From Pain to Fear Recognition via Pavlovian Learning in an Organic–Inorganic Hybrid Neuromorphic Transistor. (28th January 2022) - Wei, Liubo; Jiang, Jie; Wan, Qing
Abstract: The pain perception system is of great importance for the human body to perceive noxious stimuli in external environment and make an appropriate reaction. Therefore, the hardware realization of nociceptors using emerging solid‐state device is of great importance toward the next‐generation intelligent electronic devices. However, at present, the pain recognition with threshold regulation is still very lacking by using the solid‐state device. Herein, a novel pain‐perceptual device based on organic–inorganic hybrid MoS2 transistor is fabricated by using polyvinyl alcohol‐based electrolyte. The key characteristics of pain perception, such as threshold, sensitization, and desensitization behaviors, are realized in the organic–inorganic hybrid neuromorphic transistor based on the unique ion migration mechanism. Most importantly, the device exhibits a clear transition from pain to fear recognition through the Pavlovian training. These results provide a promising strategy to the next generation of bio‐inspired electronic devices, smart healthcare, cognitive electronics, etc. Abstract : In this work, an organic–inorganic hybrid MoS2 transistor gated with PVA‐based polymer electrolyte is successfully demonstrated to mimic the recognition transition from pain to fear using Pavlovian learning rule. The typical pain‐perceptual characteristics is realized in the device. Most importantly, after Pavlov's conditional learning, a clear recognition transition from pain to fear is finally realized in the organic–inorganic hybrid transistor.