Bayesian network analysis reveals alterations to default mode network connectivity in individuals at risk for Alzheimer's disease

PLoS One. 2013 Dec 6;8(12):e82104. doi: 10.1371/journal.pone.0082104. eCollection 2013.

Abstract

Alzheimer's disease (AD) is associated with abnormal functioning of the default mode network (DMN). Functional connectivity (FC) changes to the DMN have been found in patients with amnestic mild cognitive impairment (aMCI), which is the prodromal stage of AD. However, whether or not aMCI also alters the effective connectivity (EC) of the DMN remains unknown. We employed a combined group independent component analysis (ICA) and Bayesian network (BN) learning approach to resting-state functional MRI (fMRI) data from 17 aMCI patients and 17 controls, in order to establish the EC pattern of DMN, and to evaluate changes occurring in aMCI. BN analysis demonstrated heterogeneous regional convergence degree across DMN regions, which were organized into two closely interacting subsystems. Compared to controls, the aMCI group showed altered directed connectivity weights between DMN regions in the fronto-parietal, temporo-frontal, and temporo-parietal pathways. The aMCI group also exhibited altered regional convergence degree in the right inferior parietal lobule. Moreover, we found EC changes in DMN regions in aMCI were correlated with regional FC levels, and the connectivity metrics were associated with patients' cognitive performance. This study provides novel sights into our understanding of the functional architecture of the DMN and adds to a growing body of work demonstrating the importance of the DMN as a mechanism of aMCI.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Alzheimer Disease / physiopathology*
  • Bayes Theorem
  • Cognition / physiology
  • Cognitive Dysfunction / physiopathology
  • Demography
  • Female
  • Humans
  • Male
  • Nerve Net / physiopathology*
  • Risk Factors

Grants and funding

This work was supported by the National Natural Science Foundation of China (31271108, 31200847, 30911120494 and 31070916), the Knowledge Innovation Project of the Chinese Academy of Sciences (KSCX2-EW-J-8), the CAS/SAFEA International Partnership Program for Creative Research Team (Y2CX131003), and Scientific Foundation of Institute of Psychology, Chinese Academy of Sciences (Y1CX251005). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.