Atypical resting synchrony in autism spectrum disorder

Autism spectrum disorder (ASD) is increasingly understood to be associated with aberrant functional brain connectivity. Few studies, however, have described such atypical neural synchrony among specific brain regions. Here, we used magnetoencephalography (MEG) to characterize alterations in functional connectivity in adolescents with ASD through source space analysis of phase synchrony. Resting‐state MEG data were collected from 16 adolescents with ASD and 15 age‐ and sex‐matched typically developing (TD) adolescents. Atlas‐guided reconstruction of neural activity at various cortical and subcortical regions was performed and inter‐regional phase synchrony was calculated in physiologically relevant frequency bands. Using a multilevel approach, we characterized atypical resting‐state synchrony within specific anatomically defined networks as well as altered network topologies at both regional and whole‐network scales. Adolescents with ASD demonstrated frequency‐dependent alterations in inter‐regional functional connectivity. Hyperconnectivity was observed among the frontal, temporal, and subcortical regions in beta and gamma frequency ranges. In contrast, parietal and occipital regions were hypoconnected to widespread brain regions in theta and alpha bands in ASD. Furthermore, we isolated a hyperconnected network in the gamma band in adolescents with ASD which encompassed orbitofrontal, subcortical, and temporal regions implicated in social cognition. Results from graph analyses confirmed that frequency‐dependent alterations of network topologies exist at both global and local levels. We present the first source‐space investigation of oscillatory phase synchrony in resting‐state MEG in ASD. This work provides evidence of atypical connectivity at physiologically relevant time scales and indicates that alterations of functional connectivity in adolescents with ASD are frequency dependent and region dependent. Hum Brain Mapp 35:6049–6066, 2014. © 2014 Wiley Periodicals, Inc.     

Proposed link rates in the human brain

There is increasing experimental evidence that neuronal synchronization is necessary for the large-scale integration of distributed neuronal activity to realize various time-dependent coherent neuronal assemblies in the brain. Phase synchronization seems a promising candidate to quantify the time-dependent, frequency specific, synchrony between simultaneously recorded electroencephalogram (EEG) signals that may partially reflect this former process. We introduce a link rate (LR) as a measure of the spatial-temporal incidence of phase synchronization and phase de-synchronization. The concept is exemplified in its application to the analysis of spontaneous phase synchronization. To this end, three scalp EEG recordings are used: a normal control, a patient suffering from epileptic seizures and a patient with diffuse brain damage due to anoxia, showing a burst-suppression EEG. In addition, the method is applied to surrogate data (white noise). We find in the normal control that LR(control)=13.90+/-0.04 (mean+/-S.E.M.), which is different from the surrogate data, where we find that LR(surr)=15.36+/-0.05. In the two pathological conditions, the LR is significantly and strongly reduced to LR(burst)=4.52+/-0.05 and LR(seizure)=5.40+/-0.08. The derived LR seems a sensitive measure to relevant changes in synchronization, as these occur in the dynamic process of generating different spatial-temporal networks, both in physiological and pathological conditions.     

Emotions amplify speaker–listener neural alignment

Individuals often align their emotional states during conversation. Here, we reveal how such emotional alignment is reflected in synchronization of brain activity across speakers and listeners. Two “speaker” subjects told emotional and neutral autobiographical stories while their hemodynamic brain activity was measured with functional magnetic resonance imaging (fMRI). The stories were recorded and played back to 16 “listener” subjects during fMRI. After scanning, both speakers and listeners rated the moment‐to‐moment valence and arousal of the stories. Time‐varying similarity of the blood‐oxygenation‐level‐dependent (BOLD) time series was quantified by intersubject phase synchronization (ISPS) between speaker–listener pairs. Telling and listening to the stories elicited similar emotions across speaker–listener pairs. Arousal was associated with increased speaker–listener neural synchronization in brain regions supporting attentional, auditory, somatosensory, and motor processing. Valence was associated with increased speaker–listener neural synchronization in brain regions involved in emotional processing, including amygdala, hippocampus, and temporal pole. Speaker–listener synchronization of subjective feelings of arousal was associated with increased neural synchronization in somatosensory and subcortical brain regions; synchronization of valence was associated with neural synchronization in parietal cortices and midline structures. We propose that emotion‐dependent speaker–listener neural synchronization is associated with emotional contagion, thereby implying that listeners reproduce some aspects of the speaker's emotional state at the neural level.     

