Artículo
Derivation of human chromatic discrimination ability from an information-theoretical notion of distance in color space
Fecha de publicación:
22/12/2016
Editorial:
M I T Press
Revista:
Neural Computation
ISSN:
0899-7667
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
The accuracy with which humans detect chromatic differences varies throughout color space. For example, we are far more precise when discriminating two similar orange stimuli than two similar green stimuli. In order for two colors to be perceived as different, the neurons representing chromatic information must respond differently, and the difference must be larger than the trial-to-trial variability of the response to each separate color. Photoreceptors constitute the first stage in the processing of color information; many more stages are required before humans can consciously report whether two stimuli are perceived as chromatically distinguishable. Therefore, although photoreceptor absorption curves are expected to influence the accuracy of conscious discriminability, there is no reason to believe that they should suffice to explain it. Herewedevelop information-theoretical tools based on the Fisher metric that demonstrate that photoreceptor absorption properties explain about 87% of the variance of human color discrimination ability, as tested by previous behavioral experiments. In the context of this theory, the bottleneck in chromatic information processing is determined by photoreceptor absorption characteristics. Subsequent encoding stages modify only marginally the chromatic discriminability at the photoreceptor level.
Palabras clave:
Color
,
Cones
,
Discrimination
,
Fisher Information
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Colecciones
Articulos(CCT - PATAGONIA NORTE)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - PATAGONIA NORTE
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - PATAGONIA NORTE
Citación
Da Fonseca, María de Los Angeles; Samengo, Ines; Derivation of human chromatic discrimination ability from an information-theoretical notion of distance in color space; M I T Press; Neural Computation; 28; 12; 22-12-2016; 2628-2655
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