Unveiling neural activity changes in mild cognitive impairment using microstate analysis and machine learning.

Journal: Journal of Alzheimer's disease : JAD
PMID: 39772750

Abstract

BACKGROUND: Mild cognitive impairment (MCI) is recognized as a condition that may increase the risk of developing Alzheimer's disease (AD). Understanding the neural correlates of MCI is crucial for elucidating its pathophysiology and developing effective interventions. Electroencephalogram (EEG) microstates, reflecting brain activity changes, have shown promise in MCI research. However, current approaches often lack comprehensive characterization of the complex neural dynamics associated with MCI.

Authors

  • Xiaotian Wu
    Yale University, New Haven, CT, USA VA Connecticut Healthcare System, West Haven, CT, USA.
  • Yanli Liu
    Baodi Clinical College, Tianjin Medical University, 8 Guangchuan Road, Tianjin, 301800, China.
  • Jiajun Che
    Department of Psychology, Chengde Medical University, Chengde City, Hebei Province, China.
  • Nan Cheng
  • Dong Wen
    Center for Medical Informatics, Peking University, Beijing, China.
  • Haining Liu
    Department of Psychology, Chengde Medical University, Chengde City, Hebei Province, China.
  • Xianling Dong
    Present Address: Department of Biomedical Engineering, Chengde Medical University, Chengde City, Hebei Province, China.

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