Short-, Medium- and Long-Term Neural Dynamics of Conceptual Learning

概念学习的短期、中期和长期神经动力学学习概念的过程本质上是动态的，随着概念的各个方面逐渐被理解，既有短期的神经变化，也有长期的材料巩固，以便将来检索。高级形式的学习，如语言和数学推理，只能在人类身上进行研究，因为它们超出了其他物种的已知能力。因此，需要提供高时间和高空间分辨率的非侵入性大脑研究技术。该提案代表了学习神经科学的一个新兴领域，基于最近的一项发展，该发展使功能磁共振成像（fMRI）的方法能够揭示人类大脑中概念学习的神经动力学的全部范围。到目前为止，功能磁共振成像一直是一种只能研究长期神经变化的工具，因为它的反应是基于大脑血液反应的缓慢的时间动态。因此，不可能通过人类大脑局部皮层激活的复合体来跟踪学习过程的时间演变。将采用一种创新的方法来分析神经动力学，以研究在学习语言和数学推理任务期间大脑中的神经信息流，以确定这两种学习是如何发生的。此外，与认知加工研究相比，功能磁共振成像技术具有更高的空间分辨率，这将使研究重点集中在局部神经群的分析上。我们的新技术发展使我们能够将认知过程的神经动力学解析为其固有的时间分辨率，并跟踪概念学习过程中动态的变化。这种新颖的方法对于理解一般学习过程，特别是概念学习过程中神经种群动态的变化具有很高的价值。目前的提案将提供人类大脑认知过程的神经动力学知识，这将对我们对学习过程的理解产生革命性的影响。特别是，它将从根本上增强建立学习过程的神经基础计算模型的能力，并允许在第一次学习高级概念时将大脑中的信息流序列映射出来。这种新能力将促进从认知神经科学领域到教育领域的有效学习动态信息传递的详细策略。

Short-, Medium- and Long-Term Neural Dynamics of Conceptual LearningThe process of learning concepts is inherently dynamic, with both short-term neural changes as the aspects of the concept are progressively understood, and longer-term consolidation of the material for retrieval at future times. Higher forms of learning, such as verbal and mathematical reasoning, can be studied only in humans because they are beyond the known abilities of other species. Thus, non-invasive brain research technologies that provide both high-temporal and high-spatial resolution are required. The proposal represents an emerging domain in the neuroscience of learning, based on a recent development that enables the methodology of functional Magnetic Resonance Imaging (fMRI) to reveal the full range of the neural dynamics of conceptual learning in the human brain. Until now, fMRI has been a tool that could only study long-term neural changes because its response is based on the slow temporal dynamics of the cerebral blood response. As a result, it has been impossible to follow the temporal evolution of the learning process through the complex of local cortical activations in the human brain. An innovative approach will be taken to the analysis of neural dynamics to study the neural information flow in the brain during the learning of both verbal and mathematical reasoning tasks to determine how these two kinds of learning take place. In addition, a much higher spatial resolution of the fMRI technique than is usual in the study of cognitive processing will focus the study on the analysis of local neural populations. Our new technical developments allow us to resolve the neural dynamics of cognitive processing to their native temporal resolution and track the changes in dynamics as the conceptual learning proceeds. This novel approach is of high value in understanding the changes in neural population dynamics underlying the learning process in general, and of the processes of conceptual learning in particular. The current proposal will provide knowledge of the neural dynamics of cognitive processing in the human brain that can have a transformative impact on our understanding of the learning process. In particular, it will radically enhance the ability to build computational models of the neural underpinnings of the learning process, and allow the sequence of information flow in the brain to be mapped as advanced concepts are learned for the first time. This novel capability will promote detailed strategies for enhancing information transfer about effective learning dynamics from the field of cognitive neuroscience to the educational arena.