Neuromorphic Circuit of Classical and Operant Conditioning Based on Tunable Neural Circuitry Motifs

Most memristive bionic circuits focus on how to realize bionic functions, few studies consider the biomimetic of the circuit structure and operation rules, so it is difficult to learn, memorize, and make decisions as biological neural networks. In this work, a multifunctional neuromorphic circuit inspired by tunable neural circuitry motifs is proposed. The circuit is more closely with biological characteristics in both structure and functions, which is designed based on neural circuit architectures. By connecting different neural circuitry motifs, the circuit realizes operant conditioning functions such as random exploration, behavioral frequency modulation, and decision-making. Also, the circuit integrated classical conditioning and operant conditioning in order to mimic the decision-making process, which was driven by the association of secondary and primary stimuli. In addition, the factors influencing decision-making are researched, such as the rates of learning and forgetting, and the conversion of short-term to long-term memory. The operational results of the proposed circuits in LTspice show that they can mimic the aforementioned functions, which have advantages in bionicity and scalability. This work can be applied in intelligent robotic platforms to achieve exploration and rescue in complex environments.