CAREER: Action Binding During Long-term Sequential Skill Learning: Computational and Neural Mechanisms

一个人是如何学习一项复杂的技能的，比如学习弹钢琴奏鸣曲？这种能力需要交互处理水平，包括概念知识（例如，乐谱上旋律的音符）和马达产生（例如，物理地按压钢琴键的动作）。这项研究计划将结合联合收割机计算模型，神经成像和脑刺激方法，探索这两个层次的顺序技能知识是如何通过相互作用的大脑系统获得的。这项工作利用了运动学习在计时运动中留下一个标记的事实，称为“组块”。“这个项目的影响从临床康复延伸到大脑功能的基本模型。一些神经退行性疾病的标志性症状，如帕金森病，是学习新技能的困难。了解技能学习如何在健康的大脑中发生，可以为神经系统疾病如何影响它提供重要的见解。科学上，这项研究计划还将试图弥合认知科学（顺序技能学习）和神经科学（基底神经节可塑性）两个基本独立的文献，为建立良好的心理现象提供生物学意义的基础。最后，通过制作新的工具和新的数据集，这项工作将与更广泛的开放科学界相结合，后者寻求通过改善工具和数据的获取来促进科学事业。

How does someone learn a complex skill that unfolds over time, such as learning to play a piano sonata? This ability entails interacting processing levels, including conceptual knowledge (e.g., the notes of the melody on the sheet of music) and motor production (e.g., the actions of physically pressing the piano keys). This research program will combine computational models, neuroimaging, and brain stimulation methods to explore how these two levels of sequential skill knowledge are acquired by interacting brain systems. The work takes advantage of the fact that motor learning leaves a signature in the timing movements, called "chunking." The impact of this project extends from clinical rehabilitation to basic models of brain function. A hallmark symptom of some neurodegenerative conditions, like Parkinson's disease, is a difficulty in learning new skills. Understanding how skill learning occurs in the healthy brain can provide critical insights into how it is affected in neurological conditions. Scientifically, this research program will also attempt to bridge two largely independent literatures in cognitive science (sequential skill learning) and neuroscience (basal ganglia plasticity), providing a biologically meaningful foundation for well established psychological phenomena. Finally, by producing new tools and novel data sets that will be made publicly available, the work will integrate with the broader open-science community that seeks to foster the scientific enterprise by improving access to tools and data.