Sensory perception, motor control, and cognition necessitate reliable timing in the range of milliseconds to seconds, which implies the existence of a highly accurate timing system. Yet, partly owing to the fact that temporal processing is modulated by contextual factors, perceived time is not isomorphic to physical time. Temporal estimates exhibit regression to the mean of an interval distribution (global context) and are also affected by preceding trials (local context). Recent Bayesian models of interval timing have provided important insights regarding these observations, but questions remain as to how exposure to past intervals shapes perceived time. In this article, we provide a brief overview of Bayesian models of interval timing and their contribution to current understanding of context effects. We then proceed to highlight recent developments in the field concerning precision weighting of Bayesian evidence in both healthy timing and disease and the neurophysiological and neurochemical signatures of timing prediction errors. We further aim to bring attention to current outstanding questions for Bayesian models of interval timing, such as the likelihood conceptualization. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

中文翻译：

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间隔时间的贝叶斯模型中的时间背景：最近的进展和未来的方向。

感官知觉、运动控制和认知需要毫秒到秒范围内的可靠计时，这意味着存在高度准确的计时系统。然而，部分由于时间处理受上下文因素调节的事实，感知时间与物理时间不同。时间估计显示回归到区间分布的平均值（全局上下文），并且还受到先前试验（局部上下文）的影响）。最近的间隔时间贝叶斯模型为这些观察提供了重要的见解，但关于过去间隔如何影响感知时间的问题仍然存在。在本文中，我们简要概述了间隔时间的贝叶斯模型及其对当前理解上下文效应的贡献。然后，我们继续强调该领域的最新进展，即贝叶斯证据在健康时间和疾病中的精确加权以及时间预测误差的神经生理学和神经化学特征。我们进一步旨在引起人们对间隔时间贝叶斯模型的当前突出问题的关注，例如可能性概念化。（PsycInfo 数据库记录 (c) 2022 APA，保留所有权利）。