Abnormal topography of EEG microstates in Gilles de la Tourette syndrome

Association of resting-state theta–gamma coupling with selective visual attention in children with tic disorders

A tic disorder (TD) is a neurodevelopmental disorder characterized by tics, which are repetitive movements and/or vocalizations that occur due to aberrant sensory gating. Its pathophysiology involves dysfunction in multiple parts of the cortico-striato-thalamo-cortical circuits. Spontaneous brain activity during the resting state can be used to evaluate the baseline brain state, and it is associated with various aspects of behavior and cognitive processes. Theta–gamma coupling (TGC) is an emerging technique for examining how neural networks process information through interactions. However, the resting-state TGC of patients with TD and its correlation with cognitive function have not yet been studied. We investigated the resting-state TGC of 13 patients with TD and compared it with that of 13 age-matched healthy children. The participants underwent resting-state electroencephalography with their eyes closed. At the global level, patients with TD showed a significantly lower resting-state TGC than healthy children. Resting-state TGC with the eyes closed was significantly negatively correlated with the attention quotient calculated for omission errors in a selective visual attention test. These findings indicate that the resting-state brain network, which is important for the attentional processing of visual information, is dysfunctional in patients with TD. Additionally, these findings support the view that TGC reflects information processing and signal interactions at the global level. Patients with TD may have difficulty gating irrelevant sensory information in the resting state while their eyes are closed.

Resting state electroencephalography microstates in autism spectrum disorder: A mini-review

Atypical spatial organization and temporal characteristics, found via resting state electroencephalography (EEG) microstate analysis, have been associated with psychiatric disorders but these temporal and spatial parameters are less known in autism spectrum disorder (ASD). EEG microstates reflect a short time period of stable scalp potential topography. These canonical microstates (i.e., A, B, C, and D) and more are identified by their unique topographic map, mean duration, fraction of time covered, frequency of occurrence and global explained variance percentage; a measure of how well topographical maps represent EEG data. We reviewed the current literature for resting state microstate analysis in ASD and identified eight publications. This current review indicates there is significant alterations in microstate parameters in ASD populations as compared to typically developing (TD) populations. Microstate parameters were also found to change in relation to specific cognitive processes. However, as microstate parameters are found to be changed by cognitive states, the differently acquired data (e.g., eyes closed or open) resting state EEG are likely to produce disparate results. We also review the current understanding of EEG sources of microstates and the underlying brain networks.

Discrimination of Tourette Syndrome Based on the Spatial Patterns of the Resting-State EEG Network

Tourette syndrome (TS) is a neuropsychiatric disorder with childhood onset characterized by chronic motor and vocal tics; however, the current diagnosis of TS patients is subjective, as it is mainly assessed based on the parents' description alongside specific evaluations. The early and accurate diagnosis of TS based on its potential symptoms in children would be of benefit in their future therapy, but reliable diagnoses are difficult due to the lack of objective knowledge of the etiology and pathogenesis of TS. In this study, resting-state electroencephalograms were first collected from 36 patients and 21 healthy controls (HCs); the corresponding resting-state functional networks were then constructed, and the potential differences in network topology between the two groups were extracted by using the topology of the spatial pattern of the network (SPN). Compared to the HCs, the TS patients exhibited decreased frontotemporal/occipital/parietal connectivity. When classifying the two groups, compared to the network properties, the derived SPN features achieved a much higher accuracy of 92.31%. The intrinsic long-range connectivity between the frontal and the temporal/occipital/parietal lobes was damaged in the patient group, and this dysfunctional network pattern might serve as a reliable biomarker to differentiate TS patients from HCs as well as to assess the severity of tic symptoms.

EEG Microstates Temporal Dynamics Differentiate Individuals with Mood and Anxiety Disorders From Healthy Subjects

