Dr. Lauren Barghout Profile

Dr. Lauren Barghout

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Publications (3)

Proceedings Article | 3 June 1997 Paper

Seven models of masking

Stanley Klein, Thom Carney, Lauren Barghout-Stein, Christopher Tyler

Proceedings Volume 3016, (1997) https://doi.org/10.1117/12.274510

KEYWORDS: Transducers, Visual process modeling, Data modeling, Spatial frequencies, Visualization, Image compression, Visibility, Samarium, Medical imaging, Eye

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Proceedings Article | 3 June 1997 Paper

Partitioning mechanisms of masking: contrast transducer versus divisive inhibition

Lauren Barghout-Stein, Christopher Tyler, Stanley Klein

Proceedings Volume 3016, (1997) https://doi.org/10.1117/12.274550

KEYWORDS: Transducers, Interference (communication), Spatial frequencies, Systems modeling, Visualization, Psychophysics, Signal to noise ratio, Visual system, Target detection, Signal detection

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The properties of spatial vision mechanisms are often explored psychophysically with simultaneous masking paradigms. A variety of hypotheses have been proposed to explain how the mask pattern utilized in these paradigms increases threshold. Numerous studies have investigated the properties of a particular origin of masking hypothesis but few have attempted to compare the properties of masking at several points in the process. Our study isolates masking due to lateral divisive inhibition at a point where mechanism responses are combined, and compares it with masking of the same target due to a nonlinearity either intrinsic to a mechanism or directly operating on the response of a single mechanism. We also measure the slopes of psychometric functions to examine the relationship between uncertainty and mask contrast. Studies of simultaneous masking utilizing a pedestal mask (an identical test and mask pattern) have measured facilitation for low contrast masks. This decrease in threshold from the solo target threshold is commonly referred to as the 'dipper' effect and has been explained as an increase in signal-to- noise ratio from the high unmasked level occurring as the visual system becomes more certain of target location. The level of uncertainty is indicated by the slope of sensitivity to the target as a function of target contrast in the threshold region. In these studies, high contrast masks have evoked an increase in target threshold. There have been many theories explaining this threshold increase. Some suggest that masking is the result of an intrinsic nonlinearity within a mechanism or of a contrast nonlinearity that operates directly on the output of a single mechanism. Others put the source of masking at a gain control operation which occurs when a surrounding set of mechanisms divide the response of a single mechanism by their summed response. Still others attribute the masking to noise that is multiplicative relative to the neural response signal, or noise that intrudes on the detecting mechanism from neighboring mechanisms. A detailed review of this debate is provided by the paper by Klein et al., 3016-02 in this Proceedings. Threshold elevation functions that show the relationship between mask spatial frequency and masking magnitude cannot illuminate this debate, as we demonstrated at ARVO (1994). For that study, we generated threshold elevation functions (the ratio of unmasked versus masked target threshold) for multi-channel systems using computational models that invoked either divisive inhibition, a set of transducer nonlinearities or multiplicative noise. Threshold elevation functions were indistinguishable when each masking process was assumed to have similar strength. These results led us to design the experiment presented here, which attempts to compare the effects of two of these masking processes, lateral divisive inhibition and nonlinear transducer compression.

Proceedings Article | 17 March 1994 Paper

Computational reconstruction of the mechanisms of human stereopsis

Christopher Tyler, Lauren Barghout, Leonid Kontsevich

Proceedings Volume 2054, (1994) https://doi.org/10.1117/12.171143

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The properties of human stereoscopic mechanisms may be derived from dichoptic interaction and masking effects on stereoscopic detection thresholds in any relevant stimulus domain (spatial frequency, temporal frequency, disparity, orientation, etc.). The present study focuses on the spatial properties of mechanisms underlying stereoscopic depth detection. The computational approach is based on the full exploration of plausible model structures to characterize their idiosyncrasies, which often allows exclusion of proposed mechanisms by comparison with data obtained under conditions in which the idiosyncrasies should be expressed. For example, we conducted a detailed analysis of threshold elevation functions (TEFs) under plausible channel shapes, combination rules and masking behavior derived from previous studies. The analysis reveals that TEFs may be much narrower than and differ in shape from the underlying mechanisms. For example, only two discrete channels are required to produce TEFs peaking close to each fixed test frequency, with no relation to channel peaks. We apply this analysis to the stereospatial masking functions collected by Yang and Blake (1991) to determine the likely channel structure underlying the empirical masking performance. The analysis generally supports the two-mechanism model that they propose but shows that the assumptions underlying their estimates of the unmasked sensitivity function are incorrect. The analysis excludes stereospatial channels tuned below 2.5 c/deg, a region in which Schor, Wood, and Ogawa (1984) obtained evidence for many narrowly tuned channels by measuring disparity thresholds for targets with different peak tunings in the two eyes. Our computational model for the latter data is consistent with the lowest tuned channel being at 2.5 c/deg, this channel being narrowly tuned to dichoptic contrast differences, as described by Legge and Gu (1989) and Halpern and Blake (1988). Thus, all such stereo tuning data can be explained in a model in which all stereoscopic channels are tuned above 2.5 c/deg.

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