{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,11]],"date-time":"2026-10-11T12:47:29Z","timestamp":1791722849310,"version":"4.3.4"},"reference-count":308,"publisher":"MIT Press","license":[{"start":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T00:00:00Z","timestamp":1779321600000},"content-version":"vor","delay-in-days":140,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["13851350"],"award-info":[{"award-number":["13851350"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004937","name":"Bundesministerium f\u00fcr Forschung und Technologie","doi-asserted-by":"publisher","award":["01EQ2403G"],"award-info":[{"award-number":["01EQ2403G"]}],"id":[{"id":"10.13039\/501100004937","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007569","name":"Carl-Zeiss-Stiftung","doi-asserted-by":"crossref","award":["P2022-00-087"],"award-info":[{"award-number":["P2022-00-087"]}],"id":[{"id":"10.13039\/100007569","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["direct.mit.edu"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,6,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Normative modeling has become a cornerstone of computational neuroscience, offering a powerful framework for detecting individual deviations from typical brain function. This review traces its trajectory in electrophysiology of the brain, from early studies in the 1970s, through a period of relative neglect, to its recent revival driven by machine learning advances and the availability of large-scale datasets. We provide a structured overview of this evolution, showing the shift from small, site-specific age-based models to increasingly harmonized approaches that integrate diverse biological and methodological innovations. Key studies are compared with respect to cohort composition, modeling strategies, and validation procedures, situating each within the broader arc of methodological progress. Despite this momentum, significant challenges remain, such as a lack of standardized practices, limited comparability across studies, and the need for richer integration of complex neurophysiological signals. Looking ahead, we argue that the future of electrophysiological normative modeling lies in scaling and unifying efforts, through international collaborations, standardized pipelines, and the incorporation of novel features. By coupling machine learning with both cross-sectional and longitudinal designs, the field can progress from proof-of-concept demonstrations to precise, individualized brain mapping. Ultimately, such advances will provide the foundation for clinical applications, enabling cost-effective personalized treatment monitoring and a more refined understanding of individual differences in complex brain disorders.<\/jats:p>","DOI":"10.1162\/imag.a.1269","type":"journal-article","created":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T20:01:41Z","timestamp":1779393701000},"update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":1,"title":["From early to contemporary normative modeling: Mapping individual differences in neurophysiological signals"],"prefix":"10.1162","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-3839-845X","authenticated-orcid":false,"given":"Francesco Antonio","family":"Mallus","sequence":"first","affiliation":[{"name":"Department of Psychiatry and Psychotherapy, University Hospital T\u00fcbingen, T\u00fcbingen, Germany"},{"name":"Graduate Training Center of Neuroscience, International Max-Planck Research School, T\u00fcbingen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanwu","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Psychiatry and Psychotherapy, University Hospital T\u00fcbingen, T\u00fcbingen, Germany"},{"name":"Max-Planck Institute for Intelligent Systems, T\u00fcbingen, Germany"},{"name":"German Center for Mental Health (DZPG), partner site T\u00fcbingen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard","family":"Dinga","sequence":"additional","affiliation":[{"name":"Department of Neurology, Jena University Hospital, Jena, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mostafa Seyed","family":"Kia","sequence":"additional","affiliation":[{"name":"Center of Cognitive Science and Artificial Intelligence, Tilburg University, Tilburg, The Netherlands"},{"name":"Donders Institute for Cognition, Brain and Behavior, Radboud University, Nijmegen, The Netherlands"},{"name":"Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center, Utrecht, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tijl","family":"Grootswagers","sequence":"additional","affiliation":[{"name":"The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abele","family":"Michela","sequence":"additional","affiliation":[{"name":"CIBM Center for Biomedical Imaging, University of Geneva, Geneva, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tomas","family":"Ros","sequence":"additional","affiliation":[{"name":"CIBM Center for Biomedical Imaging, University of Geneva, Geneva, Switzerland"},{"name":"Department of Clinical Neuroscience, University of Geneva, Geneva, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Wolfers","sequence":"additional","affiliation":[{"name":"Department of Psychiatry and Psychotherapy, University Hospital T\u00fcbingen, T\u00fcbingen, Germany"},{"name":"German Center for Mental Health (DZPG), Jena-Magdeburg-Halle, Jena, Germany"},{"name":"Institute of Psychology, Friedrich Schiller University Jena, Jena, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"281","published-online":{"date-parts":[[2026,6,15]]},"reference":[{"issue":"3","key":"2026061515561152400_IMAG.a.1269-b1","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1093\/pch\/9.3.174","volume":"9","author":"A health professional\u2019s guide to using growth charts","year":"2004","journal-title":"Paediatrics & Child Health"},{"key":"2026061515561152400_IMAG.a.1269-b2","volume-title":"Symposium on the Analysis of Central Nervous System and Cardiovascular Data Using Computer Methods","author":"Adey","year":"1965"},{"issue":"4475","key":"2026061515561152400_IMAG.a.1269-b3","doi-asserted-by":"crossref","first-page":"1259","DOI":"10.1126\/science.7434027","article-title":"Developmental equations reflect brain dysfunctions","volume":"210","author":"Ahn","year":"1980","journal-title":"Science"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b4","first-page":"e12325","article-title":"Mayo normative studies: A conditional normative model for longitudinal change on the Auditory Verbal Learning Test and preliminary validation in preclinical Alzheimer\u2019s disease","volume":"14","author":"Alden","year":"2022","journal-title":"Alzheimer\u2019s & Dementia: Diagnosis, Assessment & Disease Monitoring"},{"key":"2026061515561152400_IMAG.a.1269-b5","doi-asserted-by":"crossref","first-page":"128","DOI":"10.3389\/fphys.2010.00128","article-title":"Fractal complexity in spontaneous EEG metastable-state transitions: New vistas on integrated neural dynamics","volume":"1","author":"Allegrini","year":"2010","journal-title":"Frontiers in Physiology"},{"key":"2026061515561152400_IMAG.a.1269-b6","doi-asserted-by":"crossref","first-page":"570583","DOI":"10.3389\/fncir.2020.570583","article-title":"The dynamics of functional brain networks associated with depressive symptoms in a nonclinical sample","volume":"14","author":"Alonso Mart\u00ednez","year":"2020","journal-title":"Frontiers in Neural