Tracking Temporal Evolution of Nonlinear Dynamics in Hippocampus using Time-Varying Volterra Kernels

被引：14

作者：

Chan, Rosa H. M. ^{[1
]}

Song, Dong ^{[1
]}

Berger, Theodore W. ^{[1
]}

机构：

[1] Univ So Calif, Dept Biomed Engn, Los Angeles, CA 90089 USA

来源：

2008 30TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-8 | 2008年

关键词：

D O I：

10.1109/IEMBS.2008.4650336

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Hippocampus and other parts of the cortex are not stationary, but change as a function of time and experience. The goal of this study is to apply adaptive modeling techniques to the tracking of multiple-input, multiple-output (MIMO) nonlinear dynamics underlying spike train transformations across brain subregions, e.g. CA3 and CA1 of the hippocampus. A stochastic state point process adaptive filter will be used to track the temporal evolutions of both feedforward and feedback kernels in the natural flow of multiple behavioral events.

引用

页码：4996 / 4999

页数：4

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