Biomedical subjects

W H Beaudot

Publications and source records attributed to W H Beaudot.

5 recordsLinked to original sources

PubMed2001

Dynamics of contour integration.

To determine the dynamics of contour integration the temporal properties of the individual contour elements were varied as well as those of the contour they form. A temporal version of a contour integration paradigm (Field, D. J., Hayes, A., & Hess, R. F. (1993) Vision Research, 33, 173-193) was used to assess these two temporal dynamics as a function of the contrast of individual elements and the curvature of the contour. The results show that the dynamics of contour integration are good when the contrast of the individual elements is modulated in time (10-30 Hz), but are poor when contour linking per se is temporally modulated (1-12 Hz). The dynamics of contour linking is not dependent on the absolute contrast of the linking elements, so long as they are visible, but does vary with the curvature of the contour. For straight contours, temporal resolution is around 6-12 Hz but falls to around 1-2 Hz for curved contours.

Analysis of Variance↗

PubMed2001

Processing time of contour integration: the role of colour, contrast, and curvature.

We investigated the temporal properties of the red - green, blue-yellow, and luminance mechanisms in a contour-integration task which required the linking of orientation across space to detect a 'path'. Reaction times were obtained for simple detection of the stimulus regardless of the presence of a path, and for path detection measured by a yes/no procedure with path and no-path stimuli randomly presented. Additional processing times for contour integration were calculated as the difference between reaction times for simple stimulus detection and path detection, and were measured as a function of stimulus contrast for straight and curved paths. We found that processing time shows effects not apparent in choice reaction-time measurements. (i) Processing time for curved paths is longer than for straight paths. (ii) For straight paths, the achromatic mechanism is faster than the two chromatic ones, with no difference between the red-green and blue-yellow mechanisms. For curved paths there is no difference in processing time between mechanisms. (iii) The extra processing time required to detect curved compared to straight paths is longest for the achromatic mechanism, and similar for the red - green and blue-yellow mechanisms. (iv) Detection of the absence of a path requires at least 50 ms of additional time independently of chromaticity, contrast, and path curvature. The significance of these differences and similarities between postreceptoral mechanisms is discussed.

Analysis of Variance↗

PubMed2000

Contour integration in color vision: a common process for the blue-yellow, red-green and luminance mechanisms?

We compare the performance of the red-green, blue-yellow and luminance postreceptoral mechanisms on a contour integration task requiring the linking of oriented Gabor elements across space to extract a winding 'path' or contour. We first establish that for all three mechanisms curvature and contrast are independent; losses in performance due to one cannot be compensated by changes in the other. We then compare contour integration by the three mechanisms using a method that controls for their differences in cone contrast thresholds. Our results show that despite the poor orientation discrimination thresholds and poor spatial sampling found for the blue-yellow mechanism, all three mechanisms perform similarly on contour integration over a wide range of curvatures. Furthermore, all three mechanisms have the same dependence on path curvature. We also investigate the effects of adding external orientation noise. Our results imply that the internal orientation noise for extracting 'aligned' path elements is similar in the three mechanisms and for all path curvatures, and the relative efficiencies are also similar for the three mechanisms. To account for our results, we propose that the three postreceptoral mechanisms use a common contour integration process. This linking process, however, cannot be color-blind; our last experiment shows that linking between different chromatic mechanisms or between opposite spatial phases disrupts contour integration. We thus propose that the common integration process remains sensitive to the color contrast and phase of its inputs.

Color Perception↗

PubMed2000

Role of chromaticity, contrast, and local orientation cues in the perception of density.

We compared the role of the red-green, blue-yellow, and luminance post-receptoral mechanisms in the perception of density. The task requires the comparison of densities between two stimuli composed of oriented bandpass elements, pseudo-randomly scattered across an area of constant size. The perception of density differences was measured by a temporal 2AFC procedure for all pairs of mechanisms and for four possible densities. We found that stimuli of identical physical densities are not perceived equally: there is a consistent bias in favour of blue-yellow stimuli which are perceived as significantly more dense than red-green and achromatic stimuli. We considered three factors that could have differentially affected the density perception of blue-yellow stimuli: an increase in the perceived size of the individual blue-yellow elements, a perceived contrast difference, and the presence of local orientation cues. We found that the increased perceived density of the blue-yellow stimuli occurred despite the fact that there was no increase in perceived size of the individual elements, and remained despite corrections for the two other factors. We conclude that the significant increase in perceived density for the blue-yellow mechanism is a global effect, associated with a perceived colour 'melting' of the elements in the array. Our data were fitted with the occupancy model of Allik and Tuulmets (1991, Perception & Psychophysics 49 303-314) and we found that blue-yellow stimuli have a greater 'occupancy' than red-green or achromatic stimuli.

Color Perception↗

PubMed1996

Sensory coding in the vertebrate retina: towards an adaptive control of visual sensitivity.

We propose a theoretical framework for the adaptive control of visual sensitivity in the vertebrate retina. The photoreceptor transfer function is modelled with a Michaelis-Menten law instead of a logarithmic function. This more plausible function has a biophysical correlate, and it allows consideration of the photoreceptor as the main locus of retinal adaptation. The retinal model suggests that the function of photoreceptors might be to control visual sensitivity, defined as the optimal transcoding of non-stationary visual information. This is done by using an adaptive transfer function whose parameters are spatiotemporally and locally estimated by the subsequent retinal circuit and fed back to the photoreceptors. The proposed model also supports the functional architecture of the vertebrate retina.

Journal Article↗