Dynamic regional phase synchrony (DRePS)

Dynamic functional brain connectivity analysis is a fast expanding field in computational neuroscience research with the promise of elucidating brain network interactions. Sliding temporal window based approaches are commonly used in order to explore dynamic behavior of brain networks in task‐free functional magnetic resonance imaging (fMRI) data. However, the low effective temporal resolution of sliding window methods fail to capture the full dynamics of brain activity at each time point. These also require subjective decisions regarding window size and window overlap. In this study, we introduce dynamic regional phase synchrony (DRePS), a novel analysis approach that measures mean local instantaneous phase coherence within adjacent fMRI voxels. We evaluate the DRePS framework on simulated data showing that the proposed measure is able to estimate synchrony at higher temporal resolution than sliding windows of local connectivity. We applied DRePS analysis to task‐free fMRI data of 20 control subjects, revealing ultra‐slow dynamics of local connectivity in different brain areas. Spatial clustering based on the DRePS feature time series reveals biologically congruent local phase synchrony networks (LPSNs). Taken together, our results demonstrate three main findings. Firstly, DRePS has increased temporal sensitivity compared to sliding window correlation analysis in capturing locally synchronous events. Secondly, DRePS of task‐free fMRI reveals ultra‐slow fluctuations of ～0.002–0.02 Hz. Lastly, LPSNs provide plausible spatial information about time‐varying brain local phase synchrony. With the DRePS method, we introduce a framework for interrogating brain local connectivity, which can potentially provide biomarkers of human brain function in health and disease. Hum Brain Mapp 37:1970–1985, 2016. © 2016 Wiley Periodicals, Inc.     

Control of phase synchronization of neuronal activity in the rat hippocampus

Analysis of the synchronization mechanisms of neural activity is crucial to the understanding of the generation, propagation and control of epileptiform activity. Recently, phase synchronization (PS) analysis was applied to quantify the partial synchrony that exists in complex chaotic or noisy systems. In a previous study, we have shown that neural activity between two remotely located sites can be synchronized through a complete cut of the tissue by endogenous non-synaptic signals. Therefore, it should be possible to apply signals to control PS. In this study, we test the hypothesis that stimulation amplitudes below excitation level (sub-threshold) can be used to control phase synchronization of two neural signals and we investigate the underlying mechanisms. PS of neuronal activity is first analysed in two coupled Rossler neuron models. Both synchronization and desynchronization could be generated with sub-threshold sinusoidal stimulation. Phase synchronization was then studied in in vitro brain slices. Neuronal activity between two sites was modulated by the application of small sinusoidal electric fields. PS between two remote sites could be achieved by the application of two identical waveforms while phase desynchronization of two close sites was generated by the application of a stimulus at a single site. These results show that sub-threshold stimuli are able to phase synchronize or desynchronize two networks and suggest that small signals could play an important role in normal neural activity and epilepsy.     

Out‐of‐synchrony speech entrainment in developmental dyslexia

Developmental dyslexia is a reading disorder often characterized by reduced awareness of speech units. Whether the neural source of this phonological disorder in dyslexic readers results from the malfunctioning of the primary auditory system or damaged feedback communication between higher‐order phonological regions (i.e., left inferior frontal regions) and the auditory cortex is still under dispute. Here we recorded magnetoencephalographic (MEG) signals from 20 dyslexic readers and 20 age‐matched controls while they were listening to ～10‐s‐long spoken sentences. Compared to controls, dyslexic readers had (1) an impaired neural entrainment to speech in the delta band (0.5–1 Hz); (2) a reduced delta synchronization in both the right auditory cortex and the left inferior frontal gyrus; and (3) an impaired feedforward functional coupling between neural oscillations in the right auditory cortex and the left inferior frontal regions. This shows that during speech listening, individuals with developmental dyslexia present reduced neural synchrony to low‐frequency speech oscillations in primary auditory regions that hinders higher‐order speech processing steps. The present findings, thus, strengthen proposals assuming that improper low‐frequency acoustic entrainment affects speech sampling. This low speech‐brain synchronization has the strong potential to cause severe consequences for both phonological and reading skills. Interestingly, the reduced speech‐brain synchronization in dyslexic readers compared to normal readers (and its higher‐order consequences across the speech processing network) appears preserved through the development from childhood to adulthood. Thus, the evaluation of speech‐brain synchronization could possibly serve as a diagnostic tool for early detection of children at risk of dyslexia. Hum Brain Mapp 37:2767–2783, 2016. © 2016 Wiley Periodicals, Inc .     