Electroencephalography (EEG) measures the brain’s electrophysiological spatio-temporal activities with high temporal resolution. Multichannel and broadband analysis of EEG signals is referred to as EEG microstates (EEG-ms) and can characterize such dynamic neuronal activity. EEG-ms have gained much attention due to the increasing evidence of their association with mental activities and large-scale brain networks identified by functional magnetic resonance imaging (fMRI). Spatially independent EEG-ms are quasi-stationary topographies (e.g., stable, lasting a few dozen milliseconds) typically classified into four canonical classes (microstates A through D). They can be identified by clustering EEG signals around EEG global field power (GFP) maxima points. We examined the EEG-ms properties and the dynamics of cohorts of mood and anxiety (MA) disorders subjects (n = 61) and healthy controls (HCs; n = 52). In both groups, we found four distinct classes of EEG-ms (A through D), which did not differ among cohorts. This suggests a lack of significant structural cortical abnormalities among cohorts, which would otherwise affect the EEG-ms topographies. However, both cohorts’ brain network dynamics significantly varied, as reflected in EEG-ms properties. Compared to HC, the MA cohort features a lower transition probability between EEG-ms B and D and higher transition probability from A to D and from B to C, with a trend towards significance in the average duration of microstate C. Furthermore, we harnessed a recently introduced theoretical approach to analyze the temporal dependencies in EEG-ms. The results revealed that the transition matrices of MA group exhibit higher symmetrical and stationarity properties as compared to HC ones. In addition, we found an elevation in the temporal dependencies among microstates, especially in microstate B for the MA group. The determined alteration in EEG-ms temporal dependencies among the cohorts suggests that brain abnormalities in mood and anxiety disorders reflect aberrant neural dynamics and a temporal dwelling among ceratin brain states (i.e., mood and anxiety disorders subjects have a less dynamicity in switching between different brain states).

Comparison of EEG microstates with resting state fMRI and FDG-PET measures in the default mode network via simultaneously recorded trimodal (PET/MR/EEG) data

Simultaneous trimodal positron emission tomography/magnetic resonance imaging/electroencephalography (PET/MRI/EEG) resting state (rs) brain data were acquired from 10 healthy male volunteers. The rs-functional MRI (fMRI) metrics, such as regional homogeneity (ReHo), degree centrality (DC) and fractional amplitude of low-frequency fluctuations (fALFFs), as well as 2-[18F]fluoro-2-desoxy-d-glucose (FDG)-PET standardised uptake value (SUV), were calculated and the measures were extracted from the default mode network (DMN) regions of the brain. Similarly, four microstates for each subject, showing the diverse functional states of the whole brain via topographical variations due to global field power (GFP), were estimated from artefact-corrected EEG signals. In this exploratory analysis, the GFP of microstates was nonparametrically compared to rs-fMRI metrics and FDG-PET SUV measured in the DMN of the brain. The rs-fMRI metrics (ReHO, fALFF) and FDG-PET SUV did not show any significant correlations with any of the microstates. The DC metric showed a significant positive correlation with microstate C (r_s  = 0.73, p = .01). FDG-PET SUVs indicate a trend for a negative correlation with microstates A, B and C. The positive correlation of microstate C with DC metrics suggests a functional relationship between cortical hubs in the frontal and occipital lobes. The results of this study suggest further exploration of this method in a larger sample and in patients with neuropsychiatric disorders. The aim of this exploratory pilot study is to lay the foundation for the development of such multimodal measures to be applied as biomarkers for diagnosis, disease staging, treatment response and monitoring of neuropsychiatric disorders.

Altered Brain Microstate Dynamics in Adolescents with Narcolepsy

Narcolepsy is a chronic sleep disorder caused by a loss of hypocretin-1 producing neurons in the hypothalamus. Previous neuroimaging studies have investigated brain function in narcolepsy during rest using positron emission tomography (PET) and single photon emission computed tomography (SPECT). In addition to hypothalamic and thalamic dysfunction they showed aberrant prefrontal perfusion and glucose metabolism in narcolepsy. Given these findings in brain structure and metabolism in narcolepsy, we anticipated that changes in functional magnetic resonance imaging (fMRI) resting state network (RSN) dynamics might also be apparent in patients with narcolepsy. The objective of this study was to investigate and describe brain microstate activity in adolescents with narcolepsy and correlate these to RSNs using simultaneous fMRI and electroencephalography (EEG). Sixteen adolescents (ages 13-20) with a confirmed diagnosis of narcolepsy were recruited and compared to age-matched healthy controls. Simultaneous EEG and fMRI data were collected during 10 min of wakeful rest. EEG data were analyzed for microstates, which are discrete epochs of stable global brain states obtained from topographical EEG analysis. Functional MRI data were analyzed for RSNs. Data showed that narcolepsy patients were less likely than controls to spend time in a microstate which we found to be related to the default mode network and may suggest a disruption of this network that is disease specific. We concluded that adolescents with narcolepsy have altered resting state brain dynamics.

