COMPASS: Continuous Open Mouse Phenotyping of Activity and Sleep Status.
COMPASS: Continuous Open Mouse Phenotyping of Activity and Sleep Status.
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DOI：
10.12688/wellcomeopenres.9892.2
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发表时间：
2016
影响因子：
--
通讯作者：
Peirson SN
中科院分区：
文献类型：
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作者：
Brown LA;Hasan S;Foster RG;Peirson SN
背景：活动和休息节律的破坏发生在许多疾病中，并提供了健康生理和行为的重要指标。然而，在睡眠和昼夜节律研究领域之外，由于需要专门的资源和专业知识，这些节律过程很少被测量。直到最近，测量实验室啮齿动物活动的主要方法一直是基于自愿跑轮活动。相比之下，测量睡眠需要使用脑电图（EEG），这涉及侵入性外科手术和耗时的数据分析。 方法：在这里，我们描述了一个简单的，非侵入性的系统来测量小鼠的活动，基于被动红外（PIR）运动传感器。仔细校准该系统将允许用户同时评估小鼠的睡眠状态。使用开源工具和简单的传感器可以降低成本和数据文件的大小，以提高易用性和吸收。 结果如下：除了提供关于昼夜节律活动参数的准确数据之外，在这里，我们表明>40秒的延长不动性提供了可靠的睡眠指标，与EEG定义的睡眠良好相关（Pearson r >0.95，4只小鼠）。 结论：虽然对小鼠睡眠模式的任何详细分析都需要EEG，但行为定义的睡眠提供了一种同时对昼夜节律和睡眠进行表型分析的有价值的非侵入性方法。虽然以前的方法依赖于对视频数据的分析，但在这里，我们表明简单的运动传感器提供了一种廉价有效的替代方案，可以进行数周甚至数月的实时分析和纵向研究。产生的数据文件很小，便于存放和共享。我们将该系统命名为COMPASS -连续开放式小鼠活动和睡眠状态表型分析。这种简单的方法在表型筛选中特别有价值，并为非专家提供了评估活动和休息周期的理想工具。
Background: Disruption of rhythms in activity and rest occur in many diseases, and provide an important indicator of healthy physiology and behaviour. However, outside the field of sleep and circadian rhythm research, these rhythmic processes are rarely measured due to the requirement for specialised resources and expertise. Until recently, the primary approach to measuring activity in laboratory rodents has been based on voluntary running wheel activity. By contrast, measuring sleep requires the use of electroencephalography (EEG), which involves invasive surgical procedures and time-consuming data analysis. Methods: Here we describe a simple, non-invasive system to measure home cage activity in mice based upon passive infrared (PIR) motion sensors. Careful calibration of this system will allow users to simultaneously assess sleep status in mice. The use of open-source tools and simple sensors keeps the cost and the size of data-files down, in order to increase ease of use and uptake. Results: In addition to providing accurate data on circadian activity parameters, here we show that extended immobility of >40 seconds provides a reliable indicator of sleep, correlating well with EEG-defined sleep (Pearson’s r >0.95, 4 mice). Conclusions: Whilst any detailed analysis of sleep patterns in mice will require EEG, behaviourally-defined sleep provides a valuable non-invasive means of simultaneously phenotyping both circadian rhythms and sleep. Whilst previous approaches have relied upon analysis of video data, here we show that simple motion sensors provide a cheap and effective alternative, enabling real-time analysis and longitudinal studies extending over weeks or even months. The data files produced are small, enabling easy deposition and sharing. We have named this system COMPASS - Continuous Open Mouse Phenotyping of Activity and Sleep Status. This simple approach is of particular value in phenotyping screens as well as providing an ideal tool to assess activity and rest cycles for non-specialists.