Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA.
Developmental Psychology and Child Education Laboratory, University Paris Descartes, Paris, France.
Commun Biol. 2021 Mar 25;4(1):405. doi: 10.1038/s42003-021-01872-1.
Efficient memory-based problem-solving strategies are a cardinal feature of expertise across a wide range of cognitive domains in childhood. However, little is known about the neurocognitive mechanisms that underlie the acquisition of efficient memory-based problem-solving strategies. Here we develop, to the best of our knowledge, a novel neurocognitive process model of latent memory processes to investigate how cognitive training designed to improve children's problem-solving skills alters brain network organization and leads to increased use and efficiency of memory retrieval-based strategies. We found that training increased both the use and efficiency of memory retrieval. Functional brain network analysis revealed training-induced changes in modular network organization, characterized by increase in network modules and reorganization of hippocampal-cortical circuits. Critically, training-related changes in modular network organization predicted performance gains, with emergent hippocampal, rather than parietal cortex, circuitry driving gains in efficiency of memory retrieval. Our findings elucidate a neurocognitive process model of brain network mechanisms that drive learning and gains in children's efficient problem-solving strategies.
基于记忆的高效问题解决策略是儿童在广泛认知领域中专业知识的一个主要特征。然而，对于支持高效基于记忆的问题解决策略习得的神经认知机制知之甚少。在这里，我们开发了一个新颖的潜在记忆过程的神经认知过程模型，据我们所知，该模型旨在研究旨在提高儿童解决问题技能的认知训练如何改变大脑网络组织并导致基于记忆检索的策略的更多使用和效率提高。我们发现，训练增加了记忆检索的使用和效率。功能脑网络分析揭示了训练诱导的模块网络组织变化，其特征是网络模块的增加和海马体-皮质电路的重新组织。至关重要的是，模块化网络组织的训练相关变化预测了表现的提高，新兴的海马体而不是顶叶皮层电路驱动记忆检索效率的提高。我们的研究结果阐明了一个神经认知过程模型，该模型驱动着儿童高效问题解决策略的学习和提高。
