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 Experiment Videos

Assessment criteria for MEG/EEG cortical patch tests.

Chang-Hwan Im1, Kwang-Ok An, Hyun-Kyo Jung

  • 1ENG420-040, School of Electrical Engineering, Seoul National University, Shillim-dong, Kwanak-gu, Seoul 151-742, Korea. ichism@elecmech.snu.ac.kr

Physics in Medicine and Biology
|September 5, 2003
PubMed
Summary

Researchers developed new criteria to quantitatively assess magnetoencephalography/electroencephalography (MEG/EEG) source localization techniques. These criteria offer a reliable index for validating methods using simulated cortical source models.

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

Melanopic equivalent daylight illuminance of 2 lx maintains and restores physiological and neurophysiological circadian rhythms in rats.

Scientific reports·2026
Same author

Assessment of urban tree effectiveness for submicron soot aerosols reduction through combined deposition and resuspension experiments.

Environmental pollution (Barking, Essex : 1987)·2026
Same author

SleepPACNet: new convolutional neural network considering phase-amplitude coupling for automatic sleep stage classification using single-channel electroencephalogram.

Scientific reports·2026
Same author

Prediction of treatment responsiveness to home-based transcranial photobiomodulation (tPBM) intervention for cognitive decline using fNIRS concurrently recorded during tPBM.

Frontiers in aging neuroscience·2026
Same author

Altered resting-state sensorimotor network in patients with obsessive-compulsive disorder: An EEG study.

Journal of affective disorders·2026
Same author

Functional near-infrared spectroscopy-based computer-aided diagnosis of major depressive disorder using explainable artificial intelligence: Comparison with conventional machine learning.

Journal of affective disorders·2025

Area of Science:

  • Neuroscience
  • Biophysics
  • Medical Imaging

Background:

  • Magnetoencephalography/electroencephalography (MEG/EEG) source localization is crucial for understanding brain activity.
  • Current validation methods like phantom experiments or artificial data sets have limitations.
  • Artificial data sets generated via forward calculation are preferred for their simplicity and control.

Purpose of the Study:

  • To propose novel quantitative assessment criteria for MEG/EEG source localization techniques.
  • To address the lack of established criteria for validating reconstructed results, especially for cortically distributed source models.
  • To provide a reliable method for comparing and validating different MEG/EEG source localization approaches.

Main Methods:

  • Development of four distinct assessment criteria.

Related Experiment Videos

  • Criteria designed to measure accuracy, focalization, noise-robustness, and spurious sources.
  • Validation using simulated data with cortically distributed source models under varying noise conditions and reconstruction techniques.

    • Main Results:

    • The proposed criteria provide a reliable index for validating MEG/EEG source localization techniques.
    • Demonstrated the utility of the criteria by comparing four different reconstruction results.
    • Effectively evaluated performance across different noise levels and source modeling approaches.

    Conclusions:

    • The newly proposed criteria offer a robust framework for quantitatively validating MEG/EEG source localization methods.
    • These criteria are particularly useful for evaluating techniques applied to cortically distributed source models.
    • Facilitates more rigorous and objective comparison of different source localization software and algorithms.