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MUPET-Mouse Ultrasonic Profile ExTraction: A Signal Processing Tool for Rapid and Unsupervised Analysis of Ultrasonic Vocalizations

Overview
Journal Neuron
Publisher Cell Press
Specialty Neurology
Date 2017 May 5
PMID 28472651
Citations 66
Authors
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Abstract

Vocalizations play a significant role in social communication across species. Analyses in rodents have used a limited number of spectro-temporal measures to compare ultrasonic vocalizations (USVs), which limits the ability to address repertoire complexity in the context of behavioral states. Using an automated and unsupervised signal processing approach, we report the development of MUPET (Mouse Ultrasonic Profile ExTraction) software, an open-access MATLAB tool that provides data-driven, high-throughput analyses of USVs. MUPET measures, learns, and compares syllable types and provides an automated time stamp of syllable events. Using USV data from a large mouse genetic reference panel and open-source datasets produced in different social contexts, MUPET analyzes the fine details of syllable production and repertoire use. MUPET thus serves as a new tool for USV repertoire analyses, with the capability to be adapted for use with other species.

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References
1.
Peirce J, Lu L, Gu J, Silver L, Williams R . A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet. 2004; 5:7. PMC: 420238. DOI: 10.1186/1471-2156-5-7. View

2.
Holmstrom L, Eeuwes L, Roberts P, Portfors C . Efficient encoding of vocalizations in the auditory midbrain. J Neurosci. 2010; 30(3):802-19. PMC: 6633079. DOI: 10.1523/JNEUROSCI.1964-09.2010. View

3.
Neilans E, Holfoth D, Radziwon K, Portfors C, Dent M . Discrimination of ultrasonic vocalizations by CBA/CaJ mice (Mus musculus) is related to spectrotemporal dissimilarity of vocalizations. PLoS One. 2014; 9(1):e85405. PMC: 3887032. DOI: 10.1371/journal.pone.0085405. View

4.
Bennur S, Tsunada J, Cohen Y, Liu R . Understanding the neurophysiological basis of auditory abilities for social communication: a perspective on the value of ethological paradigms. Hear Res. 2013; 305:3-9. PMC: 3818520. DOI: 10.1016/j.heares.2013.08.008. View

5.
Hammerschmidt K, Whelan G, Eichele G, Fischer J . Mice lacking the cerebral cortex develop normal song: insights into the foundations of vocal learning. Sci Rep. 2015; 5:8808. PMC: 4351519. DOI: 10.1038/srep08808. View