefore, we carried out an electroencephalography (EEG) study to investigate how music training was associated with brain activity during the verbal memory encoding phase. Sixty participants were recruited, 30 of whom had received music training for at least one year (the MT group) and 30 of whom had never received music training (the NMT group). The participants in the two groups were matched for age, education, gender distribution, and cognitive capability. Their verbal and visual memory functions were assessed using standardized neuropsychological tests and EEG was used to record their brain activity during the verbal memory encoding phase. Consistent with previous studies, the MT group demonstrated better verbal memory than the NMT group during both the learning and the delayed recall trials in the paper-and-pencil tests. The MT group also exhibited greater learning capacity during the learning trials. Compared with the NMT group, the MT group showed an increase in long-range left and right intrahemispheric EEG coherence in the theta frequency band during the verbal memory encoding phase. In addition, their event-related left intrahemispheric theta coherence was positively associated with subsequent verbal memory performance as measured by discrimination scores. These results suggest that music training may modulate the cortical synchronization of the neural networks involved in verbal memory formation.

Music training is associated with cortical synchronization reflected in EEG coherence during verbal memory encoding

PubMed Central

Cheung, Mei-chun; Chan, Agnes S.; Liu, Ying; Law, Derry; Wong, Christina W. Y.

2017-01-01

Music training can improve cognitive functions. Previous studies have shown that children and adults with music training demonstrate better verbal learning and memory performance than those without such training. Although prior studies have shown an association between music training and changes in the structural and functional organization of the brain, there is no concrete evidence of the underlying neural correlates of the verbal memory encoding phase involved in such enhanced memory performance. Therefore, we carried out an electroencephalography (EEG) study to investigate how music training was associated with brain activity during the verbal memory encoding phase. Sixty participants were recruited, 30 of whom had received music training for at least one year (the MT group) and 30 of whom had never received music training (the NMT group). The participants in the two groups were matched for age, education, gender distribution, and cognitive capability. Their verbal and visual memory functions were assessed using standardized neuropsychological tests and EEG was used to record their brain activity during the verbal memory encoding phase. Consistent with previous studies, the MT group demonstrated better verbal memory than the NMT group during both the learning and the delayed recall trials in the paper-and-pencil tests. The MT group also exhibited greater learning capacity during the learning trials. Compared with the NMT group, the MT group showed an increase in long-range left and right intrahemispheric EEG coherence in the theta frequency band during the verbal memory encoding phase. In addition, their event-related left intrahemispheric theta coherence was positively associated with subsequent verbal memory performance as measured by discrimination scores. These results suggest that music training may modulate the cortical synchronization of the neural networks involved in verbal memory formation. PMID:28358852

Automated detection of a preseizure state based on a decrease in synchronization in intracranial electroencephalogram recordings from epilepsy patients

NASA Astrophysics Data System (ADS)

Mormann, Florian; Andrzejak, Ralph G.; Kreuz, Thomas; Rieke, Christoph; David, Peter; Elger, Christian E.; Lehnertz, Klaus

2003-02-01

The question whether information extracted from the electroencephalogram (EEG) of epilepsy patients can be used for the prediction of seizures has recently attracted much attention. Several studies have reported evidence for the existence of a preseizure state that can be detected using different measures derived from the theory of dynamical systems. Most of these studies, however, have neglected to sufficiently investigate the specificity of the observed effects or suffer from other methodological shortcomings. In this paper we present an automated technique for the detection of a preseizure state from EEG recordings using two different measures for synchronization between recording sites, namely, the mean phase coherence as a measure for phase synchronization and the maximum linear cross correlation as a measure for lag synchronization. Based on the observation of characteristic drops in synchronization prior to seizure onset, we used this phenomenon for the characterization of a preseizure state and its distinction from the remaining seizure-free interval. After optimizing our technique on a group of 10 patients with temporal lobe epilepsy we obtained a successful detection of a preseizure state prior to 12 out of 14 analyzed seizures for both measures at a very high specificity as tested on recordings from the seizure-free interval. After checking for in-sample overtraining via cross validation, we applied a surrogate test to validate the observed predictability. Based on our results, we discuss the differences of the two synchronization measures in terms of the dynamics underlying seizure generation in focal epilepsies.

EEG oscillatory patterns are associated with error prediction during music performance and are altered in musician's dystonia.

PubMed

Ruiz, María Herrojo; Strübing, Felix; Jabusch, Hans-Christian; Altenmüller, Eckart

2011-04-15

Skilled performance requires the ability to monitor ongoing behavior, detect errors in advance and modify the performance accordingly. The acquisition of fast predictive mechanisms might be possible due to the extensive training characterizing expertise performance. Recent EEG studies on piano performance reported a negative event-related potential (ERP) triggered in the ACC 70 ms before performance errors (pitch errors due to incorrect keypress). This ERP component, termed pre-error related negativity (pre-ERN), was assumed to reflect processes of error detection in advance. However, some questions remained to be addressed: (i) Does the electrophysiological marker prior to errors reflect an error signal itself or is it related instead to the implementation of control mechanisms? (ii) Does the posterior frontomedial cortex (pFMC, including ACC) interact with other brain regions to implement control adjustments following motor prediction of an upcoming error? (iii) Can we gain insight into the electrophysiological correlates of error prediction and control by assessing the local neuronal synchronization and phase interaction among neuronal populations? (iv) Finally, are error detection and control mechanisms defective in pianists with musician's dystonia (MD), a focal task-specific dystonia resulting from dysfunction of the basal ganglia-thalamic-frontal circuits? Consequently, we investigated the EEG oscillatory and phase synchronization correlates of error detection and control during piano performances in healthy pianists and in a group of pianists with MD. In healthy pianists, the main outcomes were increased pre-error theta and beta band oscillations over the pFMC and 13-15 Hz phase synchronization, between the pFMC and the right lateral prefrontal cortex, which predicted corrective mechanisms. In MD patients, the pattern of phase synchronization appeared in a different frequency band (6-8 Hz) and correlated with the severity of the disorder. The present findings shed new light on the neural mechanisms, which might implement motor prediction by means of forward control processes, as they function in healthy pianists and in their altered form in patients with MD. Copyright © 2010 Elsevier Inc. All rights reserved.

Transcranial magnetic stimulation-induced global propagation of transient phase resetting associated with directional information flow.

PubMed

Kawasaki, Masahiro; Uno, Yutaka; Mori, Jumpei; Kobata, Kenji; Kitajo, Keiichi

2014-01-01

Electroencephalogram (EEG) phase synchronization analyses can reveal large-scale communication between distant brain areas. However, it is not possible to identify the directional information flow between distant areas using conventional phase synchronization analyses. In the present study, we applied transcranial magnetic stimulation (TMS) to the occipital area in subjects who were resting with their eyes closed, and analyzed the spatial propagation of transient TMS-induced phase resetting by using the transfer entropy (TE), to quantify the causal and directional flow of information. The time-frequency EEG analysis indicated that the theta (5 Hz) phase locking factor (PLF) reached its highest value at the distant area (the motor area in this study), with a time lag that followed the peak of the transient PLF enhancements of the TMS-targeted area at the TMS onset. Phase-preservation index (PPI) analyses demonstrated significant phase resetting at the TMS-targeted area and distant area. Moreover, the TE from the TMS-targeted area to the distant area increased clearly during the delay that followed TMS onset. Interestingly, the time lags were almost coincident between the PLF and TE results (152 vs. 165 ms), which provides strong evidence that the emergence of the delayed PLF reflects the causal information flow. Such tendencies were observed only in the higher-intensity TMS condition, and not in the lower-intensity or sham TMS conditions. Thus, TMS may manipulate large-scale causal relationships between brain areas in an intensity-dependent manner. We demonstrated that single-pulse TMS modulated global phase dynamics and directional information flow among synchronized brain networks. Therefore, our results suggest that single-pulse TMS can manipulate both incoming and outgoing information in the TMS-targeted area associated with functional changes.

Lifespan Differences in Cortical Dynamics of Auditory Perception

ERIC Educational Resources Information Center

Muller, Viktor; Gruber, Walter; Klimesch, Wolfgang; Lindenberger, Ulman

2009-01-01

Using electroencephalographic recordings (EEG), we assessed differences in oscillatory cortical activity during auditory-oddball performance between children aged 9-13 years, younger adults, and older adults. From childhood to old age, phase synchronization increased within and between electrodes, whereas whole power and evoked power decreased. We…

Classification of autism spectrum disorder using supervised learning of brain connectivity measures extracted from synchrostates

NASA Astrophysics Data System (ADS)

Jamal, Wasifa; Das, Saptarshi; Oprescu, Ioana-Anastasia; Maharatna, Koushik; Apicella, Fabio; Sicca, Federico

2014-08-01

Objective. The paper investigates the presence of autism using the functional brain connectivity measures derived from electro-encephalogram (EEG) of children during face perception tasks. Approach. Phase synchronized patterns from 128-channel EEG signals are obtained for typical children and children with autism spectrum disorder (ASD). The phase synchronized states or synchrostates temporally switch amongst themselves as an underlying process for the completion of a particular cognitive task. We used 12 subjects in each group (ASD and typical) for analyzing their EEG while processing fearful, happy and neutral faces. The minimal and maximally occurring synchrostates for each subject are chosen for extraction of brain connectivity features, which are used for classification between these two groups of subjects. Among different supervised learning techniques, we here explored the discriminant analysis and support vector machine both with polynomial kernels for the classification task. Main results. The leave one out cross-validation of the classification algorithm gives 94.7% accuracy as the best performance with corresponding sensitivity and specificity values as 85.7% and 100% respectively. Significance. The proposed method gives high classification accuracies and outperforms other contemporary research results. The effectiveness of the proposed method for classification of autistic and typical children suggests the possibility of using it on a larger population to validate it for clinical practice.

Disturbed resting state EEG synchronization in bipolar disorder: A graph-theoretic analysis☆

PubMed Central

Kim, Dae-Jin; Bolbecker, Amanda R.; Howell, Josselyn; Rass, Olga; Sporns, Olaf; Hetrick, William P.; Breier, Alan; O'Donnell, Brian F.

2013-01-01

Disruption of functional connectivity may be a key feature of bipolar disorder (BD) which reflects disturbances of synchronization and oscillations within brain networks. We investigated whether the resting electroencephalogram (EEG) in patients with BD showed altered synchronization or network properties. Resting-state EEG was recorded in 57 BD type-I patients and 87 healthy control subjects. Functional connectivity between pairs of EEG channels was measured using synchronization likelihood (SL) for 5 frequency bands (δ, θ, α, β, and γ). Graph-theoretic analysis was applied to SL over the electrode array to assess network properties. BD patients showed a decrease of mean synchronization in the alpha band, and the decreases were greatest in fronto-central and centro-parietal connections. In addition, the clustering coefficient and global efficiency were decreased in BD patients, whereas the characteristic path length increased. We also found that the normalized characteristic path length and small-worldness were significantly correlated with depression scores in BD patients. These results suggest that BD patients show impaired neural synchronization at rest and a disruption of resting-state functional connectivity. PMID:24179795

Estimating cognitive workload using wavelet entropy-based features during an arithmetic task.

PubMed

Zarjam, Pega; Epps, Julien; Chen, Fang; Lovell, Nigel H

2013-12-01

Electroencephalography (EEG) has shown promise as an indicator of cognitive workload; however, precise workload estimation is an ongoing research challenge. In this investigation, seven levels of workload were induced using an arithmetic task, and the entropy of wavelet coefficients extracted from EEG signals is shown to distinguish all seven levels. For a subject-independent multi-channel classification scheme, the entropy features achieved high accuracy, up to 98% for channels from the frontal lobes, in the delta frequency band. This suggests that a smaller number of EEG channels in only one frequency band can be deployed for an effective EEG-based workload classification system. Together with analysis based on phase locking between channels, these results consistently suggest increased synchronization of neural responses for higher load levels. Copyright © 2013 Elsevier Ltd. All rights reserved.

Changes of EEG Spectra and Functional Connectivity during an Object-Location Memory Task in Alzheimer's Disease.

PubMed

Han, Yuliang; Wang, Kai; Jia, Jianjun; Wu, Weiping

2017-01-01

Object-location memory is particularly fragile and specifically impaired in Alzheimer's disease (AD) patients. Electroencephalogram (EEG) was utilized to objectively measure memory impairment for memory formation correlates of EEG oscillatory activities. We aimed to construct an object-location memory paradigm and explore EEG signs of it. Two groups of 20 probable mild AD patients and 19 healthy older adults were included in a cross-sectional analysis. All subjects took an object-location memory task. EEG recordings performed during object-location memory tasks were compared between the two groups in the two EEG parameters (spectral parameters and phase synchronization). The memory performance of AD patients was worse than that of healthy elderly adults The power of object-location memory of the AD group was significantly higher than the NC group (healthy elderly adults) in the alpha band in the encoding session, and alpha and theta bands in the retrieval session. The channels-pairs the phase lag index value of object-location memory in the AD group was clearly higher than the NC group in the delta, theta, and alpha bands in encoding sessions and delta and theta bands in retrieval sessions. The results provide support for the hypothesis that the AD patients may use compensation mechanisms to remember the items and episode.

The interaction of rhinal cortex and hippocampus in human declarative memory formation.

PubMed

Fell, Jürgen; Klaver, Peter; Elger, Christian E; Fernández, Guillén

2002-01-01

Human declarative memory formation crucially depends on processes within the medial temporal lobe (MTL). These processes can be monitored in real-time by recordings from depth electrodes implanted in the MTL of patients with epilepsy who undergo presurgical evaluation. In our studies, patients performed a word memorization task during depth EEG recording. Afterwards, the difference between event-related potentials (ERPs) corresponding to subsequently remembered versus forgotten words was analyzed. These kind of studies revealed that successful memory encoding is characterized by an early process generated by the rhinal cortex within 300 ms following stimulus onset. This rhinal process precedes a hippocampal process, which starts about 200 ms later. Further investigation revealed that the rhinal process seems to be a correlate of semantic preprocessing which supports memory formation, whereas the hippocampal process appears to be a correlate of an exclusively mnemonic operation. These studies yielded only indirect evidence for an interaction of rhinal cortex and hippocampus. Direct evidence for a memory related cooperation between both structures, however, has been found in a study analyzing so called gamma activity, EEG oscillations of around 40 Hz. This investigation showed that successful as opposed to unsuccessful memory formation is accompanied by an initial enhancement of rhinal-hippocampal phase synchronization, which is followed by a later desynchronization. Present knowledge about the function of phase synchronized gamma activity suggests that this phase coupling and decoupling initiates and later terminates communication between the two MTL structures. Phase synchronized rhinal-hippocampal gamma activity may, moreover, accomplish Hebbian synaptic modifications and thus provide an initial step of declarative memory formation on the synaptic level.

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.

EEG alpha synchronization is related to top-down processing in convergent and divergent thinking

PubMed Central

Benedek, Mathias; Bergner, Sabine; Könen, 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 demands and to specific cognitive process involved in creative thinking. To this end, EEG was measured during a convergent and a divergent thinking task (i.e., creativity-related task) which once were processed involving low and once involving high internal processing demands. High internal processing demands were established by masking the stimulus (after encoding) and thus preventing further bottom-up processing. Frontal alpha synchronization was observed during convergent and divergent thinking only under exclusive top-down control (high internal processing demands), but not when bottom-up processing was allowed (low internal processing demands). We conclude that frontal alpha synchronization is related to top-down control rather than to specific creativity-related cognitive processes. Frontal alpha synchronization, which has been observed in a variety of different creativity tasks, thus may not reflect a brain state that is specific for creative cognition but can probably be attributed to high internal processing demands which are typically involved in creative thinking. PMID:21925520

Regional Slow Waves and Spindles in Human Sleep

PubMed Central

Nir, Yuval; Staba, Richard J.; Andrillon, Thomas; Vyazovskiy, Vladyslav V.; Cirelli, Chiara; Fried, Itzhak; Tononi, Giulio

2011-01-01

SUMMARY The most prominent EEG events in sleep are slow waves, reflecting a slow (<1 Hz) oscillation between up and down states in cortical neurons. It is unknown whether slow oscillations are synchronous across the majority or the minority of brain regions—are they a global or local phenomenon? To examine this, we recorded simultaneously scalp EEG, intracerebral EEG, and unit firing in multiple brain regions of neurosurgical patients. We find that most sleep slow waves and the underlying active and inactive neuronal states occur locally. Thus, especially in late sleep, some regions can be active while others are silent. We also find that slow waves can propagate, usually from medial prefrontal cortex to the medial temporal lobe and hippocampus. Sleep spindles, the other hallmark of NREM sleep EEG, are likewise predominantly local. Thus, intracerebral communication during sleep is constrained because slow and spindle oscillations often occur out-of-phase in different brain regions. PMID:21482364

Dysfunctional long-range coordination of neural activity during Gestalt perception in schizophrenia.

PubMed

Uhlhaas, Peter J; Linden, David E J; Singer, Wolf; Haenschel, Corinna; Lindner, Michael; Maurer, Konrad; Rodriguez, Eugenio

2006-08-02

Recent theoretical and empirical research on schizophrenia converges on the notion that core aspects of the pathophysiology of the disorder may arise from a dysfunction in the coordination of distributed neural activity. Synchronization of neural responses in the beta-band (15-30 Hz) and gamma-band range (30-80 Hz) has been implicated as a possible neural substrate for dysfunctional coordination in schizophrenia. To test this hypothesis, we examined the electroencephalography (EEG) activity in 19 patients with a Diagnostic and Statistical Manual of Mental Disorder, edition IV criteria, diagnosis of schizophrenia and 19 healthy control subjects during a Gestalt perception task. EEG data were analyzed for phase synchrony and induced spectral power as an index of neural synchronization. Schizophrenia patients were impaired significantly in the detection of images that required the grouping of stimulus elements into coherent object representations. This deficit was accompanied by longer reaction times in schizophrenia patients. Deficits in Gestalt perception in schizophrenia patients were associated with reduced phase synchrony in the beta-band (20-30 Hz), whereas induced spectral power in the gamma-band (40-70 Hz) was mainly intact. Our findings suggest that schizophrenia patients are impaired in the long-range synchronization of neural responses, which may reflect a core deficit in the coordination of neural activity and underlie the specific cognitive dysfunctions associated with the disorder.

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

PubMed

Pletzer, Belinda; Kerschbaum, Hubert; Klimesch, Wolfgang

2010-06-04

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

A new EEG synchronization strength analysis method: S-estimator based normalized weighted-permutation mutual information.

PubMed

Cui, Dong; Pu, Weiting; Liu, Jing; Bian, Zhijie; Li, Qiuli; Wang, Lei; Gu, Guanghua

2016-10-01

Synchronization is an important mechanism for understanding information processing in normal or abnormal brains. In this paper, we propose a new method called normalized weighted-permutation mutual information (NWPMI) for double variable signal synchronization analysis and combine NWPMI with S-estimator measure to generate a new method named S-estimator based normalized weighted-permutation mutual information (SNWPMI) for analyzing multi-channel electroencephalographic (EEG) synchronization strength. The performances including the effects of time delay, embedding dimension, coupling coefficients, signal to noise ratios (SNRs) and data length of the NWPMI are evaluated by using Coupled Henon mapping model. The results show that the NWPMI is superior in describing the synchronization compared with the normalized permutation mutual information (NPMI). Furthermore, the proposed SNWPMI method is applied to analyze scalp EEG data from 26 amnestic mild cognitive impairment (aMCI) subjects and 20 age-matched controls with normal cognitive function, who both suffer from type 2 diabetes mellitus (T2DM). The proposed methods NWPMI and SNWPMI are suggested to be an effective index to estimate the synchronization strength. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effects of mental tasks on the cardiorespiratory synchronization.

PubMed

Zhang, Jianbao; Yu, Xiaolin; Xie, Dongdong

2010-01-31

The cardiovascular and respiratory systems are functionally related to each other, but it is unclear if the cerebral cortex can affect their interaction. The effect of a mental task on the synchronization between cardiovascular and respiratory systems was investigated in the article. Electroencephalogram (EEG), electrocardiogram (ECG) and respiratory signal (RES) were collected from 29 healthy male subjects during the mental arithmetic (MA) task and the synchrogram was used to estimate the strength of cardiorespiratory synchronization. Our results showed that MA task significantly increased the breath rate, the heart rate and the EEG power spectral energy in theta band at FC3, FC4 and C4 electrodes (p<0.01), decreased the duration of cardiorespiratory synchronization epochs (p<0.05). Moreover the duration of cardiorespiratory synchronization epochs during MA task was negatively correlated with the EEG power spectral energy in theta band at FC3, FC4 and C4 electrodes and the sympathetic activity (p<0.05). The results demonstrated that ANS and cerebral cortex are implicated in the changes of cardiorespiratory synchronization during MA task. Copyright 2009 Elsevier B.V. All rights reserved.

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

PubMed

Popivanov, D; Mineva, A; Krekule, I

1999-05-21

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

Effective Synchronization of EEG and EMG for Mobile Brain/Body Imaging in Clinical Settings.

PubMed

Artoni, Fiorenzo; Barsotti, Annalisa; Guanziroli, Eleonora; Micera, Silvestro; Landi, Alberto; Molteni, Franco

2017-01-01

Mobile Brain/Body Imaging (MoBI) is rapidly gaining traction as a new imaging modality to study how cognitive processes support locomotion. Electroencephalogram (EEG) and electromyogram (EMG), due to their time resolution, non-invasiveness and portability are the techniques of choice for MoBI, but synchronization requirements among others restrict its use to high-end research facilities. Here we test the effectiveness of a technique that enables us to achieve MoBI-grade synchronization of EEG and EMG, even when other strategies (such as Lab Streaming Layer (LSL)) cannot be used e.g., due to the unavailability of proprietary Application Programming Interfaces (APIs), which is often the case in clinical settings. The proposed strategy is that of aligning several spikes at the beginning and end of the session. We delivered a train of spikes to the EEG amplifier and EMG electrodes every 2 s over a 10-min time period. We selected a variable number of spikes (from 1 to 10) both at the beginning and end of the time series and linearly resampled the data so as to align them. We then compared the misalignment of the "middle" spikes over the whole recording to test for jitter and synchronization drifts, highlighting possible nonlinearities (due to hardware filters) and estimated the maximum length of the recording to achieve a [-5 to 5] ms misalignment range. We demonstrate that MoBI-grade synchronization can be achieved within 10-min recordings with a 1.7 ms jitter and [-5 5] ms misalignment range. We show that repeated spike delivery can be used to test online synchronization options and to troubleshoot synchronization issues over EEG and EMG. We also show that synchronization cannot rely only on the equipment sampling rate advertised by manufacturers. The synchronization strategy described can be used virtually in every clinical environment, and may increase the interest among a broader spectrum of clinicians and researchers in the MoBI framework, ultimately leading to a better understanding of the brain processes underlying locomotion control and the development of more effective rehabilitation approaches.

Intra- and interbrain synchronization and network properties when playing guitar in duets

PubMed Central

Sänger, Johanna; Müller, Viktor; Lindenberger, Ulman

2012-01-01

To further test and explore the hypothesis that synchronous oscillatory brain activity supports interpersonally coordinated behavior during dyadic music performance, we simultaneously recorded the electroencephalogram (EEG) from the brains of each of 12 guitar duets repeatedly playing a modified Rondo in two voices by C.G. Scheidler. Indicators of phase locking and of within-brain and between-brain phase coherence were obtained from complex time-frequency signals based on the Gabor transform. Analyses were restricted to the delta (1–4 Hz) and theta (4–8 Hz) frequency bands. We found that phase locking as well as within-brain and between-brain phase-coherence connection strengths were enhanced at frontal and central electrodes during periods that put particularly high demands on musical coordination. Phase locking was modulated in relation to the experimentally assigned musical roles of leader and follower, corroborating the functional significance of synchronous oscillations in dyadic music performance. Graph theory analyses revealed within-brain and hyperbrain networks with small-worldness properties that were enhanced during musical coordination periods, and community structures encompassing electrodes from both brains (hyperbrain modules). We conclude that brain mechanisms indexed by phase locking, phase coherence, and structural properties of within-brain and hyperbrain networks support interpersonal action coordination (IAC). PMID:23226120

Comparison of connectivity analyses for resting state EEG data

NASA Astrophysics Data System (ADS)

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

2017-06-01

Objective. In the present work, a nonlinear measure (transfer entropy, TE) was used in a multivariate approach for the analysis of effective connectivity in high density resting state EEG data in eyes open and eyes closed. Advantages of the multivariate approach in comparison to the bivariate one were tested. Moreover, the multivariate TE was compared to an effective linear measure, i.e. directed transfer function (DTF). Finally, the existence of a relationship between the information transfer and the level of brain synchronization as measured by phase synchronization value (PLV) was investigated. Approach. The comparison between the connectivity measures, i.e. bivariate versus multivariate TE, TE versus DTF, TE versus PLV, was performed by means of statistical analysis of indexes based on graph theory. Main results. The multivariate approach is less sensitive to false indirect connections with respect to the bivariate estimates. The multivariate TE differentiated better between eyes closed and eyes open conditions compared to DTF. Moreover, the multivariate TE evidenced non-linear phenomena in information transfer, which are not evidenced by the use of DTF. We also showed that the target of information flow, in particular the frontal region, is an area of greater brain synchronization. Significance. Comparison of different connectivity analysis methods pointed to the advantages of nonlinear methods, and indicated a relationship existing between the flow of information and the level of synchronization of the brain.

Cerebrospinal Fluid Biomarkers of Alzheimer's Disease Correlate With Electroencephalography Parameters Assessed by Exact Low-Resolution Electromagnetic Tomography (eLORETA).

PubMed

Hata, Masahiro; Tanaka, Toshihisa; Kazui, Hiroaki; Ishii, Ryouhei; Canuet, Leonides; Pascual-Marqui, Roberto D; Aoki, Yasunori; Ikeda, Shunichiro; Sato, Shunsuke; Suzuki, Yukiko; Kanemoto, Hideki; Yoshiyama, Kenji; Iwase, Masao

2017-09-01

Recently, cerebrospinal fluid (CSF) biomarkers related to Alzheimer's disease (AD) have garnered a lot of clinical attention. To explore neurophysiological traits of AD and parameters for its clinical diagnosis, we examined the association between CSF biomarkers and electroencephalography (EEG) parameters in 14 probable AD patients. Using exact low-resolution electromagnetic tomography (eLORETA), artifact-free 40-sesond EEG data were estimated with current source density (CSD) and lagged phase synchronization (LPS) as the EEG parameters. Correlations between CSF biomarkers and the EEG parameters were assessed. Patients with AD showed significant negative correlation between CSF beta-amyloid (Aβ)-42 concentration and the logarithms of CSD over the right temporal area in the theta band. Total tau concentration was negatively correlated with the LPS between the left frontal eye field and the right auditory area in the alpha-2 band in patients with AD. Our study results suggest that AD biomarkers, in particular CSF Aβ42 and total tau concentrations are associated with the EEG parameters CSD and LPS, respectively. Our results could yield more insights into the complicated pathology of AD.

A novel technique for phase synchrony measurement from the complex motor imaginary potential of combined body and limb action

NASA Astrophysics Data System (ADS)

Zhou, Zhong-xing; Wan, Bai-kun; Ming, Dong; Qi, Hong-zhi

2010-08-01

In this study, we proposed and evaluated the use of the empirical mode decomposition (EMD) technique combined with phase synchronization analysis to investigate the human brain synchrony of the supplementary motor area (SMA) and primary motor area (M1) during complex motor imagination of combined body and limb action. We separated the EEG data of the SMA and M1 into intrinsic mode functions (IMFs) using the EMD method and determined the characteristic IMFs by power spectral density (PSD) analysis. Thereafter, the instantaneous phases of the characteristic IMFs were obtained by the Hilbert transformation, and the single-trial phase-locking value (PLV) features for brain synchrony measurement between the SMA and M1 were investigated separately. The classification performance suggests that the proposed approach is effective for phase synchronization analysis and is promising for the application of a brain-computer interface in motor nerve reconstruction of the lower limbs.

Localization of synchronous cortical neural sources.

PubMed

Zerouali, Younes; Herry, Christophe L; Jemel, Boutheina; Lina, Jean-Marc

2013-03-01

Neural synchronization is a key mechanism to a wide variety of brain functions, such as cognition, perception, or memory. High temporal resolution achieved by EEG recordings allows the study of the dynamical properties of synchronous patterns of activity at a very fine temporal scale but with very low spatial resolution. Spatial resolution can be improved by retrieving the neural sources of EEG signal, thus solving the so-called inverse problem. Although many methods have been proposed to solve the inverse problem and localize brain activity, few of them target the synchronous brain regions. In this paper, we propose a novel algorithm aimed at localizing specifically synchronous brain regions and reconstructing the time course of their activity. Using multivariate wavelet ridge analysis, we extract signals capturing the synchronous events buried in the EEG and then solve the inverse problem on these signals. Using simulated data, we compare results of source reconstruction accuracy achieved by our method to a standard source reconstruction approach. We show that the proposed method performs better across a wide range of noise levels and source configurations. In addition, we applied our method on real dataset and identified successfully cortical areas involved in the functional network underlying visual face perception. We conclude that the proposed approach allows an accurate localization of synchronous brain regions and a robust estimation of their activity.

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.

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

PubMed

Maidhof, Clemens; Kästner, Torsten; Makkonen, Tommi

2014-03-01

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

Beta oscillatory responses in healthy subjects and subjects with mild cognitive impairment☆

PubMed Central

Güntekin, Bahar; Emek-Savaş, Derya Durusu; Kurt, Pınar; Yener, Görsev Gülmen; Başar, Erol

2013-01-01

The aim of the present study was to investigate the role of beta oscillatory responses upon cognitive load in healthy subjects and in subjects with mild cognitive impairment (MCI). The role of beta oscillations upon cognitive stimulation is least studied in comparison to other frequency bands. The study included 17 consecutive patients with MCI (mean age = 70.8 ± 5.6 years) according to Petersen's criteria, and 17 age- and education-matched normal elderly controls (mean age = 68.5 ± 5.5 years). The experiments used a visual oddball paradigm. EEG was recorded at 30 cortical locations. EEG-evoked power, inter-trial phase synchronization, and event-related beta responses filtered in 15–20 Hz were obtained in response to target and non-target stimuli for both groups of subjects. In healthy subjects, EEG-evoked beta power, inter-trial phase synchronization of beta responses and event-related filtered beta responses were significantly higher in responses to target than non-target stimuli (p < 0.05). In MCI patients, there were no differences in evoked beta power between target and non-target stimuli. Furthermore, upon presentation of visual oddball paradigm, occipital electrodes depict higher beta response in comparison to other electrode sites. The increased beta response upon presentation of target stimuli in healthy subjects implies that beta oscillations could shift the system to an attention state, and had important function in cognitive activity. This may, in future, open the way to consider beta activity as an important operator in brain cognitive processes. PMID:24179847

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

PubMed Central

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

2014-01-01

Sleep spindles are a hallmark of NREM sleep. They result from a widespread thalamo-cortical loop and involve synchronous cortical networks that are still poorly understood. We investigated whether brain activity during spindles can be characterized by specific patterns of functional connectivity among cortical generators. For that purpose, we developed a wavelet-based approach aimed at imaging the synchronous oscillatory cortical networks from simultaneous MEG-EEG recordings. First, we detected spindles on the EEG and extracted the corresponding frequency-locked MEG activity under the form of an analytic ridge signal in the time-frequency plane (Zerouali et al., 2013). Secondly, we performed source reconstruction of the ridge signal within the Maximum Entropy on the Mean framework (Amblard et al., 2004), yielding a robust estimate of the cortical sources producing observed oscillations. Lastly, we quantified functional connectivity among cortical sources using phase-locking values. The main innovations of this methodology are (1) to reveal the dynamic behavior of functional networks resolved in the time-frequency plane and (2) to characterize functional connectivity among MEG sources through phase interactions. We showed, for the first time, that the switch from fast to slow oscillatory mode during sleep spindles is required for the emergence of specific patterns of connectivity. Moreover, we show that earlier synchrony during spindles was associated with mainly intra-hemispheric connectivity whereas later synchrony was associated with global long-range connectivity. We propose that our methodology can be a valuable tool for studying the connectivity underlying neural processes involving sleep spindles, such as memory, plasticity or aging. PMID:25389381

Functional brain networks in healthy subjects under acupuncture stimulation: An EEG study based on nonlinear synchronization likelihood analysis

NASA Astrophysics Data System (ADS)

Yu, Haitao; Liu, Jing; Cai, Lihui; Wang, Jiang; Cao, Yibin; Hao, Chongqing

2017-02-01

Electroencephalogram (EEG) signal evoked by acupuncture stimulation at "Zusanli" acupoint is analyzed to investigate the modulatory effect of manual acupuncture on the functional brain activity. Power spectral density of EEG signal is first calculated based on the autoregressive Burg method. It is shown that the EEG power is significantly increased during and after acupuncture in delta and theta bands, but decreased in alpha band. Furthermore, synchronization likelihood is used to estimate the nonlinear correlation between each pairwise EEG signals. By applying a threshold to resulting synchronization matrices, functional networks for each band are reconstructed and further quantitatively analyzed to study the impact of acupuncture on network structure. Graph theoretical analysis demonstrates that the functional connectivity of the brain undergoes obvious change under different conditions: pre-acupuncture, acupuncture, and post-acupuncture. The minimum path length is largely decreased and the clustering coefficient keeps increasing during and after acupuncture in delta and theta bands. It is indicated that acupuncture can significantly modulate the functional activity of the brain, and facilitate the information transmission within different brain areas. The obtained results may facilitate our understanding of the long-lasting effect of acupuncture on the brain function.

Brain coordination dynamics: True and false faces of phase synchrony and metastability

PubMed Central

Tognoli, Emmanuelle; Kelso, J.A. Scott

2009-01-01

Understanding the coordination of multiple parts in a complex system such as the brain is a fundamental challenge. We present a theoretical model of cortical coordination dynamics that shows how brain areas may cooperate (integration) and at the same time retain their functional specificity (segregation). This model expresses a range of desirable properties that the brain is known to exhibit, including self-organization, multi-functionality, metastability and switching. Empirically, the model motivates a thorough investigation of collective phase relationships among brain oscillations in neurophysiological data. The most serious obstacle to interpreting coupled oscillations as genuine evidence of inter-areal coordination in the brain stems from volume conduction of electrical fields. Spurious coupling due to volume conduction gives rise to zero-lag (inphase) and antiphase synchronization whose magnitude and persistence obscure the subtle expression of real synchrony. Through forward modeling and the help of a novel colorimetric method, we show how true synchronization can be deciphered from continuous EEG patterns. Developing empirical efforts along the lines of continuous EEG analysis constitutes a major response to the challenge of understanding how different brain areas work together. Key predictions of cortical coordination dynamics can now be tested thereby revealing the essential modus operandi of the intact living brain. PMID:18938209

Minimizing calibration time using inter-subject information of single-trial recognition of error potentials in brain-computer interfaces.

PubMed

Iturrate, Iñaki; Montesano, Luis; Chavarriaga, Ricardo; del R Millán, Jose; Minguez, Javier

2011-01-01

One of the main problems of both synchronous and asynchronous EEG-based BCIs is the need of an initial calibration phase before the system can be used. This phase is necessary due to the high non-stationarity of the EEG, since it changes between sessions and users. The calibration process limits the BCI systems to scenarios where the outputs are very controlled, and makes these systems non-friendly and exhausting for the users. Although it has been studied how to reduce calibration time for asynchronous signals, it is still an open issue for event-related potentials. Here, we propose the minimization of the calibration time on single-trial error potentials by using classifiers based on inter-subject information. The results show that it is possible to have a classifier with a high performance from the beginning of the experiment, and which is able to adapt itself making the calibration phase shorter and transparent to the user.

Synchronizing MIDI and wireless EEG measurements during natural piano performance.

PubMed

Zamm, Anna; Palmer, Caroline; Bauer, Anna-Katharina R; Bleichner, Martin G; Demos, Alexander P; Debener, Stefan

2017-07-08

Although music performance has been widely studied in the behavioural sciences, less work has addressed the underlying neural mechanisms, perhaps due to technical difficulties in acquiring high-quality neural data during tasks requiring natural motion. The advent of wireless electroencephalography (EEG) presents a solution to this problem by allowing for neural measurement with minimal motion artefacts. In the current study, we provide the first validation of a mobile wireless EEG system for capturing the neural dynamics associated with piano performance. First, we propose a novel method for synchronously recording music performance and wireless mobile EEG. Second, we provide results of several timing tests that characterize the timing accuracy of our system. Finally, we report EEG time domain and frequency domain results from N=40 pianists demonstrating that wireless EEG data capture the unique temporal signatures of musicians' performances with fine-grained precision and accuracy. Taken together, we demonstrate that mobile wireless EEG can be used to measure the neural dynamics of piano performance with minimal motion constraints. This opens many new possibilities for investigating the brain mechanisms underlying music performance. Copyright © 2017 Elsevier B.V. All rights reserved.

