Impedance spectroscopy of neurons, inductors and synapses: A path to understanding brain-like computation

[EN] This review underscores the growing relevance of impedance spectroscopy (IS) in neuromorphic research and its capacity to advance brain-inspired computation. Neuromorphic systems, which emulate biological neural networks, provide compact, adaptive, and energy-efficient solutions for edge applications such as robotics, wearable health monitoring, and environmental sensing. Since early studies on electrochemical oscillators, IS has been pivotal in probing neuron-like dynamics. Frequency-domain analysis of artificial synapses yields essential insights into synaptic plasticity¿the core mechanism of learning and memory¿shaped by functions like retention and filtering. Memristor-based synapses display chemical inductor behavior, evident as a negative arc in impedance spectra, highlighting their complex dynamics. More broadly, IS is increasingly positioned not only as a diagnostic tool for material performance but also as a framework for designing systems governed by ion migration, accumulation, and relaxation. By capturing these processes, IS provides a powerful perspective for analyzing and engineering physical computation components.