ArticleScientific reports2019
Quantifying ultrasonic mouse vocalizations using acoustic analysis in a supervised statistical machine learning framework.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Self-vocalizations activate the developing auditory cortex via an intracortical pathway.Science advances · 2026Article
- Elevated maternal testosterone induces sex-specific neurodevelopmental changes and ASD-related behavioral phenotypes in rat offspring.Pediatric research · 2026Article
- Article
- A humanized NOVA1 splicing factor alters mouse vocal communications.Nature communications · 2025Article
- Differential Encoding of Two-Tone Harmonics in the Male and Female Mouse Auditory Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Rodent tests of depression and anxiety: Construct validity and translational relevance.Cognitive, affective & behavioral neuroscience · 2024Review
- Stuttering associated with a pathogenic variant in the chaperone protein cyclophilin 40.Brain : a journal of neurology · 2023Article
- Extended performance analysis of deep-learning algorithms for mice vocalization segmentation.Scientific reports · 2023Article
- MLKL deficiency protects against low-grade, sterile inflammation in aged mice.Cell death and differentiation · 2023Article
- Prenatal low-dose methylmercury exposure causes premature neuronal differentiation and autism-like behaviors in a rodent model.iScience · 2023Article
- BAMBI: A new method for automated assessment of bidirectional early-life interaction between maternal behavior and pup vocalization in mouse dam-pup dyads.Frontiers in behavioral neuroscience · 2023Article
- Quantifying Sex Differences in Behavior in the Era of "Big" Data.Cold Spring Harbor perspectives in biology · 2022Review
- Relevance, redundancy, and complementarity trade-off (RRCT): A principled, generic, robust feature-selection tool.Patterns (New York, N.Y.) · 2022Article
- Capturing the songs of mice with an improved detection and classification method for ultrasonic vocalizations (BootSnap).PLoS computational biology · 2022Article
- A feature of maternal sleep apnea during gestation causes autism-relevant neuronal and behavioral phenotypes in offspring.PLoS biology · 2022Article
- Rates of ultrasonic vocalizations are more strongly related than acoustic features to non-vocal behaviors in mouse pups.Frontiers in behavioral neuroscience · 2022Article
- Ultrasonic vocalizations in mice: relevance for ethologic and neurodevelopmental disorders studies.Neural regeneration research · 2021Review
- Newborn mice form lasting CA2-dependent memories of their mothers.Cell reports · 2021Article
- Automatic classification of mice vocalizations using Machine Learning techniques and Convolutional Neural Networks.PloS one · 2021Article
- Similarities between the Effects of Prenatal Chlorpyrifos and Valproic Acid on Ultrasonic Vocalization in Infant Wistar Rats.International journal of environmental research and public health · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Examination of rodent vocalizations in experimental conditions can yield valuable insights into how disease manifests and progresses over time. It can also be used as an index of social interest, motivation, emotional development or motor function depending on the animal model under investigation. Most mouse communication is produced in ultrasonic frequencies beyond human hearing. These ultrasonic vocalizations (USV) are typically described and evaluated using expert defined classification of the spectrographic appearance or simplistic acoustic metrics resulting in nine call types. In this study, we aimed to replicate the standard expert-defined call types of communicative vocal behavior in mice by using acoustic analysis to characterize USVs and a principled supervised learning setup. We used four feature selection algorithms to select parsimonious subsets with maximum predictive accuracy, which are then presented into support vector machines (SVM) and random forests (RF). We assessed the resulting models using 10-fold cross-validation with 100 repetitions for statistical confidence and found that a parsimonious subset of 8 acoustic measures presented to RF led to 85% correct out-of-sample classification, replicating the experts' labels. Acoustic measures can be used by labs to describe USVs and compare data between groups, and provide insight into vocal-behavioral patterns of mice by automating the process on matching the experts' call types.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.