Interictal to Ictal Phase Transition in a Small-World Network

NASA Astrophysics Data System (ADS)

Nemzer, Louis; Cravens, Gary; Worth, Robert

Real-time detection and prediction of seizures in patients with epilepsy is essential for rapid intervention. Here, we perform a full Hodgkin-Huxley calculation using n 50 in silico neurons configured in a small-world network topology to generate simulated EEG signals. The connectivity matrix, constructed using a Watts-Strogatz algorithm, admits randomized or deterministic entries. We find that situations corresponding to interictal (non-seizure) and ictal (seizure) states are separated by a phase transition that can be influenced by congenital channelopathies, anticonvulsant drugs, and connectome plasticity. The interictal phase exhibits scale-free phenomena, as characterized by a power law form of the spectral power density, while the ictal state suffers from pathological synchronization. We compare the results with intracranial EEG data and show how these findings may be used to detect or even predict seizure onset. Along with the balance of excitatory and inhibitory factors, the network topology plays a large role in determining the overall characteristics of brain activity. We have developed a new platform for testing the conditions that contribute to the phase transition between non-seizure and seizure states.

Frontal-temporal synchronization of EEG signals quantified by order patterns cross recurrence analysis during propofol anesthesia.

PubMed

Shalbaf, Reza; Behnam, Hamid; Sleigh, Jamie W; Steyn-Ross, D Alistair; Steyn-Ross, Moira L

2015-05-01

Characterizing brain dynamics during anesthesia is a main current challenge in anesthesia study. Several single channel electroencephalogram (EEG)-based commercial monitors like the Bispectral index (BIS) have suggested to examine EEG signal. But, the BIS index has obtained numerous critiques. In this study, we evaluate the concentration-dependent effect of the propofol on long-range frontal-temporal synchronization of EEG signals collected from eight subjects during a controlled induction and recovery design. We used order patterns cross recurrence plot and provide an index named order pattern laminarity (OPL) to assess changes in neuronal synchronization as the mechanism forming the foundation of conscious perception. The prediction probability of 0.9 and 0.84 for OPL and BIS specified that the OPL index correlated more strongly with effect-site propofol concentration. Also, our new index makes faster reaction to transients in EEG recordings based on pharmacokinetic and pharmacodynamic model parameters and demonstrates less variability at the point of loss of consciousness (standard deviation of 0.04 for OPL compared with 0.09 for BIS index). The result show that the OPL index can estimate anesthetic state of patient more efficiently than the BIS index in lightly sedated state with more tolerant of artifacts.

Time-Frequency Analysis of Chemosensory Event-Related Potentials to Characterize the Cortical Representation of Odors in Humans

PubMed Central

Huart, Caroline; Legrain, Valéry; Hummel, Thomas; Rombaux, Philippe; Mouraux, André

2012-01-01

Background The recording of olfactory and trigeminal chemosensory event-related potentials (ERPs) has been proposed as an objective and non-invasive technique to study the cortical processing of odors in humans. Until now, the responses have been characterized mainly using across-trial averaging in the time domain. Unfortunately, chemosensory ERPs, in particular, olfactory ERPs, exhibit a relatively low signal-to-noise ratio. Hence, although the technique is increasingly used in basic research as well as in clinical practice to evaluate people suffering from olfactory disorders, its current clinical relevance remains very limited. Here, we used a time-frequency analysis based on the wavelet transform to reveal EEG responses that are not strictly phase-locked to onset of the chemosensory stimulus. We hypothesized that this approach would significantly enhance the signal-to-noise ratio of the EEG responses to chemosensory stimulation because, as compared to conventional time-domain averaging, (1) it is less sensitive to temporal jitter and (2) it can reveal non phase-locked EEG responses such as event-related synchronization and desynchronization. Methodology/Principal Findings EEG responses to selective trigeminal and olfactory stimulation were recorded in 11 normosmic subjects. A Morlet wavelet was used to characterize the elicited responses in the time-frequency domain. We found that this approach markedly improved the signal-to-noise ratio of the obtained EEG responses, in particular, following olfactory stimulation. Furthermore, the approach allowed characterizing non phase-locked components that could not be identified using conventional time-domain averaging. Conclusion/Significance By providing a more robust and complete view of how odors are represented in the human brain, our approach could constitute the basis for a robust tool to study olfaction, both for basic research and clinicians. PMID:22427997

Synchrony of two uncoupled neurons under half wave sine current stimulation

NASA Astrophysics Data System (ADS)

Peng, Yueping; Wang, Jue; Jian, Zhong

2009-04-01

Two uncoupled Hindmarsh-Rose neurons under different initial discharge patterns are stimulated by the half wave sine current; and the synchronization mechanism of the two neurons is discussed by analyzing their membrane potentials and their interspike interval (ISI) distribution. Under the half wave sine current stimulation, the two uncoupled neurons under different initial conditions, whose parameter r (the parameter r is related to the membrane penetration of calcium ion, and reflects the changing speed of the slow adaptation current) is different or the same, can realize discharge synchronization (phase synchronization) or the full synchronization (state synchronization). The synchronization characteristics are mainly related to the frequency and the amplitude of the half wave sine current, and are little related to the parameter r and the initial state of the two neurons. This investigation shows the mechanism of the current's amplitude and its frequency affecting the synchronization process of neurons, and the neurons' discharge patterns and synchronization process can be adjusted and controlled by the current's amplitude and its frequency. This result is of far reaching importance to study synchronization and encode of many neurons or neural network, and provides the theoretic basis for studying the mechanism of some nervous diseases such as epilepsy and Alzheimer's disease by the slow wave of EEG.

Uppermost synchronized generators of spike-wave activity are localized in limbic cortical areas in late-onset absence status epilepticus.

PubMed

Piros, Palma; Puskas, Szilvia; Emri, Miklos; Opposits, Gabor; Spisak, Tamas; Fekete, Istvan; Clemens, Bela

2014-03-01

Absence status (AS) epilepticus with generalized spike-wave pattern is frequently found in severely ill patients in whom several disease states co-exist. The cortical generators of the ictal EEG pattern and EEG functional connectivity (EEGfC) of this condition are unknown. The present study investigated the localization of the uppermost synchronized generators of spike-wave activity in AS. Seven patients with late-onset AS were investigated by EEG spectral analysis, LORETA (Low Resolution Electromagnetic Tomography) source imaging, and LSC (LORETA Source Correlation) analysis, which estimates cortico-cortical EEGfC among 23 ROIs (regions of interest) in each hemisphere. All the patients showed generalized ictal EEG activity. Maximum Z-scored spectral power was found in the 1-6 Hz and 12-14 Hz frequency bands. LORETA showed that the uppermost synchronized generators of 1-6 Hz band activity were localized in frontal and temporal cortical areas that are parts of the limbic system. For the 12-14 Hz band, abnormally synchronized generators were found in the antero-medial frontal cortex. Unlike the rather stereotyped spectral and LORETA findings, the individual EEGfC patterns were very dissimilar. The findings are discussed in the context of nonconvulsive seizure types and the role of the underlying cortical areas in late-onset AS. The diversity of the EEGfC patterns remains an enigma. Localizing the cortical generators of the EEG patterns contributes to understanding the neurophysiology of the condition. Copyright © 2013 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Use of phase-locking value in sensorimotor rhythm-based brain-computer interface: zero-phase coupling and effects of spatial filters.

PubMed

Jian, Wenjuan; Chen, Minyou; McFarland, Dennis J

2017-11-01

Phase-locking value (PLV) is a potentially useful feature in sensorimotor rhythm-based brain-computer interface (BCI). However, volume conduction may cause spurious zero-phase coupling between two EEG signals and it is not clear whether PLV effects are independent of spectral amplitude. Volume conduction might be reduced by spatial filtering, but it is uncertain what impact this might have on PLV. Therefore, the goal of this study was to explore whether zero-phase PLV is meaningful and how it is affected by spatial filtering. Both amplitude and PLV feature were extracted in the frequency band of 10-15 Hz by classical methods using archival EEG data of 18 subjects trained on a two-target BCI task. The results show that with right ear-referenced data, there is meaningful long-range zero-phase synchronization likely involving the primary motor area and the supplementary motor area that cannot be explained by volume conduction. Another novel finding is that the large Laplacian spatial filter enhances the amplitude feature but eliminates most of the phase information seen in ear-referenced data. A bipolar channel using phase-coupled areas also includes both phase and amplitude information and has a significant practical advantage since fewer channels required.

DCCA cross-correlation coefficients reveals the change of both synchronization and oscillation in EEG of Alzheimer disease patients

NASA Astrophysics Data System (ADS)

Chen, Yingyuan; Cai, Lihui; Wang, Ruofan; Song, Zhenxi; Deng, Bin; Wang, Jiang; Yu, Haitao

2018-01-01

Alzheimer's disease (AD) is a degenerative disorder of neural system that affects mainly the older population. Recently, many researches show that the EEG of AD patients can be characterized by EEG slowing, enhanced complexity of the EEG signals, and EEG synchrony. In order to examine the neural synchrony at multi scales, and to find a biomarker that help detecting AD in diagnosis, detrended cross-correlation analysis (DCCA) of EEG signals is applied in this paper. Several parameters, namely DCCA coefficients in the whole brain, DCCA coefficients at a specific scale, maximum DCCA coefficient over the span of all time scales and the corresponding scale of such coefficients, were extracted to examine the synchronization, respectively. The results show that DCCA coefficients have a trend of increase as scale increases, and decreases as electrode distance increases. Comparing DCCA coefficients in AD patients with healthy controls, a decrease of synchronization in the whole brain, and a bigger scale corresponding to maximum correlation is discovered in AD patients. The change of max-correlation scale may relate to the slowing of oscillatory activities. Linear combination of max DCCA coefficient and max-correlation scale reaches a classification accuracy of 90%. From the above results, it is reasonable to conclude that DCCA coefficient reveals the change of both oscillation and synchrony in AD, and thus is a powerful tool to differentiate AD patients from healthy elderly individuals.

Methodological aspects of EEG and body dynamics measurements during motion

PubMed Central

Reis, Pedro M. R.; Hebenstreit, Felix; Gabsteiger, Florian; von Tscharner, Vinzenz; Lochmann, Matthias

2014-01-01

EEG involves the recording, analysis, and interpretation of voltages recorded on the human scalp which originate from brain gray matter. EEG is one of the most popular methods of studying and understanding the processes that underlie behavior. This is so, because EEG is relatively cheap, easy to wear, light weight and has high temporal resolution. In terms of behavior, this encompasses actions, such as movements that are performed in response to the environment. However, there are methodological difficulties which can occur when recording EEG during movement such as movement artifacts. Thus, most studies about the human brain have examined activations during static conditions. This article attempts to compile and describe relevant methodological solutions that emerged in order to measure body and brain dynamics during motion. These descriptions cover suggestions on how to avoid and reduce motion artifacts, hardware, software and techniques for synchronously recording EEG, EMG, kinematics, kinetics, and eye movements during motion. Additionally, we present various recording systems, EEG electrodes, caps and methods for determinating real/custom electrode positions. In the end we will conclude that it is possible to record and analyze synchronized brain and body dynamics related to movement or exercise tasks. PMID:24715858

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.

Genetic influences on functional connectivity associated with feedback processing and prediction error: Phase coupling of theta-band oscillations in twins.

PubMed

Demiral, Şükrü Barış; Golosheykin, Simon; Anokhin, Andrey P

2017-05-01

Detection and evaluation of the mismatch between the intended and actually obtained result of an action (reward prediction error) is an integral component of adaptive self-regulation of behavior. Extensive human and animal research has shown that evaluation of action outcome is supported by a distributed network of brain regions in which the anterior cingulate cortex (ACC) plays a central role, and the integration of distant brain regions into a unified feedback-processing network is enabled by long-range phase synchronization of cortical oscillations in the theta band. Neural correlates of feedback processing are associated with individual differences in normal and abnormal behavior, however, little is known about the role of genetic factors in the cerebral mechanisms of feedback processing. Here we examined genetic influences on functional cortical connectivity related to prediction error in young adult twins (age 18, n=399) using event-related EEG phase coherence analysis in a monetary gambling task. To identify prediction error-specific connectivity pattern, we compared responses to loss and gain feedback. Monetary loss produced a significant increase of theta-band synchronization between the frontal midline region and widespread areas of the scalp, particularly parietal areas, whereas gain resulted in increased synchrony primarily within the posterior regions. Genetic analyses showed significant heritability of frontoparietal theta phase synchronization (24 to 46%), suggesting that individual differences in large-scale network dynamics are under substantial genetic control. We conclude that theta-band synchronization of brain oscillations related to negative feedback reflects genetically transmitted differences in the neural mechanisms of feedback processing. To our knowledge, this is the first evidence for genetic influences on task-related functional brain connectivity assessed using direct real-time measures of neuronal synchronization. Copyright © 2016 Elsevier B.V. All rights reserved.

Motif-Synchronization: A new method for analysis of dynamic brain networks with EEG

NASA Astrophysics Data System (ADS)

Rosário, R. S.; Cardoso, P. T.; Muñoz, M. A.; Montoya, P.; Miranda, J. G. V.

2015-12-01

The major aim of this work was to propose a new association method known as Motif-Synchronization. This method was developed to provide information about the synchronization degree and direction between two nodes of a network by counting the number of occurrences of some patterns between any two time series. The second objective of this work was to present a new methodology for the analysis of dynamic brain networks, by combining the Time-Varying Graph (TVG) method with a directional association method. We further applied the new algorithms to a set of human electroencephalogram (EEG) signals to perform a dynamic analysis of the brain functional networks (BFN).

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

PubMed

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

2015-08-01

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

Spherical Harmonics Reveal Standing EEG Waves and Long-Range Neural Synchronization during Non-REM Sleep.

PubMed

Sivakumar, Siddharth S; Namath, Amalia G; Galán, Roberto F

2016-01-01

Previous work from our lab has demonstrated how the connectivity of brain circuits constrains the repertoire of activity patterns that those circuits can display. Specifically, we have shown that the principal components of spontaneous neural activity are uniquely determined by the underlying circuit connections, and that although the principal components do not uniquely resolve the circuit structure, they do reveal important features about it. Expanding upon this framework on a larger scale of neural dynamics, we have analyzed EEG data recorded with the standard 10-20 electrode system from 41 neurologically normal children and adolescents during stage 2, non-REM sleep. We show that the principal components of EEG spindles, or sigma waves (10-16 Hz), reveal non-propagating, standing waves in the form of spherical harmonics. We mathematically demonstrate that standing EEG waves exist when the spatial covariance and the Laplacian operator on the head's surface commute. This in turn implies that the covariance between two EEG channels decreases as the inverse of their relative distance; a relationship that we corroborate with empirical data. Using volume conduction theory, we then demonstrate that superficial current sources are more synchronized at larger distances, and determine the characteristic length of large-scale neural synchronization as 1.31 times the head radius, on average. Moreover, consistent with the hypothesis that EEG spindles are driven by thalamo-cortical rather than cortico-cortical loops, we also show that 8 additional patients with hypoplasia or complete agenesis of the corpus callosum, i.e., with deficient or no connectivity between cortical hemispheres, similarly exhibit standing EEG waves in the form of spherical harmonics. We conclude that spherical harmonics are a hallmark of spontaneous, large-scale synchronization of neural activity in the brain, which are associated with unconscious, light sleep. The analogy with spherical harmonics in quantum mechanics suggests that the variances (eigenvalues) of the principal components follow a Boltzmann distribution, or equivalently, that standing waves are in a sort of "thermodynamic" equilibrium during non-REM sleep. By extension, we speculate that consciousness emerges as the brain dynamics deviate from such equilibrium.

Spherical Harmonics Reveal Standing EEG Waves and Long-Range Neural Synchronization during Non-REM Sleep

PubMed Central

Sivakumar, Siddharth S.; Namath, Amalia G.; Galán, Roberto F.

2016-01-01

Previous work from our lab has demonstrated how the connectivity of brain circuits constrains the repertoire of activity patterns that those circuits can display. Specifically, we have shown that the principal components of spontaneous neural activity are uniquely determined by the underlying circuit connections, and that although the principal components do not uniquely resolve the circuit structure, they do reveal important features about it. Expanding upon this framework on a larger scale of neural dynamics, we have analyzed EEG data recorded with the standard 10–20 electrode system from 41 neurologically normal children and adolescents during stage 2, non-REM sleep. We show that the principal components of EEG spindles, or sigma waves (10–16 Hz), reveal non-propagating, standing waves in the form of spherical harmonics. We mathematically demonstrate that standing EEG waves exist when the spatial covariance and the Laplacian operator on the head's surface commute. This in turn implies that the covariance between two EEG channels decreases as the inverse of their relative distance; a relationship that we corroborate with empirical data. Using volume conduction theory, we then demonstrate that superficial current sources are more synchronized at larger distances, and determine the characteristic length of large-scale neural synchronization as 1.31 times the head radius, on average. Moreover, consistent with the hypothesis that EEG spindles are driven by thalamo-cortical rather than cortico-cortical loops, we also show that 8 additional patients with hypoplasia or complete agenesis of the corpus callosum, i.e., with deficient or no connectivity between cortical hemispheres, similarly exhibit standing EEG waves in the form of spherical harmonics. We conclude that spherical harmonics are a hallmark of spontaneous, large-scale synchronization of neural activity in the brain, which are associated with unconscious, light sleep. The analogy with spherical harmonics in quantum mechanics suggests that the variances (eigenvalues) of the principal components follow a Boltzmann distribution, or equivalently, that standing waves are in a sort of “thermodynamic” equilibrium during non-REM sleep. By extension, we speculate that consciousness emerges as the brain dynamics deviate from such equilibrium. PMID:27445777

Method for Improving EEG Based Emotion Recognition by Combining It with Synchronized Biometric and Eye Tracking Technologies in a Non-invasive and Low Cost Way

PubMed Central

López-Gil, Juan-Miguel; Virgili-Gomá, Jordi; Gil, Rosa; Guilera, Teresa; Batalla, Iolanda; Soler-González, Jorge; García, Roberto

2016-01-01

Technical advances, particularly the integration of wearable and embedded sensors, facilitate tracking of physiological responses in a less intrusive way. Currently, there are many devices that allow gathering biometric measurements from human beings, such as EEG Headsets or Health Bracelets. The massive data sets generated by tracking of EEG and physiology may be used, among other things, to infer knowledge about human moods and emotions. Apart from direct biometric signal measurement, eye tracking systems are nowadays capable of determining the point of gaze of the users when interacting in ICT environments, which provides an added value research on many different areas, such as psychology or marketing. We present a process in which devices for eye tracking, biometric, and EEG signal measurements are synchronously used for studying both basic and complex emotions. We selected the least intrusive devices for different signal data collection given the study requirements and cost constraints, so users would behave in the most natural way possible. On the one hand, we have been able to determine basic emotions participants were experiencing by means of valence and arousal. On the other hand, a complex emotion such as empathy has also been detected. To validate the usefulness of this approach, a study involving forty-four people has been carried out, where they were exposed to a series of affective stimuli while their EEG activity, biometric signals, and eye position were synchronously recorded to detect self-regulation. The hypothesis of the work was that people who self-regulated would show significantly different results when analyzing their EEG data. Participants were divided into two groups depending on whether Electro Dermal Activity (EDA) data indicated they self-regulated or not. The comparison of the results obtained using different machine learning algorithms for emotion recognition shows that using EEG activity alone as a predictor for self-regulation does not allow properly determining whether a person in self-regulation its emotions while watching affective stimuli. However, adequately combining different data sources in a synchronous way to detect emotions makes it possible to overcome the limitations of single detection methods. PMID:27594831

Method for Improving EEG Based Emotion Recognition by Combining It with Synchronized Biometric and Eye Tracking Technologies in a Non-invasive and Low Cost Way.

PubMed

López-Gil, Juan-Miguel; Virgili-Gomá, Jordi; Gil, Rosa; García, Roberto

2016-01-01

Technical advances, particularly the integration of wearable and embedded sensors, facilitate tracking of physiological responses in a less intrusive way. Currently, there are many devices that allow gathering biometric measurements from human beings, such as EEG Headsets or Health Bracelets. The massive data sets generated by tracking of EEG and physiology may be used, among other things, to infer knowledge about human moods and emotions. Apart from direct biometric signal measurement, eye tracking systems are nowadays capable of determining the point of gaze of the users when interacting in ICT environments, which provides an added value research on many different areas, such as psychology or marketing. We present a process in which devices for eye tracking, biometric, and EEG signal measurements are synchronously used for studying both basic and complex emotions. We selected the least intrusive devices for different signal data collection given the study requirements and cost constraints, so users would behave in the most natural way possible. On the one hand, we have been able to determine basic emotions participants were experiencing by means of valence and arousal. On the other hand, a complex emotion such as empathy has also been detected. To validate the usefulness of this approach, a study involving forty-four people has been carried out, where they were exposed to a series of affective stimuli while their EEG activity, biometric signals, and eye position were synchronously recorded to detect self-regulation. The hypothesis of the work was that people who self-regulated would show significantly different results when analyzing their EEG data. Participants were divided into two groups depending on whether Electro Dermal Activity (EDA) data indicated they self-regulated or not. The comparison of the results obtained using different machine learning algorithms for emotion recognition shows that using EEG activity alone as a predictor for self-regulation does not allow properly determining whether a person in self-regulation its emotions while watching affective stimuli. However, adequately combining different data sources in a synchronous way to detect emotions makes it possible to overcome the limitations of single detection methods.

Reward Expectation Modulates Feedback-Related Negativity and EEG Spectra

PubMed Central

Cohen, Michael X; Elger, Christian E.; Ranganath, Charan

2007-01-01

The ability to evaluate outcomes of previous decisions is critical to adaptive decision-making. The feedback-related negativity (FRN) is an event-related potential (ERP) modulation that distinguishes losses from wins, but little is known about the effects of outcome probability on these ERP responses. Further, little is known about the frequency characteristics of feedback processing, for example, event-related oscillations and phase synchronizations. Here, we report an EEG experiment designed to address these issues. Subjects engaged in a probabilistic reinforcement learning task in which we manipulated, across blocks, the probability of winning and losing to each of two possible decision options. Behaviorally, all subjects quickly adapted their decision-making to maximize rewards. ERP analyses revealed that the probability of reward modulated neural responses to wins, but not to losses. This was seen both across blocks as well as within blocks, as learning progressed. Frequency decomposition via complex wavelets revealed that EEG responses to losses, compared to wins, were associated with enhanced power and phase coherence in the theta frequency band. As in the ERP analyses, power and phase coherence values following wins but not losses were modulated by reward probability. Some findings between ERP and frequency analyses diverged, suggesting that these analytic approaches provide complementary insights into neural processing. These findings suggest that the neural mechanisms of feedback processing may differ between wins and losses. PMID:17257860

Objective response detection in an electroencephalogram during somatosensory stimulation.

PubMed

Simpson, D M; Tierra-Criollo, C J; Leite, R T; Zayen, E J; Infantosi, A F

2000-06-01

Techniques for objective response detection aim to identify the presence of evoked potentials based purely on statistical principles. They have been shown to be potentially more sensitive than the conventional approach of subjective evaluation by experienced clinicians and could be of great clinical use. Three such techniques to detect changes in an electroencephalogram (EEG) synchronous with the stimuli, namely, magnitude-squared coherence (MSC), the phase-synchrony measure (PSM) and the spectral F test (SFT) were applied to EEG signals of 12 normal subjects under conventional somatosensory pulse stimulation to the tibial nerve. The SFT, which uses only the power spectrum, showed the poorest performance, while the PSM, based only on the phase spectrum, gave results almost as good as those of the MSC, which uses both phase and power spectra. With the latter two techniques, stimulus responses were evident in the frequency range of 20-80 Hz in all subjects after 200 stimuli (5 Hz stimulus frequency), whereas for visual recognition at least 500 stimuli are usually applied. Based on these results and on simulations, the phase-based techniques appear promising for the automated detection and monitoring of somatosensory evoked potentials.

Cortical light scattering during interictal epileptic spikes in frontal lobe epilepsy in children: A fast optical signal and electroencephalographic study.

PubMed

Manoochehri, Mana; Mahmoudzadeh, Mahdi; Bourel-Ponchel, Emilie; Wallois, Fabrice

2017-12-01

Interictal epileptic spikes (IES) represent a signature of the transient synchronous and excessive discharge of a large ensemble of cortical heterogeneous neurons. Epilepsy cannot be reduced to a hypersynchronous activation of neurons whose functioning is impaired, resulting on electroencephalogram (EEG) in epileptic seizures or IES. The complex pathophysiological mechanisms require a global approach to the interactions between neural synaptic and nonsynaptic, vascular, and metabolic systems. In the present study, we focused on the interaction between synaptic and nonsynaptic mechanisms through the simultaneous noninvasive multimodal multiscale recording of high-density EEG (HD-EEG; synaptic) and fast optical signal (FOS; nonsynaptic), which evaluate rapid changes in light scattering related to changes in membrane configuration occurring during neuronal activation of IES. To evaluate changes in light scattering occurring around IES, three children with frontal IES were simultaneously recorded with HD-EEG and FOS. To evaluate change in synchronization, time-frequency representation analysis of the HD-EEG was performed simultaneously around the IES. To independently evaluate our multimodal method, a control experiment with somatosensory stimuli was designed and applied to five healthy volunteers. Alternating increase-decrease-increase in optical signals occurred 200 ms before to 180 ms after the IES peak. These changes started before any changes in EEG signal. In addition, time-frequency domain EEG analysis revealed alternating decrease-increase-decrease in the EEG spectral power concomitantly with changes in the optical signal during IES. These results suggest a relationship between (de)synchronization and neuronal volume changes in frontal lobe epilepsy during IES. These changes in the neuronal environment around IES in frontal lobe epilepsy observed in children, as they have been in rats, raise new questions about the synaptic/nonsynaptic mechanisms that propel the neurons to hypersynchronization, as occurs during IES. We further demonstrate that this noninvasive multiscale multimodal approach is suitable for studying the pathophysiology of the IES in patients. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

The effects of music on brain functional networks: a network analysis.

PubMed

Wu, J; Zhang, J; Ding, X; Li, R; Zhou, C

2013-10-10

The human brain can dynamically adapt to the changing surroundings. To explore this issue, we adopted graph theoretical tools to examine changes in electroencephalography (EEG) functional networks while listening to music. Three different excerpts of Chinese Guqin music were played to 16 non-musician subjects. For the main frequency intervals, synchronizations between all pair-wise combinations of EEG electrodes were evaluated with phase lag index (PLI). Then, weighted connectivity networks were created and their organizations were characterized in terms of an average clustering coefficient and characteristic path length. We found an enhanced synchronization level in the alpha2 band during music listening. Music perception showed a decrease of both normalized clustering coefficient and path length in the alpha2 band. Moreover, differences in network measures were not observed between musical excerpts. These experimental results demonstrate an increase of functional connectivity as well as a more random network structure in the alpha2 band during music perception. The present study offers support for the effects of music on human brain functional networks with a trend toward a more efficient but less economical architecture. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

Alterations in post-movement beta event related synchronization throughout the migraine cycle: A controlled, longitudinal study.

PubMed

Mykland, Martin Syvertsen; Bjørk, Marte Helene; Stjern, Marit; Sand, Trond

2018-04-01

Background The migraine brain is believed to have altered cortical excitability compared to controls and between migraine cycle phases. Our aim was to evaluate post-activation excitability through post-movement beta event related synchronization (PMBS) in sensorimotor cortices with and without sensory discrimination. Subjects and methods We recorded EEG of 41 migraine patients and 31 healthy controls on three different days with classification of days in relation to migraine phases. During each recording, subjects performed one motor and one sensorimotor task with the right wrist. Controls and migraine patients in the interictal phase were compared with repeated measures (R-) ANOVA and two sample Student's t-test. Migraine phases were compared to the interictal phase with R-ANOVA and paired Student's t-test. Results The difference between PMBS at the contralateral and ipsilateral sensorimotor cortex was altered throughout the migraine cycle. Compared to the interictal phase, we found decreased PMBS at the ipsilateral sensorimotor cortex in the ictal phase and increased PMBS in the preictal phase. Lower ictal PMBS was found in bilateral sensorimotor cortices in patients with right side headache predominance. Conclusion The cyclic changes of PMBS in migraine patients may indicate that a dysfunction in deactivation and interhemispheric inhibition of the sensorimotor cortex is involved in the migraine attack cascade.

Evaluating the event-related synchronization and desynchronization by means of a statistical frequency test.

PubMed

Miranda de Sá, Antonio Mauricio F L; Infantosi, Antonio Fernando C; Lazarev, Vladimir V

2007-01-01

In the present work, a commonly used index for evaluating the Event-Related Synchronization and Desynchronization (ERS/ERD) in the EEG was expressed as a function of the Spectral F-Test (SFT), which is a statistical test for assessing if two sample spectra are from populations with identical theoretical spectra. The sampling distribution of SFT has been derived, allowing hence ERS/ERD to be evaluated under a statistical basis. An example of the technique was also provided in the EEG signals from 10 normal subjects during intermittent photic stimulation.

Graph theoretical analysis of EEG functional connectivity during music perception.

PubMed

Wu, Junjie; Zhang, Junsong; Liu, Chu; Liu, Dongwei; Ding, Xiaojun; Zhou, Changle

2012-11-05

The present study evaluated the effect of music on large-scale structure of functional brain networks using graph theoretical concepts. While most studies on music perception used Western music as an acoustic stimulus, Guqin music, representative of Eastern music, was selected for this experiment to increase our knowledge of music perception. Electroencephalography (EEG) was recorded from non-musician volunteers in three conditions: Guqin music, noise and silence backgrounds. Phase coherence was calculated in the alpha band and between all pairs of EEG channels to construct correlation matrices. Each resulting matrix was converted into a weighted graph using a threshold, and two network measures: the clustering coefficient and characteristic path length were calculated. Music perception was found to display a higher level mean phase coherence. Over the whole range of thresholds, the clustering coefficient was larger while listening to music, whereas the path length was smaller. Networks in music background still had a shorter characteristic path length even after the correction for differences in mean synchronization level among background conditions. This topological change indicated a more optimal structure under music perception. Thus, prominent small-world properties are confirmed in functional brain networks. Furthermore, music perception shows an increase of functional connectivity and an enhancement of small-world network organizations. Copyright © 2012 Elsevier B.V. All rights reserved.

Capturing with EEG the neural entrainment and coupling underlying sensorimotor synchronization to the beat.

PubMed

Nozaradan, Sylvie; Zerouali, Younes; Peretz, Isabelle; Mouraux, André

2015-03-01

Synchronizing movements with rhythmic inputs requires tight coupling of sensory and motor neural processes. Here, using a novel approach based on the recording of steady-state-evoked potentials (SS-EPs), we examine how distant brain areas supporting these processes coordinate their dynamics. The electroencephalogram was recorded while subjects listened to a 2.4-Hz auditory beat and tapped their hand on every second beat. When subjects tapped to the beat, the EEG was characterized by a 2.4-Hz SS-EP compatible with beat-related entrainment and a 1.2-Hz SS-EP compatible with movement-related entrainment, based on the results of source analysis. Most importantly, when compared with passive listening of the beat, we found evidence suggesting an interaction between sensory- and motor-related activities when subjects tapped to the beat, in the form of (1) additional SS-EP appearing at 3.6 Hz, compatible with a nonlinear product of sensorimotor integration; (2) phase coupling of beat- and movement-related activities; and (3) selective enhancement of beat-related activities over the hemisphere contralateral to the tapping, suggesting a top-down effect of movement-related activities on auditory beat processing. Taken together, our results are compatible with the view that rhythmic sensorimotor synchronization is supported by a dynamic coupling of sensory and motor related activities. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Listening to a baby crying induces higher electroencephalographic synchronization among prefrontal, temporal and parietal cortices in adoptive mothers.

PubMed

Pérez-Hernández, M; Hernández-González, M; Hidalgo-Aguirre, R M; Amezcua-Gutiérrez, C; Guevara, M A

2017-05-01

Women who adopt babies show caring behaviors and respond to stimuli from their infants just as biological mothers do, but several studies have shown that the cerebral functionality of biological mothers (BM) and adoptive mothers (AM) changes in relation to the type and emotional mean of the stimuli they receive from their babies. The complex perception and processing of different stimuli with emotional content (such as those emitted by babies) require functional synchronization among different cortical and subcortical brain areas. To determine whether the degree of functional synchronization between cortices varies when they perceive such stimuli, this study characterized the degree of cortical electroencephalographic (EEG) synchronization (correlation) among prefrontal, temporal and parietal areas in BM, AM and non-mothers while listening to a recording of a baby crying. BM showed a decreased EEG synchronization between the prefrontal and temporal cortices that may indicate a decrease in the modulatory control that the former exerts on the posterior cortices, and could be associated with deeper emotional involvement and increased sensitivity to the baby crying. The AM, in contrast, had higher degree of EEG synchronization between cortical areas in both hemispheres, likely associated with a greater modulation of the affective information of the crying baby, which allowed them to perceive it as less unpleasant. These data enrich our knowledge of the neurofunctional changes involved in motherhood, and of the neural processes that allow mothers (biological and adoptive) to be sensitive to their infants' cues and respond appropriately. Copyright © 2017 Elsevier Inc. All rights reserved.

Relative electroencephalographic desynchronization and synchronization in humans to emotional film content: an analysis of the 4-6, 6-8, 8-10 and 10-12 Hz frequency bands.

PubMed

Krause, C M; Viemerö, V; Rosenqvist, A; Sillanmäki, L; Aström, T

2000-05-26

The reactivity of different narrow electroencephalographic (EEG) frequencies (4-6, 6-8, 8-10 and 10-12 Hz) to three types of emotionally laden film clips (aggressive, sad, neutral) were examined. We observed that different EEG frequency bands responded differently to the three types of film content. In the 4-6 Hz frequency band, the viewing of aggressive film content elicited greater relative synchronization as compared the responses elicited by the viewing of sad and neutral film content. The 6-8 Hz and 8-10 Hz frequency bands exhibited reactivity to the chronological succession of film viewing whereas the responses of the 10-12 Hz frequency band evolved within minutes during film viewing. Our results propose dissociations between the responses of different frequencies within the EEG to different emotion-related stimuli. Narrow frequency band EEG analysis offers an adequate tool for studying cortical activation patterns during emotion-related information processing.

Macroscopic and microscopic spectral properties of brain networks during local and global synchronization

NASA Astrophysics Data System (ADS)

Maksimenko, Vladimir A.; Lüttjohann, Annika; Makarov, Vladimir V.; Goremyko, Mikhail V.; Koronovskii, Alexey A.; Nedaivozov, Vladimir; Runnova, Anastasia E.; van Luijtelaar, Gilles; Hramov, Alexander E.; Boccaletti, Stefano

2017-07-01

We introduce a practical and computationally not demanding technique for inferring interactions at various microscopic levels between the units of a network from the measurements and the processing of macroscopic signals. Starting from a network model of Kuramoto phase oscillators, which evolve adaptively according to homophilic and homeostatic adaptive principles, we give evidence that the increase of synchronization within groups of nodes (and the corresponding formation of synchronous clusters) causes also the defragmentation of the wavelet energy spectrum of the macroscopic signal. Our methodology is then applied to getting a glance into the microscopic interactions occurring in a neurophysiological system, namely, in the thalamocortical neural network of an epileptic brain of a rat, where the group electrical activity is registered by means of multichannel EEG. We demonstrate that it is possible to infer the degree of interaction between the interconnected regions of the brain during different types of brain activities and to estimate the regions' participation in the generation of the different levels of consciousness.

Trajectory of frequency stability in typical development.

PubMed

Frohlich, Joel; Irimia, Andrei; Jeste, Shafali S

2015-03-01

This work explores a feature of brain dynamics, metastability, by which transients are observed in functional brain data. Metastability is a balance between static (stable) and dynamic (unstable) tendencies in electrophysiological brain activity. Furthermore, metastability is a theoretical mechanism underlying the rapid synchronization of cell assemblies that serve as neural substrates for cognitive states, and it has been associated with cognitive flexibility. While much previous research has sought to characterize metastability in the adult human brain, few studies have examined metastability in early development, in part because of the challenges of acquiring adequate, noise free continuous data in young children. To accomplish this endeavor, we studied a new method for characterizing the stability of EEG frequency in early childhood, as inspired by prior approaches for describing cortical phase resets in the scalp EEG of healthy adults. Specifically, we quantified the variance of the rate of change of the signal phase (i.e., frequency) as a proxy for phase resets (signal instability), given that phase resets occur almost simultaneously across large portions of the scalp. We tested our method in a cohort of 39 preschool age children (age =53 ± 13.6 months). We found that our outcome variable of interest, frequency variance, was a promising marker of signal stability, as it increased with the number of phase resets in surrogate (artificial) signals. In our cohort of children, frequency variance decreased cross-sectionally with age (r = -0.47, p = 0.0028). EEG signal stability, as quantified by frequency variance, increases with age in preschool age children. Future studies will relate this biomarker with the development of executive function and cognitive flexibility in children, with the overarching goal of understanding metastability in atypical development.

