A fully automated social interaction chamber for studying social threat learning in mice.

IF 2.6 3区 医学 Q2 BEHAVIORAL SCIENCES Frontiers in Behavioral Neuroscience Pub Date : 2024-11-05 eCollection Date: 2024-01-01 DOI:10.3389/fnbeh.2024.1481935
Ellora M McTaggart, Noah W Miller, Maria M Ortiz-Juza, Nicolas C Pégard, Jose Rodriguez-Romaguera
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Abstract

Social interactions are fundamental for our survival as a predominately social species. We need and seek positive social interactions to navigate the world. However, when social interactions are negative, and occur in the presence of an aversive event, learning occurs to associate such social interactions as threatening. Gaining insight into the neural circuits that drive social threat learning is crucial for understanding social interactions. Animal models can be leveraged to employ technologies that allow us to track neuronal processes with very high resolution to obtain a better understanding of the neural circuits involved. To accomplish this, we need robust behavioral models that are replicable and high throughput. Here, we present an open-source social interaction chamber that detects social interaction and automatically pairs it with foot shock. The social interaction chamber is designed to easily integrate into modular chambers commonly used for auditory and context threat learning. It contains an array of optical gates that precisely track mouse-to-mouse interactions in real time with digital triggers that can communicate with external devices to deliver a foot shock. We find that pairing social interactions with electric foot shock using our fully automated social interaction chamber is optimal for social threat associations. We further demonstrate that timing of social contact with foot shock produces optimal learning.

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用于研究小鼠社会威胁学习的全自动社会互动室。
作为一个以社会性为主的物种,社会交往是我们生存的根本。我们需要并寻求积极的社会交往,以适应这个世界。然而,当社交互动是消极的,并且发生在厌恶事件的情况下时,我们就会学习将这种社交互动与威胁联系起来。深入了解驱动社会威胁学习的神经回路对于理解社会互动至关重要。我们可以利用动物模型,采用能让我们以极高分辨率跟踪神经元过程的技术,从而更好地了解相关的神经回路。为了实现这一目标,我们需要可复制、高通量的强大行为模型。在这里,我们介绍一种开源的社交互动室,它能检测社交互动,并自动将其与脚震配对。社交互动室的设计易于集成到常用于听觉和情境威胁学习的模块化室中。它包含一个光学门阵列,能实时精确地跟踪鼠标与鼠标之间的互动,并带有数字触发器,能与外部设备通信,以发出脚击。我们发现,使用我们的全自动社交互动室,将社交互动与电击脚掌配对使用,是社交威胁关联的最佳选择。我们还进一步证明,社交接触与脚电击的时机能产生最佳学习效果。
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来源期刊
Frontiers in Behavioral Neuroscience
Frontiers in Behavioral Neuroscience BEHAVIORAL SCIENCES-NEUROSCIENCES
CiteScore
4.70
自引率
3.30%
发文量
506
审稿时长
6-12 weeks
期刊介绍: Frontiers in Behavioral Neuroscience is a leading journal in its field, publishing rigorously peer-reviewed research that advances our understanding of the neural mechanisms underlying behavior. Field Chief Editor Nuno Sousa at the Instituto de Pesquisa em Ciências da Vida e da Saúde (ICVS) is supported by an outstanding Editorial Board of international experts. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians and the public worldwide. This journal publishes major insights into the neural mechanisms of animal and human behavior, and welcomes articles studying the interplay between behavior and its neurobiological basis at all levels: from molecular biology and genetics, to morphological, biochemical, neurochemical, electrophysiological, neuroendocrine, pharmacological, and neuroimaging studies.
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