Data Sheet 1_Licking microstructure behavior classifies a spectrum of emotional states in mice.pdf

Measuring precise emotional tagging for taste information, with or without the use of words, is challenging. While affective taste valence and salience are core components of emotional experiences, traditional behavioral assays for taste preference, which often rely on cumulative consumption, lack the resolution to distinguish between different affective states, such as innate versus learned aversion, which are known to be mediated by distinct neural circuits. To overcome this limitation, we developed an open-source system for high-resolution microstructural analysis of licking behavior in freely moving mice. Our approach integrates traditional lick burst analysis with a proprietary software pipeline that utilizes interlick interval (ILI) distributions and principal component analysis (PCA) to create a multidimensional behavioral profile of the animal. Using this system, we characterized the licking patterns associated with innate appetitive, aversive, and neutral tastants. While conventional burst analysis failed to differentiate between two palatable stimuli (water and saccharin), our multidimensional approach revealed distinct and quantifiable behavioral signatures for each. Critically, this approach successfully dissociates innate and learned aversive taste valences, a distinction that cannot be achieved using standard metrics. By providing the designs for our custom-built setup and analysis software under an open-source license, this study offers a comprehensive and accessible methodology for examining hedonic responses in future studies. This powerful toolkit enhances our understanding of sensory valence processing and provides a robust platform for future investigations of the neurobiology of ingestive behavior.

对味觉信息开展精准情感标记（无论是否依托语言）颇具挑战。尽管味觉情感效价与显著性是情感体验的核心构成要素，但传统味觉偏好行为检测方法往往依赖累积摄食量，其检测分辨率不足以区分不同的情感状态，例如已知由不同神经环路介导的先天厌恶与后天习得厌恶。为克服这一局限，我们开发了一套开源系统，用于对自由活动小鼠的舔舐行为开展高分辨率微观结构分析。本方法将传统舔舐爆发分析与一套专属软件流程相结合，该流程利用舔舐间隔（interlick interval, ILI）分布与主成分分析（principal component analysis, PCA），为实验动物构建多维行为特征谱。借助该系统，我们对与先天偏好性、厌恶性及中性味觉刺激相关的舔舐模式进行了表征。尽管传统爆发分析无法区分两种适口性刺激（水与糖精），但我们的多维分析方法揭示了二者各自独特且可量化的行为特征标记。尤为关键的是，该方法成功区分了先天与后天习得的厌恶性味觉效价，而这一区分无法通过标准指标实现。本研究以开源许可协议公开了定制化实验装置的设计方案与分析软件，为未来研究中开展快感反应检测提供了一套全面且易于获取的方法学工具。这套高效工具套件不仅加深了我们对感官效价加工机制的理解，更为未来开展摄食行为神经生物学相关研究提供了可靠的实验平台。