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Statistical inference for ratiometric imaging of excitable cells: a self‐organizing state‐space model
Author(s) -
Iwahashi Ryouhei,
Tateno Takashi
Publication year - 2012
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.21808
Subject(s) - state space representation , bayesian inference , particle filter , state space , state vector , inference , biological system , bayesian probability , state (computer science) , calcium , monte carlo method , computer science , algorithm , chemistry , mathematics , kalman filter , artificial intelligence , statistics , physics , organic chemistry , classical mechanics , biology
Concentrations of free intracellular calcium ions ([Ca 2+ ] i ) in excitable cells are often measured using indicator dyes, such as fura‐2. Of note, however, these indicator dyes are divalent metal ion chelators that affect intrinsic changes in [Ca 2+ ] i . To examine whether indicator dyes alter calcium signaling, we estimated [Ca 2+ ] i using a novel statistical inference method that examines fluorescence signals and the calcium current through the cell membrane. We first constructed a model of transient [Ca 2+ ] i , which was then translated into a state‐space model with such state variables as [Ca 2+ ] i , endogenous calcium buffer, and calcium indicators. Then, a self‐organizing state‐space model was defined by augmenting a state vector with unknown parameters from the original state‐space model. In the model, some unknown parameters were estimated with the original state vector. Next, we used a recursive Bayesian estimation to obtain a set of state vectors and the unknown parameters associated with a set of observation vectors. To calculate the recursive Bayesian estimation, we used a sequential Monte Carlo method, which is referred to as a particle filter method . To verify the effectiveness of the proposed method, we carried out experiments with a set of test data from a model with known parameters. The results show that our proposed method properly estimated the temporal profiles of [Ca 2+ ] i , the indicator dye concentration, and certain model parameters in a noisy environment. © 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.