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在行为小鼠中,将机械刺激与大脑记录相结合的远程自动传递

Remote automated delivery of mechanical stimuli coupled to brain recordings in behaving mice.

作者信息

Burdge Justin, Jhumka Anissa, Khan Ashar, Ogundare Simon, Baer Nicholas, Fulton Sasha, Kaplan Alexander, Bistis Brittany, Foster William, Thackray Joshua, Toussaint Andre, Li Miao, Morizawa Yosuke M, Nazarian Jacob, Yadessa Leah, George Arlene J, Delinois Abednego, Mayiseni Wadzanayi, Loran Noah, Yang Guang, Margolis David J, Abraira Victoria E, Abdus-Saboor Ishmail

机构信息

Zuckerman Mind Brain Behavior Institute, Columbia University in the City of New York.

Department of Biological Sciences, Columbia University in the City of New York.

出版信息

bioRxiv. 2025 Jun 8:2024.05.06.592101. doi: 10.1101/2024.05.06.592101.

Abstract

The canonical framework for testing pain and mechanical sensitivity in rodents is manual delivery of stimuli to the paw. However, this approach is time consuming, produces variability in results, requires significant training, and is ergonomically unfavorable to the experimenter. To circumvent limitations in manual delivery of stimuli, we have created a device called the ARM (Automated Reproducible Mechano-stimulator). Built using a series of linear stages, cameras, and stimulus holders, the ARM is more accurate at hitting the desired target, delivers stimuli faster, and decreases variability in delivery of von Frey hair filaments. We demonstrate that the ARM can be combined with traditional measurements of pain behavior and automated machine-learning based pipelines. Importantly, the ARM enables remote testing of mice with experimenters outside the testing room. Using remote testing, we found that mice habituated more quickly when an experimenter was not present and experimenter presence leads to significant sex-dependent differences in paw withdrawal and pain associated behaviors. Lastly, to demonstrate the utility of the ARM for neural circuit dissection of pain mechanisms, we combined the ARM with cellular-resolved microendoscopy in the amygdala, linking stimulus, behavior, and brain activity of amygdala neurons that encode negative pain states. Taken together, the ARM improves speed, accuracy, and robustness of mechanical pain assays and can be combined with automated pain detection systems and brain recordings to map central control of pain.

摘要

在啮齿动物中测试疼痛和机械敏感性的经典框架是手动向爪子施加刺激。然而,这种方法耗时、结果存在变异性、需要大量训练,并且从人体工程学角度对实验者不利。为了规避手动施加刺激的局限性,我们创建了一种名为ARM(自动可重复机械刺激器)的设备。ARM由一系列线性平台、摄像头和刺激物固定器组成,在击中目标时更精确,施加刺激更快,并减少了冯·弗里氏毛发细丝施加过程中的变异性。我们证明,ARM可以与传统的疼痛行为测量方法以及基于机器学习的自动化流程相结合。重要的是,ARM能够让实验者在测试室之外对小鼠进行远程测试。通过远程测试,我们发现当实验者不在场时小鼠适应得更快,并且实验者在场会导致爪子缩回及疼痛相关行为出现显著的性别差异。最后,为了证明ARM在疼痛机制神经回路剖析中的效用,我们将ARM与杏仁核中的细胞分辨率显微内窥镜检查相结合,将编码负性疼痛状态的杏仁核神经元的刺激、行为和大脑活动联系起来。综上所述,ARM提高了机械性疼痛检测的速度、准确性和稳健性,并且可以与自动化疼痛检测系统和大脑记录相结合,以绘制疼痛的中枢控制图谱。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17a6/12157349/5131c98f4777/nihpp-2024.05.06.592101v2-f0001.jpg

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