Josh M Salet, Wouter Kruijne, Hedderik van Rijn, Sander A Los, Martijn Meeter
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引用次数: 16
摘要
时间准备是在预测未来事件时发生的认知功能。这通常被认为涉及到在产生高危险的时间点上最大限度地准备的过程。然而,尽管它们在文献中占有突出地位,但基于风险的理论未能解释所有的经验准备现象。在这里,我们提出了形式化的时间准备多迹理论(fttp),这是一个综合模型,它发展了另一种观点,即时间准备是由联想学习产生的。ftp建立在间隔计时、运动规划和联想记忆领域的既定计算原理之上。在fmpp中,时间准备是由时间表征与抑制和激活运动单元之间的联想学习产生的。模拟表明,mptp可以解释各种时间尺度上的现象,从以秒为时间尺度的顺序效应到以周为时间尺度的长期记忆效应。我们将fmpp与依赖于风险函数的模型进行了对比,并表明fmpp的学习机制对于捕获全方位的经验效应至关重要。在一个使用高斯前周期分布的关键实验中,我们显示数据与mtp的预测一致,并偏离危险函数。此外,我们还演示了如何改变ftp的参数来解释参与者在准备过程中的差异。总之,我们提出了一个统一的计算框架来解释时间准备中的一系列现象,这些现象不能用传统的理论框架来共同解释。(PsycInfo Database Record (c) 2022 APA,版权所有)。
FMTP: A unifying computational framework of temporal preparation across time scales.
Temporal preparation is the cognitive function that takes place when anticipating future events. This is commonly considered to involve a process that maximizes preparation at time points that yield a high hazard. However, despite their prominence in the literature, hazard-based theories fail to explain the full range of empirical preparation phenomena. Here, we present the formalized multiple trace theory of temporal preparation (fMTP), an integrative model which develops the alternative perspective that temporal preparation results from associative learning. fMTP builds on established computational principles from the domains of interval timing, motor planning, and associative memory. In fMTP, temporal preparation results from associative learning between a representation of time on the one hand and inhibitory and activating motor units on the other hand. Simulations demonstrate that fMTP can explain phenomena across a range of time scales, from sequential effects operating on a time scale of seconds to long-term memory effects occurring over weeks. We contrast fMTP with models that rely on the hazard function and show that fMTP's learning mechanisms are essential to capture the full range of empirical effects. In a critical experiment using a Gaussian distribution of foreperiods, we show the data to be consistent with fMTP's predictions and to deviate from the hazard function. Additionally, we demonstrate how changing fMTP's parameters can account for participant-to-participant variations in preparation. In sum, with fMTP we put forward a unifying computational framework that explains a family of phenomena in temporal preparation that cannot be jointly explained by conventional theoretical frameworks. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
期刊介绍:
Psychological Review publishes articles that make important theoretical contributions to any area of scientific psychology, including systematic evaluation of alternative theories.