68 research outputs found

    The perception of color from motion

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    We introduce and explore a color phenomenon which requires the prior perception of motion to produce a spread of color over a region defined by motion. We call this motion-induced spread of color dynamic color spreading. The perception of dynamic color spreading is yoked to the perception of apparent motion: As the ratings of perceived motion increase, the ratings of color spreading increase. The effect is most pronounced if the region defined by motion is near 1 degree of visual angle. As the luminance contrast between the region defined by motion and the surround changes, perceived saturation of color spreading changes while perceived hue remains roughly constant. Dynamic color spreading is sometimes, but not always, bounded by a subjective contour. We discuss these findings in terms of interactions between color and motion pathways

    Spectral Tuning of Opponent Pathways is Temporally Dependent

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    Psychophysical test and field sensitivity data suggest that the spectral sensitivities of red/green opponent channels (red/green cells) become progressively nonopponent with decreases in stimulus size or duration. Recent data show that the shape of the field sensitivity depends not on field size per se but on the relative size of test and field. The present study examined the effect on field sensitivity of variations in the temporal parameters of stimulation. The results suggest a more complicated interaction than is observed in the spatial domain. Spectral tuning depends not only on the relative durations of test and field but also on the offset asynchrony between the two lights. Only when the test is extinguished prior to the field do the data show evidence of red/green activity. When the two lights coterminate. the field sensitivity resembles a nonopponent function, regardless of stimulus duration

    Spectral Tuning of Opponent Channels is Spatially Dependent

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    Psychophysical detection and appearance data suggest that the spectral tuning of opponent pathways varies with test size. The present study examines the effect on spectral sensitivity of the relative size of test and surround fields. Increment thresholds and flashed‐field sensitivities were obtained for 580 nm and 641 nm targets. Three spatial configurations were used. The pattern of sensitivity loss is shown to depend on the spatial relation between test and field; the effect of the spatial relation in turn depends on test wavelength. The findings are explained by the activity of a changing network of spatially and spectrally opponent cells

    A new look at calretinin-immunoreactive amacrine cell types in the monkey retina

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    We have examined amacrine cells that are calretinin-immunoreactive (-IR) in the macaque monkey retina with the aim of classifying them into morphological and functional subtypes. There are calretinin-IR cells in the fovea and throughout the retina. Their highest density is reached at 1.0 mm from the foveal pit (10,500 cells/mm2) and falls to 2,600/mm2 by 10 mm of eccentricity. Nearest-neighbor statistics for the calretinin-IR cell body distribution indicate a nonregular pattern, with a regularity index of 1.4–1.6. There is an increase or “bump” of cell density 3.5–4.0 mm from the foveal pit, corresponding to the rod photoreceptor density peak. Based on morphological differences, there appear to be three types of amacrine cell that are calretinin-IR. To determine the types, we doubly immunolabeled retinas, from fovea to periphery, for calretinin-IR in combination with other calcium binding proteins and inhibitory amino acid neurotransmitters. Labeling with parvalbumin and calretinin antibodies indicated that 70% of the amacrine cells were solely calretinin-IR, and 30% contained parvalbumin-IR as well. In the same way, 70% of the calretinin-IR amacrine cells colocalized calbindin, but 30% were only calretinin-IR. Among the calretinin/calbindin-colocalized cells, there were small-field and wide-field types. Double labeling with antibodies to calretinin and γ-aminobutyric acid (GABA) and to calretinin and glycine revealed the majority to be glycine-IR, but some were GABA-IR. The glycine-IR population consists mainly of AII amacrine cell types, but clearly another non-AII type is involved. The non-AII glycine-IR population resembles a small- to medium-field diffuse type. The calretinin-IR wide-field type is GABAergic and corresponds to an A19 type. The central, rod-free, fovea contains the calretinin-IR, non-AII glycine-IR type and the calretinin-IR, GABAergic type only. To learn more concerning the circuitry of the calretinin/glycine-IR, non-AII amacrine cell type in isolation from AII amacrine cells, we concentrated on the rod-free fovea, where AII amacrine cells are absent. We performed a serial section electron microscopy (EM) study on four calretinin-IR cells. They were involved with cone pathway circuitry. They got input from ON and OFF midget bipolar cells, reciprocated synapses to these bipolar cells, and provided synapses to ON-center ganglion cells. Thus we have obtained new information on a cone pathway amacrine cell of the central monkey fovea that is involved in the midget system.National Institute of Health; Grant number EY03323 (H.K.); Research to Prevent Blindness grant (Department of Ophthalmology, University of Utah School of Medicine)

    Analyzing the metrics of the perceptual space in a new multistage physiological colour vision model

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    In this work, the metric of a new multistage colour vision model, ATTD05, is assessed and a new colour difference formula is suggested. Firstly, the uniformity of the ATTD05 colour space was compared with that of CIECAM02 for some Munsell samples, because if the model yields a uniform perceptual space, we will be able to implement a colour difference formula as a Euclidian distance between two points. Secondly, we developed a new space based on the perceptual descriptors of the model: brightness, hue, colourfulness, and saturation. After that, we calculated the free parameters of the space that better fit the measured and experimental data of two datasets (small-magnitude and large-magnitude colour differences), by minimizing the performance factor (PF/3). Finally, we compare colour differences calculated for ATTD05 and for other models. The PF/3 and the STRESS parameters were used to decide which model predicts better perceptual differences and, therefore, which model was the more uniform.Spanish Ministry for Education and Science; contract grant numbers: DPI2005-08999-C02-02 and DPI2008-06455-C02-02
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