Sensorimotor network hypersynchrony as an endophenotype in families with genetic generalized epilepsy: A resting‐state functional magnetic resonance imaging study

Recent evidence suggests that three specific brain networks show state‐dependent levels of synchronization before, during, and after episodes of generalized spike‐wave discharges (GSW) in patients with genetic generalized epilepsy (GGE). Here, we investigate whether synchronization in these networks differs between patients with GGE (n = 13), their unaffected first‐degree relatives (n = 17), and healthy controls (n = 18). All subjects underwent two 10‐minute simultaneous electroencephalographic–functional magnetic resonance imaging (fMRI) recordings without GSW. Whole‐brain data were divided into 90 regions, and blood oxygen level–dependent (BOLD) phase synchrony in a 0.04–0.07‐Hz band was estimated between all pairs of regions. Three networks were defined: (1) the network with highest synchrony during GSW events, (2) a sensorimotor network, and (3) an occipital network. Average synchrony (mean node degree) was inferred across each network over time. Notably, synchrony was significantly higher in the sensorimotor network in patients and in unaffected relatives, compared to controls. There was a trend toward higher synchrony in the GSW network in patients and in unaffected relatives. There was no difference between groups for the occipital network. Our findings provide evidence that elevated fMRI BOLD synchrony in a sensorimotor network is a state‐independent endophenotype of GGE, present in patients in the absence of GSW, and present in unaffected relatives.     

Brain dynamics sustaining rapid rule extraction from speech

Language acquisition is a complex process that requires the synergic involvement of different cognitive functions, which include extracting and storing the words of the language and their embedded rules for progressive acquisition of grammatical information. As has been shown in other fields that study learning processes, synchronization mechanisms between neuronal assemblies might have a key role during language learning. In particular, studying these dynamics may help uncover whether different oscillatory patterns sustain more item-based learning of words and rule-based learning from speech input. Therefore, we tracked the modulation of oscillatory neural activity during the initial exposure to an artificial language, which contained embedded rules. We analyzed both spectral power variations, as a measure of local neuronal ensemble synchronization, as well as phase coherence patterns, as an index of the long-range coordination of these local groups of neurons. Synchronized activity in the gamma band (20-40 Hz), previously reported to be related to the engagement of selective attention, showed a clear dissociation of local power and phase coherence between distant regions. In this frequency range, local synchrony characterized the subjects who were focused on word identification and was accompanied by increased coherence in the theta band (4-8 Hz). Only those subjects who were able to learn the embedded rules showed increased gamma band phase coherence between frontal, temporal, and parietal regions.     

Role of tau protein on neocortical and hippocampal oscillatory patterns

Tau is a neuronal microtubule‐associated protein implicated in microtubules stabilization, axonal establishment and elongation during neuronal morphogenesis. Because of its elevated expression in neocortical regions and hippocampus, tau might play a role in sculpting collective neural responses underlying slow and fast brain oscillations and/or long‐range synchronization patterns between hippocampus and neocortex. To test this hypothesis, local field potentials were recorded in tau‐deficient (tau^?/?) and wild‐type mice from different neocortical regions and from the hippocampus during spontaneous motor exploratory behavior. We found that tau^?/? mice showed hippocampal theta slowing and reduced levels of gamma long‐range synchronization involving the frontal cortex. We hypothesize that the lack of normal phosphorylated tau during early stages of development might influence the maturation of parvalbumin interneurons affecting the spatiotemporal structure of long‐range gamma synchronization. Also, the proper functioning of gap‐junction channels might be compromised by the absence of tau in hippocampal networks. Altogether, these results provide novel insights into the functional role of tau protein in the formation of collective neural responses and emergence of neocortical‐hippocampal interactions in the mammalian brain. © 2010 Wiley‐Liss, Inc.     

