机构：[1]LIAMA Center for Computational Medicine, National Laboratory of Pattern Recognition, Institute of Automation, The Chinese Academy of Sciences, Beijing 100190, China[2]Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 3EB, UK[3]Department of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China[4]Department of Neurology,Xuanwu Hospital of Capital Medical University, Beijing 100053, China神经内科首都医科大学宣武医院[5]Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China放射科首都医科大学宣武医院[6]Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China[7]The Queensland Brain Institute, The University of Queensland, Brisbane QLD 4072, Australia[8]Clinical Unit Cambridge, GlaxoSmithKline, Addenbrooke’s Hospital, Cambridge CB2 0SZ, UK
Alzheimer's disease (AD) is increasingly recognized as a disconnection syndrome, which leads to cognitive impairment due to the disruption of functional activity across large networks or systems of interconnected brain regions. We explored abnormal functional magnetic resonance imaging (fMRI) resting-state dynamics, functional connectivity, and weighted functional networks, in a sample of patients with severe AD (N = 18) and age-matched healthy volunteers (N = 21). We found that patients had reduced amplitude and regional homogeneity of low-frequency fMRI oscillations, and reduced the strength of functional connectivity, in several regions previously described as components of the default mode network, for example, medial posterior parietal cortex and dorsal medial prefrontal cortex. In patients with severe AD, functional connectivity was particularly attenuated between regions that were separated by a greater physical distance; and loss of long distance connectivity was associated with less efficient global and nodal network topology. This profile of functional abnormality in severe AD was consistent with the results of a comparable analysis of data on 2 additional groups of patients with mild AD (N = 17) and amnestic mild cognitive impairment (MCI; N = 18). A greater degree of cognitive impairment, measured by the mini-mental state examination across all patient groups, was correlated with greater attenuation of functional connectivity, particularly over long connection distances, for example, between anterior and posterior components of the default mode network, and greater reduction of global and nodal network efficiency. These results indicate that neurodegenerative disruption of fMRI oscillations and connectivity in AD affects long-distance connections to hub nodes, with the consequent loss of network efficiency. This profile was evident also to a lesser degree in the patients with less severe cognitive impairment, indicating that the potential of resting-state fMRI measures as biomarkers or predictors of disease progression in AD.
基金：
the National Key Basic Research and Development Program (973), (grant number 2011CB707800);
the Natural Science Foundation of China, (grant numbers 60831004, 81270020, and 30900476);
the Natural Science Foundation of Tianjin, (grant number11JCZDJC19300).
第一作者机构：[1]LIAMA Center for Computational Medicine, National Laboratory of Pattern Recognition, Institute of Automation, The Chinese Academy of Sciences, Beijing 100190, China[2]Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 3EB, UK
共同第一作者：
通讯作者：
通讯机构：[*1]LIAMA Center for Computational Medicine, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190 China.
推荐引用方式(GB/T 7714)：
Yong Liu,Chunshui Yu,Xinqing Zhang,et al.Impaired Long Distance Functional Connectivity and Weighted Network Architecture in Alzheimer's Disease[J].CEREBRAL CORTEX.2014,24(6):1422-1435.doi:10.1093/cercor/bhs410.
APA：
Yong Liu,Chunshui Yu,Xinqing Zhang,Jieqiong Liu,Yunyun Duan...&Ed Bullmore.(2014).Impaired Long Distance Functional Connectivity and Weighted Network Architecture in Alzheimer's Disease.CEREBRAL CORTEX,24,(6)
MLA：
Yong Liu,et al."Impaired Long Distance Functional Connectivity and Weighted Network Architecture in Alzheimer's Disease".CEREBRAL CORTEX 24..6(2014):1422-1435
医学