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Related Concept Videos

Vision01:24

Vision

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.
Photoreceptors and Visual Pathways01:22

Photoreceptors and Visual Pathways

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, whereas...
Visual System01:26

Visual System

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.
Once through the pupil, the light passes through the lens, a...
Anatomy of the Eyeball01:20

Anatomy of the Eyeball

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 layer, the vascular tunic,...

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Related Experiment Video

Updated: Jun 20, 2026

Laser-scanning Photostimulation of Optogenetically Targeted Forebrain Circuits
07:43

Laser-scanning Photostimulation of Optogenetically Targeted Forebrain Circuits

Published on: December 27, 2013

Optical outer-product learning in a neural network using optically stimulable phosphor.

F Itoh, K Kitayama, Y Tamura

    Optics Letters
    |September 22, 2009
    PubMed
    Summary
    This summary is machine-generated.

    Optically stimulable phosphors (OSP) enable a new memory device for optical neural networks. This technology allows for modifiable synaptic weights, crucial for learnable AI systems.

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    Area of Science:

    • Materials Science
    • Artificial Intelligence
    • Optoelectronics

    Background:

    • Optical neural networks (ONNs) require efficient memory devices for synaptic weight storage.
    • Existing memory technologies face limitations in speed, resolution, or rewritability for complex AI tasks.

    Purpose of the Study:

    • To demonstrate a novel memory device utilizing optically stimulable phosphor (OSP) for modifiable synaptic weights in learnable ONNs.
    • To explore the potential of OSP materials in advancing AI hardware.

    Main Methods:

    • Experimental demonstration of an OSP-based memory device.
    • Characterization of OSP properties relevant to synaptic weight storage (analog, parallel access, erasable, rewritable, high resolution, fast response).

    Main Results:

    • Successful implementation of an OSP memory device for modifiable synaptic weights.
    • OSP exhibits key characteristics suitable for mass storage of synaptic weight information.
    • The device shows potential for use in learnable optical neural networks.

    Conclusions:

    • Optically stimulable phosphor is a promising material for next-generation AI memory devices.
    • OSP-based memory offers a viable solution for efficient and dynamic synaptic weight modulation in optical computing.
    • This work paves the way for advanced, learnable optical neural network architectures.