Prognostic Value of EEG Microstates in Acute Stroke

Zappasodi, Filippo; Croce, Pierpaolo; Giordani, Alessandro; Assenza, Giovanni; Giannantoni, Nadia Mariagrazia; Profice, Paolo; Granata, Giuseppe; Rossini, Paolo Maria; Tecchio, Franca

doi:10.1007/s10548-017-0572-0

Cited by 76 publications

(74 citation statements)

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“…A study by Lehmann et al [25] in which microstate configurations and syntax were found significantly different for imagery, and abstract thoughts, respectively, is considered as a validation of their link with cognitive processes. In a clinical context, studies employing microstate analysis found substantial electrophysiological signatures for altered neuronal processes that differ between healthy controls and subjects with psychopathology [26], dementia [27], schizophrenia [28], and stroke [29], provide further evidence of their usefulness. Moreover, recent studies assessing resting state dynamics using simultaneous EEG and fMRI has shown that the imprints of abruptly changing short-lived states of brain calculated using multichannel electrode array are related to resting-state networks.…”

Section: Introductionmentioning

confidence: 93%

Normal Aging: Alterations in Scalp EEG Using Broadband and Band-Resolved Topographic Maps

2020

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Given the majority of age-related diseases have been described as disconnection syndromes, understanding the functional connections of normal aging is of considerable importance. Here, an EEG-based scalp level analysis has been performed to identify the alterations in the synchronized brain regions in aged, compared to young persons. Two groups, aged and young subjects were studied, each consisting of 18 participants. First, conventionally extracted broadband topographic maps, also called microstate maps, were examined. The results showed an overall dominant alteration: a uniform decrease in synchronization of brain regions related to cognitive processing resources that was observed only when the maps C and D were characterized in temporal parameters. However, no remarkable change in the spatial distribution was found between the groups. This failure in identifying differences in the spatial distribution was hypothesized to be due to the presence of superimposed signals of several frequencies in the broadband signal that is used for the extraction of microstate maps. Second, spectrally resolved band-wise topographic maps, which we have shown, in a previous study, are able to detect spectral details associated with broadband microstates maps, were used to address this failure. The use of the instantaneous frequency concept is essential in the extraction of band-wise topographic maps, and represents a novelty compared to current studies. The method consists of three steps: (a) from EEG signal, the Empirical Mode Decomposition method is used to extract underlying oscillatory components; (b) these intrinsic oscillatory components are then amplitude demodulated and subjected to numerical equations for the calculation of instantaneous features, such as amplitude, and frequency; finally, (c) based on these instantaneous features, band-wise topographic maps are extracted. Here, as a first application to aging data, these band-wise topographic maps have shown the capability of capturing the age-related changes in both spatial distributions, and in temporal characterization. Spatially, the potential distribution in the aged and the young subject groups, respectively, showed differences, while, in temporal characterization, both increases and decreases were observed, suggesting the lengths of synchronized activities vary differentially, and in accordance with results from fMRI studies. These observed differences also support the dedifferentiation and compensation mechanisms.

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Section: Introductionmentioning

confidence: 93%

Normal Aging: Alterations in Scalp EEG Using Broadband and Band-Resolved Topographic Maps

2020

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“…conditions or groups (Nishida et al, 2013;Santarnecchi et al, 2017;Zappasodi et al, 2017). The boxplot in Figure 4 illustrates the different steps of microstate analysis.…”

Section: Determining Microstates: Fitting the Cluster Maps To The Datamentioning

confidence: 99%

“…The microstate approach has also be used to investigated conditions such as dementia (Nishida et al, 2013), narcolepsy (Drissi et al, 2016), panic disorder (Kikuchi et al, 2011), multiple sclerosis (Gschwind et al, 2016), head injury (Corradini and Persinger, 2014), diplegia (Gao et al, 2017), and stroke (Zappasodi et al, 2017). In contrast to schizophrenia, decreased occurrence of microstate C and changes in microstate A and B have been observed in patients with most of these other conditions, indicating that imbalances in microstate C and D may be specific to schizophrenia.…”

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EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review

