BCM Learning Rules Emulated by a-IGZO-Based Photoelectronic Neuromorphic Transistors

Abstract

Hardware implementation of Bienenstock–Cooper–Munro (BCM) learning rules would be of great implications toward artificial intelligent systems. In this work, amorphous indium gallium zinc oxide (a-IGZO)-based photoelectronic neuromorphic transistors were proposed for mimicking BCM learning rules. A SiO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> electrolyte film with a large electric-double-layer capacitance ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.33~\mu \text{F}$ </tex-math></inline-formula> /cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) was used for the gate dielectric film. Light induced short-term synaptic plasticity can be mimicked by such device, including excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and high-pass temporal filtering. More importantly, BCM learning rules are realized based on this photoelectronic neuromorphic transistor. These results would provide a step forward the development of photoelectronic neuromorphic systems with sophisticated learning rules.