论文标题
人脑的功能连接与完全相关
Functional Connectome of the Human Brain with Total Correlation
论文作者
论文摘要
最近的研究提出，使用总相关用来描述大脑区域之间的功能连通性作为传统成对措施（例如相关或互信息）的多元替代方案。在这项工作中，我们以这个想法为基础，基于总相关性推断一个大规模（整个大脑）连接网络，并表明将这种网络用作大脑改变的生物标志物的可能性。特别是，这项工作使用相关解释（Corex）来估计总相关性。首先，我们证明，与地面真实价值相比，Corex的总相关和聚类结果的估计值是可信的。其次，从更广泛的FMRI数据集中提取的推断的大规模连接网络与现有的神经科学研究一致，但有趣的是，可以估计超出配对区域的其他关系。最后，我们展示了基于总相关性的连接图如何也是有效的工具，可以帮助发现脑部疾病。
Recent studies proposed the use of Total Correlation to describe functional connectivity among brain regions as a multivariate alternative to conventional pair-wise measures such as correlation or mutual information. In this work we build on this idea to infer a large scale (whole brain) connectivity network based on Total Correlation and show the possibility of using this kind of networks as biomarkers of brain alterations. In particular, this work uses Correlation Explanation (CorEx) to estimate Total Correlation. First, we prove that CorEx estimates of total correlation and clustering results are trustable compared to ground truth values. Second, the inferred large scale connectivity network extracted from the more extensive open fMRI datasets is consistent with existing neuroscience studies but, interestingly, can estimate additional relations beyond pair-wise regions. And finally, we show how the connectivity graphs based on Total Correlation can also be an effective tool to aid in the discovery of brain diseases.
