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神经计算模型在时间感知中的应用。

Neurocomputational models of time perception.

机构信息

Bernstein Center for Computational Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim of Heidelberg University, J 5, 68159, Mannheim, Germany,

出版信息

Adv Exp Med Biol. 2014;829:49-71. doi: 10.1007/978-1-4939-1782-2_4.

Abstract

Mathematical modeling is a useful tool for understanding the neurodynamical and computational mechanisms of cognitive abilities like time perception, and for linking neurophysiology to psychology. In this chapter, we discuss several biophysical models of time perception and how they can be tested against experimental evidence. After a brief overview on the history of computational timing models, we list a number of central psychological and physiological findings that such a model should be able to account for, with a focus on the scaling of the variability of duration estimates with the length of the interval that needs to be estimated. The functional form of this scaling turns out to be predictive of the underlying computational mechanism for time perception. We then present four basic classes of timing models (ramping activity, sequential activation of neuron populations, state space trajectories and neural oscillators) and discuss two specific examples in more detail. Finally, we review to what extent existing theories of time perception adhere to the experimental constraints.

摘要

数学建模是理解时间感知等认知能力的神经动力学和计算机制的有用工具,并可将神经生理学与心理学联系起来。在本章中,我们讨论了几种时间感知的生物物理模型,以及如何根据实验证据对它们进行检验。在简要概述计算定时模型的历史之后,我们列出了此类模型应该能够解释的一些重要的心理和生理发现,重点是与需要估计的间隔长度成比例的持续时间估计的可变性。这种缩放的函数形式对于时间感知的基础计算机制具有预测性。然后,我们提出了四个基本类别的定时模型(斜坡活动、神经元群体的顺序激活、状态空间轨迹和神经振荡器),并更详细地讨论了两个具体示例。最后,我们回顾了现有的时间感知理论在多大程度上符合实验约束。

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