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Related Experiment Video

Updated: Oct 2, 2025

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

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

Published on: March 21, 2019

Individualized event structure drives individual differences in whole-brain functional connectivity.

Richard F Betzel¹, Sarah A Cutts², Sarah Greenwell³

¹Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, United States; Program in Neuroscience, Indiana University, Bloomington, IN 47405, United States; Network Science Institute, Indiana University, Bloomington, IN 47405, United States; Cognitive Science Program, Indiana University, Bloomington, IN 47405, United States.

|February 22, 2022

Summary

Brain network "events" drive individualized functional connectivity. These short, high-amplitude cofluctuations are unique to individuals, offering a dynamic basis for brain organization and markers.

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Last Updated: Oct 2, 2025

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Area of Science:

Neuroscience
Brain Imaging
Systems Neuroscience

Background:

Resting-state functional connectivity (rsFC) reveals brain organization and clinical markers.
The precise origins and drivers of rsFC, especially in individuals, remain unclear.
Current models often overlook the dynamic, moment-to-moment contributions to rsFC.

Purpose of the Study:

To investigate the origins of individualized functional connectivity using novel decomposition methods.
To identify and characterize the role of transient brain network events in shaping rsFC.
To develop a model of functional connectivity based on these dynamic events.

Main Methods:

Utilized novel methodology to decompose functional connectivity into framewise contributions.
Employed two dense-sampling datasets to analyze brain network events (high-amplitude cofluctuations).
Developed a statistical test to identify events in empirical neuroimaging recordings.

Main Results:

Identified 'events'—short-lived, high-amplitude cofluctuation patterns—as key contributors to rsFC.
Demonstrated that event patterns are repeatable within individuals across scans.
Showed that individual event patterns are idiosyncratic variants of group-level templates.

Conclusions:

Brain network events provide an individualized, dynamic basis for functional connectivity.
Group-averaged connectivity models are suboptimal for explaining participant-specific rsFC.
Transient, high-amplitude cofluctuations are primary drivers of both static and dynamic rsFC.