Novel methodology for detection and prediction of mild cognitive impairment using resting-state EEG.

ABSTRACT:

Background

Early discrimination and prediction of cognitive decline are crucial for the study of neurodegenerative mechanisms and interventions to promote cognitive resiliency.

Methods

Our research is based on resting-state electroencephalography (EEG) and the current dataset includes 137 consensus-diagnosed, community-dwelling Black Americans (ages 60-90 years, 84 healthy controls [HC]; 53 mild cognitive impairment [MCI]) recruited through Wayne State University and Michigan Alzheimer's Disease Research Center. We conducted multiscale analysis on time-varying brain functional connectivity and developed an innovative soft discrimination model in which each decision on HC or MCI also comes with a connectivity-based score.

Results

The leave-one-out cross-validation accu

SUBMITTER: Deng J 

PROVIDER: S-EPMC10811294 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature