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Updated: Jan 17, 2026
Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
Published on: June 15, 2018
Characterizing resting-state EEG oscillatory and aperiodic activity in neurodegenerative diseases: A multicentric
Alberto Jaramillo-Jimenez1, Yorguin-Jose Mantilla-Ramos2, Diego A Tovar-Rios3
1Centre for Age-Related Medicine (SESAM), Stavanger University Hospital, Stavanger, Norway; Grupo de Neurociencias de Antioquia (GNA), Facultad de Medicina, Universidad de Antioquia, Medellín, Colombia; Grupo Neuropsicología y Conducta (GRUNECO), Facultad de Medicina, Universidad de Antioquia, Medellín, Colombia; Semillero de Investigación NeuroCo, Facultad de Ingeniería & Facultad de Medicina, Universidad de Antioquia, Medellín, Colombia.
Background:
Abnormalities in resting-state electroencephalogram (rsEEG) posterior alpha rhythm are promising biomarkers of neurodegenerative diseases (NDDs), often assessed via spectral analysis, ignoring the signal's non-rhythmic (aperiodic) component. Evidence assessing aperiodic and oscillatory rsEEG abnormalities across NDDs is scarce and often underpowered. Multicenter studies could tackle these limitations, but data pooling might introduce site-related rsEEG differences (batch effects). This study aims to characterize rsEEG oscillatory and aperiodic patterns across NDDs, minimizing potential batch effects.
Methods:
RsEEGs (n = 639; 11 sites) were automatically preprocessed. Signals comprised healthy controls (HC = 153), Lewy Body Dementias (LBD = 95), Parkinson's Disease (PD = 71), Alzheimer's Disease (AD = 186), Frontotemporal Dementia (FTD = 23), Mild Cognitive Impairment (MCI) in positive Lewy Bodies pathology or PD (MCI-LBD = 34), and MCI in positive AD pathology (MCI-AD = 77). Power spectrum batch effects were harmonized using reComBat (age, sex, and diagnosis-adjusted). Harmonization was evaluated with functional and mass-univariate ANOVAs. Oscillatory and aperiodic parameters were extracted from the batch-harmonized power spectrum. NDDs-related differences were estimated with functional and mass-univariate tests, bootstrapped pairwise comparisons, and logistic regressions.
Results:
Statistical testing showed reduced batch effects after harmonization. Significantly steeper aperiodic parameters and lower oscillatory center frequency were observed in LBD compared to other NDDs. The oscillatory extended alpha power was lower in AD comparisons (except AD vs. LBD).
Conclusions:
Batch effects in the rsEEG power spectrum can be mitigated with harmonization. Oscillatory alpha power reduction may better reflect AD abnormalities, whereas pronounced oscillatory frequency slowing and greater aperiodic activity characterize LBD.
