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.
%0 Journal Article
%1 Barb_2001_1087
%A Barbieri, Riccardo
%A Frank, Loren M.
%A Quirk, Michael C.
%A Wilson, Matthew A.
%A Brown, Emery N.
%D 2001
%J Neurocomputing
%K Gaussian Hippocampal Inhomogeneous Intensity-rescaling Interspike Quantile-quantile cells, distribution, gamma interval inverse place plot, process, transformation.
%P 1087--1093
%T Diagnostic methods for statistical models of place cell spiking activity
%U http://www.sciencedirect.com/science/article/B6V10-435KK2K-54/2/ed7422dc22aacb650b8ed8bdb84dffdb
%V 38-40
%X 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.
@article{Barb_2001_1087,
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.},
added-at = {2009-06-03T11:20:58.000+0200},
author = {Barbieri, Riccardo and Frank, Loren M. and Quirk, Michael C. and Wilson, Matthew A. and Brown, Emery N.},
biburl = {https://www.bibsonomy.org/bibtex/2a2cc6c852719e9dc681626aa6e7306fa/hake},
description = {The whole bibliography file I use.},
file = {Barb_2001_1087.pdf:Barb_2001_1087.pdf:PDF},
interhash = {32cfc40139c096e7a81d4367c3e65a9e},
intrahash = {a2cc6c852719e9dc681626aa6e7306fa},
journal = {Neurocomputing},
keywords = {Gaussian Hippocampal Inhomogeneous Intensity-rescaling Interspike Quantile-quantile cells, distribution, gamma interval inverse place plot, process, transformation.},
month = {June},
pages = {1087--1093},
timestamp = {2009-06-03T11:21:01.000+0200},
title = {Diagnostic methods for statistical models of place cell spiking activity},
url = {http://www.sciencedirect.com/science/article/B6V10-435KK2K-54/2/ed7422dc22aacb650b8ed8bdb84dffdb},
volume = {38-40},
year = 2001
}