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

Brain source localization using a fourth-order deflation scheme.

Laurent Albera1, Anne Ferréol, Delphine Cosandier-Rimélé

  • 1INSERM, U642, Rennes, F-3500, France. laurent.albera@univ-rennes1.fr

IEEE Transactions on Bio-Medical Engineering
|February 14, 2008
PubMed
Summary
This summary is machine-generated.

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

Personalized whole-brain models of seizure propagation.

Journal of neural engineering·2025
Same author

Robust graph-based denoising for cardiac acceleration signals.

Computers in biology and medicine·2025
Same author

Deep learning on high-density EEG during a cognitive task distinguishes patients with Parkinson's disease from healthy controls.

Journal of neural engineering·2025
Same author

Realistic Subject-Specific Simulation of Resting State Scalp EEG Based on Physiological Model.

Brain topography·2025
Same author

Personalized multichannel transcranial direct current electrical stimulation (tDCS) in drug-resistant epilepsy: A SEEG based open-labeled study.

Epilepsia open·2025
Same author

Auditory evoked delta brushes involve stimulus-specific cortical networks in preterm infants.

iScience·2025
Same journal

Magnetic Resonance Spectroscopy Deep Learning with Magnetic Resonance Background Generator Enables In Vivo Metabolite Quantification of Hepatic Encephalopathy.

IEEE transactions on bio-medical engineering·2026
Same journal

Use of RPNIs and Implanted Electrodes for Prosthetic Wrist and Multi-Grip Hand Control during Functional Tasks: A Case Study.

IEEE transactions on bio-medical engineering·2026
Same journal

Healthy Limb Driven Prediction for Real Time Control of Unilateral Exoskeletons in Gait Rehabilitation.

IEEE transactions on bio-medical engineering·2026
Same journal

A Miniature Wearable Ultrasound System for Continuous Bladder Monitoring with Sleeping-Position-Robust Modeling Strategies.

IEEE transactions on bio-medical engineering·2026
Same journal

A Bi-objective Array Optimization Framework for Magnetocardiographic Source Imaging.

IEEE transactions on bio-medical engineering·2026
Same journal

A Dynamic Mutual Information Measure of Phase-Amplitude Coupling with Uncertainty Quantification.

IEEE transactions on bio-medical engineering·2026
See all related articles

A new method, FO-D-MUSIC, precisely pinpoints brain current sources from EEG/MEG data. This advanced technique improves localization accuracy for challenging scenarios, outperforming traditional algorithms.

Area of Science:

  • Neuroscience
  • Biophysics
  • Signal Processing

Background:

  • Inverse problems in neuroimaging are often ill-posed, challenging accurate localization of brain activity.
  • Electroencephalography (EEG) and magnetoencephalography (MEG) are crucial for non-invasively measuring brain function.
  • Existing methods struggle with unconstrained source orientations and complex head geometries.

Purpose of the Study:

  • To introduce a high-resolution method, FO-D-MUSIC, for solving inverse problems in EEG/MEG data.
  • To enable precise localization of brain current sources with unconstrained orientations.
  • To validate the method's performance across various challenging conditions.

Main Methods:

  • The FO-D-MUSIC method leverages the separability of the data transfer matrix.

Related Experiment Videos

  • It incorporates fourth-order (FO) virtual array theory.
  • A deflation concept extended to FO statistics handles statistically dependent sources.

    • Main Results:

    • Computer simulations demonstrate the superiority of FO-D-MUSIC.
    • The method excels in localizing closely spaced sources.
    • It performs well with limited electrode counts and noisy data.

    Conclusions:

    • FO-D-MUSIC offers a significant advancement in localizing brain current sources.
    • The method provides high-resolution and accurate results for EEG/MEG data.
    • It outperforms classical algorithms in complex and challenging neuroimaging scenarios.