Diagnostic methods for statistical models of place cell spiking activity

被引:1
作者
Barbieri, R
Frank, LM
Quirk, MC
Wilson, MA
Brown, EN
机构
[1] Harvard Univ, Massachusetts Gen Hosp,Div Hlth Sci & Technol, Sch Med,MIT,Neurosci Stat Res Lab, Dept Anesthesia & Crit Care,Clin 3, Boston, MA 02114 USA
[2] MIT, Neurosci Res Ctr, RIKEN, Ctr Learning & Memory,Dept Brain & Cognit Sci, Cambridge, MA 02139 USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
hippocampal place cells; interspike interval distribution; inhomogeneous gamma process; inhomogeneous inverse gaussian process; quantile-quantile plot; intensity-rescaling transformation;
D O I
10.1016/S0925-2312(01)00450-7
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We analyze the stochastic structure of CA1 hippocampal place cell spiking activity with stimulus-response models based on inhomogeneous Poisson (IP), inhomogeneous gamma (IG) and inhomogeneous inverse Gaussian (IIG) interspike interval probability densities that have Markov dependence. We present a technique based on quantile-quantile (Q-Q) plots derived from the intensity-rescaling transformation, and use it along with Akaike's (AIC) and Bayesian (BIC) information critieria to assess model goodness of fit. The Q-Q plots give readily interpretable, graphical diagnostic methods of the model fits, and show that the IG and IIG models give more accurate descriptions of place cell spiking activity than the IP model. (C) 2001 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:1087 / 1093
页数:7
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