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Automated Behavioral Experiments in Mice Reveal Periodic Cycles of Task Engagement within Circadian Rhythms

机译:小鼠的自动行为实验揭示了昼夜节律中任务参与的周期性周期

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摘要

High-throughput automated experiments accelerate discovery in neuroscience research and reduce bias. To enable high-throughput behavioral experiments, we developed a user-friendly and scalable automated system that can simultaneously train hundreds of mice on behavioral tasks, with time-stamped behavioral information recorded continuously for weeks. We trained 12 cages of C57BL/6J mice (24 mice, 2 mice/cage) to perform auditory behavioral tasks. We found that circadian rhythms modulated overall behavioral activity as expected for nocturnal animals. However, auditory detection and discrimination accuracy remained consistently high in both light and dark cycles. We also found a periodic modulation of behavioral response rates only during the discrimination task, suggesting that the mice periodically reduce task engagement (i.e., take “breaks”) when task difficulty increases due to the more complex stimulus–response paradigm for discrimination versus detection. Our results highlight how automated systems for continuous high-throughput behavioral experiments enable both efficient data collection and new observations on animal behavior.
机译:高通量自动化实验可加快神经科学研究的发现并减少偏差。为了进行高通量的行为实验,我们开发了一个用户友好且可扩展的自动化系统,该系统可以同时训练数百只小鼠执行行为任务,并在数周内连续记录带时间戳的行为信息。我们训练了12个C57BL / 6J小鼠笼子(24只小鼠,每笼2只小鼠)来执行听觉行为任务。我们发现,昼夜节律可以调节夜间动物的整体行为活动。然而,在黑暗和黑暗周期中,听觉检测和辨别的准确性始终保持较高水平。我们还发现仅在歧视任务期间行为反应速率的周期性调节,这表明当任务难度增加时,由于歧视与检测的刺激-响应范式更加复杂,小鼠会定期减少任务投入(即“休息”)。我们的结果强调了用于连续高通量行为实验的自动化系统如何实现有效的数据收集和对动物行为的新观察。

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