Background
Human emotion is a crucial component of drug abuse and addiction.
Ultrasonic vocalizations (USVs) elicited by rodents are a highly
translational animal model of emotion in drug abuse studies. A major
roadblock to comprehensive use of USV data is the overwhelming burden to
attain accurate USV assessment in a timely manner. One of the most accurate
methods of analyzing USVs, human auditory detection with simultaneous
spectrogram inspection, requires USV sound files to be played back
4% normal speed.
New Method
WAAVES (WAV-file Automated Analysis of Vocalizations Environment
Specific) is an automated USV assessment program utilizing MATLAB’s
Signal and Image Processing Toolboxes in conjunction with a series of
customized filters to separate USV calls from background noise, and
accurately tabulate and categorize USVs as flat or frequency-modulated (FM)
calls. In the current report, WAAVES functionality is demonstrated by USV
analyses of cocaine self-administration data collected over 10 daily
sessions.
Results
WAAVES counts are significantly correlated with human auditory counts
(r(48)=0.9925; p<0.001). Statistical analyses used WAAVES output
to examine individual differences in USV responses to cocaine,
cocaine-associated cues and relationships between USVs, cocaine intake and
locomotor activity.
Comparison with Existing Method
WAAVES output is highly accurate and provides tabulated data in
approximately 0.4% of the time required when using human auditory
detection methods.
Conclusions
The development of a customized USV analysis program, such as WAAVES
streamlines USV assessment and enhances the ability to utilize USVs as a
tool to advance drug abuse research and ultimately develop effective
treatments.