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Resting-State EEG Microstate Dynamics as Neurophysiological Biomarkers Across the Alzheimer’s Disease Continuum: A Systematic Review

Sep 2026 · Diagnostics · Vol 16 · 0 citations · 66 references
Medicine

TL;DR

Electroencephalography microstates, brief periods of quasi-stable large-scale neural synchrony, have emerged as candidate markers of resting-state network disruption and show graded group-level differences across clinically defined SCD, MCI, and AD dementia samples.

Abstract

Background/Objectives: Alzheimer’s disease (AD) is preceded by clinically defined syndromes of subjective cognitive decline (SCD) and mild cognitive impairment (MCI), which are etiologically heterogeneous and belong to the AD continuum only when amyloid and tau pathology is biologically confirmed. Electroencephalography (EEG) microstates, brief periods of quasi-stable large-scale neural synchrony, have emerged as candidate markers of resting-state network disruption. This systematic review evaluated EEG microstate differences across clinically defined SCD, MCI, and AD dementia samples and the extent to which these have been related to amyloid/tau/neurodegeneration (AT(N)) biomarkers. Methods: PubMed/MEDLINE and EMBASE were searched (January 1990 to June 2026) on 30 June 2026 following preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 guidelines, with an expanded search of Scopus, IEEE Xplore, Web of Science, PROSPERO, ClinicalTrials.gov, and WHO International Clinical Trials Registry Platform (searched 5 August 2026). Twenty-six primary studies met the eligibility criteria and were synthesized narratively. Two recently published meta-analyses identified by the same search were not counted among the included studies; they were appraised using AMSTAR 2 and used only to benchmark the primary-study synthesis, avoiding double counting of overlapping datasets. Methodological quality was appraised using the Newcastle–Ottawa Scale adapted for cross-sectional studies. Results: A graded pattern of microstate differences was identified across diagnostic groups. Microstate A duration and coverage were significantly increased at both the MCI and AD dementia stages. Microstate D duration, occurrence, and coverage were reduced at the MCI stage in the pooled contextual estimates, although only two independent primary samples contributed a microstate D contrast at this stage, whereas only microstate D occurrence was significantly reduced at the AD dementia stage. Microstate C occurrence was significantly reduced at the AD dementia stage in the pooled contextual estimate, but no individual primary sample showed a significant reduction and two of six reported an increase, so the pooled and primary-study evidence diverge for this parameter. Reductions in microstate C at the SCD stage were reported by a single primary study and were associated with cerebrospinal fluid amyloid-β pathology. The direction of effect was not uniform across primary studies at any stage, and the number of independent samples contributing to each comparison ranged from none to six. Methodological heterogeneity limited direct cross-study comparability. Conclusions: Resting-state EEG microstate parameters show graded group-level differences across clinically defined SCD, MCI, and AD dementia samples. Because the evidence base is predominantly cross-sectional and only four of the 26 studies confirmed underlying AD pathology biologically, these findings should be interpreted as preliminary group-level neurophysiological correlates rather than as established diagnostic biomarkers or as evidence of early-detection or clinical-staging utility. Longitudinal cohorts and diagnostic-accuracy studies in AT(N)-stratified samples are required before any clinical application can be considered.

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