Dong Tingting, Huang Qiuping, Huang Shucai, Xin Jiang, Jia Qiaolan, Gao Yang, Shen Hongxian, Tang Yan, Zhang Hao
School of Computer Science and Engineering, Central South University, Changsha, China.
National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.
Front Psychol. 2021 Aug 30;12:717519. doi: 10.3389/fpsyg.2021.717519. eCollection 2021.
Methamphetamine (MA) can cause brain structural and functional impairment, but there are few studies on whether this difference will sustain on MA abstainers. The purpose of this study is to investigate the correlation of brain networks in MA abstainers. In this study, 47 people detoxified for at least 14 months and 44 normal people took a resting-state functional magnetic resonance imaging (RS-fMRI) scan. A dynamic (i.e., time-varying) functional connectivity (FC) is obtained by applying sliding windows in the time courses on the independent components (ICs). The windowed correlation data for each IC were then clustered by k-means. The number of subjects in each cluster was used as a new feature for individual identification. The results show that the classifier achieved satisfactory performance (82.3% accuracy, 77.7% specificity, and 85.7% sensitivity). We find that there are significant differences in the brain networks of MA abstainers and normal people in the time domain, but the spatial differences are not obvious. Most of the altered functional connections (time-varying) are identified to be located at dorsal default mode network. These results have shown that changes in the correlation of the time domain may play an important role in identifying MA abstainers. Therefore, our findings provide valuable insights in the identification of MA and elucidate the pathological mechanism of MA from a resting-state functional integration point of view.
甲基苯丙胺(MA)可导致脑结构和功能损害,但关于这种差异在MA戒除者身上是否会持续存在的研究较少。本研究的目的是调查MA戒除者脑网络的相关性。在本研究中,47名戒毒至少14个月的人和44名正常人接受了静息态功能磁共振成像(RS-fMRI)扫描。通过在独立成分(IC)的时间进程中应用滑动窗口来获得动态(即时变)功能连接(FC)。然后对每个IC的窗口化相关数据进行k均值聚类。每个聚类中的受试者数量被用作个体识别的新特征。结果表明,分类器取得了令人满意的性能(准确率82.3%、特异性77.7%、灵敏度85.7%)。我们发现,MA戒除者和正常人的脑网络在时域存在显著差异,但空间差异不明显。大多数改变的功能连接(时变)被确定位于背侧默认模式网络。这些结果表明,时域相关性的变化可能在识别MA戒除者中起重要作用。因此,我们的研究结果为MA的识别提供了有价值的见解,并从静息态功能整合的角度阐明了MA的病理机制。