A Generalization and Differentiation Circuit Implementation Based on Neural Mechanisms

Pavlov conditioning theory can explain part of biological behavior accurately, and has a profound influence on the development of behavioral psychology. Reinforcement, extinction, generalization and differentiation are the four basic principles of conditional reflex. Among them, reinforcement and extinction respectively correspond to learning and forgetting in Pavlov associative memory, and have been widely discussed. However, there are few studies on generalization and differentiation, and the circuits designed in the past cannot precisely reflect the experimental phenomenon. In this article, a generalization and differentiation circuit based on neural mechanisms is designed using memristors. This circuit improves on the previous generalization and differentiation circuits, so that it can distinguish similar but different tactile stimulus, and regularly generate different outputs according to the degree of similarity. The difference in the output corresponds to the variation in saliva secretion in response to different tactile stimuli in the biological system. At the same time, the number of tactile stimuli is increased, which helps to improve the resolution of the circuit to distinguish similar stimuli. In addition, this article considers the connections of neurons from the perspective of neural mechanisms, which makes the circuit structure more conform to biological properties. Finally, the above-mentioned functions have been verified in PSPICE.