Differentiated Effective Connectivity Patterns of the Executive Control Network in Progressive MCI: A Potential Biomarker for Predicting AD

Objective: Mild cognitive impairment (MCI) is often a transitional state between normal aging and Alzheimer's disease (AD). When observed longitudinally, some MCI patients convert to AD, while a considerable portion either remains MCI or revert to a normal functioning state. This divergence has provided some enlightenment on a potential biomarker to be represented in the resting state brain activities of MCI patients with different post-hoc labels. Recent studies have shown impaired executive functions, other than typically explicated memory impairment with AD/MCI patients. This observation raises the question that whether or not the executive control network (ECN) was impaired, which pivotally supports the central executive functions. Given the fact that effective connectivity is a sufficient index in detecting resting brain abnormalities in AD/MCI, the current study specifically asks a question whether the effective connectivity patterns are differentiated in MCI patients with different post-hoc labels. Keywords: Effective connectivity, granger causality analysis, executive control network, progressive MCI, resting state, independent component analysis, biomarker.