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Updated: May 22, 2026

Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment
Published on: August 7, 2017
Altered default-mode network activation in mild cognitive impairment compared with healthy aging
Frederick De Vogelaere1, Patrick Santens, Erik Achten
1Department of Neurology, Ghent University Hospital, De Pintelaan 185, Ghent, Belgium. Frederick.DeVogelaere@UGent.be
Early Alzheimer's disease (AD) detection is crucial. This study found reduced default-mode network (DMN) activation in mild cognitive impairment (MCI) patients, suggesting potential early biomarkers for AD progression.
Area of Science:
- Neuroscience
- Gerontology
Background:
- Global population aging drives increased prevalence of Alzheimer's disease (AD) and mild cognitive impairment (MCI).
- Early identification of individuals at risk is essential for disease management and preserving quality of life.
Purpose of the Study:
- To identify and compare the default-mode network (DMN) in healthy elderly individuals and patients with MCI.
- To investigate hippocampal and lateral temporal involvement within the DMN in these groups.
Main Methods:
- Utilized independent component analysis (ICA) and statistical parametric mapping (SPM).
- Compared DMN functional activation between MCI patients and age/education-matched healthy elderly controls.
Main Results:
- MCI patients exhibited reduced DMN cortical activation, particularly in the retrosplenial cortex/posterior cingulate cortex, left hippocampus, and frontal areas.
- Increased activation was noted in MCI patients within the medial prefrontal cortex and bilateral middle temporal/angular cortex.
- Lateral temporal regions showed slightly increased DMN activation in MCI patients compared to controls, more pronounced on the right.
Conclusions:
- Findings suggest alterations in DMN resting-state networks in early MCI.
- Discussed in the context of early pathological changes in AD and MCI and compensatory mechanisms.
- Highlights potential for DMN analysis as a biomarker for early detection and disease monitoring.
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