Structural connectivity allows for multi-threading during rest: the structure of the cortex leads to efficient...

Area of Science:

• Neuroscience
• Computational Neuroscience
• Functional Neuroimaging

Background:

• The human cortex displays structured activity patterns even without external stimulation, known as resting state networks (RSNs).
• These RSNs manifest as low-frequency (<0.1 Hz) fluctuations in functional magnetic resonance imaging (fMRI) signals during rest.
• The default mode network (DMN) is a highly interconnected RSN of particular interest.

Purpose of the Study:

• To investigate the relationship between the cortex's structural connectivity and its resting-state dynamics.
• To explore how the degree of structural connectivity influences resting state network activity, focusing on the DMN.

Main Methods:

• Analysis of experimental resting-state fMRI data from human subjects.
• Large-scale computational simulations of cortical activity using diffusion tensor imaging (DTI)/diffusion spectrum imaging (DSI)-based neuroanatomical connectivity matrices.
• Modification of neuroanatomical connectivity matrices within the computational model to assess the role of structural hubs.

Main Results:

• The DMN was identified as the most frequently and longest-active functional network in experimental fMRI data.
• Computational simulations revealed a strong correlation between the mean degree of functional networks and their activation duration.
• This correlation was contingent upon the presence of structural hubs within the neuroanatomical connectivity matrices.

Conclusions:

• The high degree of connectivity within the DMN drives the observed resting-state dynamics.
• The brain efficiently transitions between internally and externally oriented processing during rest due to the DMN's hub-like structure.
• Structural connectivity, particularly the presence of hubs, is crucial for understanding resting-state functional dynamics.