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Videos de Conceptos Relacionados

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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Updated: Jul 1, 2026

Monocular Visual Deprivation and Ocular Dominance Plasticity Measurement in the Mouse Primary Visual Cortex
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Monocular Visual Deprivation and Ocular Dominance Plasticity Measurement in the Mouse Primary Visual Cortex

Published on: February 8, 2020

La experiencia natural no supervisada altera rápidamente la representación de objetos invariantes en la corteza

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
Resumen

El aprendizaje de lentitud temporal sin supervisión (UTL, por sus siglas en inglés) altera la forma en que las neuronas de la corteza temporal inferior (TI) reconocen objetos. Este mecanismo de aprendizaje ayuda a construir representaciones de objetos tolerantes a los cambios de posición, escala y pose.

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Área de la Ciencia:

  • La neurociencia es la neurociencia.
  • La neurociencia computacional es una neurociencia computacional.
  • Visión por ordenador Visión por ordenador Visión por ordenador Visión por ordenador Visión por ordenador

Sus antecedentes:

  • El reconocimiento de objetos es complejo debido a la variabilidad de las imágenes de la retina para un solo objeto.
  • Las neuronas en la corteza temporal inferior (TI) exhiben selectividad para los objetos, pero son invariantes a los cambios en la posición, la escala y la postura.
  • Los mecanismos neuronales subyacentes a esta tolerancia a la representación de objetos siguen siendo en gran medida desconocidos.

Objetivo del estudio:

  • Para investigar cómo el cerebro construye la tolerancia neuronal para el reconocimiento de objetos.
  • Explorar el papel del aprendizaje de lentitud temporal sin supervisión (UTL) en el desarrollo de representaciones de objetos invariantes.

Principales métodos:

  • Manipulación dirigida de la contiguidad temporal de la entrada visual experimentada por los sujetos.
  • Registrar las respuestas neuronales de la corteza temporal inferior (TI) para evaluar los cambios en la tolerancia a la posición.
  • Cuantificar los efectos del aprendizaje de lentitud temporal sin supervisión (UTL) en las respuestas neuronales a lo largo del tiempo.

Principales resultados:

  • Las alteraciones en la contiguidad temporal de la experiencia visual llevaron a cambios significativos en la tolerancia de posición de la neurona IT.
  • El aprendizaje de la lentitud temporal sin supervisión (UTL) fue sustancial y aumentó con la experiencia acumulada.
  • Se observaron cambios significativos en la tolerancia de las neuronas IT después de solo una hora de UTL.

Conclusiones:

  • El aprendizaje de lentitud temporal no supervisado (UTL) es un mecanismo potencial para construir y mantener representaciones de objetos tolerantes en el flujo visual.
  • Este proceso de aprendizaje puede explicar cómo el cerebro logra la invariancia en el reconocimiento de objetos.
  • Los hallazgos se alinean con los modelos teóricos y los estudios de percepción de objetos humanos, lo que sugiere un principio computacional unificado.