Dynamic visual noise affects ill-defined, not well-defined, images. Issue 1 (2nd January 2020) - Chubala, Chrissy M.; Ensor, Tyler M.; Neath, Ian; Surprenant, Aimée M.
ABSTRACT: Dynamic visual noise (DVN), a matrix of squares that randomly alternate between black and white, interferes with some but not all tasks that involve visuo-spatial processing. Although visual working memory is generally invoked to explain the detrimental effects of DVN, the failure of DVN to impair memory for some stimuli that should be processed via visual working memory has not been satisfactorily explained. The image-definition hypothesis proposes that DVN will impair only ill-defined, not well-defined, images. We report five experiments that test this hypothesis. Experiments 1 and 2 use stimuli that lead to well-defined visual images (matrices, photographs of common objects) and no effect of DVN was observed. In contrast, Experiments 3 and 4 use stimuli that lead to ill-defined visual images (textures, photographs of snowflakes) and DVN affected performance. Experiment 5 demonstrated that a potentially disconfirmatory result in the literature was due to analysing proportion correct rather than a measure of discriminability. These results offer initial support for the image-definition hypothesis, and we discuss the implications for theories explaining DVN.