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

Stable EEG source estimation for standardized Kalman filter using rate-of-change tracking.

Computer methods and programs in biomedicine·2026
Same author

Standardized Kalman filtering for dynamical source localization of concurrent subcortical and cortical brain activity.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2024
Same author

Guanylate-binding protein 1 acts as a pro-viral factor for the life cycle of hepatitis C virus.

PLoS pathogens·2024
Same author

Standardized hierarchical adaptive Lp regression for noise robust focal epilepsy source reconstructions.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2024
Same author

Pressure-Poisson equation in numerical simulation of cerebral arterial circulation and its effect on the electrical conductivity of the brain.

Computer methods and programs in biomedicine·2023
Same author

Multi-compartment head modeling in EEG: Unstructured boundary-fitted tetra meshing with subcortical structures.

PloS one·2023

Related Experiment Video

Updated: Jan 14, 2026

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

12.2K

Enhanced Localization and Orientation Estimations in Focal EEG Source Imaging Using SVD-Based Coordinate Transform.

Joonas Lahtinen1, Alexandra Koulouri2,3

  • 1Faculty of Information Technology and Communication Sciences, Tampere University, Korkeakoulunkatu 3, Tampere, 33014, Finland. joonas.j.lahtinen@tuni.fi.

Brain Topography
|October 22, 2025
PubMed
Summary

This study enhances electroencephalography (EEG) source imaging by using Singular Value Decomposition (SVD) with Hierarchical Adaptive L1-Regression (HAL1R). The new method improves neural source localization and orientation accuracy for better brain activity mapping.

Keywords:
Adaptive LassoAdaptive group LassoEEGSVDSource imagingSparsity constraints

More Related Videos

Detecting Pre-Stimulus Source-Level Effects on Object Perception with Magnetoencephalography
09:25

Detecting Pre-Stimulus Source-Level Effects on Object Perception with Magnetoencephalography

Published on: July 26, 2019

7.3K
Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization
09:57

Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization

Published on: September 20, 2024

3.4K

Related Experiment Videos

Last Updated: Jan 14, 2026

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

12.2K
Detecting Pre-Stimulus Source-Level Effects on Object Perception with Magnetoencephalography
09:25

Detecting Pre-Stimulus Source-Level Effects on Object Perception with Magnetoencephalography

Published on: July 26, 2019

7.3K
Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization
09:57

Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization

Published on: September 20, 2024

3.4K

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Accurate neural source localization and orientation are critical for electroencephalography (EEG) source imaging, especially for focal brain activities.
  • Existing methods may suffer from orientation biases and limited stability in complex scenarios.

Purpose of the Study:

  • To introduce an enhanced EEG source imaging method by integrating a Singular Value Decomposition (SVD)-based coordinate transform into Hierarchical Adaptive L1-Regression (HAL1R).
  • To improve the accuracy and stability of neural source localization and orientation estimation.

Main Methods:

  • Applied SVD transform to lead field matrix columns for physiologically meaningful orientation bases.
  • Incorporated sparsity enforcement into these bases to mitigate orientation biases.
  • Validated the approach using numerical simulations and somatosensory evoked potential (SEP) data.

Main Results:

  • The SVD-based HAL1R demonstrated improved localization stability and orientation accuracy compared to conventional methods like Adaptive Group LASSO, UNG Beamformer, and Dipole Scanning.
  • Physiologically meaningful orientation bases derived from SVD align better with brain properties.

Conclusions:

  • The SVD-based HAL1R framework offers a robust and generalizable methodology for EEG source imaging.
  • This enhanced approach improves accuracy and utility in clinical and research applications, including pre-surgical planning and cortical mapping.