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Updated: May 30, 2025

Acquisition of Resting-State Functional Magnetic Resonance Imaging Data in the Rat

Acquisition of Resting-State Functional Magnetic Resonance Imaging Data in the Rat

Published on: August 28, 2021

Time Persistence of the FMRI Resting-State Functional Brain Networks.

Shu Guo^1,2, Orr Levy^3,4, Hila Dvir²

¹State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience

|January 29, 2025

Summary

This summary is machine-generated.

Brain networks show decreasing similarity over time, with sensory networks being more persistent. Individual brain network persistence is stable, heritable, and linked to behavior.

Keywords:

fMRI functional connectivity individual differences network persistence resting-state networks time persistence

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Area of Science:

Neuroscience
Network Science
Systems Biology

Background:

Time persistence is crucial in complex systems, including the brain.
Previous studies examined neural time-series persistence but not at the network level across timescales.
Individual differences in brain network time persistence remain unexplored.

Purpose of the Study:

To systematically investigate network time persistence across various timescales (seconds to days) and brain subnetworks.
To develop a framework for estimating link- and node-level network time persistence.
To explore individual differences in network time persistence and their relationship to behavior.

Main Methods:

Analysis of three functional MRI resting-state datasets.
Development of a novel framework to quantify network time persistence at link and node levels.
Examination of persistence across timescales from within-run gaps to between-day intervals.

Main Results:

Brain functional networks gradually lose similarity over time, with significant decay within minutes and between days.
Network time persistence differs across functional networks; sensory networks exhibit higher persistence than nonsensory networks.
Individuals display stable, characteristic patterns of network time persistence with a genetic basis, linked to behavioral performance.

Conclusions:

The study provides a comprehensive characterization of resting-state functional brain network time persistence.
Network time persistence varies across subnetworks and individuals, suggesting functional significance.
Individual differences in network time persistence may play a role in brain function and cognitive abilities.