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Steps towards a computational ethology: an automatized, interactive setup to investigate filial imprinting and biological predispositions
Biological Cybernetics ( IF 1.9 ) Pub Date : 2021-07-17 , DOI: 10.1007/s00422-021-00886-6
Mirko Zanon 1 , Bastien S Lemaire 1 , Giorgio Vallortigara 1
Affiliation  

Soon after hatching, the young of precocial species, such as domestic chicks or ducklings, learn to recognize their social partner by simply being exposed to it (imprinting process). Even artificial objects or stimuli displayed on monitor screens can effectively trigger filial imprinting, though learning is canalized by spontaneous preferences for animacy signals, such as certain kinds of motion or a face-like appearance. Imprinting is used as a behavioural paradigm for studies on memory formation, early learning and predispositions, as well as number and space cognition, and brain asymmetries. Here, we present an automatized setup to expose and/or test animals for a variety of imprinting experiments. The setup consists of a cage with two high-frequency screens at the opposite ends where stimuli are shown. Provided with a camera covering the whole space of the cage, the behaviour of the animal is recorded continuously. A graphic user interface implemented in Matlab allows a custom configuration of the experimental protocol, that together with Psychtoolbox drives the presentation of images on the screens, with accurate time scheduling and a highly precise framerate. The setup can be implemented into a complete workflow to analyse behaviour in a fully automatized way by combining Matlab (and Psychtoolbox) to control the monitor screens and stimuli, DeepLabCut to track animals’ behaviour, Python (and R) to extract data and perform statistical analyses. The automated setup allows neuro-behavioural scientists to perform standardized protocols during their experiments, with faster data collection and analyses, and reproducible results.



中文翻译:

迈向计算行为学的步骤:用于研究子孙印记和生物倾向的自动化交互式设置

孵化后不久,早熟物种的幼仔,例如家养小鸡或小鸭,通过简单地接触它来学会识别他们的社会伙伴(印记过程)。即使是显示在监视器屏幕上的人造物体或刺激也可以有效地触发子孙印记,尽管学习是通过对生命信号的自发偏好来引导的,例如某些类型的运动或类似脸的外观。印记被用作研究记忆形成、早期学习和倾向,以及数字和空间认知以及大脑不对称性的行为范式。在这里,我们提出了一种自动化设置,用于暴露和/或测试动物以进行各种印记实验。该装置由一个笼子组成,在显示刺激的两端有两个高频屏幕。提供覆盖笼子整个空间的摄像机,连续记录动物的行为。在 Matlab 中实现的图形用户界面允许自定义配置实验协议,与 Psychtoolbox 一起驱动屏幕上的图像呈现,具有准确的时间安排和高精度的帧速率。通过结合 Matlab(和 Psychtoolbox)来控制监视器屏幕和刺激,DeepLabCut 跟踪动物的行为,Python(和 R)来提取数据和执行统计,该设置可以实现到一个完整的工作流程中,以完全自动化的方式分析行为分析。自动化设置允许神经行为科学家在他们的实验期间执行标准化协议,更快的数据收集和分析,以及可重复的结果。具有准确的时间调度和高精度的帧率。通过结合 Matlab(和 Psychtoolbox)来控制监视器屏幕和刺激,DeepLabCut 跟踪动物的行为,Python(和 R)来提取数据和执行统计,该设置可以实现到一个完整的工作流程中,以完全自动化的方式分析行为分析。自动化设置允许神经行为科学家在他们的实验期间执行标准化协议,更快的数据收集和分析,以及可重复的结果。具有准确的时间调度和高精度的帧率。通过结合 Matlab(和 Psychtoolbox)来控制监视器屏幕和刺激,DeepLabCut 跟踪动物的行为,Python(和 R)来提取数据和执行统计,该设置可以实现到一个完整的工作流程中,以完全自动化的方式分析行为分析。自动化设置允许神经行为科学家在他们的实验期间执行标准化协议,更快的数据收集和分析,以及可重复的结果。

更新日期:2021-07-18
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