2018

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SummaryThe present review discusses a well-established method for characterizing resting-state activity of the human brain using multichannel electroencephalography (EEG). This method involves the examination of electrical microstates in the brain, which are defined as successive short time periods during which the configuration of the scalp potential field remains semi-stable, suggesting quasi-simultaneity of activity among the nodes of largescale networks. A few prototypic microstates, which occur in a repetitive sequence across time, can be reliably identified across participants. Researchers have proposed that these microstates represent the basic building blocks of the chain of spontaneous conscious mental processes, and that their occurrence and temporal dynamics determine the quality of mentation. Several studies have further demonstrated that disturbances of mental processes associated with neurological and psychiatric conditions manifest as changes in the temporal dynamics of specific microstates. Combined EEG-fMRI studies and EEG source imaging studies have indicated that EEG microstates are closely associated with resting-state networks as identified using fMRI. The scale-free properties of the time series of EEG microstates explain why similar networks can be observed at such different time scales.The present review will provide an overview of these EEG microstates, available methods for analysis, the functional interpretations of findings regarding these microstates, and their behavioral and clinical correlates.

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“…Recently, a correlation between the four microstate topographies and the blood oxygenated level dependent (BOLD) activations in regions belonging to different human resting state brain networks has been found 21,22 . Indeed, modularity of brain dynamics in behavioural and cognitive control has been evidenced through microstate analysis and microstates have been proved to be useful in the study of brain diseases 20,[23][24][25][26][27][28] .…”

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EEG microstates associated with intra- and inter-subject alpha variability

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Quercia

Costa

et al. 2020

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Variation of the magnitude of posterior alpha rhythm (8-12 Hz) has functional and behavioural effects in sensory processing and cognitive performances. Electrical brain activity, as revealed by electroencephalography (EEG), can be represented by a sequence of microstates of about 40-120 ms duration, in which distributed neural pools are synchronously active and generate stable spatial potential topographies on the scalp. Microstate dynamics may reflect transitions between global states characterized by selective inhibition of specific intra-cortical regions, mediated by alpha activity. We investigated the intra-subject and inter-subject relationship between microstate features and alpha band. High-density EEG signals were acquired in 29 healthy subjects during ten minutes of eyes closed rest. Individual EEG signal epochs were classified into four groups depending on the amount of occipital alpha power, and microstate metrics (duration, coverage and frequency of occurrence) were calculated and compared across groups. Correlations between alpha power and microstate metrics between individuals were also performed. To assess if microstate parameter variations are specific for the alpha band, the same analysis was also performed for theta and beta bands, as well as for global field power. We observed an increase in the metrics of microstate, previously associated to the visual system, with the level of intra-subject amplitude alpha oscillations, together with lower coverage of microstate associated with executive attention network and a higher frequency of microstate associated with task negative network. Other modulation effects of broad-band EEG power level on microstate metrics were observed. These effects are not specific for the alpha band, since they can equally be attributed to fluctuations in other frequency bands. We can interpret our results as a regulation mechanism mediated by posterior alpha level, dynamically interacting with other frequency bands, responsible for the switching between active areas.The dynamics of human brain signals uncover organized fluctuations both at rest and during task or sensory input. Such time signal variability has been recently linked to the efficiency of functional abilities and directly associated to cognitive performances in functional Magnetic Resonance Imaging (fMRI), Magnetoencephalographic (MEG), Electrocorticographic (ECoG) and Electroencephalographic (EEG) studies (for a review see Buzsáki and colleagues 1 ).Alpha rhythm (8-12 Hz) is a prominent component of the spectral content of electrical brain signals, as recorded at the scalp surface by EEG or MEG 2 . Although the parieto-occipital alpha rhythm has been supposed for years to reflect an idle status, it is currently considered to play a crucial role in higher cognitive processes and memory performances and to have a functional significance even at rest 3,4 . Specifically, perception and other ongoing neural activities have been related to alpha rhythm modulation 5 . In this regards, Hanslmayr 6 hypothesised that ...

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Prognostic Value of EEG Microstates in Acute Stroke

Cited by 76 publications

References 65 publications

Normal Aging: Alterations in Scalp EEG Using Broadband and Band-Resolved Topographic Maps

Normal Aging: Alterations in Scalp EEG Using Broadband and Band-Resolved Topographic Maps

EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review

EEG microstates associated with intra- and inter-subject alpha variability

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