Linking functional connectivity and dynamic properties of resting-state networks
1Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
Scientific Reports
|December 2, 2017
Summary
Brain activity organizes into resting-state networks (RSNs). Higher synchrony and metastability in RSNs correlate with specific functional connectivity patterns, revealing links between brain network dynamics and function.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Systems Neuroscience
Background:
- Spontaneous brain activity forms resting-state networks (RSNs) crucial for cognitive functions.
- RSNs exhibit functional connectivity (cohesion, integration) and dynamic properties (synchrony, metastability).
Purpose of the Study:
- To investigate the relationship between functional connectivity and dynamic properties of RSNs.
- To understand how network dynamics support diverse cognitive operations.
Main Methods:
- Utilized functional Magnetic Resonance Imaging (fMRI) data.
- Employed an anatomically constrained Kuramoto model to analyze network dynamics.
Main Results:
- Simulated data indicated synchrony and metastability emerge at specific coupling strengths (5 ≤ k ≤ 12).
- Empirical RSNs showed higher metastability linked to greater cohesion and lower integration.
- Higher-order RSNs exhibited lower metastability and synchrony compared to sensory/motor RSNs.
Conclusions:
- Functional and dynamic properties of RSNs are intricately connected.
- Network dynamics provide insights into the neural architectures supporting optimal brain function.
