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自动化超声发声分析:WAAVES 程序。

Automating ultrasonic vocalization analyses: the WAAVES program.

机构信息

The University of Texas at Austin, Department of Psychology, Behavioral Neuroscience, 108 East Dean Keeton Avenue, Stop A8000, Austin, TX 78712-1043, USA.

出版信息

J Neurosci Methods. 2013 Sep 30;219(1):155-61. doi: 10.1016/j.jneumeth.2013.06.006. Epub 2013 Jul 4.

Abstract

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.

摘要

背景

人类情感是药物滥用和成瘾的关键组成部分。啮齿动物发出的超声发声(USVs)是药物滥用研究中情绪的一种高度转化动物模型。全面使用 USV 数据的主要障碍是及时获得准确的 USV 评估的压倒性负担。分析 USV 的最准确方法之一是人类听觉检测与同时的声谱图检查,这需要将 USV 声音文件以 4%的正常速度回放。

新方法

WAAVES(特定环境的声谱分析自动化 USV 评估程序)是一种自动化的 USV 评估程序,利用 MATLAB 的信号和图像处理工具箱以及一系列定制滤波器,将 USV 呼叫与背景噪声分离,并准确地对 USV 进行计数和分类为平调或调频(FM)呼叫。在当前报告中,通过可卡因自我给药数据的 USV 分析演示了 WAAVES 的功能,这些数据是在 10 个日常会议中收集的。

结果

WAAVES 的计数与人类听觉计数显著相关(r(48)=0.9925;p<0.001)。统计分析使用 WAAVES 输出来检查个体对可卡因、可卡因相关线索的 USV 反应差异以及 USV、可卡因摄入量和运动活动之间的关系。

与现有方法的比较

WAAVES 的输出高度准确,并在使用人类听觉检测方法时,大约节省了 0.3%的时间提供了表格数据。

结论

开发定制的 USV 分析程序,如 WAAVES,可简化 USV 评估并增强将 USV 作为工具用于推进药物滥用研究并最终开发有效治疗方法的能力。

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