Clustering on Mouse Ultrasonic Vocalization Data(Session 1a)

Abstract

It has been found that male mice emit ultrasonic vocalizations (USVs) towards females during male-female interaction. The purpose of this paper is to classify the waveforms of the mouse USV data. The data are transformed by FFT (Fast Fourier Transformation). Because the USV data are very noisy, it is impossible to analyze them by existing software. We first smooth the USV waveforms from the noisy data by a moving average method, and then fit them with a polynomial regression. After that, we classify the obtained USV curves by a functional clustering method. This analysis also can help us to find a rule (or grammar) of the USVs in communication between mice.