Synchronization of nonidentical neural mass models via the concept of dissipativity

Abstract Synchronization widely exists in brain networks and plays a significant role in the transmission and processing of signals in cognitive processes. Abnormal synchronization can lead to neurological and psychiatric disorders such as schizophrenia and Alzheimer's disease. It is an essential and challenging task to design a controller achieve synchronization between different brain regions. This paper aims to investigate the synchronization problem of two nonidentical neural populations. Error feedback controller are proposed to achieve synchronization between two nonidentical neural populations. In addition, the sufficient conditions of synchronization are provided by utilizing Lurie system theory and the concept of dissipativity. The numerical simulations used two types of Wendling neural mass models. One type of model can be coupled to form a neural network which could help to investigate synchronization on macro level. And the other model can simulate realistic rapid brainwave activity related to the integration of multiple sensory perceptions.