Abstract
Background: Nonlinear dynamical measures, such as fractal dimension (FD), entropy, and
Lempel-Ziv complexity (LZC), have been extensively investigated individually for
detecting information content in magnetoencephalograms (MEGs) from patients with
Alzheimer’s dementia (AD).
Objective: To compare systematically the performance of twenty conventional and
recently introduced nonlinear dynamical measures in studying AD vs. mild cognitive
impairment (MCI) and healthy control (HC) subjects using MEG.
Methods: We compared twenty nonlinear measures to distinguish MEG recordings from
36 AD participants (mean age=74.06±6.95 years); 18 MCI participants (mean
age=74.89±5.57 years, and 26 HC subjects (mean age=71.77±6.38 years) in different brain
regions and also evaluated the effect of the length of MEG epochs on their performance.
We also studied the correlation between these measures and cognitive performance based
on the Mini Mental State Examination (MMSE).
Results: The results obtained by LZC, zero-crossing rate (ZCR), FD, and dispersion
entropy (DispEn) measures showed significant differences among the three groups. There
was no significant difference between HC and MCI. The highest Hedge’s g effect sizes for
HC vs. AD and MCI vs. AD were respectively obtained by Higuchi’s FD (HFD) and fuzzy
DispEn (FuzDispEn) in the whole brain and was most prominent in left lateral. The results
obtained by HFD and FuzDispEn had a significant correlation with the MMSE scores.
DispEn-based techniques, LZC, and ZCR, compared with HFD, were less sensitive to
epoch length in distinguishing HC form AD.
Conclusions: FuzDispEn was the most consistent technique to distinguish MEG dynamical
patterns in AD compared with HC and MCI.