MODELLING AND SIMULATION OF A NEUROPHYSIOLOGICAL EXPERIMENT BY SPATIO-TEMPORAL POINT PROCESSES

Viktor Beneš, Blažena Frcalová

Abstract

We present a stochastic model of an experimentmonitoring the spiking activity of a place cell of hippocampus of an experimental animal moving in an arena. Doubly stochastic spatio-temporal point process is used to model and quantify overdispersion. Stochastic intensity is modelled by a Lévy based random field while the animal path is simplified to a discrete random walk. In a simulation study first a method suggested previously is used. Then it is shown that a solution of the filtering problem yields the desired inference to the random intensity. Two approaches are suggested and the new one based on finite point process density is applied. Using Markov chain Monte Carlo we obtain numerical results from the simulated model. The methodology is discussed.

Keywords
filtering; overdispersion; spatio-temporal point process; spike train

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DOI: 10.5566/ias.v27.p47-52

Image Analysis & Stereology
EISSN 1854-5165 (Electronic version)
ISSN 1580-3139 (Printed version)