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Driving singing behaviour in songbirds using multi-modal, multi-agent virtual reality

View ORCID ProfileLeon Bonde Larsen, View ORCID ProfileIris Adam, View ORCID ProfileGordon J. Berman, John Hallam, View ORCID ProfileCoen P.H. Elemans
doi: https://doi.org/10.1101/2021.10.20.465086
Leon Bonde Larsen
1University of Southern Denmark, SDU-Biorobotics, Odense, Denmark
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  • For correspondence: lelar@mmmi.sdu.dk
Iris Adam
2University of Southern Denmark, Department of Biology, Odense, Denmark
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Gordon J. Berman
3Emory University, Department of Biology, Atlanta GA, USA
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John Hallam
1University of Southern Denmark, SDU-Biorobotics, Odense, Denmark
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Coen P.H. Elemans
2University of Southern Denmark, Department of Biology, Odense, Denmark
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Abstract

Interactive biorobotics provides unique experimental potential to study the mechanisms underlying social communication but is limited by our ability to build expressive robots that exhibit the complex behaviours of birds and small mammals. An alternative to physical robots is to use virtual reality (VR). Here, we designed and built a modular, audio-visual virtual reality environment that allows online, multi-modal, multi-agent interaction for social communication. We tested this system in songbirds, which provide an exceptionally powerful and tractable model system to study social communication. We show that zebra finches (Taeniopygia guttata) communicating through the VR environment exhibit normal call timing behaviour, males sing female directed song and both males and females display high-intensity courtship behaviours to their mates. These results suggest that the VR system provides a sufficiently natural environment to elicit normal social communication behaviour. Furthermore, we developed a fully unsupervised online song motif detector and used it to manipulate the virtual social environment of male zebra finches based on the number of motifs sung. Our VR setup represents a first step in taking automatic behaviour annotation into the online domain and allows for animal-computer interaction using higher level behaviours such as song. Our unsupervised acoustic analysis eliminates the need for annotated training data thus reducing labour investment and experimenter bias.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.
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Posted October 20, 2021.
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Driving singing behaviour in songbirds using multi-modal, multi-agent virtual reality
Leon Bonde Larsen, Iris Adam, Gordon J. Berman, John Hallam, Coen P.H. Elemans
bioRxiv 2021.10.20.465086; doi: https://doi.org/10.1101/2021.10.20.465086
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Driving singing behaviour in songbirds using multi-modal, multi-agent virtual reality
Leon Bonde Larsen, Iris Adam, Gordon J. Berman, John Hallam, Coen P.H. Elemans
bioRxiv 2021.10.20.465086; doi: https://doi.org/10.1101/2021.10.20.465086

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