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Transient networks of spatio-temporal connectivity map communication pathways in brain functional systems
Alessandra Griffa1, Benjamin Ricaud2, Kirell Benzi2
1Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne 1011, Switzerland; Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland.
Neuroimage
|April 17, 2017
Summary
This study integrates brain oscillations and structural connectivity to reveal dynamic brain networks. These networks show how brain activity travels along anatomical pathways, offering new insights into brain function.
Area of Science:
- Neuroscience
- Network Science
- Computational Biology
Background:
- Characterizing dynamic brain connectivity is crucial for understanding neural function.
- Current methods often lack integration of structural connectivity information.
- Resting-state functional MRI (fMRI) and diffusion MRI (dMRI) provide complementary data on brain function and structure.
Purpose of the Study:
- To develop a framework integrating infra-slow neural oscillations and anatomical connectivity.
- To capture transient networks of spatio-temporal connectivity in the human brain.
- To investigate how functional activity propagates on the structural connectome.
Main Methods:
- Utilized a multilayer-graph framework combining infra-slow neural oscillations (from fMRI) and anatomical connectivity maps (from dMRI).
- Analyzed data from 71 healthy subjects to identify transient spatio-temporal networks.
- Examined the spatial and temporal characteristics and activation trajectories within these networks.
Main Results:
- Identified transient brain networks exhibiting power-law size distributions in space and time.
- Observed global organization of these networks into known functional systems.
- Demonstrated wave-like activation trajectories along anatomically connected regions, propagating through polysynaptic paths distinct from shortest paths.
Conclusions:
- The proposed framework effectively models time-varying brain interactions on the structural connectome.
- Transient networks may represent communication channels and neural assemblies, supporting the communication-through-coherence principle.
- This work advances the understanding of brain structure-function relationships and large-scale neural communication mechanisms.