Hierarchical organization unveiled by functional connectivity in complex brain networks

Area of Science:

• Neuroscience
• Computational Neuroscience
• Network Science

Background:

• Complex networks, such as the brain, exhibit hierarchical clustering.
• Understanding how network topology influences dynamical patterns is crucial.

Purpose of the Study:

• To investigate the relationship between network topology and synchronization dynamics in the cat cortical brain network.
• To explore how hierarchical clustering impacts functional organization.

Main Methods:

• Modeling the cat cortical brain network with hierarchically clustered topology.
• Representing each node (cortical area) as a subnetwork of interacting excitable neurons.
• Simulating synchronization dynamics within this model.

Main Results:

• The model demonstrated hierarchical modular organization in its dynamics.
• Functional clusters emerged that coincided with anatomical communities at various scales.
• Synchronization patterns reflected the underlying network structure.

Conclusions:

• Network topology, specifically hierarchical clustering, significantly shapes brain dynamics.
• Functional organization in the brain arises from its underlying anatomical structure.
• This provides insights into the link between network structure and emergent brain function.