论文标题
采用点模式分析和图形结构的肠神经系统的生成建模
Generative modeling of the enteric nervous system employing point pattern analysis and graph construction
论文作者
论文摘要
我们描述了结肠中肠神经系统（ENS）结构的生成网络模型，该模型采用了通过共聚焦显微镜获得的人类和小鼠组织样品图像中的数据。我们的模型将空间点模式分析与图生成结合在一起，以表征神经节（神经元和神经胶质细胞的簇），伴有膜间连接以及神经节内神经元组织的空间和拓扑特性。我们采用混合硬核 - 曲折工艺来实现空间模式和平面随机图生成来构建空间嵌入式网络。我们表明，我们的生成模型可能在基础研究和翻译研究中有所帮助，并且足以模拟年龄和健康状况不同的个人的ENS架构。对ENS Connectome的了解越来越多，可以使神经调节策略在治疗中使用，并阐明肠运动障碍患者的解剖学诊断标准。
We describe a generative network model of the architecture of the enteric nervous system (ENS) in the colon employing data from images of human and mouse tissue samples obtained through confocal microscopy. Our models combine spatial point pattern analysis with graph generation to characterize the spatial and topological properties of the ganglia (clusters of neurons and glial cells), the inter-ganglionic connections, and the neuronal organization within the ganglia. We employ a hybrid hardcore-Strauss process for spatial patterns and a planar random graph generation for constructing the spatially embedded network. We show that our generative model may be helpful in both basic and translational studies, and it is sufficiently expressive to model the ENS architecture of individuals who vary in age and health status. Increased understanding of the ENS connectome will enable the use of neuromodulation strategies in treatment and clarify anatomic diagnostic criteria for people with bowel motility disorders.
