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

Flexible Prescribed-Time Optimal Control With Adaptive State-Input Constraint Bounds via Actor-Critic Learning.

IEEE transactions on neural networks and learning systems·2026
Same author

The contribution of the koniocellular visual pathway to aversive learning in human visual cortex.

Journal of neurophysiology·2026
Same author

Toward Comprehensive Information-Theoretic Multi-View Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

Social anxiety is associated with greater autonomic and visuocortical generalization of conditioned aversive responses to faces.

Cognitive, affective & behavioral neuroscience·2026
Same author

Changes in visuocortical engagement and oscillatory brain activity during associative learning.

Scientific reports·2026
Same author

Multimodal and Hyperspectral Dataset for Segmentation of Bulky Waste using VIS, IR, NIR, and Terahertz Imaging.

Scientific data·2026

Related Experiment Video

Updated: Mar 27, 2026

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy
08:23

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy

Published on: November 13, 2016

11.9K

Long-term scalp epileptic EEG quantification with GMA dynamics.

Hong Ji, Mehrnaz Kh Hazrati, Badong Chen

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |January 7, 2016
    PubMed
    Summary

    This study introduces the generalized measure of association (GMA) for automatic seizure detection using scalp electroencephalography (EEG). GMA effectively quantifies brain region interactions, showing significant changes before and during epileptic seizures.

    More Related Videos

    Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy
    10:22

    Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy

    Published on: December 6, 2016

    21.3K
    Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
    11:25

    Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

    Published on: July 26, 2013

    44.3K

    Related Experiment Videos

    Last Updated: Mar 27, 2026

    A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy
    08:23

    A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy

    Published on: November 13, 2016

    11.9K
    Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy
    10:22

    Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy

    Published on: December 6, 2016

    21.3K
    Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
    11:25

    Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

    Published on: July 26, 2013

    44.3K

    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Signal Processing

    Background:

    • Epileptic seizures present a significant challenge for automatic detection using scalp electroencephalography (EEG).
    • Understanding the complex dynamical interactions between brain regions during seizures is crucial for improving detection algorithms.

    Purpose of the Study:

    • To propose and evaluate the generalized measure of association (GMA) as a novel method for automatic seizure detection.
    • To quantify statistical dependencies and infer dynamical interactions of brain regions using scalp EEG data.

    Main Methods:

    • Employing the generalized measure of association (GMA) to analyze scalp EEG signals.
    • Quantifying statistical dependencies and dynamical interactions between brain regions.
    • Validating the method using clinical EEG recordings from epileptic patients.

    Main Results:

    • GMA values demonstrated dramatic changes preceding and during epileptic seizures.
    • The estimated GMA effectively reflects dynamic coupling and decoupling between brain regions.
    • Significant alterations in GMA indicate potential for seizure detection.

    Conclusions:

    • The generalized measure of association (GMA) is a promising tool for automatic seizure detection in scalp EEG.
    • GMA provides a valuable quantitative measure of epileptic EEG signal dynamics.
    • This approach enhances the understanding of brain region interactions during seizures.