Characteristic phasic evolution of convulsive seizure in PCDH19-related epilepsy.

PubMed

Ikeda, Hiroko; Imai, Katsumi; Ikeda, Hitoshi; Shigematsu, Hideo; Takahashi, Yukitoshi; Inoue, Yushi; Higurashi, Norimichi; Hirose, Shinichi

2016-03-01

PCDH19-related epilepsy is a genetic disorder that was first described in 1971, then referred to as "epilepsy and mental retardation limited to females". PCDH19 has recently been identified as the responsible gene, but a detailed characterization of the seizure manifestation based on video-EEG recording is still limited. The purpose of this study was to elucidate features of the seizure semiology in children with PCDH19-related epilepsy. To do this, ictal video-EEG recordings of 26 convulsive seizures in three girls with PCDH19-related epilepsy were analysed. All seizures occurred in clusters, mainly during sleep accompanied by fever. The motor manifestations consisted of six sequential phases: "jerk", "reactive", "mild tonic", "fluttering", "mild clonic", and "postictal". Some phases were brief or lacking in some seizures, whereas others were long or pronounced. In the reactive phase, the patients looked fearful or startled with sudden jerks and turned over reactively. The tonic and clonic components were less intense compared with those of typical tonic-clonic seizures in other types of epilepsy. The fluttering phase was characterised initially by asymmetric, less rhythmic, and less synchronous tremulous movement and was then followed by the subtle clonic phase. Subtle oral automatism was observed in the postictal phase. The reactive, mild tonic, fluttering and mild clonic phases were most characteristic of seizures of PCDH19-related epilepsy. Ictal EEG started bilaterally and was symmetric in some patients but asymmetric in others. It showed asymmetric rhythmic discharges in some seizures at later phases. The electroclinical pattern of the phasic evolution of convulsive seizure suggests a focal onset seizure with secondary generalisation. Based on our findings, we propose that the six unique sequential phases in convulsive seizures suggest the diagnosis of PCDH19-related epilepsy when occurring in clusters with or without high fever in girls. [Published with video sequences online].

Finding brain oscillations with power dependencies in neuroimaging data.

PubMed

Dähne, Sven; Nikulin, Vadim V; Ramírez, David; Schreier, Peter J; Müller, Klaus-Robert; Haufe, Stefan

2014-08-01

Phase synchronization among neuronal oscillations within the same frequency band has been hypothesized to be a major mechanism for communication between different brain areas. On the other hand, cross-frequency communications are more flexible allowing interactions between oscillations with different frequencies. Among such cross-frequency interactions amplitude-to-amplitude interactions are of a special interest as they show how the strength of spatial synchronization in different neuronal populations relates to each other during a given task. While, previously, amplitude-to-amplitude correlations were studied primarily on the sensor level, we present a source separation approach using spatial filters which maximize the correlation between the envelopes of brain oscillations recorded with electro-/magnetoencephalography (EEG/MEG) or intracranial multichannel recordings. Our approach, which is called canonical source power correlation analysis (cSPoC), is thereby capable of extracting genuine brain oscillations solely based on their assumed coupling behavior even when the signal-to-noise ratio of the signals is low. In addition to using cSPoC for the analysis of cross-frequency interactions in the same subject, we show that it can also be utilized for studying amplitude dynamics of neuronal oscillations across subjects. We assess the performance of cSPoC in simulations as well as in three distinctively different analysis scenarios of real EEG data, each involving several subjects. In the simulations, cSPoC outperforms unsupervised state-of-the-art approaches. In the analysis of real EEG recordings, we demonstrate excellent unsupervised discovery of meaningful power-to-power couplings, within as well as across subjects and frequency bands. Copyright © 2014 Elsevier Inc. All rights reserved.

A case of schizencephaly has a normal surface EEG but abnormal intracranial EEG: epilepsia partialis continua or dystonia?

PubMed

Lv, Yudan; Ma, Dihui; Meng, Hongmei; Zan, Wang; Li, Cui

2013-10-01

Schizencephaly is a congenital malformation of the cerebral hemispheres, with communication between the lateral ventricle and the subarachnoid space. Marinelli reported that schizencephaly may be associated with continuous involuntary hand movements, such as dystonia or epilepsia partialis continua (EPC). We describe a young Chinese patient with continuous involuntary movements of the contralateral hand affected by schizencephaly. He has a normal scalp electroencephalogram (EEG) but abnormal intracranial EEG, with synchronized periodic lateralized epileptiform discharges. The results obtained from these EEG investigations and the clinical features of the involuntary movements are in favor of a diagnosis of secondary EPC.

Frontal theta and beta synchronizations for monetary reward increase visual working memory capacity

PubMed Central

Yamaguchi, Yoko

2013-01-01

Visual working memory (VWM) capacity is affected by motivational influences; however, little is known about how reward-related brain activities facilitate the VWM systems. To investigate the dynamic relationship between VWM- and reward-related brain activities, we conducted time–frequency analyses using electroencephalograph (EEG) data obtained during a monetary-incentive delayed-response task that required participants to memorize the position of colored disks. In case of a correct answer, participants received a monetary reward (0, 10 or 50 Japanese yen) announced at the beginning of each trial. Behavioral results showed that VWM capacity under high-reward condition significantly increased compared with that under low- or no-reward condition. EEG results showed that frontal theta (6 Hz) amplitudes enhanced during delay periods and positively correlated with VWM capacity, indicating involvement of theta local synchronizations in VWM. Moreover, frontal beta activities (24 Hz) were identified as reward-related activities, because delay-period amplitudes correlated with increases in VWM capacity between high-reward and no-reward conditions. Interestingly, cross-frequency couplings between frontal theta and beta phases were observed only under high-reward conditions. These findings suggest that the functional dynamic linking between VWM-related theta and reward-related beta activities on the frontal regions plays an integral role in facilitating increases in VWM capacity. PMID:22349800

Frontal theta and beta synchronizations for monetary reward increase visual working memory capacity.

PubMed

Kawasaki, Masahiro; Yamaguchi, Yoko

2013-06-01

Visual working memory (VWM) capacity is affected by motivational influences; however, little is known about how reward-related brain activities facilitate the VWM systems. To investigate the dynamic relationship between VWM- and reward-related brain activities, we conducted time-frequency analyses using electroencephalograph (EEG) data obtained during a monetary-incentive delayed-response task that required participants to memorize the position of colored disks. In case of a correct answer, participants received a monetary reward (0, 10 or 50 Japanese yen) announced at the beginning of each trial. Behavioral results showed that VWM capacity under high-reward condition significantly increased compared with that under low- or no-reward condition. EEG results showed that frontal theta (6 Hz) amplitudes enhanced during delay periods and positively correlated with VWM capacity, indicating involvement of theta local synchronizations in VWM. Moreover, frontal beta activities (24 Hz) were identified as reward-related activities, because delay-period amplitudes correlated with increases in VWM capacity between high-reward and no-reward conditions. Interestingly, cross-frequency couplings between frontal theta and beta phases were observed only under high-reward conditions. These findings suggest that the functional dynamic linking between VWM-related theta and reward-related beta activities on the frontal regions plays an integral role in facilitating increases in VWM capacity.

[The comparative analysis of changes of short pieces of EEG at perception of music on the basis of the event-related synchronization/desynchronization and wavelet-synchrony].

PubMed

Oknina, L B; Kuptsova, S V; Romanov, A S; Masherov, E L; Kuznetsova, O A; Sharova, E V

2012-01-01

The going of present pilot study is an analysis of features changes of EEG short pieces registered from 32 sites, at perception of musical melodies healthy examinees depending on logic (cognizance) and emotional (it was pleasant it was not pleasant) melody estimations. For this purpose changes of event-related synchronization/desynchronization, and also wavelet-synchrony of EEG-responses at 31 healthy examinees at the age from 18 till 60 years were compared. It is shown that at a logic estimation of music the melody cognizance is accompanied the event-related desynchronization in the left fronto-parietal-temporal area. At an emotional estimation of a melody the event-related synchronization in left fronto - temporal area for the pleasant melodies, desynchronization in temporal area for not pleasant and desynchronization in occipital area for the melodies which are not causing the emotional response is typical. At the analysis of wavelet-synchrony of EEG characterizing jet changes of interaction of cortical zones, it is revealed that the most distinct topographical distinctions concern type of processing of the heard music: logic (has learned-hasn't learned) or emotional (it was pleasant-it was not pleasant). If at an emotional estimation changes interhemispheric communications between associative cortical zones (central, frontal, temporal), are more expressed at logic - between inter - and intrahemispheric communications of projective zones of the acoustic analyzer (temporal area). It is supposed that the revealed event-related synchronization/desynhronization reflects, most likely, an activation component of an estimation of musical fragments whereas the wavelet-analysis provides guidance on character of processing of musical stimulus.

Prognostic and diagnostic value of EEG signal coupling measures in coma.

PubMed

Zubler, Frederic; Koenig, Christa; Steimer, Andreas; Jakob, Stephan M; Schindler, Kaspar A; Gast, Heidemarie

2016-08-01

Our aim was to assess the diagnostic and predictive value of several quantitative EEG (qEEG) analysis methods in comatose patients. In 79 patients, coupling between EEG signals on the left-right (inter-hemispheric) axis and on the anterior-posterior (intra-hemispheric) axis was measured with four synchronization measures: relative delta power asymmetry, cross-correlation, symbolic mutual information and transfer entropy directionality. Results were compared with etiology of coma and clinical outcome. Using cross-validation, the predictive value of measure combinations was assessed with a Bayes classifier with mixture of Gaussians. Five of eight measures showed a statistically significant difference between patients grouped according to outcome; one measure revealed differences in patients grouped according to the etiology. Interestingly, a high level of synchrony between the left and right hemisphere was associated with mortality on intensive care unit, whereas higher synchrony between anterior and posterior brain regions was associated with survival. The combination with the best predictive value reached an area-under the curve of 0.875 (for patients with post anoxic encephalopathy: 0.946). EEG synchronization measures can contribute to clinical assessment, and provide new approaches for understanding the pathophysiology of coma. Prognostication in coma remains a challenging task. qEEG could improve current multi-modal approaches. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Increased Intra-Participant Variability in Children with Autistic Spectrum Disorders: Evidence from Single-Trial Analysis of Evoked EEG

PubMed Central

Milne, Elizabeth

2011-01-01

Intra-participant variability in clinical conditions such as autistic spectrum disorder (ASD) is an important indicator of pathophysiological processing. The data reported here illustrate that trial-by-trial variability can be reliably measured from EEG, and that intra-participant EEG variability is significantly greater in those with ASD than in neuro-typical matched controls. EEG recorded at the scalp is a linear mixture of activity arising from muscle artifacts and numerous concurrent brain processes. To minimize these additional sources of variability, EEG data were subjected to two different methods of spatial filtering. (i) The data were decomposed using infomax independent component analysis, a method of blind source separation which un-mixes the EEG signal into components with maximally independent time-courses, and (ii) a surface Laplacian transform was performed (current source density interpolation) in order to reduce the effects of volume conduction. Data are presented from 13 high functioning adolescents with ASD without co-morbid ADHD, and 12 neuro-typical age-, IQ-, and gender-matched controls. Comparison of variability between the ASD and neuro-typical groups indicated that intra-participant variability of P1 latency and P1 amplitude was greater in the participants with ASD, and inter-trial α-band phase coherence was lower in the participants with ASD. These data support the suggestion that individuals with ASD are less able to synchronize the activity of stimulus-related cell assemblies than neuro-typical individuals, and provide empirical evidence in support of theories of increased neural noise in ASD. PMID:21716921

Culture Modulates the Brain Response to Harmonic Violations: An EEG Study on Hierarchical Syntactic Structure in Music.

PubMed

Akrami, Haleh; Moghimi, Sahar

2017-01-01

We investigated the role of culture in processing hierarchical syntactic structures in music. We examined whether violation of non-local dependencies manifest in event related potentials (ERP) for Western and Iranian excerpts by recording EEG while participants passively listened to sequences of modified/original excerpts. We also investigated oscillatory and synchronization properties of brain responses during processing of hierarchical structures. For the Western excerpt, subjective ratings of conclusiveness were marginally significant and the difference in the ERP components fell short of significance. However, ERP and behavioral results showed that while listening to culturally familiar music, subjects comprehended whether or not the hierarchical syntactic structure was fulfilled. Irregularities in the hierarchical structures of the Iranian excerpt elicited an early negativity in the central regions bilaterally, followed by two later negativities from 450-700 to 750-950 ms. The latter manifested throughout the scalp. Moreover, violations of hierarchical structure in the Iranian excerpt were associated with (i) an early decrease in the long range alpha phase synchronization, (ii) an early increase in the oscillatory activity in the beta band over the central areas, and (iii) a late decrease in the theta band phase synchrony between left anterior and right posterior regions. Results suggest that rhythmic structures and melodic fragments, representative of Iranian music, created a familiar context in which recognition of complex non-local syntactic structures was feasible for Iranian listeners. Processing of neural responses to the Iranian excerpt indicated neural mechanisms for processing of hierarchical syntactic structures in music at different levels of cortical integration.

Multivariate and multiorgan analysis of cardiorespiratory variability signals: the CAP sleep case.

PubMed

Bianchi, Anna M; Ferini-Strambi, Luigi; Castronovo, Vincenza; Cerutti, Sergio

2006-10-01

Signals from different systems are analyzed during sleep on a beat-to-beat basis to provide a quantitative measure of synchronization with the heart rate variability (HRV) signal, oscillations of which reflect the action of the autonomic nervous system. Beat-to-beat variability signals synchronized to QRS occurrence on ECG signals were extracted from respiration, electroencephalogram (EEG) and electromyogram (EMG) traces. The analysis was restricted to sleep stage 2. Cyclic alternating pattern (CAP) periods were detected from EEG signals and the following conditions were identified: stage 2 non-CAP (2 NCAP), stage 2 CAP (2 CAP) and stage 2 CAP with myoclonus (2 CAP MC). The coupling relationships between pairs of variability signals were studied in both the time and frequency domains. Passing from 2 NCAP to 2 CAP, sympathetic activation is indicated by tachycardia and reduced respiratory arrhythmia in the heart rate signal. At the same time, we observed a marked link between EEG and HRV at the CAP frequency. During 2 CAP MC, the increased synchronization involved myoclonus and respiration. The underlying mechanism seems to be related to a global control system at the central level that involves the different systems.

Online detection of fetal acidemia during labour by testing synchronization of EEG and heart rate: a prospective study in fetal sheep.

PubMed

Wang, Xiaogang; Durosier, L Daniel; Ross, Michael G; Richardson, Bryan S; Frasch, Martin G

2014-01-01

Severe fetal acidemia during labour can result in life-lasting neurological deficits, but the timely detection of this condition is often not possible. This is because the positive predictive value (PPV) of fetal heart rate (FHR) monitoring, the mainstay of fetal health surveillance during labour, to detect concerning fetal acidemia is around 50%. In fetal sheep model of human labour, we reported that severe fetal acidemia (pH<7.00) during repetitive umbilical cord occlusions (UCOs) is preceded ∼60 minutes by the synchronization of electroencephalogram (EEG) and FHR. However, EEG and FHR are cyclic and noisy, and although the synchronization might be visually evident, it is challenging to detect automatically, a necessary condition for bedside utility. Here we present and validate a novel non-parametric statistical method to detect fetal acidemia during labour by using EEG and FHR. The underlying algorithm handles non-stationary and noisy data by recording number of abnormal episodes in both EEG and FHR. A logistic regression is then deployed to test whether these episodes are significantly related to each other. We then apply the method in a prospective study of human labour using fetal sheep model (n = 20). Our results render a PPV of 68% for detecting impending severe fetal acidemia ∼60 min prior to pH drop to less than 7.00 with 100% negative predictive value. We conclude that this method has a great potential to improve PPV for detection of fetal acidemia when it is implemented at the bedside. We outline directions for further refinement of the algorithm that will be achieved by analyzing larger data sets acquired in prospective human pilot studies.

Intrahemispheric theta rhythm desynchronization impairs working memory.

PubMed

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

2017-01-01

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

Microinjection of procaine and electrolytic lesion in the ventral tegmental area suppresses hippocampal theta rhythm in urethane-anesthetized rats.

PubMed

Orzeł-Gryglewska, Jolanta; Jurkowlaniec, Edyta; Trojniar, Weronika

2006-01-30

The midbrain ventral tegmental area (VTA), a key structure of the mesocorticolimbic system is anatomically connected with the hippocampal formation. In addition mesocortical dopamine was found to influence hippocampus-related memory and hippocampal synaptic plasticity, both being linked to the theta rhythm. Therefore, the aim of the present study was to evaluate the possible role of the VTA in the regulation of the hippocampal theta activity. The study was performed on urethane-anesthetized male Wistar rats in which theta rhythm was evoked by tail pinch. It was found that unilateral, temporal inactivation of the VTA by means of direct procaine injection resulted in bilateral suppression of the hippocampal theta which manifested as a loss of synchronization of hippocampal EEG and respective reduction of the power and also the frequency of the 3-6 Hz theta band. Depression of the power of the 3-6 Hz component of the EEG signal was also seen in spontaneous hippocampal EEG after procaine. The permanent destruction of the VTA by means of unilateral electrocoagulation evoked a long-lasting, mainly ipsilateral depression of the power of the theta with some influence on its frequency. Simultaneously, there was a substantial increase of the power in higher frequency bands indicating decrease of a synchrony of the hippocampal EEG activity. On the basis of these results indicating impairment of synchronization of the hippocampal activity the VTA may be considered as another part of the brainstem theta synchroning system.

Dynamics of corticospinal motor control during overground and treadmill walking in humans.

PubMed

Roeder, Luisa; Boonstra, Tjeerd Willem; Smith, Simon S; Kerr, Graham K

2018-05-30

Increasing evidence suggests cortical involvement in the control of human gait. However, the nature of corticospinal interactions remains poorly understood. We performed time-frequency analysis of electrophysiological activity acquired during treadmill and overground walking in 22 healthy, young adults. Participants walked at their preferred speed (4.2, SD 0.4 km h -1 ), which was matched across both gait conditions. Event-related power, corticomuscular coherence (CMC) and inter-trial coherence (ITC) were assessed for EEG from bilateral sensorimotor cortices and EMG from the bilateral tibialis anterior (TA) muscles. Cortical power, CMC and ITC at theta, alpha, beta and gamma frequencies (4-45 Hz) increased during the double support phase of the gait cycle for both overground and treadmill walking. High beta (21-30 Hz) CMC and ITC of EMG was significantly increased during overground compared to treadmill walking, as well as EEG power in theta band (4-7 Hz). The phase spectra revealed positive time lags at alpha, beta and gamma frequencies, indicating that the EEG response preceded the EMG response. The parallel increases in power, CMC and ITC during double support suggest evoked responses at spinal and cortical populations rather than a modulation of ongoing corticospinal oscillatory interactions. The evoked responses are not consistent with the idea of synchronization of ongoing corticospinal oscillations, but instead suggest coordinated cortical and spinal inputs during the double support phase. Frequency-band dependent differences in power, CMC and ITC between overground and treadmill walking suggest differing neural control for the two gait modalities, emphasizing the task-dependent nature of neural processes during human walking.

Chronic pretrigeminal and cerveau isolé cats.

PubMed

Slósarska, M; Zernicki, B

1973-01-01

Ten pretrigeminal and ten cerveau isole cats were observed chronically. During 24-36 h sessions EEG activity was continuously recorded and the EEG and ocular responses to visual and olfactory stimuli were studied. In the pretrigeminal cat acute and chronic stages were distinguished, and in the cerveau isole, acute, "early chronic" and "late chronic" stages. During the acute stage, the pretrigeminal cat is continuously awake, whereas the cerveau isole is comatose. During the "early chronic stage", which lasted at least about 3 weeks, the cerveau isole is semicomatose. During the chronic stage in the pretrigeminal cat and the "late chronic stage" in the cerveau isole, the sleep-waking cycle is present. In both preparations alert wakefulness, drowsiness, light .synchronized sleep and deep synchronized sleep occupy, respectively, about 30 percent, 45 percent, 15 percent and 10 percent of the time. Thus, synchronized sleep is strikingly reduced in comparison with an intact cat, while desynchronized sleep is absent.

Scale-free dynamics of the synchronization between sleep EEG power bands and the high frequency component of heart rate variability in normal men and patients with sleep apnea-hypopnea syndrome.

PubMed

Dumont, Martine; Jurysta, Fabrice; Lanquart, Jean-Pol; Noseda, André; van de Borne, Philippe; Linkowski, Paul

2007-12-01

To investigate the dynamics of the synchronization between heart rate variability and sleep electroencephalogram power spectra and the effect of sleep apnea-hypopnea syndrome. Heart rate and sleep electroencephalogram signals were recorded in controls and patients with sleep apnea-hypopnea syndrome that were matched for age, gender, sleep parameters, and blood pressure. Spectral analysis was applied to electrocardiogram and electroencephalogram sleep recordings to obtain power values every 20s. Synchronization likelihood was computed between time series of the normalized high frequency spectral component of RR-intervals and all electroencephalographic frequency bands. Detrended fluctuation analysis was applied to the synchronizations in order to qualify their dynamic behaviors. For all sleep bands, the fluctuations of the synchronization between sleep EEG and heart activity appear scale free and the scaling exponent is close to one as for 1/f noise. We could not detect any effect due to sleep apnea-hypopnea syndrome. The synchronizations between the high frequency component of heart rate variability and all sleep power bands exhibited robust fluctuations characterized by self-similar temporal behavior of 1/f noise type. No effects of sleep apnea-hypopnea syndrome were observed in these synchronizations. Sleep apnea-hypopnea syndrome does not affect the interdependence between the high frequency component of heart rate variability and all sleep power bands as measured by synchronization likelihood.

Statistical detection of EEG synchrony using empirical bayesian inference.

PubMed

Singh, Archana K; Asoh, Hideki; Takeda, Yuji; Phillips, Steven

2015-01-01

There is growing interest in understanding how the brain utilizes synchronized oscillatory activity to integrate information across functionally connected regions. Computing phase-locking values (PLV) between EEG signals is a popular method for quantifying such synchronizations and elucidating their role in cognitive tasks. However, high-dimensionality in PLV data incurs a serious multiple testing problem. Standard multiple testing methods in neuroimaging research (e.g., false discovery rate, FDR) suffer severe loss of power, because they fail to exploit complex dependence structure between hypotheses that vary in spectral, temporal and spatial dimension. Previously, we showed that a hierarchical FDR and optimal discovery procedures could be effectively applied for PLV analysis to provide better power than FDR. In this article, we revisit the multiple comparison problem from a new Empirical Bayes perspective and propose the application of the local FDR method (locFDR; Efron, 2001) for PLV synchrony analysis to compute FDR as a posterior probability that an observed statistic belongs to a null hypothesis. We demonstrate the application of Efron's Empirical Bayes approach for PLV synchrony analysis for the first time. We use simulations to validate the specificity and sensitivity of locFDR and a real EEG dataset from a visual search study for experimental validation. We also compare locFDR with hierarchical FDR and optimal discovery procedures in both simulation and experimental analyses. Our simulation results showed that the locFDR can effectively control false positives without compromising on the power of PLV synchrony inference. Our results from the application locFDR on experiment data detected more significant discoveries than our previously proposed methods whereas the standard FDR method failed to detect any significant discoveries.

Mild traumatic brain injury: graph-model characterization of brain networks for episodic memory.

PubMed

Tsirka, Vasso; Simos, Panagiotis G; Vakis, Antonios; Kanatsouli, Kassiani; Vourkas, Michael; Erimaki, Sofia; Pachou, Ellie; Stam, Cornelis Jan; Micheloyannis, Sifis

2011-02-01

Episodic memory is among the cognitive functions that can be affected in the acute phase following mild traumatic brain injury (MTBI). The present study used EEG recordings to evaluate global synchronization and network organization of rhythmic activity during the encoding and recognition phases of an episodic memory task varying in stimulus type (kaleidoscope images, pictures, words, and pseudowords). Synchronization of oscillatory activity was assessed using a linear and nonlinear connectivity estimator and network analyses were performed using algorithms derived from graph theory. Twenty five MTBI patients (tested within days post-injury) and healthy volunteers were closely matched on demographic variables, verbal ability, psychological status variables, as well as on overall task performance. Patients demonstrated sub-optimal network organization, as reflected by changes in graph parameters in the theta and alpha bands during both encoding and recognition. There were no group differences in spectral energy during task performance or on network parameters during a control condition (rest). Evidence of less optimally organized functional networks during memory tasks was more prominent for pictorial than for verbal stimuli. Copyright © 2010 Elsevier B.V. All rights reserved.

Development of hypersynchrony in the cortical network during chemoconvulsant-induced epileptic seizures in vivo.

PubMed

Cymerblit-Sabba, Adi; Schiller, Yitzhak

2012-03-01

The prevailing view of epileptic seizures is that they are caused by increased hypersynchronous activity in the cortical network. However, this view is based mostly on electroencephalography (EEG) recordings that do not directly monitor neuronal synchronization of action potential firing. In this study, we used multielectrode single-unit recordings from the hippocampus to investigate firing of individual CA1 neurons and directly monitor synchronization of action potential firing between neurons during the different ictal phases of chemoconvulsant-induced epileptic seizures in vivo. During the early phase of seizures manifesting as low-amplitude rhythmic β-electrocorticography (ECoG) activity, the firing frequency of most neurons markedly increased. To our surprise, the average overall neuronal synchronization as measured by the cross-correlation function was reduced compared with control conditions with ~60% of neuronal pairs showing no significant correlated firing. However, correlated firing was not uniform and a minority of neuronal pairs showed a high degree of correlated firing. Moreover, during the early phase of seizures, correlated firing between 9.8 ± 5.1% of all stably recorded pairs increased compared with control conditions. As seizures progressed and high-frequency ECoG polyspikes developed, the firing frequency of neurons further increased and enhanced correlated firing was observed between virtually all neuronal pairs. These findings indicated that epileptic seizures represented a hyperactive state with widespread increase in action potential firing. Hypersynchrony also characterized seizures. However, it initially developed in a small subset of neurons and gradually spread to involve the entire cortical network only in the later more intense ictal phases.

Alpha Power Increase After Transcranial Alternating Current Stimulation at Alpha Frequency (α-tACS) Reflects Plastic Changes Rather Than Entrainment

PubMed Central

Vossen, Alexandra; Gross, Joachim; Thut, Gregor

2015-01-01

Background Periodic stimulation of occipital areas using transcranial alternating current stimulation (tACS) at alpha (α) frequency (8–12 Hz) enhances electroencephalographic (EEG) α-oscillation long after tACS-offset. Two mechanisms have been suggested to underlie these changes in oscillatory EEG activity: tACS-induced entrainment of brain oscillations and/or tACS-induced changes in oscillatory circuits by spike-timing dependent plasticity. Objective We tested to what extent plasticity can account for tACS-aftereffects when controlling for entrainment “echoes.” To this end, we used a novel, intermittent tACS protocol and investigated the strength of the aftereffect as a function of phase continuity between successive tACS episodes, as well as the match between stimulation frequency and endogenous α-frequency. Methods 12 healthy participants were stimulated at around individual α-frequency for 11–15 min in four sessions using intermittent tACS or sham. Successive tACS events were either phase-continuous or phase-discontinuous, and either 3 or 8 s long. EEG α-phase and power changes were compared after and between episodes of α-tACS across conditions and against sham. Results α-aftereffects were successfully replicated after intermittent stimulation using 8-s but not 3-s trains. These aftereffects did not reveal any of the characteristics of entrainment echoes in that they were independent of tACS phase-continuity and showed neither prolonged phase alignment nor frequency synchronization to the exact stimulation frequency. Conclusion Our results indicate that plasticity mechanisms are sufficient to explain α-aftereffects in response to α-tACS, and inform models of tACS-induced plasticity in oscillatory circuits. Modifying brain oscillations with tACS holds promise for clinical applications in disorders involving abnormal neural synchrony. PMID:25648377

Alpha Power Increase After Transcranial Alternating Current Stimulation at Alpha Frequency (α-tACS) Reflects Plastic Changes Rather Than Entrainment.

PubMed

Vossen, Alexandra; Gross, Joachim; Thut, Gregor

2015-01-01

Periodic stimulation of occipital areas using transcranial alternating current stimulation (tACS) at alpha (α) frequency (8-12 Hz) enhances electroencephalographic (EEG) α-oscillation long after tACS-offset. Two mechanisms have been suggested to underlie these changes in oscillatory EEG activity: tACS-induced entrainment of brain oscillations and/or tACS-induced changes in oscillatory circuits by spike-timing dependent plasticity. We tested to what extent plasticity can account for tACS-aftereffects when controlling for entrainment "echoes." To this end, we used a novel, intermittent tACS protocol and investigated the strength of the aftereffect as a function of phase continuity between successive tACS episodes, as well as the match between stimulation frequency and endogenous α-frequency. 12 healthy participants were stimulated at around individual α-frequency for 11-15 min in four sessions using intermittent tACS or sham. Successive tACS events were either phase-continuous or phase-discontinuous, and either 3 or 8 s long. EEG α-phase and power changes were compared after and between episodes of α-tACS across conditions and against sham. α-aftereffects were successfully replicated after intermittent stimulation using 8-s but not 3-s trains. These aftereffects did not reveal any of the characteristics of entrainment echoes in that they were independent of tACS phase-continuity and showed neither prolonged phase alignment nor frequency synchronization to the exact stimulation frequency. Our results indicate that plasticity mechanisms are sufficient to explain α-aftereffects in response to α-tACS, and inform models of tACS-induced plasticity in oscillatory circuits. Modifying brain oscillations with tACS holds promise for clinical applications in disorders involving abnormal neural synchrony. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Ripples on spikes show increased phase-amplitude coupling in mesial temporal lobe epilepsy seizure onset zones

PubMed Central

Weiss, Shennan A; Orosz, Iren; Salamon, Noriko; Moy, Stephanie; Wei, Linqing; Van ’t Klooster, Maryse A; Knight, Robert T; Harper, Ronald M; Bragin, Anatol; Fried, Itzhak; Engel, Jerome; Staba, Richard J

2016-01-01

Objective Ripples (80–150 Hz) recorded from clinical macroelectrodes have been shown to be an accurate biomarker of epileptogenic brain tissue. We investigated coupling between epileptiform spike phase and ripple amplitude to better understand the mechanisms that generate this type of pathological ripple (pRipple) event. Methods We quantified phase amplitude coupling (PAC) between epileptiform EEG spike phase and ripple amplitude recorded from intracranial depth macroelectrodes during episodes of sleep in 12 patients with mesial temporal lobe epilepsy. PAC was determined by 1) a phasor transform that corresponds to the strength and rate of ripples coupled with spikes, and a 2) ripple-triggered average to measure the strength, morphology, and spectral frequency of the modulating and modulated signals. Coupling strength was evaluated in relation to recording sites within and outside the seizure onset zone (SOZ). Results Both the phasor transform and ripple-triggered averaging methods showed ripple amplitude was often robustly coupled with epileptiform EEG spike phase. Coupling was more regularly found inside than outside the SOZ, and coupling strength correlated with the likelihood a macroelectrode’s location was within the SOZ (p<0.01). The ratio of the rate of ripples coupled with EEG spikes inside the SOZ to rates of coupled ripples in non-SOZ was greater than the ratio of rates of ripples on spikes detected irrespective of coupling (p<0.05). Coupling strength correlated with an increase in mean normalized ripple amplitude (p<0.01), and a decrease in mean ripple spectral frequency (p<0.05). Significance Generation of low-frequency (80–150 Hz) pRipples in the SOZ involves coupling between epileptiform spike phase and ripple amplitude. The changes in excitability reflected as epileptiform spikes may also cause clusters of pathologically interconnected bursting neurons to grow and synchronize into aberrantly large neuronal assemblies. PMID:27723936

A Brain-Machine Interface Based on ERD/ERS for an Upper-Limb Exoskeleton Control.

PubMed

Tang, Zhichuan; Sun, Shouqian; Zhang, Sanyuan; Chen, Yumiao; Li, Chao; Chen, Shi

2016-12-02

To recognize the user's motion intention, brain-machine interfaces (BMI) usually decode movements from cortical activity to control exoskeletons and neuroprostheses for daily activities. The aim of this paper is to investigate whether self-induced variations of the electroencephalogram (EEG) can be useful as control signals for an upper-limb exoskeleton developed by us. A BMI based on event-related desynchronization/synchronization (ERD/ERS) is proposed. In the decoder-training phase, we investigate the offline classification performance of left versus right hand and left hand versus both feet by using motor execution (ME) or motor imagery (MI). The results indicate that the accuracies of ME sessions are higher than those of MI sessions, and left hand versus both feet paradigm achieves a better classification performance, which would be used in the online-control phase. In the online-control phase, the trained decoder is tested in two scenarios (wearing or without wearing the exoskeleton). The MI and ME sessions wearing the exoskeleton achieve mean classification accuracy of 84.29% ± 2.11% and 87.37% ± 3.06%, respectively. The present study demonstrates that the proposed BMI is effective to control the upper-limb exoskeleton, and provides a practical method by non-invasive EEG signal associated with human natural behavior for clinical applications.

Frequency-Unspecific Effects of θ-tACS Related to a Visuospatial Working Memory Task

PubMed Central

Kleinert, Maria-Lisa; Szymanski, Caroline; Müller, Viktor

2017-01-01

Working memory (WM) is crucial for intelligent cognitive functioning, and synchronization phenomena in the fronto-parietal network have been suggested as an underlying neural mechanism. In an attempt to provide causal evidence for this assumption, we applied transcranial alternating current stimulation (tACS) at theta frequency over fronto-parietal sites during a visuospatial match-to-sample (MtS) task. Depending on the stimulation protocol, i.e., in-phase, anti-phase or sham, we anticipated a differential impact of tACS on behavioral WM performance as well as on the EEG (electroencephalography) during resting state before and after stimulation. We hypothesized that in-phase tACS of the fronto-parietal theta network (stimulation frequency: 5 Hz; intensity: 1 mA peak-to-peak) would result in performance enhancement, whereas anti-phase tACS would cause performance impairment. Eighteen participants (nine female) received in-phase, anti-phase, and sham stimulation in balanced order. While being stimulated, subjects performed the MtS task, which varied in executive demand (two levels: low and high). EEG analysis of power peaks within the delta (0.5–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), and beta (12–30 Hz) frequency bands was carried out. No significant differences were observed between in-phase and anti-phase stimulation regarding both behavioral and EEG measurements. Yet, with regard to the alpha frequency band, we observed a statistically significant drop of peak power from pre to post in the sham condition, whereas alpha power remained on a similar level in the actively stimulated conditions. Our results indicate a frequency-unspecific modulation of neuronal oscillations by tACS. However, the closer participants’ individual theta peak frequencies were to the stimulation frequency of 5 Hz after anti-phase tACS, the faster they responded in the MtS task. This effect did not reach statistical significance during in-phase tACS and was not present during sham. A lack of statistically significant behavioral results in the MtS task and frequency-unspecific effects on the electrophysiological level question the effectiveness of tACS in modulating cortical oscillations in a frequency-specific manner. PMID:28747881

[Influence of acupuncture of Zusanli (ST 36) on connectivity of brain functional network in healthy subjects].

