Functional clustering of mouse ultrasonic vocalization data

Xiaoling Dou, Shingo Shirahata, Hiroki Sugimoto

Research output: Contribution to journalArticlepeer-review

4 Citations (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
Article numbere0196834
JournalPloS one
Volume13
Issue number5
DOIs
Publication statusPublished - 2019 Jul 1

ASJC Scopus subject areas

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

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