WHAT CAN TOPOLOGY TELL US ABOUT THE NEURAL CODE?

被引：54
|
作者：
Curto, Carina [1 ]
机构：
[1] Penn State Univ, Dept Math, State Coll, PA 16801 USA
来源：
BULLETIN OF THE AMERICAN MATHEMATICAL SOCIETY | 2017年 / 54卷 / 01期
关键词：
PERSISTENT HOMOLOGY; MODEL;
D O I：
10.1090/bull/1554
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
Neuroscience is undergoing a period of rapid experimental progress and expansion. New mathematical tools, previously unknown in the neuroscience community, are now being used to tackle fundamental questions and analyze emerging data sets. Consistent with this trend, the last decade has seen an uptick in the use of topological ideas and methods in neuroscience. In this paper I will survey recent applications of topology in neuroscience, and explain why topology is an especially natural tool for understanding neural codes.
引用
收藏
页码：63 / 78
页数：16
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