Global field synchronization reveals rapid eye movement sleep as most synchronized brain state in the human EEG

Study of the Synchronization and Transmission of Intracellular Signaling Oscillations in Cells Using Bispectral Analysis

The oscillation synchronization analysis in biological systems will expand our knowledge about the response of living systems to changes in environmental conditions. This knowledge can be used in medicine (diagnosis, therapy, monitoring) and agriculture (increasing productivity, resistance to adverse effects). Currently, the search is underway for an informative, accurate and sensitive method for analyzing the synchronization of oscillatory processes in cell biology. It is especially pronounced in analyzing the concentration oscillations of intracellular signaling molecules in electrically nonexcitable cells. The bispectral analysis method could be applied to assess the characteristics of synchronized oscillations of intracellular mediators. We chose endothelial cells from mouse microvessels as model cells. Concentrations of well-studied calcium and nitric oxide (NO) were selected for study in control conditions and well-described stress: heating to 40 °C and hyperglycemia. The bispectral analysis allows us to accurately evaluate the proportion of synchronized cells, their synchronization degree, and the amplitude and frequency of synchronized calcium and NO oscillations. Heating to 40 °C increased cell synchronization for calcium but decreased for NO oscillations. Hyperglycemia abolished this effect. Heating to 40 °C changed the frequencies and increased the amplitudes of synchronized oscillations of calcium concentration and the NO synthesis rate. The first part of this paper describes the principles of the bispectral analysis method and equations and modifications of the method we propose. In the second part of this paper, specific examples of the application of bispectral analysis to assess the synchronization of living cells in vitro are presented. The discussion compares the capabilities of bispectral analysis with other analytical methods in this field.

Global Functional Connectivity is Associated with Mind Wandering Domain of Comfort

The resting-state paradigm is frequently applied to study spontaneous activity of the brain in normal and clinical conditions. To assess the relationship between brain activity and subjective experiences, various questionnaires are used. Previous studies using Amsterdam Resting State Questionnaire were focusing on fMRI functional connectivity or EEG microstates and spectral aspect. Here, we utilized Global Field Synchronization as the parameter to estimate global functional connectivity. By re-analyzing the resting-state data from 226 young healthy participants we showed a strong evidence of relationship between ARSQ domain of Comfort and GFS values in the alpha range (r = 0.210, BF10 = 12.338) and substantial evidence for positive relationship between ARSQ domain of Comfort and GFS in the beta frequency range (r = 196, BF10 = 6.307). Our study indicates the relevance of assessments of spontaneous thought occurring during the resting-state for the understanding of the individual intrinsic electrical brain activity.

Frequency-dependent connectivity in large-scale resting-state brain networks during sleep

Functional connectivity (FC) during sleep has been shown to break down as non-rapid eye movement (NREM) sleep deepens before returning to a state closer to wakefulness during rapid eye movement (REM) sleep. However, the specific spatial and temporal signatures of these fluctuations in connectivity patterns remain poorly understood. This study aimed to investigate how frequency-dependent network-level FC fluctuates during nocturnal sleep in healthy young adults using high-density electroencephalography (hdEEG). Specifically, we examined source-localized FC in resting-state networks during NREM2, NREM3 and REM sleep (sleep stages scored using a semi-automatic procedure) in the first three sleep cycles of 29 participants. Our results showed that FC within and between all resting-state networks decreased from NREM2 to NREM3 sleep in multiple frequency bands and all sleep cycles. The data also highlighted a complex modulation of connectivity patterns during the transition to REM sleep whereby delta and sigma bands hosted a persistence of the connectivity breakdown in all networks. In contrast, a reconnection occurred in the default mode and the attentional networks in frequency bands characterizing their organization during wake (i.e., alpha and beta bands, respectively). Finally, all network pairs (except the visual network) showed higher gamma-band FC during REM sleep in cycle three compared to earlier sleep cycles. Altogether, our results unravel the spatial and temporal characteristics of the well-known breakdown in connectivity observed as NREM sleep deepens. They also illustrate a complex pattern of connectivity during REM sleep that is consistent with network- and frequency-specific breakdown and reconnection processes.