Circuits"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b7","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1016\/0013-4694(87)90119-2","article-title":"EEG developmental equations confirmed for Cuban schoolchildren","volume":"67","author":"Alvarez","year":"1987","journal-title":"Electroencephalography and Clinical Neurophysiology"},{"key":"2026061515561152400_IMAG.a.1269-b8","article-title":"Normative modelling in neuroimaging: A practical guide for researchers (version 2)","author":"Alyas","year":"2025","journal-title":"arXiv"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b9","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/0013-4694(89)90015-1","article-title":"On the structure of EEG development","volume":"73","author":"Amador","year":"1989","journal-title":"Electroencephalography and Clinical Neurophysiology"},{"key":"2026061515561152400_IMAG.a.1269-b10","doi-asserted-by":"crossref","unstructured":"American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Association. https:\/\/doi.org\/10.1176\/appi.books.9780890425596","DOI":"10.1176\/appi.books.9780890425596"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b11","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1016\/j.schres.2013.12.008","article-title":"Resting-state connectivity in the prodromal phase of schizophrenia: Insights from EEG microstates","volume":"152","author":"Andreou","year":"2014","journal-title":"Schizophrenia Research"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b12","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1080\/10874208.2011.623088","article-title":"Neurofeedback and QEEG: The Space-Race \u2026","volume":"15","author":"Arns","year":"2011","journal-title":"Journal of Neurotherapy"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b13","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1214\/10-AOS823","article-title":"Regression on manifolds: Estimation of the exterior derivative","volume":"39","author":"Aswani","year":"2011","journal-title":"The Annals of Statistics"},{"key":"2026061515561152400_IMAG.a.1269-b14","doi-asserted-by":"crossref","first-page":"470","DOI":"10.1016\/j.bbi.2023.11.005","article-title":"Machine learning and artificial intelligence in neuroscience: A primer for researchers","volume":"115","author":"Badrulhisham","year":"2024","journal-title":"Brain, Behavior, and Immunity"},{"key":"2026061515561152400_IMAG.a.1269-b15","doi-asserted-by":"crossref","first-page":"101134","DOI":"10.1016\/j.dcn.2022.101134","article-title":"Spatiotemporal dynamics of EEG microstates in four- to eight-year-old children: Age- and sex-related effects","volume":"57","author":"Bagdasarov","year":"2022","journal-title":"Developmental Cognitive Neuroscience"},{"issue":"3","key":"2026061515561152400_IMAG.a.1269-b16","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1038\/nn.4504","article-title":"Magnetoencephalography for brain electrophysiology and imaging","volume":"20","author":"Baillet","year":"2017","journal-title":"Nature Neuroscience"},{"key":"2026061515561152400_IMAG.a.1269-b17","doi-asserted-by":"crossref","first-page":"e01867","DOI":"10.7554\/eLife.01867","article-title":"Fast transient networks in spontaneous human brain activity","volume":"3","author":"Baker","year":"2014","journal-title":"eLife"},{"key":"2026061515561152400_IMAG.a.1269-b18","unstructured":"Banville, H., Benchetrit, Y., d\u2019Ascoli, S., Rapin, J., & King, J.-R. (2025). Scaling laws for decoding images from brain activity (Version 2). arXiv. https:\/\/doi.org\/10.48550\/ARXIV.2501.15322"},{"key":"2026061515561152400_IMAG.a.1269-b19","doi-asserted-by":"crossref","first-page":"1336438","DOI":"10.3389\/fnbot.2024.1336438","article-title":"Metastability indexes global changes in the dynamic working point of the brain following brain stimulation","volume":"18","author":"Bapat","year":"2024","journal-title":"Frontiers in Neurorobotics"},{"key":"2026061515561152400_IMAG.a.1269-b20","doi-asserted-by":"crossref","first-page":"119699","DOI":"10.1016\/j.neuroimage.2022.119699","article-title":"Accommodating site variation in neuroimaging data using normative and hierarchical Bayesian models","volume":"264","author":"Bayer","year":"2022","journal-title":"NeuroImage"},{"key":"2026061515561152400_IMAG.a.1269-b21","article-title":"A machine learning-based approach for estimating and testing associations with multivariate outcomes (arXiv:1803.04877)","author":"Benkeser","year":"2018","journal-title":"arXiv"},{"key":"2026061515561152400_IMAG.a.1269-b22","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.neurobiolaging.2019.10.004","article-title":"EEG spectral power abnormalities and their relationship with cognitive dysfunction in patients with Alzheimer\u2019s disease and type 2 diabetes","volume":"85","author":"Benwell","year":"2020","journal-title":"Neurobiology of Aging"},{"issue":"6","key":"2026061515561152400_IMAG.a.1269-b23","doi-asserted-by":"crossref","first-page":"1949","DOI":"10.1093\/brain\/awab480","article-title":"Normative intracranial EEG maps epileptogenic tissues in focal epilepsy","volume":"145","author":"Bernabei","year":"2022","journal-title":"Brain"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b24","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1093\/schbul\/sbae107","article-title":"A 10-year longitudinal study of brain cortical thickness in people with first-episode psychosis using normative models","volume":"51","author":"Berthet","year":"2024","journal-title":"Schizophrenia Bulletin"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b25","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1038\/s42003-020-01212-9","article-title":"A normative modelling approach reveals age-atypical cortical thickness in a subgroup of males with autism spectrum disorder","volume":"3","author":"Bethlehem","year":"2020","journal-title":"Communications Biology"},{"issue":"7906","key":"2026061515561152400_IMAG.a.1269-b26","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1038\/s41586-022-04554-y","article-title":"Brain charts for the human lifespan","volume":"604","author":"Bethlehem","year":"2022","journal-title":"Nature"},{"key":"2026061515561152400_IMAG.a.1269-b27","doi-asserted-by":"crossref","first-page":"802764","DOI":"10.3389\/fnhum.2022.802764","article-title":"The acceptability, feasibility, and utility of portable electroencephalography to study resting-state neurophysiology in rural communities","volume":"16","author":"Bhavnani","year":"2022","journal-title":"Frontiers in Human Neuroscience"},{"issue":"3","key":"2026061515561152400_IMAG.a.1269-b28","doi-asserted-by":"crossref","first-page":"R80","DOI":"10.1016\/j.cub.2018.11.052","article-title":"Electroencephalography","volume":"29","author":"Biasiucci","year":"2019","journal-title":"Current Biology"},{"key":"2026061515561152400_IMAG.a.1269-b29","doi-asserted-by":"crossref","first-page":"16","DOI":"10.3389\/fninf.2015.00016","article-title":"The PREP pipeline: Standardized preprocessing for large-scale EEG analysis","volume":"9","author":"Bigdely-Shamlo","year":"2015","journal-title":"Frontiers in Neuroinformatics"},{"issue":"11","key":"2026061515561152400_IMAG.a.1269-b30","doi-asserted-by":"crossref","first-page":"1308","DOI":"10.1136\/jnnp.57.11.1308","article-title":"Electroencephalography","volume":"57","author":"Binnie","year":"1994","journal-title":"Journal of Neurology, Neurosurgery & Psychiatry"},{"key":"2026061515561152400_IMAG.a.1269-b31","doi-asserted-by":"crossref","first-page":"555119","DOI":"10.3389\/fnins.2020.555119","article-title":"Resting state healthy EEG: The first wave of the Cuban Normative Database","volume":"14","author":"Bosch-Bayard","year":"2020","journal-title":"Frontiers in Neuroscience"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b32","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1177\/155005940103200203","article-title":"3D statistical parametric mapping of EEG source spectra by Means of Variable Resolution Electromagnetic Tomography (VARETA)","volume":"32","author":"Bosch-Bayard","year":"2001","journal-title":"Clinical Electroencephalography"},{"key":"2026061515561152400_IMAG.a.1269-b33","doi-asserted-by":"crossref","first-page":"119864","DOI":"10.1016\/j.neuroimage.2023.119864","article-title":"Normative models for neuroimaging markers: Impact of model selection, sample size and evaluation criteria","volume":"268","author":"Bozek","year":"2023","journal-title":"NeuroImage"},{"key":"2026061515561152400_IMAG.a.1269-b34","doi-asserted-by":"crossref","first-page":"117245","DOI":"10.1016\/j.neuroimage.2020.117245","article-title":"Age-related trends in neuromagnetic transient beta burst characteristics during a sensorimotor task and rest in the Cam-CAN open-access dataset","volume":"222","author":"Brady","year":"2020","journal-title":"NeuroImage"},{"key":"2026061515561152400_IMAG.a.1269-b35","unstructured":"Brenner, M., Weber, E., Koppe, G., & Durstewitz, D. (2024, October 4). Learning Interpretable Hierarchical Dynamical Systems Models from Time Series Data. The Thirteenth International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=Vp2OAxMs2s"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b36","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1038\/s41398-024-03047-y","article-title":"Applications of OPM-MEG for translational neuroscience: A perspective","volume":"14","author":"Brickwedde","year":"2024","journal-title":"Translational Psychiatry"},{"key":"2026061515561152400_IMAG.a.1269-b37","doi-asserted-by":"crossref","first-page":"1222","DOI":"10.3389\/fnins.2019.01222","article-title":"An age-adjusted EEG source classifier accurately detects school-aged Barbadian children that had protein energy malnutrition in the first year of life","volume":"13","author":"Bringas Vega","year":"2019","journal-title":"Frontiers in Neuroscience"},{"key":"2026061515561152400_IMAG.a.1269-b38","doi-asserted-by":"crossref","first-page":"119458","DOI":"10.1016\/j.neuroimage.2022.119458","article-title":"Neuroimaging and global health","volume":"260","author":"Bringas-Vega","year":"2022","journal-title":"NeuroImage"},{"issue":"8","key":"2026061515561152400_IMAG.a.1269-b39","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1016\/j.tins.2022.05.008","article-title":"Magnetoencephalography with optically pumped magnetometers (OPM-MEG): The next generation of functional neuroimaging","volume":"45","author":"Brookes","year":"2022","journal-title":"Trends in Neurosciences"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b40","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1111\/j.1752-8062.2011.00394.x","article-title":"Patient-oriented research in the era of personalized medicine","volume":"5","author":"Brown","year":"2012","journal-title":"Clinical and Translational Science"},{"issue":"6","key":"2026061515561152400_IMAG.a.1269-b41","doi-asserted-by":"crossref","first-page":"729","DOI":"10.1080\/09515080600923271","article-title":"What is a brain state?","volume":"19","author":"Brown","year":"2006","journal-title":"Philosophical Psychology"},{"key":"2026061515561152400_IMAG.a.1269-b42","volume-title":"Introduction to quantitative EEG and neurofeedback: Advanced theory and applications","author":"Budzynski","year":"2009","edition":"2nd"},{"issue":"5679","key":"2026061515561152400_IMAG.a.1269-b43","doi-asserted-by":"crossref","first-page":"1926","DOI":"10.1126\/science.1099745","article-title":"Neuronal oscillations in cortical networks","volume":"304","author":"Buzs\u00e1ki","year":"2004","journal-title":"Science"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b44","doi-asserted-by":"crossref","first-page":"204","DOI":"10.1186\/s12883-014-0204-1","article-title":"The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) study protocol: A cross-sectional, lifespan, multidisciplinary examination of healthy cognitive ageing","volume":"14","author":"Cam-CAN","year":"2014","journal-title":"BMC Neurology"},{"key":"2026061515561152400_IMAG.a.1269-b45","first-page":"749","article-title":"Novelty processing in the auditory system: Detection, adaptation or expectation?","volume":"2","author":"Carbajal","year":"2020","journal-title":"The Senses: A Comprehensive Reference"},{"issue":"9","key":"2026061515561152400_IMAG.a.1269-b46","doi-asserted-by":"crossref","first-page":"3898","DOI":"10.1038\/s41380-022-01646-z","article-title":"Case-control study of neuropsychiatric symptoms in electronic health records following COVID-19 hospitalization in 2 academic health systems","volume":"27","author":"Castro","year":"2022","journal-title":"Molecular Psychiatry"},{"key":"2026061515561152400_IMAG.a.1269-b47","doi-asserted-by":"crossref","first-page":"114040","DOI":"10.1016\/j.measurement.2023.114040","article-title":"EEG complexity-based algorithm using Multiscale Fuzzy Entropy: Towards a detection of Alzheimer\u2019s disease","volume":"225","author":"Cataldo","year":"2024","journal-title":"Measurement"},{"key":"2026061515561152400_IMAG.a.1269-b48","unstructured":"Cattaneo, M. D., Jansson, M., & Newey, W. K. (2015). Inference in linear regression models with many covariates and heteroskedasticity (Version 2). arXiv. https:\/\/doi.org\/10.48550\/ARXIV.1507.02493"},{"key":"2026061515561152400_IMAG.a.1269-b49","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1007\/978-3-031-76081-5_5","article-title":"Machine learning with brain data: Feature engineering and analysis methods","volume-title":"Expanding senses using neurotechnology","author":"Chaudhary","year":"2025"},{"issue":"8","key":"2026061515561152400_IMAG.a.1269-b50","doi-asserted-by":"crossref","first-page":"1454","DOI":"10.1038\/s41592-024-02359-7","article-title":"Applying interpretable machine learning in computational biology\u2014Pitfalls, recommendations and opportunities for new developments","volume":"21","author":"Chen","year":"2024","journal-title":"Nature Methods"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b51","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1177\/1550059420962343","article-title":"Quantitative EEG in childhood attention deficit hyperactivity disorder and learning disabilities","volume":"52","author":"Chiarenza","year":"2021","journal-title":"Clinical EEG and Neuroscience"},{"issue":"6","key":"2026061515561152400_IMAG.a.1269-b52","doi-asserted-by":"crossref","first-page":"785","DOI":"10.1007\/s10548-015-0437-3","article-title":"MEG-EEG information fusion and electromagnetic source imaging: From theory to clinical application in epilepsy","volume":"28","author":"Chowdhury","year":"2015","journal-title":"Brain Topogr"},{"issue":"7","key":"2026061515561152400_IMAG.a.1269-b53","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1016\/j.biopsych.2025.07.021","article-title":"Lifespan normative models of white matter fractional anisotropy: Applications to early