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

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

Reliability of resting-state microstate features in electroencephalography

Background

Electroencephalographic (EEG) microstate analysis is a method of identifying quasi-stable functional brain states (“microstates”) that are altered in a number of neuropsychiatric disorders, suggesting their potential use as biomarkers of neurophysiological health and disease. However, use of EEG microstates as neurophysiological biomarkers requires assessment of the test-retest reliability of microstate analysis.

Methods

We analyzed resting-state, eyes-closed, 30-channel EEG from 10 healthy subjects over 3 sessions spaced approximately 48 hours apart. We identified four microstate classes and calculated the average duration, frequency, and coverage fraction of these microstates. Using Cronbach's α and the standard error of measurement (SEM) as indicators of reliability, we examined: (1) the test-retest reliability of microstate features using a variety of different approaches; (2) the consistency between TAAHC and k-means clustering algorithms; and (3) whether microstate analysis can be reliably conducted with 19 and 8 electrodes.

Results

The approach of identifying a single set of “global” microstate maps showed the highest reliability (mean Cronbach's α>0.8, SEM ≈10% of mean values) compared to microstates derived by each session or each recording. There was notably low reliability in features calculated from maps extracted individually for each recording, suggesting that the analysis is most reliable when maps are held constant. Features were highly consistent across clustering methods (Cronbach's α>0.9). All features had high test-retest reliability with 19 and 8 electrodes.

Conclusions

High test-retest reliability and cross-method consistency of microstate features suggests their potential as biomarkers for assessment of the brain's neurophysiological health.

Increased frontomotor oscillations during tic suppression in children with Tourette syndrome

This work investigated whether Tourette syndrome patients exhibit alterations in neural oscillations during spontaneous expression and suppression of tics. Electroencephalograms (EEGs) were recorded from 9 medication-naïve children with Tourette syndrome and 10 age-matched healthy subjects in resting conditions and during tic suppression. Their cortical oscillations were examined using the power spectral method and partial directed coherence. The authors found increased oscillations of broad frequency bands in the frontomotor regions of patients during tic expression, suggesting the involvement of aberrant cortical oscillations in Tourette syndrome. More significantly, prominent increases in theta oscillation in the prefrontal area and directed frontomotor interactions in the theta and beta bands were observed during tic suppression. Furthermore, the directed EEG interaction from the frontal to motor regions was positively correlated with the severity of tic symptoms. These findings suggest that the frontal to motor interaction of cortical oscillations plays a significant role in tic suppression.

Neuropsychological evaluation in the diagnosis and treatment of Tourette's syndrome

The neurobiological basis of Tourette's syndrome is reviewed for the purpose of presenting a clinically relevant account of the neuropsychology of the disorder for the clinician who is behaviorally oriented. The neuropathology and neuropsychological deficits typically found in Tourette's are reviewed, and a neuropsychological test battery is described that can be used to help characterize the clinical presentation of the disorder. Although Tourette's syndrome is ultimately diagnosed by behavioral criteria, characterizing the cognitive deficits (or lack thereof) associated with the disorder is integral to fully appreciating the challenges posed by the disorder in any given case. The variety of cognitive deficits associated with Tourette's is reviewed to show the importance of the neuropsychological evaluation in differential diagnostic, therapeutic, and prognostic decisions.

Neurophysiology of Tourette's syndrome: pathophysiological considerations

At present the neurophysiology of Tourette's syndrome (TS) has been investigated largely from two perspectives; one for evaluation of the dysfunction of the cerebral cortex and the other for clarification of the neuronal mechanisms that underlie tics and related symptoms. For the former the following examinations have been conducted: quantitative analyses of scalp electroencephalography (EEG), premovement EEG potentials, contingent negative variation, transcranial magnetic stimulation, and neuroimaging studies, including echo-planar images and positron emission tomography scans. These explorations have revealed the likely involvement of the subcortical and the cortical structures, particularly of the basal ganglia, in the pathophysiology of TS. For the latter, surface electromyography, evoked potentials, saccadic eye movements, and polysomnographies have been performed, and again have suggested a dysfunction of the basal ganglia and the brainstem neurons in TS patients. These neurophysiological studies suggest dysfunction of both motor and non-motor basal ganglia-thalamocortical circuitries in TS patients, which is hypothesized to be caused by hypofunction of the dopamine (DA) neurons associated with DA receptor supersensitivity, a well as hypofunction of the serotonergic neurons of the brainstem. Polysomnographical examination suggests that the dysfunction of the nigrostriatal (NS)-DA neurons is not a progressive process, but that the dysfunction is closely associated with an early occurrence of the developmental decrement of the activities of the NS-DA system to mature in a normal fashion. The associated DA receptor supersensitivity is assumed to be a consequence of this developmental abnormality and not due to denervation supersensitivity.

