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Investigation of the effective connectivity of resting state networks in Alzheimer's disease: a functional MRI study combining independent components analysis and multivariate Granger causality analysis
Author(s) -
Liu Zhenyu,
Zhang Yumei,
Bai Lijun,
Yan Hao,
Dai Ruwei,
Zhong Chongguang,
Wang Hu,
Wei Wenjuan,
Xue Ting,
Feng Yuanyuan,
You Youbo,
Tian Jie
Publication year - 2012
Publication title -
nmr in biomedicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.278
H-Index - 114
eISSN - 1099-1492
pISSN - 0952-3480
DOI - 10.1002/nbm.2803
Subject(s) - default mode network , resting state fmri , granger causality , neuroscience , psychology , functional magnetic resonance imaging , cognition , neuroimaging , disease , causality (physics) , functional connectivity , neurophysiology , medicine , computer science , machine learning , physics , quantum mechanics
Recent neuroimaging studies have shown that the cognitive and memory decline in patients with Alzheimer's disease (AD) is coupled with abnormal functions of focal brain regions and disrupted functional connectivity between distinct brain regions, as well as losses in small‐world attributes. However, the causal interactions among the spatially isolated, but functionally related, resting state networks (RSNs) are still largely unexplored. In this study, we first identified eight RSNs by independent components analysis from resting state functional MRI data of 18 patients with AD and 18 age‐matched healthy subjects. We then performed a multivariate Granger causality analysis (mGCA) to evaluate the effective connectivity among the RSNs. We found that patients with AD exhibited decreased causal interactions among the RSNs in both intensity and quantity relative to normal controls. Results from mGCA indicated that the causal interactions involving the default mode network and auditory network were weaker in patients with AD, whereas stronger causal connectivity emerged in relation to the memory network and executive control network. Our findings suggest that the default mode network plays a less important role in patients with AD. Increased causal connectivity of the memory network and self‐referential network may elucidate the dysfunctional and compensatory processes in the brain networks of patients with AD. These preliminary findings may provide a new pathway towards the determination of the neurophysiological mechanisms of AD. Copyright © 2012 John Wiley & Sons, Ltd.