psychosis","volume":"99","author":"Cirstian","year":"2026","journal-title":"Biological Psychiatry"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b54","doi-asserted-by":"crossref","first-page":"460","DOI":"10.1176\/jnp.2006.18.4.460","article-title":"The value of quantitative electroencephalography in clinical psychiatry: A report by the committee on research of the american neuropsychiatric association","volume":"18","author":"Coburn","year":"2006","journal-title":"The Journal of Neuropsychiatry and Clinical Neurosciences"},{"issue":"4022","key":"2026061515561152400_IMAG.a.1269-b55","doi-asserted-by":"crossref","first-page":"664","DOI":"10.1126\/science.175.4022.664","article-title":"Magnetoencephalography: Detection of the brain\u2019s electrical activity with a superconducting magnetometer","volume":"175","author":"Cohen","year":"1972","journal-title":"Science"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b56","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/0013-4694(83)90005-6","article-title":"Demonstration of useful differences between magnetoencephalogram and electroencephalogram","volume":"56","author":"Cohen","year":"1983","journal-title":"Electroencephalography and Clinical Neurophysiology"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b57","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/S1570-677X(02)00033-3","article-title":"The secular trend in human physical growth: A biological view","volume":"1","author":"Cole","year":"2003","journal-title":"Economics & Human Biology"},{"issue":"5","key":"2026061515561152400_IMAG.a.1269-b58","doi-asserted-by":"crossref","first-page":"382","DOI":"10.3109\/03014460.2012.694475","article-title":"The development of growth references and growth charts","volume":"39","author":"Cole","year":"2012","journal-title":"Annals of Human Biology"},{"key":"2026061515561152400_IMAG.a.1269-b59","volume-title":"EEG Technology","author":"Cooper","year":"2014"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b61","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1016\/j.ijforecast.2003.09.002","article-title":"Flexible regression models and relative forecast performance","volume":"20","author":"Dahl","year":"2004","journal-title":"International Journal of Forecasting"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b62","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.ijpsycho.2013.04.018","article-title":"Prestimulus alpha and beta determinants of ERP responses in the Go\/NoGo task","volume":"89","author":"De Blasio","year":"2013","journal-title":"International Journal of Psychophysiology"},{"key":"2026061515561152400_IMAG.a.1269-b63","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1162\/imag_a_00132","article-title":"Non-Gaussian normative modelling with hierarchical Bayesian regression","volume":"2","author":"De Boer","year":"2024","journal-title":"Imaging Neuroscience"},{"key":"2026061515561152400_IMAG.a.1269-b64","doi-asserted-by":"crossref","unstructured":"Deco, G., Kringelbach, M. L., Jirsa, V. K., & Ritter, P. (2017). The dynamics of resting fluctuations in the brain: Metastability and its dynamical cortical core. Scientific Reports, 7(1), 3095. https:\/\/www.nature.com\/articles\/s41598-017-03073-5","DOI":"10.1038\/s41598-017-03073-5"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b65","doi-asserted-by":"crossref","first-page":"2372","DOI":"10.1038\/s41598-023-27528-0","article-title":"EEG is better left alone","volume":"13","author":"Delorme","year":"2023","journal-title":"Scientific Reports"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b66","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.jneumeth.2003.10.009","article-title":"EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis","volume":"134","author":"Delorme","year":"2004","journal-title":"Journal of Neuroscience Methods"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b68","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1590\/S0004-282X2004000100008","article-title":"Quantitative electroencephalography (qEEG) to discriminate primary degenerative dementia from major depressive disorder (depression)","volume":"62","author":"Deslandes","year":"2004","journal-title":"Arquivos de Neuro-Psiquiatria"},{"issue":"3","key":"2026061515561152400_IMAG.a.1269-b69","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1542\/peds.96.3.497","article-title":"Growth of breast-fed infants deviates from current reference data: A pooled analysis of US, Canadian, and European Data Sets","volume":"96","author":"Dewey","year":"1995","journal-title":"Pediatrics"},{"key":"2026061515561152400_IMAG.a.1269-b70","doi-asserted-by":"crossref","first-page":"101425","DOI":"10.1016\/j.dcn.2024.101425","article-title":"Multi-site EEG studies in early infancy: Methods to enhance data quality","volume":"69","author":"Dickinson","year":"2024","journal-title":"Developmental Cognitive Neuroscience"},{"key":"2026061515561152400_IMAG.a.1269-b72","article-title":"Normative modeling of neuroimaging data using generalized additive models of location scale and shape","author":"Dinga","year":"2021","journal-title":"bioRxiv"},{"key":"2026061515561152400_IMAG.a.1269-b73","doi-asserted-by":"crossref","first-page":"111546","DOI":"10.1016\/j.brainresbull.2025.111546","article-title":"A normative model\u2013based assessment framework for large-scale, multi-site EEG data","volume":"231","author":"Dong","year":"2025","journal-title":"Brain Research Bulletin"},{"key":"2026061515561152400_IMAG.a.1269-b74","doi-asserted-by":"crossref","unstructured":"Dong, Z., Wu, Y., Xiao, Y., Chong, J. S. X., Jin, Y., & Zhou, J. H. (2023). Beyond the snapshot: Brain tokenized graph transformer for longitudinal brain functional connectome embedding (arXiv:2307.00858). arXiv. http:\/\/arxiv.org\/abs\/2307.00858","DOI":"10.1007\/978-3-031-43904-9_34"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b75","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1080\/21622965.2023.2288865","article-title":"Quantitative electroencephalography in children with attention deficit hyperactivity disorder and healthy children: Behavioral and age correlates","volume":"14","author":"Duric","year":"2025","journal-title":"Applied Neuropsychology: Child"},{"issue":"11","key":"2026061515561152400_IMAG.a.1269-b76","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1038\/s41583-023-00740-7","article-title":"Reconstructing computational system dynamics from neural data with recurrent neural networks","volume":"24","author":"Durstewitz","year":"2023","journal-title":"Nature Reviews Neuroscience"},{"issue":"16","key":"2026061515561152400_IMAG.a.1269-b77","doi-asserted-by":"crossref","first-page":"8983","DOI":"10.3390\/app15168983","article-title":"Multilayer neural-network-based EEG analysis for the detection of epilepsy, migraine, and schizophrenia","volume":"15","author":"Dursun","year":"2025","journal-title":"Applied Sciences"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b78","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1038\/s41398-025-03441-0","article-title":"Beyond homogeneity: Charting the landscape of heterogeneity in neurodevelopmental and psychiatric electroencephalography","volume":"15","author":"Ebadi","year":"2025","journal-title":"Translational Psychiatry"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b79","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1097\/WNP.0000000000000547","article-title":"Book review: EEG in