Modeling perceptual discrimination in dynamic noise: Time-changed diffusion and release from inhibition

The speed and accuracy of discrimination of featurally-defined stimuli such as letters, oriented bars, and Gabor patches are reduced when they are embedded in dynamic visual noise, but, unlike other discriminability manipulations, dynamic noise produces significant shifts of RT distributions on the time axis. These shifts appear to be associated with a delay in the onset of evidence accumulation by a decision process until a stable perceptual representation of the stimulus has formed. We consider two models for this task, which assume that evidence accumulation and perceptual processes are dynamically coupled. One is a time-changed diffusion model in which the drift and diffusion coefficient grow in proportion to one another. The other is a release from inhibition model, in which the emerging perceptual representation modulates an Ornstein–Uhlenbeck decay coefficient. Both models successfully reproduce the families of RT distributions found in the dynamic noise task, including the shifts in the leading edge of the distribution and the pattern of fast errors. We conclude that both models are plausible psychological models for this task.