Preserved Electroencephalogram Power and Global Synchronization Predict Better Neurological Outcome in Sudden Cardiac Arrest Survivors

Quantitative EEG (qEEG) delineates complex brain activities. Global field synchronization (GFS) is one multichannel EEG analysis that measures global functional connectivity through quantification of synchronization between signals. We hypothesized that preservation of global functional connectivity of brain activity might be a surrogate marker for good outcome in sudden cardiac arrest (SCA) survivors. In addition, we examined the relation of phase coherence and GFS in a mathematical approach. We retrospectively collected EEG data of SCA survivors in one academic medical center. We included 75 comatose patients who were resuscitated following in-hospital or out-of-hospital nontraumatic cardiac arrest between 2013 and 2017 in the intensive care unit (ICU) of National Taiwan University Hospital (NTUH). Twelve patients (16%) were defined as good outcome (GO) (CPC 1-2). The mean age in the GO group was low (51.6 ± 15.7 vs. 68.1 ± 12.9, p < 0.001). We analyzed standard EEG power, computed EEG GFS, and assessed the cerebral performance category (CPC) score 3 months after discharge. The alpha band showed the highest discrimination ability (area under curve [AUC] = 0.78) to predict GO using power. The alpha band of GFS showed the highest AUC value (0.8) to predict GO in GFS. Furthermore, by combining EEG power + GFS, the alpha band showed the best prediction value (AUC 0.86) in predicting GO. The sensitivity of EEG power + GFS was 73%, specificity was 93%, PPV was 0.67%, and NPV was 0.94%. In conclusion, by combining GFS and EEG power analysis, the neurological outcome of the nontraumatic cardiac arrest survivor can be well-predicted. Furthermore, we proved from a mathematical point of view that although both amplitude and phase contribute to obtaining GFS, the interference in phase variation drastically changes the possibility of generating a good GFS score.

Asynchronous and Coherent Dynamics in Balanced Excitatory-Inhibitory Spiking Networks

Dynamic excitatory-inhibitory (E-I) balance is a paradigmatic mechanism invoked to explain the irregular low firing activity observed in the cortex. However, we will show that the E-I balance can be at the origin of other regimes observable in the brain. The analysis is performed by combining extensive simulations of sparse E-I networks composed of N spiking neurons with analytical investigations of low dimensional neural mass models. The bifurcation diagrams, derived for the neural mass model, allow us to classify the possible asynchronous and coherent behaviors emerging in balanced E-I networks with structural heterogeneity for any finite in-degree K. Analytic mean-field (MF) results show that both supra and sub-threshold balanced asynchronous regimes are observable in our system in the limit N >> K >> 1. Due to the heterogeneity, the asynchronous states are characterized at the microscopic level by the splitting of the neurons in to three groups: silent, fluctuation, and mean driven. These features are consistent with experimental observations reported for heterogeneous neural circuits. The coherent rhythms observed in our system can range from periodic and quasi-periodic collective oscillations (COs) to coherent chaos. These rhythms are characterized by regular or irregular temporal fluctuations joined to spatial coherence somehow similar to coherent fluctuations observed in the cortex over multiple spatial scales. The COs can emerge due to two different mechanisms. A first mechanism analogous to the pyramidal-interneuron gamma (PING), usually invoked for the emergence of γ-oscillations. The second mechanism is intimately related to the presence of current fluctuations, which sustain COs characterized by an essentially simultaneous bursting of the two populations. We observe period-doubling cascades involving the PING-like COs finally leading to the appearance of coherent chaos. Fluctuation driven COs are usually observable in our system as quasi-periodic collective motions characterized by two incommensurate frequencies. However, for sufficiently strong current fluctuations these collective rhythms can lock. This represents a novel mechanism of frequency locking in neural populations promoted by intrinsic fluctuations. COs are observable for any finite in-degree K, however, their existence in the limit N >> K >> 1 appears as uncertain.