Neural synchrony in schizophrenia: from networks to new treatments

Evidence is accumulating that brain regions communicate with each other in the temporal domain, relying on coincidence of neural activity to detect phasic relationships among neurons and neural assemblies. This coordination between neural populations has been described as "self-organizing," an "emergent property" of neural networks arising from the temporal synchrony between synaptic transmission and firing of distinct neuronal populations. Evidence is also accumulating that communication and coordination failures between different brain regions may account for a wide range of problems in schizophrenia, from psychosis to cognitive dysfunction. We review the knowledge about the functional neuroanatomy and neurochemistry of neural oscillations and oscillation abnormalities in schizophrenia. Based on this, we argue that we can begin to use oscillations, across frequencies, to do translational studies to understand the neural basis of schizophrenia.     

Dynamic links between theta executive functions and alpha storage buffers in auditory and visual working memory

Working memory (WM) tasks require not only distinct functions such as a storage buffer and central executive functions, but also coordination among these functions. Neuroimaging studies have revealed the contributions of different brain regions to different functional roles in WM tasks; however, little is known about the neural mechanism governing their coordination. Electroencephalographic (EEG) rhythms, especially theta and alpha, are known to appear over distributed brain regions during WM tasks, but the rhythms associated with task‐relevant regional coupling have not been obtained thus far. In this study, we conducted time–frequency analyses for EEG data in WM tasks that include manipulation periods and memory storage buffer periods. We used both auditory WM tasks and visual WM tasks. The results successfully demonstrated function‐specific EEG activities. The frontal theta amplitudes increased during the manipulation periods of both tasks. The alpha amplitudes increased during not only the manipulation but also the maintenance periods in the temporal area for the auditory WM and the parietal area for the visual WM. The phase synchronization analyses indicated that, under the relevant task conditions, the temporal and parietal regions show enhanced phase synchronization in the theta bands with the frontal region, whereas phase synchronization between theta and alpha is significantly enhanced only within the individual areas. Our results suggest that WM task‐relevant brain regions are coordinated by distant theta synchronization for central executive functions, by local alpha synchronization for the memory storage buffer, and by theta–alpha coupling for inter‐functional integration.     

Uncovering phase‐coupled oscillatory networks in electrophysiological data

Phase consistent neuronal oscillations are ubiquitous in electrophysiological recordings, and they may reflect networks of phase‐coupled neuronal populations oscillating at different frequencies. Because neuronal oscillations may reflect rhythmic modulations of neuronal excitability, phase‐coupled oscillatory networks could be the functional building block for routing information through the brain. Current techniques are not suited for directly characterizing such networks. To be able to extract phase‐coupled oscillatory networks we developed a new method, which characterizes networks by phase coupling between sites. Importantly, this method respects the fact that neuronal oscillations have energy in a range of frequencies. As a consequence, we characterize these networks by between‐site phase relations that vary as a function of frequency, such as those that result from between‐site temporal delays. Using human electrocorticographic recordings we show that our method can uncover phase‐coupled oscillatory networks that show interesting patterns in their between‐site phase relations, such as travelling waves. We validate our method by demonstrating it can accurately recover simulated networks from a realistic noisy environment. By extracting phase‐coupled oscillatory networks and investigating patterns in their between‐site phase relations we can further elucidate the role of oscillations in neuronal communication. Hum Brain Mapp 36:2655–2680, 2015. © 2015 Wiley Periodicals, Inc.     

What does phase information of oscillatory brain activity tell us about cognitive processes?

The electroencephalogram (EEG) bears the possibility to investigate oscillatory processes in the human brain. In the animal brain it has been shown that the phase of cortical oscillations is related to the exact timing of neural activity. The potential role of oscillatory phase and phase synchronization for the explanation of cortical information processing has been largely underestimated in the human EEG until now. Here it is argued that EEG phase (synchronization) reflects the exact timing of communication between distant but functionally related neural populations, the exchange of information between global and local neuronal networks, and the sequential temporal activity of neural processes in response to incoming sensory stimuli. Three different kinds of phase synchronization are discussed: (i) phase coupling between brain sites, (ii) phase synchronization across frequencies, and (iii) phase-locking to external events. In this review recent work is presented demonstrating that EEG phase synchronization provides valuable information about the neural correlates of various cognitive processes, and that it leads to a better understanding of how memory and attention processes are interrelated.     

