Bayesian selection of Markov models for symbol sequences: application to microsaccadic eye movements.
Complex biological dynamics often generate sequences of discrete events which can be described as a Markov process. The order of the underlying Markovian stochastic process is fundamental for characterizing statistical dependencies within sequences. As an example for this class of biological systems...
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2012-01-01
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doaj-bf5d48098db6428bbec39d3e61a8075a2020-11-24T21:53:57ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-0179e4338810.1371/journal.pone.0043388Bayesian selection of Markov models for symbol sequences: application to microsaccadic eye movements.Mario BettenbühlMarco RusconiRalf EngbertMatthias HolschneiderComplex biological dynamics often generate sequences of discrete events which can be described as a Markov process. The order of the underlying Markovian stochastic process is fundamental for characterizing statistical dependencies within sequences. As an example for this class of biological systems, we investigate the Markov order of sequences of microsaccadic eye movements from human observers. We calculate the integrated likelihood of a given sequence for various orders of the Markov process and use this in a Bayesian framework for statistical inference on the Markov order. Our analysis shows that data from most participants are best explained by a first-order Markov process. This is compatible with recent findings of a statistical coupling of subsequent microsaccade orientations. Our method might prove to be useful for a broad class of biological systems.http://europepmc.org/articles/PMC3435382?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mario Bettenbühl Marco Rusconi Ralf Engbert Matthias Holschneider |
spellingShingle |
Mario Bettenbühl Marco Rusconi Ralf Engbert Matthias Holschneider Bayesian selection of Markov models for symbol sequences: application to microsaccadic eye movements. PLoS ONE |
author_facet |
Mario Bettenbühl Marco Rusconi Ralf Engbert Matthias Holschneider |
author_sort |
Mario Bettenbühl |
title |
Bayesian selection of Markov models for symbol sequences: application to microsaccadic eye movements. |
title_short |
Bayesian selection of Markov models for symbol sequences: application to microsaccadic eye movements. |
title_full |
Bayesian selection of Markov models for symbol sequences: application to microsaccadic eye movements. |
title_fullStr |
Bayesian selection of Markov models for symbol sequences: application to microsaccadic eye movements. |
title_full_unstemmed |
Bayesian selection of Markov models for symbol sequences: application to microsaccadic eye movements. |
title_sort |
bayesian selection of markov models for symbol sequences: application to microsaccadic eye movements. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2012-01-01 |
description |
Complex biological dynamics often generate sequences of discrete events which can be described as a Markov process. The order of the underlying Markovian stochastic process is fundamental for characterizing statistical dependencies within sequences. As an example for this class of biological systems, we investigate the Markov order of sequences of microsaccadic eye movements from human observers. We calculate the integrated likelihood of a given sequence for various orders of the Markov process and use this in a Bayesian framework for statistical inference on the Markov order. Our analysis shows that data from most participants are best explained by a first-order Markov process. This is compatible with recent findings of a statistical coupling of subsequent microsaccade orientations. Our method might prove to be useful for a broad class of biological systems. |
url |
http://europepmc.org/articles/PMC3435382?pdf=render |
work_keys_str_mv |
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