clinical practice","volume":"36","author":"Edwards","year":"2019","journal-title":"Journal of Clinical Neurophysiology"},{"issue":"Pt B","key":"2026061515561152400_IMAG.a.1269-b80","doi-asserted-by":"crossref","first-page":"1065","DOI":"10.1016\/j.neuroimage.2015.10.079","article-title":"Sharing the wealth: Neuroimaging data repositories","volume":"124","author":"Eickhoff","year":"2016","journal-title":"NeuroImage"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b81","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1097\/WCO.0b013e32835ee5b8","article-title":"Connectomics and epilepsy","volume":"26","author":"Engel","year":"2013","journal-title":"Current Opinion in Neurology"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b82","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1001\/jamapsychiatry.2023.3850","article-title":"Normative modeling of brain morphometry in clinical high risk for psychosis","volume":"81","author":"ENIGMA Clinical High Risk for Psychosis Working Group","year":"2024","journal-title":"JAMA Psychiatry"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b83","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1186\/s12874-019-0779-8","article-title":"Evaluating selection bias in a population-based cohort study with low baseline participation: The LIFE-Adult-Study","volume":"19","author":"Enzenbach","year":"2019","journal-title":"BMC Medical Research Methodology"},{"issue":"6","key":"2026061515561152400_IMAG.a.1269-b84","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1177\/1550059420905724","article-title":"Entropy: A promising EEG biomarker dichotomizing subjects with opioid use disorder and healthy controls","volume":"51","author":"Erguzel","year":"2020","journal-title":"Clinical EEG and Neuroscience"},{"issue":"44","key":"2026061515561152400_IMAG.a.1269-b85","doi-asserted-by":"crossref","first-page":"17615","DOI":"10.1073\/pnas.1310134110","article-title":"What is a representative brain? Neuroscience meets population science","volume":"110","author":"Falk","year":"2013","journal-title":"Proceedings of the National Academy of Sciences of the United States of America"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b86","doi-asserted-by":"crossref","first-page":"22","DOI":"10.3390\/info8010022","article-title":"Information flow in the brain: Ordered sequences of metastable states","volume":"8","author":"Fingelkurts","year":"2017","journal-title":"Information"},{"key":"2026061515561152400_IMAG.a.1269-b87","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.neuroimage.2017.03.064","article-title":"Can brain state be manipulated to emphasize individual differences in functional connectivity?","volume":"160","author":"Finn","year":"2017","journal-title":"NeuroImage"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b88","doi-asserted-by":"crossref","first-page":"774","DOI":"10.1016\/j.neuroimage.2012.01.021","article-title":"FreeSurfer","volume":"62","author":"Fischl","year":"2012","journal-title":"NeuroImage"},{"key":"2026061515561152400_IMAG.a.1269-b89","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.neuroimage.2017.08.047","article-title":"Harmonization of multi-site diffusion tensor imaging data","volume":"161","author":"Fortin","year":"2017","journal-title":"NeuroImage"},{"issue":"10","key":"2026061515561152400_IMAG.a.1269-b90","doi-asserted-by":"crossref","first-page":"688","DOI":"10.1038\/s41583-024-00846-6","article-title":"Structure\u2013function coupling in macroscale human brain networks","volume":"25","author":"Fotiadis","year":"2024","journal-title":"Nature Reviews Neuroscience"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b91","doi-asserted-by":"crossref","first-page":"368","DOI":"10.1007\/s11682-016-9599-1","article-title":"Resting-state global functional connectivity as a biomarker of cognitive reserve in mild cognitive impairment","volume":"11","author":"Franzmeier","year":"2017","journal-title":"Brain Imaging and Behavior"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b92","doi-asserted-by":"crossref","first-page":"1130","DOI":"10.1093\/brain\/awy035","article-title":"Atlas of the normal intracranial electroencephalogram: Neurophysiological awake activity in different cortical areas","volume":"141","author":"Frauscher","year":"2018","journal-title":"Brain"},{"key":"2026061515561152400_IMAG.a.1269-b93","doi-asserted-by":"crossref","first-page":"118715","DOI":"10.1016\/j.neuroimage.2021.118715","article-title":"Warped Bayesian linear regression for normative modelling of big data","volume":"245","author":"Fraza","year":"2021","journal-title":"NeuroImage"},{"key":"2026061515561152400_IMAG.a.1269-b94","doi-asserted-by":"crossref","first-page":"106284","DOI":"10.1016\/j.neubiorev.2025.106284","article-title":"The promise of quantifying individual risk for brain disorders through normative modeling, a narrative review","volume":"176","author":"Fraza","year":"2025","journal-title":"Neuroscience & Biobehavioral Reviews"},{"key":"2026061515561152400_IMAG.a.1269-b95","doi-asserted-by":"crossref","unstructured":"Freeman, W. J., & Holmes, M. D. (2005). Metastability, instability, and state transition in neocortex. Neural Networks, 18, 497. https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0893608005001085","DOI":"10.1016\/j.neunet.2005.06.014"},{"key":"2026061515561152400_IMAG.a.1269-b96","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.jad.2014.10.010","article-title":"Depression is not a consistent syndrome: An investigation of unique symptom patterns in the STAR*D study","volume":"172","author":"Fried","year":"2015","journal-title":"Journal of Affective Disorders"},{"issue":"10","key":"2026061515561152400_IMAG.a.1269-b97","doi-asserted-by":"crossref","first-page":"2067","DOI":"10.1017\/S0033291713002900","article-title":"Depression is more than the sum score of its parts: Individual DSM symptoms have different risk factors","volume":"44","author":"Fried","year":"2014","journal-title":"Psychological Medicine"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b98","doi-asserted-by":"crossref","first-page":"1374","DOI":"10.1038\/s42003-022-04331-7","article-title":"Neural complexity is a common denominator of human consciousness across diverse regimes of cortical dynamics","volume":"5","author":"Frohlich","year":"2022","journal-title":"Communications Biology"},{"key":"2026061515561152400_IMAG.a.1269-b99","unstructured":"Frotscher, A., Kapoor, J., Wolfers, T., & Baumgartner, C. F. (2023). Unsupervised anomaly detection using aggregated normative diffusion (arXiv:2312.01904). arXiv. https:\/\/doi.org\/10.48550\/arXiv.2312.01904"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b100","doi-asserted-by":"crossref","first-page":"e26565","DOI":"10.1002\/hbm.26565","article-title":"Estimating cortical thickness trajectories in children across different scanners using transfer learning from normative models","volume":"45","author":"Gaiser","year":"2024","journal-title":"Human Brain Mapping"},{"issue":"7","key":"2026061515561152400_IMAG.a.1269-b101","doi-asserted-by":"crossref","first-page":"4180","DOI":"10.1007\/s00415-024-12340-1","article-title":"Functional connectivity changes in neurodegenerative biomarker-positive athletes with repeated concussions","volume":"271","author":"Garcia-Cordero","year":"2024","journal-title":"Journal of