Synchronization between Outputs of Neurons and Neuron Populations with Discrete Control Algorithm Basing on Least-square Method

As a new method on curing mental diseases, Deep Brain Stimulation (DBS) gives great help to patients who do not respond to drug therapies. However, most of the DBS therapies used at present are using high-frequency signals as open-loop stimulating signals, whose mechanism is not sufficiently understood. In this paper, basing on the synchronization mechanism and the close-loop stability theory, we have designed a close-loop method to propose a potential therapy for curing mental diseases with deep brain stimulation. Through reconstruct the input-output dynamics with least square method, we can use a new regressive input-output model to describe the relationship between the input and output of the abnormal neuron population. Using the parameters estimated in the regressive model, we can design a set of DBS signals to make the output of abnormal neuron population accurately track the desired output signal. The method is robust and can be applied even when the abnormal neuron population is disturbed by heavy noise.