On the Reliability of the EEG Microstate Approach

Abstract

EEG microstates represent functional brain networks observable in resting EEG recordings that remain stable for 40–120ms before rapidly switching into another network. It is assumed that microstate characteristics (i.e., durations, occurrences, percentage coverage, and transitions) may serve as neural markers of mental and neurological disorders and psychosocial traits. However, robust data on their retest-reliability are needed to provide the basis for this assumption. Furthermore, researchers currently use different methodological approaches that need to be compared regarding their consistency and suitability to produce reliable results. Based on an extensive dataset largely representative of western societies (2 days with two resting EEG measures each; day one: n = 583; day two: n = 542) we found good to excellent short-term retest-reliability of microstate durations, occurrences, and coverages (average ICCs = 0.874-0.920). There was good overall long-term retest-reliability of these microstate characteristics (average ICCs = 0.671-0.852), even when the interval between measures was longer than half a year, supporting the longstanding notion that microstate durations, occurrences, and coverages represent stable neural traits. Findings were robust across different EEG systems (64 vs. 30 electrodes), recording lengths (3 vs. 2 min), and cognitive states (before vs. after experiment). However, we found poor retest-reliability of transitions. There was good to excellent consistency of microstate characteristics across clustering procedures (except for transitions), and both procedures produced reliable results. Grand-mean fitting yielded more reliable results compared to individual fitting. Overall, these findings provide robust evidence for the reliability of the microstate approach.

Microstate Analysis of Infant EEG: Tutorial and Reliability

“…Antonova et al, 2022). The same study also indicated that compared to temporal properties, transition probabilities show much lower test-retest reliability (most ICCs falling below 0.7; Antonova et al, 2022), as did another study (most ICCs falling below 0.5;Kleinert et al, 2023); though neither study assessed internal consistency. Another hypothesis is that the infant brain does not have well-developed rules that govern intrinsic brain activity.…”

“…First, we did not have data from multiple sessions to assess the test-retest reliability of microstates. While previous work demonstrated adequate to excellent short-and long-term test-retest reliability of microstate measures over multiple sessions in adults (Antonova et al, 2022;Khanna et al, 2014;Kleinert et al, 2023;Liu et al, 2020;Popov et al, 2023), future work will need to directly assess this in infants. Second, while EEG data was collected during video-watching to reduce movement-related artifacts, it is not clear whether videos impacted microstate measures.…”

Electroencephalography microstates highlight specific mindfulness traits

“…Accordingly, microstate temporal dynamics are assumed to provide a window into the higher-order integration processes at the brain scale level (Michel & Koenig, 2018). Moreover, recent studies have shown that microstate dynamics showed good long-term retest-reliability over time (Kleinert et al, 2023) and might have some heritability (da Cruz et al, 2020), supporting the notion that they also represent stable mental traits. In this line, they were investigated in a wide range of studies from state to trait brain processes, such as states of alertness (Brodbeck et al, 2012;Comsa et al, 2019;Zanesco, Denkova, & Jha, 2021), spontaneous phenomenal experiences (Lehmann et al, 2010;Pipinis et al, 2017), self-generated cognition (Bréchet et al, 2019;Milz et al, 2016;Seitzman et al, 2017), personality traits (Kleinert et al, 2022;Schiller et al, 2020;Zanesco et al, 2020) or psychiatric disorders (Damborsk a et al, 2019;Grieder et al, 2016;Rieger et al, 2016).…”

Topographical polarity reveals continuous EEG microstate transitions and electric field direction in healthy aging

“…One method for capturing the global spatiotemporal dynamics of whole-brain EEG is EEG microstate analysis (Khanna et al, 2015; Michel & Koenig, 2018). EEG microstates are spatial patterns of scalp potential topographies that transition metastably within a time frame of approximately 40–120 milliseconds (Kleinert et al, 2024; Michel & Koenig, 2018). They reflect the large-scale neural dynamics of brain networks predominant in scalp EEG (Zanesco et al, 2020).…”

“…They highlighted the low test-retest reliability of EEG microstate measures, particularly among older individuals. While the stability and reliability of EEG microstate indices remain subjects of debate (Antonova et al, 2022; Khanna et al, 2014; Kleinert et al, 2024; Liu et al, 2020; Popov et al, 2023; Zanesco et al, 2020), indices that focus on temporal transitions between states, such as state transition matrices, might be informative, especially for describing continuous trajectories.…”