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在任务控制模式之间切换会产生更高的重编程成本,而不是重新编程响应.
Dana Maslovat1, Alex Bui1, Allison Bui1
1School of Human Kinetics, University of Ottawa, 200 Lees Ave, Ottawa, ON, Canada.
Neuroscience
|August 5, 2024
概括
在预测和反应运动控制之间切换需要大量的重编程时间. 大脑需要更多的时间来切换控制模式,而不是启动新的反应.
科学领域:
- 发动机控制器 发动机控制器
- 人类运动科学 人类运动科学
- 认知神经科学是一种认知神经科学.
背景情况:
- 运动同步在反应和预测控制模式之间有所不同.
- 反应控制同步肌肉活动 (EMG),导致肢体异步运动.
- 预测控制通过延迟肌肉活动的开始来同步四肢运动.
研究的目的:
- 调查在预测和反应控制模式之间切换的重编程成本.
- 检查警告刺激的时间如何影响切换控制模式的能力.
- 量化与同步四肢运动的切换控制策略相关的时间成本.
主要方法:
- 参与者执行了一项同步的手和脚跟提升任务.
- 在运动目标前250毫秒或500毫秒呈现警告刺激.
- 测量了反应时间 (RT),以评估控制模式切换和重编程成本.
主要成果:
- 参与者只有当刺激在目标时间提前500毫秒时,才成功切换到反应性对照.
- 与简单的和选择性的RT任务相比,切换到反应式控制导致了显著更长的RT任务.
- 切换控制模式的重新编程成本很大,超过了 de novo 响应编程的时间.
结论:
- 在预测式和反应式电机控制之间切换会产生大量的重编程成本.
- 切换控制模式的能力取决于可用的准备时间.
- 这些发现突出了参与调整运动控制策略的复杂神经过程.
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