First-episode schizophrenics show normal duration and topography of quasistationary EEG segments as compared to controls, during rest as well as during active tasks

In patients suffering from chronic schizophrenia, both altered temporospatial structure of the EEG and impaired activation during cognitive tasks have repeatedly been demonstrated. The present study evaluates whether similar abnormalities are present in drug-naive first-episode schizophrenics. The EEGs of 32 schizophrenic patients and of 52 healthy controls were recorded during a simple and a complicated motor task, a simple and a complicated auditory stimulus, and during resting periods between the tasks. The temporospatial characteristics were evaluated by adaptive segmentation of EEG, which decomposes an EEG into temporal segments of quasistationary activity. No differences in the temporal and topographic aspects of the EEGs were found between the first-episode schizophrenic patients and the controls, neither during the resting EEGs nor during active tasks. Moreover, the dynamic course of the EEGs, defined as the alternation between task-related changes of temporospatial patterns and the reappearance of resting patterns, was identical in patients and controls. The present findings suggest that while abnormal EEG power spectra seem a consistent finding in treated as well as in never-treated schizophrenics, altered temporospatial patterns and reduced task-related EEG changes are inconsistent signs.

Decreased duration and altered topography of electroencephalographic microstates in patients with panic disorder

The topography and temporal sequence of scalp electrical fields were analyzed by adaptive segmentation of the continuous electroencephalogram (EEG) in 27 patients with panic disorder and 28 control subjects during rest phases and during the viewing of a neutral (mushroom) or an emotionally relevant (casualty) picture. The results indicate decreased duration of brain microstates in panic patients during all conditions. Comparison of the resting phases with the viewing conditions revealed a significant acceleration of EEG microstates in both the patients and the control subjects. Patients and control subjects differed in the topography of the fields during rest: control subjects showed a left-anterior/right-posterior orientation, while panic patients showed a predominantly right-anterior/left-posterior orientation. Neither group displayed any topographic changes when viewing the mushroom picture. However, when viewing the anxiety-specific casualty picture, panic patients shifted fields in a different way than did control subjects. Centroid topography does not permit clear localization of the cortical generators. It is concluded that panic patients show a generally increased cortical activation compared with healthy control subjects, and activate different neuronal arrays when viewing an anxiety-specific stimulus.

Decreased EEG microstate duration and anteriorisation of the brain electrical fields in mild and moderate dementia of the Alzheimer type

Spatially oriented segmentation allows researchers to break down the continuous stream of the ongoing EEG into microstates with stable topography of the brain electrical landscapes. The resulting microstates were shown to be related to conscious mental experience as well as to psychiatric disorders typically associated with thought disorders. In the present study, the microstates of the resting EEG of patients presenting with mild or moderate probable dementia of the Alzheimer type (DAT) were investigated. A significant anteriorisation of the centers of gravity of the microstate fields, an increase of the microstates' optimal window size and a reduced duration of sustained microstates were found. These differences were statistically more robust than the typical changes in the frequency domain (diffuse slowing) and were significantly correlated with the cognitive decline. The adaptive spatial segmentation into microstates is discussed as a method to extract meaningful EEG parameters for the early diagnosis and staging of Alzheimer's disease.

EEG-microstates in mild memory impairment and Alzheimer's disease: possible association with disturbed information processing

The only available functional neuroimaging methods reaching the time resolution of human information processing are EEG and MEG. Since spectral analysis implies analysis of longer time epochs, the high temporal resolution of EEG is partly lost. By dividing the EEG in the time-domain into segments of similar spatial distribution on the scalp (microstates) it has been possible to assess patterns of neuronal activity representing the information process currently performed by the brain. In the present study alterations of EEG microstates in subjective (n = 31) and objective (n = 38) memory impairment as well as in probable Alzheimer disease (DAT: n = 64) compared to healthy controls (n = 21) were investigated. The main findings were reduced segment durations and a more anterior center of gravity of the microstate topography in DAT. With more pronounced cognitive dysfunction larger window sizes were found. Shorter microstates and larger windows reflect more rapidly changing spatial activation patterns, and are interpreted as an impaired capability to establish stable brain states necessary for normal brain function. The anteriorization of the microstates is consistent with results in the frequency domain and may reflect neuropathological changes in DAT.