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基于基底神经节机理的行为决策模型 被引量:3

BEHAVIOR DECISION-MAKING MODEL BASED ON BASAL GANGLIA MECHANISM
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摘要 基底神经节是大脑深部一系列神经功能核团的总称,主要与周围的大脑皮层、丘脑、小脑和脑干相连.基底神经节的主要功能是参与运动调节和随意运动控制,特别是行为的决策确定和动作选择.本文主要介绍基于基底神经节机理的行为决策确定模型,重点综述决策确定和动作选择的理论模型进展.首先介绍了基底神经节的解剖结构,即输入核、输出核、多巴胺系统和中继核,进而描述了基底神经节的功能连接(直接通路、间接通路和超直接通路),然后基于基底神经节的多个皮质-BG回路之间的相互作用,概述了决策模型在运动和行为选择等方面的理论模型,主要有Gurney的选择-控制模型、Humphries的神经元群模型、Frank的认知决策模型、Wang的选择决策模型和Rabinovich相空间动力学选择模型等.最后讨论了这些理论决策模型和大脑疾病(帕金森病)的相互关系等. Basal ganglia are a series of neurological nuclei in deep brain,which are mainly connected with the sur⁃rounding cerebral cortex,thalamus,cerebellum and brainstem.The main function of basal ganglia is to participate in motor regulation and random motion control,especially in decision-making and action selection of behavior.This paper mainly introduced the behavioral decision-making model based on the mechanism of basal ganglia,and focused on the progress of theoretical models of decision-making and action selection.Firstly,the anatomical structure of basal ganglia,composed of input nucleus,output nucleus,dopamine system and relay nucleus,were introduced,and then the func⁃tional connections of basal ganglia(direct pathway,indirect pathway and hyper-direct pathway)were described.Second⁃ly,the theoretical progress of decision models in motion and action selection based on the interaction between multiple cortical-BG circuits in the basal ganglia was summarized,including Gurney’s select-control model,Humphries’neuron population model,Frank’s cognitive decision model,Wang’s choice decision model and Rabinovich's phase space dy⁃namics decision model.Finally,the relationship between these theoretical decision models and brain diseases(e.g.Par⁃kinson's disease)was discussed.
作者 宋健 刘深泉 臧杰 Song Jian;Liu Shenquan;Zang Jie(School of Mathematics,South China University of Technology,Guang zhou 510640,China)
出处 《动力学与控制学报》 2020年第6期1-31,共31页 Journal of Dynamics and Control
基金 国家自然科学基金资助项目(11572127,11872183)。
关键词 基底神经节 神经回路 决策确定 行为选择 动力学模型 帕金森病 basal ganglia nerve circuit decision-making action selection dynamic models Parkinson’s diseas
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