Longitudinal characterization of EEG power spectra during eyes open and eyes closed conditions in children. (15th August 2022) - Isler, Joseph R.; Pini, Nicolò; Lucchini, Maristella; Shuffrey, Lauren C.; Morales, Santiago; Bowers, Maureen E.; Leach, Stephanie C.; Sania, Ayesha; Wang, Lily; Condon, Carmen; Nugent, J. David; Elliott, Amy J.; et al.
Abstract: This study is the first to examine spectrum‐wide (1 to 250 Hz) differences in electroencephalogram (EEG) power between eyes open (EO) and eyes closed (EC) resting state conditions in 486 children. The results extend the findings of previous studies by characterizing EEG power differences from 30 to 250 Hz between EO and EC across childhood. Developmental changes in EEG power showed spatial and frequency band differences as a function of age and EO/EC condition. A 64‐electrode system was used to record EEG at 4, 5, 7, 9, and 11 years of age. Specific findings were: (1) the alpha peak shifts from 8 Hz at 4 years to 9 Hz at 11 years, (2) EC results in increased EEG power (compared to EO) at lower frequencies but decreased EEG power at higher frequencies for all ages, (3) the EEG power difference between EO and EC changes from positive to negative within a narrow frequency band which shifts toward higher frequencies with age, from 9 to 12 Hz at 4 years to 32 Hz at 11 years, (4) at all ages EC is characterized by an increase in lower frequency EEG power most prominently over posterior regions, (5) at all ages, during EC, decreases in EEG power above 30 Hz are mostly over anterior regions of the scalp. This report demonstrates that the simple challenge of opening and closing the eyes offers the potential to provide quantitative biomarkers of phenotypic variation in brain maturation by employing a brief, minimally invasive protocol throughout childhood. Abstract : EEG resting state activity changes throughout childhood and is different in eyes open versus eyes closed conditions across the full EEG power spectrum. These differences in cortical activity measured by scalp EEG, using a brief, minimally invasive protocol, may provide quantitative biomarkers of phenotypic variation in brain maturation.