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肥胖患者额 - 中边缘网络的拓扑组织紊乱。

Disrupted topological organization of the frontal-mesolimbic network in obese patients.

机构信息

Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, China.

Department of Radiology, Tangdu Hospital, Fourth Military Medical University, Xi'an, Shaanxi, 710038, China.

出版信息

Brain Imaging Behav. 2018 Dec;12(6):1544-1555. doi: 10.1007/s11682-017-9802-z.

Abstract

Neuroimaging studies have revealed brain functional abnormalities in frontal-mesolimbic regions in obesity. However, the effects of obesity on brain network topology remains largely unknown. In the current study, we employed resting-state functional magnetic resonance imaging and graph theory methods to investigate obesity-related changes in brain network topology in 26 obese patients and 28 normal weight subjects. Results revealed that the whole-brain networks of the two groups exhibited typical features of small-world topology. Obese patients showed significantly increased shortest path length (Lp) and decreased global efficiency (Eglob). Moreover, decreased nodal-degree/efficiency was found in frontal (medial orbitofrontal cortex-mOFC, rostral anterior cingulate cortex-rACC), striatal (caudate/nucleus accumbens) and limbic regions (insula, amygdala, hippocampus/parahippocampal gyrus) and thalamus in obese patients. Network-based statistics showed that a sub-network, composed of 31 nodes and 30 edges, was significantly disrupted in obese patients; 29 out of 30 connections were associated with the right rACC. In the obese group, Lp and Eglob were negatively correlated with body mass index (BMI, P < 0.005), and BMI was negatively correlated with nodal-degree/efficiency of the mOFC (P < 0.001). Findings suggest disruption of the small-world organization and a global reduction of integration of functional brain networks involving the right rACC in obesity and implicating the mOFC in mediating severity.

摘要

神经影像学研究揭示了肥胖症患者额-中边缘区域的大脑功能异常。然而,肥胖对大脑网络拓扑结构的影响在很大程度上仍然未知。在当前的研究中,我们采用静息态功能磁共振成像和图论方法,研究了 26 名肥胖患者和 28 名正常体重受试者中与肥胖相关的大脑网络拓扑结构变化。结果表明,两组的全脑网络均表现出典型的小世界拓扑特征。肥胖患者的最短路径长度(Lp)显著增加,全局效率(Eglob)降低。此外,肥胖患者的额(内侧眶额皮层-mOFC、额前扣带皮层-rACC)、纹状体(尾状核/伏隔核)和边缘区域(岛叶、杏仁核、海马/海马旁回)以及丘脑的节点度/效率降低。基于网络的统计分析显示,肥胖患者的一个由 31 个节点和 30 条边组成的子网络明显被破坏;30 个连接中的 29 个与右侧 rACC 有关。在肥胖组中,Lp 和 Eglob 与体重指数(BMI)呈负相关(P<0.005),BMI 与 mOFC 的节点度/效率呈负相关(P<0.001)。研究结果表明,肥胖会破坏大脑网络的小世界组织,降低大脑网络的整体整合,涉及右侧 rACC,而 mOFC 可能在调节严重程度方面发挥作用。

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