title: Stability and change in perception: spatial organization in temporal context.
abstract: Perceptual multistability has often been explained using the concepts of adaptation and hysteresis. In this paper we show that effects that would typically be accounted for by adaptation and hysteresis can be explained without assuming the existence of dedicated mechanisms for adaptation and hysteresis. Instead, our data suggest that perceptual multistability reveals lasting states of the visual system rather than changes in the system caused by stimulation. We presented observers with two successive multistable stimuli and found that the probability that they saw the favored organization in the first stimulus was inversely related to the probability that they saw the same organization in the second. This pattern of negative contingency is orientation-tuned and occurs no matter whether the observer had or had not seen the favored organization in the first stimulus. This adaptation-like effect of negative contingency combines multiplicatively with a hysteresis-like effect that increases the likelihood of the just-perceived organization. Both effects are consistent with a probabilistic model in which perception depends on an orientation-tuned intrinsic bias that slowly (and stochastically) changes its orientation tuning over time.
authors.affiliation: Vision Science, University of California at Berkeley, 360 Minor Hall, Berkeley, CA 94720-2020, USA. sergeg@uclink.berkeley.edu
authors.forename: Sergei
authors.initials: S
authors.lastname: Gepshtein
authors.forename: Michael
authors.initials: M
authors.lastname: Kubovy
mesh_terms: D000222:Adaptation, Physiological / Q000502:physiology*; D000328:Adult; D001921:Brain / Q000502:physiology*; D003657:Decision Making / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological; D015233:Models, Statistical; D015588:Observer Variation; D009949:Orientation / Q000502:physiology*; D010364:Pattern Recognition, Visual / Q000502:physiology*; D010775:Photic Stimulation; D013997:Time Factors