Network-level permutation entropy of resting-state MEG recordings: A novel biomarker for early-stage Alzheimer's disease?

ABSTRACT: Increasing evidence suggests that measures of signal variability and complexity could present promising biomarkers for Alzheimer's disease (AD). Earlier studies have however been limited to the characterization of local activity. Here, we investigate whether a network version of permutation entropy could serve as a novel biomarker for early-stage AD. Resting-state source-space magnetoencephalography was recorded in 18 subjects with subjective cognitive decline (SCD) and 18 subjects with mild cognitive impairment (MCI). Local activity was characterized by permutation entropy (PE). Network-level interactions were studied using the inverted joint permutation entropy (JPE_inv), corrected for volume conduction. The JPE_inv showed a reduction of nonlinear connectivity in MCI

SUBMITTER: Scheijbeler EP 

PROVIDER: S-EPMC9208018 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature