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Related Concept Videos

Visual System01:26

Visual System

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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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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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Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
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Visual agnosia is a condition characterized by the inability to recognize visually presented objects despite having normal vision. For instance, a person with visual agnosia can describe the shape and color of an object but cannot identify or name it. This impairment does not affect their visual field, acuity, color vision, brightness discrimination, language, or memory. An example of this condition in a social setting is someone at a dinner party asking for "that silver thing with a round...
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Development of an Audio-based Virtual Gaming Environment to Assist with Navigation Skills in the Blind
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Creating and controlling visual environments using BonVision.

Gonçalo Lopes1, Karolina Farrell2, Edward Ab Horrocks2

  • 1NeuroGEARS Ltd., London, United Kingdom.

Elife
|April 21, 2021
PubMed
Summary
This summary is machine-generated.

Researchers developed BonVision, an open-source software for creating real-time visual environments. This tool simplifies complex closed-loop experiments for studying brain function and behavior in various animal models.

Keywords:
augmented realityhumanmousenavigationneuroscienceratspatial visionvirtual realityzebrafish

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Area of Science:

  • Neuroscience
  • Computer Science
  • Bioengineering

Background:

  • Real-time closed-loop visual environments are crucial for understanding brain function and behavior.
  • Current implementations are complex, limiting accessibility for non-experts and widespread adoption.

Purpose of the Study:

  • To develop an accessible, open-source software solution for creating real-time closed-loop visual environments.
  • To facilitate advanced experimental designs in neuroscience and behavioral research.

Main Methods:

  • Developed BonVision, an open-source software based on the Bonsai graphical programming language.
  • Integrated BonVision with experimental hardware for seamless data acquisition and stimulus presentation.
  • Enabled real-time interaction with deep neural networks and communication with measurement devices.

Main Results:

  • BonVision provides an easy-to-use platform for displaying virtual reality, augmented reality, and standard visual stimuli.
  • Successfully tested on humans and mice, demonstrating versatility across different species.
  • Facilitates integration with diverse experimental hardware and deep neural networks for closed-loop control.

Conclusions:

  • BonVision democratizes the creation of sophisticated closed-loop visual experiments.
  • The software supports novel experimental designs and broadens research capabilities in neuroscience and behavioral studies.
  • Its open-source nature and hardware integration foster wider adoption and collaboration in the scientific community.