Goulding Evan H, Schenk A Katrin, Juneja Punita, MacKay Adrienne W, Wade Jennifer M, Tecott Laurence H
Department of Psychiatry, University of California, San Francisco, CA 94143, USA.
Proc Natl Acad Sci U S A. 2008 Dec 30;105(52):20575-82. doi: 10.1073/pnas.0809053106. Epub 2008 Dec 23.
Patterns of behavior exhibited by mice in their home cages reflect the function and interaction of numerous behavioral and physiological systems. Detailed assessment of these patterns thus has the potential to provide a powerful tool for understanding basic aspects of behavioral regulation and their perturbation by disease processes. However, the capacity to identify and examine these patterns in terms of their discrete levels of organization across diverse behaviors has been difficult to achieve and automate. Here, we describe an automated approach for the quantitative characterization of fundamental behavioral elements and their patterns in the freely behaving mouse. We demonstrate the utility of this approach by identifying unique features of home cage behavioral structure and changes in distinct levels of behavioral organization in mice with single gene mutations altering energy balance. The robust, automated, reproducible quantification of mouse home cage behavioral structure detailed here should have wide applicability for the study of mammalian physiology, behavior, and disease.
小鼠在其饲养笼中表现出的行为模式反映了众多行为和生理系统的功能及相互作用。因此,对这些模式进行详细评估有可能为理解行为调节的基本方面及其受疾病过程干扰的情况提供一个有力工具。然而,要在不同行为的离散组织水平上识别和检查这些模式一直难以实现且自动化。在这里,我们描述了一种自动方法,用于定量表征自由活动小鼠的基本行为要素及其模式。我们通过识别饲养笼行为结构的独特特征以及单基因突变改变能量平衡的小鼠在不同行为组织水平上的变化,来证明这种方法的实用性。这里详细介绍的对小鼠饲养笼行为结构进行稳健、自动、可重复的量化,应该在哺乳动物生理学、行为学和疾病研究中具有广泛的适用性。