Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Electroencephalography Microstate Instability and Clinical Outcomes in Individuals at Clinical High Risk of Psychosis.

JAMA psychiatry·2026
Same author

Mobile alcohol-specific inhibition training in adolescents and young adults with alcohol use disorder: study protocol for a randomized controlled feasibility trial.

Frontiers in psychology·2026
Same author

EEG microstates reveal distinct network dynamics in lucid and non-lucid REM sleep.

Consciousness and cognition·2026
Same author

EEG Microstate Correlates of Emotional Processing in Patients with Alcohol use Disorder and Healthy Controls: An Exploratory Resting-EEG Study.

Brain topography·2026
Same author

VitalCSI: Contactless Respiratory Rate Estimation Using Consumer-Grade Wi-Fi Channel State Information.

Sensors (Basel, Switzerland)·2026
Same author

Cognitive adaptations for memory deficits in MCI and AD patients: A meta-analysis of EEG microstates.

NeuroImage. Clinical·2026
Same journal

Diffusion-Informed Joint Segmentation Enhances Detection of Thalamic Atrophy in Parkinson's Disease.

Brain topography·2026
Same journal

Local Field Potential Recordings Using Deep Brain Stimulation: A Practical Workflow and Open-Source Signal Processing Pipeline.

Brain topography·2026
Same journal

Electrocortical Indices of Default Mode Network-Related Activity in ADHD and Modulation Through Mindfulness-Based Cognitive Therapy.

Brain topography·2026
Same journal

Electroencephalogram for the Diagnosis of Depression: A Systematic Review and Meta-Analysis of Diagnostic Test Accuracy.

Brain topography·2026
Same journal

Mapping Whole-Brain Nonlinear Structure-Function Dynamics in Aging via Neural Granger Causality.

Brain topography·2026
Same journal

Association Between Spatiotemporal Properties of Global Brain Activity and Childhood Emotional and Behavioral Problems: Evidence from Microstate C.

Brain topography·2026
See all related articles

Related Experiment Video

Updated: Dec 1, 2025

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
11:28

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Published on: June 30, 2018

12.0K

EEG Microstates Predict Concurrent fMRI Dynamic Functional Connectivity States.

Rodolfo Abreu1,2, João Jorge3,4, Alberto Leal5

  • 1ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal.

Brain Topography
|November 8, 2020
PubMed
Summary
This summary is machine-generated.

Electroencephalography (EEG) microstates accurately predict dynamic functional connectivity (dFC) states derived from functional MRI (fMRI). This finding links EEG microstates to brain network dynamics, offering insights into the electrophysiological basis of brain states.

Keywords:
EEG microstatesRandom forestsSimultaneous EEG-fMRIfMRI dynamic functional connectivity

More Related Videos

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
06:40

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography

Published on: June 15, 2018

10.5K
Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
08:36

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

7.5K

Related Experiment Videos

Last Updated: Dec 1, 2025

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
11:28

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Published on: June 30, 2018

12.0K
Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
06:40

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography

Published on: June 15, 2018

10.5K
Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
08:36

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

7.5K

Area of Science:

  • Neuroscience
  • Cognitive Neuroscience
  • Brain Imaging

Background:

  • Resting-state functional MRI (fMRI) reveals dynamic functional connectivity (dFC) states that vary over time.
  • These dFC states are linked to cognitive and pathological conditions but their neuronal basis is debated.
  • Resting-state EEG studies identify recurrent microstates thought to reflect large-scale network activity.

Purpose of the Study:

  • To investigate the relationship between EEG microstates and fMRI-derived dFC states.
  • To determine if EEG microstates can predict concurrent fMRI dFC states.

Main Methods:

  • Simultaneous EEG-fMRI data from healthy subjects at rest were analyzed.
  • A random forests classifier was trained to predict fMRI dFC states using EEG microstates.
  • Performance was compared against alternative EEG features like spectral power.

Main Results:

  • EEG microstates accurately predicted concurrent fMRI dFC states with 90% accuracy.
  • EEG microstates significantly outperformed spectral power in predicting dFC states.
  • This demonstrates a strong association between EEG microstates and fMRI dFC states.

Conclusions:

  • EEG microstates provide robust electrophysiological signatures of fMRI dFC states.
  • The study provides evidence for the neuronal underpinnings of dynamic functional connectivity.
  • EEG microstates reflect the temporal dynamics of large-scale brain networks.