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Related Concept Videos

Vision01:24

Vision

53.5K
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

Parallel Processing

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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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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.
Once through the pupil, the light passes through the lens, a...
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Extracting Visual Evoked Potentials from EEG Data Recorded During fMRI-guided Transcranial Magnetic Stimulation
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Reconstructing visual illusory experiences from human brain activity.

Fan L Cheng1,2, Tomoyasu Horikawa2, Kei Majima1

  • 1Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan.

Science Advances
|November 15, 2023
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Summary
This summary is machine-generated.

Researchers reconstructed visual illusions from brain activity using deep neural networks (DNNs). This technique visualizes subjective experiences, offering insights into the brain

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Computer Vision

Background:

  • Visual illusions offer insights into sensory processing.
  • The neural basis of subjective visual experiences is not fully understood.

Purpose of the Study:

  • To reconstruct illusory percepts from brain activity using deep neural network (DNN) models.
  • To investigate how brain activity relates to subjective visual experiences.

Main Methods:

  • Utilized a brain decoding technique combined with DNN representations.
  • Trained a reconstruction model on natural images to link brain activity with perceptual features.
  • Tested the model on illusory line and neon color spreading phenomena.

Main Results:

  • Successfully reconstructed images of illusory lines and neon color spreading from brain activity.
  • Reconstructed percepts aligned with subjective illusory experiences.
  • Observed variations in reconstructions across different visual cortical areas.

Conclusions:

  • The developed framework can materialize subjective visual experiences.
  • This approach sheds light on the brain's internal representations during visual processing.
  • Brain decoding combined with DNNs is a promising method for studying visual perception.