Estimating membrane resistance over dendrite using Markov random field

Jun Kitazono, Toshiaki Omori, Toru Aonishi, Masato Okada

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


With developments in optical imaging over the past decade, statistical methods for estimating dendritic membrane resistance from observed noisy signals have been proposed. In most of previous studies, membrane resistance over a dendritic tree was assumed to be constant, or membrane resistance at a point rather than that over a dendrite was investigated. Membrane resistance, however, is actually not constant over a dendrite. In a previous study, a method was proposed in which membrane resistance value is expressed as a non-constant function of position on dendrite, and parameters of the function are estimated. Although this method is effective, it is applicable only when the appropriate function is known. We propose a statistical method, which does not express membrane resistance as a function of position on dendrite, for estimating membrane resistance over a dendrite from observed membrane potentials. We use the Markov random field (MRF) as a prior distribution of the membrane resistance. In the MRF, membrane resistance is not expressed as a function of position on dendrite, but is assumed to be smoothly varying along a dendrite. We apply our method to synthetic data to evaluate its efficacy, and show that even when we do not know the appropriate function, our method can accurately estimate the membrane resistance.

Original languageEnglish
Pages (from-to)186-191
Number of pages6
JournalIPSJ Online Transactions
Issue number2012
Publication statusPublished - 2012


  • Cable equation
  • Dendrite
  • Markov random field
  • Membrane potential imaging
  • Membrane resistance

ASJC Scopus subject areas

  • Computer Science(all)


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