Synchronization control of interconnected systems with applications to neuronal networks

Motivated by recent interest in deep brain stimulation and its application to the treatment of neurological diseases, this paper addresses the problem of synchronization control for a class of interconnected compartmental models. In view of the measurement and actuation constraints typical of biological systems, it is assumed that the information available for feedback is a mean field quantity. It is shown that, under mean field static feedback, the level of synchronization of the network can be regulated to meet desired bounds. The theoretical results are applied to synchronization control of a network of FitzHugh-Nagumo neuronal models.