Automated classification of mouse pup isolation syllables: from cluster analysis to an Excel-based “mouse pup syllable classification calculator”

Jasmine M S Grimsley,Marie A Gadziola,Jeffrey J Wenstrup

doi:10.3389/fnbeh.2012.00089

Jasmine M S Grimsley, Marie A Gadziola + Show 1 more

Open Access

https://doi.org/10.3389/fnbeh.2012.00089

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Abstract

Mouse pups vocalize at high rates when they are cold or isolated from the nest. The proportions of each syllable type produced carry information about disease state and are being used as behavioral markers for the internal state of animals. Manual classifications of these vocalizations identified 10 syllable types based on their spectro-temporal features. However, manual classification of mouse syllables is time consuming and vulnerable to experimenter bias. This study uses an automated cluster analysis to identify acoustically distinct syllable types produced by CBA/CaJ mouse pups, and then compares the results to prior manual classification methods. The cluster analysis identified two syllable types, based on their frequency bands, that have continuous frequency-time structure, and two syllable types featuring abrupt frequency transitions. Although cluster analysis computed fewer syllable types than manual classification, the clusters represented well the probability distributions of the acoustic features within syllables. These probability distributions indicate that some of the manually classified syllable types are not statistically distinct. The characteristics of the four classified clusters were used to generate a Microsoft Excel-based mouse syllable classifier that rapidly categorizes syllables, with over a 90% match, into the syllable types determined by cluster analysis.

Highlights

The isolation vocalizations of infant mice are used as behavioral markers of stress (Rupniak et al, 2000) or disease state (Ricceri et al, 2007; Scattoni et al, 2008; Young et al, 2010; Wohr et al, 2011a)
This study first uses cluster analysis to determine the number of discrete syllable categories produced by pups, describes and evaluates a Microsoft Excel-based automated calculator to classify mouse pup isolation calls into these syllable types
A two-step cluster analysis identified four acoustically discrete syllable types produced by mouse pups

Summary

Introduction

The isolation vocalizations of infant mice are used as behavioral markers of stress (Rupniak et al, 2000) or disease state (Ricceri et al, 2007; Scattoni et al, 2008; Young et al, 2010; Wohr et al, 2011a). While several studies show that the rate of vocalizations relates to stress, disease state, social context, or strain (Rupniak et al, 2000; Hahn and Schanz, 2002; Young et al, 2010), it is clear that the types of emitted syllables are affected in pups (Scattoni et al, 2008; Young et al, 2010; Chabout et al, 2012) and adults (Chabout et al, 2012). This study first uses cluster analysis to determine the number of discrete syllable categories produced by pups, describes and evaluates a Microsoft Excel-based automated calculator to classify mouse pup isolation calls into these syllable types. The number of syllable categories has been determined subjectively by the experimenter, based on visual inspection of the spectrogram, with syllables sharing unique spectro-temporal features grouped together (Sales and Smith, 1978; Portfors, 2007; Sugimoto et al, 2011)

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