Analysis of ultrasonic vocalizations from mice using computer vision and machine learning
- Yale University, United States
- Yale University School of Medicine, United States
- Universidade Federal do Rio Grande do Sul, Brazil
Abstract
Mice emit ultrasonic vocalizations (USV) that communicate socially-relevant information. To detect and classify these USVs, here we describe VocalMat. VocalMat is a software that uses image-processing and differential geometry approaches to detect USVs in audio files, eliminating the need for user-defined parameters. VocalMat also uses computational vision and machine learning methods to classify USVs into distinct categories. In a dataset of >4,000 USVs emitted by mice, VocalMat detected over 98% of manually labeled USVs and accurately classified ~86% of the USVs out of eleven USV categories. We then used dimensionality reduction tools to analyze the probability distribution of USV classification among different experimental groups, providing a robust method to quantify and qualify the vocal repertoire of mice. Thus, VocalMat makes it possible to perform automated, accurate, and quantitative analysis of USVs without the need for user inputs, opening the opportunity for detailed and high-throughput analysis of this behavior.
Data availability
All the data and code used in this work is publicly available and can be found in the links below: https://osf.io/bk2uj/https://www.dietrich-lab.org/vocalmatThis information is also present in the manuscript at section 4.12 (Code and data availability).
Article and author information
Author details
Marcelo O Dietrich
Funding
National Institute of Diabetes and Digestive and Kidney Diseases
- Marcelo O Dietrich
Howard Hughes Medical Institute (Gilliam Fellowship)
- Gabriela M Bosque Ortiz
- Marcelo O Dietrich
Brain and Behavior Research Foundation
- Marcelo O Dietrich
Whitehall Foundation
- Marcelo O Dietrich
Charles H. Hood Foundation
- Marcelo O Dietrich
Foundation for Prader-Willi Research
- Marcelo O Dietrich
Reginald and Michiko Spector Award in Neuroscience
- Marcelo O Dietrich
Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Sérgio Bampi
- Marcelo O Dietrich
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
- Antonio H O Fonseca
- Gustavo M Santana
- Sérgio Bampi
- Marcelo O Dietrich
Yale Center for Clinical Investigation Scholar Award
- Marcelo O Dietrich
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. The protocol was reviewed and approved by the Yale University Institutional Animal Care and Use Committee (IACUC). All of the animals were handled according to the approved IACUC protocol (#2018-20042) of the Yale University School of Medicine.
Copyright
© 2021, Fonseca et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Analysis of ultrasonic vocalizations from mice using computer vision and machine learning
eLife 10:e59161.
https://doi.org/10.7554/eLife.59161
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