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S S Wolfson

Publications and source records attributed to S S Wolfson.

7 recordsLinked to original sources

Comparing increment and decrement probes in the probed-sinewave paradigm.

Using the probed-sinewave paradigm, we explore the differences between increment and decrement probes across a range of frequencies (approx. 1-19 Hz). In this paradigm, detection threshold is measured for a small test probe presented on a large sinusoidally flickering background (at eight different phases). Probe thresholds are very similar for increment and decrement probes, but there is a very small (and systematic) difference: increment thresholds are usually slightly higher relative to decrement thresholds during the part of the cycle when the background's intensity is increasing. Although Wilson's (1997, Vis. Neuro., 14, 403-423) model substantially underestimates the size of this difference, it predicts some phase dependency. However, the existence of On- and Off-pathways in Wilson's model is not important for these predictions. A recent model by Snippe, Poot, and van Hateren (2000, Vis. Neuro., 17, 449-462) may be able to predict this result by using explicit contrast-gain control rather than separate On- and Off-pathways. Auxiliary experiments measuring the perceived polarity of the probe provide a further argument suggesting that separate On- and Off-pathways are not useful in explaining increment and decrement probe thresholds.

Adaptation, Ocular↗

A note about preferred orientations at the first and second stages of complex (second-order) texture channels.

Complex (second-order) channels have been useful in explaining many of the phenomena of perceived texture segregation. These channels contain two stages of linear filtering with an intermediate pointwise nonlinearity. One unanswered question about these hypothetical channels is that of the relationship between the preferred orientations of the two stages of filtering. Is a particular orientation at the second stage equally likely to occur with all orientations at the first stage, or is there a bias in the "mapping" between the two stages' preferred orientations? In this study we consider two possible mappings: that where the orientations at the two stages are identical (called "consistent" here) and that where the orientations at the two stages are perpendicular ("inconsistent"). We explore these mappings using a texture-segregation task with textures composed of arrangements of grating-patch elements. The results imply that, to explain perceived texture segregation, complex channels with a consistent orientation mapping must be either somewhat more prevalent or more effective than those with an inconsistent mapping.

Contrast Sensitivity↗

Exploring the dynamics of light adaptation: the effects of varying the flickering background's duration in the probed-sinewave paradigm.

In the probed-sinewave paradigm, threshold for detecting a probe is measured at various phases with respect to a sinusoidally-flickering background. Here we vary the duration of the flickering background before (and after) the test probe is presented. The adaptation is rapid; after approximately 10-30 ms of the flickering background, probe threshold is the same as that on a continually-flickering background. It is interesting that this result holds at both low (1. 2 Hz) and middle (9.4 Hz) frequencies because at middle frequencies (but not at low) there is a dc-shift, i.e. probe threshold is elevated at all phases relative to that on a steady background (of the same mean luminance). We compare our results to predictions from Wilson's model [Wilson (1997), Visual Neuroscience, 14, 403-423; Hood & Graham (1998), Visual Neuroscience, 15, 957-967] of light adaptation. The model predicts the rapid adaptation, and the dc-shift, but not the detailed shape of the probe-threshold-versus-phase curve at middle frequencies.

Adaptation, Ocular↗

Long range interactions between oriented texture elements.

Long range interactions between texture elements (short, oriented line segments) were examined. Specifically, we studied the influence of a background array of texture elements on the detectability of a target element (separated from the background by an intermediate textured region) using textures like those of Caputo (Vis. Res. 1996, 36, 2815-2826). We found that, in general, when the background elements were oriented orthogonally to the target element, detection of the target element was better than when the background elements had the same orientation as the target element. We discuss these interactions in terms of inhibitory and excitatory connections between orientation and spatial frequency selective linear filters (e.g. filters which mimic V1 simple cells) which would respond to the individual texture elements.

Choice Behavior↗

Examining edge- and region-based texture analysis mechanisms.

Instantaneous texture discrimination performance was examined for different texture stimuli to uncover the use of edge-based and region-based texture analysis mechanisms. Textures were composed of randomly placed, short, oriented line segments. Line segment orientation was chosen randomly using a Gaussian distribution (described by a mean and a standard deviation). One such distribution determined the orientations on the left side of the image, and a second distribution was used for the right side. The two textures either abutted to form an edge or were separated by a blank region. A texture difference in mean orientation led to superior discrimination performance when the textures abutted. On the other hand, when the textures differed in the standard deviation of the orientation distribution, performance was similar in the two conditions. These results suggest that edge-based texture analysis mechanisms were used (i.e. were the most sensitive) in the abutting difference-in-mean case, but region-based texture analysis mechanisms were used in the other three cases.

Differential Threshold↗

Discrimination of orientation-defined texture edges.

Preattentive texture segregation was examined using textures composed of randomly placed, oriented line segments. A difference in texture element orientation produced an illusory, or orientation-defined, texture edge. Subjects discriminated between two textures, one with a straight texture edge and one with a "wavy" texture edge. Across conditions the orientation of the texture elements and the orientation of the texture edge varied. Although the orientation difference across the texture edge (the "texture gradient") is an important determinant of texture segregation performance, it is not the only one. Evidence from several experiments suggests that configural effects are also important. That is, orientation-defined texture edges are strongest when the texture elements (on one side of the edge) are parallel to the edge. This result is not consistent with a number of texture segregation models including feature- and filter-based models. One possible explanation is that the second-order channel used to detect a texture edge of a particular orientation gives greater weight to first-order input channels of that same orientation.

Discrimination, Psychological↗

Processing in the probed-sinewave paradigm is likely retinal.

In the probed-sinewave paradigm-used to study the dynamics of light adaptation-a small probe of light is superimposed on a sinusoidally flickering background. Detection threshold for the probe is measured at various times with respect to the flickering background. Here we present such stimuli using three methods: monoptic (the probe and the flickering background are presented to the same eye), dichoptic (the probe is presented to one eye and the flickering background is presented to the other eye), and binocular (the probe and the flickering background are both presented to both eyes). The results suggest that the processing associated with detecting the probe is primarily in the retina (or any place with monocular input). However, the results also suggest a slight amount of processing in the cortex (or any place with binocular input), particularly at the higher frequency of flickering background used here (9.4 Hz vs. 1.2 Hz). A simple schematic model with three ocular-dominance channels is consistent with the results.

Adaptation, Ocular↗