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间隔与模式计时的神经计算模型。

Neurocomputational Models of Interval and Pattern Timing.

作者信息

Hardy Nicholas F, Buonomano Dean V

机构信息

Departments of Neurobiology and Psychology, and Integrative Center for Learning and Memory, University of California, Los Angeles, Los Angeles, CA 90095.

出版信息

Curr Opin Behav Sci. 2016 Apr;8:250-257. doi: 10.1016/j.cobeha.2016.01.012. Epub 2016 Feb 12.

Abstract

Most of the computations and tasks performed by the brain require the ability to tell time, and process and generate temporal patterns. Thus, there is a diverse set of neural mechanisms in place to allow the brain to tell time across a wide range of scales: from interaural delays on the order of microseconds to circadian rhythms and beyond. Temporal processing is most sophisticated on the scale of tens of milliseconds to a few seconds, because it is within this range that the brain must recognize and produce complex temporal patterns-such as those that characterize speech and music. Most models of timing, however, have focused primarily on simple intervals and durations, thus it is not clear whether they will generalize to complex pattern-based temporal tasks. Here, we review neurobiologically based models of timing in the subsecond range, focusing on whether they generalize to tasks that require placing consecutive intervals in the context of an overall pattern, that is, .

摘要

大脑执行的大多数计算和任务都需要具备计时能力,以及处理和生成时间模式的能力。因此,存在多种神经机制,使大脑能够在广泛的时间尺度上计时:从微秒级的双耳延迟到昼夜节律等等。时间处理在几十毫秒到几秒的尺度上最为复杂,因为正是在这个范围内,大脑必须识别并产生复杂的时间模式,例如那些表征语音和音乐的模式。然而,大多数计时模型主要集中在简单的间隔和持续时间上,因此尚不清楚它们是否能推广到基于复杂模式的时间任务中。在这里,我们回顾基于神经生物学的亚秒级计时模型,重点关注它们是否能推广到需要在整体模式的背景下放置连续间隔的任务,即 。

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