The flexibility-generalisability trade-off during the acquisition and reuse of abstract representations

人类通过对从经验中获得的信息进行抽象和解构，从而获得关于世界的知识。抽象涉及到灵活性和通用性之间的权衡；丰富、详细的知识可以在狭窄的语境中灵活使用，而抽象的知识可以以更有限的方式使用，但可以推广到更广泛的语境中。大脑如何获取和重用抽象知识是一个开放的研究领域。特别是，学习的结构（观察的顺序和信息内容）如何影响所获得的知识的性质还没有得到很好的理解。首先，我们计划使用功能磁共振成像来研究大脑活动模式如何对应于认知任务中的灵活性和泛化表现。其次，我们的目标是设计一个主动学习任务来研究学习结构如何在灵活性和一般性之间进行权衡。这将为学习结构如何影响获得的知识和表现的特性提供生物学基础，有助于系统神经科学对学习和泛化的理解。此外，这些见解还可以应用于教育和机器学习，为教学方法和教育技术提供信息，并有助于设计更强大、更灵活的计算模型。相关的BBSRC优先领域：-生物科学的系统方法-数据驱动的生物学-生物科学的技术开发-脑科学和心理健康-电子科学

Humans derive knowledge about the world by abstracting and decontextualising information acquired through experience. Abstraction involves a trade-off between flexibility and generalisability; rich, detailed knowledge can be used flexibly in a narrow context, while abstract knowledge can be used in a more limited way but can be generalized to a wider variety of contexts. How the brain acquires and reuses abstract knowledge is an open area of research. In particular, how the structure of learning (the order and information content of observations) affects the properties of acquired knowledge is not well understood. Firstly, we plan to use fMRI to investigate how patterns of brain activity correspond to flexibility and generalisation performance in a cognitive task. Secondly, we aim to design an active learning task to study how the structure of learning mediates the trade-off between flexibility and generality. This would provide a biological basis for how the structure of learning affects the properties of acquired knowledge and performance, contributing towards a Systems Neuroscience understanding of learning and generalisation. Additionally, these insights could have applications in education and machine learning, by informing pedagogical methods and education technology, as well as contributing to the design of more robust and flexible computational models.Relevant BBSRC priority areas: - Systems approaches to the biosciences- Data-driven biology- Technology development for the biosciences- Brain science and mental health- e-Science