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Related Concept Videos

Vision01:24

Vision

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Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
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The Retina01:32

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The retina is a layer of nervous tissue at the back of the eye that transduces light into neural signals. This process, called phototransduction, is carried out by rod and cone photoreceptor cells in the back of the retina.
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The eye is a spherical, hollow structure composed of three tissue layers. The outer layer — the fibrous tunic, comprises the sclera — a white structure — and the cornea, which is transparent. The sclera encompasses some of the ocular surface, most of which is not visible. However, the 'white of the eye' is distinctively visible in humans compared to other species. The cornea, a clear covering at the front of the eye, enables light penetration. The eye's middle...
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Photoreceptors and Visual Pathways01:22

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At the molecular level, visual signals trigger transformations in photopigment molecules, resulting in changes in the photoreceptor cell's membrane potential. The photon's energy level is denoted by its wavelength, with each specific wavelength of visible light associated with a distinct color. The spectral range of visible light, classified as electromagnetic radiation, spans from 380 to 720 nm. Electromagnetic radiation wavelengths exceeding 720 nm fall under the infrared category,...
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Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
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Color Vision01:24

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Color perception begins in the retina, the light-sensitive layer at the back of the eye. Two main theories explain how colors are seen: the trichromatic theory and the opponent-process theory. The trichromatic theory, proposed by Thomas Young in 1802 and extended by Hermann von Helmholtz in 1852, suggests that color vision is based on three types of cone receptors in the retina. These cones are sensitive to different but overlapping ranges of wavelengths corresponding to red, blue, and green.
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Related Experiment Video

Updated: Aug 4, 2025

Transpupillary Two-Photon In Vivo Imaging of the Mouse Retina
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A two-dimensional mid-infrared optoelectronic retina enabling simultaneous perception and encoding.

Fakun Wang1, Fangchen Hu1,2, Mingjin Dai1

  • 1School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, 639798, Singapore.

Nature Communications
|April 6, 2023
PubMed
Summary
This summary is machine-generated.

We developed a compact, retina-inspired device for mid-infrared (MIR) object recognition. This novel optoelectronic system efficiently perceives and encodes MIR data for advanced neuromorphic computing applications.

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Area of Science:

  • Optoelectronics
  • Neuromorphic Computing
  • Artificial Intelligence

Background:

  • Current infrared machine vision systems are bulky and inefficient.
  • The human retina offers an intelligent, compact neural architecture for perception.
  • There is a need for efficient, compact systems in the Internet of Things era.

Purpose of the Study:

  • To present a novel retina-inspired mid-infrared (MIR) optoelectronic device.
  • To enable simultaneous data perception and encoding for MIR stimuli.
  • To advance neuromorphic computing with bio-inspired hardware.

Main Methods:

  • Utilizing a two-dimensional (2D) heterostructure for device fabrication.
  • Implementing an all-optical excitation mechanism with a stochastic near-infrared (NIR) sampling terminal.
  • Employing a rate encoding algorithm to convert MIR intensity into spike trains.

Main Results:

  • The device demonstrates simultaneous perception and encoding of MIR signals.
  • Achieved a wide dynamic working range and high encoding precision.
  • Attained over 96% inference accuracy on a MIR MNIST dataset using a spiking neural network (SNN).

Conclusions:

  • The developed device mimics the human retina's efficiency for MIR perception and encoding.
  • This technology offers a compact and efficient solution for MIR object recognition.
  • The device shows significant potential for integration into neuromorphic computing systems.