Presentation 2006-06-15
Statical Estimation of Phase Response Curve
Keisuke OTA, Toru AONISHI,
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Abstract(in English) The phase response curves (PRCs) represennt an impulse response of oscillatory system to capture an essence of a nonequilibrium dynamics induced by a small disturbance. Wheareas measuring PRCs is important for bridging single neuron dynamics and network dynamics, estimating methods for PRCs have not yet been established. In this paper, we proposed a Bayesian approach to estimate PRCs from noisy data measured by perturbation-response experiments. First, we analyzed the stochastic process describing the observation process in perturbation-response experiments, and obtained a probability distribution of the deterioration process of PRCs. Then, by introducing a prior generating PRCs, we proposed the Maximum A Posteriori (MAP) estimation algorithm for PRCs.
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Keyword(in English) Phase Response Curve / Liner Response Theory / Fokker-Planck Equation / Bayesian Approach / MAP Estimation
Paper # NC2006-13
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Committee NC
Conference Date 2006/6/8(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Statical Estimation of Phase Response Curve
Sub Title (in English)
Keyword(1) Phase Response Curve
Keyword(2) Liner Response Theory
Keyword(3) Fokker-Planck Equation
Keyword(4) Bayesian Approach
Keyword(5) MAP Estimation
1st Author's Name Keisuke OTA
1st Author's Affiliation Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology()
2nd Author's Name Toru AONISHI
2nd Author's Affiliation Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology
Date 2006-06-15
Paper # NC2006-13
Volume (vol) vol.106
Number (no) 101
Page pp.pp.-
#Pages 5
Date of Issue