Elsevier

Animal Behaviour

Volume 116, June 2016, Pages 181-193
Animal Behaviour

A novel statistical method for behaviour sequence analysis and its application to birdsong

https://doi.org/10.1016/j.anbehav.2016.04.001Get rights and content

Highlights

  • Vocal signals contain acoustic elements that differ in order and duration.

  • We used novel statistical methods to examine this in male European starling songs.

  • Songs of males in breeding and nonbreeding condition were statistically separable.

  • Males in breeding condition produced sexually relevant attributes of song.

  • Results also demonstrated a role for the medial preoptic nucleus in this process.

Complex vocal signals, such as birdsong, contain acoustic elements that differ in both order and duration. These elements may convey socially relevant meaning, both independently and through their interactions, yet statistical methods that combine order and duration data to extract meaning have not, to our knowledge, been fully developed. Here we design novel semi-Markov methods, Bayesian estimation and classification trees to extract order and duration information from behavioural sequences and apply these methods to songs produced by male European starlings, Sturnus vulgaris, in two social contexts in which the function of song differs: a spring (breeding) and autumn (nonbreeding) context. Additionally, previous data indicate that damage to the medial preoptic nucleus (POM), a brain area known to regulate male sexually motivated behaviour, affects structural aspects of starling song such that males in a sexually relevant context (i.e. spring) sing shorter songs than appropriate for this context. We further test the utility of our statistical approach by comparing attributes of song structure in POM-lesioned males to song produced by control spring and autumn males. Spring and autumn songs were statistically separable based on the duration and order of phrase types. Males produced more structurally complex aspects of song in spring than in autumn. Spring song was also longer and more stereotyped than autumn song, both attributes used by females to select mates. Songs produced by POM-lesioned males in some cases fell between measures of spring and autumn songs but differed most from songs produced by autumn males. Overall, these statistical methods can effectively extract biologically meaningful information contained in many behavioural sequences given sufficient sample sizes and replication numbers.

Section snippets

Animals

We captured 58 male and 48 female adult European starlings between December 2006 and February 2007 in Madison, Wisconsin, U.S.A. The birds were housed indoors in same-sex groups in stainless-steel cages on an 18:6 h light:dark cycle to induce a photorefractory state, a condition characterized by regressed gonads and a lack of sexual behaviour (Falk & Gwinner, 1988). All experiments were in accordance with the National Institutes of Health Guidelines and approved by the Institutional Animal Care

Initial Exploratory Statistical Analysis and Definition of State Space

The song recording collection consisted of songs recorded from spring control males (N = 13 birds, 1–82 songs per individual), spring POM-lesioned males (N = 7 birds, 1–42 songs per individual) and autumn males (N = 12 birds, 10–63 songs per individual).

Whistle1 had a significantly longer duration than whistle2 (mean ± SD: whistle1: 7.30 ± 2.38 s; whistle2: 3.86 ± 2.43 s; Wilcoxon two-sample test: W = 46,037.5, P < 0.001). The duration of whistleSong (17.68 ± 6.64 s) was significantly longer than that of whistle1 (W

Discussion

We developed novel statistical tools to analyse sequence data that differ in both order and duration and applied them to sequences of birdsong. We first discuss what these statistical methods reveal about birdsong and then highlight the strengths of this statistical approach.

Acknowledgments

This paper is based upon work supported by National Institute of Mental Health (NIMH) grants R01MH65645 and R01MH080225 to L.V.R. We gratefully acknowledge Ian Batterman for his assistance with song analysis, Alex Kreibich and Tram Ta for their assistance with data manipulation and Kate Skogen and Chris Elliott for animal care.

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