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多稳态知觉中主导相位分布的历史依赖性变化。

History-dependent changes to distribution of dominance phases in multistable perception.

机构信息

Department of General Psychology and Methodology, University of Bamberg, Bamberg, Bavaria, Germany.

Research Group EPÆG (Ergonomics, Psychological Æsthetics, Gestalt), Bamberg, Bavaria, Germany.

出版信息

J Vis. 2023 Mar 1;23(3):16. doi: 10.1167/jov.23.3.16.

Abstract

Multistability - spontaneous switches of perception when viewing a stimulus compatible with several percepts - is often characterized by the distribution of durations of dominance phases. For continuous viewing conditions, these distributions are similar for various multistable displays and share two characteristic features: a Gamma-like distribution shape and dependence of dominance durations on the perceptual history. Both properties depend on a balance between self-adaptation (also conceptualized as a weakening stability prior) and noise. Prior experimental work and simulations that systematically manipulated displays showed that faster self-adaptation leads to a more "normal-like" distribution and, typically, to more regular dominance durations. We used a leaky integrator approach to estimate accumulated differences in self-adaptation between competing representations and used it as a predictor when fitting two parameters of a Gamma distribution independently. We confirmed earlier work showing that larger differences in self-adaptation led to a more "normal-like" distribution suggesting similar mechanisms that rely on the balance between self-adaptation and noise. However, these larger differences led to less regular dominance phases suggesting that longer times required for recovery from adaptation give noise more chances to induce a spontaneous switch. Our results also remind us that individual dominance phases are not "independent and identically distributed."

摘要

多稳态性——当观看与多种知觉相容的刺激时,知觉会自发地发生转换——通常表现为主导阶段持续时间的分布特征。对于连续的观看条件,这些分布在各种多稳态显示中是相似的,并具有两个特征:伽马样分布形状和主导持续时间对知觉历史的依赖性。这两个特性都取决于自我适应(也可以概念化为稳定性先验的削弱)和噪声之间的平衡。之前的实验工作和模拟系统地操纵显示表明,更快的自我适应导致更“正态样”的分布,通常导致更规则的主导持续时间。我们使用漏积分器方法来估计竞争表示之间自我适应的累积差异,并在独立拟合伽马分布的两个参数时将其用作预测因子。我们证实了早期的工作,表明更大的自我适应差异导致更“正态样”的分布,这表明了依赖于自我适应和噪声之间平衡的类似机制。然而,这些更大的差异导致主导阶段的规则性降低,这表明从适应中恢复所需的时间越长,噪声就越有可能引发自发转换。我们的结果还提醒我们,个体主导阶段并非“独立同分布”。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1f66/10064931/cca272c9bace/jovi-23-3-16-f001.jpg

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