Spatiotemporal dynamics of EEG microstates in four- to eight-year-old children: Age- and sex-related effects

Bagdasarov, A.A.; Roberts, Kenneth; Bréchet, Lucie; Brunet, Denis; Michel, Christoph M.; Gaffrey, Michael S.

doi:10.1016/j.dcn.2022.101134

Cited by 25 publications

(42 citation statements)

References 60 publications

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“…In schizophrenia research, parameters of microstate A and D were found to be significantly altered in younger patient groups ( 52 ). Furthermore, in both NT and TD populations, studies have reported significant developmental effect of age and sex over microstate parameters ( 12 , 53 , 54 ). It is worth noting that the ages of participants in Bochet et al ( 43 ) did not vary as much in comparison to all the studies combined (see Table 1 ).…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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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.

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Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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“…The microstate method has also been demonstrated its practicability in 4–8-year-old children. 30 In terms of computation time, our approach is also very reasonable. The correlation values between IEDs and SMS are similar and equally high with or without marking and separating IEDs from the rest of the EEG.…”

Section: Discussionmentioning

confidence: 80%

Spike-microstates correlate with interictal epileptogenic discharges: a marker for hidden epileptic activity

Rochas

Gschwind

Nedeltchev

et al. 2023

Brain Communications

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Objectively estimating disease severity and treatment success is a main problem in outpatient managing of epilepsy. Self-reported seizures diaries are well-known to underestimate the actual seizure count, and repeated EEGs might not show interictal epileptiform discharges (IEDs), although patients suffer from seizures. In this prospective study we investigate the potential of microstate analysis to monitor epilepsy patients independently of their IED count. From our databank of candidates for epilepsy surgery we included 18 patients who underwent controlled resting EEG sessions (with eyes closed, 30 min), at around the same time of the day, during at least 4 days (range: 4-8 days; mean: 5). Nine patients with temporal foci, six with extratemporal foci, three with generalized epilepsy were included. Each patient’s IEDs were marked and the topographic voltage maps of the IED peaks were averaged, and an individual average spike-topography (AST) was created. The AST was then backfitted to each timepoint of the whole EEG resulting in the Spike-Microstate (SMS). The presence of the SMS in the residual EEG outside of the short IEDs epochs was determined for each recording session in each patient and correlated with the occurrence of the IEDs across all recording session, as well as with the drug charge of each day. Overall, SMS was much more represented in the routine EEG than the IEDs: they were identified 262 times more often than IEDs. The SMS time coverage correlated significantly with the IED occurrence rate (rho = 0.56; p< 0.001). If only patients with focal epilepsy were considered, this correlation was even higher rho = 0.69 (p < 0.001). Drug charge per day did not correlate with SMS. In this proof-of-concept study, the time coverage of SMS correlated strongly with the occurrence rate of the IEDs, they can be retrieved in the scalp EEG at a much higher occurrence rate. We conclude that SMS, once obtained for a given patient, are a more abundant marker of hidden epileptic activity than IEDs, in particular in focal epilepsy, and can be used also in absence of IEDs. Future larger studies are needed to verify its potential as monitoring tool and to determine cut-off values when drug protection becomes imperfect.

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“…The resampling approach is thought to improve the reliability of k-means clustering and has been used in recent work (Bagdasarov et al, 2022(Bagdasarov et al, , 2023Férat et al, 2022). The meta-criterion -an aggregate measure of seven independent criteria (Bréchet et al, 2019;Custo et al, 2017) -determined the optimal number of clusters for each epoch, resulting in k optimal clusters for each of 50 epochs or k*50 topographies for each participant.…”

Section: Stage 1: Individual-level Clusteringmentioning

confidence: 99%

“…The amplitude of activity produced at each solution point was saved as a scalar, positive value and averaged across time points for each microstate. Inverse solutions were combined across participants and thresholded to the solution points above the 95th percentile of values as done in previous work (Bagdasarov et al, 2022;Bréchet et al, 2020Bréchet et al, , 2021. The nal product was a thresholded, group-level source distribution for each microstate.…”

Section: Stage 4: Source Localizationmentioning

confidence: 99%

Microstate Analysis of Infant EEG: Tutorial and Reliability

Bagdasarov

Brunet

Michel

et al. 2023

Preprint

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Microstate analysis of resting-state EEG is a unique data-driven method for identifying patterns of scalp potential topographies, or microstates, that reflect stable but transient periods of synchronized neural activity evolving dynamically over time. During infancy – a critical period of rapid brain development and brain plasticity – microstate analysis offers a unique opportunity for characterizing the spatial and temporal dynamics of brain activity. However, whether measurements derived from this approach (e.g., temporal properties, transition probabilities, neural sources) show strong psychometric properties (i.e., reliability) during infancy is unknown and key information for advancing our understanding of how microstates are shaped by early life experiences and whether they relate to individual differences in infant abilities. A lack of methodological resources for performing microstate analysis of infant EEG has further hindered adoption of this cutting-edge approach by infant researchers. As a result, in the current study, we systematically addressed these knowledge gaps and report that all microstate-based measurements of brain organization and functioning except for transition probabilities were highly stable and reliable with as little as 2–3 minutes of video-watching resting-state data and provide a step-by-step tutorial, accompanying website, and open-access data for performing microstate analysis using a free, user-friendly software called Cartool. Taken together, the current study supports the reliability and feasibility of using EEG microstate analysis to study infant brain development and increases the accessibility of this approach for the field of developmental neuroscience.

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Spatiotemporal dynamics of EEG microstates in four- to eight-year-old children: Age- and sex-related effects

Cited by 25 publications

References 60 publications

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

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

Spike-microstates correlate with interictal epileptogenic discharges: a marker for hidden epileptic activity

Microstate Analysis of Infant EEG: Tutorial and Reliability

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