Neurology"},{"issue":"20","key":"2026061515561152400_IMAG.a.1269-b102","doi-asserted-by":"crossref","first-page":"23203","DOI":"10.1007\/s10489-023-04702-5","article-title":"Feature engineering of EEG applied to mental disorders: A systematic mapping study","volume":"53","author":"Garc\u00eda-Ponsoda","year":"2023","journal-title":"Applied Intelligence"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b103","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/0013-4694(88)90205-2","article-title":"Development of the EEG of school-age children and adolescents II. Topography","volume":"69","author":"Gasser","year":"1988","journal-title":"Electroencephalography and Clinical Neurophysiology"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b104","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/0013-4694(88)90204-0","article-title":"Development of the EEG of school-age children and adolescents. I. Analysis of band power","volume":"69","author":"Gasser","year":"1988","journal-title":"Electroencephalography and Clinical Neurophysiology"},{"issue":"3","key":"2026061515561152400_IMAG.a.1269-b105","doi-asserted-by":"crossref","first-page":"e211","DOI":"10.1016\/S2589-7500(23)00250-9","article-title":"Normative modelling of brain morphometry across the lifespan with CentileBrain: Algorithm benchmarking and model optimisation","volume":"6","author":"Ge","year":"2024","journal-title":"The Lancet Digital Health"},{"issue":"3","key":"2026061515561152400_IMAG.a.1269-b106","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1007\/s11229-024-04741-6","article-title":"Computational psychiatry and the evolving concept of a mental disorder","volume":"204","author":"Genin","year":"2024","journal-title":"Synthese"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b107","doi-asserted-by":"crossref","first-page":"160044","DOI":"10.1038\/sdata.2016.44","article-title":"The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments","volume":"3","author":"Gorgolewski","year":"2016","journal-title":"Scientific Data"},{"key":"2026061515561152400_IMAG.a.1269-b108","doi-asserted-by":"crossref","first-page":"446","DOI":"10.1016\/j.neuroimage.2013.10.027","article-title":"MNE software for processing MEG and EEG data","volume":"86","author":"Gramfort","year":"2014","journal-title":"NeuroImage"},{"key":"2026061515561152400_IMAG.a.1269-b109","doi-asserted-by":"crossref","first-page":"981657","DOI":"10.3389\/fnint.2022.981657","article-title":"A perspective on enhancing representative samples in developmental human neuroscience: Connecting science to society","volume":"16","author":"Green","year":"2022","journal-title":"Frontiers in Integrative Neuroscience"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b110","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1038\/s41597-021-01102-7","article-title":"Human EEG recordings for 1,854 concepts presented in rapid serial visual presentation streams","volume":"9","author":"Grootswagers","year":"2022","journal-title":"Scientific Data"},{"issue":"RR-9","key":"2026061515561152400_IMAG.a.1269-b111","first-page":"1","article-title":"Use of World Health Organization and CDC growth charts for children aged 0-59 months in the United States","volume":"59","author":"Grummer-Strawn","year":"2010","journal-title":"MMWR. Recommendations and Reports: Morbidity and Mortality Weekly Report. Recommendations and Reports"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b112","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1103\/RevModPhys.65.413","article-title":"Magnetoencephalography\u2014Theory, instrumentation, and applications to noninvasive studies of the working human brain","volume":"65","author":"H\u00e4m\u00e4l\u00e4inen","year":"1993","journal-title":"Reviews of Modern Physics"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b113","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1056\/NEJMp1006304","article-title":"The path to personalized medicine","volume":"363","author":"Hamburg","year":"2010","journal-title":"New England Journal of Medicine"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b114","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1016\/j.neuroimage.2011.11.074","article-title":"Magnetoencephalography: From SQUIDs to neuroscience","volume":"61","author":"Hari","year":"2012","journal-title":"NeuroImage"},{"issue":"6","key":"2026061515561152400_IMAG.a.1269-b115","doi-asserted-by":"crossref","first-page":"482","DOI":"10.1016\/0013-4694(90)90135-7","article-title":"Effect of sex, psychosocial disadvantages and biological risk factors on EEG maturation","volume":"75","author":"Harmony","year":"1990","journal-title":"Electroencephalography and Clinical Neurophysiology"},{"issue":"11","key":"2026061515561152400_IMAG.a.1269-b116","doi-asserted-by":"crossref","first-page":"1590","DOI":"10.1111\/psyp.12906","article-title":"Theta- and delta-band EEG network dynamics during a novelty oddball task","volume":"54","author":"Harper","year":"2017","journal-title":"Psychophysiology"},{"key":"2026061515561152400_IMAG.a.1269-b117","doi-asserted-by":"crossref","first-page":"e82580","DOI":"10.7554\/eLife.82580","article-title":"THINGS-data, a multimodal collection of large-scale datasets for investigating object representations in human brain and behavior","author":"Hebart","year":"2023","journal-title":"eLife 12"},{"issue":"5","key":"2026061515561152400_IMAG.a.1269-b118","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1590\/0004-282x-anp-2021-0083","article-title":"Magnetoencephalography in clinical practice","volume":"80","author":"Hegazy","year":"2022","journal-title":"Arquivos de Neuro-Psiquiatria"},{"issue":"3","key":"2026061515561152400_IMAG.a.1269-b119","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1177\/155005941104200303","article-title":"Multimodal quantitative neuroimaging databases and methods: The Cuban Human Brain Mapping Project","volume":"42","author":"Hernandez-Gonzalez","year":"2011","journal-title":"Clinical EEG and Neuroscience"},{"issue":"3","key":"2026061515561152400_IMAG.a.1269-b120","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1017\/S1092852915000929","article-title":"Comorbidity between neurological illness and psychiatric disorders","volume":"21","author":"Hesdorffer","year":"2016","journal-title":"CNS Spectrums"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b121","doi-asserted-by":"crossref","first-page":"e000396","DOI":"10.1136\/bmjmed-2022-000396","article-title":"Non-linear predictor outcome associations","volume":"2","author":"Ho","year":"2023","journal-title":"BMJ Medicine"},{"key":"2026061515561152400_IMAG.a.1269-b122","first-page":"2722","article-title":"Flow++: Improving flow-based generative models with variational dequantization and architecture design","volume-title":"International Conference on Machine Learning","author":"Ho","year":"2019"},{"key":"2026061515561152400_IMAG.a.1269-b123","first-page":"6840","article-title":"Denoising diffusion probabilistic models","volume":"33","author":"Ho","year":"2020","journal-title":"Advances in Neural Information Processing Systems"},{"key":"2026061515561152400_IMAG.a.1269-b124","unstructured":"Hu, S., Huang, X., Hu, Y., Xiang, X., Sheng, X., Zhou, D., & Valdes-Sosa, P. A. (2025). GANORM: Lifespan normative modeling of EEG network topology based on multinational cross-spectra (Version 1). arXiv. https:\/\/doi.org\/10.48550\/ARXIV.2506.02566"},{"key":"2026061515561152400_IMAG.a.1269-b125","doi-asserted-by":"crossref","first-page":"121122","DOI":"10.1016\/j.neuroimage.2025.121122","article-title":"How do the resting EEG preprocessing states affect the outcomes of postprocessing?","volume":"310","author":"Hu","year":"2025","journal-title":"NeuroImage"},{"issue":"7","key":"2026061515561152400_IMAG.a.1269-b126","doi-asserted-by":"crossref","first-page":"1737","DOI":"10.1088\/0031-9155\/46\/7\/301","article-title":"Simultaneous MEG and EEG source analysis","volume":"46","author":"Huizenga","year":"2001","journal-title":"Physics in Medicine and Biology"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b127","doi-asserted-by":"crossref","first-page":"8894","DOI":"10.1038\/s41598-019-45289-7","article-title":"EEG functional connectivity metrics wPLI and wSMI account for distinct types of brain functional interactions","volume":"9","author":"Imperatori","year":"2019","journal-title":"Scientific Reports"},{"key":"2026061515561152400_IMAG.a.1269-b128","unstructured":"Insel, T.