Characterization of and compensation for the nonstationarity of spike shapes during physiological recordings

作     者：Penev, PS Dimitrov, AG Miller, JP 

作者机构：Rockefeller Univ Lab Computat Neurosci New York NY 10021 USA Montana State Univ Ctr Computat Biol Bozeman MT 59717 USA 

出 版 物：《NEUROCOMPUTING》 (神经计算)

年 卷 期：2001年第38卷

页      面：1695-1701页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Institutes of Health  NIH  (MH57179  MH12159) 

主　　题：independent manifolds factorial coding spike sorting cricket 

摘      要：In a typical neurophysiological recording, the shape of the voltage trace due to an action potential depends, among other things, on the mutual geometry of the tissue and the electrode, and on the overall health of the preparation, These parameters change throughout the duration of the experiment, typically continuously and slowly, with occasional abrupt jumps. Here we propose a method to characterize such slow drifts by the estimation of a one-dimensional curved manifold, embedded in the large-dimensional space of spike shapes, along which the data cluster. We model each event as the closest point on this manifold, which is the maximum-likelihood expectation of its spike shape, and a residual, which can be analyzed subsequently. We apply the method to both intra- and extracellular recordings. (C) 2001 Published by Elsevier Science B.V.