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

Cross-subject decoding of internal mental states using predictive time-series modeling.

Science bulletin·2026
Same author

Age-dependent acceleration of structural brain aging in medication-free major depressive disorder linked to neuroanatomical phenotype findings from COORDINATE-MDD consortium.

medRxiv : the preprint server for health sciences·2026
Same author

Aberrant dynamic functional architecture in major depressive disorder: Vertex-Wise large-sample fMRI analyses reveal network-specific alterations and symptom associations.

Translational psychiatry·2026
Same author

Transfer learning from 2D natural images to 4D fMRI brain images via geometric mapping.

Medical image analysis·2026
Same author

Brain plasticity underlying acquisition of new organizational skills in children: A Rashomon analysis.

Frontiers in neuroimaging·2025
Same author

Shared but distinct functional connectome profiles underlying rumination in depressed and healthy individuals.

BMC psychiatry·2025
Same journal

Pupil-DLC: an open-source deep learning pipeline for scalable, marker-less tracking of pupil dynamics across conscious and unconscious states.

Journal of neuroscience methods·2026
Same journal

Time as the language of Behavior: events, sequences, patterns and meanings.

Journal of neuroscience methods·2026
Same journal

Detection of cochlear microphonic for differential diagnosis between auditory neuropathy mice and noise-induced sensorineural hearing loss mice.

Journal of neuroscience methods·2026
Same journal

Assessment metrics for pain control in rats: A methodological commentary.

Journal of neuroscience methods·2026
Same journal

Infant EEG preprocessing pipelines: A capability framework and current gaps in practice.

Journal of neuroscience methods·2026
Same journal

Methods for measuring neural activity during voluntary wheel running.

Journal of neuroscience methods·2026
See all related articles

Related Experiment Video

Updated: May 28, 2026

Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment
08:43

Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment

Published on: August 7, 2017

Granger causality analysis implementation on MATLAB: a graphic user interface toolkit for fMRI data processing.

Zhen-Xiang Zang1, Chao-Gan Yan, Zhang-Ye Dong

  • 1School of Science, Beijing Jiaotong University, Beijing, China. zangzx416@sina.com

Journal of Neuroscience Methods
|October 25, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces REST-GCA, a new graphical user interface toolkit for Granger causality analysis (GCA) in functional magnetic resonance imaging (fMRI). REST-GCA reveals bidirectional causal effects between brain regions, enhancing fMRI data analysis.

More Related Videos

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

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

Related Experiment Videos

Last Updated: May 28, 2026

Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment
08:43

Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment

Published on: August 7, 2017

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

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

Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Brain Connectivity Analysis

Background:

  • Functional magnetic resonance imaging (fMRI) studies frequently employ Granger causality analysis (GCA) to infer causal relationships between brain regions.
  • Existing analysis toolkits may lack comprehensive features for advanced statistical inference in GCA.

Purpose of the Study:

  • To develop and validate REST-GCA, a MATLAB-based graphical user interface (GUI) toolkit for Granger causality analysis (GCA) of resting-state fMRI data.
  • To implement methods for transforming GCA outputs to improve normality for parametric statistical inference at the group level.
  • To investigate the causal interactions between the right frontal-insular cortex (rFIC) and other brain regions using the developed toolkit.

Main Methods:

  • Implementation of GCA within a MATLAB GUI toolkit (REST-GCA), building upon the Resting State fMRI Data Analysis Toolkit (REST).
  • Inclusion of residual-based F-statistics and signed-path coefficients as output measures.
  • Integration of a normalization procedure to transform F-statistics for parametric group-level analysis, validated using Jarque-Bera and Lilliefors tests.
  • Voxel-wise GCA applied to resting-state fMRI data from 30 healthy participants, examining causal effects involving the rFIC.

Main Results:

  • The REST-GCA toolkit successfully outputs residual-based F-statistics and signed-path coefficients.
  • The implemented transformation significantly improved the normality of the F-statistics, facilitating parametric inference.
  • Analysis revealed a bidirectional positive causal effect between the rFIC and the dorsal anterior cingulate cortex (dACC) based on normalized F-scores.
  • Signed-path coefficients indicated a positive causal effect from rFIC to dACC and a negative causal effect from dACC to rFIC.

Conclusions:

  • REST-GCA provides a valuable and user-friendly toolkit for conducting Granger causality analysis on fMRI data.
  • The toolkit's normalization feature enhances the reliability of group-level causal inference in neuroimaging studies.
  • The findings demonstrate the utility of REST-GCA in uncovering complex directional brain interactions, such as those between the rFIC and dACC.