Implementing an artificial synapse and neuron using a Si nanowire ion-sensitive field-effect transistor and indium-gallium-zinc-oxide memristors

Abstract

In this study, we implement an artificial synapse and neuron in a single platform by combining a silicon nanowire (SiNW) ion-sensitive field-effect transistor (ISFET), an indium-gallium-zinc-oxide (IGZO) memristor, and a voltage-controlled oscillator (VCO). The chemical and electrical operations of the synapse are emulated using the pH sensor operation of the ISFET and long-term potentiation/short-term plasticity of the IGZO memristor, respectively. The concentration of hydrogen ions in an electrolyte is successfully transformed via a VCO-based neuron into modulation of synaptic strength, i.e., the current of the memristor. It mimics the strength of the synaptic connection modulated by the concentration of the neurotransmitter. Thus, the chemical-electrical signal conversion in chemical synapses is clearly demonstrated. Furthermore, the proposed artificial platform can discriminate the chemical synapse from the electrical synapse and the path of the neuro-signal propagation and that of memorization/update of synaptic strength. This can potentially provide a new insight into the principles of brain-inspired computing that can overcome the bottleneck of the state-of-the-art von-Neumann computing systems. © 2019 Elsevier B.V.