自动注释的运动跟踪识别了在慢性社会失败压力之后的独特的社会行为特征
Joeri Bordes1, Lucas Miranda2,3, Maya Reinhardt1
1Research Group Neurobiology of Stress Resilience, Max Planck Institute of Psychiatry, 80804, Munich, Germany.
Nature communications
|July 18, 2023
概括
新的工具DeepOF分析了老鼠在压力后的行为. 它揭示了与压力诱导的大型抑郁症 (MDD) 相关的明显的社会互动模式,有助于研究和药物开发.
科学领域:
- 神经科学是一个神经科学.
- 行为科学 行为科学
- 计算生物学 计算生物学
背景情况:
- 严重的压力会增加与压力相关的疾病的风险,例如严重抑郁症 (MDD).
- 大型抑郁症的特征是社会功能和动机受损.
- 慢性社会失败压力是研究MDD的关键动物模型.
研究的目的:
- 介绍DeepOF,这是一个开源工具,用于分析小鼠的个人和社会行为.
- 使用无标记物姿势估计来进行自然主义的行为评估.
- 在MDD的小鼠模型中调查压力诱导的行为变化.
主要方法:
- 开发了DeepOF,使用DeepLabCut注释的姿势数据使用监督和无监督管道.
- 将DeepOF应用于遭受慢性社会失败压力的雄性小鼠.
- 将DeepOF的发现与经典的社会回避任务进行了比较.
主要成果:
- DeepOF检测到明显的压力诱导的社会行为模式,特别是在最初的社交接触.
- 这些模式随着时间的推移而习惯.
- 与传统方法相比,DeepOF提供了更清晰,更详细的行为概况.
结论:
- DeepOF增强了对动物社会行为和与压力相关的疾病的研究.
- 该工具促进了行为分类中的可重现性和统一性.
- DeepOF促进了对精神疾病的生物学洞察力和潜在药物开发.
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