脊柱内部神经元群体动态 基础的灵活模式生成
bioRxiv : the preprint server for biology
|July 1, 2024
概括
研究人员使用人工智能分析了猫在运动过程中脊髓内部神经元的活动. 这揭示了神经群体动态如何精确地控制步骤定时和肌肉力量,为运动控制提供了洞察力.
科学领域:
- 神经科学是一个神经科学.
- 计算神经科学是一种神经科学.
- 发动机控制器的控制器
背景情况:
- 哺乳动物的脊柱运动网络包括各种内部神经元,这些内部神经元对于编排运动至关重要.
- 了解脊柱内部神经网络如何计算和修改运动输出仍然是一个重大挑战.
研究的目的:
- 为了研究脊柱内部神经元群活动与运动输出之间的关系.
- 揭示神经动力学在毫秒时间尺度上如何影响一步一步的运动控制.
主要方法:
- 对腰部内部神经元群体记录和多肌肉电肌图分析,用于执行空气步行的脊椎猫.
- 应用人工智能方法来识别内部神经元群活动的状态空间轨迹.
主要成果:
- 内部神经元状态空间轨迹中的特定区域与延伸器-曲器交替中的毫秒时间尺度调整相对应.
- 轨迹路径的变化与肌肉输出大小在单步基础上的微伏尺度调整密切相关.
结论:
- 脊柱内部神经元人口活动动态,当通过状态空间轨迹分析时,精确地捕捉出运动时间和肌肉激活幅度的变化.
- 这项研究提供了一个高分辨率的视图的神经计算底层的运动控制在个别步骤的水平.
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