Population-level modeling can define quantitative measures of individual aging by applying
machine learning to large volumes of brain images. These measures of brain age, obtained …

Owing to a lack of appropriate biomarkers for accurate diagnosis and treatment, psychiatric
disorders cause significant distress and functional impairment, leading to social and …

Objective Quantitative electroencephalography (QEEG) is a non-invasive, reliable and
easily accessible modality to assess neuronal activity. QEEG in acute stroke may predict …

Introduction Harmonization protocols that address batch effects and cross‐site
methodological differences in multi‐center studies are critical for strengthening …

Abstract Objective This study aims 1) To analyse differences in resting-state
electroencephalogram (rs-EEG) spectral features of Parkinson's Disease (PD) and healthy …

Electroencephalography (EEG) data is often collected from diverse contexts involving
different populations and EEG devices. This variability can induce distribution shifts in the …

Objective This study compares the complementary information from semi-quantitative EEG
(sqEEG) and spectral quantitative EEG (spectral-qEEG) to detect the life-long effects of early …

Resting-state EEG (rs-EEG) has been demonstrated to aid in Parkinson's disease (PD)
diagnosis. In particular, the power spectral density (PSD) of low-frequency bands (δ and θ) …

Objective Pooling multisite resting-state electroencephalography (rsEEG) datasets may
introduce bias due to batch effects (ie, cross-site differences in the rsEEG related to …

The article presents the results of a study aimed at finding covariates to account for the
activity of implicit cognitive processes in conditions of functional rest of the subjects and …