Hu Yang, Du Wenying, Zhang Yiwen, Li Ningning, Han Ying, Yang Zhi
Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China.
Front Aging Neurosci. 2019 Mar 27;11:67. doi: 10.3389/fnagi.2019.00067. eCollection 2019.
A functional brain network, termed the parietal memory network (PMN), has been shown to reflect the familiarity of stimuli in both memory encoding and retrieval. The function of this network has been separated from the commonly investigated default mode network (DMN) in both resting-state fMRI and task-activations. This study examined the deficit of the PMN in Alzheimer's disease (AD) patients using resting-state fMRI and independent component analysis (ICA) and investigated its diagnostic value in identifying AD patients. The DMN was also examined as a reference network. In addition, the robustness of the findings was examined using different types of analysis methods and parameters. Our results showed that the integrity as an intrinsic connectivity network for the PMN was significantly decreased in AD and this feature showed at least equivalent predictive ability to that for the DMN. These findings were robust to varied methods and parameters. Our findings suggest that the intrinsic connectivity of the PMN is disrupted in AD and further call for considering the PMN and the DMN separately in clinical neuroimaging studies.
一个被称为顶叶记忆网络(PMN)的功能性脑网络已被证明在记忆编码和检索过程中都能反映刺激的熟悉程度。在静息态功能磁共振成像(fMRI)和任务激活中,该网络的功能已与常用的默认模式网络(DMN)区分开来。本研究使用静息态fMRI和独立成分分析(ICA)检查了阿尔茨海默病(AD)患者的PMN缺陷,并研究了其在识别AD患者中的诊断价值。DMN也作为参考网络进行了检查。此外,还使用不同类型的分析方法和参数检查了研究结果的稳健性。我们的结果表明,作为PMN固有连接网络的完整性在AD中显著降低,并且该特征显示出至少与DMN相当的预测能力。这些发现对各种方法和参数都很稳健。我们的研究结果表明,AD中PMN的固有连接被破坏,并进一步呼吁在临床神经影像学研究中分别考虑PMN和DMN。