Journal of Neuroscience Methods ( IF 3 ) Pub Date : 2020-06-20 , DOI: 10.1016/j.jneumeth.2020.108810 Marloes H van der Goot 1 , Hetty Boleij 1 , Jan van den Broek 2 , Amber R Salomons 1 , Saskia S Arndt 1 , Hein A van Lith 3
Background
Despite extensive environmental standardization and the use of genetically and microbiologically defined mice of similar age and sex, individuals of the same mouse inbred strain commonly differ in quantitative traits. This is a major issue as it affects the quality of experimental results. Standard analysis practices summarize numerical data by means and associated measures of dispersion, while individual values are ignored. Perhaps taking individual values into account in statistical analysis may improve the quality of results.
New method
The present study re-inspected existing data on emotional reactivity profiles in 125 BALB/cJ and 129 mice, which displayed contrasting patterns of habituation and sensitization when repeatedly exposed to a novel environment (modified Hole Board). Behaviors were re-analyzed on an individual level, using a multivariate approach, in order to explore whether this yielded new information regarding subtypes of response, and their expression between and within strains.
Results
Clustering individual mice across multiple behavioral dimensions identified two response profiles: a habituation and a sensitization cluster.
Comparison with existing method(s)
These retrospect analyses identified habituation and sensitization profiles that were similar to those observed in the original data but also yielded new information such as a more pronounced sensitization response. Also, it allowed for the identification of individuals that deviated from the predominant response profile within a strain.
Conclusions
The present approach allows for the behavioral characterization of experimental animals on an individual level and as such provides a valuable contribution to existing approaches that take individual variation into account in statistical analysis.
中文翻译:
基于个体的多维方法,用于识别近交小鼠的情绪反应概况。
背景
尽管进行了广泛的环境标准化,并且使用了年龄和性别相似的遗传和微生物学定义的小鼠,但同一小鼠自交系的个体在数量性状上通常有所不同。这是一个主要问题,因为它会影响实验结果的质量。标准分析实践通过分散的手段和相关度量汇总了数值数据,而忽略了各个值。也许在统计分析中考虑单个值可以提高结果的质量。
新方法
本研究重新检查了125 BALB / cJ和129小鼠的情绪反应概况的现有数据,这些数据在反复暴露于新环境(改良的孔板)中显示出习惯化和致敏的对比模式。为了研究这种行为是否产生了有关反应亚型及其在菌株间和菌株内的表达的新信息,使用多变量方法对个体行为进行了重新分析。
结果
跨多个行为维度对单个小鼠进行聚类可确定两个响应曲线:习惯化和敏化聚类。
与现有方法的比较
这些回顾分析确定了习惯性和致敏性,它们与原始数据中观察到的相似,但也产生了新的信息,例如更明显的致敏反应。而且,它允许鉴定偏离菌株内主要反应谱的个体。
结论
本方法允许在个体水平上表征实验动物的行为,因此对在统计分析中考虑个体差异的现有方法提供了有价值的贡献。