Amphibian-inspired neuromorphic dynamic vision systems based on ferroelectric field-effect transistor.

Zhai, Yongbiao; Chen, Peijie; Luo, Ying; Lv, Ziyu; Ding, Guanglong; Yang, Junjie; Zheng, Minglin; Zhou, Ye et al. · Nat Commun · 2026

basic_science · Level V

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Abstract

The dynamic vision sensor captures visual information as discrete events, enabling high-speed imaging with reduced data redundancy, but is limited by lack of color sensitivity, a speed-noise trade-off, and inefficient data transfer. Here we show an amphibian-inspired dynamic vision system (ADVS) based on ferroelectric field-effect transistors that emulates the hierarchical functions of amphibian retinas, including spectral perception, spatial preprocessing, and event-driven neural encoding. The ferroelectric transistors exhibit broadband photosensitivity (365-637 nm) and bidirectional photoresponses, enabling multichannel spectral recognition from ultraviolet to visible light. Device arrays further reproduce center-surround receptive-field-like processing, enhancing spatial contrast while suppressing background noise under weak illumination. Owing to the steep switching characteristics (SS<sub>min</sub> = 53.8 mV dec<sup>-1</sup>) of the transistors, the system also supports microsecond-scale event-driven spiking responses. Combined with bioinspired hierarchical preprocessing framework and event-driven convolutional neural network, the ADVS achieves 96.5% accuracy in dynamic facial expression recognition and real-time multi-agent trajectory prediction with <5% error.