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Bioinspired Photoresponsive Single Transistor Neuron for a Neuromorphic Visual System.

Joon-Kyu HanDae-Myeong GeumMun-Woo LeeJi-Man YuSeong Kwang KimSang Hyeon KimYang-Kyu Choi
Published in: Nano letters (2020)
Realizing a neuromorphic-based artificial visual system with low-cost hardware requires a neuromorphic device that can react to light stimuli. This study introduces a photoresponsive neuron device composed of a single transistor, developed by engineering an artificial neuron that responds to light, just like retinal neurons. Neuron firing is activated primarily by electrical stimuli such as current via a well-known single transistor latch phenomenon. Its firing characteristics, represented by spiking frequency and amplitude, are additionally modulated by optical stimuli such as photons. When light is illuminated onto the neuron transistor, electron-hole pairs are generated, and they allow the neuron transistor to fire at lower firing threshold voltage. Different photoresponsive properties can be modulated by the intensity and wavelength of the light, analogous to the behavior of retinal neurons. The artificial visual system can be miniaturized because a photoresponsive neuronal function is realized without bulky components such as image sensors and extra circuits.
Keyphrases
  • low cost
  • optical coherence tomography
  • spinal cord
  • diabetic retinopathy
  • deep learning
  • high intensity
  • mass spectrometry
  • functional connectivity
  • perovskite solar cells