An Automated Squint Method for Time-syncing Behavior and Brain Dynamics in Mouse Pain Studies.

IF 1.2 4区 综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES Jove-Journal of Visualized Experiments Pub Date : 2024-11-01 DOI:10.3791/67136
Nathan McCutcheon, Micah S Johnson, Brandon Rea, Mahnoor Ghumman, Levi Sowers, Rainbo Hultman
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Abstract

Spontaneous pain has been challenging to track in real time and quantify in a way that prevents human bias. This is especially true for metrics of head pain, as in disorders such as migraine. Eye squint has emerged as a continuous variable metric that can be measured over time and is effective for predicting pain states in such assays. This paper provides a protocol for the use of DeepLabCut (DLC) to automate and quantify eye squint (Euclidean distance between eyelids) in restrained mice with freely rotating head motions. This protocol enables unbiased quantification of eye squint to be paired with and compared directly against mechanistic measures such as neurophysiology. We provide an assessment of AI training parameters necessary for achieving success as defined by discriminating squint and non-squint periods. We demonstrate an ability to reliably track and differentiate squint in a CGRP-induced migraine-like phenotype at a sub second resolution.

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用于小鼠疼痛研究中行为和大脑动态时间同步的自动眯眼法
实时跟踪自发性疼痛并以防止人为偏差的方式对其进行量化一直是一项挑战。对于头部疼痛(如偏头痛)的测量尤其如此。眯眼已成为一种连续可变的指标,可在一段时间内进行测量,并能在此类检测中有效预测疼痛状态。本文提供了一种使用 DeepLabCut(DLC)自动量化受约束小鼠斜视(眼睑之间的欧氏距离)的方案,小鼠的头部运动可以自由旋转。该方案可将斜视的无偏量化与神经生理学等机理测量进行配对和直接比较。我们对人工智能训练参数进行了评估,这些参数是成功实现区分斜视和非斜视期所必需的。我们展示了在 CGRP 诱导的偏头痛样表型中以亚秒级分辨率可靠跟踪和区分斜视的能力。
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来源期刊
Jove-Journal of Visualized Experiments
Jove-Journal of Visualized Experiments MULTIDISCIPLINARY SCIENCES-
CiteScore
2.10
自引率
0.00%
发文量
992
期刊介绍: JoVE, the Journal of Visualized Experiments, is the world''s first peer reviewed scientific video journal. Established in 2006, JoVE is devoted to publishing scientific research in a visual format to help researchers overcome two of the biggest challenges facing the scientific research community today; poor reproducibility and the time and labor intensive nature of learning new experimental techniques.
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