Li Qinglin, Meso Andrew Isaac, Logothetis Nikos K, Keliris Georgios A
Department of Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.
IMPRS for Cognitive and Systems Neuroscience, University Tuebingen, Tübingen, Germany.
Front Neurosci. 2019 May 28;13:523. doi: 10.3389/fnins.2019.00523. eCollection 2019.
Sensory input is inherently ambiguous but our brains achieve remarkable perceptual stability. Prior experience and knowledge of the statistical properties of the world are thought to play a key role in the stabilization process. Individual differences in responses to ambiguous input and biases toward one or the other interpretation could modulate the decision mechanism for perception. However, the role of perceptual bias and its interaction with stimulus spatial properties such as regularity and element density remain to be understood. To this end, we developed novel bi-stable moving visual stimuli in which perception could be parametrically manipulated between two possible mutually exclusive interpretations: transparently or coherently moving. We probed perceptual stability across three composite stimulus element density levels with normal or degraded regularity using a factorial design. We found that increased density led to the amplification of individual biases and consequently to a stabilization of one interpretation over the alternative. This effect was reduced for degraded regularity, demonstrating an interaction between density and regularity. To understand how prior knowledge could be used by the brain in this task, we compared the data with simulations coming from four different hierarchical models of causal inference. These models made different assumptions about the use of prior information by including conditional priors that either facilitated or inhibited motion direction integration. An architecture that included a prior inhibiting motion direction integration consistently outperformed the others. Our results support the hypothesis that direction integration based on sensory likelihoods maybe the default processing mode with conditional priors inhibiting integration employed in order to help motion segmentation and transparency perception.
感觉输入本质上是模糊的,但我们的大脑却能实现显著的感知稳定性。人们认为,先前的经验以及对世界统计特性的了解在这一稳定过程中起着关键作用。对模糊输入的反应存在个体差异,以及对一种或另一种解释的偏向,可能会调节感知的决策机制。然而,感知偏向的作用及其与刺激空间特性(如规律性和元素密度)的相互作用仍有待了解。为此,我们开发了新颖的双稳态移动视觉刺激,其中感知可以在两种可能相互排斥的解释之间进行参数化操作:透明移动或连贯移动。我们使用析因设计,在具有正常或降低规律性的三种复合刺激元素密度水平上探究了感知稳定性。我们发现,密度增加会导致个体偏向的放大,从而使一种解释相对于另一种解释更加稳定。对于降低的规律性,这种效应会减弱,这表明密度和规律性之间存在相互作用。为了理解大脑如何在这项任务中利用先前的知识,我们将数据与来自四种不同因果推理层次模型的模拟结果进行了比较。这些模型对先前信息的使用做出了不同假设,包括促进或抑制运动方向整合的条件先验。一个包含抑制运动方向整合的先验的架构始终优于其他架构。我们的结果支持这样一种假设,即基于感官可能性的方向整合可能是默认的处理模式,而条件先验抑制整合则被用于帮助运动分割和透明感知。