Graph theoretical analysis of complex networks in the brain.
Graph theoretical analysis of complex networks in the brain.
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DOI：
10.1186/1753-4631-1-3
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发表时间：
2007-07-05
期刊：
影响因子：
--
通讯作者：
Reijneveld, Jaap C
中科院分区：
文献类型：
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作者：
Stam, Cornelis J;Reijneveld, Jaap C
自从发现小世界和无标度网络以来，从网络角度研究复杂系统已经取得了巨大的进展。近年来，复杂网络的许多重要属性已经被描述出来。特别是，在理解网络的结构特性和这些网络上发生的动力学性质之间的关系方面已经取得了重大进展。例如，耦合振荡器的复杂网络的“同步性”可以通过图形频谱分析来确定。复杂网络理论的这些发展激发了神经科学领域的新应用。图分析已用于基于功能磁共振成像、脑电图和脑磁图的神经网络模型、解剖连接和功能连接的研究。这些研究表明，人脑可以被建模为一个复杂的网络，并且在解剖学和功能连接水平上可能具有小世界结构。假设这种小世界结构反映了与快速同步和信息传输、最小布线成本以及本地处理和全局集成之间的平衡相关的最佳情况。功能网络的拓扑结构可能受到遗传和解剖因素的限制，但可以在任务过程中进行修改。越来越多的证据表明，阿尔茨海默病、精神分裂症、脑肿瘤和癫痫等各种类型的脑部疾病可能与功能网络拓扑偏离最佳小世界模式有关。
Since the discovery of small-world and scale-free networks the study of complex systems from a network perspective has taken an enormous flight. In recent years many important properties of complex networks have been delineated. In particular, significant progress has been made in understanding the relationship between the structural properties of networks and the nature of dynamics taking place on these networks. For instance, the 'synchronizability' of complex networks of coupled oscillators can be determined by graph spectral analysis. These developments in the theory of complex networks have inspired new applications in the field of neuroscience. Graph analysis has been used in the study of models of neural networks, anatomical connectivity, and functional connectivity based upon fMRI, EEG and MEG. These studies suggest that the human brain can be modelled as a complex network, and may have a small-world structure both at the level of anatomical as well as functional connectivity. This small-world structure is hypothesized to reflect an optimal situation associated with rapid synchronization and information transfer, minimal wiring costs, as well as a balance between local processing and global integration. The topological structure of functional networks is probably restrained by genetic and anatomical factors, but can be modified during tasks. There is also increasing evidence that various types of brain disease such as Alzheimer's disease, schizophrenia, brain tumours and epilepsy may be associated with deviations of the functional network topology from the optimal small-world pattern.