Computational Analysis of Neonatal Mouse Ultrasonic Vocalization

Pilib Ó Broin, Michael V. Beckert, Tomohisa Takahashi, Takeshi Izumi, Kenny Ye, Gina Kang, Patricia Pouso, Mackenzie Topolski, Jose L. Pena, Noboru Hiroi

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Neonatal vocalization is structurally altered in mouse models of autism spectrum disorder (ASD). Our published data showed that pup vocalization, under conditions of maternal separation, contains sequences whose alterations in a genetic mouse model of ASD impair social communication between pups and mothers. We describe details of a method which reveals the statistical structure of call sequences that are functionally critical for optimal maternal care. Entropy analysis determines the degree of non-random call sequencing. A Markov model determines the actual call sequences used by pups. Sparse partial least squares discriminant analysis (sPLS-DA) identifies call sequences that differentiate groups and reveals the degrees of individual variability in call sequences between groups. These three sets of analyses can be used to identify the otherwise hidden call structure that is altered in mouse models of developmental neuropsychiatric disorders, including not only autism but also schizophrenia.

Original languageEnglish (US)
Pages (from-to)e46
JournalCurrent protocols in mouse biology
Volume8
Issue number2
DOIs
StatePublished - Jun 1 2018
Externally publishedYes

Keywords

  • Markov model
  • USV
  • autism spectrum disorder
  • entropy
  • mouse models
  • sPLS-DA
  • schizophrenia

ASJC Scopus subject areas

  • Medicine(all)

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