The organization of physiological brain networks

Area of Science:

• Neuroscience
• Network Science
• Clinical Neurophysiology

Background:

• Understanding brain communication is key in neuroscience.
• Simple activation studies are insufficient; complex network analysis is needed.
• Brain network studies have surged with advanced imaging and network theory.

Purpose of the Study:

• To review modern network theory applications in healthy brain function.
• To explore how brain network organization changes in neurological disease.
• To highlight the role of clinical neurophysiology techniques like EEG and MEG.

Main Methods:

• Application of modern network theory to brain data.
• Utilizing high-density electroencephalography (EEG).
• Employing magnetoencephalography (MEG), functional MRI, and structural MRI.

Main Results:

• Healthy brains exhibit "small-world networks" with dense local and critical long-distance connections.
• Normal brain networks show hierarchical modularity and a hub-node backbone.
• Neurological diseases disrupt optimal brain network organization.

Conclusions:

• Brain function relies on complex, self-organized network architectures.
• Network analysis provides insights into healthy cognition and disease pathology.
• EEG and MEG are valuable tools for studying brain networks in health and disease.