Li, MinMinLiWang, YingYingWangLopez-Naranjo, CarlosCarlosLopez-NaranjoReyes, Ronaldo Cesar GarciaRonaldo Cesar GarciaReyesHamid, Aini Ismafairus AbdAini Ismafairus AbdHamidEvans, Alan CAlan CEvansSavostyanov, Alexander NAlexander NSavostyanovCalzada-Reyes, AnaAnaCalzada-ReyesAreces-Gonzalez, ArioskyArioskyAreces-GonzalezVillringer, ArnoArnoVillringerTobon-Quintero, Carlos ACarlos ATobon-QuinteroGarcia-Agustin, DaysiDaysiGarcia-AgustinPaz-Linares, DeirelDeirelPaz-LinaresYao, DezhongDezhongYaoDong, LiLiDongAubert-Vazquez, EduardoEduardoAubert-VazquezReza, FaruqueFaruqueRezaOmar, HazimHazimOmarAbdullah, Jafri MalinJafri MalinAbdullahGaller, Janina RJanina RGallerOchoa-Gomez, John FJohn FOchoa-GomezPrichep, Leslie SLeslie SPrichepGalan-Garcia, LidiceLidiceGalan-GarciaMorales-Chacon, LiliaLiliaMorales-ChaconValdes-Sosa, Mitchell JMitchell JValdes-SosaTröndle, MariusMariusTröndleZulkifly, Mohd Faizal Bin MohdMohd Faizal Bin MohdZulkiflyRahman, Muhammad Riddha Bin AbdulMuhammad Riddha Bin AbdulRahmanMilakhina, Natalya SNatalya SMilakhinaLanger, NicolasNicolasLangerRudych, PavelPavelRudychHu, ShiangShiangHuKönig, ThomasThomasKönig0000-0002-1472-4638Virues-Alba, Trinidad ATrinidad AVirues-AlbaLei, XuXuLeiBringas-Vega, Maria LMaria LBringas-VegaBosch-Bayard, Jorge FJorge FBosch-BayardValdes-Sosa, Pedro AntonioPedro AntonioValdes-Sosa2024-10-092024-10-092022-08-01https://boris-portal.unibe.ch/handle/20.500.12422/70134This paper extends the frequency domain quantitative electroencephalography (qEEG) methods pursuing higher sensitivity to detect Brain Developmental Disorders. Prior qEEG work lacked integration of cross-spectral information omitting important functional connectivity descriptors. Lack of geographical diversity precluded accounting for site-specific variance, increasing qEEG nuisance variance. We ameliorate these weaknesses. i) Create lifespan Riemannian multinational qEEG norms for cross-spectral tensors. These norms result from the HarMNqEEG project fostered by the Global Brain Consortium. We calculate the norms with data from 9 countries, 12 devices, and 14 studies, including 1564 subjects. Instead of raw data, only anonymized metadata and EEG cross-spectral tensors were shared. After visual and automatic quality control, developmental equations for the mean and standard deviation of qEEG traditional and Riemannian DPs were calculated using additive mixed-effects models. We demonstrate qEEG "batch effects" and provide methods to calculate harmonized z-scores. ii) We also show that the multinational harmonized Riemannian norms produce z-scores with increased diagnostic accuracy to predict brain dysfunction at school-age produced by malnutrition only in the first year of life. iii) We offer open code and data to calculate different individual z-scores from the HarMNqEEG dataset. These results contribute to developing bias-free, low-cost neuroimaging technologies applicable in various health settings.enBatch effects EEG Cross-Spectrum ElectroencephalographyClinical neurosciencequantitative EEG Harmonization Mahalanobis distance Riemannian geometry z-scorearticle10.48350/1692343539828510.1016/j.neuroimage.2022.119190