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A Compact Statistical Model of the Song Syntax in Bengalese Finch

Songs of many songbird species consist of variable sequences of a finite number of syllables. A common approach for characterizing the syntax of these complex syllable sequences is to use transition probabilities between the syllables. This is equivalent to the Markov model, in which each syllable i...

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Detalles Bibliográficos
Autores principales: Jin, Dezhe Z., Kozhevnikov, Alexay A.
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3060163/
https://www.ncbi.nlm.nih.gov/pubmed/21445230
http://dx.doi.org/10.1371/journal.pcbi.1001108
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author Jin, Dezhe Z.
Kozhevnikov, Alexay A.
author_facet Jin, Dezhe Z.
Kozhevnikov, Alexay A.
author_sort Jin, Dezhe Z.
collection PubMed
description Songs of many songbird species consist of variable sequences of a finite number of syllables. A common approach for characterizing the syntax of these complex syllable sequences is to use transition probabilities between the syllables. This is equivalent to the Markov model, in which each syllable is associated with one state, and the transition probabilities between the states do not depend on the state transition history. Here we analyze the song syntax in Bengalese finch. We show that the Markov model fails to capture the statistical properties of the syllable sequences. Instead, a state transition model that accurately describes the statistics of the syllable sequences includes adaptation of the self-transition probabilities when states are revisited consecutively, and allows associations of more than one state to a given syllable. Such a model does not increase the model complexity significantly. Mathematically, the model is a partially observable Markov model with adaptation (POMMA). The success of the POMMA supports the branching chain network model of how syntax is controlled within the premotor song nucleus HVC, but also suggests that adaptation and many-to-one mapping from the syllable-encoding chain networks in HVC to syllables should be included in the network model.
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spelling pubmed-30601632011-03-28 A Compact Statistical Model of the Song Syntax in Bengalese Finch Jin, Dezhe Z. Kozhevnikov, Alexay A. PLoS Comput Biol Research Article Songs of many songbird species consist of variable sequences of a finite number of syllables. A common approach for characterizing the syntax of these complex syllable sequences is to use transition probabilities between the syllables. This is equivalent to the Markov model, in which each syllable is associated with one state, and the transition probabilities between the states do not depend on the state transition history. Here we analyze the song syntax in Bengalese finch. We show that the Markov model fails to capture the statistical properties of the syllable sequences. Instead, a state transition model that accurately describes the statistics of the syllable sequences includes adaptation of the self-transition probabilities when states are revisited consecutively, and allows associations of more than one state to a given syllable. Such a model does not increase the model complexity significantly. Mathematically, the model is a partially observable Markov model with adaptation (POMMA). The success of the POMMA supports the branching chain network model of how syntax is controlled within the premotor song nucleus HVC, but also suggests that adaptation and many-to-one mapping from the syllable-encoding chain networks in HVC to syllables should be included in the network model. Public Library of Science 2011-03-17 /pmc/articles/PMC3060163/ /pubmed/21445230 http://dx.doi.org/10.1371/journal.pcbi.1001108 Text en Jin, Kozhevnikov. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Jin, Dezhe Z.
Kozhevnikov, Alexay A.
A Compact Statistical Model of the Song Syntax in Bengalese Finch
title A Compact Statistical Model of the Song Syntax in Bengalese Finch
title_full A Compact Statistical Model of the Song Syntax in Bengalese Finch
title_fullStr A Compact Statistical Model of the Song Syntax in Bengalese Finch
title_full_unstemmed A Compact Statistical Model of the Song Syntax in Bengalese Finch
title_short A Compact Statistical Model of the Song Syntax in Bengalese Finch
title_sort compact statistical model of the song syntax in bengalese finch
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3060163/
https://www.ncbi.nlm.nih.gov/pubmed/21445230
http://dx.doi.org/10.1371/journal.pcbi.1001108
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