Functional clustering of mouse ultrasonic vocalization data

Xiaoling Dou, Shingo Shirahata, Hiroki Sugimoto

    Research output: Contribution to journalArticle

    1 Citation (Scopus)

    Abstract

    Mouse ultrasonic vocalizations (USVs) are studied in many fields of science. However, various noise and varied USV patterns in observed signals make complete automatic analysis difficult. We improve several methods to reduce noise, detect USV calls and automatically cluster USV calls. After reduction of noise and detection of USV calls, we consider USV calls as functional data and characterize them as USV functions with B-spline basis functions. For discontinuous USV calls, breakpoints in the USV functions are defined using multiple knots in the construction of the B-spline basis functions, and a hierarchical method is used to cluster the USV functions by shape. We finally show the performance of the proposed methods with USV data recorded for laboratory mice.

    Original languageEnglish
    Pages (from-to)e0196834
    JournalPLoS One
    Volume13
    Issue number5
    DOIs
    Publication statusPublished - 2018 Jan 1

    Fingerprint

    vocalization
    Ultrasonics
    Cluster Analysis
    ultrasonics
    mice
    Acoustic noise
    Noise
    Splines
    knots
    methodology

    ASJC Scopus subject areas

    • Biochemistry, Genetics and Molecular Biology(all)
    • Agricultural and Biological Sciences(all)

    Cite this

    Functional clustering of mouse ultrasonic vocalization data. / Dou, Xiaoling; Shirahata, Shingo; Sugimoto, Hiroki.

    In: PLoS One, Vol. 13, No. 5, 01.01.2018, p. e0196834.

    Research output: Contribution to journalArticle

    Dou, Xiaoling ; Shirahata, Shingo ; Sugimoto, Hiroki. / Functional clustering of mouse ultrasonic vocalization data. In: PLoS One. 2018 ; Vol. 13, No. 5. pp. e0196834.
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