Abstract
Normative modeling provides a principled framework for quantifying individual deviations from typical brain development and is increasingly used to study heterogeneity in neuropsychiatric conditions. While widely applied to structural phenotypes, functional normative models remain underdeveloped. Here, we introduce MEGaNorm, a normative modeling framework for charting lifespan trajectories of resting-state magnetoencephalography (MEG) brain oscillations. Using a large, multi-site dataset comprising 1846 individuals aged 6-88 and spanning three MEG systems, we model relative oscillatory power in canonical frequency bands using hierarchical Bayesian regression, accounting for age, sex, and site effects. To support interpretation at multiple scales, we introduce Neuro-Oscillo Charts, visual tools that summarize normative trajectories at the population level and quantify individual-level deviations, enabling personalized assessment of functional brain dynamics. Applying this framework to a Parkinson’s disease cohort (n = 160), we demonstrate that normative deviation scores reveal disease-related abnormalities and identify a continuum of patients in the theta-beta deviation space. This work establishes a multi-site normative reference for resting-state MEG oscillations (3-40 Hz) across a broad age range, enabling population-level characterization and individualized benchmarking. All models and tools are openly available and designed for federated, continual adaptation as new data become available, providing a methodological foundation toward precision neuropsychiatry.
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Data availability
No new data were collected for this study. All datasets used in this study are publicly available from established open-access neuroimaging repositories. The Human Connectome Project (HCP Young Adult) dataset107 is available from the Human Connectome Project repository at https://www.humanconnectome.org/study/hcp-young-adult. Access requires registration and agreement to the HCP data use terms. The Open MEG Archive (OMEGA) dataset106 is available via the OMEGA repository, https://doi.org/10.23686/0015896. The National Institute of Mental Health (NIMH) dataset108 is available from OpenNeuro under accession number ds004215.v1.0.3https://openneuro.org/datasets/ds005752/versions/2.1.0. The Cambridge Center for Ageing and Neuroscience (Cam-CAN) dataset105 is available through the Cam-CAN data portal at https://camcan-archive.mrc-cbu.cam.ac.uk/dataaccess/. Access requires an application and approval by the Cam-CAN data access committee. The Boys Town National Research Hospital (BTH) dataset40 is publicly available via the data link provided in the original publication: https://cdn.boystown.org/media/Rempe_Ott_PNAS_2023_Data.zip. The Mother Of Unification Studies (MOUS) dataset109 is available from the Radboud Data Repository, 10.34973/37n0-yc51. We gratefully acknowledge the considerable open-science efforts of the neuroimaging community in making these datasets publicly available. This work would not have been possible without the commitment of these research teams to data sharing and transparent science. All derived data underlying the figures and statistical analyses generated in this study will be made publicly available at https://github.com/ML4PNP/MEG_Norm. All other data supporting the findings of this study are available from the corresponding author upon reasonable request.
Code availability
All custom code developed for data processing, model training, and analysis is openly available in the MEGaNorm GitHub repository and archived on Zenodo78. The code is released under the GNU General Public License v3.0 and includes documentation for installation and usage. Scripts to reproduce the main analyses and figures in this paper are provided in the paper GitHub repository at https://github.com/ML4PNP/MEG_Norm. Additionally, we plan to openly share the derived normative models via the PCNPortal for model extension and adaptation to new datasets.
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Acknowledgements
S.M.K. gratefully acknowledges the starter grant for the “MEGaNorm" project, funded by the Dutch Ministry of Education, Culture and Science under the National Sector Plan. S.M.K. further acknowledges NWA Innovative projects within the routes grant (NWA.1418.24.006) and Small Compute Applications grant (EINF-8659) from the Netherlands Organization for Scientific Research (NWO). S.M.K. thanks the Digital Sciences for Society program at Tilburg University for the Growth Project grant (DSFS 202417) supporting the project “Charting the Normative Electroencephalography in Healthy Aging Population".
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M.Z., S.M.K. conceived the study, developed the methodology, implemented the software, performed the formal analyses, curated the data, conducted the investigation, and generated the visualizations. Y.V., A.d.B., and A.M. contributed to methodology development and software design. A.M., T.R., T.W., R.D., M.Š.P., and M.v.W. contributed to conceptual development and investigation. S.M.K., M.v.W., and M.Š.P. were involved in the supervision. S.M.K. acquired funding and provided resources. M.Z. drafted the original manuscript. All authors reviewed and edited the manuscript and approved the final version.
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Communications Biology thanks Dipanjan Roy, Marios Antonakakis and the other anonymous reviewer(s) for their contribution to the peer review of this work. Primary handling editor: Benjamin Bessieres. A peer review file is available.
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Zamanzadeh, M., Verduyn, Y., de Boer, A. et al. Normative modeling of MEG brain oscillations across the human lifespan. Commun Biol (2026). https://doi.org/10.1038/s42003-026-09825-2
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DOI: https://doi.org/10.1038/s42003-026-09825-2
