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From Sensorimotor Sequence to Grammatical Construction: Evidence from Simulation and Neurophysiology

机译：从感觉运动序列到语法结构：来自模拟和神经生理学的证据

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摘要

The current research describes a functional trajectory from sensorimotor sequence learning to the learning of grammatical constructions in language. A brief review of the functional neurophysiology of the cortex and basal ganglia will be provided as background for a neural network model of this system in sensorimotor sequence learning. Sequential behavior is then defined in terms of serial, temporal and abstract structure. The resulting neuro-computational framework is demonstrated to account for observed sequence learning behavior. More interestingly, this framework naturally extends to grammatical constructions as form-to-meaning mappings. Predictions from the neuro-computational model concerning parallels in language and cognitive sequence processing are tested against behavioral and neurophysiological observations in humans, resulting in a refinement of the allocation of model functions to subdivisions of Broca's area. From a functional perspective this analysis will provide insight into the relation between the coding structure in human languages, and constraints derived from the underlying neurophysiological computational mechanisms.
机译：当前的研究描述了从感觉运动序列学习到语言语法结构学习的功能轨迹。皮层和基底神经节的功能神经生理学的简要回顾将作为该系统在感觉运动序列学习中的神经网络模型的背景知识。然后根据序列，时间和抽象结构定义顺序行为。结果表明，所得的神经计算框架可解决观察到的序列学习行为。更有趣的是，这个框架自然地扩展到语法构造，即形式到意义的映射。对照人类的行为和神经生理学观察结果，测试了来自神经计算模型的有关语言和认知序列处理中相似之处的预测，从而完善了对Broca区域细分的模型功能分配。从功能的角度来看，此分析将提供有关人类语言的编码结构与从潜在的神经生理学计算机制得出的约束之间的关系的见解。

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