快速反对分类感应运动错误的响应,这些错误并不表明错误的大小是基于短期和长期记忆的优化
Michael R McGarity-Shipley1, Simona Markovik Jantz1, Roland S Johansson2
1Centre for Neuroscience Studies, Queen's University, Kingston, Ontario K7L 3N6, Canada.
概括
当一个物体出乎意料地沉重时,运动系统迅速适应起重力,使用内存来调整试验中的反应. 这保证了在不同的起重环境中有效地操纵物体.
科学领域:
- 神经科学是一个神经科学.
- 发动机控制器的控制器
- 人类运动性能 人类运动性能
背景情况:
- 熟练的运动性能依赖于快速的纠正反应,以维持运动目标,尽管存在干扰.
- 已知在触及过程中纠正反应的适应性,但对物体操纵后的对象操纵过程中反应的理解较少.
- 对意外沉重物体的纠正反应涉及由于缺少感官反而导致垂直力快速增加.
研究的目的:
- 为了研究当一个物体的重量意外地比预期的更重时,纠正式提升反应的适应性.
- 为了确定这个响应是否可以根据以前的升降器的记忆进行调整,考虑到未知的错误大小.
- 检查短期和长期经验如何影响提升反应的收益.
主要方法:
- 参与者反复举起物体,在"捕获试验"中偶尔会增加重量.
- 测量了纠正反应的增益 (力增加率).
- 根据试验中反应增长的变化及其与基线和捕捞试验重量的关系来评估适应性.
主要成果:
- 参与者在两到三次捕获试验中将响应的增加调整为更重的物体重量.
- 第一次捕获试验的响应增长与物体的基线重量进行缩放.
- 这表明基于短期 (最近的试验) 和长期 (基线) 经验,提升反应的适应.
结论:
- 校正式提升反应的增益是根据先前的经验而适应的,即使精确的感觉预测错误是未知的.
- 近期和长期记忆都有助于调整校正力的规模,在不同的举重环境中保持响应效率.
- 这突显了运动系统能够根据学习到的预期预测和调整运动指令的能力.
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