Centro Atómico Bariloche, Instituto Balseiro, CONICET, Bariloche, 8400 Río Negro, Argentina.
Philos Trans A Math Phys Eng Sci. 2010 Dec 28;368(1933):5633-44. doi: 10.1098/rsta.2010.0279.
In this work, we focus on a complex-network approach for the study of the brain. In particular, we consider functional brain networks, where the vertices represent different anatomical regions and the links their functional connectivity. First, we build these networks using data obtained with functional magnetic resonance imaging. Then, we analyse the main characteristics of these complex networks, including degree distribution, the presence of modules and hierarchical structure. Finally, we present a network model with dynamical nodes and adaptive links. We show that the model allows for the emergence of complex networks with characteristics similar to those observed in functional brain networks.
在这项工作中，我们专注于大脑的复杂网络研究方法。具体来说，我们考虑功能脑网络，其中顶点代表不同的解剖区域，而边代表它们的功能连接。首先，我们使用功能磁共振成像获得的数据构建这些网络。然后，我们分析这些复杂网络的主要特征，包括度分布、模块的存在和层次结构。最后，我们提出了一个具有动态节点和自适应边的网络模型。我们表明，该模型允许出现具有与功能脑网络相似特征的复杂网络。