PubMed

Li, Nuo; Wang, Pang; Deng, Bin; Wei, Xi-le; Che, Yan-qiu; Jia, Chen-hui; Guo, Yi; Chao, Wang

2011-08-01

To observe the effect of acupuncture of Zusanli (ST 36) on electroencephalogram (EEG) so as to probe into its law in regulating the interconnectivity of brain functional network. A total of 9 healthy young volunteer students (6 male, 3 female) participated in the present study. They were asked to take a dorsal position on a test-bed. EEG signals were acquired from 22 surface scalp electrodes (Fp1, Fp2, F7, F3, F2, F4, F8, A1, T3, C3, C2, C4, T4, A2, T5, P3, P2, P4, T6, O2, O1 and O2) fixed on the subject's head. Acupuncture stimulation was applied to the right Zusanli (ST 36) by manipulating the filiform needle with uniform reducing-reinforcing method and at a frequency of about 50 cycles/min for 2 min. Then the stimulation was stopped for 10 min, and repeated once again (needle-twirling frequency: 150 and 200 cycles/min), 3 times altogether. The acquired EEG data were analyzed by using coherence estimation method, average path length, average clustering coefficient, and the average degree of the articulation points (nodes) for analyzing the synchronization of EEG signals before, during and after acupuncture. In comparison with pre-acupuncture, the coherence amplitude values of EEG-delta (1-4 Hz) and y (31-47 Hz) waves were increased significantly after acupuncture of ST 36. No significant changes were found in the amplitude values of EEG-theta (5-8 Hz), -alpha (9-13 Hz) and-beta (14-30 Hz) waves after acupuncture stimulation. During and after acupuncture, the synchronism values of EEG-delta waves of different leads and numbers of interconnectivity between every two brain functional regions in majority of the 9 volunteers were increased clearly. In all volunteers, the degree values of all nodes except A1 and A2, the average clustering coefficients along with the increase of the threshold (r), and the average path lengths of the brain functional network of EEG-delta waves during and after acupuncture were also increased evidently (the latter two items, P < 0.05), suggesting an increase of the information exchange and functional connectivity of different brain regions. Acupuncture of Zusanli (ST 36) can increase the amplitude and synchronization of EEG-delta waves of different leads, and potentiate the functional interconnectivity of brain functional network.

Long-range correlation of the membrane potential in neocortical neurons during slow oscillation

PubMed Central

Volgushev, Maxim; Chauvette, Sylvain; Timofeev, Igor

2012-01-01

Large amplitude slow waves are characteristic for the summary brain activity, recorded as electroencephalogram (EEG) or local field potentials (LFP), during deep stages of sleep and some types of anesthesia. Slow rhythm of the synchronized EEG reflects an alternation of active (depolarized, UP) and silent (hyperpolarized, DOWN) states of neocortical neurons. In neurons, involvement in the generalized slow oscillation results in a long-range synchronization of changes of their membrane potential as well as their firing. Here, we aimed at intracellular analysis of details of this synchronization. We asked which components of neuronal activity exhibit long-range correlations during the synchronized EEG? To answer this question, we made simultaneous intracellular recordings from two to four neocortical neurons in cat neocortex. We studied how correlated is the occurrence of active and silent states, and how correlated are fluctuations of the membrane potential in pairs of neurons located close one to the other or separated by up to 13 mm. We show that strong long-range correlation of the membrane potential was observed only (i) during the slow oscillation but not during periods without the oscillation, (ii) during periods which included transitions between the states but not during within-the-state periods, and (iii) for the low-frequency (<5 Hz) components of membrane potential fluctuations but not for the higher-frequency components (>10 Hz). In contrast to the neurons located several millimeters one from the other, membrane potential fluctuations in neighboring neurons remain strongly correlated during periods without slow oscillation. We conclude that membrane potential correlation in distant neurons is brought about by synchronous transitions between the states, while activity within the states is largely uncorrelated. The lack of the generalized fine-scale synchronization of membrane potential changes in neurons during the active states of slow oscillation may allow individual neurons to selectively engage in short living episodes of correlated activity—a process that may be similar to dynamical formation of neuronal ensembles during activated brain states. PMID:21854963

Assessing cortical synchronization during transcranial direct current stimulation: A graph-theoretical analysis.

PubMed

Mancini, Matteo; Brignani, Debora; Conforto, Silvia; Mauri, Piercarlo; Miniussi, Carlo; Pellicciari, Maria Concetta

2016-10-15

Transcranial direct current stimulation (tDCS) is a neuromodulation technique that can alter cortical excitability and modulate behaviour in a polarity-dependent way. Despite the widespread use of this method in the neuroscience field, its effects on ongoing local or global (network level) neuronal activity are still not foreseeable. A way to shed light on the neuronal mechanisms underlying the cortical connectivity changes induced by tDCS is provided by the combination of tDCS with electroencephalography (EEG). In this study, twelve healthy subjects underwent online tDCS-EEG recording (i.e., simultaneous), during resting-state, using 19 EEG channels. The protocol involved anodal, cathodal and sham stimulation conditions, with the active and the reference electrodes in the left frontocentral area (FC3) and on the forehead over the right eyebrow, respectively. The data were processed using a network model, based on graph theory and the synchronization likelihood. The resulting graphs were analysed for four frequency bands (theta, alpha, beta and gamma) to evaluate the presence of tDCS-induced differences in synchronization patterns and graph theory measures. The resting state network connectivity resulted altered during tDCS, in a polarity-specific manner for theta and alpha bands. Anodal tDCS weakened synchronization with respect to the baseline over the fronto-central areas in the left hemisphere, for theta band (p<0.05). In contrast, during cathodal tDCS a significant increase in inter-hemispheric synchronization connectivity was observed over the centro-parietal, centro-occipital and parieto-occipital areas for the alpha band (p<0.05). Local graph measures showed a tDCS-induced polarity-specific differences that regarded modifications of network activities rather than specific region properties. Our results show that applying tDCS during the resting state modulates local synchronization as well as network properties in slow frequency bands, in a polarity-specific manner. Copyright © 2016 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Chandran, Vinod

2012-12-01

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

First and Second Language in the Brain: Neuronal Correlates of Language Processing and Spelling Strategies

ERIC Educational Resources Information Center

Weber, Patricia; Kozel, Nadja; Purgstaller, Christian; Kargl, Reinhard; Schwab, Daniela; Fink, Andreas

2013-01-01

This study explores oscillatory brain activity by means of event-related synchronization and desynchronization (%ERS/ERD) of EEG activity during the use of phonological and orthographic-morphological spelling strategies in L2 (English) and L1 (German) in native German speaking children. EEG was recorded while 33 children worked on a task requiring…

Cortical connectivity modulation during sleep onset: A study via graph theory on EEG data.

PubMed

Vecchio, Fabrizio; Miraglia, Francesca; Gorgoni, Maurizio; Ferrara, Michele; Iberite, Francesco; Bramanti, Placido; De Gennaro, Luigi; Rossini, Paolo Maria

2017-11-01

Sleep onset is characterized by a specific and orchestrated pattern of frequency and topographical EEG changes. Conventional power analyses of electroencephalographic (EEG) and computational assessments of network dynamics have described an earlier synchronization of the centrofrontal areas rhythms and a spread of synchronizing signals from associative prefrontal to posterior areas. Here, we assess how "small world" characteristics of the brain networks, as reflected in the EEG rhythms, are modified in the wakefulness-sleep transition comparing the pre- and post-sleep onset epochs. The results show that sleep onset is characterized by a less ordered brain network (as reflected by the higher value of small world) in the sigma band for the frontal lobes indicating stronger connectivity, and a more ordered brain network in the low frequency delta and theta bands indicating disconnection on the remaining brain areas. Our results depict the timing and topography of the specific mechanisms for the maintenance of functional connectivity of frontal brain regions at the sleep onset, also providing a possible explanation for the prevalence of the frontal-to-posterior information flow directionality previously observed after sleep onset. Hum Brain Mapp 38:5456-5464, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Interactions between core and matrix thalamocortical projections in human sleep spindle synchronization

PubMed Central

Bonjean, Maxime; Baker, Tanya; Bazhenov, Maxim; Cash, Sydney; Halgren, Eric; Sejnowski, Terrence

2012-01-01

Sleep spindles, which are bursts of 11–15 Hz that occur during non-REM sleep, are highly synchronous across the scalp when measured with EEG, but have low spatial coherence and exhibit low correlation with EEG signals when simultaneously measured with MEG spindles in humans. We developed a computational model to explore the hypothesis that the spatial coherence of the EEG spindle is a consequence of diffuse matrix projections of the thalamus to layer 1 compared to the focal projections of the core pathway to layer 4 recorded by the MEG. Increasing the fanout of thalamocortical connectivity in the matrix pathway while keeping the core pathway fixed led to increased synchrony of the spindle activity in the superficial cortical layers in the model. In agreement with cortical recordings, the latency for spindles to spread from the core to the matrix was independent of the thalamocortical fanout but highly dependent on the probability of connections between cortical areas. PMID:22496571

Affective Pacman: A Frustrating Game for Brain-Computer Interface Experiments

NASA Astrophysics Data System (ADS)

Reuderink, Boris; Nijholt, Anton; Poel, Mannes

We present the design and development of Affective Pacman, a game that induces frustration to study the effect of user state changes on the EEG signal. Affective Pacman is designed to induce frustration for short periods, and allows the synchronous recording of a wide range of sensors, such as physiological sensors and EEG in addition to the game state. A self-assessment is integrated in the game to track changes in user state. Preliminary results indicate a significant effect of the frustration induction on the EEG.

Tackling creativity at its roots: Evidence for different patterns of EEG alpha activity related to convergent and divergent modes of task processing

PubMed Central

Jauk, Emanuel; Benedek, Mathias; Neubauer, Aljoscha C.

2012-01-01

The distinction between convergent and divergent cognitive processes given by Guilford (1956) had a strong influence on the empirical research on creative thinking. Neuroscientific studies typically find higher event-related synchronization in the EEG alpha rhythm for individuals engaged in creative ideation tasks compared to intelligence-related tasks. This study examined, whether these neurophysiological effects can also be found when both cognitive processing modes (convergent vs. divergent) are assessed by means of the same task employing a simple variation of instruction. A sample of 55 participants performed the alternate uses task as well as a more basic word association task while EEG was recorded. On a trial-by-trial basis, participants were either instructed to find a most common solution (convergent condition) or a most uncommon solution (divergent condition). The answers given in the divergent condition were in both tasks significantly more original than those in the convergent condition. Moreover, divergent processing was found to involve higher task-related EEG alpha power than convergent processing in both the alternate uses task and the word association task. EEG alpha synchronization can hence explicitly be associated with divergent cognitive processing rather than with general task characteristics of creative ideation tasks. Further results point to a differential involvement of frontal and parietal cortical areas by individuals of lower versus higher trait creativity. PMID:22390860

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

PubMed

Mammone, Nadia; Labate, Domenico; Lay-Ekuakille, Aime; Morabito, Francesco C

2012-12-01

Epileptic seizures are thought to be generated and to evolve through an underlying anomaly of synchronization in the activity of groups of neuronal populations. The related dynamic scenario of state transitions is revealed by detecting changes in the dynamical properties of Electroencephalography (EEG) signals. The recruitment procedure ending with the crisis can be explored through a spatial-temporal plot from which to extract suitable descriptors that are able to monitor and quantify the evolving synchronization level from the EEG tracings. In this paper, a spatial-temporal analysis of EEG recordings based on the concept of permutation entropy (PE) is proposed. The performance of PE are tested on a database of 24 patients affected by absence (generalized) seizures. The results achieved are compared to the dynamical behavior of the EEG of 40 healthy subjects. Being PE a feature which is dependent on two parameters, an extensive study of the sensitivity of the performance of PE with respect to the parameters' setting was carried out on scalp EEG. Once the optimal PE configuration was determined, its ability to detect the different brain states was evaluated. According to the results here presented, it seems that the widely accepted model of "jump" transition to absence seizure should be in some cases coupled (or substituted) by a gradual transition model characteristic of self-organizing networks. Indeed, it appears that the transition to the epileptic status is heralded before the preictal state, ever since the interictal stages. As a matter of fact, within the limits of the analyzed database, the frontal-temporal scalp areas appear constantly associated to PE levels higher compared to the remaining electrodes, whereas the parieto-occipital areas appear associated to lower PE values. The EEG of healthy subjects neither shows any similar dynamic behavior nor exhibits any recurrent portrait in PE topography.

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

NASA Astrophysics Data System (ADS)

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

2011-04-01

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

Adaptive noise canceling of electrocardiogram artifacts in single channel electroencephalogram.

PubMed

Cho, Sung Pil; Song, Mi Hye; Park, Young Cheol; Choi, Ho Seon; Lee, Kyoung Joung

2007-01-01

A new method for estimating and eliminating electrocardiogram (ECG) artifacts from single channel scalp electroencephalogram (EEG) is proposed. The proposed method consists of emphasis of QRS complex from EEG using least squares acceleration (LSA) filter, generation of synchronized pulse with R-peak and ECG artifacts estimation and elimination using adaptive filter. The performance of the proposed method was evaluated using simulated and real EEG recordings, we found that the ECG artifacts were successfully estimated and eliminated in comparison with the conventional multi-channel techniques, which are independent component analysis (ICA) and ensemble average (EA) method. From this we can conclude that the proposed method is useful for the detecting and eliminating the ECG artifacts from single channel EEG and simple to use for ambulatory/portable EEG monitoring system.

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.

Functional disorganization of small-world brain networks in mild Alzheimer's Disease and amnestic Mild Cognitive Impairment: an EEG study using Relative Wavelet Entropy (RWE).

PubMed

Frantzidis, Christos A; Vivas, Ana B; Tsolaki, Anthoula; Klados, Manousos A; Tsolaki, Magda; Bamidis, Panagiotis D

2014-01-01

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

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

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

PubMed

Puce, Aina; Hämäläinen, Matti S

2017-05-31

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

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

Robust electroencephalogram phase estimation with applications in brain-computer interface systems.

PubMed

Seraj, Esmaeil; Sameni, Reza

2017-03-01

In this study, a robust method is developed for frequency-specific electroencephalogram (EEG) phase extraction using the analytic representation of the EEG. Based on recent theoretical findings in this area, it is shown that some of the phase variations-previously associated to the brain response-are systematic side-effects of the methods used for EEG phase calculation, especially during low analytical amplitude segments of the EEG. With this insight, the proposed method generates randomized ensembles of the EEG phase using minor perturbations in the zero-pole loci of narrow-band filters, followed by phase estimation using the signal's analytical form and ensemble averaging over the randomized ensembles to obtain a robust EEG phase and frequency. This Monte Carlo estimation method is shown to be very robust to noise and minor changes of the filter parameters and reduces the effect of fake EEG phase jumps, which do not have a cerebral origin. As proof of concept, the proposed method is used for extracting EEG phase features for a brain computer interface (BCI) application. The results show significant improvement in classification rates using rather simple phase-related features and a standard K-nearest neighbors and random forest classifiers, over a standard BCI dataset. The average performance was improved between 4-7% (in absence of additive noise) and 8-12% (in presence of additive noise). The significance of these improvements was statistically confirmed by a paired sample t-test, with 0.01 and 0.03 p-values, respectively. The proposed method for EEG phase calculation is very generic and may be applied to other EEG phase-based studies.

Timely event-related synchronization fading and phase de-locking and their defects in migraine.

PubMed

Yum, Myung-Kul; Moon, Jin-Hwa; Kang, Joong Koo; Kwon, Oh-Young; Park, Ki-Jong; Shon, Young-Min; Lee, Il Keun; Jung, Ki-Young

2014-07-01

To investigate the characteristics of event-related synchronization (ERS) fading and phase de-locking of alpha waves during passive auditory stimulation (PAS) in the migraine patients. The subjects were 16 adult women with migraine and 16 normal controls. Electroencephalographic (EEG) data obtained during PAS with standard (SS) and deviant stimuli (DS) were used. Alpha ERS fading, the phase locking index (PLI) and de-locking index (DLI) were evaluated from the 10 Hz complex Morlet wavelet components at 100 ms (t100) and 300 ms (t300) after PAS. At t100, significant ERS was found with SS and DS in the migraineurs and controls (P=0.000). At t300 in the controls, ERS faded to zero for DS while in the migraineurs there was no fading for DS. In both groups the PLI for SS and DS was significantly reduced, i.e. de-locked, at t300 compared to t100 (P=0.000). In the migraineurs, the DLI for DS was significantly lower than in the controls (P=0.003). The alpha ERS fading and phase de-locking are defective in migraineurs during passive auditory cognitive processing. The defects in timely alpha ERS fading and in de-locking may play a role in the different attention processing in migraine patients. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Theta oscillations locked to intended actions rhythmically modulate perception.

PubMed

Tomassini, Alice; Ambrogioni, Luca; Medendorp, W Pieter; Maris, Eric

2017-07-07

Ongoing brain oscillations are known to influence perception, and to be reset by exogenous stimulations. Voluntary action is also accompanied by prominent rhythmic activity, and recent behavioral evidence suggests that this might be coupled with perception. Here, we reveal the neurophysiological underpinnings of this sensorimotor coupling in humans. We link the trial-by-trial dynamics of EEG oscillatory activity during movement preparation to the corresponding dynamics in perception, for two unrelated visual and motor tasks. The phase of theta oscillations (~4 Hz) predicts perceptual performance, even >1 s before movement. Moreover, theta oscillations are phase-locked to the onset of the movement. Remarkably, the alignment of theta phase and its perceptual relevance unfold with similar non-monotonic profiles, suggesting their relatedness. The present work shows that perception and movement initiation are automatically synchronized since the early stages of motor planning through neuronal oscillatory activity in the theta range.

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

PubMed Central

Roy, Abhrajeet; Baxter, Bryan

2014-01-01

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

Electrocortical activity distinguishes between uphill and level walking in humans.

PubMed

Bradford, J Cortney; Lukos, Jamie R; Ferris, Daniel P

2016-02-01

The objective of this study was to determine if electrocortical activity is different between walking on an incline compared with level surface. Subjects walked on a treadmill at 0% and 15% grades for 30 min while we recorded electroencephalography (EEG). We used independent component (IC) analysis to parse EEG signals into maximally independent sources and then computed dipole estimations for each IC. We clustered cortical source ICs and analyzed event-related spectral perturbations synchronized to gait events. Theta power fluctuated across the gait cycle for both conditions, but was greater during incline walking in the anterior cingulate, sensorimotor and posterior parietal clusters. We found greater gamma power during level walking in the left sensorimotor and anterior cingulate clusters. We also found distinct alpha and beta fluctuations, depending on the phase of the gait cycle for the left and right sensorimotor cortices, indicating cortical lateralization for both walking conditions. We validated the results by isolating movement artifact. We found that the frequency activation patterns of the artifact were different than the actual EEG data, providing evidence that the differences between walking conditions were cortically driven rather than a residual artifact of the experiment. These findings suggest that the locomotor pattern adjustments necessary to walk on an incline compared with level surface may require supraspinal input, especially from the left sensorimotor cortex, anterior cingulate, and posterior parietal areas. These results are a promising step toward the use of EEG as a feed-forward control signal for ambulatory brain-computer interface technologies.

Investigating Cooperative Behavior in Ecological Settings: An EEG Hyperscanning Study.

PubMed

Toppi, Jlenia; Borghini, Gianluca; Petti, Manuela; He, Eric J; De Giusti, Vittorio; He, Bin; Astolfi, Laura; Babiloni, Fabio

2016-01-01

The coordinated interactions between individuals are fundamental for the success of the activities in some professional categories. We reported on brain-to-brain cooperative interactions between civil pilots during a simulated flight. We demonstrated for the first time how the combination of neuroelectrical hyperscanning and intersubject connectivity could provide indicators sensitive to the humans' degree of synchronization under a highly demanding task performed in an ecological environment. Our results showed how intersubject connectivity was able to i) characterize the degree of cooperation between pilots in different phases of the flight, and ii) to highlight the role of specific brain macro areas in cooperative behavior. During the most cooperative flight phases pilots showed, in fact, dense patterns of interbrain connectivity, mainly linking frontal and parietal brain areas. On the contrary, the amount of interbrain connections went close to zero in the non-cooperative phase. The reliability of the interbrain connectivity patterns was verified by means of a baseline condition represented by formal couples, i.e. pilots paired offline for the connectivity analysis but not simultaneously recorded during the flight. Interbrain density was, in fact, significantly higher in real couples with respect to formal couples in the cooperative flight phases. All the achieved results demonstrated how the description of brain networks at the basis of cooperation could effectively benefit from a hyperscanning approach. Interbrain connectivity was, in fact, more informative in the investigation of cooperative behavior with respect to established EEG signal processing methodologies applied at a single subject level.

Investigating Cooperative Behavior in Ecological Settings: An EEG Hyperscanning Study

PubMed Central

Petti, Manuela; He, Eric J.; De Giusti, Vittorio; He, Bin; Astolfi, Laura; Babiloni, Fabio

2016-01-01

The coordinated interactions between individuals are fundamental for the success of the activities in some professional categories. We reported on brain-to-brain cooperative interactions between civil pilots during a simulated flight. We demonstrated for the first time how the combination of neuroelectrical hyperscanning and intersubject connectivity could provide indicators sensitive to the humans’ degree of synchronization under a highly demanding task performed in an ecological environment. Our results showed how intersubject connectivity was able to i) characterize the degree of cooperation between pilots in different phases of the flight, and ii) to highlight the role of specific brain macro areas in cooperative behavior. During the most cooperative flight phases pilots showed, in fact, dense patterns of interbrain connectivity, mainly linking frontal and parietal brain areas. On the contrary, the amount of interbrain connections went close to zero in the non-cooperative phase. The reliability of the interbrain connectivity patterns was verified by means of a baseline condition represented by formal couples, i.e. pilots paired offline for the connectivity analysis but not simultaneously recorded during the flight. Interbrain density was, in fact, significantly higher in real couples with respect to formal couples in the cooperative flight phases. All the achieved results demonstrated how the description of brain networks at the basis of cooperation could effectively benefit from a hyperscanning approach. Interbrain connectivity was, in fact, more informative in the investigation of cooperative behavior with respect to established EEG signal processing methodologies applied at a single subject level. PMID:27124558

Functional connectivity analysis in EEG source space: The choice of method

PubMed Central

Knyazeva, Maria G.

2017-01-01

Functional connectivity (FC) is among the most informative features derived from EEG. However, the most straightforward sensor-space analysis of FC is unreliable owing to volume conductance effects. An alternative—source-space analysis of FC—is optimal for high- and mid-density EEG (hdEEG, mdEEG); however, it is questionable for widely used low-density EEG (ldEEG) because of inadequate surface sampling. Here, using simulations, we investigate the performance of the two source FC methods, the inverse-based source FC (ISFC) and the cortical partial coherence (CPC). To examine the effects of localization errors of the inverse method on the FC estimation, we simulated an oscillatory source with varying locations and SNRs. To compare the FC estimations by the two methods, we simulated two synchronized sources with varying between-source distance and SNR. The simulations were implemented for hdEEG, mdEEG, and ldEEG. We showed that the performance of both methods deteriorates for deep sources owing to their inaccurate localization and smoothing. The accuracy of both methods improves with the increasing between-source distance. The best ISFC performance was achieved using hd/mdEEG, while the best CPC performance was observed with ldEEG. In conclusion, with hdEEG, ISFC outperforms CPC and therefore should be the preferred method. In the studies based on ldEEG, the CPC is a method of choice. PMID:28727750

Relationship of Topology, Multiscale Phase Synchronization, and State Transitions in Human Brain Networks

PubMed Central

Kim, Minkyung; Kim, Seunghwan; Mashour, George A.; Lee, UnCheol

2017-01-01

How the brain reconstitutes consciousness and cognition after a major perturbation like general anesthesia is an important question with significant neuroscientific and clinical implications. Recent empirical studies in animals and humans suggest that the recovery of consciousness after anesthesia is not random but ordered. Emergence patterns have been classified as progressive and abrupt transitions from anesthesia to consciousness, with associated differences in duration and electroencephalogram (EEG) properties. We hypothesized that the progressive and abrupt emergence patterns from the unconscious state are associated with, respectively, continuous and discontinuous synchronization transitions in functional brain networks. The discontinuous transition is explainable with the concept of explosive synchronization, which has been studied almost exclusively in network science. We used the Kuramato model, a simple oscillatory network model, to simulate progressive and abrupt transitions in anatomical human brain networks acquired from diffusion tensor imaging (DTI) of 82 brain regions. To facilitate explosive synchronization, distinct frequencies for hub nodes with a large frequency disassortativity (i.e., higher frequency nodes linking with lower frequency nodes, or vice versa) were applied to the brain network. In this simulation study, we demonstrated that both progressive and abrupt transitions follow distinct synchronization processes at the individual node, cluster, and global network levels. The characteristic synchronization patterns of brain regions that are “progressive and earlier” or “abrupt but delayed” account for previously reported behavioral responses of gradual and abrupt emergence from the unconscious state. The characteristic network synchronization processes observed at different scales provide new insights into how regional brain functions are reconstituted during progressive and abrupt emergence from the unconscious state. This theoretical approach also offers a principled explanation of how the brain reconstitutes consciousness and cognitive functions after physiologic (sleep), pharmacologic (anesthesia), and pathologic (coma) perturbations. PMID:28713258

Motor cortex synchronization influences the rhythm of motor performance in premanifest huntington's disease.

PubMed

Casula, Elias P; Mayer, Isabella M S; Desikan, Mahalekshmi; Tabrizi, Sarah J; Rothwell, John C; Orth, Michael

2018-03-01

In Huntington's disease there is evidence of structural damage in the motor system, but it is still unclear how to link this to the behavioral disorder of movement. One feature of choreic movement is variable timing and coordination between sequences of actions. We postulate this results from desynchronization of neural activity in cortical motor areas. The objective of this study was to explore the ability to synchronize activity in a motor network using transcranial magnetic stimulation and to relate this to timing of motor performance. We examined synchronization in oscillatory activity of cortical motor areas in response to an external input produced by a pulse of transcranial magnetic stimulation. We combined this with EEG to compare the response of 16 presymptomatic Huntington's disease participants with 16 age-matched healthy volunteers to test whether the strength of synchronization relates to the variability of motor performance at the following 2 tasks: a grip force task and a speeded-tapping task. Phase synchronization in response to M1 stimulation was lower in Huntington's disease than healthy volunteers (P < .01), resulting in a reduced cortical activity at global (P < .02) and local levels (P < .01). Participants who showed better timed motor performance also showed stronger oscillatory synchronization (r = -0.356; P < .05) and higher cortical activity (r = -0.393; P < .05). Our data may model the ability of the motor command to respond to more subtle, physiological inputs from other brain areas. This novel insight indicates that impairments of the timing accuracy of synchronization and desynchronization could be a physiological basis for some key clinical features of Huntington's disease. © 2018 International Parkinson and Movement Disorder Society. © 2018 International Parkinson and Movement Disorder Society.

Relationship of Topology, Multiscale Phase Synchronization, and State Transitions in Human Brain Networks.

PubMed

Kim, Minkyung; Kim, Seunghwan; Mashour, George A; Lee, UnCheol

2017-01-01

How the brain reconstitutes consciousness and cognition after a major perturbation like general anesthesia is an important question with significant neuroscientific and clinical implications. Recent empirical studies in animals and humans suggest that the recovery of consciousness after anesthesia is not random but ordered. Emergence patterns have been classified as progressive and abrupt transitions from anesthesia to consciousness, with associated differences in duration and electroencephalogram (EEG) properties. We hypothesized that the progressive and abrupt emergence patterns from the unconscious state are associated with, respectively, continuous and discontinuous synchronization transitions in functional brain networks. The discontinuous transition is explainable with the concept of explosive synchronization, which has been studied almost exclusively in network science. We used the Kuramato model, a simple oscillatory network model, to simulate progressive and abrupt transitions in anatomical human brain networks acquired from diffusion tensor imaging (DTI) of 82 brain regions. To facilitate explosive synchronization, distinct frequencies for hub nodes with a large frequency disassortativity (i.e., higher frequency nodes linking with lower frequency nodes, or vice versa) were applied to the brain network. In this simulation study, we demonstrated that both progressive and abrupt transitions follow distinct synchronization processes at the individual node, cluster, and global network levels. The characteristic synchronization patterns of brain regions that are "progressive and earlier" or "abrupt but delayed" account for previously reported behavioral responses of gradual and abrupt emergence from the unconscious state. The characteristic network synchronization processes observed at different scales provide new insights into how regional brain functions are reconstituted during progressive and abrupt emergence from the unconscious state. This theoretical approach also offers a principled explanation of how the brain reconstitutes consciousness and cognitive functions after physiologic (sleep), pharmacologic (anesthesia), and pathologic (coma) perturbations.

Hippocampal, amygdala, and neocortical synchronization of theta rhythms is related to an immediate recall during rey auditory verbal learning test.

PubMed

Babiloni, Claudio; Vecchio, Fabrizio; Mirabella, Giovanni; Buttiglione, Maura; Sebastiano, Fabio; Picardi, Angelo; Di Gennaro, Giancarlo; Quarato, Pier P; Grammaldo, Liliana G; Buffo, Paola; Esposito, Vincenzo; Manfredi, Mario; Cantore, Giampaolo; Eusebi, Fabrizio

2009-07-01

It is well known that theta rhythms (3-8 Hz) are the fingerprint of hippocampus, and that neural activity accompanying encoding of words differs according to whether the items are later remembered or forgotten ["subsequent memory effect" (SME)]. Here, we tested the hypothesis that temporal synchronization of theta rhythms among hippocampus, amygdala, and neocortex is related to immediate memorization of repeated words. To address this issue, intracerebral electroencephalographic (EEG) activity was recorded in five subjects with drug-resistant temporal lobe epilepsy (TLE), under presurgical monitoring routine. During the recording of the intracerebral EEG activity, the subjects performed a computerized version of Rey auditory verbal learning test (RAVLT), a popular test for the clinical evaluation of the immediate and delayed memory. They heard the same list of 15 common words for five times. Each time, immediately after listening the list, the subjects were required to repeat as many words as they could recall. Spectral coherence of the intracerebral EEG activity was computed in order to assess the temporal synchronization of the theta (about 3-8 Hz) rhythms among hippocampus, amygdala, and temporal-occipital neocortex. We found that theta coherence values between amygdala and hippocampus, and between hippocampus and occipital-temporal cortex, were higher in amplitude during successful than unsuccessful immediate recall. A control analysis showed that this was true also for a gamma band (40-45 Hz). Furthermore, these theta and gamma effects were not observed in an additional (control) subject with drug-resistant TLE and a wide lesion to hippocampus. In conclusion, a successful immediate recall to the RAVLT was associated to the enhancement of temporal synchronization of the theta (gamma) rhythms within a cerebral network including hippocampus, amygdala, and temporal-occipital neocortex. Copyright 2009 Wiley-Liss, Inc

Urodynamic function during sleep-like brain states in urethane anesthetized rats.

PubMed

Crook, J; Lovick, T

2016-01-28

The aim was to investigate urodynamic parameters and functional excitability of the periaqueductal gray matter (PAG) during changes in sleep-like brain states in urethane anesthetized rats. Simultaneous recordings of detrusor pressure, external urethral sphincter (EUS) electromyogram (EMG), cortical electroencephalogram (EEG), and single-unit activity in the PAG were made during repeated voiding induced by continuous infusion of saline into the bladder. The EEG cycled between synchronized, high-amplitude slow wave activity (SWA) and desynchronized low-amplitude fast activity similar to slow wave and 'activated' sleep-like brain states. During (SWA, 0.5-1.5 Hz synchronized oscillation of the EEG waveform) voiding became more irregular than in the 'activated' brain state (2-5 Hz low-amplitude desynchronized EEG waveform) and detrusor void pressure threshold, void volume threshold and the duration of bursting activity in the external urethral sphincter EMG were raised. The spontaneous firing rate of 23/52 neurons recorded within the caudal PAG and adjacent tegmentum was linked to the EEG state, with the majority of responsive cells (92%) firing more slowly during SWA. Almost a quarter of the cells recorded (12/52) showed phasic changes in firing rate that were linked to the occurrence of voids. Inhibition (n=6), excitation (n=4) or excitation/inhibition (n=2) was seen. The spontaneous firing rate of 83% of the micturition-responsive cells was sensitive to changes in EEG state. In nine of the 12 responsive cells (75%) the responses were reduced during SWA. We propose that during different sleep-like brain states changes in urodynamic properties occur which may be linked to changing excitability of the micturition circuitry in the periaqueductal gray. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

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

PubMed Central

Puce, Aina; Hämäläinen, Matti S.

2017-01-01

Electroencephalography (EEG) and magnetoencephalography (MEG) are non-invasive electrophysiological methods, which record electric potentials and magnetic fields due to electric currents in synchronously-active neurons. With MEG being more sensitive to neural activity from tangential currents and EEG being able to detect both radial and tangential sources, the two methods are complementary. Over the years, neurophysiological studies have changed considerably: high-density recordings are becoming de rigueur; there is interest in both spontaneous and evoked activity; and sophisticated artifact detection and removal methods are available. Improved head models for source estimation have also increased the precision of the current estimates, particularly for EEG and combined EEG/MEG. Because of their complementarity, more investigators are beginning to perform simultaneous EEG/MEG studies to gain more complete information about neural activity. Given the increase in methodological complexity in EEG/MEG, it is important to gather data that are of high quality and that are as artifact free as possible. Here, we discuss some issues in data acquisition and analysis of EEG and MEG data. Practical considerations for different types of EEG and MEG studies are also discussed. PMID:28561761

Neural synchronization deficits linked to cortical hyper-excitability and auditory hypersensitivity in fragile X syndrome.

PubMed

Ethridge, Lauren E; White, Stormi P; Mosconi, Matthew W; Wang, Jun; Pedapati, Ernest V; Erickson, Craig A; Byerly, Matthew J; Sweeney, John A

2017-01-01

Studies in the fmr1 KO mouse demonstrate hyper-excitability and increased high-frequency neuronal activity in sensory cortex. These abnormalities may contribute to prominent and distressing sensory hypersensitivities in patients with fragile X syndrome (FXS). The current study investigated functional properties of auditory cortex using a sensory entrainment task in FXS. EEG recordings were obtained from 17 adolescents and adults with FXS and 17 age- and sex-matched healthy controls. Participants heard an auditory chirp stimulus generated using a 1000-Hz tone that was amplitude modulated by a sinusoid linearly increasing in frequency from 0-100 Hz over 2 s. Single trial time-frequency analyses revealed decreased gamma band phase-locking to the chirp stimulus in FXS, which was strongly coupled with broadband increases in gamma power. Abnormalities in gamma phase-locking and power were also associated with theta-gamma amplitude-amplitude coupling during the pre-stimulus period and with parent reports of heightened sensory sensitivities and social communication deficits. This represents the first demonstration of neural entrainment alterations in FXS patients and suggests that fast-spiking interneurons regulating synchronous high-frequency neural activity have reduced functionality. This reduced ability to synchronize high-frequency neural activity was related to the total power of background gamma band activity. These observations extend findings from fmr1 KO models of FXS, characterize a core pathophysiological aspect of FXS, and may provide a translational biomarker strategy for evaluating promising therapeutics.

Aerosol Drug Delivery During Noninvasive Positive Pressure Ventilation: Effects of Intersubject Variability and Excipient Enhanced Growth

PubMed Central

Walenga, Ross L.; Kaviratna, Anubhav; Hindle, Michael

2017-01-01

Abstract Background: Nebulized aerosol drug delivery during the administration of noninvasive positive pressure ventilation (NPPV) is commonly implemented. While studies have shown improved patient outcomes for this therapeutic approach, aerosol delivery efficiency is reported to be low with high variability in lung-deposited dose. Excipient enhanced growth (EEG) aerosol delivery is a newly proposed technique that may improve drug delivery efficiency and reduce intersubject aerosol delivery variability when coupled with NPPV. Materials and Methods: A combined approach using in vitro experiments and computational fluid dynamics (CFD) was used to characterize aerosol delivery efficiency during NPPV in two new nasal cavity models that include face mask interfaces. Mesh nebulizer and in-line dry powder inhaler (DPI) sources of conventional and EEG aerosols were both considered. Results: Based on validated steady-state CFD predictions, EEG aerosol delivery improved lung penetration fraction (PF) values by factors ranging from 1.3 to 6.4 compared with conventional-sized aerosols. Furthermore, intersubject variability in lung PF was very high for conventional aerosol sizes (relative differences between subjects in the range of 54.5%–134.3%) and was reduced by an order of magnitude with the EEG approach (relative differences between subjects in the range of 5.5%–17.4%). Realistic in vitro experiments of cyclic NPPV demonstrated similar trends in lung delivery to those observed with the steady-state simulations, but with lower lung delivery efficiencies. Reaching the lung delivery efficiencies reported with the steady-state simulations of 80%–90% will require synchronization of aerosol administration during inspiration and reducing the size of the EEG aerosol delivery unit. Conclusions: The EEG approach enabled high-efficiency lung delivery of aerosols administered during NPPV and reduced intersubject aerosol delivery variability by an order of magnitude. Use of an in-line DPI device that connects to the NPPV mask appears to be a convenient method to rapidly administer an EEG aerosol and synchronize the delivery with inspiration. PMID:28075194

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.

Intra- and inter-brain synchronization during musical improvisation on the guitar.

