Scholarlink

<p>Neuromorphic systems, inspired by nature, are sought to efficiently process analogue inputs in real and complex environments. This could lead to ultralow-power in-sensor intelligent edge computers. Here, we present an artificial sensory oscillator neuron consisting of a III–V semiconductor micropillar quantum resonant tunnelling diode (RTD) with GaAs photosensitive absorption layers. The oscillatory optical neuron encodes incoming analogue optical data into spatiotemporal oscillatory signals. We demonstrate that near-infrared light within a certain intensity range activates a region of negative differential resistance, and subsequently, large-amplitude voltage oscillations. As a result, optic analogue information is encoded into electrical oscillations resulting in amplification of sensory light inputs. Under pulse-modulated light, excitation and inhibition of burst firing patterns can be controlled within a single oscillatory neuron, simulating neural activity in networks in the form of breather-type oscillatory phenomena. Such spatiotemporal oscillatory patterns (burst firing) form the basis for the combined sensing, pre-processing, and encoding abilities of the vision-nervous system found in biological organisms. This work paves the way for future artificial visual systems using III–V semiconductor nano-optoelectronic circuits in applications for light-driven neurorobotics, bioinspired optoelectronics, and in-sensor neuromorphic computing systems for real-time processing of sensory data.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Light-induced negative differential resistance and neural oscillations in neuromorphic photonic semiconductor micropillar sensory neurons

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月25日

查看全文
  • Bejoys Jacob,
  • Juan Silva,
  • José M. L. Figueiredo,
  • Jana B. Nieder,
  • Bruno Romeira

摘要

Neuromorphic systems, inspired by nature, are sought to efficiently process analogue inputs in real and complex environments. This could lead to ultralow-power in-sensor intelligent edge computers. Here, we present an artificial sensory oscillator neuron consisting of a III–V semiconductor micropillar quantum resonant tunnelling diode (RTD) with GaAs photosensitive absorption layers. The oscillatory optical neuron encodes incoming analogue optical data into spatiotemporal oscillatory signals. We demonstrate that near-infrared light within a certain intensity range activates a region of negative differential resistance, and subsequently, large-amplitude voltage oscillations. As a result, optic analogue information is encoded into electrical oscillations resulting in amplification of sensory light inputs. Under pulse-modulated light, excitation and inhibition of burst firing patterns can be controlled within a single oscillatory neuron, simulating neural activity in networks in the form of breather-type oscillatory phenomena. Such spatiotemporal oscillatory patterns (burst firing) form the basis for the combined sensing, pre-processing, and encoding abilities of the vision-nervous system found in biological organisms. This work paves the way for future artificial visual systems using III–V semiconductor nano-optoelectronic circuits in applications for light-driven neurorobotics, bioinspired optoelectronics, and in-sensor neuromorphic computing systems for real-time processing of sensory data.