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

Neural representations of visual categories are dynamically tailored to the discrimination required by the task.

Cerebral cortex (New York, N.Y. : 1991)·2025
Same author

Large language models surpass human experts in predicting neuroscience results.

Nature human behaviour·2024
Same author

Competition between emotional faces in visuospatial working memory.

Journal of experimental psychology. Learning, memory, and cognition·2024
Same author

Theta-phase dependent neuronal coding during sequence learning in human single neurons.

Nature communications·2021
Same author

Subitizing object parts reveals a second stage of individuation.

Psychonomic bulletin & review·2020
Same author

A simple rule to describe interactions between visual categories.

The European journal of neuroscience·2020
Same journal

Intrinsic Functional Architecture Reflects Individual Differences in Passive Working Memory: An Exploratory Resting-State fMRI Study.

Human brain mapping·2026
Same journal

Symptom Overlap and Neurobiological Similarities Between Posttraumatic Stress Disorder and Tinnitus.

Human brain mapping·2026
Same journal

Test-Retest Reliability of Sensorimotor Activity Measured With Spinal Cord fMRI.

Human brain mapping·2026
Same journal

The Human Visual Claustrum Responses to Physical Stimulus Properties and Subjective Content During Movie Viewing.

Human brain mapping·2026
Same journal

miniMORPH: A Morphometry Pipeline for Low-Field MRI in Infants.

Human brain mapping·2026
Same journal

Reduced Cerebral Blood Flow in the Early Chronic Phase of Recurrent Concussion Among Female Collegiate-Aged Athletes.

Human brain mapping·2026
See all related articles

Related Experiment Video

Updated: Aug 14, 2025

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

11.8K

Estimating neural activity from visual areas using functionally defined EEG templates.

Marlene Poncet1, Justin M Ales1

  • 1School of Psychology and Neuroscience, University of St Andrews, St Andrews, UK.

Human Brain Mapping
|January 19, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method using EEG topographical templates to pinpoint brain regions responsible for neural activity. This approach enhances spatial resolution for electroencephalography (EEG) data analysis.

Keywords:
electroencephalographyelectrophysiologyfunctional areassource localizationvisual areas

More Related Videos

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks
06:57

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Published on: August 9, 2016

11.5K
Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

14.7K

Related Experiment Videos

Last Updated: Aug 14, 2025

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

11.8K
Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks
06:57

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Published on: August 9, 2016

11.5K
Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

14.7K

Area of Science:

  • Neuroscience
  • Cognitive Science
  • Biomedical Engineering

Background:

  • Electroencephalography (EEG) is a widely used, cost-effective technique for measuring human neural activity.
  • A key limitation of EEG is its poor spatial resolution, hindering the precise localization of brain activity sources.
  • Existing source localization methods can be complex and require individual brain scans.

Purpose of the Study:

  • To develop an accessible and user-friendly method for improving the spatial localization of EEG signals.
  • To create standardized EEG topographical templates based on functional brain regions.
  • To enable accurate estimation of the contribution of specific visual areas to observed EEG activity.

Main Methods:

  • Utilized MRI and fMRI data from 50 participants to simulate scalp activity patterns for each visual area.
  • Averaged simulated signals to generate functionally defined EEG topographical templates.
  • Validated the method through extensive simulations and analysis of real EEG data.

Main Results:

  • The developed method demonstrates comparable performance to individual source localization techniques.
  • The approach is robust across various influencing factors.
  • Results are easily interpretable in terms of functional brain regions and facilitate cross-modal comparisons.

Conclusions:

  • The proposed EEG topographical template method offers an inexpensive, easy-to-use, and expandable solution for enhanced EEG source localization.
  • This technique overcomes the limitations of individual brain scan requirements, making it applicable to diverse EEG datasets.
  • The method provides interpretable results, advancing the understanding of neural activity localization in neuroscience research.