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第453期“工物学术论坛”:利用量子探测器搜寻(轴子暗光子等)超轻波动型暗物质
分子筛膜多维构筑基元与传输分离机制
氢能的电化学获取与利用
“清美”沙龙 | 世俗生活的象征——《根特祭坛画》中的灰色画
报告题目:
小鼠海马CA1记忆功能的神经元网络编码
 报告人:
林龙年
脑功能基因组学教育部重点实验室
华东师范大学 副教授
报告时间:
2005-10-28 10:00
报告地点:
生命科学楼一楼 报告厅
主办单位:
医学院
  简介:

报告题目: 小鼠海马CA1记忆功能的神经元网络编码 

报告人: 林龙年 副教授

华东师范大学 脑功能基因组学教育部重点实验室

http://www.ecnu.edu.cn/sbg/faculties.htm

时间:

1028日上午10:00-11:30

地点:

生命科学楼一楼 报告厅

主办单位:医学院

  内容简介: 

To examine the network-level organizing principles by

which the brain achieves its real-time encoding of episodic information, we have

developed a 96-channel array to simultaneously record the activity patterns of

as many as 260 individual neurons in the mouse hippocampus during various

startling episodes. We find that the mnemonic startling episodes triggered

firing changes in a set of CA1 neurons in both startle-type and

environment-dependent manners. Pattern classification methods reveal that these

firing changes form distinct ensemble representations in a low-dimensional

encoding subspace. Application of a sliding window technique further enabled us

to reliably capture not only the temporal dynamics of real-time network encoding

but also postevent processing of newly formed ensemble traces. Our analyses

revealed that the network-encoding power is derived from a set of functional

coding units, termed neural cliques, in the CA1 network. The individual neurons

within neural cliques exhibit ‘‘collective cospiking’’ dynamics that allow the

neural clique to overcome the response variability of its members and to achieve

real-time encoding robustness. Conversion of activation patterns of these coding

unit assemblies into a set of real-time digital codes permits concise and

universal representation and categorization of discrete behavioral episodes

across different individual brains.

 

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