\n           (2013). Tranforming diagnosis. PsychRights. https:\/\/psychrights.org\/2013\/130429NIMHTransformingDiagnosis.htm"},{"issue":"7","key":"2026061515561152400_IMAG.a.1269-b129","doi-asserted-by":"crossref","first-page":"748","DOI":"10.1176\/appi.ajp.2010.09091379","article-title":"Research domain criteria (RDoC): Toward a new classification framework for research on mental disorders","volume":"167","author":"Insel","year":"2010","journal-title":"American Journal of Psychiatry"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b130","doi-asserted-by":"crossref","first-page":"700","DOI":"10.1172\/JCI38832","article-title":"Disruptive insights in psychiatry: Transforming a clinical discipline","volume":"119","author":"Insel","year":"2009","journal-title":"Journal of Clinical Investigation"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b131","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1176\/appi.ajp.2014.14020138","article-title":"The NIMH Research Domain Criteria (RDoC) Project: Precision medicine for psychiatry","volume":"171","author":"Insel","year":"2014","journal-title":"American Journal of Psychiatry"},{"key":"2026061515561152400_IMAG.a.1269-b132","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1007\/978-3-030-32423-0_8","article-title":"Deep learning for automatic EEG feature extraction: An application in drivers\u2019 mental workload classification","volume-title":"Human mental workload: Models and applications","author":"Islam","year":"2019"},{"issue":"11","key":"2026061515561152400_IMAG.a.1269-b133","doi-asserted-by":"crossref","first-page":"e1011613","DOI":"10.1371\/journal.pcbi.1011613","article-title":"Using normative modeling and machine learning for detecting mild traumatic brain injury from magnetoencephalography data","volume":"19","author":"It\u00e4linna","year":"2023","journal-title":"PLoS Computational Biology"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b134","doi-asserted-by":"crossref","first-page":"597","DOI":"10.1017\/S0033291703001399","article-title":"Prevalence, co-morbidity and correlates of mental disorders in the general population: Results from the German Health Interview and Examination Survey (GHS)","volume":"34","author":"Jacobi","year":"2004","journal-title":"Psychological Medicine"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b135","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1016\/S0261-3794(99)00028-1","article-title":"Loess: A nonparametric, graphical tool for depicting relationships between variables","volume":"19","author":"Jacoby","year":"2000","journal-title":"Electoral Studies"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b136","first-page":"73","article-title":"Clinical applications of EEG as an excellent tool for event related potentials in psychiatric and neurotic disorders","volume":"14","author":"Jadhav","year":"2022","journal-title":"International Journal of Physiology, Pathophysiology and Pharmacology"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b137","doi-asserted-by":"crossref","first-page":"13442","DOI":"10.1038\/s41598-023-39700-7","article-title":"Normative brain mapping using scalp EEG and potential clinical application","volume":"13","author":"Janiukstyte","year":"2023","journal-title":"Scientific Reports"},{"issue":"6","key":"2026061515561152400_IMAG.a.1269-b138","doi-asserted-by":"crossref","first-page":"e801","DOI":"10.1002\/cpz1.801","article-title":"Introduction to the use of linear and nonlinear regression analysis in quantitative biological assays","volume":"3","author":"Jarantow","year":"2023","journal-title":"Current Protocols"},{"key":"2026061515561152400_IMAG.a.1269-b139","article-title":"Predicting subject traits from brain spectral signatures: An application to brain ageing","author":"Jarne","year":"2023","journal-title":"bioRxiv"},{"issue":"11","key":"2026061515561152400_IMAG.a.1269-b140","doi-asserted-by":"crossref","first-page":"982","DOI":"10.1016\/j.tics.2025.09.001","article-title":"Confronting the connectivity crisis in human M\/EEG research","volume":"29","author":"Jensen","year":"2025","journal-title":"Trends in Cognitive Sciences"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b141","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1097\/WCO.0000000000000181","article-title":"Electrophysiological biomarkers of diagnosis and outcome in neurodevelopmental disorders","volume":"28","author":"Jeste","year":"2015","journal-title":"Current Opinion in Neurology"},{"issue":"9","key":"2026061515561152400_IMAG.a.1269-b142","doi-asserted-by":"crossref","first-page":"2042","DOI":"10.1017\/S0033291724000138","article-title":"Age-atypical brain functional networks in autism spectrum disorder: A normative modeling approach","volume":"54","author":"Jiang","year":"2024","journal-title":"Psychological Medicine"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b143","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1177\/1535759720934852","article-title":"Intracranial EEG in the 21st century","volume":"20","author":"Jobst","year":"2020","journal-title":"Epilepsy Currents"},{"issue":"4475","key":"2026061515561152400_IMAG.a.1269-b144","doi-asserted-by":"crossref","first-page":"1255","DOI":"10.1126\/science.7434026","article-title":"Developmental equations for the electroencephalogram","volume":"210","author":"John","year":"1980","journal-title":"Science"},{"issue":"4297","key":"2026061515561152400_IMAG.a.1269-b145","doi-asserted-by":"crossref","first-page":"1393","DOI":"10.1126\/science.867036","article-title":"Neurometrics: Numerical taxonomy identifies different profiles of brain functions within groups of behaviorally similar people","volume":"196","author":"John","year":"1977","journal-title":"Science"},{"key":"2026061515561152400_IMAG.a.1269-b146","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1016\/S0079-6123(08)62700-4","article-title":"Chapter 28 Neurometric studies of aging and cognitive impairment","volume":"85","author":"John","year":"1991","journal-title":"Progress in Brain Research"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b147","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1093\/biostatistics\/kxj037","article-title":"Adjusting batch effects in microarray expression data using empirical Bayes methods","volume":"8","author":"Johnson","year":"2007","journal-title":"Biostatistics"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b148","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1300\/J184v10n04_05","article-title":"What