Artificial fear neural circuit based on noise triboelectric nanogenerator and photoelectronic neuromorphic transistor

Abstract

Fear neural circuits can recognize precisely threatening stimuli and enable the early-warning for the individual in the real world. In this regard, implementation of fear neural circuits functions by neuromorphic devices could potentially improve the intelligent adaptability and cognition of humanoid robots. Here, an artificial fear neural circuit is proposed, which consists of a noise triboelectric nanogenerator (N-TENG) and an amorphous indium gallium zinc oxide based photoelectronic neuromorphic transistor (IGZO-PNT). Such an artificial fear neural circuit collects sound wave and light signals from the N-TENG and a-IGZO channel, respectively, converts these signals to electrical signals and integrates them into excitatory postsynaptic currents by the IGZO-PNT. The innate-fear and learned-fear behaviors are emulated by our artificial fear neural circuit. Furthermore, as a proof of concept, the escape behavior after fear triggered is realized by using a vibrator. Our biomimetic design can promote the developments of next-generation photoelectronic neuromorphic systems and humanoid robots.