发现人类连接组中的性别和年龄暗示边缘
Discovering Sex and Age Implicator Edges in the Human Connectome
摘要：
确定大型图中的重要顶点（例如，Google的PageRank（在万维网图表的情况下）促进了优秀网络搜索引擎的构建，返回与提交的用户查询相对应的最重要的点击。有趣的是，直到现在，在大型图中寻找重要的边而不是顶点受到的关注要少得多。在这里，我们研究了人类的结构脑组织（或连接体），通过扩散磁共振成像（dMRI）方法，与边缘连接皮质和皮质下灰质区和加权的纤维强度，沿边缘发现的纤维束的数量来衡量。我们在这些脑图中确定了几个“单一”重要的边缘，其高或低的权重暗示了观察对象的性别或年龄。我们称这些边缘为暗示边缘，因为仅从它们的重量，人们可以以超过67%的准确度推断出受试者的性别，或者以超过62%的准确度推断出受试者的年龄组。我们认为，这些大脑连接是最重要的特征的性别或年龄的主题。令人惊讶的是，暗示男性性别的边缘大多位于大脑的前部，而暗示女性性别的边缘大多位于后部。此外，大多数的半球间暗示边缘是男性的，而半球内的主要是女性的边缘。我们发现性别或年龄暗示边缘的开创性方法也可以应用于表征其他生物和医学特性，包括神经退行性疾病和精神疾病，除了性别或年龄的主题，如果大型和高质量的神经成像数据集变得可用。
英文摘要：
Determining important vertices in large graphs (e.g., Google's PageRank in the case of the graph of the World Wide Web) facilitated the construction of excellent web search engines, returning the most important hits corresponding to the submitted user queries. Interestingly, finding important edges -- instead of vertices -- in large graphs has received much less attention until now. Here we examine the human structural braingraph (or connectome), identified by diffusion magnetic resonance imaging (dMRI) methods, with edges connecting cortical and subcortical gray matter areas and weighted by fiber strengths, measured by the number of the discovered fiber tracts along the edge. We identify several "single" important edges in these braingraphs, whose high or low weights imply the sex or the age of the subject observed. We call these edges implicator edges since solely from their weight, one can infer the sex of the subject with more than 67 \% accuracy or their age group with more than 62\% accuracy. We argue that these brain connections are the most important ones characterizing the sex or the age of the subjects. Surprisingly, the edges implying the male sex are mostly located in the anterior parts of the brain, while those implying the female sex are mostly in the posterior regions. Additionally, most of the inter-hemispheric implicator edges are male ones, while the intra-hemispheric ones are predominantly female edges. Our pioneering method for finding the sex- or age implicator edges can also be applied for characterizing other biological and medical properties, including neurodegenerative- and psychiatric diseases besides the sex or the age of the subject, if large and high-quality neuroimaging datasets become available.
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