Bio‐Inspired Wide‐Field Visual Neuron Implemented with Ultra‐Low Information Loss Population Coding

IF 26.8 1区 材料科学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Xi Wang, Qian He, Hanxi Li, Xinwei Zhang, Hailiang Wang, Zuqi Zhu, Jian Chai, Yongqing Bai, Yishu Zhang, Yang Xu, Bin Yu
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引用次数: 0

Abstract

Modern neuromorphic systems face critical bottlenecks in emulating biological vision, particularly in reconciling wide‐spectrum perception, distortion‐free encoding, and population‐level signal processing. Drawing inspiration from the stochastic‐resilient population coding of macaque visual neurons, an advanced visual neuron prototype is developed that incorporates photoelectric multi‐stimulation field‐effect transistor and innovative parallel threshold‐switch architecture. The visual neuron integrates broadband photodetection (350–1000 nm) with biomimetic spike population encoding in a monolithic architecture. The photosensitive MoSe2/MoS2 heterojunction region in field‐effect transistor extends the visual perception field from UV to infrared wavelengths (350–700 nm to 350–1000 nm), doubling the original field. Meanwhile, under the same conditions, the photocurrent response achieves a 1.36‐fold increase from 0.109 to 0.148 A (W cm−2)−1. The parallel threshold‐switching design transforms single‐unit encoding into cooperative population coding, achieving an 82.1% reduction rate in signal distortion. When deployed in a spiking neural network, this population‐coding paradigm demonstrates high accuracy in pattern recognition, surpassing single neuron architectures by 12.1%, while maintaining the information processing time at the biological scale (<200 ms). By unifying van der Waals heterostructure photonics with macaque‐derived neural population coding principles, this work establishes a transformative framework for bioinspired vision hardware, bridging the critical gap between neuromorphic materials and cortical processing efficiency.
采用超低信息丢失种群编码实现的生物启发宽视场视觉神经元
现代神经形态系统在模拟生物视觉方面面临着关键的瓶颈,特别是在协调宽频谱感知、无失真编码和群体级信号处理方面。从猕猴视觉神经元的随机弹性群体编码中获得灵感,开发了一种先进的视觉神经元原型,该原型结合了光电多刺激场效应晶体管和创新的并行阈值开关架构。视觉神经元将宽带光探测(350-1000 nm)与仿生峰群编码集成在一个单片架构中。场效应晶体管中的光敏MoSe2/MoS2异质结区将视觉感知场从紫外波长扩展到红外波长(350-700 nm至350-1000 nm),是原视场的两倍。同时,在相同的条件下,光电流响应从0.109增加到0.148 a (W cm−2)−1,增加了1.36倍。并行阈值开关设计将单单元编码转换为协同群体编码,实现了82.1%的信号失真降低率。当在尖峰神经网络中部署时,这种群体编码范式在模式识别方面表现出很高的准确性,比单个神经元结构高出12.1%,同时保持了生物尺度(200 ms)的信息处理时间。通过将范德华异质结构光子学与猕猴衍生的神经种群编码原理相结合,本研究建立了一个生物启发视觉硬件的变革框架,弥合了神经形态材料与皮层处理效率之间的关键差距。
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来源期刊
Advanced Materials
Advanced Materials 工程技术-材料科学:综合
CiteScore
43.00
自引率
4.10%
发文量
2182
审稿时长
2 months
期刊介绍: Advanced Materials, one of the world's most prestigious journals and the foundation of the Advanced portfolio, is the home of choice for best-in-class materials science for more than 30 years. Following this fast-growing and interdisciplinary field, we are considering and publishing the most important discoveries on any and all materials from materials scientists, chemists, physicists, engineers as well as health and life scientists and bringing you the latest results and trends in modern materials-related research every week.
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