Toward a realistic simulation framework for large-scale neural correlates in clinical applications

Recent advances in neural engineering and mathematical methods influence more and more the way in which brain disorders and symptoms are being diagnosed and treated. In this direction, experimental findings, which emphasize on the correlation between large-scale neural correlates reflected in electroencephalographic data and neuronal mechanisms, have propelled the development of novel brain computer interfaces that represent a step ahead toward the realization of neural rehabilitation devices. In spite of this progress, a forward simulation framework that can reliably assist clinical studies in testing hypothesis related to neural correlates with respect to cognitive mechanisms and brain malfunctioning, is still in its infancy. To address this issue, we propose a cortico-subcortical simulation framework by means of the neural field approach. We show that this method allows for the consideration of relevant brain structures. We provide an instance in which our framework is successfully tested and discuss about a potential clinical application. It is concluded that our methodology represents a promising tool in assisting clinical studies for the treatment and diagnosis of brain disorders and studies concerning behavioral mechanisms.