부산대학교 도서관

In this article, three different implementations of an Axon-Hillock circuit are presented, one of the basic building blocks of spiking neural networks. In this work, we explored the design of such circuits using a unipolar thin-film transistor technology based on amorphous InGaZnO, often used for large-area electronics. All the designed circuits are fabricated by direct material deposition and patterning on top of a flexible polyimide substrate. Axon-Hillock circuits presented in this article consistently show great adaptability of the basic properties of a spiking neuron such as output spike frequency adaptation and output spike width adaptation. Additional degrees of adaptability are demonstrated with each of the Axon-Hillock circuit varieties: neuron circuit threshold voltage adaptation, differentiation between input signal importance, and refractory period modulation. The proposed neuron can change its firing frequency up to three orders of magnitude by varying a single voltage brought to a circuit terminal. This allows the neuron to function, and potentially learn, at vastly different timescales that coincide with the biologically meaningful timescales, going from milliseconds to seconds, relevant for circuits meant for interaction with the environment. Thanks to careful design choices, the average measured power consumption is kept in the nW range, realistically allowing upscaling towards the spiking neural networks in the future. The spiking neuron with refractory period modulation presented in this work has an area of 607.3 μm × 492.2 μm, it experimentally demonstrated firing rates as low as 11.926 mHz, and its energy consumption per spike is ≈ 700 pJ at 30 Hz.