Memristor-Based Context-Dependent Sensitization and System Desensitization Neural Circuit for the Emotional Regulation of Industrial Robots

By boosting reactions to stimuli, sensitization helps organisms adapt both physically and mentally. It is a crucial mechanism for dealing with environmental shifts and dangers. Although most memristor-based neural networks only consider the processes of habituation and dehabituation. However, the phenomenon of sensitization corresponding to habituation tends to be neglected. A memristor-based context-dependent sensitization and system desensitization neural network circuit is designed in this article. The circuit consists of sensitization module, sensitization generalization module, context-dependent module, and system desensitization module. First, when stronger stimuli appear repeatedly, the sensitization function of increasing the intensity of individual responses is realized through the sensitization module. Second, when new stimuli that are similar to the original stimuli appear, sensitization also occur. In addition, when the context changes, the effects on sensitization and biological responses are achieved through context-dependent modules. Finally, reduction of anxiety responses associated with specific stimuli is achieved through systematic desensitization of organisms using the principle of reciprocal inhibition. The simulation results of PSPICE verify the above functions. The circuit provides a reference for bionic emotional robots in neural computing and industrial applications.