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

Functional brain organization is stable within individuals across years.

bioRxiv : the preprint server for biology·2026
Same author

Precision fMRI reveals densely interdigitated network patches with conserved motifs in the lateral prefrontal cortex.

Neuron·2026
Same author

Transient Frontal Fracturing: A Theoretical Account of Hyperfocus.

Journal of cognitive neuroscience·2026
Same author

Towards precision functional brain network mapping in Parkinson's disease.

NeuroImage. Clinical·2026
Same author

Situating the salience and parietal memory networks in the context of multiple parallel distributed networks using precision functional mapping.

Cell reports·2025
Same author

Dense Phenotyping of Human Brain Network Organization Using Precision fMRI.

Annual review of psychology·2025

Related Experiment Video

Updated: Jul 24, 2025

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

7.3K

From correlation to communication: Disentangling hidden factors from functional connectivity changes.

Yuhua Yu1, Caterina Gratton1,2,3, Derek M Smith1,4

  • 1Department of Psychology, Northwestern University, Evanston, IL, USA.

Network Neuroscience (Cambridge, Mass.)
|July 3, 2023
PubMed
Summary

Researchers developed a new metric, "communication change," to better understand brain functional connectivity (FC). This method helps distinguish local brain coupling from network-wide influences, improving interpretations of fMRI data.

Keywords:
BOLD varianceFunctional connectivityNeural correlationsNeural coupling

More Related Videos

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

10.2K
Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
12:09

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy

Published on: August 5, 2014

18.1K

Related Experiment Videos

Last Updated: Jul 24, 2025

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

7.3K
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

10.2K
Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
12:09

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy

Published on: August 5, 2014

18.1K

Area of Science:

  • Neuroimaging
  • Systems Neuroscience
  • Computational Neuroscience

Background:

  • Functional connectivity (FC) derived from BOLD fMRI signals is widely used but interpretation is often ambiguous.
  • FC is influenced by both local neural interactions and non-local network inputs, complicating analysis.
  • Existing methods struggle to disentangle these factors, limiting conclusions about context-specific brain function.

Purpose of the Study:

  • To develop a method for estimating the contribution of non-local network input to functional connectivity changes.
  • To propose a novel metric, 'communication change,' to differentiate local coupling from network input effects.
  • To validate the utility of 'communication change' in understanding task-induced alterations in brain networks.

Main Methods:

  • Proposed a new metric, 'communication change,' utilizing BOLD signal correlation and variance.
  • Employed computational simulations to model brain network dynamics.
  • Conducted empirical analysis using fMRI data across different task contexts.

Main Results:

  • Non-local network input significantly contributes to task-induced functional connectivity changes.
  • The 'communication change' metric effectively tracks local coupling modifications during tasks.
  • 'Communication change' demonstrates superior ability to discriminate between different task types compared to standard FC change.

Conclusions:

  • The novel 'communication change' metric offers a more precise way to assess local neural coupling.
  • This index helps disentangle local versus network-wide influences on functional connectivity.
  • Potential applications include enhancing the understanding of large-scale brain network interactions in various cognitive states.