Construction and analysis of non-Gaussian spatial models of neural spiking activity
The spiking activity of rat CA1 hippocampal place cells during open field foraging can be described with stimulus-response models based on an inhomogeneous Poisson (IP) interspike interval probability model. The spatial structure of this model has been previously represented as a simple Gaussian surface. We analyze four new spatial models, two extensions of the Gaussian surface, a surface based on a logistic transformation, and a surface constructed by using Zernike polynomials. Goodness-of-fit analysis based on the Bayesian information criterion (BIC) shows that the Zernike polynomial surfaces give the most accurate description of the spatial place cell spiking activity under this experimental paradigm.
hippocampal place cells zernike polynomials interspike interval distribution inhomogeneous poisson process