Cognitive decline in Parkinson's disease is associated with reduced complexity of EEG at baseline

Parkinson’s disease is a neurodegenerative disorder requiring motor signs for diagnosis, but showing more widespread pathological alterations from its beginning. Compared to age-matched healthy individuals, patients with Parkinson’s disease bear a 6-fold lifetime risk of dementia. For individualized counselling and treatment, prognostic biomarkers for assessing future cognitive deterioration in early stages of Parkinson’s disease are needed. In a case–control study, 42 cognitively normal patients with Parkinson’s disease were compared with 24 healthy control participants matched for age, sex and education. Tsallis entropy and band power of the δ, θ, α, β and γ-band were evaluated in baseline EEG at eyes-open and eyes-closed condition. As the θ-band showed the most pronounced differences between Parkinson’s disease and healthy control groups, further analysis focussed on this band. Tsallis entropy was then compared across groups with 16 psychological test scores at baseline and follow-ups at 6 months and 3 years. In group comparison, patients with Parkinson’s disease showed lower Tsallis entropy than healthy control participants. Cognitive deterioration at 3 years was correlated with Tsallis entropy in the eyes-open condition (P < 0.00079), whereas correlation at 6 months was not yet significant. Tsallis entropy measured in the eyes-closed condition did not correlate with cognitive outcome. In conclusion, the lower the EEG entropy levels at baseline in the eyes-open condition, the higher the probability of cognitive decline over 3 years. This makes Tsallis entropy a candidate prognostic biomarker for dementia in Parkinson’s disease. The ability of the cortex to execute complex functions underlies cognitive health, whereas cognitive decline might clinically appear when compensatory capacity is exhausted.

EEG connectivity across sleep cycles and age

STUDY OBJECTIVES

In young adults, sleep is associated with important changes in cerebral connectivity during the first cycle of non-rapid eye movement (NREM) sleep. Our study aimed to evaluate how electroencephalography (EEG) connectivity during sleep differs between young and older individuals, and across the sleep cycles.

METHODS

We used imaginary coherence to estimate EEG connectivity during NREM and rapid eye movement (REM) sleep in 30 young (14 women; 20-30 years) and 29 older (18 women; 50-70 years) individuals. We also explored the association between coherence and cognitive measures.

RESULTS

Older individuals showed lower EEG connectivity in stage N2 but higher connectivity in REM and stage N3 compared to the younger cohort. Age-related differences in N3 were driven by the first sleep cycle. EEG connectivity was lower in REM than N3, especially in younger individuals. Exploratory analyses, controlling for the effects of age, indicated that higher EEG connectivity in delta during N2 was associated with higher processing speed, whereas, during REM sleep, lower EEG connectivity in delta and sigma was associated with higher verbal memory performance and a higher global averaged intelligence quotient score.

CONCLUSION

Our results indicated that age modifies sleep EEG connectivity but the direction and the magnitude of these effects differ between sleep stages and cycles. Results in N3 and REM point to a reduced ability of the older brains to disconnect as compared to the younger ones. Our results also support the notion that cerebral functional connectivity during sleep may be associated with cognitive functions.

Sleep Physiology, Circadian Rhythms, Waking Performance and the Development of Sleep-Wake Therapeutics

