A statistical perspective to visual masking

Sevda Agaoglu; Mehmet N Agaoglu; Bruno Breitmeyer; Haluk Ogmen

doi:10.1016/j.visres.2015.07.003

A statistical perspective to visual masking

Vision Res. 2015 Oct;115(Pt A):23-39. doi: 10.1016/j.visres.2015.07.003. Epub 2015 Aug 24.

Authors

Sevda Agaoglu¹, Mehmet N Agaoglu¹, Bruno Breitmeyer², Haluk Ogmen³

Affiliations

¹ Department of Electrical and Computer Engineering, University of Houston, N308 Engineering Building 1, Houston, TX 77204-4005, USA; Center for Neuro-Engineering and Cognitive Science, University of Houston, Houston, TX 77204-4005, USA.
² Department of Psychology, University of Houston, Houston, TX 77204-5022, USA; Center for Neuro-Engineering and Cognitive Science, University of Houston, Houston, TX 77204-4005, USA.
³ Department of Electrical and Computer Engineering, University of Houston, N308 Engineering Building 1, Houston, TX 77204-4005, USA; Center for Neuro-Engineering and Cognitive Science, University of Houston, Houston, TX 77204-4005, USA. Electronic address: ogmen@uh.edu.

PMID: 26238247
DOI: 10.1016/j.visres.2015.07.003

Abstract

A stimulus (mask) reduces the visibility of another stimulus (target) when they are presented in close spatio-temporal vicinity of each other, a phenomenon called visual masking. Visual masking has been extensively studied to understand dynamics of information processing in the visual system. In this study, we adopted a statistical point of view, rather than a mechanistic one, to investigate how mask-related activities might influence target-related ones within the context of visual masking. We modeled the distribution of response errors of human observers in three different visual masking experiments, namely para-/meta-contrast masking, pattern masking by noise, and pattern masking by structure. We adopted statistical models, which have been used previously in studies of visual short-term memory, to capture response characteristics of observers under masking conditions. We tested the following scenarios: (i) mask activity may reduce a target's signal-to-noise ratio (SNR) without interfering with its encoding precision. (ii) Mask activity may "interfere" with the encoding of a target and cause decreased precision in observer's reports. (iii) Decreased performance due to masking may result from the confusion or "misbinding" of a mask's features with those of the target, when they are similar as in the case of pattern masking by structure. Our results show that in all three types of masking, the reduction of a target's SNR was the primary process whereby masking occurred. A significant decrease, correlated with masking strength, in the precision of the target's encoding was observed in para-/meta-contrast and pattern masking by structure, but not in pattern masking by noise. We interpret these findings as the mask reducing the target's SNR (i) by suppressing or interrupting the signal of the target in para-/meta-contrast, (ii) by increasing noise in pattern masking by noise, and (iii) a combination of the two in pattern masking by structure.

Keywords: Metacontract; Noise masking; Paracontrast; Statistical mixture models; Structure masking; Visual masking.

MeSH terms

Contrast Sensitivity / physiology
Humans
Memory, Short-Term / physiology
Models, Statistical*
Pattern Recognition, Visual / physiology*
Perceptual Masking / physiology*
Photic Stimulation / methods
Reaction Time / physiology
Signal-To-Noise Ratio