The organization of physiological brain networks

One of the central questions in neuroscience is how communication in the brain is organized under normal conditions and how this architecture breaks down in neurological disease. It has become clear that simple activation studies are no longer sufficient. There is an urgent need to understand the brain as a complex structural and functional network. Interest in brain network studies has increased strongly with the advent of modern network theory and increasingly powerful investigative techniques such as “high-density EEG”, MEG, functional and structural MRI. Modern network studies of the brain have demonstrated that healthy brains self-organize towards so-called “small-world networks” characterized by a combination of dense local connectivity and critical long-distance connections. In addition, normal brain networks display hierarchical modularity, and a connectivity backbone that consists of interconnected hub nodes. This complex architecture is believed to arise under genetic control and to underlie cognition and intelligence. Optimal brain network organization becomes disrupted in neurological disease in characteristic ways. This review gives an overview of modern network theory and its applications to healthy brain function and neurological disease, in particular using techniques from clinical neurophysiology, such as EEG and MEG.

► The brain can be represented as a complex network with functionally connected units at several levels that changes in neurological and psychiatric disease.
► Existing clinical neurophysiology techniques and network models to explain network properties are reviewed.
► In addition to the already established network models, we suggest a heuristic model including hierarchical modularity.