PubMed

Müller, Viktor; Sänger, Johanna; Lindenberger, Ulman

2013-01-01

Humans interact with the environment through sensory and motor acts. Some of these interactions require synchronization among two or more individuals. Multiple-trial designs, which we have used in past work to study interbrain synchronization in the course of joint action, constrain the range of observable interactions. To overcome the limitations of multiple-trial designs, we conducted single-trial analyses of electroencephalography (EEG) signals recorded from eight pairs of guitarists engaged in musical improvisation. We identified hyper-brain networks based on a complex interplay of different frequencies. The intra-brain connections primarily involved higher frequencies (e.g., beta), whereas inter-brain connections primarily operated at lower frequencies (e.g., delta and theta). The topology of hyper-brain networks was frequency-dependent, with a tendency to become more regular at higher frequencies. We also found hyper-brain modules that included nodes (i.e., EEG electrodes) from both brains. Some of the observed network properties were related to musical roles during improvisation. Our findings replicate and extend earlier work and point to mechanisms that enable individuals to engage in temporally coordinated joint action.

Intra- and Inter-Brain Synchronization during Musical Improvisation on the Guitar

PubMed Central

Müller, Viktor; Sänger, Johanna; Lindenberger, Ulman

2013-01-01

Humans interact with the environment through sensory and motor acts. Some of these interactions require synchronization among two or more individuals. Multiple-trial designs, which we have used in past work to study interbrain synchronization in the course of joint action, constrain the range of observable interactions. To overcome the limitations of multiple-trial designs, we conducted single-trial analyses of electroencephalography (EEG) signals recorded from eight pairs of guitarists engaged in musical improvisation. We identified hyper-brain networks based on a complex interplay of different frequencies. The intra-brain connections primarily involved higher frequencies (e.g., beta), whereas inter-brain connections primarily operated at lower frequencies (e.g., delta and theta). The topology of hyper-brain networks was frequency-dependent, with a tendency to become more regular at higher frequencies. We also found hyper-brain modules that included nodes (i.e., EEG electrodes) from both brains. Some of the observed network properties were related to musical roles during improvisation. Our findings replicate and extend earlier work and point to mechanisms that enable individuals to engage in temporally coordinated joint action. PMID:24040094

Effect of synchronized or desynchronized music listening during osteopathic treatment: an EEG study.

PubMed

Mercadié, Lolita; Caballe, Julie; Aucouturier, Jean-Julien; Bigand, Emmanuel

2014-01-01

While background music is often used during osteopathic treatment, it remains unclear whether it facilitates treatment, and, if it does, whether it is listening to music or jointly listening to a common stimulus that is most important. We created three experimental situations for a standard osteopathic procedure in which patients and practitioner listened either to silence, to the same music in synchrony, or (unknowingly) to different desynchronized montages of the same material. Music had no effect on heart rate and arterial pressure pre- and posttreatment compared to silence, but EEG measures revealed a clear effect of synchronized versus desynchronized listening: listening to desynchronized music was associated with larger amounts of mu-rhythm event-related desynchronization (ERD), indicating decreased sensorimotor fluency compared to what was gained in the synchronized music listening condition. This result suggests that, if any effect can be attributed to music for osteopathy, it is related to its capacity to modulate empathy between patient and therapist and, further, that music does not systematically create better conditions for empathy than silence. Copyright © 2013 Society for Psychophysiological Research.

[EEG correlates of aggression and anxiety in a social interaction model].

PubMed

Kniazev, G G; Bocharov, A V; Mitrofanova, L G; Slobodskoĭ-Pliusnin, Ia Iu; Pylkova, L V

2011-01-01

Aggressiveness- and anxiety-related behavioral and oscillatory patterns were investigated in 49 18-30 year old subjects during virtual social interactions. The subjects were presented with pictures of "angry", "happy", and "neutral" faces and had to choose one out of three options: "attack", "avoid", or "make friends". Sources of cortical EEG were localized with sLORETA software. Subjects with high aggressiveness chose attack more frequently and this behavior was accompanied by a stronger induced delta and theta synchronization in the right orbitofrontal cortex. In subjects with high anxiety, delta and theta responses were stronger induced in the right temporal cortex during their more frequent avoidance behavior. Thus, both in anxious and in aggressive subjects, typical behavior was accompanied by increased induced low-frequency synchronization whose localization implies that it is associated with motivational and emotional processes.

Wedge MUSIC: a novel approach to examine experimental differences of brain source connectivity patterns from EEG/MEG data.

PubMed

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

2014-11-01

We introduce a novel method to estimate bivariate synchronization, i.e. interacting brain sources at a specific frequency or band, from MEG or EEG data robust to artifacts of volume conduction. The data driven calculation is solely based on the imaginary part of the cross-spectrum as opposed to the imaginary part of coherency. In principle, the method quantifies how strong a synchronization between a distinct pair of brain sources is present in the data. As an input of the method all pairs of pre-defined locations inside the brain can be used which is computationally exhaustive. In contrast to that, reference sources can be used that have been identified by any source reconstruction technique in a prior analysis step. We introduce different variants of the method and evaluate the performance in simulations. As a particular advantage of the proposed methodology, we demonstrate that the novel approach is capable of investigating differences in brain source interactions between experimental conditions or with respect to a certain baseline. For measured data, we first show the application on resting state MEG data where we find locally synchronized sources in the motor-cortex based on the sensorimotor idle rhythms. Finally, we show an example on EEG motor imagery data where we contrast hand and foot movements. Here, we also find local interactions in the expected brain areas. Copyright © 2014. Published by Elsevier Inc.

The modulation of brain functional connectivity with manual acupuncture in healthy subjects: An electroencephalograph case study

NASA Astrophysics Data System (ADS)

Yi, Guo-Sheng; Wang, Jiang; Han, Chun-Xiao; Deng, Bin; Wei, Xi-Le; Li, Nuo

2013-02-01

Manual acupuncture is widely used for pain relief and stress control. Previous studies on acupuncture have shown its modulatory effects on the functional connectivity associated with one or a few preselected brain regions. To investigate how manual acupuncture modulates the organization of functional networks at a whole-brain level, we acupuncture at ST36 of a right leg to obtain electroencephalograph (EEG) signals. By coherence estimation, we determine the synchronizations between all pairwise combinations of EEG channels in three acupuncture states. The resulting synchronization matrices are converted into functional networks by applying a threshold, and the clustering coefficients and path lengths are computed as a function of threshold. The results show that acupuncture can increase functional connections and synchronizations between different brain areas. For a wide range of thresholds, the clustering coefficient during acupuncture and post-acupuncture period is higher than that during the pre-acupuncture control period, whereas the characteristic path length is shorter. We provide further support for the presence of “small-world" network characteristics in functional networks by using acupuncture. These preliminary results highlight the beneficial modulations of functional connectivity by manual acupuncture, which could contribute to the understanding of the effects of acupuncture on the entire brain, as well as the neurophysiological mechanisms underlying acupuncture. Moreover, the proposed method may be a useful approach to the further investigation of the complexity of patterns of interrelations between EEG channels.

Dynamics of EEG functional connectivity during statistical learning.

PubMed

Tóth, Brigitta; Janacsek, Karolina; Takács, Ádám; Kóbor, Andrea; Zavecz, Zsófia; Nemeth, Dezso

2017-10-01

Statistical learning is a fundamental mechanism of the brain, which extracts and represents regularities of our environment. Statistical learning is crucial in predictive processing, and in the acquisition of perceptual, motor, cognitive, and social skills. Although previous studies have revealed competitive neurocognitive processes underlying statistical learning, the neural communication of the related brain regions (functional connectivity, FC) has not yet been investigated. The present study aimed to fill this gap by investigating FC networks that promote statistical learning in humans. Young adults (N=28) performed a statistical learning task while 128-channels EEG was acquired. The task involved probabilistic sequences, which enabled to measure incidental/implicit learning of conditional probabilities. Phase synchronization in seven frequency bands was used to quantify FC between cortical regions during the first, second, and third periods of the learning task, respectively. Here we show that statistical learning is negatively correlated with FC of the anterior brain regions in slow (theta) and fast (beta) oscillations. These negative correlations increased as the learning progressed. Our findings provide evidence that dynamic antagonist brain networks serve a hallmark of statistical learning. Copyright © 2017 Elsevier Inc. All rights reserved.

A synchronization method for wireless acquisition systems, application to brain computer interfaces.

PubMed

Foerster, M; Bonnet, S; van Langhenhove, A; Porcherot, J; Charvet, G

2013-01-01

A synchronization method for wireless acquisition systems has been developed and implemented on a wireless ECoG recording implant and on a wireless EEG recording helmet. The presented algorithm and hardware implementation allow the precise synchronization of several data streams from several sensor nodes for applications where timing is critical like in event-related potential (ERP) studies. The proposed method has been successfully applied to obtain visual evoked potentials and compared with a reference biosignal amplifier. The control over the exact sampling frequency allows reducing synchronization errors that will otherwise accumulate during a recording. The method is scalable to several sensor nodes communicating with a shared base station.

Association between increased EEG signal complexity and cannabis dependence.

PubMed

Laprevote, Vincent; Bon, Laura; Krieg, Julien; Schwitzer, Thomas; Bourion-Bedes, Stéphanie; Maillard, Louis; Schwan, Raymund

2017-12-01

Both acute and regular cannabis use affects the functioning of the brain. While several studies have demonstrated that regular cannabis use can impair the capacity to synchronize neural assemblies during specific tasks, less is known about spontaneous brain activity. This can be explored by measuring EEG complexity, which reflects the spontaneous variability of human brain activity. A recent study has shown that acute cannabis use can affect that complexity. Since the characteristics of cannabis use can affect the impact on brain functioning, this study sets out to measure EEG complexity in regular cannabis users with or without dependence, in comparison with healthy controls. We recruited 26 healthy controls, 25 cannabis users without cannabis dependence and 14 cannabis users with cannabis dependence, based on DSM IV TR criteria. The EEG signal was extracted from at least 250 epochs of the 500ms pre-stimulation phase during a visual evoked potential paradigm. Brain complexity was estimated using Lempel-Ziv Complexity (LZC), which was compared across groups by non-parametric Kruskall-Wallis ANOVA. The analysis revealed a significant difference between the groups, with higher LZC in participants with cannabis dependence than in non-dependent cannabis users. There was no specific localization of this effect across electrodes. We showed that cannabis dependence is associated to an increased spontaneous brain complexity in regular users. This result is in line with previous results in acute cannabis users. It may reflect increased randomness of neural activity in cannabis dependence. Future studies should explore whether this effect is permanent or diminishes with cannabis cessation. Copyright © 2017 Elsevier B.V. and ECNP. All rights reserved.

Disturbed temporal dynamics of brain synchronization in vision loss.

PubMed

Bola, Michał; Gall, Carolin; Sabel, Bernhard A

2015-06-01

Damage along the visual pathway prevents bottom-up visual input from reaching further processing stages and consequently leads to loss of vision. But perception is not a simple bottom-up process - rather it emerges from activity of widespread cortical networks which coordinate visual processing in space and time. Here we set out to study how vision loss affects activity of brain visual networks and how networks' activity is related to perception. Specifically, we focused on studying temporal patterns of brain activity. To this end, resting-state eyes-closed EEG was recorded from partially blind patients suffering from chronic retina and/or optic-nerve damage (n = 19) and healthy controls (n = 13). Amplitude (power) of oscillatory activity and phase locking value (PLV) were used as measures of local and distant synchronization, respectively. Synchronization time series were created for the low- (7-9 Hz) and high-alpha band (11-13 Hz) and analyzed with three measures of temporal patterns: (i) length of synchronized-/desynchronized-periods, (ii) Higuchi Fractal Dimension (HFD), and (iii) Detrended Fluctuation Analysis (DFA). We revealed that patients exhibit less complex, more random and noise-like temporal dynamics of high-alpha band activity. More random temporal patterns were associated with worse performance in static (r = -.54, p = .017) and kinetic perimetry (r = .47, p = .041). We conclude that disturbed temporal patterns of neural synchronization in vision loss patients indicate disrupted communication within brain visual networks caused by prolonged deafferentation. We propose that because the state of brain networks is essential for normal perception, impaired brain synchronization in patients with vision loss might aggravate the functional consequences of reduced visual input. Copyright © 2015 Elsevier Ltd. All rights reserved.

Electroencephalography and Brain MRI Patterns in Encephalopathy.

PubMed

Wabulya, Angela; Lesser, Ronald P; Llinas, Rafael; Kaplan, Peter W

2016-04-01

Using electroencephalography (EEG) and histology in patients with diffuse encephalopathy, Gloor et al reported that paroxysmal synchronous discharges (PSDs) on EEG required combined cortical gray (CG) and "subcortical" gray (SCG) matter pathology, while polymorphic delta activity (PDA) occurred in patients with white matter pathology. In patients with encephalopathy, we compared EEG findings and magnetic resonance imaging (MRI) to determine if MRI reflected similar pathological EEG correlations. Retrospective case control study of 52 cases with EEG evidence of encephalopathy and 50 controls without evidence of encephalopathy. Review of clinical, EEG and MRI data acquired within 4 days of each other. The most common EEG finding in encephalopathy was background slowing, in 96.1%. We found PSDs in 0% of cases with the combination of CG and SCG abnormalities. Although 13.5% (n=7) had PSDs on EEG; 3 of these had CG and 4 had SCG abnormalities. A total of 73.1% (38/52) had white matter abnormalities-of these 28.9% (11/38) had PDA. PSDs were found with either CG or "SCG" MRI abnormalities and did not require a combination of the two. In agreement with Gloor et al, PDA occurred with white matter MRI abnormalities in the absence of gray matter abnormalities. © EEG and Clinical Neuroscience Society (ECNS) 2015.

Electroencephalographic changes in albino rats subjected to stress

NASA Technical Reports Server (NTRS)

Mercier, J.; Assouline, G.; Fondarai, J.

1980-01-01

Twenty one albino Wistar rats were subjected to stress for 7 hours. There was a significant difference in the slopes of regression lines for 7 nonulcerous rats and those for 14 ulcerous rats. Nonulcerous rats subjected to stress showed greater EEG curve synchronization than did ulcerous rats. If curve synchronization can be equated to a relaxed state, it may therefore be possible to explain the protective action of hypnotics, tranquilizers and analgesics on ulcers.

Improving Synchronization and Functional Connectivity in Autism Spectrum Disorders through Plasticity-Induced Rehabilitation Training

DTIC Science & Technology

2011-08-01

EEG ; neurofeedback ; autism spectrum disorders 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF...Since  PIRT  or   neurofeedback  training  is  to  be  guided  by  a   quantitative  analysis  of  the   EEG ,  it  was...software for the neurofeedback training at UCSD and SLDC have been acquired, piloted, and are working • Training of Research Assistants has

Classifying EEG for Brain-Computer Interface: Learning Optimal Filters for Dynamical System Features

PubMed Central

Song, Le; Epps, Julien

2007-01-01

Classification of multichannel EEG recordings during motor imagination has been exploited successfully for brain-computer interfaces (BCI). In this paper, we consider EEG signals as the outputs of a networked dynamical system (the cortex), and exploit synchronization features from the dynamical system for classification. Herein, we also propose a new framework for learning optimal filters automatically from the data, by employing a Fisher ratio criterion. Experimental evaluations comparing the proposed dynamical system features with the CSP and the AR features reveal their competitive performance during classification. Results also show the benefits of employing the spatial and the temporal filters optimized using the proposed learning approach. PMID:18364986

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

PubMed

Low, Yin Fen; Strauss, Daniel J

2009-08-01

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

Structure and Topology Dynamics of Hyper-Frequency Networks during Rest and Auditory Oddball Performance.

PubMed

Müller, Viktor; Perdikis, Dionysios; von Oertzen, Timo; Sleimen-Malkoun, Rita; Jirsa, Viktor; Lindenberger, Ulman

2016-01-01

Resting-state and task-related recordings are characterized by oscillatory brain activity and widely distributed networks of synchronized oscillatory circuits. Electroencephalographic recordings (EEG) were used to assess network structure and network dynamics during resting state with eyes open and closed, and auditory oddball performance through phase synchronization between EEG channels. For this assessment, we constructed a hyper-frequency network (HFN) based on within- and cross-frequency coupling (WFC and CFC, respectively) at 10 oscillation frequencies ranging between 2 and 20 Hz. We found that CFC generally differentiates between task conditions better than WFC. CFC was the highest during resting state with eyes open. Using a graph-theoretical approach (GTA), we found that HFNs possess small-world network (SWN) topology with a slight tendency to random network characteristics. Moreover, analysis of the temporal fluctuations of HFNs revealed specific network topology dynamics (NTD), i.e., temporal changes of different graph-theoretical measures such as strength, clustering coefficient, characteristic path length (CPL), local, and global efficiency determined for HFNs at different time windows. The different topology metrics showed significant differences between conditions in the mean and standard deviation of these metrics both across time and nodes. In addition, using an artificial neural network approach, we found stimulus-related dynamics that varied across the different network topology metrics. We conclude that functional connectivity dynamics (FCD), or NTD, which was found using the HFN approach during rest and stimulus processing, reflects temporal and topological changes in the functional organization and reorganization of neuronal cell assemblies.

Structure and Topology Dynamics of Hyper-Frequency Networks during Rest and Auditory Oddball Performance

PubMed Central

Müller, Viktor; Perdikis, Dionysios; von Oertzen, Timo; Sleimen-Malkoun, Rita; Jirsa, Viktor; Lindenberger, Ulman

2016-01-01

Resting-state and task-related recordings are characterized by oscillatory brain activity and widely distributed networks of synchronized oscillatory circuits. Electroencephalographic recordings (EEG) were used to assess network structure and network dynamics during resting state with eyes open and closed, and auditory oddball performance through phase synchronization between EEG channels. For this assessment, we constructed a hyper-frequency network (HFN) based on within- and cross-frequency coupling (WFC and CFC, respectively) at 10 oscillation frequencies ranging between 2 and 20 Hz. We found that CFC generally differentiates between task conditions better than WFC. CFC was the highest during resting state with eyes open. Using a graph-theoretical approach (GTA), we found that HFNs possess small-world network (SWN) topology with a slight tendency to random network characteristics. Moreover, analysis of the temporal fluctuations of HFNs revealed specific network topology dynamics (NTD), i.e., temporal changes of different graph-theoretical measures such as strength, clustering coefficient, characteristic path length (CPL), local, and global efficiency determined for HFNs at different time windows. The different topology metrics showed significant differences between conditions in the mean and standard deviation of these metrics both across time and nodes. In addition, using an artificial neural network approach, we found stimulus-related dynamics that varied across the different network topology metrics. We conclude that functional connectivity dynamics (FCD), or NTD, which was found using the HFN approach during rest and stimulus processing, reflects temporal and topological changes in the functional organization and reorganization of neuronal cell assemblies. PMID:27799906

Distinction between added-energy and phase-resetting mechanisms in non-invasively detected somatosensory evoked responses.

PubMed

Fedele, T; Scheer, H-J; Burghoff, M; Waterstraat, G; Nikulin, V V; Curio, G

2013-01-01

Non-invasively recorded averaged event-related potentials (ERP) represent a convenient opportunity to investigate human brain perceptive and cognitive processes. Nevertheless, generative ERP mechanisms are still debated. Two previous approaches have been contested in the past: the added-energy model in which the response raises independently from the ongoing background activity, and the phase-reset model, based on stimulus-driven synchronization of oscillatory ongoing activity. Many criteria for the distinction of these two models have been proposed, but there is no definitive methodology to disentangle them, owing also to the limited information at the single trial level. Here, we propose a new approach combining low-noise EEG technology and multivariate decomposition techniques. We present theoretical analyses based on simulated data and identify in high-frequency somatosensory evoked responses an optimal target for the distinction between the two mechanisms.

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

PubMed Central

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

2015-01-01

Transient sensory, motor or cognitive event elicit not only phase-locked event-related potentials (ERPs) in the ongoing electroencephalogram (EEG), but also induce non-phase-locked modulations of ongoing EEG oscillations. These modulations can be detected when single-trial waveforms are analysed in the time-frequency domain, and consist in stimulus-induced decreases (event-related desynchronization, ERD) or increases (event-related synchronization, ERS) of synchrony in the activity of the underlying neuronal populations. ERD and ERS reflect changes in the parameters that control oscillations in neuronal networks and, depending on the frequency at which they occur, represent neuronal mechanisms involved in cortical activation, inhibition and binding. ERD and ERS are commonly estimated by averaging the time-frequency decomposition of single trials. However, their trial-to-trial variability that can reflect physiologically-important information is lost by across-trial averaging. Here, we aim to (1) develop novel approaches to explore single-trial parameters (including latency, frequency and magnitude) of ERP/ERD/ERS; (2) disclose the relationship between estimated single-trial parameters and other experimental factors (e.g., perceived intensity). We found that (1) stimulus-elicited ERP/ERD/ERS can be correctly separated using principal component analysis (PCA) decomposition with Varimax rotation on the single-trial time-frequency distributions; (2) time-frequency multiple linear regression with dispersion term (TF-MLRd) enhances the signal-to-noise ratio of ERP/ERD/ERS in single trials, and provides an unbiased estimation of their latency, frequency, and magnitude at single-trial level; (3) these estimates can be meaningfully correlated with each other and with other experimental factors at single-trial level (e.g., perceived stimulus intensity and ERP magnitude). The methods described in this article allow exploring fully non-phase-locked stimulus-induced cortical oscillations, obtaining single-trial estimate of response latency, frequency, and magnitude. This permits within-subject statistical comparisons, correlation with pre-stimulus features, and integration of simultaneously-recorded EEG and fMRI. PMID:25665966

Electroencephalography and quantitative electroencephalography in mild traumatic brain injury.

PubMed

Haneef, Zulfi; Levin, Harvey S; Frost, James D; Mizrahi, Eli M

2013-04-15

Mild traumatic brain injury (mTBI) causes brain injury resulting in electrophysiologic abnormalities visible in electroencephalography (EEG) recordings. Quantitative EEG (qEEG) makes use of quantitative techniques to analyze EEG characteristics such as frequency, amplitude, coherence, power, phase, and symmetry over time independently or in combination. QEEG has been evaluated for its use in making a diagnosis of mTBI and assessing prognosis, including the likelihood of progressing to the postconcussive syndrome (PCS) phase. We review the EEG and qEEG changes of mTBI described in the literature. An attempt is made to separate the findings seen during the acute, subacute, and chronic phases after mTBI. Brief mention is also made of the neurobiological correlates of qEEG using neuroimaging techniques or in histopathology. Although the literature indicates the promise of qEEG in making a diagnosis and indicating prognosis of mTBI, further study is needed to corroborate and refine these methods.

Electroencephalography and Quantitative Electroencephalography in Mild Traumatic Brain Injury

PubMed Central

Levin, Harvey S.; Frost, James D.; Mizrahi, Eli M.

2013-01-01

Abstract Mild traumatic brain injury (mTBI) causes brain injury resulting in electrophysiologic abnormalities visible in electroencephalography (EEG) recordings. Quantitative EEG (qEEG) makes use of quantitative techniques to analyze EEG characteristics such as frequency, amplitude, coherence, power, phase, and symmetry over time independently or in combination. QEEG has been evaluated for its use in making a diagnosis of mTBI and assessing prognosis, including the likelihood of progressing to the postconcussive syndrome (PCS) phase. We review the EEG and qEEG changes of mTBI described in the literature. An attempt is made to separate the findings seen during the acute, subacute, and chronic phases after mTBI. Brief mention is also made of the neurobiological correlates of qEEG using neuroimaging techniques or in histopathology. Although the literature indicates the promise of qEEG in making a diagnosis and indicating prognosis of mTBI, further study is needed to corroborate and refine these methods. PMID:23249295

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

PubMed

Vakalopoulos, Costa

2014-01-01

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

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

PubMed

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

2015-01-01

Future treatments of Alzheimer's disease need the identification of cases at high risk at the preclinical stage of the disease before the development of irreversible structural damage. We investigated here whether subtle cognitive deterioration in a population of healthy elderly individuals could be predicted by EEG signals at baseline under cognitive activation. Continuous EEG was recorded in 97 elderly control subjects and 45 age-matched mild cognitive impairment (MCI) cases during a simple attentional and a 2-back working memory task. Upon 18-month neuropsychological follow-up, the final sample included 55 stable (sCON) and 42 deteriorated (dCON) controls. We examined the P1, N1, P3, and PNwm event-related components as well as the oscillatory activities in the theta (4-7 Hz), alpha (8-13 Hz), and beta (14-25 Hz) frequency ranges (ERD/ERS: event-related desynchronization/synchronization, and ITC: inter-trial coherence). Behavioral performance, P1, and N1 components were comparable in all groups. The P3, PNwm, and all oscillatory activity indices were altered in MCI cases compared to controls. Only three EEG indices distinguished the two control groups: alpha and beta ERD (dCON >  sCON) and beta ITC (dCON <  sCON). These findings show that subtle cognitive deterioration has no impact on EEG indices associated with perception, discrimination, and working memory processes but mostly affects attention, resulting in an enhanced recruitment of attentional resources. In addition, cognitive decline alters neural firing synchronization at high frequencies (14-25 Hz) at early stages, and possibly affects lower frequencies (4-13 Hz) only at more severe stages.

Mobile phone emission modulates interhemispheric functional coupling of EEG alpha rhythms.

PubMed

Vecchio, Fabrizio; Babiloni, Claudio; Ferreri, Florinda; Curcio, Giuseppe; Fini, Rita; Del Percio, Claudio; Rossini, Paolo Maria

2007-03-01

We tested the working hypothesis that electromagnetic fields from mobile phones (EMFs) affect interhemispheric synchronization of cerebral rhythms, an important physiological feature of information transfer into the brain. Ten subjects underwent two electroencephalographic (EEG) recordings, separated by 1 week, following a crossover double-blind paradigm in which they were exposed to a mobile phone signal (global system for mobile communications; GSM). The mobile phone was held on the left side of the subject head by a modified helmet, and orientated in the normal position for use over the ear. The microphone was orientated towards the corner of the mouth, and the antenna was near the head in the parietotemporal area. In addition, we positioned another similar phone (but without battery) on the right side of the helmet, to balance the weight and to prevent the subject localizing the side of GSM stimulation (and consequently lateralizing attention). In one session the exposure was real (GSM) while in the other it was Sham; both sessions lasted 45 min. Functional interhemispheric connectivity was modelled using the analysis of EEG spectral coherence between frontal, central and parietal electrode pairs. Individual EEG rhythms of interest were delta (about 2-4 Hz), theta (about 4-6 Hz), alpha 1 (about 6-8 Hz), alpha 2 (about 8-10 Hz) and alpha 3 (about 10-12 Hz). Results showed that, compared to Sham stimulation, GSM stimulation modulated the interhemispheric frontal and temporal coherence at alpha 2 and alpha 3 bands. The present results suggest that prolonged mobile phone emission affects not only the cortical activity but also the spread of neural synchronization conveyed by interhemispherical functional coupling of EEG rhythms.

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

PubMed

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

2012-01-01

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

Effects of phencyclidine (PCP) and MK 801 on the EEGq in the prefrontal cortex of conscious rats; antagonism by clozapine, and antagonists of AMPA-, alpha(1)- and 5-HT(2A)-receptors.

PubMed

Sebban, Claude; Tesolin-Decros, Brigitte; Ciprian-Ollivier, Jorge; Perret, Laurent; Spedding, Michael

2002-01-01

1. The electroencephalographic (EEG) effects of the propsychotic agent phencyclidine (PCP), were studied in conscious rats using power spectra (0 - 30 Hz), from the prefrontal cortex or sensorimotor cortex. PCP (0.1 - 3 mg kg(-1) s.c.) caused a marked dose-dependent increase in EEG power in the frontal cortex at 1 - 3 Hz with decreases in power at higher frequencies (9 - 30 Hz). At high doses (3 mg kg(-1) s.c.) the entire spectrum shifted to more positive values, indicating an increase in cortical synchronization. MK 801 (0.05 - 0.1 mg kg(-1) i.p.) caused similar effects but with lesser changes in power. 2. In contrast, the non-competitive AMPA antagonists GYKI 52466 and GYKI 53655 increased EEG power over the whole power spectrum (1 - 10 mg kg(-1) i.p.). The atypical antipsychotic clozapine (0.2 mg kg(-1) s.c.) synchronized the EEG (peak 8 Hz). The 5-HT(2A)-antagonist, M100907, specifically increased EEG power at 2 - 3 Hz at low doses (10 and 50 microg kg(-1) s.c.), whereas at higher doses (0.1 mg kg(-1) s.c.) the profile resembled that of clozapine. 3. Clozapine (0.2 mg kg(-1) s.c. ), GYKI 53655 (5 mg kg(-1) i.p.), prazosin (0.05 and 0.1 mg kg(-1) i.p.), and M100907 (0.01 and 0.05 mg kg(-1) s.c.) antagonized the decrease in power between 5 and 30 Hz caused by PCP (1 mg kg(-1) s.c.), but not the increase in power at 1 - 3 Hz in prefrontal cortex.

Higher Frontal EEG Synchronization in Young Women with Major Depression: A Marker for Increased Homeostatic Sleep Pressure?

PubMed Central

Birchler-Pedross, Angelina; Frey, Sylvia; Chellappa, Sarah Laxhmi; Götz, Thomas; Brunner, Patrick; Knoblauch, Vera; Wirz-Justice, Anna; Cajochen, Christian

2011-01-01

Study Objectives: Major depressive disorder (MDD) is often associated with disturbances in circadian and/or sleep-wake dependent processes, which both regulate daytime energy and sleepiness levels. Design: Analysis of continuous electroencephalographic (EEG) recordings during 40 h of extended wakefulness under constant routine conditions. Artifact-free EEG samples derived from 12 locations were subjected to spectral analysis. Additionally, half-hourly ratings of subjective tension and sleepiness levels and salivary melatonin measurements were collected. Setting: Centre for Chronobiology, Psychiatric Hospitals of the University of Basel, Switzerland. Participants: Eight young healthy women and 8 young untreated women with MDD. Interventions: N/A. Measurements and Results: MDD women exhibited higher frontal low-frequency (FLA) EEG activity (0.5-5.0 Hz) during extended wakefulness than controls, particularly during the night. Enhanced FLA was paralleled by higher levels of subjective sleepiness and tension. In MDD women, overall FLA levels correlated positively with depression scores. The timing of melatonin onset did not significantly differ between the two groups, but the nocturnal secretion of salivary melatonin was significantly attenuated in MDD women. Conclusions: Our data imply that young women with MDD live on a higher homeostatic sleep pressure level, as indexed by enhanced FLA during wakefulness. Its positive correlation with depression scores indicates a possible functional relationship. High FLA could reflect a use-dependent phenomenon in depression (enhanced cognitive rumination or tension) and/or an attenuated circadian arousal signal. Citation: Birchler-Pedross A; Frey S; Chellappa SL; Götz T; Brunner P; Knoblauch V; Wirz-Justice A; Cajochen C. Higher frontal EEG synchronization in young women with major depression: a marker for increased homeostatic sleep pressure? SLEEP 2011;34(12):1699-1706. PMID:22131608

Psilocybin-induced spiritual experiences and insightfulness are associated with synchronization of neuronal oscillations.

PubMed

Kometer, Michael; Pokorny, Thomas; Seifritz, Erich; Volleinweider, Franz X

2015-10-01

During the last years, considerable progress has been made toward understanding the neuronal basis of consciousness by using sophisticated behavioral tasks, brain-imaging techniques, and various psychoactive drugs. Nevertheless, the neuronal mechanisms underlying some of the most intriguing states of consciousness, including spiritual experiences, remain unknown. To elucidate state of consciousness-related neuronal mechanisms, human subjects were given psilocybin, a naturally occurring serotonergic agonist and hallucinogen that has been used for centuries to induce spiritual experiences in religious and medical rituals. In this double-blind, placebo-controlled study, 50 healthy human volunteers received a moderate dose of psilocybin, while high-density electroencephalogram (EEG) recordings were taken during eyes-open and eyes-closed resting states. The current source density and the lagged phase synchronization of neuronal oscillations across distributed brain regions were computed and correlated with psilocybin-induced altered states of consciousness. Psilocybin decreased the current source density of neuronal oscillations at 1.5-20 Hz within a neural network comprising the anterior and posterior cingulate cortices and the parahippocampal regions. Most intriguingly, the intensity levels of psilocybin-induced spiritual experience and insightfulness correlated with the lagged phase synchronization of delta oscillations (1.5-4 Hz) between the retrosplenial cortex, the parahippocampus, and the lateral orbitofrontal area. These results provide systematic evidence for the direct association of a specific spatiotemporal neuronal mechanism with spiritual experiences and enhanced insight into life and existence. The identified mechanism may constitute a pathway for modulating mental health, as spiritual experiences can promote sustained well-being and psychological resilience.

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

PubMed

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

2014-02-01

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

Resting-state EEG power and coherence vary between migraine phases.

PubMed

Cao, Zehong; Lin, Chin-Teng; Chuang, Chun-Hsiang; Lai, Kuan-Lin; Yang, Albert C; Fuh, Jong-Ling; Wang, Shuu-Jiun

2016-12-01

Migraine is characterized by a series of phases (inter-ictal, pre-ictal, ictal, and post-ictal). It is of great interest whether resting-state electroencephalography (EEG) is differentiable between these phases. We compared resting-state EEG energy intensity and effective connectivity in different migraine phases using EEG power and coherence analyses in patients with migraine without aura as compared with healthy controls (HCs). EEG power and isolated effective coherence of delta (1-3.5 Hz), theta (4-7.5 Hz), alpha (8-12.5 Hz), and beta (13-30 Hz) bands were calculated in the frontal, central, temporal, parietal, and occipital regions. Fifty patients with episodic migraine (1-5 headache days/month) and 20 HCs completed the study. Patients were classified into inter-ictal, pre-ictal, ictal, and post-ictal phases (n = 22, 12, 8, 8, respectively), using 36-h criteria. Compared to HCs, inter-ictal and ictal patients, but not pre- or post-ictal patients, had lower EEG power and coherence, except for a higher effective connectivity in fronto-occipital network in inter-ictal patients (p < .05). Compared to data obtained from the inter-ictal group, EEG power and coherence were increased in the pre-ictal group, with the exception of a lower effective connectivity in fronto-occipital network (p < .05). Inter-ictal and ictal patients had decreased EEG power and coherence relative to HCs, which were "normalized" in the pre-ictal or post-ictal groups. Resting-state EEG power density and effective connectivity differ between migraine phases and provide an insight into the complex neurophysiology of migraine.

EEG in the classroom: Synchronised neural recordings during video presentation

PubMed Central

Poulsen, Andreas Trier; Kamronn, Simon; Dmochowski, Jacek; Parra, Lucas C.; Hansen, Lars Kai

2017-01-01

We performed simultaneous recordings of electroencephalography (EEG) from multiple students in a classroom, and measured the inter-subject correlation (ISC) of activity evoked by a common video stimulus. The neural reliability, as quantified by ISC, has been linked to engagement and attentional modulation in earlier studies that used high-grade equipment in laboratory settings. Here we reproduce many of the results from these studies using portable low-cost equipment, focusing on the robustness of using ISC for subjects experiencing naturalistic stimuli. The present data shows that stimulus-evoked neural responses, known to be modulated by attention, can be tracked for groups of students with synchronized EEG acquisition. This is a step towards real-time inference of engagement in the classroom. PMID:28266588

EEG in the classroom: Synchronised neural recordings during video presentation

NASA Astrophysics Data System (ADS)

Poulsen, Andreas Trier; Kamronn, Simon; Dmochowski, Jacek; Parra, Lucas C.; Hansen, Lars Kai

2017-03-01

We performed simultaneous recordings of electroencephalography (EEG) from multiple students in a classroom, and measured the inter-subject correlation (ISC) of activity evoked by a common video stimulus. The neural reliability, as quantified by ISC, has been linked to engagement and attentional modulation in earlier studies that used high-grade equipment in laboratory settings. Here we reproduce many of the results from these studies using portable low-cost equipment, focusing on the robustness of using ISC for subjects experiencing naturalistic stimuli. The present data shows that stimulus-evoked neural responses, known to be modulated by attention, can be tracked for groups of students with synchronized EEG acquisition. This is a step towards real-time inference of engagement in the classroom.

Wavelet analysis of epileptic spikes

NASA Astrophysics Data System (ADS)

Latka, Miroslaw; Was, Ziemowit; Kozik, Andrzej; West, Bruce J.

2003-05-01

Interictal spikes and sharp waves in human EEG are characteristic signatures of epilepsy. These potentials originate as a result of synchronous pathological discharge of many neurons. The reliable detection of such potentials has been the long standing problem in EEG analysis, especially after long-term monitoring became common in investigation of epileptic patients. The traditional definition of a spike is based on its amplitude, duration, sharpness, and emergence from its background. However, spike detection systems built solely around this definition are not reliable due to the presence of numerous transients and artifacts. We use wavelet transform to analyze the properties of EEG manifestations of epilepsy. We demonstrate that the behavior of wavelet transform of epileptic spikes across scales can constitute the foundation of a relatively simple yet effective detection algorithm.

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.

