School of Psychology, University of Southampton, Southampton SO17 1BJ, UK.
J Neurosci. 2010 Nov 3;30(44):14745-9. doi: 10.1523/JNEUROSCI.2749-10.2010.
The human visual system adapts to the changing statistics of its environment. For example, the light-from-above prior, an assumption that aids the interpretation of ambiguous shading information, can be modified by haptic (touch) feedback. Here we investigate the mechanisms that drive this adaptive learning. In particular, we ask whether visual information can be as effective as haptics in driving visual recalibration and whether increased information (feedback from multiple modalities) induces faster learning. During several hours' training, feedback encouraged observers to modify their existing light-from-above assumption. Feedback was one of the following: (1) haptic only, (2) haptic and stereoscopic (providing binocular shape information), or (3) stereoscopic only. Haptic-only feedback resulted in substantial learning; the perceived shape of shaded objects was modified in accordance with observers' new light priors. However, the addition of continuous visual feedback (condition 2) substantially reduced learning. When visual-only feedback was provided intermittently (condition 3), mimicking the time course of the haptic feedback of conditions 1 and 2, substantial learning returned. The intermittent nature of conflict information, or feedback, appears critical for learning. It causes an initial, erroneous percept to be corrected. Contrary to previous proposals, we found no particular advantage for cross-modal feedback. Instead, we suggest that an "oops" factor drives efficient learning; recalibration is prioritized when a mismatch exists between sequential representations of an object property. This "oops" factor appears important both across and within sensory modalities, suggesting a general principle for perceptual learning and recalibration.
人类视觉系统会适应环境统计信息的变化。例如,光来自上方的先验假设(一种有助于解释模糊阴影信息的假设)可以通过触觉(触摸)反馈进行修改。在这里,我们研究了驱动这种自适应学习的机制。特别是,我们要问视觉信息是否可以像触觉一样有效地驱动视觉重新校准,以及增加信息(来自多种模式的反馈)是否会诱导更快的学习。在数小时的训练中,反馈鼓励观察者修改他们现有的光来自上方的假设。反馈有以下几种:(1)仅触觉,(2)触觉和立体(提供双目形状信息),或(3)仅立体。仅触觉反馈导致了大量的学习;阴影物体的感知形状根据观察者的新光先验进行了修改。然而,添加连续的视觉反馈(条件 2)大大减少了学习。当仅提供间歇性的视觉反馈(条件 3)时,模仿了条件 1 和 2 的触觉反馈的时间进程,大量的学习又回来了。冲突信息(或反馈)的间歇性似乎对学习至关重要。它会纠正初始的错误感知。与之前的提议相反,我们没有发现跨模式反馈的特殊优势。相反,我们认为“哎呀”因素驱动了有效的学习;当物体属性的连续表示之间存在不匹配时,重新校准会被优先处理。这个“哎呀”因素似乎在跨感觉模式和在感觉模式内都很重要,这表明了一种用于感知学习和重新校准的一般原则。