Operation of Neuronal Membrane Simulator Circuit for Tests with Memristor Based on Graphene and Graphene Oxide

Abstract

Artificial neural networks have been developed by researchers based on the understanding of different brain skills, such as learning and remembering. Memristors can simulate from memory process to neural membrane functioning. Since the first neural networks were proposed, research has been divided into two areas: one aimed at simulating biological phenomena and the other directed at applications. In this work, we intend to carry out a study on the reproduction of neuronal membrane behavior through a resistor-capacitor (RC) circuit associated with a memristor. RC circuit has the property of simulating neural membrane at the moment of the action potential, through charge and discharge curve of a capacitor. Memristor will be the component responsible for the non-linear behavior of circuit due to its resistive switching (RS) property, where it switches from a high resistance state (HRS) to low resistance state (LRS), or vice versa, depending on the voltage; this phenomenon can be reproduced many times. Two types of experiments were performed: the first one, temporal, where the output voltage was obtained as a function of time and time constant could be calculated for each section of the graph. In the second measure, it was possible to obtain the output voltage behavior as a function of input voltage; non-linearity could be observed through hysteresis formation and changes could be perceived by the formation of a step in some cases, which indicates a change in the continuity of behavior in relation to voltage. Important observations were made regarding the operation of the RC circuit; both resistance and capacitor influenced output voltage curve behavior. Together with memristor, it was possible to verify that the behavior of neurotransmitters in action potential could be simulated.