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首页> 外文期刊>Clinical EEG and neuroscience: official journal of the EEG and Clinical Neuroscience Society (ENCS) >Graph theoretical analysis of organization of functional brain networks in ADHD
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Graph theoretical analysis of organization of functional brain networks in ADHD

机译：图论分析ADHD中功能性大脑网络的组织

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摘要

This article presents a new methodology for investigation of the organization of the overall and hemispheric brain network of patients with attention-deficit hyperactivity disorder (ADHD) using theoretical analysis of a weighted graph with the goal of discovering how the brain topology is affected in such patients. The synchronization measure used is the nonlinear fuzzy synchronization likelihood (FSL) developed by the authors recently. Recent evidence indicates a normal neocortex has a small-world (SW) network with a balance between local structure and global structure characteristics. Such a network results in optimal balance between segregation and integration which is essential for high synchronizabilty and fast information transmission in a complex network. The SW network is characterized by the coexistence of dense clustering of connections (C) and short path lengths (L) among the network units. The results of investigation of C show the local structure of functional left-hemisphere brain networks of ADHD diverges from that of non-ADHD which is recognizable in the delta electroencephalograph (EEG) sub-band. Also, the results of investigation for L show the global structure of functional left-hemisphere brain networks of ADHD diverges from that of non-ADHD which is observable in the delta EEG sub-band. It is concluded that the changes in left-hemisphere brain's structure of ADHD from that of the non-ADHD are so much that L and C can distinguish the ADHD brain from the non-ADHD brain in the delta EEG sub-band.
机译：本文通过加权图的理论分析，提出了一种新的方法，用于研究注意力缺陷多动障碍（ADHD）患者的整体和半球脑网络的组织结构，目的是发现此类患者的大脑拓扑结构如何受到影响。作者最近使用的同步度量是非线性模糊同步似然（FSL）。最近的证据表明，正常的新皮层具有一个小世界（SW）网络，在局部结构和全局结构特征之间保持平衡。这样的网络导致隔离和集成之间的最佳平衡，这对于复杂网络中的高同步性和快速信息传输至关重要。 SW网络的特征是网络单元之间密集的连接群集（C）和短路径长度（L）共存。 C的研究结果表明，ADHD的功能性左半脑大脑网络的局部结构与非ADHD的局部结构不同，后者在三角洲脑电图（EEG）子带中可以识别。另外，对L的研究结果表明，ADHD的功能性左半脑大脑网络的整体结构与非ADHD的结构不同，后者在δEEG子带中可见。结论是，左脑半球大脑ADHD结构与非ADHD大脑结构的变化是如此之大，以至于L和C可以在ΔEEG子带中将ADHD大脑与非ADHD大脑区分开。

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