Intracranial EEG potentials estimated from MEG sources: A new approach to correlate MEG and iEEG data in epilepsy.

PubMed

Grova, Christophe; Aiguabella, Maria; Zelmann, Rina; Lina, Jean-Marc; Hall, Jeffery A; Kobayashi, Eliane

2016-05-01

Detection of epileptic spikes in MagnetoEncephaloGraphy (MEG) requires synchronized neuronal activity over a minimum of 4cm2. We previously validated the Maximum Entropy on the Mean (MEM) as a source localization able to recover the spatial extent of the epileptic spike generators. The purpose of this study was to evaluate quantitatively, using intracranial EEG (iEEG), the spatial extent recovered from MEG sources by estimating iEEG potentials generated by these MEG sources. We evaluated five patients with focal epilepsy who had a pre-operative MEG acquisition and iEEG with MRI-compatible electrodes. Individual MEG epileptic spikes were localized along the cortical surface segmented from a pre-operative MRI, which was co-registered with the MRI obtained with iEEG electrodes in place for identification of iEEG contacts. An iEEG forward model estimated the influence of every dipolar source of the cortical surface on each iEEG contact. This iEEG forward model was applied to MEG sources to estimate iEEG potentials that would have been generated by these sources. MEG-estimated iEEG potentials were compared with measured iEEG potentials using four source localization methods: two variants of MEM and two standard methods equivalent to minimum norm and LORETA estimates. Our results demonstrated an excellent MEG/iEEG correspondence in the presumed focus for four out of five patients. In one patient, the deep generator identified in iEEG could not be localized in MEG. MEG-estimated iEEG potentials is a promising method to evaluate which MEG sources could be retrieved and validated with iEEG data, providing accurate results especially when applied to MEM localizations. Hum Brain Mapp 37:1661-1683, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Diagnostic and therapeutic yield of a patient-controlled portable EEG device with dry electrodes for home-monitoring neurological outpatients-rationale and protocol of the HOMEONE pilot study.

PubMed

Neumann, Thomas; Baum, Anne Katrin; Baum, Ulrike; Deike, Renate; Feistner, Helmut; Hinrichs, Hermann; Stokes, Joseph; Robra, Bernt-Peter

2018-01-01

The HOME ONE study is part of the larger HOME project, which aims to provide evidence of diagnostic and therapeutic yield ("change of management") of a patient-controlled portable EEG device with dry electrodes for the purposes of EEG home-monitoring neurological outpatients. The HOME ONE study is the first step in the process of investigating whether outpatient EEG home-monitoring changes the diagnosis and treatment of patients in comparison to conventional EEG ("change of management"). Both EEG devices (conventional and portable) will be systematically compared via a two-phase intra-individual assessment.In the first phase (pilot study phase), both EEG devices will be used within neurologist practices (all other things being equal). This pilot study (involving 130 patients) will evaluate the technical usability and efficacy of the new portable dry electrode EEG recorder in comparison to conventional EEG devices. Judgements will be based on technical assessments and EEG record examinations of private practitioners and two experienced neurologists (percent of concordant readings and kappa values).The second phase (feasibility study phase) aims to assess patients' acceptability and feasibility of the EEG home-monitoring and will provide insights into the extent diagnostic and therapeutic yields can be expected.For this purpose, a conventional EEG will be recorded in neurologist practices. Thereafter, the practice staff will instruct the patients on how the portable EEG device functions. The patients will subsequently use the devices in their home environment.The evaluation will compare the before and after documented diagnostic findings and the therapeutic consequences of the private practitioners with those of two experienced neurologists. To the best of our knowledge, this will be the first study of its kind to examine new approaches to diagnosing unclear consciousness disorders or other disorders of the CNS or the cardiovascular system through the use of a patient-controlled portable EEG device with dry electrodes for the purpose of home-monitoring neurological outpatients. If the two phases of the HOME ONE study provide sufficient evidence of diagnostic and therapeutic yields, this would justify (indication-specific) full-scale randomized controlled trials or observational studies. DRKS DRKS00012685. Registered 9 August 2017, retrospectively registered.

Circadian variation of EEG power spectra in NREM and REM sleep in humans: dissociation from body temperature

NASA Technical Reports Server (NTRS)

Dijk, D. J.

1999-01-01

In humans, EEG power spectra in REM and NREM sleep, as well as characteristics of sleep spindles such as their duration, amplitude, frequency and incidence, vary with circadian phase. Recently it has been hypothesized that circadian variations in EEG spectra in humans are caused by variations in brain or body temperature and may not represent phenomena relevant to sleep regulatory processes. To test this directly, a further analysis of EEG power spectra - collected in a forced desynchrony protocol in which sleep episodes were scheduled to a 28-h period while the rhythms of body temperature and plasma melatonin were oscillating at their near 24-h period - was carried out. EEG power spectra were computed for NREM and REM sleep occurring between 90-120 and 270-300 degrees of the circadian melatonin rhythm, i.e. just after the clearance of melatonin from plasma in the 'morning' and just after the 'evening' increase in melatonin secretion. Average body temperatures during scheduled sleep at these two circadian phases were identical (36.72 degrees C). Despite identical body temperatures, the power spectra in NREM sleep were very different at these two circadian phases. EEG activity in the low frequency spindle range was significantly and markedly enhanced after the evening increase in plasma melatonin as compared to the morning phase. For REM sleep, significant differences in power spectra during these two circadian phases, in particular in the alpha range, were also observed. The results confirm that EEG power spectra in NREM and REM sleep vary with circadian phase, suggesting that the direct contribution of temperature to the circadian variation in EEG power spectra is absent or only minor, and are at variance with the hypothesis that circadian variations in EEG power spectra are caused by variations in temperature.

Annual Summary Report, 15 June 1960-14 June 1961,

DTIC Science & Technology

The habituation and the dishabituation of the visual responses to repetitive light flashes were investigated in the cerveau isole cat. The...system show that EEG synchronization increases following bilateral withdrawal of the retinal dark discharge in the cerveau isole cat, and following

Is there "neural efficiency" during the processing of visuo-spatial information in male humans? An EEG study.

PubMed

Capotosto, Paolo; Perrucci, M Gianni; Brunetti, Marcella; Del Gratta, Cosimo; Doppelmayr, Michael; Grabner, Roland H; Klimesch, Wolfgang; Neubauer, Aljoscha; Neuper, Christa; Pfurtscheller, Gert; Romani, Gian Luca; Babiloni, Claudio

2009-12-28

More intelligent persons (high IQ) typically present a higher cortical activity during tasks requiring the encoding of visuo-spatial information, namely higher alpha (about 10 Hz) event-related desynchronization (ERD; Doppelmayr et al., 2005). The opposite is true ("neural efficiency") during the retrieval of the encoded information, as revealed by both lower alpha ERD and/or lower theta (about 5 Hz) event-related synchronization (ERS; Grabner et al., 2004). To reconcile these contrasting results, here we evaluated the working hypothesis that more intelligent male subjects are characterized by a high cortical activity during the encoding phase. This deep encoding would explain the relatively low cortical activity for the retrieval of the encoded information. To test this hypothesis, electroencephalographic (EEG) data were recorded in 22 healthy young male volunteers during visuo-spatial information processing (encoding) and short-term retrieval of the encoded information. Cortical activity was indexed by theta ERS and alpha ERD. It was found that the higher the subjects' total IQ, the stronger the frontal theta ERS during the encoding task. Furthermore, the higher the subjects' total IQ, the lower the frontal high-frequency alpha ERD (about 10-12 Hz) during the retrieval task. This was not true for parietal counterpart of these EEG rhythms. These results reconcile previous contrasting evidence confirming that more intelligent persons do not ever show event-related cortical responses compatible with "neural efficiency" hypothesis. Rather, their cortical activity would depend on flexible and task-adapting features of frontal activation.

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

PubMed

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

2014-03-01

Thought blocks (TBs) are characterized by regular interruptions in the stream of thought. Outward signs are abrupt and repeated interruptions in the flow of conversation or actions while subjective experience is that of a total and uncontrollable emptying of the mind. In the very limited bibliography regarding TB, the phenomenon is thought to be conceptualized as a disturbance of consciousness that can be attributed to stoppages of continuous information processing due to an increase in the volume of information to be processed. In an attempt to investigate potential expression of the phenomenon on the functional properties of electroencephalographic (EEG) activity, an EEG study was contacted in schizophrenic patients with persisting auditory verbal hallucinations (AVHs) who additionally exhibited TBs. In this case, we hypothesized that the persistent and dense AVHs could serve the role of an increased information flow that the brain is unable to process, a condition that is perceived by the person as TB. Phase synchronization analyses performed on EEG segments during the experience of TBs showed that synchrony values exhibited a long-range common mode of coupling (grouped behavior) among the left temporal area and the remaining central and frontal brain areas. These common synchrony-fluctuation schemes were observed for 0.5 to 2s and were detected in a 4-s window following the estimated initiation of the phenomenon. The observation was frequency specific and detected in the broad alpha band region (6-12Hz). The introduction of synchrony entropy (SE) analysis applied on the cumulative synchrony distribution showed that TB states were characterized by an explicit preference of the system to be functioned at low values of synchrony, while the synchrony values are broadly distributed during the recovery state. Our results indicate that during TB states, the phase locking of several brain areas were converged uniformly in a narrow band of low synchrony values and in a distinct time window, impeding thus the ability of the system to recruit and to process information during this time window. Copyright © 2014 Elsevier B.V. All rights reserved.

Fluctuations of the fractal dimension of the electroencephalogram during periodic breathing in heart failure patients.

PubMed

Maestri, Roberto; La Rovere, Maria Teresa; Robbi, Elena; Pinna, Gian Domenico

2010-06-01

The physiological mechanisms responsible for periodic breathing (PB) in heart failure (HF) patients are still debated. A role for rhythmic shifts in the level of wakefulness has been suggested, but their existence has never been proven. In this study we investigated the existence of an oscillation in EEG activity during PB in these patients and assessed its relationship with the ventilatory oscillation. EEG activity was measured by the fractal dimension (FD) and by a spectral technique (weighted mean frequency, WMF) in 17 stable HF patients (mean age +/- SD: 57+/-10 yrs, NYHA class: 2.6 +/- 0.4, LVEF: 24 +/- 6%), with sustained PB during supine rest. The relationship between minute ventilation (MV) signal and FD and WMF was assessed by coherence analysis. Most patients (10/17) showed a well defined oscillation in FD and WMF at the frequency of PB closely linked (coherence > 0.7) with the oscillation of MV. In the remaining patients, neither FD nor WMF showed a clear oscillatory pattern synchronous with MV. Overall, the two EEG-derived parameters showed the same coherence with the ventilatory oscillation (mean coherence +/- SD: 0.65 +/- 0.25 vs 0.66 +/- 0.23, for FD and WMF respectively, p = 0.44). Our results provide evidence that during PB in HF patients, EEG activity often, but not always, fluctuates synchronously with the ventilatory oscillation. These fluctuations can be effectively detected by the fractal dimension, but classical spectral methods provide substantially the same information. Other mechanisms, particularly chemical instability in the respiratory control system, are likely to play a role in the genesis of PB.

Graph Theoretical Analysis of BOLD Functional Connectivity during Human Sleep without EEG Monitoring.

PubMed

Lv, Jun; Liu, Dongdong; Ma, Jing; Wang, Xiaoying; Zhang, Jue

2015-01-01

Functional brain networks of human have been revealed to have small-world properties by both analyzing electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) time series. In our study, by using graph theoretical analysis, we attempted to investigate the changes of paralimbic-limbic cortex between wake and sleep states. Ten healthy young people were recruited to our experiment. Data from 2 subjects were excluded for the reason that they had not fallen asleep during the experiment. For each subject, blood oxygen level dependency (BOLD) images were acquired to analyze brain network, and peripheral pulse signals were obtained continuously to identify if the subject was in sleep periods. Results of fMRI showed that brain networks exhibited stronger small-world characteristics during sleep state as compared to wake state, which was in consistent with previous studies using EEG synchronization. Moreover, we observed that compared with wake state, paralimbic-limbic cortex had less connectivity with neocortical system and centrencephalic structure in sleep. In conclusion, this is the first study, to our knowledge, has observed that small-world properties of brain functional networks altered when human sleeps without EEG synchronization. Moreover, we speculate that paralimbic-limbic cortex organization owns an efficient defense mechanism responsible for suppressing the external environment interference when humans sleep, which is consistent with the hypothesis that the paralimbic-limbic cortex may be functionally disconnected from brain regions which directly mediate their interactions with the external environment. Our findings also provide a reasonable explanation why stable sleep exhibits homeostasis which is far less susceptible to outside world.

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

PubMed

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

2007-01-01

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

Resting state EEG power, intra-hemisphere and inter-hemisphere coherence in bipolar disorder

NASA Astrophysics Data System (ADS)

Handayani, Nita; Khotimah, S. N.; Haryanto, F.; Arif, I.; Taruno, Warsito P.

2017-02-01

This paper examines the differences of EEG power and coherence between bipolar disorder patients and healthy subjects in the resting state. Observations are focused on the prefrontal cortex area by calculating intra-hemisphere and inter-hemisphere coherence. EEG data acquisition are conducted by using wireless Emotiv Epoc on AF3, AF4, FC5, FC6, F7 and F8 channels. The power spectral analysis shows that in bipolar disoder there is an increase of power in the delta, theta and beta frequencies, and power decrease in the alpha frequency. The coherence test results show that both intra-hemisphere and inter-hemisphere coherence in bipolar disorder patients are lower than healthy subjects. This shows the lack of brain synchronization in bipolar disorder patients.

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.

Mining EEG with SVM for Understanding Cognitive Underpinnings of Math Problem Solving Strategies

PubMed Central

López, Julio

2018-01-01

We have developed a new methodology for examining and extracting patterns from brain electric activity by using data mining and machine learning techniques. Data was collected from experiments focused on the study of cognitive processes that might evoke different specific strategies in the resolution of math problems. A binary classification problem was constructed using correlations and phase synchronization between different electroencephalographic channels as characteristics and, as labels or classes, the math performances of individuals participating in specially designed experiments. The proposed methodology is based on using well-established procedures of feature selection, which were used to determine a suitable brain functional network size related to math problem solving strategies and also to discover the most relevant links in this network without including noisy connections or excluding significant connections. PMID:29670667

Mining EEG with SVM for Understanding Cognitive Underpinnings of Math Problem Solving Strategies.

PubMed

Bosch, Paul; Herrera, Mauricio; López, Julio; Maldonado, Sebastián

2018-01-01

We have developed a new methodology for examining and extracting patterns from brain electric activity by using data mining and machine learning techniques. Data was collected from experiments focused on the study of cognitive processes that might evoke different specific strategies in the resolution of math problems. A binary classification problem was constructed using correlations and phase synchronization between different electroencephalographic channels as characteristics and, as labels or classes, the math performances of individuals participating in specially designed experiments. The proposed methodology is based on using well-established procedures of feature selection, which were used to determine a suitable brain functional network size related to math problem solving strategies and also to discover the most relevant links in this network without including noisy connections or excluding significant connections.

[EEG alpha indices in dependence on the menstrual cycle phase and salivary progesterone].

PubMed

Bazanova, O M; Kondratenko, A V; Kuz'minova, O I; Muravleva, K B; Petrova, S E

2014-01-01

The effects of the neurohumoral status on the EEG alpha - activity indices were studied in a within-subject design with 78 women aged 18-27 years during 1-2 menstrual cycle. Psychometric and EEG indices of alpha waves basal body temperature, saliva progesterone and cortisol level were monitored every 2-3 days. Menstrual and follicular recording sessions occurred before the ovulatory temperature rise, luteal recording session--after increasing progesterone level more than 20% respect to previous day and premenstrual sessions after decreasing progesterone level more that 20% respect to previous day. The design consisted of rest and task periods EEG, EMG and ECG recordings. Half the subjects began during their menstrual phase and half began during their luteal phase. All 5 phases were compared for differences between psychometric features EEG alpha activity, EMG and ECG baseline resting levels, as well as for reactivity to cognitive task. The results showed menstrual phase differences in all psychometric and alpha EEG indices. The cognitive fluency, alpha peak frequency, alpha band width, power in alpha-2 frequency range are maximal at luteal, alpha visual activation and reactivity to cognitive task performance--at follicular phase. The hypothesis that the EEG alpha activity depends on the hormonal status supported by the positive association salivary progesterone level with the alpha peak frequency, power in the alpha-2 band and negative--with the power of the alpha-1 band. According these results, we conclude that psycho-physiological recording sessions with women might be provided with a glance to phase of menstrual cycle.

On the Time Course of Synchronization Patterns of Neuronal Discharges in the Human Brain during Cognitive Tasks

PubMed Central

Brázdil, Milan; Janeček, Jiří; Klimeš, Petr; Mareček, Radek; Roman, Robert; Jurák, Pavel; Chládek, Jan; Daniel, Pavel; Rektor, Ivan; Halámek, Josef; Plešinger, Filip; Jirsa, Viktor

2013-01-01

Using intracerebral EEG recordings in a large cohort of human subjects, we investigate the time course of neural cross-talk during a simple cognitive task. Our results show that human brain dynamics undergo a characteristic sequence of synchronization patterns across different frequency bands following a visual oddball stimulus. In particular, an initial global reorganization in the delta and theta bands (2–8 Hz) is followed by gamma (20–95 Hz) and then beta band (12–20 Hz) synchrony. PMID:23696809

Reply to ``Comment on `Performance of different synchronization measures in real data: A case study on electroencephalographic signals' ''

NASA Astrophysics Data System (ADS)

Quian Quiroga, R.; Kraskov, A.; Kreuz, T.; Grassberger, P.

2003-06-01

We agree with the Comment by Duckrow and Albano [Phys. Rev. E 67, 063901 (2003)] that mutual information, estimated with an optimized algorithm, can be a useful tool for studying synchronization in real data. However, we point out that the improvement they found is mainly due to an interesting but nonstandard embedding technique used, and not so much due to the algorithm used for the estimation of mutual information itself. We also address the issue of stationarity of electroencephalographic (EEG) data.

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

PubMed

Subhani, Ahmad Rauf; Likun, Xia; Saeed Malik, Aamir

2012-01-01

Cerebral activation and autonomic nervous system have importance in studies such as mental stress. The aim of this study is to analyze variations in EEG scalp potential which may influence autonomic activation of heart while playing video games. Ten healthy participants were recruited in this study. Electroencephalogram (EEG) and electrocardiogram (ECG) signals were measured simultaneously during playing video game and rest conditions. Sympathetic and parasympathetic innervations of heart were evaluated from heart rate variability (HRV), derived from the ECG. Scalp potential was measured by the EEG. The results showed a significant upsurge in the value theta Fz/alpha Pz (p<0.001) while playing game. The results also showed tachycardia while playing video game as compared to rest condition (p<0.005). Normalized low frequency power and ratio of low frequency/high frequency power were significantly increased while playing video game and normalized high frequency power sank during video games. Results showed synchronized activity of cerebellum and sympathetic and parasympathetic innervation of heart.

Neuroelectrical imaging investigation of cortical activity during listening to music in prelingually deaf children with cochlear implants.

PubMed

Marsella, Pasquale; Scorpecci, Alessandro; Vecchiato, Giovanni; Maglione, Anton Giulio; Colosimo, Alfredo; Babiloni, Fabio

2014-05-01

To date, no objective measure of the pleasantness of music perception by children with cochlear implants has been reported. The EEG alpha asymmetries of pre-frontal cortex activation are known to relate to emotional/affective engagement in a perceived stimulus. More specifically, according to the "withdrawal/approach" model, an unbalanced de-synchronization of the alpha activity in the left prefrontal cortex has been associated with a positive affective state/approach toward a stimulus, and an unbalanced de-synchronization of the same activity in the right prefrontal cortex with a negative affective state/withdrawal from a stimulus. In the present study, High-Resolution EEG with Source Reconstruction was used to compare the music-induced alpha asymmetries of the prefrontal cortex in a group of prelingually deaf implanted children and in a control group of normal-hearing children. Six normal-hearing and six age-matched deaf children using a unilateral cochlear implants underwent High-Resolution EEG recordings as they were listening to a musical cartoon. Musical stimuli were delivered in three versions: Normal, Distort (reverse audio flow) and Mute. The EEG alpha rhythm asymmetry was analyzed: Power Spectral Density was calculated for each Region of Interest, together with a right-left imbalance index. A map of cortical activation was then reconstructed on a realistic cortical model. Asymmetries of EEG alpha rhythm in the prefrontal cortices were observed in both groups. In the normal-hearing children, the asymmetries were consistent with the withdrawal/approach model, whereas in cochlear implant users they were not. Moreover, in implanted children a different pattern of alpha asymmetries in extrafrontal cortical areas was noticed as compared to normal-hearing subjects. The peculiar pattern of alpha asymmetries in implanted children's prefrontal cortex in response to musical stimuli suggests an inability by these subjects to discriminate normal from dissonant music and to appreciate the pleasantness of normal music. High-Resolution EEG may prove to be a promising tool for objectively measuring prefrontal cortex alpha asymmetries in child cochlear implant users. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Inferring Functional Neural Connectivity with Phase Synchronization Analysis: A Review of Methodology

PubMed Central

Sun, Junfeng; Li, Zhijun; Tong, Shanbao

2012-01-01

Functional neural connectivity is drawing increasing attention in neuroscience research. To infer functional connectivity from observed neural signals, various methods have been proposed. Among them, phase synchronization analysis is an important and effective one which examines the relationship of instantaneous phase between neural signals but neglecting the influence of their amplitudes. In this paper, we review the advances in methodologies of phase synchronization analysis. In particular, we discuss the definitions of instantaneous phase, the indexes of phase synchronization and their significance test, the issues that may affect the detection of phase synchronization and the extensions of phase synchronization analysis. In practice, phase synchronization analysis may be affected by observational noise, insufficient samples of the signals, volume conduction, and reference in recording neural signals. We make comments and suggestions on these issues so as to better apply phase synchronization analysis to inferring functional connectivity from neural signals. PMID:22577470

Functional Brain Connectivity as a New Feature for P300 Speller.

PubMed

Kabbara, Aya; Khalil, Mohamad; El-Falou, Wassim; Eid, Hassan; Hassan, Mahmoud

2016-01-01

The brain is a large-scale complex network often referred to as the "connectome". Cognitive functions and information processing are mainly based on the interactions between distant brain regions. However, most of the 'feature extraction' methods used in the context of Brain Computer Interface (BCI) ignored the possible functional relationships between different signals recorded from distinct brain areas. In this paper, the functional connectivity quantified by the phase locking value (PLV) was introduced to characterize the evoked responses (ERPs) obtained in the case of target and non-targets visual stimuli. We also tested the possibility of using the functional connectivity in the context of 'P300 speller'. The proposed approach was compared to the well-known methods proposed in the state of the art of "P300 Speller", mainly the peak picking, the area, time/frequency based features, the xDAWN spatial filtering and the stepwise linear discriminant analysis (SWLDA). The electroencephalographic (EEG) signals recorded from ten subjects were analyzed offline. The results indicated that phase synchrony offers relevant information for the classification in a P300 speller. High synchronization between the brain regions was clearly observed during target trials, although no significant synchronization was detected for a non-target trial. The results showed also that phase synchrony provides higher performance than some existing methods for letter classification in a P300 speller principally when large number of trials is available. Finally, we tested the possible combination of both approaches (classical features and phase synchrony). Our findings showed an overall improvement of the performance of the P300-speller when using Peak picking, the area and frequency based features. Similar performances were obtained compared to xDAWN and SWLDA when using large number of trials.

Using the nonlinear control of anaesthesia-induced hypersensitivity of EEG at burst suppression level to test the effects of radiofrequency radiation on brain function

PubMed Central

Lipping, Tarmo; Rorarius, Michael; Jäntti, Ville; Annala, Kari; Mennander, Ari; Ferenets, Rain; Toivonen, Tommi; Toivo, Tim; Värri, Alpo; Korpinen, Leena

2009-01-01

Background In this study, investigating the effects of mobile phone radiation on test animals, eleven pigs were anaesthetised to the level where burst-suppression pattern appears in the electroencephalogram (EEG). At this level of anaesthesia both human subjects and animals show high sensitivity to external stimuli which produce EEG bursts during suppression. The burst-suppression phenomenon represents a nonlinear control system, where low-amplitude EEG abruptly switches to very high amplitude bursts. This switching can be triggered by very minor stimuli and the phenomenon has been described as hypersensitivity. To test if also radio frequency (RF) stimulation can trigger this nonlinear control, the animals were exposed to pulse modulated signal of a GSM mobile phone at 890 MHz. In the first phase of the experiment electromagnetic field (EMF) stimulation was randomly switched on and off and the relation between EEG bursts and EMF stimulation onsets and endpoints were studied. In the second phase a continuous RF stimulation at 31 W/kg was applied for 10 minutes. The ECG, the EEG, and the subcutaneous temperature were recorded. Results No correlation between the exposure and the EEG burst occurrences was observed in phase I measurements. No significant changes were observed in the EEG activity of the pigs during phase II measurements although several EEG signal analysis methods were applied. The temperature measured subcutaneously from the pigs' head increased by 1.6°C and the heart rate by 14.2 bpm on the average during the 10 min exposure periods. Conclusion The hypothesis that RF radiation would produce sensory stimulation of somatosensory, auditory or visual system or directly affect the brain so as to produce EEG bursts during suppression was not confirmed. PMID:19615084

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.

Phase synchronization of oscillations in cardiovascular and respiratory systems in humans

NASA Astrophysics Data System (ADS)

Tankanag, Arina V.; Grinevich, Andrey A.; Tikhonova, Irina V.; Chaplygina, Alina V.; Chemeris, Nikolay K.

2017-04-01

Phase synchronization between blood flow oscillations of left and right forearm skin sites, heart rate variability (HRV) and breath rate were studied from healthy volunteers at rest. The degree of synchronization between the phases of the analyzed signals was estimated from the value of the wavelet phase coherence. High medians of values of phase wavelet coherence function were obtained for the endothelial, neurogenic, myogenic and cardiac intervals. Significant phase synchronization were demonstrated between HRV and skin blood flow oscillations in both left and right forearms in a wide frequency range from 0.04 to 0.4 Hz. Six participants exhibited low phase synchronization (< 0.5) between the breath rate and HRV, while nine participants had high phase synchronization (> 0.5). This distribution was not affected by the sex or sympathovagal status of volunteers. Participants with low phase synchronization between breath rate and HRV featured low phase synchronization (< 0.5) between breath rate and blood flow oscillations in both forearms. Contrariwise, in subjects with high phase synchronization between respiratory rhythm and HRV both low and high phase synchronization between breath rate and blood flow oscillations in both forearms was observed. The results obtained allow us to suggest that the organism possesses a mechanism mediating the synchronization of blood flow oscillations in the skin microvasculature with all other periodical processes across the cardiovascular system, in particular, with HRV and breath rate over a wide frequency range.

Epileptic Seizure Detection with Log-Euclidean Gaussian Kernel-Based Sparse Representation.

PubMed

Yuan, Shasha; Zhou, Weidong; Wu, Qi; Zhang, Yanli

2016-05-01

Epileptic seizure detection plays an important role in the diagnosis of epilepsy and reducing the massive workload of reviewing electroencephalography (EEG) recordings. In this work, a novel algorithm is developed to detect seizures employing log-Euclidean Gaussian kernel-based sparse representation (SR) in long-term EEG recordings. Unlike the traditional SR for vector data in Euclidean space, the log-Euclidean Gaussian kernel-based SR framework is proposed for seizure detection in the space of the symmetric positive definite (SPD) matrices, which form a Riemannian manifold. Since the Riemannian manifold is nonlinear, the log-Euclidean Gaussian kernel function is applied to embed it into a reproducing kernel Hilbert space (RKHS) for performing SR. The EEG signals of all channels are divided into epochs and the SPD matrices representing EEG epochs are generated by covariance descriptors. Then, the testing samples are sparsely coded over the dictionary composed by training samples utilizing log-Euclidean Gaussian kernel-based SR. The classification of testing samples is achieved by computing the minimal reconstructed residuals. The proposed method is evaluated on the Freiburg EEG dataset of 21 patients and shows its notable performance on both epoch-based and event-based assessments. Moreover, this method handles multiple channels of EEG recordings synchronously which is more speedy and efficient than traditional seizure detection methods.

Decoding English Alphabet Letters Using EEG Phase Information

PubMed Central

Wang, YiYan; Wang, Pingxiao; Yu, Yuguo

2018-01-01

Increasing evidence indicates that the phase pattern and power of the low frequency oscillations of brain electroencephalograms (EEG) contain significant information during the human cognition of sensory signals such as auditory and visual stimuli. Here, we investigate whether and how the letters of the alphabet can be directly decoded from EEG phase and power data. In addition, we investigate how different band oscillations contribute to the classification and determine the critical time periods. An English letter recognition task was assigned, and statistical analyses were conducted to decode the EEG signal corresponding to each letter visualized on a computer screen. We applied support vector machine (SVM) with gradient descent method to learn the potential features for classification. It was observed that the EEG phase signals have a higher decoding accuracy than the oscillation power information. Low-frequency theta and alpha oscillations have phase information with higher accuracy than do other bands. The decoding performance was best when the analysis period began from 180 to 380 ms after stimulus presentation, especially in the lateral occipital and posterior temporal scalp regions (PO7 and PO8). These results may provide a new approach for brain-computer interface techniques (BCI) and may deepen our understanding of EEG oscillations in cognition. PMID:29467615

Unfavorable surgical outcomes in partial epilepsy with secondary bilateral synchrony: Intracranial electroencephalography study.

PubMed

Sunwoo, Jun-Sang; Byun, Jung-Ick; Moon, Jangsup; Lim, Jung-Ah; Kim, Tae-Joon; Lee, Soon-Tae; Jung, Keun-Hwa; Park, Kyung-Il; Chu, Kon; Kim, Manho; Chung, Chun-Kee; Jung, Ki-Young; Lee, Sang Kun

2016-05-01

Secondary bilateral synchrony (SBS) indicates bilaterally synchronous epileptiform discharges arising from a focal cortical origin. The present study aims to investigate SBS in partial epilepsy with regard to surgical outcomes and intracranial EEG findings. We retrospectively reviewed consecutive patients who underwent epilepsy surgery following extraoperative intracranial electroencephalography (EEG) study from 2008 to 2012. The presence of SBS was determined based upon the results of scalp EEG monitoring performed for presurgical evaluations. We reviewed scalp EEG, neuroimaging, intracranial EEG findings, and surgical outcomes in patients with SBS. We found 12 patients with SBS who were surgically treated for intractable partial epilepsy. Nine (75%) patients had lateralized ictal semiology and only two (16.6%) patients showed localized ictal onset in scalp EEG. Brain MRI showed epileptogenic lesion in three (25%) patients. Intracranial EEG demonstrated that ictal onset zone was widespread or non-localized in six (50%) patients. Low-voltage fast activity was the most common ictal onset EEG pattern. Rapid propagation of ictal onset was noted in 10 (83.3%) patients. Eleven patients underwent resective epilepsy surgery and only two patients (18.2%) achieved seizure-freedom (median follow-up 56 months). MRI-visible brain lesions were associated with favorable outcomes (p=0.024). Patients with SBS, compared to frontal lobe epilepsy without SBS, showed lesser localization in ictal onset EEG (p=0.029) and more rapid propagation during evolution of ictal rhythm (p=0.015). The present results suggested that resective surgery for partial epilepsy with SBS should be decided carefully, especially in case of nonlesional epilepsy. Poor localization and rapid spread of ictal onset were prominent in intracranial EEG, which might contribute to incomplete resection of the epileptogenic zone and poor surgical outcomes. Copyright © 2016 Elsevier B.V. All rights reserved.

Moderate unconjugated hyperbilirubinemia causes a transient but delayed suppression of amplitude-integrated electroencephalographic activity in preterm infants.

PubMed

Ter Horst, Hendrik J; Bos, Arend F; Duijvendijk, Jildou; Hulzebos, Christian V

2012-01-01

Unconjugated hyperbilirubinemia occurs frequently in preterm infants and may result in bilirubin encephalopathy. Amplitude-integrated electroencephalography (aEEG) is used to evaluate brain function in newborns. To investigate the influence of total serum bilirubin (TSB) on the aEEG amplitude of preterm infants and to evaluate aEEG as a noninvasive method to identify acute bilirubin encephalopathy. We performed a prospective observational study of 34 infants with a gestational age (GA) of 26-31 6/7 weeks. Infants had aEEG recordings on the 1st-5th, 8th and 15th day after birth. Infants with asphyxia, intraventricular hemorrhage >grade I or circulatory insufficiency were excluded. aEEG was evaluated by calculating the mean 5th, 50th and 95th centiles of the aEEG amplitudes. TSB peaked on the 4th day after birth. There was no synchronous relationship between TSB and aEEG amplitudes. The 5th, 50th, and 95th aEEG amplitude centiles on the 8th day correlated negatively with the TSB peak value (r = -0.37, p = 0.048; r = -0.60, p = 0.001; r = -0.44, p = 0.017, respectively), irrespective of GA. The 5th and 50th aEEG amplitude centiles increased with increasing GA (r = 0.45, p < 0.001, and r = 0.26, p < 0.001, respectively) and postnatal age (r = 0.25, p < 0.001, and r = 0.16, p = 0.023, respectively). TSB had no direct effect on aEEG amplitudes in preterm infants. There is, however, a delayed effect on electrocerebral activity in the 2nd week after birth. Copyright © 2012 S. Karger AG, Basel.

Individual Differences in Rhythmic Cortical Entrainment Correlate with Predictive Behavior in Sensorimotor Synchronization

PubMed Central

Nozaradan, Sylvie; Peretz, Isabelle; Keller, Peter E.

2016-01-01

The current study aims at characterizing the mechanisms that allow humans to entrain the mind and body to incoming rhythmic sensory inputs in real time. We addressed this unresolved issue by examining the relationship between covert neural processes and overt behavior in the context of musical rhythm. We measured temporal prediction abilities, sensorimotor synchronization accuracy and neural entrainment to auditory rhythms as captured using an EEG frequency-tagging approach. Importantly, movement synchronization accuracy with a rhythmic beat could be explained by the amplitude of neural activity selectively locked with the beat period when listening to the rhythmic inputs. Furthermore, stronger endogenous neural entrainment at the beat frequency was associated with superior temporal prediction abilities. Together, these results reveal a direct link between cortical and behavioral measures of rhythmic entrainment, thus providing evidence that frequency-tagged brain activity has functional relevance for beat perception and synchronization. PMID:26847160

Individual Differences in Rhythmic Cortical Entrainment Correlate with Predictive Behavior in Sensorimotor Synchronization.

PubMed

Nozaradan, Sylvie; Peretz, Isabelle; Keller, Peter E

2016-02-05

The current study aims at characterizing the mechanisms that allow humans to entrain the mind and body to incoming rhythmic sensory inputs in real time. We addressed this unresolved issue by examining the relationship between covert neural processes and overt behavior in the context of musical rhythm. We measured temporal prediction abilities, sensorimotor synchronization accuracy and neural entrainment to auditory rhythms as captured using an EEG frequency-tagging approach. Importantly, movement synchronization accuracy with a rhythmic beat could be explained by the amplitude of neural activity selectively locked with the beat period when listening to the rhythmic inputs. Furthermore, stronger endogenous neural entrainment at the beat frequency was associated with superior temporal prediction abilities. Together, these results reveal a direct link between cortical and behavioral measures of rhythmic entrainment, thus providing evidence that frequency-tagged brain activity has functional relevance for beat perception and synchronization.

Prefrontal, posterior parietal and sensorimotor network activity underlying speed control during walking

PubMed Central

Bulea, Thomas C.; Kim, Jonghyun; Damiano, Diane L.; Stanley, Christopher J.; Park, Hyung-Soon

2015-01-01

Accumulating evidence suggests cortical circuits may contribute to control of human locomotion. Here, noninvasive electroencephalography (EEG) recorded from able-bodied volunteers during a novel treadmill walking paradigm was used to assess neural correlates of walking. A systematic processing method, including a recently developed subspace reconstruction algorithm, reduced movement-related EEG artifact prior to independent component analysis and dipole source localization. We quantified cortical activity while participants tracked slow and fast target speeds across two treadmill conditions: an active mode that adjusted belt speed based on user movements and a passive mode reflecting a typical treadmill. Our results reveal frequency specific, multi-focal task related changes in cortical oscillations elicited by active walking. Low γ band power, localized to the prefrontal and posterior parietal cortices, was significantly increased during double support and early swing phases, critical points in the gait cycle since the active controller adjusted speed based on pelvis position and swing foot velocity. These phasic γ band synchronizations provide evidence that prefrontal and posterior parietal networks, previously implicated in visuo-spatial and somotosensory integration, are engaged to enhance lower limb control during gait. Sustained μ and β band desynchronization within sensorimotor cortex, a neural correlate for movement, was observed during walking thereby validating our methods for isolating cortical activity. Our results also demonstrate the utility of EEG recorded during locomotion for probing the multi-regional cortical networks which underpin its execution. For example, the cortical network engagement elicited by the active treadmill suggests that it may enhance neuroplasticity for more effective motor training. PMID:26029077

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.

