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Encoding01:19

Encoding

Information enters the brain through encoding, which is the input of information into the memory system. Once sensory information is received from the environment, the brain labels or codes it. The information is then organized with similar information and connected to existing concepts. Encoding occurs through automatic processing and effortful processing.
Automatic processing involves the encoding of details like time, space, frequency, and the meaning of words, usually done without conscious...
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.
Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
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...
Color Vision01:24

Color Vision

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.
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...

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Related Experiment Video

Updated: Jul 17, 2026

Visualizing Visual Adaptation
04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

Leveraging Psychophysics to Infer the Mechanisms of Encoding Change in Vision.

Jason S Hays1, Fabian A Soto1

  • 1Department of Psychology, Florida International University, Modesto A. Maidique Campus, 11200 SW 8th St, Miami, FL 33199 USA.

Computational Brain & Behavior
|July 16, 2026
PubMed
Summary

Population encoding models help study vision neuroscience, but can be ambiguous. Combining these models with psychophysical data helps differentiate neural encoding changes for clearer insights.

Keywords:
SampleTest

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Area of Science:

  • Neuroscience
  • Computational Neuroimaging
  • Psychophysics
  • Human Vision

Background:

  • Population encoding models are key for inferring neural code changes from indirect measurements in human vision research.
  • The Inverse Encoding Model (IEM) is a popular computational neuroimaging approach, but recent studies highlight potential identifiability issues where different encoding changes yield similar response estimates.

Purpose of the Study:

  • To investigate whether psychophysical data can help resolve ambiguities in population encoding models.
  • To determine which mechanisms of neural encoding change can be distinguished using psychophysical thresholds.

Main Methods:

  • Simulated psychophysical thresholds under varying external noise (TvN curves) and stimulus values (TvS curves).
  • Evaluated eight distinct mechanisms of neural encoding change, including specific/nonspecific gain, tuning, suppression, and tuning shifts.
  • Compared simulated psychophysical data patterns against predictions from different encoding change models.

Main Results:

  • Most encoding change mechanisms (except specific gain and tuning) produced distinct patterns in TvN and TvS curves.
  • Psychophysical threshold data effectively differentiated between various neural encoding change models.

Conclusions:

  • Psychophysical studies serve as a valuable complement to Inverse Encoding Models, offering crucial constraints for interpreting neural code changes.
  • Recommendations are provided for researchers to better utilize psychophysical data in conjunction with encoding models and re-interpret existing data.