首页> 外文期刊>Clinical EEG and neuroscience: official journal of the EEG and Clinical Neuroscience Society (ENCS) >Quantitative and Qualitative Comparison of EEG-Based Neural Network Organization in Two Schizophrenia Groups Differing in the Duration of Illness and Disease Burden: Graph Analysis With Application of the Minimum Spanning Tree
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Quantitative and Qualitative Comparison of EEG-Based Neural Network Organization in Two Schizophrenia Groups Differing in the Duration of Illness and Disease Burden: Graph Analysis With Application of the Minimum Spanning Tree

机译:疾病和疾病负担持续时间中脑卒中基于精神分裂症群中脑卒中的神经网络组织的定量和定性比较:图分析了最小生成树的应用

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The aim of this study was to compare neural network topology of 30 patients with first episode schizophrenia (FES) and 30 multiepisode schizophrenia (mean number of psychotic relapses =4 years, duration of illness >5 years) patients, who were assessed with graph theory methods. This comparison was designed to identify network differences, which might be assigned to the burden of a mental disease. To estimate functional connectivity, we applied the phase lag index algorithm and the minimum spanning tree (MST) for the characterization of network topology. Group comparison revealed significant between-group differences of maximal betweenness centrality and tree hierarchy in the beta-band and hierarchy in the gamma-band. MST results showed that in the beta-band the network of patients with longer duration of illness (LDI) was characterized by more centralized network, while subjects with short duration of illness (FES) showed more decentralized topology. Furthermore, in the gamma-band, our results suggest that illness duration can disturb the balance between overload prevention and large-scale integration in the brain network. A qualitative analysis proved that the topological displacement of hubs also differentiated the FES and LDI groups. Our findings suggest that the duration of illness significantly affects the topology of resting-state functional network, supporting the "disconnectivity hypothesis' in schizophrenia.
机译:本研究的目的是将30名患者的神经网络拓扑(FES)和30个多功能性精神分裂症(平均精神病次数= 4年,疾病持续时间)进行比较,以图表理论评估的患者方法。这种比较旨在识别网络差异,这可能会被分配到精神疾病的负担。为了估计功能连接,我们应用了网络拓扑表征的阶段滞后指数算法和最小生成树(MST)。群体比较揭示了在伽马带中的β波段中的最大中心和树层次之间的最大程度和树立等级之间的差异显着。 MST结果表明,在β频段中,患者患者持续时间较长的患者(LDI)的特征是由更集中的网络的特征,而疾病持续时间(FES)的受试者表现出更分散的拓扑结构。此外,在伽玛乐队中,我们的结果表明疾病持续时间可以干扰大脑网络中的过载预防和大规模集成之间的平衡。定性分析证明了集线器的拓扑位移也区分了FES和LDI组。我们的研究结果表明,疾病的持续时间显着影响了休息状态功能网络的拓扑,支持精神分裂症中的“脱离角假设”。

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