Biomedical subjects

J M Rovamo

Publications and source records attributed to J M Rovamo.

4 recordsLinked to original sources

PubMed2000

The effect of contrast and size scaling on face perception in foveal and extrafoveal vision.

PURPOSE: To determine whether face perception can be equalized across the visual field by scaling size and contrast simultaneously. METHODS: Contrast sensitivities were measured for detection (N = 1) and identification (N = 2-8) of a target face as a function of size (0.4 degrees-10 degrees) across eccentricities (E = 0 degrees-10 degrees). RESULTS: In all conditions contrast sensitivity first increased and then saturated, as a function of stimulus size. Maximum sensitivity (Smax) decreased, whereas critical size (where S = Smax/square root(2)) increased with eccentricity and set size (N). At each set size, sensitivities from all eccentricities could be equated by double scaling--i.e., translation in horizontal (size) and vertical (contrast) dimensions on log-log axes. Similarly, at each eccentricity, data from all set sizes could be superimposed using double scaling. Furthermore, all data could be superimposed onto the foveal detection curve when double scaled according to the equation F = 1 + E/E2i + logN/logN2i + E(logN)/K, where i is horizontal or vertical. This equation incorporates the eccentricity (E2) and set size (N2), where contrast and size double, as well as the interaction term (K). CONCLUSIONS: Double scaling superimposes data. Not only is this possible across set sizes or eccentricities separately, but by combining their effects, a function is provided that collapses all data to a single curve, explaining all performance variation across eccentricity and set size. Our results support the proposition based on numeral recognition that failures of spatial scaling across eccentricities may simply reflect the need for scaling both size and contrast.

Adult↗

PubMed1999

Modelling spatial contrast sensitivity functions for chromatic and luminance-modulated gratings.

We extended our detection model of achromatic spatial vision (Rovamo, J., Mustonen, J., & Näsänen, R. (1994a). Modelling contrast sensitivity as a function of retinal illuminance and grating area. Vision Research, 34, 1301-1314) to colour vision by taking into account the fact that due to the spatio-chromatic opponency of retinal ganglion cells and dorsal lateral geniculate nucleus (dLGN) neurons, equiluminous chromatic gratings are not affected by precortical lateral inhibition. We then tested the extended model by using Mullen's experimental data (Mullen, K. J. (1985). The contrast sensitivity of human color vision to red-green and blue-yellow chromatic gratings. Journal of Physiology, 359, 381-400). The band-pass shape of the spatial contrast sensitivity function for luminance-modulated green and yellow gratings transformed to a low-pass shape, resembling the chromatic spatial contrast sensitivity function for red-green and blue-yellow equiluminous gratings, when the effect of precortical lateral inhibition on grating contrast was computationally removed by dividing luminance contrast sensitivities by spatial frequency (i.e. by af, where a = 1 degree). After the removal of this direct effect of lateral inhibition, there still remained a residual shape difference between the spatial contrast sensitivity functions for chromatic and luminance gratings. It was due to indirect reduction of grating visibility by quantal noise high-pass filtered by precortical lateral inhibition. When this indirect effect of quantal noise was also removed, contrast sensitivity for luminance gratings was about twice the sensitivity for chromatic gratings at all spatial frequencies. This was evidently due to the fact that the chromatic contrast of the equiluminous grating at the opponent stage (Cole, G. R., Hine, T. & McIihagga, W. (1993). Detection mechanisms in L-, M-, and S-cone contrast space. Journal of the Optical Society of America A, 10, 38-51) was about half of the luminance contrast of either of its chromatic component. Thus, if the contrast of the equiluminous chromatic grating were not expressed as the Michelson contrast of one chromatic component grating against its own background (Mullen, K. J. (1985). The contrast sensitivity of human color vision to red-green and blue-yellow chromatic gratings. Journal of Physiology, 359, 381-400) but as chromatic contrast at the opponent stage, contrast sensitivity would be the same for chromatic and luminance gratings.

Color Perception↗

PubMed1997

Modeling spatial integration and contrast invariance in visual pattern discrimination.

PURPOSE: Human pattern discrimination performance has been reported to be largely independent of stimulus contrast but to depend on stimulus area. The authors propose a model that combines the effects of spatial integration and contrast. The model is based on the computation of similarity between pattern templates in memory and signals to be discriminated using normalized correlation. There are also two sources of additive noise, one before and one after the computation of correlation. The model was compared with human observers in an orientation discrimination task. METHODS: Orientation discrimination thresholds of human observers were measured for sinusoidal gratings of various areas, contrasts, and spatial frequencies. A two-interval, forced-choice methods was used. The performance of the model was determined by using computer simulations. RESULTS: It was found that the effects of contrast and grating area were interrelated. The decrease of orientation thresholds as a function of grating area was considerably larger at low than at high contrast. On the other hand, orientation thresholds decreased clearly as a function of contrast at the smallest grating areas but hardly at all at the largest grating areas. The model accounted well for the experimental findings. CONCLUSIONS: Because the invariance of orientation discrimination with respect to stimulus contrast depended on area, the cause of the invariance appeared to occur after spatial integration. The model explains this so that, with increasing contrast or area, the normalized correlation gradually approached a constant value. The proportion of pretemplate noise became negligible compared to the constant posttemplate noise. Thus, total noise also approached a constant value. Hence, the signal-to-noise ratio and discrimination performance became constant.

Contrast Sensitivity↗

PubMed1995

A window model for spatial integration in human pattern discrimination.

PURPOSE: A simple model of human visual pattern discrimination was designed and tested experimentally. The model is based on two assumptions. First, at any glimpse the spatial integration of image information is limited to a window. Second, the observer generates a tailored discriminator for the signals in question using available information. The model is composed of a spatial integration window followed by an ideal discriminator. METHODS: The model was tested by comparing its performance with that of human observers in orientation and contrast discrimination. Using a two-alternative, forced-choice method, human orientation and contrast discrimination thresholds were measured for cosine gratings of various areas and spatial frequencies in the presence of two-dimensional spatial noise. RESULTS: Orientation discrimination thresholds decreased considerably with increasing grating area. Thus, there was clear spatial integration. However, in contrast discrimination, thresholds appeared to decrease only slightly. To make the two tasks comparable, the results also were expressed in terms of efficiency. Human efficiency decreased with grating area in a similar way in the two tasks. This suggests that the factors limiting spatial integration are the same in both tasks. Indeed, the threshold data were explained by the model with the same window size in both tasks with good accuracy. The absolute performance of the model was approximately equal to that of human observers. CONCLUSIONS: The success of the model supports the hypothesis of a spatial integration window. It also supports the idea that human observers use knowledge about the signals to generate an efficient discriminator.

Contrast Sensitivity↗