Neural codes and homotopy types: mathematical models of place field recognition

Y. Manin
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引用次数: 15

Abstract

This note is a brief survey of some results of the recent collaboration of neurobiologists and mathematicians dedicated to stimulus reconstruction from neuronal spiking activity. This collaboration, in particular, led to the consideration of binary codes used by brain for encoding a stimuli domain such as a rodent's territory through the combinatorics of its covering by local neighborhoods. The survey is addressed to mathematicians (cf. [DeSch01]) and focuses on the idea that stimuli spaces are represented by the relevant neural codes as simplicial sets and thus encode say, the homotopy type of space if local neighborhoods are convex (see [CuIt08], [CuItVCYo13], [Yo14], [SiGh07]).}
神经编码与同伦类型:位置场识别的数学模型
本文简要介绍了神经生物学家和数学家最近合作的一些成果,这些成果致力于从神经元尖峰活动中重建刺激。特别是,这种合作导致了大脑使用二进制代码来编码刺激域的考虑,例如啮齿动物的领土通过其局部邻居覆盖的组合。这一调查是针对数学家的(参见[DeSch01]),并着重于刺激空间被相关的神经编码表示为简单集的想法,从而编码说,如果局部邻域是凸的空间的同格类型(参见[CuIt08], [CuItVCYo13], [Yo14], [SiGh07])。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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