Harrison S J, Backus B T
SUNY College of Optometry, 33 West 42nd Street, New York, NY 10036, United States.
Vision Res. 2010 Aug 23;50(18):1905-11. doi: 10.1016/j.visres.2010.06.013. Epub 2010 Jun 25.
Visual appearance depends upon the resolution of ambiguities that arise when 2D retinal images are interpreted as 3D scenes. This resolution may be characterized as a form of Bayesian perceptual inference, whereby retinal sense data combine with prior belief to yield an interpretation. Under this framework, the prior reflects environmental statistics, so an efficient system should learn by changing its prior after exposure to new statistics. We conjectured that a prior would only be modified when sense data contain disambiguating information, such that it is clear what bias is appropriate. This conjecture was tested by using a perceptually bistable stimulus, a rotating wire-frame cube, as a sensitive indicator of changes in the prior for 3D rotation direction, and by carefully matching perceptual experience of ambiguous and unambiguous versions of the stimulus across three groups of observers. We show for the first time that changes in the prior-observed as a change in bias that resists reverse learning the next day-is affected more by ambiguous stimuli than by disambiguated stimuli. Thus, contrary to our conjecture, modification of the prior occurred preferentially when the observer actively resolved ambiguity rather than when the observer was exposed to environmental contingencies. We propose that resolving stimuli that are not easily interpreted by existing visual rules must be a valid method for establishing useful perceptual biases in the natural world.
视觉外观取决于对二维视网膜图像进行三维场景解释时出现的模糊性的解决。这种解决方式可以被描述为一种贝叶斯感知推理形式,即视网膜感官数据与先验信念相结合以产生一种解释。在此框架下,先验反映环境统计信息,因此一个高效的系统应该在接触新的统计信息后通过改变其先验来进行学习。我们推测,只有当感官数据包含消除歧义的信息时,先验才会被修改,这样才能明确何种偏差是合适的。我们通过使用一种感知双稳刺激(一个旋转的线框立方体)作为三维旋转方向先验变化的敏感指标,并通过仔细匹配三组观察者对刺激的模糊和明确版本的感知体验,来检验这一推测。我们首次表明,先验的变化(表现为一种第二天能抵抗反向学习的偏差变化)受模糊刺激的影响比受明确刺激的影响更大。因此,与我们的推测相反,先验的修改优先发生在观察者主动解决模糊性时,而不是在观察者接触环境偶然性时。我们提出,解决现有视觉规则难以解释的刺激必定是在自然世界中建立有用感知偏差的一种有效方法。