Differentiated Effective Connectivity Patterns of the Executive Control Network in Progressive MCI: A Potential

Suping Cai1, Yanlin Peng1, Tao Chong1

  • 1School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071. China.

Abstract

Insights

Brain connectivity patterns in the executive control network differ among individuals with mild cognitive impairment (MCI), offering potential biomarkers for early Alzheimer's disease (AD) detection.

Area of Science:

  • Neuroscience
  • Medical Imaging
  • Cognitive Science

Background:

  • Mild cognitive impairment (MCI) is a transitional stage between normal aging and Alzheimer's disease (AD).
  • MCI progression is variable, with some patients converting to AD, while others stabilize or revert to normal cognition.
  • Executive functions, supported by the executive control network (ECN), are increasingly recognized as affected in MCI/AD.

Purpose of the Study:

  • To investigate whether effective connectivity patterns within the ECN differ among MCI patients with distinct longitudinal outcomes.
  • To identify potential neuroimaging biomarkers for stratifying MCI patient risk and progression.

Main Methods:

  • Longitudinal classification of MCI patients into reverted (MCI-R), stable (MCI-S), and progressed (MCI-P) groups.
  • Independent Component Analysis (ICA) to identify core ECN nodes.
  • Granger causality analysis to assess effective connectivity within the ECN.

Main Results:

  • Significant differences in ECN effective connectivity were observed between MCI subgroups and normal controls (NC).
  • Key ECN nodes, including the dorsolateral prefrontal cortex (dLPFC) and medial prefrontal cortex (mPFC), showed altered connectivity patterns.
  • Specific circuits within the ECN, such as "R.dLPFC→ right caudate→ left thalamus→R.dLPFC", exhibited varying degrees of damage across MCI groups.

Conclusions:

  • Differentiated effective connectivity within the ECN may serve as a potential biomarker for early AD detection.
  • These findings can inform clinical research by providing a reference for targeted interventions based on individual MCI patient risk profiles.

Related Concept Videos