Reorganized brain functional network topology in stable and progressive mild cognitive impairment

Chen Xue1, Darui Zheng1, Yiming Ruan1

  • 1Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.

PubMed
Abstract

Insights

Brain network analysis reveals distinct topological changes in stable and progressive mild cognitive impairment (MCI). These brain network alterations correlate with cognitive function, highlighting the cerebellum's key role and potential for early diagnosis.

Area of Science:

  • Neuroimaging
  • Cognitive Neuroscience
  • Network Science

Background:

  • Mild cognitive impairment (MCI) presents as stable (sMCI) or progressive (pMCI) subtypes.
  • Understanding the topological reorganization of brain functional networks is crucial for differentiating MCI subtypes.
  • Resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory offer powerful tools for network analysis.

Purpose of the Study:

  • To identify and compare the topological reorganization of brain functional networks in pMCI and sMCI patients.
  • To investigate the relationship between network topological properties and clinical outcomes.
  • To explore the role of specific brain modules, such as the cerebellum, in network interactions.

Main Methods:

  • rs-fMRI data acquired from pMCI, sMCI, and healthy control (HC) groups.
  • Graph theory applied to analyze global and nodal network metrics, modularity, and rich-club organization.
  • Statistical analyses including ANCOVA, t-tests, and correlation analysis to assess group differences and clinical correlations.

Main Results:

  • Significant differences in clustering coefficients and small-worldness observed across groups.
  • Abnormal degree centrality and nodal efficiency detected in several brain regions.
  • pMCI and sMCI groups exhibited reduced connectivity in rich-club organization compared to HC.
  • The cerebellar module demonstrated a critical role in intra- and inter-module network interactions.

Conclusions:

  • Distinct topological properties of brain functional networks differentiate sMCI, pMCI, and HC.
  • Network alterations correlate significantly with cognitive function.
  • Findings suggest potential for developing imaging biomarkers for early diagnosis and intervention in Alzheimer's disease.

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