Disturbances of the sleep-wake cycle are highly prevalent and diverse. The aetiology of some sleep disorders, such as circadian rhythm sleep-wake disorders, is understood at the conceptual level of the circadian and homeostatic regulation of sleep and in part at a mechanistic level. Other disorders such as insomnia are more difficult to relate to sleep regulatory mechanisms or sleep physiology. To further our understanding of sleep-wake disorders and the potential of novel therapeutics, we discuss recent findings on the neurobiology of sleep regulation and circadian rhythmicity and its relation with the subjective experience of sleep and the quality of wakefulness. Sleep continuity and to some extent REM sleep emerge as determinants of subjective sleep quality and waking performance. The effects of insufficient sleep primarily concern subjective and objective sleepiness as well as vigilant attention, whereas performance on higher cognitive functions appears to be better preserved albeit at the cost of increased effort. We discuss age-related, sex and other trait-like differences in sleep physiology and sleep need and compare the effects of existing pharmacological and non-pharmacological sleep- and wake-promoting treatments. Successful non-pharmacological approaches such as sleep restriction for insomnia and light and melatonin treatment for circadian rhythm sleep disorders target processes such as sleep homeostasis or circadian rhythmicity. Most pharmacological treatments of sleep disorders target specific signalling pathways with no well-established role in either sleep homeostasis or circadian rhythmicity. Pharmacological sleep therapeutics induce changes in sleep structure and the sleep EEG which are specific to the mechanism of action of the drug. Sleep- and wake-promoting therapeutics often induce residual effects on waking performance and sleep, respectively. The need for novel therapeutic approaches continues not at least because of the societal demand to sleep and be awake out of synchrony with the natural light-dark cycle, the high prevalence of sleep-wake disturbances in mental health disorders and in neurodegeneration. Novel approaches, which will provide a more comprehensive description of sleep and allow for large-scale sleep and circadian physiology studies in the home environment, hold promise for continued improvement of therapeutics for disturbances of sleep, circadian rhythms and waking performance.

Coherent chaos in a recurrent neural network with structured connectivity

We present a simple model for coherent, spatially correlated chaos in a recurrent neural network. Networks of randomly connected neurons exhibit chaotic fluctuations and have been studied as a model for capturing the temporal variability of cortical activity. The dynamics generated by such networks, however, are spatially uncorrelated and do not generate coherent fluctuations, which are commonly observed across spatial scales of the neocortex. In our model we introduce a structured component of connectivity, in addition to random connections, which effectively embeds a feedforward structure via unidirectional coupling between a pair of orthogonal modes. Local fluctuations driven by the random connectivity are summed by an output mode and drive coherent activity along an input mode. The orthogonality between input and output mode preserves chaotic fluctuations by preventing feedback loops. In the regime of weak structured connectivity we apply a perturbative approach to solve the dynamic mean-field equations, showing that in this regime coherent fluctuations are driven passively by the chaos of local residual fluctuations. When we introduce a row balance constraint on the random connectivity, stronger structured connectivity puts the network in a distinct dynamical regime of self-tuned coherent chaos. In this regime the coherent component of the dynamics self-adjusts intermittently to yield periods of slow, highly coherent chaos. The dynamics display longer time-scales and switching-like activity. We show how in this regime the dynamics depend qualitatively on the particular realization of the connectivity matrix: a complex leading eigenvalue can yield coherent oscillatory chaos while a real leading eigenvalue can yield chaos with broken symmetry. The level of coherence grows with increasing strength of structured connectivity until the dynamics are almost entirely constrained to a single spatial mode. We examine the effects of network-size scaling and show that these results are not finite-size effects. Finally, we show that in the regime of weak structured connectivity, coherent chaos emerges also for a generalized structured connectivity with multiple input-output modes.

The Improvisational State of Mind: A Multidisciplinary Study of an Improvisatory Approach to Classical Music Repertoire Performance

The recent re-introduction of improvisation as a professional practice within classical music, however cautious and still rare, allows direct and detailed contemporary comparison between improvised and "standard" approaches to performances of the same composition, comparisons which hitherto could only be inferred from impressionistic historical accounts. This study takes an interdisciplinary multi-method approach to discovering the contrasting nature and effects of prepared and improvised approaches during live chamber-music concert performances of a movement from Franz Schubert's "Shepherd on the Rock," given by a professional trio consisting of voice, flute, and piano, in the presence of an invited audience of 22 adults with varying levels of musical experience and training. The improvised performances were found to differ systematically from prepared performances in their timing, dynamic, and timbral features as well as in the degree of risk-taking and "mind reading" between performers, which included moments of spontaneously exchanging extemporized notes. Post-performance critical reflection by the performers characterized distinct mental states underlying the two modes of performance. The amount of overall body movements was reduced in the improvised performances, which showed less unco-ordinated movements between performers when compared to the prepared performance. Audience members, who were told only that the two performances would be different, but not how, rated the improvised version as more emotionally compelling and musically convincing than the prepared version. The size of this effect was not affected by whether or not the audience could see the performers, or by levels of musical training. EEG measurements from 19 scalp locations showed higher levels of Lempel-Ziv complexity (associated with awareness and alertness) in the improvised version in both performers and audience. Results are discussed in terms of their potential support for an "improvisatory state of mind" which may have aspects of flow (as characterized by Csikszentmihalyi, 1997) and primary states (as characterized by the Entropic Brain Hypothesis of Carhart-Harris et al., 2014). In a group setting, such as a live concert, our evidence suggests that this state of mind is communicable between performers and audience thus contributing to a heightened quality of shared experience.

