论文标题
神经元图：钙成像记录的微观，功能网络的图理论引物
Neuronal graphs: a graph theory primer for microscopic, functional networks of neurons recorded by Calcium imaging
论文作者
论文摘要
连接的网络是神经生物学的基本结构。了解这些网络将有助于我们阐明计算的神经机制。从数学上讲，这些网络是“图” - 包含连接对象的结构。在神经科学中，对象可能是大脑的区域，例如fMRI数据或单个神经元，例如用荧光显微镜进行钙成像。图形理论的形式研究可以为神经科学家提供大量用于探索网络的算法。图理论已经以多种方式应用于fMRI数据，但最近已开始在神经元的尺度上应用，例如来自功能性钙成像。在此引物中，我们解释了图理论的基础知识，并将其与钙成像神经元图神经元的微观功能网络相关联。我们探讨了应用于钙成像的最新示例，并强调了一些领域的研究人员可能会出现问题的领域。
Connected networks are a fundamental structure of neurobiology. Understanding these networks will help us elucidate the neural mechanisms of computation. Mathematically speaking these networks are `graphs' - structures containing objects that are connected. In neuroscience, the objects could be regions of the brain, e.g. fMRI data, or be individual neurons, e.g. calcium imaging with fluorescence microscopy. The formal study of graphs, graph theory, can provide neuroscientists with a large bank of algorithms for exploring networks. Graph theory has already been applied in a variety of ways to fMRI data but, more recently, has begun to be applied at the scales of neurons, e.g. from functional calcium imaging. In this primer we explain the basics of graph theory and relate them to features of microscopic functional networks of neurons from calcium imaging - neuronal graphs. We explore recent examples of graph theory applied to calcium imaging and we highlight some areas where researchers new to the field could go awry.
