纹状体的计算微电路。
The microcircuits of striatum in silico.
机构信息
Science for Life Laboratory, School of Electrical Engeneering and Computer Science, Royal Institute of Technology, SE-10044 Stockholm, Sweden.
Department of Neuroscience, Karolinska Institutet, SE-17165 Stockholm.
出版信息
Proc Natl Acad Sci U S A. 2020 Apr 28;117(17):9554-9565. doi: 10.1073/pnas.2000671117. Epub 2020 Apr 22.
The basal ganglia play an important role in decision making and selection of action primarily based on input from cortex, thalamus, and the dopamine system. Their main input structure, striatum, is central to this process. It consists of two types of projection neurons, together representing 95% of the neurons, and 5% of interneurons, among which are the cholinergic, fast-spiking, and low threshold-spiking subtypes. The membrane properties, soma-dendritic shape, and intrastriatal and extrastriatal synaptic interactions of these neurons are quite well described in the mouse, and therefore they can be simulated in sufficient detail to capture their intrinsic properties, as well as the connectivity. We focus on simulation at the striatal cellular/microcircuit level, in which the molecular/subcellular and systems levels meet. We present a nearly full-scale model of the mouse striatum using available data on synaptic connectivity, cellular morphology, and electrophysiological properties to create a microcircuit mimicking the real network. A striatal volume is populated with reconstructed neuronal morphologies with appropriate cell densities, and then we connect neurons together based on appositions between neurites as possible synapses and constrain them further with available connectivity data. Moreover, we simulate a subset of the striatum involving 10,000 neurons, with input from cortex, thalamus, and the dopamine system, as a proof of principle. Simulation at this biological scale should serve as an invaluable tool to understand the mode of operation of this complex structure. This platform will be updated with new data and expanded to simulate the entire striatum.
基底神经节在决策和动作选择中起着重要作用,主要基于皮质、丘脑和多巴胺系统的输入。它们的主要输入结构纹状体是这个过程的核心。它由两种类型的投射神经元组成,共同代表 95%的神经元和 5%的中间神经元,其中包括胆碱能、快速放电和低阈值放电亚型。这些神经元的膜特性、体树突形状以及纹状体内外的突触相互作用在小鼠中已经得到了很好的描述,因此可以进行足够详细的模拟,以捕捉它们的内在特性以及连接性。我们专注于纹状体细胞/微电路水平的模拟,其中分子/亚细胞和系统水平相遇。我们使用可用的突触连接、细胞形态和电生理特性数据来构建一个模仿真实网络的微电路,从而对小鼠纹状体进行了几乎全规模的建模。在一个纹状体体积中填充了具有适当细胞密度的重建神经元形态,然后根据神经突之间可能的突触连接来将神经元连接在一起,并进一步使用可用的连接数据对其进行约束。此外,我们模拟了包含 10000 个神经元的纹状体子集,其输入来自皮质、丘脑和多巴胺系统,作为一个原理证明。在这种生物尺度上的模拟应该成为理解这个复杂结构运作模式的宝贵工具。这个平台将使用新的数据进行更新,并扩展到模拟整个纹状体。