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

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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