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一种无需反馈兴奋即可实现快速精确的自我维持的头方向细胞路径整合模型。

A speed-accurate self-sustaining head direction cell path integration model without recurrent excitation.

机构信息

a Oxford Center for Theoretical Neuroscience and Artificial Intelligence, Department of Experimental Psychology , University of Oxford , Oxford , UK.

b Institute of Behavioural Neuroscience , University College London , London , UK.

出版信息

Network. 2018;29(1-4):37-69. doi: 10.1080/0954898X.2018.1559960.

DOI:10.1080/0954898X.2018.1559960
PMID:30905280
Abstract

The head direction (HD) system signals HD in an allocentric frame of reference. The system is able to update firing based on internally derived information about self-motion, a process known as path integration. Of particular interest is how path integration might maintain concordance between true HD and internally represented HD. Here we present a self-sustaining two-layer model, capable of self-organizing, which produces extremely accurate path integration. The implications of this work for future investigations of HD system path integration are discussed.

摘要

头部方向 (HD) 系统以一种以自我为中心的参考系来表示 HD。该系统能够根据关于自身运动的内部推导信息来更新其发射活动,这个过程被称为路径整合。特别有趣的是,路径整合如何保持真实 HD 和内部表示的 HD 之间的一致性。在这里,我们提出了一个能够自我组织的自维持两层模型,它能够产生极其准确的路径整合。本文讨论了这项工作对未来研究 HD 系统路径整合的意义。

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