Biomedical subjects

W McIlhagga

Publications and source records attributed to W McIlhagga.

7 recordsLinked to original sources

PubMed2006

Sinusoid = light bar + dark bar?

A sinusoidal grating can be viewed as a series of light and dark bars. Here we measure the contrast discrimination thresholds for light and dark bars individually, and find that the contrast discrimination thresholds for the whole sinusoid can be explained as ideal summation of the light and dark bar thresholds. We propose a model for light bar, dark bar, and sinusoidal contrast discrimination which involves local light adaptation and multiplicative noise. The model accounts for the data very well, and also accounts for contrast discrimination of light and dark edges.

Adaptation, Ocular↗

PubMed2004

Denoising and contrast constancy.

Contrast constancy is the ability to perceive object contrast independent of size or spatial frequency, even though these affect both retinal contrast and detectability. Like other perceptual constancies, it is evidence that the visual system infers the stable properties of objects from the changing properties of retinal images. Here it is shown that perceived contrast is based on an optimal thresholding estimator of object contrast, that is identical to the VisuShrink estimator used in wavelet denoising.

Contrast Sensitivity↗

PubMed1999

Noisy templates explain area summation.

The noisy template model is a variant of an ideal detector for a signal known except for contrast. The ideal detector cross-correlates the stimulus with a normalised template which is matched to the known signal pattern. The noisy template model simply adds noise to the matched template every time it is cross-correlated with the signal. This paper outlines the predictions of the noisy template model for area summation. The noisy template model explains Piper's Law, as does the ideal-observer, but it also explains critical area phenomena and the lack of area summation for contrast discrimination.

Computer Simulation↗

PubMed1997

Contour integration in strabismic amblyopia: the sufficiency of an explanation based on positional uncertainty.

Contour integration was measured in a group of strabismic amblyopes to determine if an explanation based solely on positional uncertainty was sufficient to explain performance. The task involved the detection of paths composed of micropatterns with correlated carrier orientations embedded in a field of similar micropatterns of random position and orientation (Field et al. Contour integration by the human visual system; Evidence for a local "association field". Vision Research, 33, 173-193, 1993). The intrinsic positional uncertainty for each amblyopic eye was measured with the same stimulus and it was found that in 10 out of our 11 amblyopic subjects, the reduced performance of the amblyopic eye could be modelled by the normal eye with an equivalent amount of positional uncertainty added to the stimulus. We conclude that the rules by which cellular outputs are combined, at least as reflected by this task, are normal in amblyopia.

Amblyopia↗

PubMed1994

Estimation of linear detection mechanisms for stimuli of medium spatial frequency.

Detection thresholds were obtained for a circularly-symmetric Gabor profile and Craik-Cornsweet profiles presented on a large white adapting field. These stimuli possessed peak spatial power between 1 and 6 c/deg. Their contrast was represented in an L, M and S cone contrast space. Detection thresholds were obtained for many vectors close to specific but theoretically important planes within this space. These data were fitted with a model comprising independent mechanisms, each a weighted sum of cone contrasts. The fit revealed a chromatic mechanism driven by delta L/L-delta M/M with no S cone input. Within cone contrast space, this mechanism was more sensitive than both a luminance mechanism with little S cone input but considerable variation in relative L to M cone input, and a blue-yellow chromatic mechanism.

Color Perception↗

PubMed1993

Detection mechanisms in L-, M-, and S-cone contrast space.

Detection thresholds were obtained for a 2 degrees Gaussian-blurred spot flashed for 200 ms on an 8.9 degrees white adapting field of 1070 trolands. The spot's contrast was represented in an L-, M-, and S-cone contrast space. Detection thresholds were obtained for many vectors close to specific but theoretically important planes within this space. A three-dimensional surface was fitted to the data generated by the probability summation of three mechanisms, each a weighted sum of cone contrasts. The fit revealed a red-green chromatic mechanism driven by delta L/L--delta M/M with no S-cone input that was 1 order of magnitude more sensitive than the two other mechanisms. The latter consisted of a luminance mechanism with little S-cone input and a blue-yellow chromatic mechanism with the S cone opposed to L and M cones.

Color Perception↗

PubMed1990

Texture segregation with luminance and chromatic contrast.

Preattentive texture discrimination was investigated using low spatial frequency texture elements. The contrast between the texture elements and the background was either purely luminance or purely chromatic, or some combination of both these types of contrast. The threshold to discriminate correctly the location of a different textured region was obtained from each subject, as was each subject's threshold to detect the elements of the texture. Using the ratio of texture to element detection as a measure of the effectiveness of texture discrimination, little difference could be found between the perception of luminance or chromatic texture. However, there were large and significant variations among subjects with otherwise normal colour vision.

Adaptation, Ocular↗