Cerebral (“brain”) organoids are high-fidelity in vitro cellular models of the developing brain, which makes them one of the go-to methods to study isolated processes of tissue organization and its electrophysiological properties, allowing to collect invaluable data for in silico modeling neurodevelopmental processes. Complex computer models of biological systems supplement in vivo and in vitro experimentation and allow researchers to look at things that no laboratory study has access to, due to either technological or ethical limitations. In this paper, we present the Biological Cellular Neural Network Modeling (BCNNM) framework designed for building dynamic spatial models of neural tissue organization and basic stimulus dynamics. The BCNNM uses a convenient predicate description of sequences of biochemical reactions and can be used to run complex models of multi-layer neural network formation from a single initial stem cell. It involves processes such as proliferation of precursor cells and their differentiation into mature cell types, cell migration, axon and dendritic tree formation, axon pathfinding and synaptogenesis. The experiment described in this article demonstrates a creation of an in silico cerebral organoid-like structure, constituted of up to 1 million cells, which differentiate and self-organize into an interconnected system with four layers, where the spatial arrangement of layers and cells are consistent with the values of analogous parameters obtained from research on living tissues. Our in silico organoid contains axons and millions of synapses within and between the layers, and it comprises neurons with high density of connections (more than 10). In sum, the BCNNM is an easy-to-use and powerful framework for simulations of neural tissue development that provides a convenient way to design a variety of tractable in silico experiments.

中文翻译：

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BCNNM：计算机神经组织发育建模框架

大脑（“大脑”）类器官是发育中大脑的高保真体外细胞模型，这使它们成为研究组织组织的孤立过程及其电生理特性的首选方法之一，从而可以为计算机收集宝贵的数据模拟神经发育过程。生物系统的复杂计算机模型补充了体内和体外实验，并允许研究人员查看由于技术或道德限制而无法进行实验室研究的事物。在本文中，我们提出了生物细胞神经网络建模 (BCNNM) 框架，该框架旨在构建神经组织组织和基本刺激动力学的动态空间模型。BCNNM 使用对生化反应序列的便捷谓词描述，可用于从单个初始干细胞运行多层神经网络形成的复杂模型。它涉及诸如前体细胞增殖及其分化为成熟细胞类型、细胞迁移、轴突和树突树形成、轴突寻路和突触发生等过程。本文中描述的实验展示了一种由多达 100 万个细胞组成的模拟大脑类器官结构的创建，这些细胞分化并自组织成一个具有四层的互连系统，其中层和细胞的空间排列是与从活组织研究中获得的类似参数值一致。我们的 in silico 类器官在层内和层之间包含轴突和数百万个突触，它包含具有高密度连接（超过 10 个）的神经元。总之，BCNNM 是一个易于使用且功能强大的神经组织发育模拟框架，它提供了一种方便的方法来设计各种易处理的计算机实验。