Perceptual judgments of sequential stimuli are systematically biased by prior expectations and by the temporal structure of sensory input. In haptic discrimination tasks, these effects often manifest as time-order asymmetries, whereby the perceived difference between two stimuli depends on their presentation order. Here, we introduce a dynamical Bayesian model that accounts for these biases by combining noisy sensory measurements with an evolving internal representation of stimulus intensity. The model formalizes perception as an inference process in which prior expectations are updated by incoming stimuli and propagate in time between observations. We test the model on psychophysical data from vibrotactile discrimination experiments, in which participants compare pairs of sequential stimuli with varying intensities. With a small number of parameters, the model quantitatively reproduces both the direction and magnitude of time-order effects across subjects, as well as the observed inter-individual variability. The inferred parameters provide a compact description of perceptual biases in terms of prior expectations and noise characteristics. Beyond fitting the data, the model induces a transformation of stimulus space, leading to a subject-dependent geometry of perceived stimuli. In this transformed space, perceptual judgments exhibit approximate symmetries that are absent in the physical stimulus coordinates. These results suggest that temporal biases in perception can be understood as a consequence of dynamical inference, and that they impose non-trivial geometric constraints on perceptual representations.

翻译：对连续刺激的感知判断会系统地受到先验期望和感觉输入时间结构的影响。在触觉辨别任务中，这些效应常表现为时间顺序不对称性，即两个刺激的感知差异取决于其呈现顺序。本文引入动态贝叶斯模型，通过结合含噪感觉测量与刺激强度的演化式内部表征来解释这些偏差。该模型将感知形式化为推断过程：先验期望由传入刺激持续更新并随时间在观测间传递。我们通过振动触觉辨别实验的心理物理数据验证模型——在该实验中，参与者比较了多对强度变化的连续刺激。借助少量参数，模型定量再现了受试者时间顺序效应的方向与幅度，以及观察到的个体间差异。推断出的参数通过先验期望和噪声特征提供了感知偏差的紧凑描述。除拟合数据外，该模型还诱导了刺激空间的变换，形成了与受试者相关的感知刺激几何结构。在此变换空间中，感知判断呈现出物理刺激坐标系中缺失的近似对称性。结果表明，感知中的时间偏差可理解为动态推断的结果，且这些偏差对感知表征施加了非平凡的几何约束。