Diagnostic methods for statistical model of place cell spiking activity

摘要

We analyze the stochastic structure of Cal hippocampal place ell 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 Form the intensity-rescaling transformation, and use it along with Akaike's (AIC) and Bayesin (EIC) information criteria 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 description of place cell spiking activity than the IP model.