期刊
JOURNAL OF NEUROSCIENCE METHODS
卷 219, 期 1, 页码 155-161出版社
ELSEVIER
DOI: 10.1016/j.jneumeth.2013.06.006
关键词
Addiction; Craving; Cocaine; Rat; Self-administration; USV
资金
- NSF [DGE1110007]
- American Foundation for Pharmaceutical Education (AFPE)
- University of Texas Undergraduate Research Awards
- [T32 NIAA07471]
- [NIAA013517]
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 0.3% 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. Published by Elsevier B.V.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据