Resting-state connectivity and network parameter analysis in alcohol-dependent males. A simultaneous EEG-MEG study.,Journal of Neuroscience Research

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Resting-state connectivity and network parameter analysis in alcohol-dependent males. A simultaneous EEG-MEG study.
Journal of Neuroscience Research ( IF 2.9 ) Pub Date : 2020-06-25 , DOI: 10.1002/jnr.24673
Ana Sion ₁ , Ricardo Bruña Fernández _{2,

3,

4} , Andrés Martínez Maldonado ₁ , Isabel Domínguez Centeno _{1,

5} , Angel Torrado-Carvajal _{6,

7} , Gabriel Rubio _{1,

8,

9,

10} , Ernesto Pereda _{2,

11} , Rosa Jurado-Barba _{1,

5}

Affiliation

12 de Octubre Biomedical Research Institute, Madrid, Spain.
Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology (CTB), Madrid, Spain.
Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Spain.
Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain.
Psychology Department, Health Science Faculty, Camilo José Cela University, Madrid, Spain.
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Medical Image Analysis and Biometry Laboratory, Universidad Rey Juan Carlos, Madrid, Spain.
12 de Octubre Hospital, Madrid, Spain.
Medicine Faculty, Complutense de Madrid University, Madrid, Spain.
Addictive Disorders Network (Red de Trastornos adictivos, RETIS), Carlos III Institute, Madrid, Spain.
Department of Industrial Engineering & IUNE, Universidad de la Laguna, San Cristóbal de La Laguna, Spain.

There is supporting evidence of alcohol negative effects on the brain: neuroimaging and psychophysiological studies finding anatomical and functional connectivity (FC) changes associated with the dependence process. Thus, the aim of this work was to evaluate brain FC and network characteristics of alcohol‐dependent individuals in resting state. For this study, we included males diagnosed with alcohol dependence (N = 25) and a group of healthy individuals (N = 23). Simultaneous EEG‐MEG (electroencephalographic and magnetoencephalographic) activity was recorded in 5 min of eyes‐closed resting state. EEG‐MEG activity was preprocessed and FC was computed through the leakage‐corrected version of phase locking value (ciPLV). Additionally, local (degree, efficiency, clustering) and global (efficiency, characteristic path length) network parameters were computed. Connectivity analysis showed an increase in phase‐lagged synchronization, mainly between frontal and frontotemporal regions, in high beta band, and a decrease in interhemispheric gamma, for alcohol‐dependent individuals. Network analysis revealed intergroup differences at the local level for high beta, indicating higher degree, clustering, and efficiency, mostly at frontal nodes, together with a decrease in these measures at more posterior sites for patients’ group. The hyper‐synchronization in beta, next to the hypo‐synchronization in gamma, could indicate an alteration in communication between hemispheres, but also a possible functional compensation mechanism in neural circuits. This could be also supported by network characteristic data, where local alterations in communication are observed.

中文翻译：

酒精依赖男性的静息状态连接和网络参数分析。同步 EEG-MEG 研究。

有证据表明酒精对大脑有负面影响：神经影像学和心理生理学研究发现与依赖过程相关的解剖和功能连接 (FC) 变化。因此，这项工作的目的是评估静息状态下酒精依赖者的大脑 FC 和网络特征。在这项研究中，我们纳入了被诊断为酒精依赖的男性 ( N = 25) 和一组健康个体 ( N = 23）。在闭眼静息状态下 5 分钟记录同时的 EEG-MEG（脑电图和脑磁图）活动。预处理 EEG-MEG 活动，并通过锁相值 (ciPLV) 的泄漏校正版本计算 FC。此外，还计算了局部（度、效率、聚类）和全局（效率、特征路径长度）网络参数。连通性分析显示，对于酒精依赖者，相位滞后同步增加，主要在额叶和额颞叶区域之间，在高 β 波段，以及半球间伽玛值减少。网络分析揭示了高贝塔在局部水平的组间差异，表明更高的程度、聚类和效率，主要是在额叶节点，以及患者组在更多后部部位的这些措施的减少。β 中的超同步与 gamma 中的低同步相邻，可能表明半球之间的交流发生了改变，但也可能表明神经回路中的功能补偿机制。这也可以得到网络特征数据的支持，其中观察到通信的局部变化。

更新日期：2020-06-25

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