CAREER: Action Binding During Long-term Sequential Skill Learning: Computational and Neural Mechanisms
CAREER: Action Binding During Long-term Sequential Skill Learning: Computational and Neural Mechanisms
批准号:
1351748
负责人:
Timothy Verstynen
金额:
$50.78万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-06-01 至 2020-09-30
中文摘要
一个人是如何学习一项复杂的技能,随着时间的推移,比如学习演奏钢琴奏鸣曲?这种能力需要相互作用的处理水平,包括概念知识(例如,乐谱上旋律的音符)和动作生产(例如,物理按钢琴键的动作)。该研究项目将结合计算模型、神经成像和脑刺激方法来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。这项研究利用了这样一个事实,即运动学习在计时运动中留下了一个特征,称为“分块”。该项目的影响从临床康复延伸到脑功能的基本模型。一些神经退行性疾病(如帕金森病)的标志性症状是难以学习新技能。了解健康大脑中技能学习是如何发生的,可以为神经系统疾病如何影响技能学习提供关键见解。在科学上,本研究项目还将尝试连接认知科学(顺序技能学习)和神经科学(基底神经节可塑性)两个很大程度上独立的文献,为建立良好的心理现象提供有生物学意义的基础。最后,通过生产将向公众提供的新工具和新数据集,这项工作将与更广泛的开放科学社区相结合,该社区寻求通过改善对工具和数据的获取来促进科学事业。
英文摘要
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.
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