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A bird’s-eye view of brain activity in socially interacting mice through mobile edge computing (MEC)

机译:通过移动边缘计算(MEC)在社会交互小鼠中脑活动的鸟瞰图

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Social cognition requires neural processing, yet a unifying method linking particular brain activities and social behaviors is lacking. Here, we embedded mobile edge computing (MEC) and light emitting diodes (LEDs) on a neurotelemetry headstage, such that a particular neural event of interest is processed by the MEC and subsequently an LED is illuminated, allowing simultaneous temporospatial visualization of that neural event in multiple, socially interacting mice. As a proof of concept, we configured our system to illuminate an LED in response to gamma oscillations in the basolateral amygdala (BLA gamma) in freely moving mice. We identified (i) BLA gamma responses to a spider robot, (ii) affect-related BLA gamma during conflict, and (iii) formation of defensive aggregation under a threat by the robot, and reduction of BLA gamma responses in the inner-located mice. Our system can provide an intuitive framework for examining brain-behavior connections in various ecological situations and population structures.
机译:社会认知需要神经处理,但缺乏关联特定大脑活动和社会行为的统一方法。这里,我们在神经电气臂脊台上嵌入移动边缘计算(MEC)和发光二极管(LED),使得MEC处理特定的兴趣事件并随后照明LED,允许同时对该神经事件进行同时的间谍可视化在多个社会相互作用的小鼠中。作为概念证明,我们将系统配置为在自由移动小鼠中响应Basolateral Amygdala(BLA Gamma)中的伽马振荡来照亮LED。我们确定(i)BLA Gamma对蜘蛛机器人的反应,(ii)在冲突期间影响相关的BLA伽玛,以及(iii)在机器人威胁下形成防御性聚集,并在内部定位的BLA Gamma反应减少老鼠。我们的系统可以提供一种直观的框架,用于在各种生态情况和人口结构中检查大脑行为联系。

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