Bioinspired Nanofluidic Circuits with Integrating Excitatory and Inhibitory Synapses

Abstract

Brain neural networks intricately integrate excitatory and inhibitory synaptic potentials to modulate the generation or suppression of action potentials, laying the foundation for neuronal computation. Although bioinspired nanofluidic systems have replicated some synaptic functions, complete integration of postsynaptic potentials remains unachieved. In this work, the developed ion concentration gradient nanofluidic memristor (ICGNM) modulates memristive effects through ion concentration gradient adjustments and exhibits synaptic plasticity phenomena, including paired-pulse facilitation, paired-pulse depression, and spike-rate-dependent plasticity. Furthermore, by incorporation of ICGNMs as the memristive elements into the classic Hodgkin–Huxley model, the action potential generation is replicated. In addition to simulating nanofluidic spiking, these ICGNMs are also employed in a bioinspired nanofluidic circuit to simulate the integration of excitatory and inhibitory synaptic signals, which is highly analogous to the signal integration in actual neural circuits. This work represents a new step toward ionic computing in solution with bioinspired nanofluidic circuits.