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.

Mapping the Information Trace in Local Field Potentials by a Computational Method of Two-Dimensional Time-Shifting Synchronization Likelihood Based on Graphic Processing Unit Acceleration.

PubMed

Zhao, Zi-Fang; Li, Xue-Zhu; Wan, You

2017-12-01

The local field potential (LFP) is a signal reflecting the electrical activity of neurons surrounding the electrode tip. Synchronization between LFP signals provides important details about how neural networks are organized. Synchronization between two distant brain regions is hard to detect using linear synchronization algorithms like correlation and coherence. Synchronization likelihood (SL) is a non-linear synchronization-detecting algorithm widely used in studies of neural signals from two distant brain areas. One drawback of non-linear algorithms is the heavy computational burden. In the present study, we proposed a graphic processing unit (GPU)-accelerated implementation of an SL algorithm with optional 2-dimensional time-shifting. We tested the algorithm with both artificial data and raw LFP data. The results showed that this method revealed detailed information from original data with the synchronization values of two temporal axes, delay time and onset time, and thus can be used to reconstruct the temporal structure of a neural network. Our results suggest that this GPU-accelerated method can be extended to other algorithms for processing time-series signals (like EEG and fMRI) using similar recording techniques.

Termination Patterns of Complex Partial Seizures: An Intracranial EEG Study

PubMed Central

Afra, Pegah; Jouny, Christopher C.; Bergey, Gregory K.

2015-01-01

Purpose While seizure onset patterns have been the subject of many reports, there have been few studies of seizure termination. In this study we report the incidence of synchronous and asynchronous termination patterns of partial seizures recorded with intracranial arrays. Methods Data were collected from patients with intractable complex partial seizures undergoing presurgical evaluations with intracranial electrodes. Patients with seizures originating from mesial temporal and neocortical regions were grouped into three groups based on patterns of seizure termination: synchronous only (So), asynchronous only (Ao), or mixed (S/A, with both synchronous and asynchronous termination patterns). Results 88% of the patients in the MT group had seizures with a synchronous pattern of termination exclusively (38%) or mixed (50%). 82% of the NC group had seizures with synchronous pattern of termination exclusively (52%) or mixed (30%). In the NC group, there was a significant difference of the range of seizure durations between So and Ao groups, with Ao exhibiting higher variability. Seizures with synchronous termination had low variability in both groups. Conclusions Synchronous seizure termination is a common pattern for complex partial seizures of both mesial temporal or neocortical onset. This may reflect stereotyped network behavior or dynamics at the seizure focus. PMID:26552555

Temporal entrainment of cognitive functions: musical mnemonics induce brain plasticity and oscillatory synchrony in neural networks underlying memory.

PubMed

Thaut, Michael H; Peterson, David A; McIntosh, Gerald C

2005-12-01

In a series of experiments, we have begun to investigate the effect of music as a mnemonic device on learning and memory and the underlying plasticity of oscillatory neural networks. We used verbal learning and memory tests (standardized word lists, AVLT) in conjunction with electroencephalographic analysis to determine differences between verbal learning in either a spoken or musical (verbal materials as song lyrics) modality. In healthy adults, learning in both the spoken and music condition was associated with significant increases in oscillatory synchrony across all frequency bands. A significant difference between the spoken and music condition emerged in the cortical topography of the learning-related synchronization. When using EEG measures as predictors during learning for subsequent successful memory recall, significantly increased coherence (phase-locked synchronization) within and between oscillatory brain networks emerged for music in alpha and gamma bands. In a similar study with multiple sclerosis patients, superior learning and memory was shown in the music condition when controlled for word order recall, and subjects were instructed to sing back the word lists. Also, the music condition was associated with a significant power increase in the low-alpha band in bilateral frontal networks, indicating increased neuronal synchronization. Musical learning may access compensatory pathways for memory functions during compromised PFC functions associated with learning and recall. Music learning may also confer a neurophysiological advantage through the stronger synchronization of the neuronal cell assemblies underlying verbal learning and memory. Collectively our data provide evidence that melodic-rhythmic templates as temporal structures in music may drive internal rhythm formation in recurrent cortical networks involved in learning and memory.

The dynamics of human cognition: Increasing global integration coupled with decreasing segregation found using iEEG.

PubMed

Cruzat, Josephine; Deco, Gustavo; Tauste-Campo, Adrià; Principe, Alessandro; Costa, Albert; Kringelbach, Morten L; Rocamora, Rodrigo

2018-05-15

Cognitive processing requires the ability to flexibly integrate and process information across large brain networks. How do brain networks dynamically reorganize to allow broad communication between many different brain regions in order to integrate information? We record neural activity from 12 epileptic patients using intracranial EEG while performing three cognitive tasks. We assess how the functional connectivity between different brain areas changes to facilitate communication across them. At the topological level, this facilitation is characterized by measures of integration and segregation. Across all patients, we found significant increases in integration and decreases in segregation during cognitive processing, especially in the gamma band (50-90 Hz). We also found higher levels of global synchronization and functional connectivity during task execution, again particularly in the gamma band. More importantly, functional connectivity modulations were not caused by changes in the level of the underlying oscillations. Instead, these modulations were caused by a rearrangement of the mutual synchronization between the different nodes as proposed by the "Communication Through Coherence" Theory. Copyright © 2018 Elsevier Inc. All rights reserved.

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

PubMed Central

Sturm, Irene; Dähne, Sven; Blankertz, Benjamin; Curio, Gabriel

2015-01-01

Note onsets in music are acoustic landmarks providing auditory cues that underlie the perception of more complex phenomena such as beat, rhythm, and meter. For naturalistic ongoing sounds a detailed view on the neural representation of onset structure is hard to obtain, since, typically, stimulus-related EEG signatures are derived by averaging a high number of identical stimulus presentations. Here, we propose a novel multivariate regression-based method extracting onset-related brain responses from the ongoing EEG. We analyse EEG recordings of nine subjects who passively listened to stimuli from various sound categories encompassing simple tone sequences, full-length romantic piano pieces and natural (non-music) soundscapes. The regression approach reduces the 61-channel EEG to one time course optimally reflecting note onsets. The neural signatures derived by this procedure indeed resemble canonical onset-related ERPs, such as the N1-P2 complex. This EEG projection was then utilized to determine the Cortico-Acoustic Correlation (CACor), a measure of synchronization between EEG signal and stimulus. We demonstrate that a significant CACor (i) can be detected in an individual listener's EEG of a single presentation of a full-length complex naturalistic music stimulus, and (ii) it co-varies with the stimuli’s average magnitudes of sharpness, spectral centroid, and rhythmic complexity. In particular, the subset of stimuli eliciting a strong CACor also produces strongly coordinated tension ratings obtained from an independent listener group in a separate behavioral experiment. Thus musical features that lead to a marked physiological reflection of tone onsets also contribute to perceived tension in music. PMID:26510120

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

PubMed

Sturm, Irene; Dähne, Sven; Blankertz, Benjamin; Curio, Gabriel

2015-01-01

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

Neural Entrainment to Auditory Imagery of Rhythms.

PubMed

Okawa, Haruki; Suefusa, Kaori; Tanaka, Toshihisa

2017-01-01

A method of reconstructing perceived or imagined music by analyzing brain activity has not yet been established. As a first step toward developing such a method, we aimed to reconstruct the imagery of rhythm, which is one element of music. It has been reported that a periodic electroencephalogram (EEG) response is elicited while a human imagines a binary or ternary meter on a musical beat. However, it is not clear whether or not brain activity synchronizes with fully imagined beat and meter without auditory stimuli. To investigate neural entrainment to imagined rhythm during auditory imagery of beat and meter, we recorded EEG while nine participants (eight males and one female) imagined three types of rhythm without auditory stimuli but with visual timing, and then we analyzed the amplitude spectra of the EEG. We also recorded EEG while the participants only gazed at the visual timing as a control condition to confirm the visual effect. Furthermore, we derived features of the EEG using canonical correlation analysis (CCA) and conducted an experiment to individually classify the three types of imagined rhythm from the EEG. The results showed that classification accuracies exceeded the chance level in all participants. These results suggest that auditory imagery of meter elicits a periodic EEG response that changes at the imagined beat and meter frequency even in the fully imagined conditions. This study represents the first step toward the realization of a method for reconstructing the imagined music from brain activity.

Neuroelectrical Decomposition of Spontaneous Brain Activity Measured with Functional Magnetic Resonance Imaging

PubMed Central

Liu, Zhongming; de Zwart, Jacco A.; Chang, Catie; Duan, Qi; van Gelderen, Peter; Duyn, Jeff H.

2014-01-01

Spontaneous activity in the human brain occurs in complex spatiotemporal patterns that may reflect functionally specialized neural networks. Here, we propose a subspace analysis method to elucidate large-scale networks by the joint analysis of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data. The new approach is based on the notion that the neuroelectrical activity underlying the fMRI signal may have EEG spectral features that report on regional neuronal dynamics and interregional interactions. Applying this approach to resting healthy adults, we indeed found characteristic spectral signatures in the EEG correlates of spontaneous fMRI signals at individual brain regions as well as the temporal synchronization among widely distributed regions. These spectral signatures not only allowed us to parcel the brain into clusters that resembled the brain's established functional subdivision, but also offered important clues for disentangling the involvement of individual regions in fMRI network activity. PMID:23796947

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.

[EEG-correlates of pilots' functional condition in simulated flight dynamics].

PubMed

Kiroy, V N; Aslanyan, E V; Bakhtin, O M; Minyaeva, N R; Lazurenko, D M

2015-01-01

The spectral characteristics of the EEG recorded on two professional pilots in the simulator TU-154 aircraft in flight dynamics, including takeoff, landing and horizontal flight (in particular during difficult conditions) were analyzed. EEG recording was made with frequency band 0.1-70 Hz continuously from 15 electrodes. The EEG recordings were evaluated using analysis of variance and discriminant analysis. Statistical significant of the identified differences and the influence of the main factors and their interactions were evaluated using Greenhouse - Gaiser corrections. It was shown that the spectral characteristics of the EEG are highly informative features of the state of the pilots, reflecting the different flight phases. High validity ofthe differences including individual characteristic, indicates their non-random nature and the possibility of constructing a system of pilots' state control during all phases of flight, based on EEG features.

Synchronous, Alternating, and Phase-Locked Stridulation by a Tropical Katydid

NASA Astrophysics Data System (ADS)

Sismondo, Enrico

1990-07-01

In the field the chirps of neighboring Mecopoda sp. (Orthoptera, Tettigoniidae, and Mecopodinae) males are normally synchronized, but between more distant individuals the chirps are either synchronous or regularly alternating. The phase response to single-stimulus chirps depends on both the phase and the intensity of the stimulus. Iteration of the Poincare map of the phase response predicts a variety of phase-locked synchronization regimes, including period-doubling bifurcations, in close agreement with experimental observations. The versatile acoustic behavior of Mecopoda encompasses most of the phenomena found in other synchronizing insects and thus provides a general model of insect synchronization behavior.

Synthesis and evaluation of phase detectors for active bit synchronizers

NASA Technical Reports Server (NTRS)

Mcbride, A. L.

1974-01-01

Self-synchronizing digital data communication systems usually use active or phase-locked loop (PLL) bit synchronizers. The three main elements of PLL synchronizers are the phase detector, loop filter, and the voltage controlled oscillator. Of these three elements, phase detector synthesis is the main source of difficulty, particularly when the received signals are demodulated square-wave signals. A phase detector synthesis technique is reviewed that provides a physically realizable design for bit synchronizer phase detectors. The development is based upon nonlinear recursive estimation methods. The phase detector portion of the algorithm is isolated and analyzed.

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.

Characteristic changes in brain electrical activity due to chronic hypoxia in patients with obstructive sleep apnea syndrome (OSAS): a combined EEG study using LORETA and omega complexity.

PubMed

Toth, Marton; Faludi, Bela; Wackermann, Jiri; Czopf, Jozsef; Kondakor, Istvan

2009-11-01

EEG background activity of patients with obstructive sleep apnea syndrome (OSAS, N = 25) was compared to that of normal controls (N = 14) to reflect alterations of brain electrical activity caused by chronic intermittent hypoxia in OSAS. Global and regional (left vs. right, anterior vs. posterior) measures of spatial complexity (Omega) were used to characterize the degree of spatial synchrony of EEG. Low resolution electromagnetic tomography (LORETA) was used to localize generators of EEG activity in separate frequency bands. Comparing patients to controls, lower Omega complexity was found globally and in the right hemisphere. Using LORETA, an increased medium frequency activity was seen bilaterally in the precuneus, paracentral and posterior cingulate cortex. These findings indicate that alterations caused by chronic hypoxia in brain electrical activity in regions associated with influencing emotional regulation, long-term memory and the default mode network. Global synchronization (lower Omega complexity) may indicate a significantly reduced number of relatively independent, parallel neural processes due to chronic global hypoxic state in apneic patients as well as over the right hemisphere.

Electroencephalography signatures of attention-deficit/hyperactivity disorder: clinical utility.

PubMed

Alba, Guzmán; Pereda, Ernesto; Mañas, Soledad; Méndez, Leopoldo D; González, Almudena; González, Julián J

2015-01-01

The techniques and the most important results on the use of electroencephalography (EEG) to extract different measures are reviewed in this work, which can be clinically useful to study subjects with attention-deficit/hyperactivity disorder (ADHD). First, we discuss briefly and in simple terms the EEG analysis and processing techniques most used in the context of ADHD. We review techniques that both analyze individual EEG channels (univariate measures) and study the statistical interdependence between different EEG channels (multivariate measures), the so-called functional brain connectivity. Among the former ones, we review the classical indices of absolute and relative spectral power and estimations of the complexity of the channels, such as the approximate entropy and the Lempel-Ziv complexity. Among the latter ones, we focus on the magnitude square coherence and on different measures based on the concept of generalized synchronization and its estimation in the state space. Second, from a historical point of view, we present the most important results achieved with these techniques and their clinical utility (sensitivity, specificity, and accuracy) to diagnose ADHD. Finally, we propose future research lines based on these results.

A user-friendly SSVEP-based brain-computer interface using a time-domain classifier.

PubMed

Luo, An; Sullivan, Thomas J

2010-04-01

We introduce a user-friendly steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) system. Single-channel EEG is recorded using a low-noise dry electrode. Compared to traditional gel-based multi-sensor EEG systems, a dry sensor proves to be more convenient, comfortable and cost effective. A hardware system was built that displays four LED light panels flashing at different frequencies and synchronizes with EEG acquisition. The visual stimuli have been carefully designed such that potential risk to photosensitive people is minimized. We describe a novel stimulus-locked inter-trace correlation (SLIC) method for SSVEP classification using EEG time-locked to stimulus onsets. We studied how the performance of the algorithm is affected by different selection of parameters. Using the SLIC method, the average light detection rate is 75.8% with very low error rates (an 8.4% false positive rate and a 1.3% misclassification rate). Compared to a traditional frequency-domain-based method, the SLIC method is more robust (resulting in less annoyance to the users) and is also suitable for irregular stimulus patterns.

Comment on ``Performance of different synchronization measures in real data: A case study on electroencephalographic signals''

NASA Astrophysics Data System (ADS)

Nicolaou, N.; Nasuto, S. J.

2005-12-01

We agree with Duckrow and Albano [Phys. Rev. E 67, 063901 (2003)] and Quian Quiroga [Phys. Rev. E 67, 063902 (2003)] that mutual information (MI) is a useful measure of dependence for electroencephalogram (EEG) data, but we show that the improvement seen in the performance of MI on extracting dependence trends from EEG is more dependent on the type of MI estimator rather than any embedding technique used. In an independent study we conducted in search for an optimal MI estimator, and in particular for EEG applications, we examined the performance of a number of MI estimators on the data set used by Quian Quiroga in their original study, where the performance of different dependence measures on real data was investigated [Phys. Rev. E 65, 041903 (2002)]. We show that for EEG applications the best performance among the investigated estimators is achieved by k -nearest neighbors, which supports the conjecture by Quian Quiroga in Phys. Rev. E 67, 063902 (2003) that the nearest neighbor estimator is the most precise method for estimating MI.

Real-time EEG-based detection of fatigue driving danger for accident prediction.

PubMed

Wang, Hong; Zhang, Chi; Shi, Tianwei; Wang, Fuwang; Ma, Shujun

2015-03-01

This paper proposes a real-time electroencephalogram (EEG)-based detection method of the potential danger during fatigue driving. To determine driver fatigue in real time, wavelet entropy with a sliding window and pulse coupled neural network (PCNN) were used to process the EEG signals in the visual area (the main information input route). To detect the fatigue danger, the neural mechanism of driver fatigue was analyzed. The functional brain networks were employed to track the fatigue impact on processing capacity of brain. The results show the overall functional connectivity of the subjects is weakened after long time driving tasks. The regularity is summarized as the fatigue convergence phenomenon. Based on the fatigue convergence phenomenon, we combined both the input and global synchronizations of brain together to calculate the residual amount of the information processing capacity of brain to obtain the dangerous points in real time. Finally, the danger detection system of the driver fatigue based on the neural mechanism was validated using accident EEG. The time distributions of the output danger points of the system have a good agreement with those of the real accident points.

EEG-based classification of imaginary left and right foot movements using beta rebound.

PubMed

Hashimoto, Yasunari; Ushiba, Junichi

2013-11-01

The purpose of this study was to investigate cortical lateralization of event-related (de)synchronization during left and right foot motor imagery tasks and to determine classification accuracy of the two imaginary movements in a brain-computer interface (BCI) paradigm. We recorded 31-channel scalp electroencephalograms (EEGs) from nine healthy subjects during brisk imagery tasks of left and right foot movements. EEG was analyzed with time-frequency maps and topographies, and the accuracy rate of classification between left and right foot movements was calculated. Beta rebound at the end of imagination (increase of EEG beta rhythm amplitude) was identified from the two EEGs derived from the right-shift and left-shift bipolar pairs at the vertex. This process enabled discrimination between right or left foot imagery at a high accuracy rate (maximum 81.6% in single trial analysis). These data suggest that foot motor imagery has potential to elicit left-right differences in EEG, while BCI using the unilateral foot imagery can achieve high classification accuracy, similar to ordinary BCI, based on hand motor imagery. By combining conventional discrimination techniques, the left-right discrimination of unilateral foot motor imagery provides a novel BCI system that could control a foot neuroprosthesis or a robotic foot. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Cell Cycle Synchronization of HeLa Cells to Assay EGFR Pathway Activation.

PubMed

Wee, Ping; Wang, Zhixiang

2017-01-01

Progression through the cell cycle causes changes in the cell's signaling pathways that can alter EGFR signal transduction. Here, we describe drug-derived protocols to synchronize HeLa cells in various phases of the cell cycle, including G1 phase, S phase, G2 phase, and mitosis, specifically in the mitotic stages of prometaphase, metaphase, and anaphase/telophase. The synchronization procedures are designed to allow synchronized cells to be treated for EGF and collected for the purpose of Western blotting for EGFR signal transduction components.S phase synchronization is performed by thymidine block, G2 phase with roscovitine, prometaphase with nocodazole, metaphase with MG132, and anaphase/telophase with blebbistatin. G1 phase synchronization is performed by culturing synchronized mitotic cells obtained by mitotic shake-off. We also provide methods to validate the synchronization methods. For validation by Western blotting, we provide the temporal expression of various cell cycle markers that are used to check the quality of the synchronization. For validation of mitotic synchronization by microscopy, we provide a guide that describes the physical properties of each mitotic stage, using their cellular morphology and DNA appearance. For validation by flow cytometry, we describe the use of imaging flow cytometry to distinguish between the phases of the cell cycle, including between each stage of mitosis.

Automatic sleep stage classification using two-channel electro-oculography.

PubMed

Virkkala, Jussi; Hasan, Joel; Värri, Alpo; Himanen, Sari-Leena; Müller, Kiti

2007-10-15

An automatic method for the classification of wakefulness and sleep stages SREM, S1, S2 and SWS was developed based on our two previous studies. The method is based on a two-channel electro-oculography (EOG) referenced to the left mastoid (M1). Synchronous electroencephalographic (EEG) activity in S2 and SWS was detected by calculating cross-correlation and peak-to-peak amplitude difference in the 0.5-6 Hz band between the two EOG channels. An automatic slow eye-movement (SEM) estimation was used to indicate wakefulness, SREM and S1. Beta power 18-30 Hz and alpha power 8-12 Hz was also used for wakefulness detection. Synchronous 1.5-6 Hz EEG activity and absence of large eye movements was used for S1 separation from SREM. Simple smoothing rules were also applied. Sleep EEG, EOG and EMG were recorded from 265 subjects. The system was tuned using data from 132 training subjects and then applied to data from 131 validation subjects that were different to the training subjects. Cohen's Kappa between the visual and the developed new automatic scoring in separating 30s wakefulness, SREM, S1, S2 and SWS epochs was substantial 0.62 with epoch by epoch agreement of 72%. With automatic subject specific alpha thresholds for offline applications results improved to 0.63 and 73%. The automatic method can be further developed and applied for ambulatory sleep recordings by using only four disposable, self-adhesive and self-applicable electrodes.

Thalamocortical and intracortical laminar connectivity determines sleep spindle properties.

PubMed

Krishnan, Giri P; Rosen, Burke Q; Chen, Jen-Yung; Muller, Lyle; Sejnowski, Terrence J; Cash, Sydney S; Halgren, Eric; Bazhenov, Maxim

2018-06-27

Sleep spindles are brief oscillatory events during non-rapid eye movement (NREM) sleep. Spindle density and synchronization properties are different in MEG versus EEG recordings in humans and also vary with learning performance, suggesting spindle involvement in memory consolidation. Here, using computational models, we identified network mechanisms that may explain differences in spindle properties across cortical structures. First, we report that differences in spindle occurrence between MEG and EEG data may arise from the contrasting properties of the core and matrix thalamocortical systems. The matrix system, projecting superficially, has wider thalamocortical fanout compared to the core system, which projects to middle layers, and requires the recruitment of a larger population of neurons to initiate a spindle. This property was sufficient to explain lower spindle density and higher spatial synchrony of spindles in the superficial cortical layers, as observed in the EEG signal. In contrast, spindles in the core system occurred more frequently but less synchronously, as observed in the MEG recordings. Furthermore, consistent with human recordings, in the model, spindles occurred independently in the core system but the matrix system spindles commonly co-occurred with core spindles. We also found that the intracortical excitatory connections from layer III/IV to layer V promote spindle propagation from the core to the matrix system, leading to widespread spindle activity. Our study predicts that plasticity of intra- and inter-cortical connectivity can potentially be a mechanism for increased spindle density as has been observed during learning.

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.

Detection of Nonverbal Synchronization through Phase Difference in Human Communication.

PubMed

Kwon, Jinhwan; Ogawa, Ken-ichiro; Ono, Eisuke; Miyake, Yoshihiro

2015-01-01

Nonverbal communication is an important factor in human communication, and body movement synchronization in particular is an important part of nonverbal communication. Some researchers have analyzed body movement synchronization by focusing on changes in the amplitude of body movements. However, the definition of "body movement synchronization" is still unclear. From a theoretical viewpoint, phase difference is the most important factor in synchronization analysis. Therefore, there is a need to measure the synchronization of body movements using phase difference. The purpose of this study was to provide a quantitative definition of the phase difference distribution for detecting body movement synchronization in human communication. The phase difference distribution was characterized using four statistical measurements: density, mean phase difference, standard deviation (SD) and kurtosis. To confirm the effectiveness of our definition, we applied it to human communication in which the roles of speaker and listener were defined. Specifically, we examined the difference in the phase difference distribution between two different communication situations: face-to-face communication with visual interaction and remote communication with unidirectional visual perception. Participant pairs performed a task supposing lecture in the face-to-face communication condition and in the remote communication condition via television. Throughout the lecture task, we extracted a set of phase differences from the time-series data of the acceleration norm of head nodding motions between two participants. Statistical analyses of the phase difference distribution revealed the characteristics of head nodding synchronization. Although the mean phase differences in synchronized head nods did not differ significantly between the conditions, there were significant differences in the densities, the SDs and the kurtoses of the phase difference distributions of synchronized head nods. These results show the difference in nonverbal synchronization between different communication types. Our study indicates that the phase difference distribution is useful in detecting nonverbal synchronization in various human communication situations.

Plastic modulation of PTSD resting-state networks by EEG neurofeedback

PubMed Central

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

2015-01-01

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

[Features of brain biopotentials' spatial organization in adolescents].

PubMed

Kruchinina, O V; Gal'perina, E I; Shepoval'nikov, A N

2014-01-01

Adolescence is characterized by an intensive formation of inter-regional cortical fields interaction, in this period significantly reorganized the activities of deep brain structures and cortical-subcortical interaction are enhanced. Our objectives were to evaluate the nature of changes in the spatial organization of brain bioelectric potentials with age and characteristics of such an organization in adolescents. For this purpose, EEG studies have been conducted in 230 subjects of both sexes aged 4 to 35 years. We estimated interdependent changes of biopotentials correlations fluctuations in 20-lead EEG, using the integral index Vol. Analyzed age-related changes of EEG correlations in rest condition and during verbal activity (Russian and English texts audition). Verbal tasks were sued in subjects over 8 years. It was found that the spatial synchronization of the EEG both in background and verbal activity increases with age, but after 20 years the rate of change is significantly reduced. In adolescence (12-17 years old), sex differences appear between the degree of EEG coherence processes occurring in the left and right hemispheres in subjects performing verbal tasks. In males 12 to 14 years nonlinear changes in overall correlation (indicators VOL) was observed, whereas in females of this age systemic reorganization of the brain interrelations occurs more smoothly, ahead of 1.5-2 years.

Anatomical connectivity influences both intra- and inter-brain synchronizations.

PubMed

Dumas, Guillaume; Chavez, Mario; Nadel, Jacqueline; Martinerie, Jacques

2012-01-01

Recent development in diffusion spectrum brain imaging combined to functional simulation has the potential to further our understanding of how structure and dynamics are intertwined in the human brain. At the intra-individual scale, neurocomputational models have already started to uncover how the human connectome constrains the coordination of brain activity across distributed brain regions. In parallel, at the inter-individual scale, nascent social neuroscience provides a new dynamical vista of the coupling between two embodied cognitive agents. Using EEG hyperscanning to record simultaneously the brain activities of subjects during their ongoing interaction, we have previously demonstrated that behavioral synchrony correlates with the emergence of inter-brain synchronization. However, the functional meaning of such synchronization remains to be specified. Here, we use a biophysical model to quantify to what extent inter-brain synchronizations are related to the anatomical and functional similarity of the two brains in interaction. Pairs of interacting brains were numerically simulated and compared to real data. Results show a potential dynamical property of the human connectome to facilitate inter-individual synchronizations and thus may partly account for our propensity to generate dynamical couplings with others.

All together now: Analogies between chimera state collapses and epileptic seizures

NASA Astrophysics Data System (ADS)

Andrzejak, Ralph G.; Rummel, Christian; Mormann, Florian; Schindler, Kaspar

2016-03-01

Conceptually and structurally simple mathematical models of coupled oscillator networks can show a rich variety of complex dynamics, providing fundamental insights into many real-world phenomena. A recent and not yet fully understood example is the collapse of coexisting synchronous and asynchronous oscillations into a globally synchronous motion found in networks of identical oscillators. Here we show that this sudden collapse is promoted by a further decrease of synchronization, rather than by critically high synchronization. This strikingly counterintuitive mechanism can be found also in nature, as we demonstrate on epileptic seizures in humans. Analyzing spatiotemporal correlation profiles derived from intracranial electroencephalographic recordings (EEG) of seizures in epilepsy patients, we found a pronounced decrease of correlation at the seizure onsets. Applying our findings in a closed-loop control scheme to models of coupled oscillators in chimera states, we succeed in both provoking and preventing outbreaks of global synchronization. Our findings not only advance the understanding of networks of coupled dynamics but can open new ways to control them, thus offering a vast range of potential new applications.

Effects of phencyclidine (PCP) and MK 801 on the EEGq in the prefrontal cortex of conscious rats; antagonism by clozapine, and antagonists of AMPA-, α1- and 5-HT2A-receptors

PubMed Central

Sebban, Claude; Tesolin-Decros, Brigitte; Ciprian-Ollivier, Jorge; Perret, Laurent; Spedding, Michael

2002-01-01

The electroencephalographic (EEG) effects of the propsychotic agent phencyclidine (PCP), were studied in conscious rats using power spectra (0 – 30 Hz), from the prefrontal cortex or sensorimotor cortex. PCP (0.1 – 3 mg kg−1 s.c.) caused a marked dose-dependent increase in EEG power in the frontal cortex at 1 – 3 Hz with decreases in power at higher frequencies (9 – 30 Hz). At high doses (3 mg kg−1 s.c.) the entire spectrum shifted to more positive values, indicating an increase in cortical synchronization. MK 801 (0.05 – 0.1 mg kg−1 i.p.) caused similar effects but with lesser changes in power. In contrast, the non-competitive AMPA antagonists GYKI 52466 and GYKI 53655 increased EEG power over the whole power spectrum (1 – 10 mg kg−1 i.p.) The atypical antipsychotic clozapine (0.2 mg kg−1 s.c.) synchronized the EEG (peak 8 Hz). The 5-HT2A-antagonist, M100907, specifically increased EEG power at 2 – 3 Hz at low doses (10 and 50 μg kg÷1 s.c.), whereas at higher doses (0.1 mg kg−1 s.c.) the profile resembled that of clozapine. Clozapine (0.2 mg kg−1 s.c.), GYKI 53655 (5 mg kg−1 i.p.), prazosin (0.05 and 0.1 mg kg−1 i.p.), and M100907 (0.01 and 0.05 mg kg−1 s.c.) antagonized the decrease in power between 5 and 30 Hz caused by PCP (1 mg kg−1 s.c.), but not the increase in power at 1 – 3 Hz in prefrontal cortex. PMID:11786481

Cardiac phase-synchronized myocardial thallium-201 single-photon emission tomography using list mode data acquisition and iterative tomographic reconstruction.

PubMed

Vemmer, T; Steinbüchel, C; Bertram, J; Eschner, W; Kögler, A; Luig, H

1997-03-01

The purpose of this study was to determine whether data acquisition in the list mode and iterative tomographic reconstruction would render feasible cardiac phase-synchronized thallium-201 single-photon emission tomography (SPET) of the myocardium under routine conditions without modifications in tracer dose, acquisition time, or number of steps of the a gamma camera. Seventy non-selected patients underwent 201T1 SPET imaging according to a routine protocol (74 MBq/2 mCi 201T1, 180 degrees rotation of the gamma camera, 32 steps, 30 min). Gamma camera data, ECG, and a time signal were recorded in list mode. The cardiac cycle was divided into eight phases, the end-diastolic phase encompassing the QRS complex, and the end-systolic phase the T wave. Both phase- and non-phase-synchronized tomograms based on the same list mode data were reconstructed iteratively. Phase-synchronized and non-synchronized images were compared. Patients were divided into two groups depending on whether or not coronary artery disease had been definitely diagnosed prior to SPET imaging. The numbers of patients in both groups demonstrating defects visible on the phase-synchronized but not on the non-synchronized images were compared. It was found that both postexercise and redistribution phase tomograms were suited for interpretation. The changes from end-diastolic to end-systolic images allowed a comparative assessment of regional wall motility and tracer uptake. End-diastolic tomograms provided the best definition of defects. Additional defects not apparent on non-synchronized images were visible in 40 patients, six of whom did not show any defect on the non-synchronized images. Of 42 patients in whom coronary artery disease had been definitely diagnosed, 19 had additional defects not visible on the non-synchronized images, in comparison to 21 of 28 in whom coronary artery disease was suspected (P < 0.02; chi 2). It is concluded that cardiac phase-synchronized 201T1 SPET of the myocardium was made feasible by list mode data acquisition and iterative reconstruction. The additional findings on the phase-synchronized tomograms, not visible on the non-synchronized ones, represented genuine defects. Cardiac phase-synchronized 201T1 SPET is advantageous in allowing simultaneous assessment of regional wall motion and tracer uptake, and in visualizing smaller defects.

Effects of partial time delays on phase synchronization in Watts-Strogatz small-world neuronal networks

NASA Astrophysics Data System (ADS)

Sun, Xiaojuan; Perc, Matjaž; Kurths, Jürgen

2017-05-01

In this paper, we study effects of partial time delays on phase synchronization in Watts-Strogatz small-world neuronal networks. Our focus is on the impact of two parameters, namely the time delay τ and the probability of partial time delay pdelay, whereby the latter determines the probability with which a connection between two neurons is delayed. Our research reveals that partial time delays significantly affect phase synchronization in this system. In particular, partial time delays can either enhance or decrease phase synchronization and induce synchronization transitions with changes in the mean firing rate of neurons, as well as induce switching between synchronized neurons with period-1 firing to synchronized neurons with period-2 firing. Moreover, in comparison to a neuronal network where all connections are delayed, we show that small partial time delay probabilities have especially different influences on phase synchronization of neuronal networks.

Effects of partial time delays on phase synchronization in Watts-Strogatz small-world neuronal networks.

PubMed

Sun, Xiaojuan; Perc, Matjaž; Kurths, Jürgen

2017-05-01

In this paper, we study effects of partial time delays on phase synchronization in Watts-Strogatz small-world neuronal networks. Our focus is on the impact of two parameters, namely the time delay τ and the probability of partial time delay p delay , whereby the latter determines the probability with which a connection between two neurons is delayed. Our research reveals that partial time delays significantly affect phase synchronization in this system. In particular, partial time delays can either enhance or decrease phase synchronization and induce synchronization transitions with changes in the mean firing rate of neurons, as well as induce switching between synchronized neurons with period-1 firing to synchronized neurons with period-2 firing. Moreover, in comparison to a neuronal network where all connections are delayed, we show that small partial time delay probabilities have especially different influences on phase synchronization of neuronal networks.

Left hemibody myoclonus due to anomalous right vertebral artery.

PubMed

Coelho, Miguel; Marti, Maria J; Valls-Solé, Josep; Pujol, Teresa; Tolosa, Eduardo

2005-01-01

A 43-year-old man presented with sporadic, sudden, brief, and involuntary jerks of his left limbs and trunk muscles. The electromyographic recordings showed short-lasting highly synchronized bursts, compatible with myoclonus limited to the left hemibody. Blink reflex, masseter silent period, cortical and spinal magnetic stimulation, somatosensory cortical evoked potentials, and electroencephalogram (EEG) were normal; the EEG back-averaging showed no spikes preceding the myoclonus. Magnetic resonance imaging and magnetic resonance angiography showed the presence of an anomalous nonectasic right vertebral artery compressing the right side of ventral medulla oblongata. We hypothesize that the aberrant right vertebral artery induced abnormal activation of descending motor tracts responsible for the myoclonus. (c) 2004 Movement Disorder Society.

Mean-field modeling of the basal ganglia-thalamocortical system. II Dynamics of parkinsonian oscillations.

PubMed

van Albada, S J; Gray, R T; Drysdale, P M; Robinson, P A

2009-04-21

Neuronal correlates of Parkinson's disease (PD) include a shift to lower frequencies in the electroencephalogram (EEG) and enhanced synchronized oscillations at 3-7 and 7-30 Hz in the basal ganglia, thalamus, and cortex. This study describes the dynamics of a recent physiologically based mean-field model of the basal ganglia-thalamocortical system, and shows how it accounts for many key electrophysiological correlates of PD. Its detailed functional connectivity comprises partially segregated direct and indirect pathways through two populations of striatal neurons, a hyperdirect pathway involving a corticosubthalamic projection, thalamostriatal feedback, and local inhibition in striatum and external pallidum (GPe). In a companion paper, realistic steady-state firing rates were obtained for the healthy state, and after dopamine loss modeled by weaker direct and stronger indirect pathways, reduced intrapallidal inhibition, lower firing thresholds of the GPe and subthalamic nucleus (STN), a stronger projection from striatum to GPe, and weaker cortical interactions. Here it is shown that oscillations around 5 and 20 Hz can arise with a strong indirect pathway, which also causes increased synchronization throughout the basal ganglia. Furthermore, increased theta power with progressive nigrostriatal degeneration is correlated with reduced alpha power and peak frequency, in agreement with empirical results. Unlike the hyperdirect pathway, the indirect pathway sustains oscillations with phase relationships that coincide with those found experimentally. Alterations in the responses of basal ganglia to transient stimuli accord with experimental observations. Reduced cortical gains due to both nigrostriatal and mesocortical dopamine loss lead to slower changes in cortical activity and may be related to bradykinesia. Finally, increased EEG power found in some studies may be partly explained by a lower effective GPe firing threshold, reduced GPe-GPe inhibition, and/or weaker intracortical connections in parkinsonian patients. Strict separation of the direct and indirect pathways is not necessary to obtain these results.