Temporal stability of functional brain modules associated with human intelligence

Individual differences in general cognitive ability (i.e., intelligence) have been linked to individual variations in the modular organization of functional brain networks. However, these analyses have been limited to static (time‐averaged) connectivity, and have not yet addressed whether dynamic changes in the configuration of brain networks relate to general intelligence. Here, we used multiband functional MRI resting‐state data (N = 281) and estimated subject‐specific time‐varying functional connectivity networks. Modularity optimization was applied to determine individual time‐variant module partitions and to assess fluctuations in modularity across time. We show that higher intelligence, indexed by an established composite measure, the Wechsler Abbreviated Scale of Intelligence (WASI), is associated with higher temporal stability (lower temporal variability) of brain network modularity. Post‐hoc analyses reveal that subjects with higher intelligence scores engage in fewer periods of extremely high modularity — which are characterized by greater disconnection of task‐positive from task‐negative networks. Further, we show that brain regions of the dorsal attention network contribute most to the observed effect. In sum, our study suggests that investigating the temporal dynamics of functional brain network topology contributes to our understanding of the neural bases of general cognitive abilities.     

Neuronal dynamics enable the functional differentiation of resting state networks in the human brain

Intrinsic brain activity is organized in spatial–temporal patterns, called resting‐state networks (RSNs), exhibiting specific structural–functional architecture. These networks presumably reflect complex neurophysiological processes and have a central role in distinct perceptual and cognitive functions. In this work, we propose an innovative approach for characterizing RSNs according to their underlying neural oscillations. We investigated specific electrophysiological properties, including spectral features, fractal dimension, and entropy, associated with eight core RSNs derived from high‐density electroencephalography (EEG) source‐reconstructed signals. Specifically, we found higher synchronization of the gamma‐band activity and higher fractal dimension values in perceptual (PNs) compared with higher cognitive (HCNs) networks. The inspection of this underlying rapid activity becomes of utmost importance for assessing possible alterations related to specific brain disorders. The disruption of the coordinated activity of RSNs may result in altered behavioral and perceptual states. Thus, this approach could potentially be used for the early detection and treatment of neurological disorders.     

Disrupted network connectivity in pediatric brain tumor survivors is a signature of injury

Cognition is compromised in pediatric brain tumor survivors but the neurophysiological basis of this compromise remains unclear. We hypothesized that reduced neural synchronization across brain networks is involved. To test this, we evaluated group differences using a retrospective cohort comparison design between 24 pediatric brain tumor survivors [11.81 ± 3.27)] and 24 age matched healthy children [12.04 ± 3.28)] in functional connectivity within a cerebellar network to examine local effects of the tumor, a whole brain network to examine diffuse effects of treatment (i.e., chemotherapy and radiation), and across multiple intrinsic connectivity networks. Neural activity was recorded during magnetoencephalography scanning while participants were at rest and functional connectivity within networks was measured using the phase lag index. We corroborated our findings using a computational model representing the local tumor effects on neural synchrony. Compared to healthy children, pediatric brain tumor survivors show increased functional connectivity for theta and beta frequency bands within the cerebellar network and increased functional connectivity for the theta band within the whole brain network that again localized to the cerebellum. Computational modeling showed that increased synchrony in the theta bad is observed following local clustering as well as sparse interarea brain connectivity. We also observed increased functional connectivity for the alpha frequency band in the ventral attention network and decreased functional connectivity within the gamma frequency band in the motor network within paedatric brain tumor survivors versus healthy children. Notably, increased gamma functional connectivity within the motor network predicted decreased reaction time on behavioral tasks in pediatric brain tumor survivors. Disrupted network synchrony may be a signature of neurological injury and disease.     

Neural synchrony and gray matter variation in human males and females: integration of 40 Hz gamma synchrony and MRI measures

Coherent cognition requires activity to be brought together across diverse brain networks. Synchronous, in-phase oscillations in the high-frequency (40 Hz) Gamma range are thought to be one mechanism underlying the functional integration of brain networks. While sex differences have been observed across a range of cognitive functions, their role in normal cortical synchronization has not been elucidated. We recorded Gamma phase synchrony in 500 male and 500 female subjects during an auditory oddball task, which taps discrimination of task-relevant signals. Results revealed a marked sex-linked dissociation in the spatio-temporal pattern of cortical synchronization. Females showed increased Gamma synchrony in the frontal brain, while males showed enhanced synchrony in the parieto-occipital region. These differences were not accounted for by sex differences in whole brain MRI volume. However, there were positive associations between Gamma synchrony and gray matter for females, while these relationships were negative for males. Sex differences in the profile of cortical synchronization may reflect distinct aspects of evolutionary advantage.     

