ArticleBrain topography2021
EEG Microstates Predict Concurrent fMRI Dynamic Functional Connectivity States.
Article in Brain topography, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.
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Who cites it
32 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Functional Aspects of Resting EEG Microstates: A Systematic Review.Brain topography · 2024Pooled it
- EEG Microstates in Early Phase Psychosis: The Effects of Acute Caffeine Consumption.Clinical EEG and neuroscience · 2022Trial
- Salience Network Dynamics Across Spontaneous Attacks, Interictal Rest and Interictal Pain Imagery in Menstrually Related Migraine.Brain topography · 2026Article
- Effects of Social Media Use on Brain Dynamics in Young Male Adults: Multistage Concurrent Electroencephalography-Functional Magnetic Resonance Imaging Study.JMIR medical informatics · 2026Article
- Excessive Use of Short Video Modulates the Temporal Dynamics of Resting-State Electroencephalography Networks.Brain topography · 2026Article
- EEG microstate alterations in Parkinson's disease dementia.Scientific reports · 2026Article
- Altered resting state EEG microstate dynamics in acute concussion in adolescents.Scientific reports · 2026Article
- A multiplex of connectome trajectories enables several connectivity patterns in parallel.eLife · 2025Article
- EEG microstate syntax analysis: A review of methodological challenges and advances.NeuroImage · 2025Review
- A Machine-Learning-Based Analysis of Resting State Electroencephalogram Signals to Identify Latent Schizotypal and Bipolar Development in Healthy University Students.Diagnostics (Basel, Switzerland) · 2025Article
- Topology Assisted Clustering of Temporal fMRI Brain Networks With Use-Case in Mitigating Non-Neural Multi-Site Variability.IEEE access : practical innovations, open solutions · 2025Article
- Effects of Short Naps on EEG Microstates: Improving Sleep Deprivation-Induced Cognitive Impairment.Nature and science of sleep · 2025Article
- Consistency of resting-state correlations between fMRI networks and EEG band power.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Dynamical models reveal anatomically reliable attractor landscapes embedded in resting-state brain networks.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Analysis of the microstates of prolonged disorders of consciousness.Frontiers in neurology · 2025Article
- Trait Aggression is Reflected by a Lower Temporal Stability of EEG Resting Networks.Brain topography · 2024Article
- EEG Microstates as a Signature of Hemispheric Lateralization in Stroke.Brain topography · 2024Article
- EEG Microstates as Markers for Cognitive Impairments in Fragile X Syndrome.Brain topography · 2024Article
- State-transition dynamics of resting-state functional magnetic resonance imaging data: model comparison and test-to-retest analysis.BMC neuroscience · 2024Article
- Frequency Analysis of EEG Microstate Sequences in Wakefulness and NREM Sleep.Brain topography · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Brain functional connectivity measured by resting-state fMRI varies over multiple time scales, and recurrent dynamic functional connectivity (dFC) states have been identified. These have been found to be associated with different cognitive and pathological states, with potential as disease biomarkers, but their neuronal underpinnings remain a matter of debate. A number of recurrent microstates have also been identified in resting-state EEG studies, which are thought to represent the quasi-simultaneous activity of large-scale functional networks reflecting time-varying brain states. Here, we hypothesized that fMRI-derived dFC states may be associated with these EEG microstates. To test this hypothesis, we quantitatively assessed the ability of EEG microstates to predict concurrent fMRI dFC states in simultaneous EEG-fMRI data collected from healthy subjects at rest. By training a random forests classifier, we found that the four canonical EEG microstates predicted fMRI dFC states with an accuracy of 90%, clearly outperforming alternative EEG features such as spectral power. Our results indicate that EEG microstates analysis yields robust signatures of fMRI dFC states, providing evidence of the electrophysiological underpinnings of dFC while also further supporting that EEG microstates reflect the dynamics of large-scale brain networks.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.