College of Information Engineering, Nanjing University of Finance and Economics, Nanjing, 210023, China.
School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China.
Cortex. 2019 Nov;120:36-48. doi: 10.1016/j.cortex.2019.04.026. Epub 2019 May 18.
Functional connectivity pattern altered of default mode network (DMN) is gaining more attention as a potential noninvasive biomarker to diagnose incipient Alzheimer's disease. However, the changed functional connectivity except for DMN, the longitudinal changes in executive control network (ECN) and frontoparietal network (FPN) also has attracted wide interest. Moreover, AD-related functional connectivity abnormalities within the DMN are well replicated research, but the (increased/decreased and reduced) functional connectivity in ECN and FPN weren't receive adequate attention. To address the above issues, in this paper, we adopt sparse inverse covariance estimation (SICE) approach to investigate the changed functional connectivity of ECN and FPN on the ADNI2 dataset. Our experimental results indicate the left superior frontal gyrus (SFGmed.L) and left thalamus (THA.L) regions of ECN has shown increased functional connectivity, the left anterior cingulate (ACG.L) region of ECN has shown decreased functional connectivity. The Superior Parietal Gyrus (SPG) regions and left paracentral lobule (PCL.L) of FPN has shown increased functional connectivity, the left supramarginal gyrus (SMG.L) regions has shown decreased functional connectivity in AD patients. On the other hand, the ACG.L regions in ECN, SMG.L and left inferior parietal (IPL.L) in FPN have shown significantly reduced functional connectivity. These results demonstrate that increased/decreased functional connectivity and reduced functional connectivity not only within DMN, but also associated with ECN and FPN. It also suggest that AD is associated with the characteristics of large-scale functional networks, and these changed functional connectivity possibly as a potential noninvasive biomarker to diagnose incipient Alzheimer's disease.
默认模式网络（DMN）的功能连接模式改变作为诊断早期阿尔茨海默病的潜在非侵入性生物标志物正受到越来越多的关注。然而，除了 DMN 之外，执行控制网络（ECN）和额顶网络（FPN）的功能连接的纵向变化也引起了广泛的关注。此外，AD 相关的 DMN 内功能连接异常的研究得到了很好的复制，但是 ECN 和 FPN 内的（增加/减少和减少）功能连接并没有得到足够的关注。为了解决上述问题，在本文中，我们采用稀疏逆协方差估计（SICE）方法来研究 ADNI2 数据集上 ECN 和 FPN 的功能连接变化。我们的实验结果表明，ECN 的左侧额上回（SFGmed.L）和左侧丘脑（THA.L）区域表现出功能连接增加，ECN 的左侧前扣带（ACG.L）区域表现出功能连接减少。FPN 的顶下小叶（SPG）区域和左侧旁中央小叶（PCL.L）表现出功能连接增加，FPN 的左侧缘上回（SMG.L）区域表现出功能连接减少。另一方面，ECN 的 ACG.L 区域、FPN 的 SMG.L 和左侧下顶叶（IPL.L）区域表现出功能连接显著减少。这些结果表明，不仅在 DMN 内，而且在 ECN 和 FPN 中都存在功能连接的增加/减少和减少。这也表明 AD 与大规模功能网络的特征有关，这些变化的功能连接可能是诊断早期阿尔茨海默病的潜在非侵入性生物标志物。
