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Related Concept Videos

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Neural Circuits

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Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
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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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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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Parallel Processing01:20

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The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
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Neurons, the fundamental units of the brain and nervous system, communicate through complex electrochemical signals that underpin all cognitive and bodily functions. This communication is primarily facilitated by a process involving the generation and propagation of an action potential along the axon of the neuron. When the internal electrical charge of a neuron surpasses a certain threshold, an action potential is triggered. This rapid change in voltage travels swiftly along the axon to the...
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Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.
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Related Experiment Video

Updated: Oct 21, 2025

Modeling the Functional Network for Spatial Navigation in the Human Brain
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Points-connecting neural network ray tracing.

Hiroshi Ohno, Takashi Usui

    Optics Letters
    |September 1, 2021
    PubMed
    Summary

    Unsupervised neural network ray tracing (NNRT) calculates light ray paths in gradient-index media. This method accurately traces ideal paths between two points without needing initial light ray direction, demonstrated using Maxwell

    Area of Science:

    • Optics and Photonics
    • Computational Physics
    • Artificial Intelligence

    Background:

    • Calculating light ray paths in gradient-index media is complex.
    • Traditional methods may require initial ray direction or detailed medium properties.
    • Neural networks offer a novel approach to solving complex optical problems.

    Purpose of the Study:

    • To introduce an unsupervised neural network ray tracing (NNRT) method.
    • To enable calculation of light ray paths between specified points in gradient-index media.
    • To demonstrate the efficacy of NNRT using a known optical system.

    Main Methods:

    • Developed an unsupervised neural network architecture for ray tracing.
    • Implemented the NNRT to find light ray paths connecting two arbitrary points.

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  • Utilized Maxwell's fisheye lens with a spherical gradient-index as a test case.

    • Main Results:

    • NNRT successfully calculated light ray paths between given points.
    • The method determined paths without prior knowledge of ray direction.
    • NNRT-traced rays followed ideal paths through the gradient-index medium.

    Conclusions:

    • Unsupervised neural network ray tracing is a viable method for gradient-index media.
    • NNRT provides accurate light ray path calculations between specified points.
    • The demonstrated accuracy suggests potential applications in optical design and simulation.