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

[Kinase-Glo luminescent kinase assay for in vitro determination of PKA activity].

Xi bao yu fen zi mian yi xue za zhi = Chinese journal of cellular and molecular immunology·2012
Same author

Functional characterization of an arrestin gene on insecticide resistance of Culex pipiens pallens.

Parasites & vectors·2012
Same author

MiR-23a inhibits myogenic differentiation through down regulation of fast myosin heavy chain isoforms.

Experimental cell research·2012
Same author

Let-7b inhibits human cancer phenotype by targeting cytochrome P450 epoxygenase 2J2.

PloS one·2012
Same author

Role of IKK/NF-κB signaling in extinction of conditioned place aversion memory in rats.

PloS one·2012
Same author

Inhibition of poly(ADP-ribose) polymerase attenuates acute kidney injury in sodium taurocholate-induced acute pancreatitis in rats.

Pancreas·2012

Related Experiment Video

Updated: Jan 18, 2026

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

10.7K

Resting-State EEG Functional Connectivity for Brain Function Analysis and Severity Classification in Obstructive

Minghui Liu, Ligang Zhou, Yalin Wang

    IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
    |September 9, 2025
    PubMed
    Summary
    This summary is machine-generated.

    Obstructive sleep apnea (OSA) alters brain function, with resting-state EEG revealing changes in functional connectivity (FC) that correlate with OSA severity. This non-invasive method accurately classifies OSA severity using machine learning.

    More Related Videos

    Resting-State Connectivity and Neuroimaging of Prefrontal Cortex Activity During a Block-Design Yoga Asana Practice Using fNIRS
    07:56

    Resting-State Connectivity and Neuroimaging of Prefrontal Cortex Activity During a Block-Design Yoga Asana Practice Using fNIRS

    Published on: June 24, 2025

    793
    Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy
    07:13

    Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy

    Published on: May 27, 2020

    7.1K

    Related Experiment Videos

    Last Updated: Jan 18, 2026

    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

    10.7K
    Resting-State Connectivity and Neuroimaging of Prefrontal Cortex Activity During a Block-Design Yoga Asana Practice Using fNIRS
    07:56

    Resting-State Connectivity and Neuroimaging of Prefrontal Cortex Activity During a Block-Design Yoga Asana Practice Using fNIRS

    Published on: June 24, 2025

    793
    Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy
    07:13

    Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy

    Published on: May 27, 2020

    7.1K

    Area of Science:

    • Neuroscience
    • Sleep Medicine
    • Biomedical Engineering

    Background:

    • Obstructive sleep apnea (OSA) is a prevalent sleep disorder globally, significantly impacting brain function.
    • Resting-state electroencephalography (EEG) offers a feasible, cost-effective, and high-temporal-resolution method for investigating brain activity.
    • Understanding OSA's neurological effects is crucial for developing effective diagnostic and therapeutic strategies.

    Purpose of the Study:

    • To investigate alterations in resting-state EEG functional connectivity (FC) in relation to OSA severity.
    • To explore the potential of FC metrics as biomarkers for OSA severity classification.
    • To develop and validate machine learning models for OSA severity prediction using EEG-derived features.

    Main Methods:

    • A large cohort of 968 participants underwent overnight polysomnography (PSG) and 15-minute resting-state EEG acquisition.
    • Participants were classified into healthy controls and mild, moderate, and severe OSA groups based on the apnea-hypopnea index (AHI).
    • Resting-state EEG FC was computed using correlation, coherence, PLV, and PLI, followed by graph-theoretical analysis and multivariate feature selection for machine learning models.

    Main Results:

    • Increased FC was observed with higher OSA severity, suggesting neural compensation, alongside regional decreases in specific brain areas.
    • Graph-theoretical analysis indicated reduced centrality and topological reorganization in the brain networks of OSA patients.
    • Machine learning models, particularly a Corr-based XGBoost model, achieved high accuracy (0.79) and AUC (0.90) in classifying OSA severity using selected FC features.

    Conclusions:

    • Resting-state EEG FC reveals significant alterations in brain function associated with OSA severity.
    • EEG-derived FC metrics serve as a promising non-invasive, task-free, and interpretable tool for OSA severity classification.
    • This approach facilitates accurate OSA severity assessment without interfering with natural sleep patterns.