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

作者: Zhenyu Liu , Yumei Zhang , Lijun Bai , Hao Yan , Ruwei Dai

DOI: 10.1002/NBM.2803

关键词: NeuroimagingDiseaseNeuroscienceResting state fMRICognitionBiologyNeurophysiologyMultivariate statisticsIndependent component analysisDefault mode network

摘要: Recent neuroimaging studies have shown that the cognitive and memory decline in patients with Alzheimer's disease (AD) is coupled abnormal functions of focal brain regions disrupted functional connectivity between distinct regions, as well losses small-world attributes. However, causal interactions among 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 MRI data 18 AD age-matched healthy subjects. We then performed a multivariate Granger causality (mGCA) to evaluate effective RSNs. found exhibited decreased both intensity quantity relative normal controls. Results mGCA indicated involving default mode network auditory were weaker AD, whereas stronger emerged relation executive control network. Our findings suggest plays less important role AD. Increased self-referential may elucidate dysfunctional compensatory processes These preliminary provide new pathway towards determination neurophysiological mechanisms Copyright (c) 2012 John Wiley & Sons, Ltd.

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