Song Jian, Lin Hui, Liu Shenquan
School of Mathematics, South China University of Technology, Guangzhou, China.
Department of Precision Instruments, Tsinghua University, Beijing, China.
Network. 2023 Feb-Feb;34(1-2):84-121. doi: 10.1080/0954898X.2023.2173816. Epub 2023 Mar 1.
Basal ganglia (BG) are a widely recognized neural basis for action selection, but its decision-making mechanism is still a difficult problem for researchers. Therefore, we constructed a spiking neural network inspired by the BG anatomical data. Simulation experiments were based on the principle of dis-inhibition and our functional hypothesis within the BG: the direct pathway, the indirect pathway, and the hyper-direct pathway of the BG jointly implement the initiation execution and termination of motor programs. Firstly, we studied the dynamic process of action selection with the network, which contained intra-group competition and inter-group competition. Secondly, we focused on the effects of the stimulus intensity and the proportion of excitation and inhibition on the GPi/SNr. The results suggested that inhibition and excitation shape action selection. They also explained why the firing rate of GPi/SNr did not continue to increase in the action-selection experiment. Finally, we discussed the experimental results with the functional hypothesis. Uniquely, this paper summarized the decision-making neural mechanism of action selection based on the direct pathway, the indirect pathway, and the hyper-direct pathway within BG.
基底神经节(BG)是广泛认可的动作选择神经基础,但其决策机制仍是研究人员面临的难题。因此,我们构建了一个受BG解剖数据启发的脉冲神经网络。模拟实验基于去抑制原理以及我们在BG内的功能假设:BG的直接通路、间接通路和超直接通路共同实现运动程序的启动、执行和终止。首先,我们用该网络研究了动作选择的动态过程,其中包括组内竞争和组间竞争。其次,我们关注刺激强度以及兴奋与抑制比例对苍白球内侧部/黑质网状部(GPi/SNr)的影响。结果表明,抑制和兴奋塑造动作选择。它们还解释了在动作选择实验中GPi/SNr的放电率为何没有持续增加。最后,我们根据功能假设讨论了实验结果。独特的是,本文总结了基于BG内直接通路、间接通路和超直接通路的动作选择决策神经机制。