title: Classification images and bubbles images in the generalized linear model.
abstract: Classification images and bubbles images are psychophysical tools that use stimulus noise to investigate what features people use to make perceptual decisions. Previous work has shown that classification images can be estimated using the generalized linear model (GLM), and here I show that this is true for bubbles images as well. Expressing the two approaches in terms of a single statistical model clarifies their relationship to one another, makes it possible to measure classification images and bubbles images simultaneously, and allows improvements developed for one method to be used with the other.
authors: Department of Psychology and Centre for Vision Research, York University, Toronto, ON, Canada. rfm@yorku.ca
authors: Richard F
authors: RF
authors: Murray
mesh_terms: D006801:Humans; D016014:Linear Models; D008959:Models, Neurological; D010775:Photic Stimulation / Q000379:methods*; D011601:Psychophysics / Q000379:methods*; D017603:Signal Detection, Psychological / Q000502:physiology; D014796:Visual Perception / Q000502:physiology*