HUSCAP logo Hokkaido Univ. logo

Hokkaido University Collection of Scholarly and Academic Papers >
Graduate School of Science / Faculty of Science >
Peer-reviewed Journal Articles, etc >

A quantitative method for analyzing species-specific vocal sequence pattern and its developmental dynamics

This item is licensed under:Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

Files in This Item:
A quantitative method.pdf6.81 MBPDFView/Open
supplementary materials.pdf611.15 kBPDFView/Open
Please use this identifier to cite or link to this item:

Title: A quantitative method for analyzing species-specific vocal sequence pattern and its developmental dynamics
Authors: Imai, Raimu Browse this author
Sawai, Azusa Browse this author
Hayase, Shin Browse this author
Furukawa, Hiroyuki Browse this author
Asogwa, Chinweike Norman Browse this author
Sanchez, Miguel Browse this author
Wang, Hongdi Browse this author
Mori, Chihiro Browse this author
Wada, Kazuhiro Browse this author →KAKEN DB
Keywords: Vocal learning
Vocal development
Zebra finch
Song learning
Species specificity
Individual variation
Issue Date: 15-Sep-2016
Publisher: Elsevier
Journal Title: Journal of neuroscience methods
Volume: 271
Start Page: 25
End Page: 33
Publisher DOI: 10.1016/j.jneumeth.2016.06.023
PMID: 27373995
Abstract: Background: Songbirds are a preeminent animal model for understanding the neural basis underlying the development and evolution of a complex learned behavior, bird song. However, only a few quantitative methods exist to analyze these species-specific sequential behaviors in multiple species using the same calculation method. New method: We report a method of analysis that focuses on calculating the frequency of characteristic syllable transitions in songs. This method comprises two steps: The first step involves forming correlation matrices of syllable similarity scores, named syllable similarity matrices (SSMs); these are obtained by calculating the round-robin comparison of all the syllables in two songs, while maintaining the sequential order of syllables in the songs. In the second step, each occurrence rate of three patterns of binarized "2 rows x 2 columns" cells in the SSMs is calculated to extract information on the characteristic syllable transitions. Results: The SSM analysis method allowed obtaining species-specific features of song patterns and intraspecies individual variability simultaneously. Furthermore, it enabled quantitative tracking of the developmental trajectory of the syllable sequence patterns. Comparison with existing method: This method enables us to extract the species-specific song patterns and dissect the regulation of song syntax development without human-biased procedures for syllable identification. This method can be adapted to study the acoustic communication systems in several animal species, such as insects and mammals. Conclusions: This present method provides a comprehensive qualitative approach for understanding the regulation of species specificity and its development in vocal learning. (C) 2016 Elsevier B.V. All rights reserved.
Rights: © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license
Type: article (author version)
Appears in Collections:理学院・理学研究院 (Graduate School of Science / Faculty of Science) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: 和多 和宏

Export metadata:

OAI-PMH ( junii2 , jpcoar_1.0 )

MathJax is now OFF:


 - Hokkaido University