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

Intrathecal Mesenchymal Stem Cells in Progressive Multiple Sclerosis: A Randomized, Double-Blind, Placebo-Controlled Trial (SMART-MS).

Neurology·2026
Same author

Cerebrovascular recovery drives restoration of neurometabolite levels after mild COVID-19.

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism·2026
Same author

Early Predictors of Long-Term Outcomes in Pediatric "Mild" Traumatic Brain Injury: A Machine Learning Approach.

Journal of neurotrauma·2026
Same author

The influence of intermittent hypercapnia on cerebrospinal fluid flow and clearance in Parkinson's disease and healthy older adults.

NPJ Parkinson's disease·2025
Same author

Optimizing pediatric "Mild" traumatic brain injury assessments: A multi-domain random forest analysis of diagnosis and outcomes.

International journal of clinical and health psychology : IJCHP·2025
Same author

Transcranial direct current stimulation treatment reduces, while repetitive transcranial magnetic stimulation treatment increases electroencephalography spike rates with refractory occipital lobe epilepsy: A case study.

Epilepsia open·2025

Related Experiment Video

Updated: May 28, 2026

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
08:36

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

Capturing inter-subject variability with group independent component analysis of fMRI data: a simulation study.

Elena A Allen1, Erik B Erhardt, Yonghua Wei

  • 1The Mind Research Network, Albuquerque, NM, USA. eallen@mrn.org

Neuroimage
|October 25, 2011
PubMed
Summary

Group independent component analysis (GICA) effectively captures individual brain differences in functional neuroimaging. This study validates GICA

More Related Videos

Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels
08:19

Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels

Published on: October 20, 2023

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
09:01

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

Related Experiment Videos

Last Updated: May 28, 2026

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
08:36

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels
08:19

Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels

Published on: October 20, 2023

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
09:01

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

Area of Science:

  • Neuroimaging
  • Functional Magnetic Resonance Imaging (fMRI)
  • Data Analysis

Background:

  • Inter-subject variability in brain activation poses challenges for group-level functional neuroimaging analysis.
  • Average activation patterns may not accurately represent individual neural responses.
  • Group independent component analysis (GICA) is a popular method for multi-subject analysis, especially when temporal models are difficult to specify.

Purpose of the Study:

  • To comprehensively evaluate the performance of GICA under realistic conditions of inter-subject variability.
  • To determine the capabilities and limitations of GICA in analyzing simulated fMRI data with spatial, temporal, and amplitude variability.
  • To address key questions regarding GICA's accuracy in estimating individual activations, the causes of component splitting, and optimal analysis of component features.

Main Methods:

  • Utilized simulated fMRI data generated with the SimTB toolbox.
  • Investigated GICA's performance across varying degrees of spatial, temporal, and amplitude variability.
  • Examined factors influencing component estimation, splitting, and feature analysis.

Main Results:

  • GICA demonstrated excellent capability in capturing between-subject differences in neural activation patterns.
  • Identified conditions under which spatial variability may preclude accurate estimation of individual subject activations.
  • Provided insights into the relationship between model order and component splitting in GICA.

Conclusions:

  • GICA is a powerful tool for analyzing inter-subject variability in functional neuroimaging.
  • Recommendations are provided for optimizing analytic choices in GICA applications.
  • The study enhances understanding of GICA's strengths and limitations in real-world neuroimaging research.