Interaction of synchronized dynamics in cortex and basal ganglia in Parkinson's disease

Parkinson's disease pathophysiology is marked by increased oscillatory and synchronous activity in the beta frequency band in cortical and basal ganglia circuits. This study explores the functional connections between synchronized dynamics of cortical areas and synchronized dynamics of subcortical areas in Parkinson's disease. We simultaneously recorded neuronal units (spikes) and local field potentials (LFP) from subthalamic nucleus (STN) and electroencephalograms (EEGs) from the scalp in parkinsonian patients, and analysed the correlation between the time courses of the spike–LFP synchronization and inter‐electrode EEG synchronization. We found the (non‐invasively obtained) time course of the synchrony strength between EEG electrodes and the (invasively obtained) time course of the synchrony between spiking units and LFP in STN to be weakly, but significantly, correlated with each other. This correlation is largest for the bilateral motor EEG synchronization, followed by bilateral frontal EEG synchronization. Our observations suggest that there may be multiple functional modes by which the cortical and basal ganglia circuits interact with each other in Parkinson's disease: not only may synchronization be observed between some areas in cortex and the basal ganglia, but also synchronization within cortex and within basal ganglia may be related, suggesting potentially a more global functional interaction. More coherent dynamics in one brain region may modulate or activate the dynamics of another brain region in a more powerful way, causing correlations between changes in synchrony strength in the two regions.     

Periods of rest in fMRI contain individual spontaneous events which are related to slowly fluctuating spontaneous activity

fMRI studies of brain activity at rest study slow (<0.1 Hz) intrinsic fluctuations in the blood‐oxygenation‐level‐dependent (BOLD) signal that are observed in a temporal scale of several minutes. The origin of these fluctuations is not clear but has previously been associated with slow changes in rhythmic neuronal activity resulting from changes in cortical excitability or neuronal synchronization. In this work, we show that individual spontaneous BOLD events occur during rest, in addition to slow fluctuations. Individual spontaneous BOLD events were identified by deconvolving the hemodynamic impulse response function for each time point in the fMRI time series, thus requiring no information on timing or a‐priori spatial information of events. The patterns of activation detected were related to the motor, visual, default‐mode, and dorsal attention networks. The correspondence between spontaneous events and slow fluctuations in these networks was assessed using a sliding window, seed‐correlation analysis, where seed regions were selected based on the individual spontaneous event BOLD activity maps. We showed that the correlation varied considerably over time, peaking at the time of spontaneous events in these networks. By regressing spontaneous events out of the fMRI signal, we showed that both the correlation strength and the power in spectral frequencies <0.1 Hz decreased, indicating that spontaneous activation events contribute to low‐frequency fluctuations observed in resting state networks with fMRI. This work provides new insights into the origin of signals detected in fMRI studies of functional connectivity. Hum Brain Mapp, 2013. © 2012 Wiley Periodicals, Inc.     

Large‐scale network organization of EEG functional connectivity in newborn infants

The organization of functional brain networks changes across human lifespan. The present study analyzed functional brain networks in healthy full‐term infants (N = 139) within 1–6 days from birth by measuring neural synchrony in EEG recordings during quiet sleep. Large‐scale phase synchronization was measured in six frequency bands with the Phase Lag Index. Macroscopic network organization characteristics were quantified by constructing unweighted minimum spanning tree graphs. The cortical networks in early infancy were found to be significantly more hierarchical and had a more cost‐efficient organization compared with MST of random control networks, more so in the theta and alpha than in other frequency bands. Frontal and parietal sites acted as the main hubs of these networks, the topological characteristics of which were associated with gestation age (GA). This suggests that individual differences in network topology are related to cortical maturation during the prenatal period, when functional networks shift from strictly centralized toward segregated configurations. Hum Brain Mapp 38:4019–4033, 2017. © 2017 Wiley Periodicals, Inc.