Transfer matrix method for instantaneous spike rate estimation

K. Watanabe, Hiroyuki Tanaka, Keiji Miura, Masato Okada

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


The spike timings of neurons are irregular and are considered to be a one-dimensional point process. The Bayesian approach is generally used to estimate the time-dependent firing rate function from sequences of spike timings. It can also be used to estimate the firing rate from only a single sequence of spikes. However, the rate function has too many degrees of freedom in general, so approximation techniques are often used to carry out the Bayesian estimation. We applied the transfer matrix method, which efficiently computes the exact marginal distribution, to the estimation of the firing rate and developed an algorithm that enables the exact results to be obtained for the Bayesian framework. Using this estimation method, we investigated how the mismatch of the prior hyperparameter value affects the marginal distribution and the firing rate estimation.

Original languageEnglish
Pages (from-to)1362-1368
Number of pages7
JournalIEICE Transactions on Information and Systems
Issue number7
Publication statusPublished - 2009


  • Bayesian estimation
  • Smoothness prior
  • Spike rate estimation
  • Transfer matrix method

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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