Automated acoustic detection of mouse scratching

Peter Elliott, Max G’Sell, Lindsey M Snyder, Sarah E Ross and Valérie Ventura

PLOS ONE, 2017, vol. 12, issue 7, 1-16

Abstract: Itch is an aversive somatic sense that elicits the desire to scratch. In animal models of itch, scratching behavior is frequently used as a proxy for itch, and this behavior is typically assessed through visual quantification. However, manual scoring of videos has numerous limitations, underscoring the need for an automated approach. Here, we propose a novel automated method for acoustic detection of mouse scratching. Using this approach, we show that chloroquine-induced scratching behavior in C57BL/6 mice can be quantified with reasonable accuracy (85% sensitivity, 75% positive predictive value). This report is the first method to apply supervised learning techniques to automate acoustic scratch detection.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0179662

DOI: 10.1371/journal.pone.0179662

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