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This article is part of the supplement: Eighteenth Annual Computational Neuroscience Meeting: CNS*2009

Open Access Open Badges Oral presentation

Bayesian estimation of the time-varing rate and irregularity of neuronal firing

Takeaki Shimokawa* and Shigeru Shinomoto

Author Affiliations

Department of Physics, Kyoto University, Sakyo-ku, Kyoto 606-8502, Japan

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BMC Neuroscience 2009, 10(Suppl 1):O6  doi:10.1186/1471-2202-10-S1-O6

The electronic version of this article is the complete one and can be found online at:

Published:13 July 2009

© 2009 Shimokawa and Shinomoto; licensee BioMed Central Ltd.


Spike trains generated by cortical neurons possess specific characteristics such as firing irregularity (see Figure 1A) other than the firing rate. Recently, our study revealed that the firing irregularity is rather specific to individual neurons and invariant with the time and the modulation of firing rate by using a metric for analyzing the time-local irregularity of spike events [1,2]. On the other hand, it was also reported that the firing irregularity varied significantly according to behavioral contexts in some other cortical area [3]. Therefore, we wish to examine how easily the firing irregularity is varied with the firing rate more systematically. For this purpose, we developed a Bayesian estimation method that allows us to estimate both the instantaneous rate and irregularity for a given spike sequence [4]. In our new framework, we first consider the stochastic process of generating spikes under a given rate and irregularity, and then invert the conditional probability distribution to infer the rate and the irregularity from the data.

thumbnailFigure 1. (A) Sample sequences of events with identical rate and different irregularity, which may be termed bursty, random (Poisson), or regular. (B) The MAP estimate of the instantaneous rate λ(t) and irregularity κ(t) for the spike sequence {ti} recorded from a V1 neuron of a Macaque (nsa2004.4; Neural Signal Archive [5]).

We applied our new method to the experimentally recorded spike data taken from Neural Signal Archive [5] (see Figure 1B), and revealed that there is a systematic correlation between firing rate and firing irregularity, and that the degree of the variability in the firing irregularity greatly depends on the cortical areas.


This study was supported in part by Grants-in-Aid for Scientific Research to SS from the MEXT Japan. TS is supported by the Research Fellowship of the JSPS for Young Scientists.


  1. Shinomoto S, Shima K, Tanji J: Differences in spiking patterns among cortical neurons.

    Neural Comput 2003, 15:2823-2842. PubMed Abstract | Publisher Full Text OpenURL

  2. Shinomoto S, Miyazaki Y, Tamura H, Fujita I: Regional and laminar differences in in vivo firing patterns of primate cortical neurons.

    J Neurophysiol 2005, 94:567-575. PubMed Abstract | Publisher Full Text OpenURL

  3. Davies RM, Gerstein GL, Baker SN: Measurement of time-dependent changes in the irregularity of neural spiking.

    J Neurophysiol 2006, 96:906-918. PubMed Abstract | Publisher Full Text OpenURL

  4. Shimokawa T, Shinomoto S: Estimating instantaneous irregularity of neuronal firing.

    Neural Comput 2009, in press. PubMed Abstract | Publisher Full Text OpenURL

  5. Neural Signal Archive [] webcite