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

The Prognostic Role of C-Reactive Protein-Triglyceride Glucose Index in Predicting Unfavorable Outcomes in Acute Ischemic Stroke: A Large-Scale Cohort Study.

Brain and behavior·2026
Same author

Combined Impact of Abdominal Obesity and Nontraditional Insulin Resistance Indices on Stroke Risk: Evidence from a Nationwide Prospective Cohort Study.

Neuroepidemiology·2026
Same author

DTI-ALPS and subcortical structural-functional coupling mediate the impact of sleep quality on working memory in insomnia disorder.

Psychological medicine·2026
Same author

Characterisation and expression profiles of the NPF gene family in Cannabis sativa L. under low nitrogen.

BMC plant biology·2026
Same author

Association of the TyG Index, Cardiometabolic Index, and Epicardial Adipose Tissue With Coronary Artery Disease.

Clinical cardiology·2026
Same author

Processing-Enhanced β-Phase Formation in BaTiO<sub>3</sub>/PVDF Composite Fibers with High Electroactive Phase Content.

Nanomaterials (Basel, Switzerland)·2026

Related Experiment Video

Updated: Apr 4, 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

12.4K

Incorporating priors for EEG source imaging and connectivity analysis.

Xu Lei1, Taoyu Wu1, Pedro A Valdes-Sosa2

  • 1Sleep and NeuroImaging Center, Faculty of Psychology, Southwest University Chongqing, China ; Key Laboratory of Cognition and Personality, Ministry of Education Chongqing, China.

Frontiers in Neuroscience
|September 9, 2015
PubMed
Summary

Combining electroencephalography source imaging (ESI) with other brain imaging techniques like MRI and fMRI enhances the study of neural circuits. This integration improves the localization of brain activity and network dynamics.

Keywords:
EEG source imagingEEG-fMRIbrain networkmultimodality

More Related Videos

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

3.9K
Neuroimaging-Guided TMS&#8211;EEG for Real-Time Cortical Network Mapping
09:55

Neuroimaging-Guided TMS–EEG for Real-Time Cortical Network Mapping

Published on: June 13, 2025

3.1K

Related Experiment Videos

Last Updated: Apr 4, 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

12.4K
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

3.9K
Neuroimaging-Guided TMS&#8211;EEG for Real-Time Cortical Network Mapping
09:55

Neuroimaging-Guided TMS–EEG for Real-Time Cortical Network Mapping

Published on: June 13, 2025

3.1K

Area of Science:

  • Neuroscience
  • Brain Imaging
  • Computational Neuroscience

Background:

  • Electroencephalography source imaging (ESI) localizes neural generators from scalp measurements.
  • Understanding large-scale neural circuit dynamics is crucial in neuroscience.
  • ESI benefits from incorporating prior information from complementary modalities.

Purpose of the Study:

  • To review and analyze priors from various neuroimaging techniques for ESI.
  • To assess the contribution of different modalities to source reconstruction.
  • To explore the integration of multimodal data for enhanced brain network analysis.

Main Methods:

  • Review of prior information from Magnetic Resonance Imaging (MRI), functional MRI (fMRI), and Positron Emission Tomography (PET).
  • Systematic introduction of spatial priors: EEG-correlated fMRI, temporally coherent networks (TCNs), and resting-state fMRI in ESI.
  • Inclusion of diffusion tensor imaging (DTI) and transcranial magnetic stimulation (TMS) for neuroelectric connectivity inference.

Main Results:

  • Analysis of modality-specific contributions to source reconstruction in ESI.
  • Demonstration of how spatial priors improve the localization of neural sources.
  • Identification of DTI and TMS as potential priors for inferring neuroelectric connectivity.

Conclusions:

  • Integrating complementary modalities with EEG source imaging offers a powerful approach.
  • Multimodal integration enhances the study of brain networks in cognitive and clinical neuroscience.
  • This combined approach promises deeper insights into brain function and dysfunction.