Evaluating functional connectivity of executive control network and frontoparietal network in Alzheimer's disease
Evaluating functional connectivity of executive control network and frontoparietal network in Alzheimer's disease
复制标题
评估阿尔茨海默病执行控制网络和额顶叶网络的功能连接
DOI:
10.1016/j.brainres.2017.10.025
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发表时间:
2017
期刊:
影响因子:
2.9
通讯作者:
Jianfeng Lu
中科院分区:
文献类型:
--
作者:
Qinghua Zhao;Hong Lu;Hichem Metmer;Will X.Y. Li(李翔宇);Jianfeng Lu
Investigating the early Alzheimer’s disease (AD) more emphasizes sensitive and specific biomarkers, which can help the clinicians to monitor the progression and treatments of AD. Among these biomarkers, default mode network (DMN) functional connectivity is gaining more attention as a potential noninvasive biomarker to diagnose incipient Alzheimer's disease. However, besides changed functional connectivity of DMN, other functional networks haven’t yet been examined systematically. Recent brain imaging studies reported that a number of reproducible and robust functional networks, which were distributed in distant neuroanatomic areas. Inspired by these works, in this paper, we apply sparse representation to the whole brain signals to identify these reproducible networks and detect partly affected brain regions of Alzheimer’s disease, then adopt sparse inverse covariance estimation (SICE) approach to investigate the changed functional connectivity of intrinsic connectivity networks. Our experimental results show that besides DMN, AD is also affected by others large scale functional brain networks and regions, e.g., executive control network (ECN), frontoparietal network (FPN), where in the superior frontal gyrus (SFGmed) and middle frontal gyrus (MFG) of ECN and in the part paracentral Lobule (PCL) of FPN have an increased functional connectivity, as well as in the Superior Parietal Gyrus (SPG) regions of FPN has shown decreased connectivity. The results may suggest AD is associated with larger scale functional networks and causes the functional connectivity change of many different brain regions. It also proves that these networks may sometimes work together to perform tasks, and such changed functional connectivity may provide a useful baseline for early AD diagnosis.