Work

Constructing artificial neurons with functional parameters comprehensively matching biological values

Year: 2025

Type: article

Abstract: The efficient signal processing in biosystems is largely attributed to the powerful constituent unit of a neuron, which encodes and decodes spatiotemporal information using spiking action potentials of ultralow amplitude and energy. Constructing devices that can emulate neuronal functions is thus considered a promising step toward advancing neuromorphic electronics and enhancing signal flow in bioelectronic interfaces. However, existent artificial neurons often have functional parameters that are distinctly mismatched with their biological counterparts, including signal amplitude and energy levels that are typically an order of magnitude larger. Here, we demonstrate artificial neurons that not only closely emulate biological neurons in functions but also match their parameters in key aspects such as signal amplitude, spiking energy, temporal features, and frequency response. Moreover, these artificial neurons can be modulated by extracellular chemical species in a manner consistent with neuromodulation in biological neurons. We further show that an artificial neuron can connect to a biological cell to process cellular signals in real-time and interpret cell states. These results advance the potential for constructing bio-emulated electronics to improve bioelectronic interface and neuromorphic integration. Artificial neurons typically have functional parameters that are mismatched with their biological counterpart. Here, the authors develop artificial neurons that emulate biological neurons in functions and match their parameters such as signal amplitude, spiking energy, temporal features, and frequency response.

Source: Nature Communications

DOI: 10.1038/s41467-025-63640-7