Characteristic Fluctuations Around Stable Attractor Dynamics Extracted from Highly Nonstationary Electroencephalographic Recordings

Since the discovery of electrical activity of the brain, electroencephalographic (EEG) recordings constitute one of the most popular techniques of brain research. However, EEG signals are highly nonstationary and one should expect that averages of the cross-correlation coefficient, which may take positive and negative values with equal probability, (almost) vanish when estimated over long data segments. Instead, we found that the average zero-lag cross-correlation matrix estimated with a running window over the whole night of sleep EEGs, or of resting state during eyes-open and eyes-closed conditions of healthy subjects shows a characteristic correlation pattern containing pronounced nonzero values. A similar correlation structure has already been encountered in scalp EEG signals containing focal onset seizures. Therefore, we conclude that this structure is independent of the physiological state. Because of its pronounced similarity across subjects, we believe that it depicts a generic feature of the brain dynamics. Namely, we interpret this pattern as a manifestation of a dynamical ground state of the brain activity, necessary to preserve an efficient operational mode, or, expressed in terms of dynamical system theory, we interpret it as a "shadow" of the evolution on (or close to) an attractor in phase space. Nonstationary dynamical aspects of higher cerebral processes should manifest in deviations from this stable pattern. We confirm this hypothesis through a correlation analysis of EEG recordings of 10 healthy subjects during night sleep, 20 recordings of 9 epilepsy patients, and 42 recordings of 21 healthy subjects in resting state during eyes-open and eyes-closed conditions. In particular, we show that the estimation of deviations from the stationary correlation structures provides a more significant differentiation of physiological states and more homogeneous results across subjects.

Global field synchronization of 40 Hz auditory steady-state response: Does it change with attentional demands?

Auditory steady-state responses (ASSRs) are increasingly used in research of neuropsychiatric disorders and for brain-computer interface applications. However, results on attentional modulation of ASSRs are inconclusive. The evaluation of large-scale effects of task-related modulation on ASSRs might give better estimation of the induced changes. The aim of the study was to test global field synchronization - a reference-independent evaluation of the amount of phase-locking among all active regions at a given frequency - during tasks differing in attentional demands to 40 Hz auditory stimulation. Twenty seven healthy young males participated in the EEG study with concurrent 40 Hz binaural click stimulation and three experimental tasks: 1) to count presented stimuli (focused attention); 2) to silently read a text (distraction); 3) to stay awake with closed eyes (resting). We showed that during auditory 40 Hz stimulation, the global field synchronization of the EEG increased as compared to the silent baseline period and the largest increase was observed when subjects counted stimuli or rested with closed eyes. Our results provide insights that depending on the method of assessment, the 40 Hz ASSR might be an indicator of both local and complex synchronization processes that are affected by the state (task performed or psychopathology) of the participants.

