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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.
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...
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.
Perceptual Constancy01:12

Perceptual Constancy

Perceptual constancy is the ability to recognize that objects remain consistent and unchanged even when their appearance varies due to changes in sensory input. There are four main types of perceptual constancy: size constancy, shape constancy, color constancy, and brightness constancy.
Size constancy is the recognition that an object remains the same size, even when its image on the retina changes. For instance, a bus is perceived to be large enough to carry people, even if it looks tiny from...
Parallel Processing01:20

Parallel Processing

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...
Motor and Sensory Areas of the Cortex01:14

Motor and Sensory Areas of the Cortex

The cerebral cortex, the brain's outermost layer, is pivotal in processing complex cognitive tasks, emotions, and various sensory inputs and executing voluntary motor activities. This intricate structure is divided into three primary functional areas: the motor areas, sensory areas, and association areas.
Motor Areas
The motor areas located in the frontal lobe are central to controlling voluntary movements. This region is further subdivided into the primary motor cortex and the premotor cortex.

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Unsupervised natural experience rapidly alters invariant object representation in visual cortex.

Nuo Li1, James J DiCarlo

  • 1McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

Science (New York, N.Y.)
|September 13, 2008
PubMed
Summary

Unsupervised temporal slowness learning (UTL) alters how neurons in the inferior temporal cortex (IT) recognize objects. This learning mechanism helps build object representations tolerant to changes in position, scale, and pose.

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Computer Vision

Background:

  • Object recognition is complex due to the variability of retinal images for a single object.
  • Neurons in the inferior temporal cortex (IT) exhibit selectivity for objects but are invariant to changes in position, scale, and pose.
  • The neural mechanisms underlying this object representational tolerance remain largely unknown.

Purpose of the Study:

  • To investigate how the brain constructs neuronal tolerance for object recognition.
  • To explore the role of unsupervised temporal slowness learning (UTL) in developing invariant object representations.

Main Methods:

  • Targeted manipulation of the temporal contiguity of visual input experienced by subjects.
  • Recording neuronal responses from the inferior temporal cortex (IT) to assess changes in position tolerance.
  • Quantifying the effects of unsupervised temporal slowness learning (UTL) on neuronal responses over time.

Main Results:

  • Alterations in visual experience's temporal contiguity led to significant changes in IT neuronal position tolerance.
  • Unsupervised temporal slowness learning (UTL) was substantial and increased with cumulative experience.
  • Significant changes in IT neuron tolerance were observed after just one hour of UTL.

Conclusions:

  • Unsupervised temporal slowness learning (UTL) is a potential mechanism for building and maintaining tolerant object representations in the visual stream.
  • This learning process may explain how the brain achieves invariance in object recognition.
  • Findings align with theoretical models and human object perception studies, suggesting a unified computational principle.