Mice, rats, and several other species communicate through ultrasonic vocalizations (USVs), outside of the human range of detection. Recently there’s been a broader adoption of USV analysis, as these vocalizations have relevance for understanding emotional states, social interactions, and other aspects of communicative behavior in rodents. In mice, these vocalizations are diverse and complex which can make manually scoring the patterns rather difficult and time consuming. To address this, Antonio Fonseca and colleagues developed and shared VocalMat, a MATLAB based toolbox for automated quantitative analysis of ultrasonic vocalizations. This software utilizes image-processing libraries to detect USVs and computational vision and machine learning algorithms to classify detected USVs. Read more about the utility of the software and performance comparisons to manual USV analysis approaches in Fonseca et al. and get instructions for downloading and using VocalMat from GitHub!
This research tool was created by your colleagues. Please acknowledge the Principal Investigator, cite the article in which the tool was described, and include an RRID in the Materials and Methods of your future publications. RRID:SCR_022342
Check out projects similar to this!