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焦虑样行为的行为学和时间分析:高架十字迷宫模型二十年回顾。

Ethological and temporal analyses of anxiety-like behavior: the elevated plus-maze model 20 years on.

作者信息

Carobrez A P, Bertoglio L J

机构信息

Departamento de Farmacologia, CCB, Universidade Federal de Santa Catarina, Florianópolis, SC, 88049-900, Brazil.

出版信息

Neurosci Biobehav Rev. 2005;29(8):1193-205. doi: 10.1016/j.neubiorev.2005.04.017. Epub 2005 Aug 9.

DOI:10.1016/j.neubiorev.2005.04.017
PMID:16084592
Abstract

As well as being considered a reliable measurement instrument of animal anxiety-like behavior, the elevated plus-maze (EPM) is also used as a post-hoc test to evaluate emotionality in genetically modified rodents. The present review considers factors which may further improve the validity (predictive/face/construct) of the EPM model: (1) the importance of measuring defensive patterns of response such as risk assessment in addition to traditional measures such as open arm time; (2) other methodological refinements such as min-by-min scoring and use of a test/retest protocol; and (3) the identification and control of major sources of variability in this test. To estimate whether current use of the EPM by researchers takes the above factor into account, a survey of the recent literature was conducted. Results showed that the majority of studies have not yet assimilated these important considerations into their use of the EPM. For example, although risk assessment measures may be more sensitive to anxiety modulating drugs than traditional measures, only a quarter of studies have adopted them. It is hoped that this review can provide insights into the optimal use of the EPM, a simple task that can be very complex in terms of behavioral analysis.

摘要

高架十字迷宫(EPM)不仅被视为动物焦虑样行为的可靠测量工具,还被用作事后检验,以评估转基因啮齿动物的情绪。本综述考虑了可能进一步提高EPM模型有效性(预测性/表面/结构)的因素:(1)除了传统测量指标(如开放臂停留时间)外,测量防御性反应模式(如风险评估)的重要性;(2)其他方法学改进,如逐分钟评分和使用重测方案;(3)识别和控制该测试中主要变异来源。为了评估研究人员目前使用EPM时是否考虑了上述因素,我们对近期文献进行了调查。结果表明,大多数研究在使用EPM时尚未将这些重要因素纳入考虑。例如,尽管风险评估指标可能比传统指标对焦虑调节药物更敏感,但只有四分之一的研究采用了这些指标。希望本综述能够为EPM的最佳使用提供见解,这一简单任务在行为分析方面可能非常复杂。

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