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arXiv · 1405.4126

Direct extraction of phase dynamics from fluctuating rhythmic data based on a Bayesian approach

Kaiichiro Ota·Toshio Aoyagi
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Abstract

Employing both Bayesian statistics and the theory of nonlinear dynamics, we present a practically efficient method to extract a phase description of weakly coupled limit-cycle oscillators directly from time series observed in a rhythmic system. As a practical application, we numerically demonstrate that this method can retrieve all the interaction functions from the fluctuating rhythmic neuronal activity exhibited by a network of asymmetrically coupled neurons. This method can be regarded as a type of statistical phase reduction method that requires no detailed modeling, and as such, it is a very practical and reliable method in application to data-driven studies of rhythmic systems.

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Kaiichiro Ota, Toshio Aoyagi. 2014-05-16. Direct extraction of phase dynamics from fluctuating rhythmic data based on a Bayesian approach. https://arxiv.org/abs/1405.4126

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