Article,

Diagnostic methods for statistical models of place cell spiking activity

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Neurocomputing, (June 2001)

Abstract

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.

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