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通过移动边缘计算(MEC)对社交互动小鼠的大脑活动进行鸟瞰。

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

作者信息

Kim Jisoo, Kim Chaewoo, Han Hio-Been, Cho Cheol Jun, Yeom Wooseob, Lee Sung Q, Choi Jee Hyun

机构信息

Center for Neuroscience, Korea Institute of Science and Technology, Hwarang-ro 14-gil 5, Seongbuk-gu, Seoul 02792, South Korea.

Department of Brain and Cognitive Engineering, Korea University, Anam-dong 5ga, Seongbuk-gu, Seoul 02841, South Korea.

出版信息

Sci Adv. 2020 Dec 2;6(49). doi: 10.1126/sciadv.abb9841. Print 2020 Dec.

Abstract

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.

摘要

社会认知需要神经处理,但目前缺乏一种将特定大脑活动与社会行为联系起来的统一方法。在这里,我们将移动边缘计算(MEC)和发光二极管(LED)嵌入到一个神经遥测头端设备中,使得感兴趣的特定神经事件由MEC进行处理,随后LED被点亮,从而能够在多只进行社会互动的小鼠中同时对该神经事件进行时空可视化。作为概念验证,我们将系统配置为在自由活动的小鼠中,响应基底外侧杏仁核中的伽马振荡(BLA伽马)来点亮LED。我们识别出:(i)对蜘蛛机器人的BLA伽马反应;(ii)冲突期间与情感相关的BLA伽马;以及(iii)在机器人威胁下形成的防御性聚集,以及位于内部的小鼠中BLA伽马反应的减少。我们的系统可以为研究各种生态情境和群体结构中的脑-行为联系提供一个直观的框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40cd/7821890/0ed72de1832b/abb9841-F1.jpg

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