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Updated: Jun 2, 2026
Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment
Published on: August 7, 2017
Using functional Magnetic Resonance Imaging to differentiate between healthy aging subjects, Mild Cognitive
Mohammad Ali Oghabian1, Seyed Amir Hossein Batouli, Maryam Norouzian
1Medical Physics and Biomedical Engineering Department, Tehran University of Medical Sciences, Tehran, Iran.
Background:
Alzheimer's disease is the most common form of dementia which is still difficult to be differentiated from other types of brain disorders. Moreover, Mild Cognitive Impairment refers to the presence of cognitive impairments that is not severe enough to meet the criteria of Alzheimer's, and its diagnosis in early stages is so critical. There is currently no distinct method available for diagnosing Alzheimer's or Mild Cognitive Impairment, and their diagnosis needs a combination of different methods and assessments.
Methods:
The aim of this study was to evaluate the effectiveness of functional Magnetic Resonance Imaging (fMRI) in differentiating between Alzheimer's, Mild Cognitive Impairment (MCI) and healthy aging. To prove fMRI's ability, resting-state brain activation patterns between these three groups of subjects were compared using Independent Component Analysis (ICA) algorithm. Forty age- and sex-matched subjects, 15 elderly, 11 MCI and 14 Alzheimer's subjects were examined.
Results:
The results showed that during a certain resting-state session, healthy aging brain benefits from larger area and greater intensity of activation (compared with MCI and Alzheimer's group) in Posterior Cingulate Cortex (PCC) region of the brain, as part of Default Mode Network.
Conclusions:
This difference in activation pattern can be used as a diagnostic criterion in using fMRI for differentiating between Alzheimer's Disease (AD), MCI and healthy aging.
