Menon V
Stanford Cognitive and Systems Neuroscience Laboratory, Palo Alto, CA.
Prog Brain Res. 2016;227:159-86. doi: 10.1016/bs.pbr.2016.04.026. Epub 2016 Jun 10.
Numerical cognition relies on interactions within and between multiple functional brain systems, including those subserving quantity processing, working memory, declarative memory, and cognitive control. This chapter describes recent advances in our understanding of memory and control circuits in mathematical cognition and learning. The working memory system involves multiple parietal-frontal circuits which create short-term representations that allow manipulation of discrete quantities over several seconds. In contrast, hippocampal-frontal circuits underlying the declarative memory system play an important role in formation of associative memories and binding of new and old information, leading to the formation of long-term memories that allow generalization beyond individual problem attributes. The flow of information across these systems is regulated by flexible cognitive control systems which facilitate the integration and manipulation of quantity and mnemonic information. The implications of recent research for formulating a more comprehensive systems neuroscience view of the neural basis of mathematical learning and knowledge acquisition in both children and adults are discussed.
数字认知依赖于多个功能性脑系统内部及之间的相互作用,这些系统包括负责数量处理、工作记忆、陈述性记忆和认知控制的系统。本章描述了我们在理解数学认知与学习中的记忆和控制回路方面的最新进展。工作记忆系统涉及多个顶叶 - 额叶回路,这些回路创建短期表征,使人们能够在几秒钟内对离散数量进行操作。相比之下,陈述性记忆系统所依赖的海马体 - 额叶回路在联想记忆的形成以及新旧信息的绑定中发挥着重要作用,从而导致长期记忆的形成,这种长期记忆能够超越个体问题属性进行概括。信息在这些系统之间的流动由灵活的认知控制系统调节,该系统促进数量信息和记忆信息的整合与操作。本文还讨论了近期研究对于构建一个更全面的系统神经科学观点的意义,该观点涉及儿童和成人数学学习及知识获取的神经基础。