Neural Network Modeling of EEG Patterns in Encephalopathy

The EEG is an accessible tool for detecting encephalopathy, which usually manifests as delirium and sometimes as coma. Several disturbances have been described in the EEG of patients with encephalopathy, including diffuse slowing and periodic discharges. The pathophysiology of these EEG alterations, however, is poorly understood. This article shows that simulating activity of large populations of neurons, using neural mass models and neural network analysis, may increase our understanding of EEG disturbances in encephalopathy. We provide a brief introduction on the concepts of neural mass modeling and graph theoretical network analysis, and insights from this approach in previous work on neurologic disease, with a focus on encephalopathy. Finally, we speculate how anatomically coupled neural mass modeling combined with network analysis could provide new insights in pathophysiology of encephalopathy.