论文标题
可视化功能网络连接的分辨率矩阵
The Resolution Matrix for Visualizing Functional Network Connectivity
论文作者
论文摘要
分辨率矩阵是用于分析逆问题（例如计算成像系统）的数学工具。当将网络连接估计视为逆问题时，分辨率矩阵描述了可以解决网络节点和边缘的程度。这对于量化网络估计的鲁棒性以及确定相关活性很有用。在本报告中，我们分析了人类Connectome项目功能性MRI数据的分辨率矩阵。我们发现，分辨率度量标准的通用指标可用于识别网络活动，尽管默认模式网络和额叶注意力网络之间的关系有了新的扭曲。
The resolution matrix is a mathematical tool for analyzing inverse problems such as computational imaging systems. When treating network connectivity estimation as an inverse problem, the resolution matrix describes the degree to which network nodes and edges can be resolved. This is useful both for quantifying robustness of the network estimate, as well as identifying correlated activity. In this report we analyze the resolution matrix for functional MRI data from the Human Connectome project. We find that common metrics of the resolution metric can be used to identify networked activity, though with a new twist on the relationship between default mode network and the frontoparietal attention network.
