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Updated: May 14, 2026

Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment
Published on: August 7, 2017
Exploring the effective connectivity of resting state networks in mild cognitive impairment: an fMRI study combining
Zhenyu Liu1, Lijun Bai, Ruwei Dai
1Intelligent Medical Research Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China. liuzhenyu@fingerpass.net.cn
Abstract:
Mild cognitive impairment (MCI) was recognized as the prodromal stage of Alzheimer's disease (AD). Recent neuroimaging studies have shown that the cognitive and memory decline in AD and MCI patients is coupled with abnormal functions of focal brain regions and disrupted functional connectivity between distinct brain regions, as well as losses of small-world attributes. However, the causal interactions among the spatially isolated but function-related resting state networks (RSNs) are still largely unexplored in MCI patients. In this study, we first identified eight RSNs by independent components analysis (ICA) from resting state functional MRI data of 16 MCI patients and 18 age-matched healthy subjects respectively. Then, we performed a multivariate Granger causality analysis (mGCA) to evaluate the effective connectivity among the RSNs. We found that MCI patients exhibited decreased causal interactions among the RSNs in both intensity and quantity compared with normal controls. Results from mGCA indicated that the causal interactions involving the default mode network (DMN) became weaker in MCI patients, while stronger causal connectivity emerged related to the memory network and executive control network. Our findings suggested that the DMN played a less important role in MCI patients. Increased causal connectivity of the memory network and executive control network may elucidate the dysfunctional and compensatory processes in the brain networks of MCI patients. These preliminary findings may be helpful for further understanding the pathological mechanisms of MCI and provide a new clue to explore the neurophysiological mechanisms of MCI.
Insights
Mild cognitive impairment (MCI) involves altered brain network communication. MCI patients show weaker causal interactions involving the default mode network but stronger connections in memory and executive control networks.
Area of Science:
- Neuroscience
- Medical Imaging
- Cognitive Neurology
Background:
- Mild cognitive impairment (MCI) is a precursor to Alzheimer's disease (AD).
- Cognitive decline in MCI and AD is linked to brain region dysfunction and disrupted functional connectivity.
- Causal interactions within resting-state networks (RSNs) in MCI remain under-explored.
Purpose of the Study:
- To investigate causal interactions among RSNs in MCI patients.
- To compare effective connectivity patterns between MCI patients and healthy controls.
- To elucidate the role of specific brain networks in MCI pathophysiology.
Main Methods:
- Identified eight RSNs using independent components analysis (ICA) on resting-state functional MRI data.
- Applied multivariate Granger causality analysis (mGCA) to assess effective connectivity among RSNs.
- Analyzed data from 16 MCI patients and 18 age-matched healthy controls.
Main Results:
- MCI patients exhibited reduced intensity and quantity of causal interactions among RSNs compared to controls.
- Causal interactions involving the default mode network (DMN) were weaker in MCI.
- Increased causal connectivity was observed in the memory and executive control networks in MCI patients.
Conclusions:
- The default mode network plays a diminished role in MCI.
- Enhanced causal connectivity in memory and executive control networks may reflect dysfunctional and compensatory brain processes in MCI.
- Findings offer insights into MCI's pathological mechanisms and neurophysiology.
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