Achieving Accurate Automatic Sleep Staging on Manually Pre-processed EEG Data Through Synchronization Feature Extraction and Graph Metrics

Sleep staging, the process of assigning labels to epochs of sleep, depending on the stage of sleep they belong, is an arduous, time consuming and error prone process as the initial recordings are quite often polluted by noise from different sources. To properly analyze such data and extract clinical knowledge, noise components must be removed or alleviated. In this paper a pre-processing and subsequent sleep staging pipeline for the sleep analysis of electroencephalographic signals is described. Two novel methods of functional connectivity estimation (Synchronization Likelihood/SL and Relative Wavelet Entropy/RWE) are comparatively investigated for automatic sleep staging through manually pre-processed electroencephalographic recordings. A multi-step process that renders signals suitable for further analysis is initially described. Then, two methods that rely on extracting synchronization features from electroencephalographic recordings to achieve computerized sleep staging are proposed, based on bivariate features which provide a functional overview of the brain network, contrary to most proposed methods that rely on extracting univariate time and frequency features. Annotation of sleep epochs is achieved through the presented feature extraction methods by training classifiers, which are in turn able to accurately classify new epochs. Analysis of data from sleep experiments on a randomized, controlled bed-rest study, which was organized by the European Space Agency and was conducted in the "ENVIHAB" facility of the Institute of Aerospace Medicine at the German Aerospace Center (DLR) in Cologne, Germany attains high accuracy rates, over 90% based on ground truth that resulted from manual sleep staging by two experienced sleep experts. Therefore, it can be concluded that the above feature extraction methods are suitable for semi-automatic sleep staging.

Disrupted Resting State Network of Fibromyalgia in Theta frequency

Fibromyalgia (FM), chronic widespread pain, exhibits spontaneous pain without external stimuli and is associated with altered brain activities during resting state. To understand the topological features of brain network in FM, we employed persistent homology which is a multiple scale network modeling framework not requiring thresholding. Spontaneous magnetoencephalography (MEG) activity was recorded in 19 healthy controls (HCs) and 18 FM patients. Barcode, single linkage dendrogram and single linkage matrix were generated based on the proposed modeling framework. In theta band, the slope of decrease in the number of connected components in barcodes showed steeper in HC, suggesting FM patients had decreased global connectivity. FM patients had reduced connectivity within default mode network, between middle/inferior temporal gyrus and visual cortex. The longer pain duration was correlated with reduced connectivity between inferior temporal gyrus and visual cortex. Our findings demonstrated that the aberrant resting state network could be associated with dysfunction of sensory processing in chronic pain. The spontaneous nature of FM pain may accrue to disruption of resting state network.

Dreamlike effects of LSD on waking imagery in humans depend on serotonin 2A receptor activation

RATIONALE

Accumulating evidence indicates that the mixed serotonin and dopamine receptor agonist lysergic acid diethylamide (LSD) induces an altered state of consciousness that resembles dreaming.

OBJECTIVES

This study aimed to test the hypotheses that LSD produces dreamlike waking imagery and that this imagery depends on 5-HT2A receptor activation and is related to subjective drug effects.

METHODS

Twenty-five healthy subjects performed an audiorecorded guided mental imagery task 7 h after drug administration during three drug conditions: placebo, LSD (100 mcg orally) and LSD together with the 5-HT2A receptor antagonist ketanserin (40 mg orally). Cognitive bizarreness of guided mental imagery reports was quantified as a standardised formal measure of dream mentation. State of consciousness was evaluated using the Altered State of Consciousness (5D-ASC) questionnaire.

RESULTS

LSD, compared with placebo, significantly increased cognitive bizarreness (p < 0.001). The LSD-induced increase in cognitive bizarreness was positively correlated with the LSD-induced loss of self-boundaries and cognitive control (p < 0.05). Both LSD-induced increases in cognitive bizarreness and changes in state of consciousness were fully blocked by ketanserin.

CONCLUSIONS

LSD produced mental imagery similar to dreaming, primarily via activation of the 5-HT2A receptor and in relation to loss of self-boundaries and cognitive control. Future psychopharmacological studies should assess the differential contribution of the D2/D1 and 5-HT1A receptors to cognitive bizarreness.

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

BACKGROUND

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.

NEW METHOD

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.

RESULTS

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.

COMPARISON WITH EXISTING METHOD(S)

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.

CONCLUSIONS

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.