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用于识别各种特定大鼠行为的自动化系统。

An automated system for the recognition of various specific rat behaviours.

机构信息

Noldus Information Technology BV, Wageningen, Netherlands.

出版信息

J Neurosci Methods. 2013 Sep 15;218(2):214-24. doi: 10.1016/j.jneumeth.2013.05.012. Epub 2013 Jun 11.

DOI:10.1016/j.jneumeth.2013.05.012
PMID:23769769
Abstract

The automated measurement of rodent behaviour is crucial to advance research in neuroscience and pharmacology. Rats and mice are used as models for human diseases; their behaviour is studied to discover and develop new drugs for psychiatric and neurological disorders and to establish the effect of genetic variation on behavioural changes. Such behaviour is primarily labelled by humans. Manual annotation is labour intensive, error-prone and subject to individual interpretation. We present a system for automated behaviour recognition (ABR) that recognises the rat behaviours 'drink', 'eat', 'sniff', 'groom', 'jump', 'rear unsupported', 'rear wall', 'rest', 'twitch' and 'walk'. The ABR system needs no on-site training; the only inputs needed are the sizes of the cage and the animal. This is a major advantage over other systems that need to be trained with hand-labelled data before they can be used in a new experimental setup. Furthermore, ABR uses an overhead camera view, which is more practical in lab situations and facilitates high-throughput testing more easily than a side-view setup. ABR has been validated by comparison with manual behavioural scoring by an expert. For this, animals were treated with two types of psychopharmaca: a stimulant drug (Amphetamine) and a sedative drug (Diazepam). The effects of drug treatment on certain behavioural categories were measured and compared for both analysis methods. Statistical analysis showed that ABR found similar behavioural effects as the human observer. We conclude that our ABR system represents a significant step forward in the automated observation of rodent behaviour.

摘要

自动化测量啮齿动物的行为对于推进神经科学和药理学研究至关重要。老鼠被用作人类疾病的模型;研究它们的行为是为了发现和开发治疗精神和神经紊乱的新药,并确定遗传变异对行为变化的影响。这些行为主要由人类进行标注。手动标注既耗费人力,又容易出错,并且还受到个体解释的影响。我们提出了一种用于自动化行为识别(ABR)的系统,该系统可识别大鼠的“喝”、“吃”、“嗅”、“梳理”、“跳”、“无支撑后肢站立”、“靠墙后肢站立”、“休息”、“抽搐”和“行走”等行为。ABR 系统不需要现场培训;唯一需要的输入是笼子和动物的大小。这是与其他系统相比的一个主要优势,其他系统需要使用手工标注的数据进行培训,然后才能在新的实验设置中使用。此外,ABR 使用顶置摄像头视图,与侧置设置相比,这种视图在实验室环境中更实用,并且更便于进行高通量测试。ABR 通过与专家进行的手动行为评分进行比较得到了验证。为此,动物接受了两种精神药物的治疗:兴奋剂(安非他命)和镇静剂(地西泮)。使用这两种分析方法测量并比较了药物治疗对某些行为类别的影响。统计分析表明,ABR 发现了与人类观察者相似的行为效果。我们得出结论,我们的 ABR 系统代表了在啮齿动物行为的自动化观察方面向前迈出的重要一步。

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