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Sci Rep. 2015 May 28;5:10237. doi: 10.1038/srep10237.

VoICE: A semi-automated pipeline for standardizing vocal analysis across models.

Author information

1
1] Department of Integrative Biology &Physiology, University of California, Los Angeles, California 90095 [2] Interdepartmental Program in Molecular, Cellular, &Integrative Physiology, University of California, Los Angeles, California 90095.
2
Department of Integrative Biology &Physiology, University of California, Los Angeles, California 90095.
3
1] Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, California 90095 [2] Center for Autism Research &Treatment, Semel Institute for Neuroscience &Human Behavior, University of California, Los Angeles, California 90095.
4
1] Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, California 90095 [2] Center for Autism Research &Treatment, Semel Institute for Neuroscience &Human Behavior, University of California, Los Angeles, California 90095 [3] Center for Neurobehavioral Genetics, Semel Institute for Neuroscience &Human Behavior, University of California, Los Angeles, California 90095.

Abstract

The study of vocal communication in animal models provides key insight to the neurogenetic basis for speech and communication disorders. Current methods for vocal analysis suffer from a lack of standardization, creating ambiguity in cross-laboratory and cross-species comparisons. Here, we present VoICE (Vocal Inventory Clustering Engine), an approach to grouping vocal elements by creating a high dimensionality dataset through scoring spectral similarity between all vocalizations within a recording session. This dataset is then subjected to hierarchical clustering, generating a dendrogram that is pruned into meaningful vocalization "types" by an automated algorithm. When applied to birdsong, a key model for vocal learning, VoICE captures the known deterioration in acoustic properties that follows deafening, including altered sequencing. In a mammalian neurodevelopmental model, we uncover a reduced vocal repertoire of mice lacking the autism susceptibility gene, Cntnap2. VoICE will be useful to the scientific community as it can standardize vocalization analyses across species and laboratories.

PMID:
26018425
PMCID:
PMC4446892
DOI:
10.1038/srep10237
[Indexed for MEDLINE]
Free PMC Article

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