Mechanisms of offline motor learning at a microscale of seconds in large-scale crowdsourced data
Mechanisms of offline motor learning at a microscale of seconds in large-scale crowdsourced data
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DOI：
10.1038/s41539-020-0066-9
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发表时间：
2020-01-01
影响因子：
4.2
通讯作者：
Cohen, Leonardo G.
中科院分区：
文献类型：
--
作者：
Bonstrup, Marlene;Iturrate, Inaki;Cohen, Leonardo G.
早期人类运动技能学习期间的表现改善被认为是由练习期间的短时间休息驱动的，以秒为单位。为了揭示这些“微离线”收益背后的未知机制，我们利用了在线众包提供的抽样能力（所有实验的累积N =951）。首先，我们复制了最初的实验室研究结果，证明了在日常生活环境中学习任务的受试者的普遍性（N=389）。第二，我们表明，离线改善休息时，显着缩短练习期的持续时间是等效的，从而证实他们不是从性能疲劳恢复的结果（N=118）。第三，每次练习后立即进行的回溯性干扰相对于经过一段时间后的干扰降低了学习率（N=373），表明运动记忆在几秒的微尺度上稳定。最后，我们表明，随机终止的实践期间并没有影响离线增益，排除了预测电机放缓的贡献（N=71）。总之，这些结果表明，微离线收益表明快速，在几秒钟内巩固占早期技能学习。
Performance improvements during early human motor skill learning are suggested to be driven by short periods of rest during practice, at the scale of seconds. To reveal the unknown mechanisms behind these "micro-offline" gains, we leveraged the sampling power offered by online crowdsourcing (cumulative N over all experiments=951). First, we replicated the original in-lab findings, demonstrating generalizability to subjects learning the task in their daily living environment (N=389). Second, we show that offline improvements during rest are equivalent when significantly shortening practice period duration, thus confirming that they are not a result of recovery from performance fatigue (N=118). Third, retroactive interference immediately after each practice period reduced the learning rate relative to interference after passage of time (N=373), indicating stabilization of the motor memory at a microscale of several seconds. Finally, we show that random termination of practice periods did not impact offline gains, ruling out a contribution of predictive motor slowing (N=71). Altogether, these results demonstrate that micro-offline gains indicate rapid, within-seconds consolidation accounting for early skill learning.