Perceptual interaction of local motion signals
- PMID: 27902829
- PMCID: PMC5132080
- DOI: 10.1167/16.14.22
Perceptual interaction of local motion signals
Abstract
Motion signals are a rich source of information used in many everyday tasks, such as segregation of objects from background and navigation. Motion analysis by biological systems is generally considered to consist of two stages: extraction of local motion signals followed by spatial integration. Studies using synthetic stimuli show that there are many kinds and subtypes of local motion signals. When presented in isolation, these stimuli elicit behavioral and neurophysiological responses in a wide range of species, from insects to mammals. However, these mathematically-distinct varieties of local motion signals typically co-exist in natural scenes. This study focuses on interactions between two kinds of local motion signals: Fourier and glider. Fourier signals are typically associated with translation, while glider signals occur when an object approaches or recedes. Here, using a novel class of synthetic stimuli, we ask how distinct kinds of local motion signals interact and whether context influences sensitivity to Fourier motion. We report that local motion signals of different types interact at the perceptual level, and that this interaction can include subthreshold summation and, in some subjects, subtle context-dependent changes in sensitivity. We discuss the implications of these observations, and the factors that may underlie them.
Figures
error bars indicate 95% CIs determined by bootstrap. Data are shown with a line color indicating glider parity (red: white G; blue: black G; green: pure F [no G]) and line style indicating the maximal motion strength at the end of the ray (solid: CF = 0, CG = 1; dashed: CF = 0.05, CG = 0.95; dot-dash: CF = 0.1, CG = 0.5; dotted: CF = 0.1, CG = 0). Black solid lines show the Weibull fit. The central plot shows all of the fits superimposed. In each panel, Weibull functions had the same shape parameter: b = 1.65 in Panel A, b = 1.70 in Panel B. Subject EIN, dataset 1.
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