Time-Frequency functional connectivity alterations in Alzheimer's disease and frontotemporal dementia: An EEG analysis using machine learning.

Journal: Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
PMID: 39708531

Abstract

OBJECTIVE: Alzheimer's disease (AD) and frontotemporal dementia (FTD) are prevalent neurodegenerative diseases characterized by altered brain functional connectivity (FC), affecting over 100 million people worldwide. This study aims to identify distinct FC patterns as potential biomarkers for differential diagnosis.

Authors

  • Huang Zheng
    School of Psychological and Cognitive Sciences, PKU-IDG/McGovern Institute for Brain Research, Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China.
  • Han Xiao
    Department of Radiation Oncology, Zhongshan Hospital, Fudan University, Shanghai, China.
  • YiNan Zhang
    School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China.
  • Haozhe Jia
  • Xing Ma
    Center for Higher Education Research and Teaching Quality Evaluation, Harbin Medical University, Harbin, Heilongjiang, 150000, China.
  • Yiqun Gan
    School of Psychological and Cognitive Sciences, Peking University, Beijing, China. Electronic address: ygan@pku.edu.cn.

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