Termination patterns of complex partial seizures: An intracranial EEG study.

PubMed

Afra, Pegah; Jouny, Christopher C; Bergey, Gregory K

2015-11-01

While seizure onset patterns have been the subject of many reports, there have been few studies of seizure termination. In this study we report the incidence of synchronous and asynchronous termination patterns of partial seizures recorded with intracranial arrays. Data were collected from patients with intractable complex partial seizures undergoing presurgical evaluations with intracranial electrodes. Patients with seizures originating from mesial temporal and neocortical regions were grouped into three groups based on patterns of seizure termination: synchronous only (So), asynchronous only (Ao), or mixed (S/A, with both synchronous and asynchronous termination patterns). 88% of the patients in the MT group had seizures with a synchronous pattern of termination exclusively (38%) or mixed (50%). 82% of the NC group had seizures with synchronous pattern of termination exclusively (52%) or mixed (30%). In the NC group, there was a significant difference of the range of seizure durations between So and Ao groups, with Ao exhibiting higher variability. Seizures with synchronous termination had low variability in both groups. Synchronous seizure termination is a common pattern for complex partials seizures of both mesial temporal or neocortical onset. This may reflect stereotyped network behavior or dynamics at the seizure focus. Copyright © 2015 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2012-10-01

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

A Synchronous Multi-Body Sensor Platform in a Wireless Body Sensor Network: Design and Implementation

PubMed Central

Gil, Yeongjoon; Wu, Wanqing; Lee, Jungtae

2012-01-01

Background Human life can be further improved if diseases and disorders can be predicted before they become dangerous, by correctly recognizing signals from the human body, so in order to make disease detection more precise, various body-signals need to be measured simultaneously in a synchronized manner. Object This research aims at developing an integrated system for measuring four signals (EEG, ECG, respiration, and PPG) and simultaneously producing synchronous signals on a Wireless Body Sensor Network. Design We designed and implemented a platform for multiple bio-signals using Bluetooth communication. Results First, we developed a prototype board and verified the signals from the sensor platform using frequency responses and quantities. Next, we designed and implemented a lightweight, ultra-compact, low cost, low power-consumption Printed Circuit Board. Conclusion A synchronous multi-body sensor platform is expected to be very useful in telemedicine and emergency rescue scenarios. Furthermore, this system is expected to be able to analyze the mutual effects among body signals. PMID:23112605

Detection of Nonverbal Synchronization through Phase Difference in Human Communication

PubMed Central

Kwon, Jinhwan; Ogawa, Ken-ichiro; Ono, Eisuke; Miyake, Yoshihiro

2015-01-01

Nonverbal communication is an important factor in human communication, and body movement synchronization in particular is an important part of nonverbal communication. Some researchers have analyzed body movement synchronization by focusing on changes in the amplitude of body movements. However, the definition of “body movement synchronization” is still unclear. From a theoretical viewpoint, phase difference is the most important factor in synchronization analysis. Therefore, there is a need to measure the synchronization of body movements using phase difference. The purpose of this study was to provide a quantitative definition of the phase difference distribution for detecting body movement synchronization in human communication. The phase difference distribution was characterized using four statistical measurements: density, mean phase difference, standard deviation (SD) and kurtosis. To confirm the effectiveness of our definition, we applied it to human communication in which the roles of speaker and listener were defined. Specifically, we examined the difference in the phase difference distribution between two different communication situations: face-to-face communication with visual interaction and remote communication with unidirectional visual perception. Participant pairs performed a task supposing lecture in the face-to-face communication condition and in the remote communication condition via television. Throughout the lecture task, we extracted a set of phase differences from the time-series data of the acceleration norm of head nodding motions between two participants. Statistical analyses of the phase difference distribution revealed the characteristics of head nodding synchronization. Although the mean phase differences in synchronized head nods did not differ significantly between the conditions, there were significant differences in the densities, the SDs and the kurtoses of the phase difference distributions of synchronized head nods. These results show the difference in nonverbal synchronization between different communication types. Our study indicates that the phase difference distribution is useful in detecting nonverbal synchronization in various human communication situations. PMID:26208100

On the interpretation of synchronization in EEG hyperscanning studies: a cautionary note.

PubMed

Burgess, Adrian P

2013-01-01

EEG Hyperscanning is a method for studying two or more individuals simultaneously with the objective of elucidating how co-variations in their neural activity (i.e., hyperconnectivity) are influenced by their behavioral and social interactions. The aim of this study was to compare the performance of different hyper-connectivity measures using (i) simulated data, where the degree of coupling could be systematically manipulated, and (ii) individually recorded human EEG combined into pseudo-pairs of participants where no hyper-connections could exist. With simulated data we found that each of the most widely used measures of hyperconnectivity were biased and detected hyper-connections where none existed. With pseudo-pairs of human data we found spurious hyper-connections that arose because there were genuine similarities between the EEG recorded from different people independently but under the same experimental conditions. Specifically, there were systematic differences between experimental conditions in terms of the rhythmicity of the EEG that were common across participants. As any imbalance between experimental conditions in terms of stimulus presentation or movement may affect the rhythmicity of the EEG, this problem could apply in many hyperscanning contexts. Furthermore, as these spurious hyper-connections reflected real similarities between the EEGs, they were not Type-1 errors that could be overcome by some appropriate statistical control. However, some measures that have not previously been used in hyperconnectivity studies, notably the circular correlation co-efficient (CCorr), were less susceptible to detecting spurious hyper-connections of this type. The reason for this advantage in performance is discussed and the use of the CCorr as an alternative measure of hyperconnectivity is advocated.

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

PubMed

Zhavoronkova, L A

2007-01-01

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

High-frequency neural activity and human cognition: past, present and possible future of intracranial EEG research

PubMed Central

Lachaux, Jean-Philippe; Axmacher, Nikolai; Mormann, Florian; Halgren, Eric; Crone, Nathan E.

2013-01-01

Human intracranial EEG (iEEG) recordings are primarily performed in epileptic patients for presurgical mapping. When patients perform cognitive tasks, iEEG signals reveal high-frequency neural activities (HFA, between around 40 Hz and 150 Hz) with exquisite anatomical, functional and temporal specificity. Such HFA were originally interpreted in the context of perceptual or motor binding, in line with animal studies on gamma-band (‘40Hz’) neural synchronization. Today, our understanding of HFA has evolved into a more general index of cortical processing: task-induced HFA reveals, with excellent spatial and time resolution, the participation of local neural ensembles in the task-at-hand, and perhaps the neural communication mechanisms allowing them to do so. This review promotes the claim that studying HFA with iEEG provides insights into the neural bases of cognition that cannot be derived as easily from other approaches, such as fMRI. We provide a series of examples supporting that claim, drawn from studies on memory, language and default-mode networks, and successful attempts of real-time functional mapping. These examples are followed by several guidelines for HFA research, intended for new groups interested by this approach. Overall, iEEG research on HFA should play an increasing role in cognitive neuroscience in humans, because it can be explicitly linked to basic research in animals. We conclude by discussing the future evolution of this field, which might expand that role even further, for instance through the use of multi-scale electrodes and the fusion of iEEG with MEG and fMRI. PMID:22750156

The effect of high mesencephalic transection (cerveau isolé) and pentobarbital on basal forebrain mechanisms of EEG synchronization.

PubMed

Obál, F; Benedek, G; Szikszay, M; Obál, F

1979-01-01

A study was made of the effects of high mesencephalic transection (cerveau isolé) and low doses of pentobarbital on the cortical synchronizations elicited in acute immobilized cats by (a) low frequency stimulation of the lateral hypothalamus (HL) and nucleus ventralis anterior thalami (VA) and (b) by low and high frequency stimulation of the laterobasal preoptic region (RPO) and olfactory tubercle (TbOf). The results obtained were as follows: (1) The synchronizations induced by basal forebrain stimulations were found to survive in acute cerveau isolé cats, moreover, even a facilitation of the synchronizing effect were observed. (2) A gradual facilitation was observed upon TbOf and RPO stimulation, while in the case of VA and HL stimulations, the facilitation appeared immediately after the transection. (3) Low doses of pentobarbital depressed the cortical effects of TbOf stimulation, while an increase of the synchronizing effect of low frequency VA and HL stimulation was found. The observations suggested that (i) the synchronizing mechanism in the ventral part of the basal forebrain (RPO and TbOf) differs from that of the thalamus and HL; (ii) the basal forebrain synchronizing mechanism is effective without the contribution of the brain stem; (iii) the mechanism responsible for the synchronizing effect of low frequency HL stimulation is similar as that described for the thalamus.

Dynamical inference: where phase synchronization and generalized synchronization meet.

PubMed

Stankovski, Tomislav; McClintock, Peter V E; Stefanovska, Aneta

2014-06-01

Synchronization is a widespread phenomenon that occurs among interacting oscillatory systems. It facilitates their temporal coordination and can lead to the emergence of spontaneous order. The detection of synchronization from the time series of such systems is of great importance for the understanding and prediction of their dynamics, and several methods for doing so have been introduced. However, the common case where the interacting systems have time-variable characteristic frequencies and coupling parameters, and may also be subject to continuous external perturbation and noise, still presents a major challenge. Here we apply recent developments in dynamical Bayesian inference to tackle these problems. In particular, we discuss how to detect phase slips and the existence of deterministic coupling from measured data, and we unify the concepts of phase synchronization and general synchronization. Starting from phase or state observables, we present methods for the detection of both phase and generalized synchronization. The consistency and equivalence of phase and generalized synchronization are further demonstrated, by the analysis of time series from analog electronic simulations of coupled nonautonomous van der Pol oscillators. We demonstrate that the detection methods work equally well on numerically simulated chaotic systems. In all the cases considered, we show that dynamical Bayesian inference can clearly identify noise-induced phase slips and distinguish coherence from intrinsic coupling-induced synchronization.

[Electroencephalographic characteristic of cognitive-specific alerting attention in verbal learning--III: Localized characteristics of EEG spatial synchronization].

PubMed

Dan'ko, S G; Kachalova, L M; Solov'eva, M L

2010-01-01

Electroencephalograms (EEG) were recorder in 19 standard derivations in 88 healthy subjects, while they were in the states: rest with eyes open; memorization (learning) of verbal bilingual semantic pairs (Latin and Russian languages); the retrieval of the rote information from memory (control). We compared estimates of EEG coherence in these states for the frequency bands theta (4-7 Hz), alpha-1 (7-10 Hz), alpha-2 (10-13 Hz), beta-1 (13-18 Hz), beta-2 (18-30 Hz), gamma (30-40 Hz). When compared with the rest most strongly expressed: for memorization a decrease of coherence in the pairs of derivations from frontal and central areas of the cortex in the EEG frequency bands; for retrieval an increase of coherence in interhemispheric derivation pairs of pariental-occipital region in majority of the frequency bands. For the retrieval also increases of coherence in the beta2 and gamma bands, along with coherence decreases at low frequencies take place in pairs formed by derivations from the parieto-occipital region with derivations from the frontal and the central ones. Dynamics of EEG coherence in comparisons of memorization and retrieval from the rest and each are expressed significantly more in the interhemispheric and crosshemispheric pairs of derivations than in the intrahemispheric pairs. Revealed topographic specificity of the dynamics of EEG coherence by changing the states is considered in terms of ideas about cognitive-specific forms of sustained goal-directed mental attention.

Electroencephalogram–Electromyography Coupling Analysis in Stroke Based on Symbolic Transfer Entropy

PubMed Central

Gao, Yunyuan; Ren, Leilei; Li, Rihui; Zhang, Yingchun

2018-01-01

The coupling strength between electroencephalogram (EEG) and electromyography (EMG) signals during motion control reflects the interaction between the cerebral motor cortex and muscles. Therefore, neuromuscular coupling characterization is instructive in assessing motor function. In this study, to overcome the limitation of losing the characteristics of signals in conventional time series symbolization methods, a variable scale symbolic transfer entropy (VS-STE) analysis approach was proposed for corticomuscular coupling evaluation. Post-stroke patients (n = 5) and healthy volunteers (n = 7) were recruited and participated in various tasks (left and right hand gripping, elbow bending). The proposed VS-STE was employed to evaluate the corticomuscular coupling strength between the EEG signal measured from the motor cortex and EMG signal measured from the upper limb in both the time-domain and frequency-domain. Results showed a greater strength of the bi-directional (EEG-to-EMG and EMG-to-EEG) VS-STE in post-stroke patients compared to healthy controls. In addition, the strongest EEG–EMG coupling strength was observed in the beta frequency band (15–35 Hz) during the upper limb movement. The predefined coupling strength of EMG-to-EEG in the affected side of the patient was larger than that of EEG-to-EMG. In conclusion, the results suggested that the corticomuscular coupling is bi-directional, and the proposed VS-STE can be used to quantitatively characterize the non-linear synchronization characteristics and information interaction between the primary motor cortex and muscles. PMID:29354091

Assessing the Minimum Number of Synchronization Triggers Necessary for Temporal Variance Compensation in Commercial Electroencephalography (EEG) Systems

DTIC Science & Technology

2012-09-01

by the ARL Translational Neuroscience Branch. It covers the Emotiv EPOC,6 Advanced Brain Monitoring (ABM) B-Alert X10,7 Quasar 8 DSI helmet-based...Systems; ARL-TR-5945; U.S. Army Research Laboratory: Aberdeen Proving Ground, MD, 2012 4 Ibid. 5 Ibid. 6 EPOC is a trademark of Emotiv . 7 B

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Single-trial Phase Entrainment of Theta Oscillations in Sensory Regions Predicts Human Associative Memory Performance.

PubMed

Wang, Danying; Clouter, Andrew; Chen, Qiaoyu; Shapiro, Kimron L; Hanslmayr, Simon

2018-06-13

Episodic memories are rich in sensory information and often contain integrated information from different sensory modalities. For instance, we can store memories of a recent concert with visual and auditory impressions being integrated in one episode. Theta oscillations have recently been implicated in playing a causal role synchronizing and effectively binding the different modalities together in memory. However, an open question is whether momentary fluctuations in theta synchronization predict the likelihood of associative memory formation for multisensory events. To address this question we entrained the visual and auditory cortex at theta frequency (4 Hz) and in a synchronous or asynchronous manner by modulating the luminance and volume of movies and sounds at 4 Hz, with a phase offset at 0° or 180°. EEG activity from human subjects (both sexes) was recorded while they memorized the association between a movie and a sound. Associative memory performance was significantly enhanced in the 0° compared to the 180° condition. Source-level analysis demonstrated that the physical stimuli effectively entrained their respective cortical areas with a corresponding phase offset. The findings suggested a successful replication of a previous study (Clouter et al., 2017). Importantly, the strength of entrainment during encoding correlated with the efficacy of associative memory such that small phase differences between visual and auditory cortex predicted a high likelihood of correct retrieval in a later recall test. These findings suggest that theta oscillations serve a specific function in the episodic memory system: Binding the contents of different modalities into coherent memory episodes. SIGNIFICANCE STATEMENT How multi-sensory experiences are bound to form a coherent episodic memory representation is one of the fundamental questions in human episodic memory research. Evidence from animal literature suggests that the relative timing between an input and theta oscillations in the hippocampus is crucial for memory formation. We precisely controlled the timing between visual and auditory stimuli and the neural oscillations at 4 Hz using a multisensory entrainment paradigm. Human associative memory formation depends on coincident timing between sensory streams processed by the corresponding brain regions. We provide evidence for a significant role of relative timing of neural theta activity in human episodic memory on a single trial level, which reveals a crucial mechanism underlying human episodic memory. Copyright © 2018 the authors.

Enhanced Burst-Suppression and Disruption of Local Field Potential Synchrony in a Mouse Model of Focal Cortical Dysplasia Exhibiting Spike-Wave Seizures.

PubMed

Williams, Anthony J; Zhou, Chen; Sun, Qian-Quan

2016-01-01

Focal cortical dysplasias (FCDs) are a common cause of brain seizures and are often associated with intractable epilepsy. Here we evaluated aberrant brain neurophysiology in an in vivo mouse model of FCD induced by neonatal freeze lesions (FLs) to the right cortical hemisphere (near S1). Linear multi-electrode arrays were used to record extracellular potentials from cortical and subcortical brain regions near the FL in anesthetized mice (5-13 months old) followed by 24 h cortical electroencephalogram (EEG) recordings. Results indicated that FL animals exhibit a high prevalence of spontaneous spike-wave discharges (SWDs), predominately during sleep (EEG), and an increase in the incidence of hyper-excitable burst/suppression activity under general anesthesia (extracellular recordings, 0.5%-3.0% isoflurane). Brief periods of burst activity in the local field potential (LFP) typically presented as an arrhythmic pattern of increased theta-alpha spectral peaks (4-12 Hz) on a background of low-amplitude delta activity (1-4 Hz), were associated with an increase in spontaneous spiking of cortical neurons, and were highly synchronized in control animals across recording sites in both cortical and subcortical layers (average cross-correlation values ranging from +0.73 to +1.0) with minimal phase shift between electrodes. However, in FL animals, cortical vs. subcortical burst activity was strongly out of phase with significantly lower cross-correlation values compared to controls (average values of -0.1 to +0.5, P < 0.05 between groups). In particular, a marked reduction in the level of synchronous burst activity was observed, the closer the recording electrodes were to the malformation (Pearson's Correlation = 0.525, P < 0.05). In a subset of FL animals (3/9), burst activity also included a spike or spike-wave pattern similar to the SWDs observed in unanesthetized animals. In summary, neonatal FLs increased the hyperexcitable pattern of burst activity induced by anesthesia and disrupted field potential synchrony between cortical and subcortical brain regions near the site of the cortical malformation. Monitoring the altered electrophysiology of burst activity under general anesthesia with multi-dimensional micro-electrode arrays may serve to define distinct neurophysiological biomarkers of epileptogenesis in human brain and improve techniques for surgical resection of epileptogenic malformed brain tissue.

Oscillatory bands, neuronal synchrony and hippocampal function: implications of the effects of prenatal choline supplementation for sleep-dependent memory consolidation.

PubMed

Cheng, Ruey-Kuang; Williams, Christina L; Meck, Warren H

2008-10-27

Choline supplementation of the maternal diet has long-term facilitative effects on spatial and temporal memory processes in the offspring. To further delineate the impact of early nutritional status on brain and behavior, we examined effects of prenatal-choline availability on hippocampal oscillatory frequency bands in 12 month-old male and female rats. Adult offspring of time-pregnant dams that were given a deficient level of choline (DEF=0.0 g/kg), sufficient choline (CON=1.1 g/kg) or supplemental choline (SUP=3.5 g/kg) in their chow during embryonic days (ED) 12-17 were implanted with an electroencephalograph (EEG) electrode in the hippocampal dentate gyrus in combination with an electromyograph (EMG) electrode patch implanted in the nuchal muscle. Five consecutive 8-h recording sessions revealed differential patterns of EEG activity as a function of awake, slow-wave sleep (SWS) and rapid-eye movement (REM) sleep states and prenatal choline status. The main finding was that SUP rats displayed increased power levels of gamma (30-100 Hz) band oscillations during all phases of the sleep/wake cycle. These findings are discussed within the context of a general review of neuronal oscillations (e.g., delta, theta, and gamma bands) and synchronization across multiple brain regions in relation to sleep-dependent memory consolidation in the hippocampus.

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.

Complexity of Multi-Dimensional Spontaneous EEG Decreases during Propofol Induced General Anaesthesia

PubMed Central

Schartner, Michael; Seth, Anil; Noirhomme, Quentin; Boly, Melanie; Bruno, Marie-Aurelie; Laureys, Steven; Barrett, Adam

2015-01-01

Emerging neural theories of consciousness suggest a correlation between a specific type of neural dynamical complexity and the level of consciousness: When awake and aware, causal interactions between brain regions are both integrated (all regions are to a certain extent connected) and differentiated (there is inhomogeneity and variety in the interactions). In support of this, recent work by Casali et al (2013) has shown that Lempel-Ziv complexity correlates strongly with conscious level, when computed on the EEG response to transcranial magnetic stimulation. Here we investigated complexity of spontaneous high-density EEG data during propofol-induced general anaesthesia. We consider three distinct measures: (i) Lempel-Ziv complexity, which is derived from how compressible the data are; (ii) amplitude coalition entropy, which measures the variability in the constitution of the set of active channels; and (iii) the novel synchrony coalition entropy (SCE), which measures the variability in the constitution of the set of synchronous channels. After some simulations on Kuramoto oscillator models which demonstrate that these measures capture distinct ‘flavours’ of complexity, we show that there is a robustly measurable decrease in the complexity of spontaneous EEG during general anaesthesia. PMID:26252378

Functional Connectivity and Quantitative EEG in Women with Alcohol Use Disorders: A Resting-State Study.

PubMed

Herrera-Díaz, Adianes; Mendoza-Quiñones, Raúl; Melie-Garcia, Lester; Martínez-Montes, Eduardo; Sanabria-Diaz, Gretel; Romero-Quintana, Yuniel; Salazar-Guerra, Iraklys; Carballoso-Acosta, Mario; Caballero-Moreno, Antonio

2016-05-01

This study was aimed at exploring the electroencephalographic features associated with alcohol use disorders (AUD) during a resting-state condition, by using quantitative EEG and Functional Connectivity analyses. In addition, we explored whether EEG functional connectivity is associated with trait impulsivity. Absolute and relative powers and Synchronization Likelihood (SL) as a measure of functional connectivity were analyzed in 15 AUD women and fifteen controls matched in age, gender and education. Correlation analysis between self-report impulsivity as measured by the Barratt impulsiveness Scale (BIS-11) and SL values of AUD patients were performed. Our results showed increased absolute and relative beta power in AUD patients compared to matched controls, and reduced functional connectivity in AUD patients predominantly in the beta and alpha bands. Impaired connectivity was distributed at fronto-central and occipito-parietal regions in the alpha band, and over the entire scalp in the beta band. We also found that impaired functional connectivity particularly in alpha band at fronto-central areas was negative correlated with non-planning dimension of impulsivity. These findings suggest that functional brain abnormalities are present in AUD patients and a disruption of resting-state EEG functional connectivity is associated with psychopathological traits of addictive behavior.

Prediction of successful memory encoding based on single-trial rhinal and hippocampal phase information.

PubMed

Höhne, Marlene; Jahanbekam, Amirhossein; Bauckhage, Christian; Axmacher, Nikolai; Fell, Juergen

2016-10-01

Mediotemporal EEG characteristics are closely related to long-term memory formation. It has been reported that rhinal and hippocampal EEG measures reflecting the stability of phases across trials are better suited to distinguish subsequently remembered from forgotten trials than event-related potentials or amplitude-based measures. Theoretical models suggest that the phase of EEG oscillations reflects neural excitability and influences cellular plasticity. However, while previous studies have shown that the stability of phase values across trials is indeed a relevant predictor of subsequent memory performance, the effect of absolute single-trial phase values has been little explored. Here, we reanalyzed intracranial EEG recordings from the mediotemporal lobe of 27 epilepsy patients performing a continuous word recognition paradigm. Two-class classification using a support vector machine was performed to predict subsequently remembered vs. forgotten trials based on individually selected frequencies and time points. We demonstrate that it is possible to successfully predict single-trial memory formation in the majority of patients (23 out of 27) based on only three single-trial phase values given by a rhinal phase, a hippocampal phase, and a rhinal-hippocampal phase difference. Overall classification accuracy across all subjects was 69.2% choosing frequencies from the range between 0.5 and 50Hz and time points from the interval between -0.5s and 2s. For 19 patients, above chance prediction of subsequent memory was possible even when choosing only time points from the prestimulus interval (overall accuracy: 65.2%). Furthermore, prediction accuracies based on single-trial phase surpassed those based on single-trial power. Our results confirm the functional relevance of mediotemporal EEG phase for long-term memory operations and suggest that phase information may be utilized for memory enhancement applications based on deep brain stimulation. Copyright © 2016 Elsevier Inc. All rights reserved.

Parietal EEG alpha suppression time of memory retrieval reflects memory load while the alpha power of memory maintenance is a composite of the visual process according to simultaneous and successive Sternberg memory tasks.

PubMed

Okuhata, Shiho; Kusanagi, Takuya; Kobayashi, Tetsuo

2013-10-25

The present study investigated EEG alpha activity during visual Sternberg memory tasks using two different stimulus presentation modes to elucidate how the presentation mode affected parietal alpha activity. EEGs were recorded from 10 healthy adults during the Sternberg tasks in which memory items were presented simultaneously and successively. EEG power and suppression time (ST) in the alpha band (8-13Hz) were computed for the memory maintenance and retrieval phases. The alpha activity differed according to the presentation mode during the maintenance phase but not during the retrieval phase. Results indicated that parietal alpha power recorded during the maintenance phase did not reflect the memory load alone. In contrast, ST during the retrieval phase increased with the memory load for both presentation modes, indicating a serial memory scanning process, regardless of the presentation mode. These results indicate that there was a dynamic transition in the memory process from the maintenance phase, which was sensitive to external factors, toward the retrieval phase, during which the process converged on the sequential scanning process, the Sternberg task essentially required. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Missile Defense: European Phased Adaptive Approach Acquisitions Face Synchronization, Transparency, and Accountability Challenges

DTIC Science & Technology

2010-12-21

House of Representatives Subject: Missile Defense: European Phased Adaptive Approach Acquisitions Face Synchronization , Transparency, and...TITLE AND SUBTITLE Missile Defense: European Phased Adaptive Approach Acquisitions Face Synchronization , Transparency, and Accountability...However, we found that DOD has not fully implemented a management process that synchronizes EPAA acquisition activities and ensures transparency and

Drowsiness/alertness algorithm development and validation using synchronized EEG and cognitive performance to individualize a generalized model

PubMed Central

Johnson, Robin R.; Popovic, Djordje P.; Olmstead, Richard E.; Stikic, Maja; Levendowski, Daniel J.; Berka, Chris

2011-01-01

A great deal of research over the last century has focused on drowsiness/alertness detection, as fatigue-related physical and cognitive impairments pose a serious risk to public health and safety. Available drowsiness/alertness detection solutions are unsatisfactory for a number of reasons: 1) lack of generalizability, 2) failure to address individual variability in generalized models, and/or 3) they lack a portable, un-tethered application. The current study aimed to address these issues, and determine if an individualized electroencephalography (EEG) based algorithm could be defined to track performance decrements associated with sleep loss, as this is the first step in developing a field deployable drowsiness/alertness detection system. The results indicated that an EEG-based algorithm, individualized using a series of brief "identification" tasks, was able to effectively track performance decrements associated with sleep deprivation. Future development will address the need for the algorithm to predict performance decrements due to sleep loss, and provide field applicability. PMID:21419826

Drowsiness/alertness algorithm development and validation using synchronized EEG and cognitive performance to individualize a generalized model.

PubMed

Johnson, Robin R; Popovic, Djordje P; Olmstead, Richard E; Stikic, Maja; Levendowski, Daniel J; Berka, Chris

2011-05-01

A great deal of research over the last century has focused on drowsiness/alertness detection, as fatigue-related physical and cognitive impairments pose a serious risk to public health and safety. Available drowsiness/alertness detection solutions are unsatisfactory for a number of reasons: (1) lack of generalizability, (2) failure to address individual variability in generalized models, and/or (3) lack of a portable, un-tethered application. The current study aimed to address these issues, and determine if an individualized electroencephalography (EEG) based algorithm could be defined to track performance decrements associated with sleep loss, as this is the first step in developing a field deployable drowsiness/alertness detection system. The results indicated that an EEG-based algorithm, individualized using a series of brief "identification" tasks, was able to effectively track performance decrements associated with sleep deprivation. Future development will address the need for the algorithm to predict performance decrements due to sleep loss, and provide field applicability. Copyright © 2011 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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.

Mapping human preictal and ictal haemodynamic networks using simultaneous intracranial EEG-fMRI

PubMed Central

Chaudhary, Umair J.; Centeno, Maria; Thornton, Rachel C.; Rodionov, Roman; Vulliemoz, Serge; McEvoy, Andrew W.; Diehl, Beate; Walker, Matthew C.; Duncan, John S.; Carmichael, David W.; Lemieux, Louis

2016-01-01

Accurately characterising the brain networks involved in seizure activity may have important implications for our understanding of epilepsy. Intracranial EEG-fMRI can be used to capture focal epileptic events in humans with exquisite electrophysiological sensitivity and allows for identification of brain structures involved in this phenomenon over the entire brain. We investigated ictal BOLD networks using the simultaneous intracranial EEG-fMRI (icEEG-fMRI) in a 30 year-old male undergoing invasive presurgical evaluation with bilateral depth electrode implantations in amygdalae and hippocampi for refractory temporal lobe epilepsy. One spontaneous focal electrographic seizure was recorded. The aims of the data analysis were firstly to map BOLD changes related to the ictal activity identified on icEEG and secondly to compare different fMRI modelling approaches. Visual inspection of the icEEG showed an onset dominated by beta activity involving the right amygdala and hippocampus lasting 6.4 s (ictal onset phase), followed by gamma activity bilaterally lasting 14.8 s (late ictal phase). The fMRI data was analysed using SPM8 using two modelling approaches: firstly, purely based on the visually identified phases of the seizure and secondly, based on EEG spectral dynamics quantification. For the visual approach the two ictal phases were modelled as ‘ON’ blocks convolved with the haemodynamic response function; in addition the BOLD changes during the 30 s preceding the onset were modelled using a flexible basis set. For the quantitative fMRI modelling approach two models were evaluated: one consisting of the variations in beta and gamma bands power, thereby adding a quantitative element to the visually-derived models, and another based on principal components analysis of the entire spectrogram in attempt to reduce the bias associated with the visual appreciation of the icEEG. BOLD changes related to the visually defined ictal onset phase were revealed in the medial and lateral right temporal lobe. For the late ictal phase, the BOLD changes were remote from the SOZ and in deep brain areas (precuneus, posterior cingulate and others). The two quantitative models revealed BOLD changes involving the right hippocampus, amygdala and fusiform gyrus and in remote deep brain structures and the default mode network-related areas. In conclusion, icEEG-fMRI allowed us to reveal BOLD changes within and beyond the SOZ linked to very localised ictal fluctuations in beta and gamma activity measured in the amygdala and hippocampus. Furthermore, the BOLD changes within the SOZ structures were better captured by the quantitative models, highlighting the interest in considering seizure-related EEG fluctuations across the entire spectrum. PMID:27114897

Mapping human preictal and ictal haemodynamic networks using simultaneous intracranial EEG-fMRI.

PubMed

Chaudhary, Umair J; Centeno, Maria; Thornton, Rachel C; Rodionov, Roman; Vulliemoz, Serge; McEvoy, Andrew W; Diehl, Beate; Walker, Matthew C; Duncan, John S; Carmichael, David W; Lemieux, Louis

2016-01-01

Accurately characterising the brain networks involved in seizure activity may have important implications for our understanding of epilepsy. Intracranial EEG-fMRI can be used to capture focal epileptic events in humans with exquisite electrophysiological sensitivity and allows for identification of brain structures involved in this phenomenon over the entire brain. We investigated ictal BOLD networks using the simultaneous intracranial EEG-fMRI (icEEG-fMRI) in a 30 year-old male undergoing invasive presurgical evaluation with bilateral depth electrode implantations in amygdalae and hippocampi for refractory temporal lobe epilepsy. One spontaneous focal electrographic seizure was recorded. The aims of the data analysis were firstly to map BOLD changes related to the ictal activity identified on icEEG and secondly to compare different fMRI modelling approaches. Visual inspection of the icEEG showed an onset dominated by beta activity involving the right amygdala and hippocampus lasting 6.4 s (ictal onset phase), followed by gamma activity bilaterally lasting 14.8 s (late ictal phase). The fMRI data was analysed using SPM8 using two modelling approaches: firstly, purely based on the visually identified phases of the seizure and secondly, based on EEG spectral dynamics quantification. For the visual approach the two ictal phases were modelled as 'ON' blocks convolved with the haemodynamic response function; in addition the BOLD changes during the 30 s preceding the onset were modelled using a flexible basis set. For the quantitative fMRI modelling approach two models were evaluated: one consisting of the variations in beta and gamma bands power, thereby adding a quantitative element to the visually-derived models, and another based on principal components analysis of the entire spectrogram in attempt to reduce the bias associated with the visual appreciation of the icEEG. BOLD changes related to the visually defined ictal onset phase were revealed in the medial and lateral right temporal lobe. For the late ictal phase, the BOLD changes were remote from the SOZ and in deep brain areas (precuneus, posterior cingulate and others). The two quantitative models revealed BOLD changes involving the right hippocampus, amygdala and fusiform gyrus and in remote deep brain structures and the default mode network-related areas. In conclusion, icEEG-fMRI allowed us to reveal BOLD changes within and beyond the SOZ linked to very localised ictal fluctuations in beta and gamma activity measured in the amygdala and hippocampus. Furthermore, the BOLD changes within the SOZ structures were better captured by the quantitative models, highlighting the interest in considering seizure-related EEG fluctuations across the entire spectrum.

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

PubMed

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

2016-11-16

Sequencing and timing of body movements are essential to perform motoric tasks. In this study, we investigate the temporal relation between cortical oscillations and human motor behavior (i.e., rhythmic finger movements). High-density EEG recordings were used for source imaging based on individual anatomy. We separated sustained and movement phase-related EEG source amplitudes based on the actual finger movements recorded by a data glove. Sustained amplitude modulations in the contralateral hand area show decrease for α (10-12 Hz) and β (18-24 Hz), but increase for high γ (60-80 Hz) frequencies during the entire movement period. Additionally, we found movement phase-related amplitudes, which resembled the flexion and extension sequence of the fingers. Especially for faster movement cadences, movement phase-related amplitudes included high β (24-30 Hz) frequencies in prefrontal areas. Interestingly, the spectral profiles and source patterns of movement phase-related amplitudes differed from sustained activities, suggesting that they represent different frequency-specific large-scale networks. First, networks were signified by the sustained element, which statically modulate their synchrony levels during continuous movements. These networks may upregulate neuronal excitability in brain regions specific to the limb, in this study the right hand area. Second, movement phase-related networks, which modulate their synchrony in relation to the movement sequence. We suggest that these frequency-specific networks are associated with distinct functions, including top-down control, sensorimotor prediction, and integration. The separation of different large-scale networks, we applied in this work, improves the interpretation of EEG sources in relation to human motor behavior. EEG recordings provide high temporal resolution suitable to relate cortical oscillations to actual movements. Investigating EEG sources during rhythmic finger movements, we distinguish sustained from movement phase-related amplitude modulations. We separate these two EEG source elements motivated by our previous findings in gait. Here, we found two types of large-scale networks, representing the right fingers in distinction from the time sequence of the movements. These findings suggest that EEG source amplitudes reconstructed in a cortical patch are the superposition of these simultaneously present network activities. Separating these frequency-specific networks is relevant for studying function and possible dysfunction of the cortical sensorimotor system in humans as well as to provide more advanced features for brain-computer interfaces. Copyright © 2016 the authors 0270-6474/16/3611671-11$15.00/0.

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

PubMed

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

2014-08-01

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

[Clinical and neurophysiological manifestations of cerebral asymmetry in cervical dystonia].

PubMed

Naryshkin, A G; Skoromets, T A; Gorelik, A L; Egorov, A Iu

2009-01-01

Based on the analysis of clinical and neurophysiological data with the use of up-to-date methods of EEG processing, the authors discuss a role of cerebral asymmetry (CA) in the pathogenesis of cervical dystonia (CD). Sixty-seven patients (31 male and 36 female) with CD have been studied. The pathological turn of the head to the right side (RT) was observed in 34 patients, to the left side (LT) - in 33 patients. The uni- or bilateral generalization of dystonic symptoms (Meig's syndrome, laterocollis) was found only in one-third of RT patients. The visual analysis of EEG of RT patients revealed the high level of EEG synchronization with signs of cortical irritation, with the prevalence in the left hemisphere, and the presence of focal epileptiform appearances in the temporal leads of the left or both hemispheres with the left-side prevalence. In LT patients, the EEG presentation was similar to normal but more often represented the variants of EEG-pattern. In these cases, the apparent manifestations of CA were not found. The coherent analysis revealed the formation of the network of coherent links, with bilateral spread, in RT patients. This may suggest the functional inequivalence of the peripersonal space of right and left hand and the dominate significance of striopallidar and thalamic structures of the left hemisphere for the total brain activity.