Disrupted resting-state brain network properties in obesity: decreased global and putaminal cortico-striatal network efficiency.
Disrupted resting-state brain network properties in obesity: decreased global and putaminal cortico-striatal network efficiency.
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DOI：
10.1017/s0033291716002646
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发表时间：
2017-03
影响因子：
6.9
通讯作者：
Voon V
中科院分区：
文献类型：
--
作者：
Baek K;Morris LS;Kundu P;Voon V
大脑网络的有效组织和通信是认知过程的基础，它们的中断可能导致病态行为。很少有研究关注肥胖和暴食症（BED）的全脑网络。在这里，我们使用多回波静息态功能磁共振成像（rsfMRI）沿着与数据驱动的图论方法来评估肥胖和BED的大脑网络特征。从40名肥胖受试者（包括20名BED患者）和40名健康对照者中收集多回波rsfMRI扫描，并使用多回波独立成分分析（ME-ICA）进行去噪。我们构建了一个全脑功能连接矩阵，其中区域平均血氧水平依赖（BOLD）信号之间的归一化相关系数来自自动解剖标记图谱中的90个脑区域。我们计算了二值化连接矩阵的全局和区域网络属性，边缘密度为5%-25%。我们还使用一个单独的包裹来验证我们的发现，哈佛-牛津地图集被包裹成470个区域。与健康对照组相比，肥胖受试者表现出显著降低的全球和局部网络效率以及降低的模块性，表明小世界和模块化网络结构的破坏。在区域指标中，肥胖受试者的壳核、苍白球和丘脑的结节程度和效率显着降低。肥胖受试者还表现出与壳核和皮质运动区相关的皮质-纹状体/皮质-丘脑网络的连接性降低。这些发现与ME-ICA具有显著性，与常规去噪或单回波分析观察到的有限组间差异。使用多回波rsfMRI数据的数据驱动分析，我们发现肥胖症的全球网络特性和运动皮质-纹状体网络的破坏与习惯形成理论一致。我们的研究结果强调了网络特性在病理性食物滥用中的作用，作为可能的生物标志物和治疗靶点。
The efficient organization and communication of brain networks underlie cognitive processing and their disruption can lead to pathological behaviours. Few studies have focused on whole-brain networks in obesity and binge eating disorder (BED). Here we used multi-echo resting-state functional magnetic resonance imaging (rsfMRI) along with a data-driven graph theory approach to assess brain network characteristics in obesity and BED. Multi-echo rsfMRI scans were collected from 40 obese subjects (including 20 BED patients) and 40 healthy controls and denoised using multi-echo independent component analysis (ME-ICA). We constructed a whole-brain functional connectivity matrix with normalized correlation coefficients between regional mean blood oxygenation level-dependent (BOLD) signals from 90 brain regions in the Automated Anatomical Labeling atlas. We computed global and regional network properties in the binarized connectivity matrices with an edge density of 5%–25%. We also verified our findings using a separate parcellation, the Harvard–Oxford atlas parcellated into 470 regions. Obese subjects exhibited significantly reduced global and local network efficiency as well as decreased modularity compared with healthy controls, showing disruption in small-world and modular network structures. In regional metrics, the putamen, pallidum and thalamus exhibited significantly decreased nodal degree and efficiency in obese subjects. Obese subjects also showed decreased connectivity of cortico-striatal/cortico-thalamic networks associated with putaminal and cortical motor regions. These findings were significant with ME-ICA with limited group differences observed with conventional denoising or single-echo analysis. Using this data-driven analysis of multi-echo rsfMRI data, we found disruption in global network properties and motor cortico-striatal networks in obesity consistent with habit formation theories. Our findings highlight the role of network properties in pathological food misuse as possible biomarkers and therapeutic targets.