Knowledge-based expert control of thalamic neuron firing mode

Abstract

This work sheds light on the possibility of using control strategies to set the parameters of electric stimulation, a commonly used technique in severe human central nervous system diseases. Currently, parameters of electric stimulation are set through a trial and error process, with a lot of undesirable side effects. Accordingly, and based on the problem of having a population of sick neurons embedded in a population of normal neurons, this work explores the possibility of using a control system based on the behavior of healthy neurons to set current parameters able to modify the electric behavior of sick neurons. Specifically, we posit a knowledge-based expert control system that modifies the firing mode of a thalamic neuron by applying a control stimulation current, with the aim of making it fire in the same mode as a reference thalamic neuron. The controller parameters are tuned based on some characteristics of neurons that have to be determined through experiments before their application, but this controller does not require a detailed mathematical model of each neuron. Simulation results indicate that the proposed system satisfies the control objectives.