Valence and salience encoding in the central amygdala

The central amygdala (CeA) has emerged as an important brain region for regulating both negative (fear and anxiety) and positive (reward) affective behaviors. The CeA has been proposed to encode affective information in the form of valence (whether the stimulus is good or bad) or salience (how significant is the stimulus), but the extent to which these two types of stimulus representation occur in the CeA is not known. Here, we used single cell calcium imaging in mice during appetitive and aversive conditioning and found that majority of CeA neurons (~65%) encode the valence of the unconditioned stimulus (US) with a smaller subset of cells (~15%) encoding the salience of the US. Valence and salience encoding of the conditioned stimulus (CS) was also observed, albeit to a lesser extent. These findings show that the CeA is a site of convergence for encoding oppositely valenced US information.

Methods
The 1-photon calcium imaging data were pre-processed and motion-corrected using the Inscopix Data Processing Software (IDPS). Cell identification was performed with a constrained non-negative matrix factorization algorithm for microendoscopic data (CNMF-E) within IDPS. All cell traces were then statistically tested using the 'circular shifting' method to determine whether their responses were significant. The code for the circular shifting method is available at https://github.com/zweifellab?tab=repositories. ++ Additionally, circular shift analysis tools (R base) have been uploaded in this dataset.

中央杏仁核（central amygdala, CeA）已被证实是调控负面（恐惧与焦虑）及正面（奖赏）情感行为的关键脑区。过往研究提出，中央杏仁核可通过效价（刺激的优劣属性）或显著性（刺激的重要程度）编码情感信息，但目前尚不明确这两种刺激表征在中央杏仁核中的具体分布情况。本研究在小鼠进行奖赏与厌恶性条件反射的过程中，采用单细胞钙成像技术开展观测，结果发现绝大多数中央杏仁核神经元（约65%）以非条件刺激（unconditioned stimulus, US）的效价进行编码，另有较小比例的细胞群（约15%）负责编码非条件刺激的显著性。同时本研究也观测到了条件刺激（conditioned stimulus, CS）的效价与显著性编码现象，尽管其占比相对更低。上述研究结果表明，中央杏仁核是整合编码相反效价非条件刺激信息的关键位点。

方法
本研究的单光子钙成像数据通过Inscopix数据处理软件（Inscopix Data Processing Software, IDPS）完成预处理与运动校正。细胞识别环节借助IDPS内置的微内窥镜数据约束非负矩阵分解算法（constrained non-negative matrix factorization algorithm for microendoscopic data, CNMF-E）实现。随后，通过循环移位法对所有细胞的钙信号轨迹进行统计学检验，以确定其反应是否具有显著性。循环移位法的代码可在https://github.com/zweifellab?tab=repositories获取。此外，本数据集还上传了基于R基础包的循环移位分析工具。