Matthew Binder1, Suzanne O Nolan2, Joaquin N Lugo3. 1. Department of Psychology and Neuroscience, Nashville, TN, 37232, USA. 2. Department of Pharmacology, Vanderbilt University Medical Center, Nashville, TN, 37232, USA. 3. Department of Psychology and Neuroscience, Nashville, TN, 37232, USA; Institute of Biomedical Studies, Baylor University, Waco, TX 76798, USA. Electronic address: joaquin_lugo@baylor.edu.
Abstract
BACKGROUND: Communicative behaviors play a vital role in mammals and are highly relevant to human neurodevelopmental conditions. Mice produce communicative vocalizations that occur in the ultrasonic range, which are commonly analyzed within the Avisoft recording system. Fully automated programs such as the Mouse Song Analyzer in MATLAB, have been developed to analyze USVs in a shorter time period, however, no study has compared the accuracy of MATLAB to Avisoft. NEW METHOD: In order to determine MATLAB's accuracy, we used data from four different mouse strains and assessed whether the total number of USVs detected was similar between systems. RESULTS: We found that there was a high correlation between systems for the number of USVs emitted from C57BL/6 and NS-Pten mice however, Avisoft detected significantly more USVs than MATLAB for both strains. For Fmr1-FVB.129 and 129 mice, large correlations were observed between systems and no significant difference was present in the USVs detected. A partial correlation was run to control for the covariates: sex, age, strain, and treatment, and found that only strain substantially influences the relationship between the USVs detected in Avisoft and those detected in MATLAB. COMPARISON WITH EXISTING METHOD: These findings demonstrate that there is a high degree of agreement between Avisoft and the Mouse Song Analyzer however, Avisoft does detect significantly more USVs depending on the strain assessed. CONCLUSIONS: Therefore, there are relative advantages and disadvantages with both systems that vocalization researchers should be aware of when interpreting USV results, and when using either system.
BACKGROUND: Communicative behaviors play a vital role in mammals and are highly relevant to human neurodevelopmental conditions. Mice produce communicative vocalizations that occur in the ultrasonic range, which are commonly analyzed within the Avisoft recording system. Fully automated programs such as the Mouse Song Analyzer in MATLAB, have been developed to analyze USVs in a shorter time period, however, no study has compared the accuracy of MATLAB to Avisoft. NEW METHOD: In order to determine MATLAB's accuracy, we used data from four different mouse strains and assessed whether the total number of USVs detected was similar between systems. RESULTS: We found that there was a high correlation between systems for the number of USVs emitted from C57BL/6 and NS-Ptenmice however, Avisoft detected significantly more USVs than MATLAB for both strains. For Fmr1-FVB.129 and 129 mice, large correlations were observed between systems and no significant difference was present in the USVs detected. A partial correlation was run to control for the covariates: sex, age, strain, and treatment, and found that only strain substantially influences the relationship between the USVs detected in Avisoft and those detected in MATLAB. COMPARISON WITH EXISTING METHOD: These findings demonstrate that there is a high degree of agreement between Avisoft and the Mouse Song Analyzer however, Avisoft does detect significantly more USVs depending on the strain assessed. CONCLUSIONS: Therefore, there are relative advantages and disadvantages with both systems that vocalization researchers should be aware of when interpreting USV results, and when using either system.
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