is quantitative EEG?","volume":"10","author":"Kaiser","year":"2007","journal-title":"Journal of Neurotherapy"},{"key":"2026061515561152400_IMAG.a.1269-b149","doi-asserted-by":"crossref","first-page":"105998","DOI":"10.1016\/j.bandc.2023.105998","article-title":"Reliability and stability of oddball P300 amplitude in older adults: The role of stimulus sequence effects","volume":"169","author":"Kamp","year":"2023","journal-title":"Brain and Cognition"},{"key":"2026061515561152400_IMAG.a.1269-b150","article-title":"The neural basis of cognition","volume-title":"Principles of neural science","author":"Kandel","year":"2014","edition":"5th"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b151","doi-asserted-by":"crossref","first-page":"342","DOI":"10.1111\/cts.12178","article-title":"Big data and large sample size: A cautionary note on the potential for bias","volume":"7","author":"Kaplan","year":"2014","journal-title":"Clinical and Translational Science"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b152","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1177\/1550059419874945","article-title":"Standardization and personalized medicine using quantitative EEG in clinical settings","volume":"52","author":"Keizer","year":"2021","journal-title":"Clinical EEG and Neuroscience"},{"issue":"6","key":"2026061515561152400_IMAG.a.1269-b153","doi-asserted-by":"crossref","first-page":"593","DOI":"10.1001\/archpsyc.62.6.593","article-title":"Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication","volume":"62","author":"Kessler","year":"2005","journal-title":"Archives of General Psychiatry"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b154","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1002\/mpr.166","article-title":"The National Comorbidity Survey Replication (NCS-R): Background and aims","volume":"13","author":"Kessler","year":"2004","journal-title":"International Journal of Methods in Psychiatric Research"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b155","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1016\/j.bbe.2020.02.002","article-title":"A comparative analysis of signal processing and classification methods for different applications based on EEG signals","volume":"40","author":"Khosla","year":"2020","journal-title":"Biocybernetics and Biomedical Engineering"},{"key":"2026061515561152400_IMAG.a.1269-b156","doi-asserted-by":"crossref","first-page":"696492","DOI":"10.3389\/fneur.2021.696492","article-title":"Intracranial EEG biomarkers for seizure lateralization in rapidly-bisynchronous epilepsy after laser corpus callosotomy","volume":"12","author":"Khuvis","year":"2021","journal-title":"Frontiers in Neurology"},{"key":"2026061515561152400_IMAG.a.1269-b157","doi-asserted-by":"crossref","first-page":"699","DOI":"10.1007\/978-3-030-59728-3_68","article-title":"Hierarchical Bayesian regression for multi-site normative modeling of neuroimaging data","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2020","author":"Kia","year":"2020"},{"issue":"12","key":"2026061515561152400_IMAG.a.1269-b158","doi-asserted-by":"crossref","first-page":"e0278776","DOI":"10.1371\/journal.pone.0278776","article-title":"Closing the life-cycle of normative modeling using federated hierarchical Bayesian regression","volume":"17","author":"Kia","year":"2022","journal-title":"PLoS One"},{"key":"2026061515561152400_IMAG.a.1269-b159","article-title":"Federated multi-site normative modeling using hierarchical Bayesian regression","author":"Kia","year":"2021","journal-title":"bioRxiv"},{"key":"2026061515561152400_IMAG.a.1269-b160","doi-asserted-by":"crossref","unstructured":"Kia, S. M., & Marquand, A. (2018a). Normative modeling of neuroimaging data using scalable multi-task Gaussian processes (version 2). arXiv. https:\/\/doi.org\/10.48550\/ARXIV.1806.01047","DOI":"10.1007\/978-3-030-00931-1_15"},{"key":"2026061515561152400_IMAG.a.1269-b161","unstructured":"Kia, S. M., & Marquand, A. F. (2018b). Neural processes mixed-effect models for deep normative modeling of clinical neuroimaging data (version 2). arXiv. https:\/\/doi.org\/10.48550\/ARXIV.1812.04998"},{"key":"2026061515561152400_IMAG.a.1269-b162","doi-asserted-by":"crossref","unstructured":"Kim, M., Leonardsen, E., Rutherford, S., Selb\u00e6k, G., Persson, K., Steen, N. E., Smeland, O. B., Ueland, T., Richard, G., Beckmann, C. F., Marquand, A. F., Alzheimer\u2019s Disease Neuroimaging Initiative (ADNI), Andreassen, O. A., Westlye, L. T., Wolfers, T., & Moberget, T. (2023). Mapping cerebellar anatomical heterogeneity in mental and neurological illnesses. bioRxiv. https:\/\/doi.org\/10.1101\/2023.11.18.567647","DOI":"10.1101\/2023.11.18.567647"},{"issue":"5","key":"2026061515561152400_IMAG.a.1269-b163","doi-asserted-by":"crossref","first-page":"100541","DOI":"10.1016\/j.bpsgos.2025.100541","article-title":"Predicting mental and neurological illnesses based on cerebellar normative features","volume":"5","author":"Kim","year":"2025","journal-title":"Biological Psychiatry Global Open Science"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b164","doi-asserted-by":"crossref","DOI":"10.1523\/ENEURO.0066-22.2022","article-title":"Navigating the statistical minefield of model selection and clustering in neuroscience","volume":"9","author":"Kir\u00e1ly","year":"2022","journal-title":"Eneuro"},{"key":"2026061515561152400_IMAG.a.1269-b165","first-page":"11283","article-title":"Generalizing to new physical systems via context-informed dynamics model","volume-title":"International Conference on Machine Learning","author":"Kirchmeyer","year":"2022"},{"key":"2026061515561152400_IMAG.a.1269-b166","doi-asserted-by":"crossref","first-page":"766781","DOI":"10.3389\/fnins.2021.766781","article-title":"Quantitative electroencephalogram standardization: A sex- and age-differentiated normative database","volume":"15","author":"Ko","year":"2021","journal-title":"Frontiers in Neuroscience"},{"issue":"3","key":"2026061515561152400_IMAG.a.1269-b167","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1080\/10874208.2012.705769","article-title":"Cognitive enhancement using 19-electrode Z-score neurofeedback","volume":"16","author":"Koberda","year":"2012","journal-title":"Journal of Neurotherapy"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b168","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1006\/nimg.2002.1070","article-title":"Millisecond by millisecond, year by year: Normative EEG microstates and developmental stages","volume":"16","author":"Koenig","year":"2002","journal-title":"NeuroImage"},{"issue":"6","key":"2026061515561152400_IMAG.a.1269-b169","doi-asserted-by":"crossref","first-page":"e70203","DOI":"10.1002\/hbm.70203","article-title":"Cross-sectional brain age assessments are limited in predicting future brain change","volume":"46","author":"Korbmacher","year":"2025","journal-title":"Human Brain Mapping"},{"issue":"9","key":"2026061515561152400_IMAG.a.1269-b170","doi-asserted-by":"crossref","first-page":"1148","DOI":"10.1038\/s41593-018-0210-5","article-title":"Cognitive computational neuroscience","volume":"21","author":"Kriegeskorte","year":"2018","journal-title":"Nature Neuroscience"},{"issue":"10","key":"2026061515561152400_IMAG.a.1269-b171","doi-asserted-by":"crossref","first-page":"108128","DOI":"10.1016\/j.celrep.2020.108128","article-title":"Brain states and transitions: Insights from computational neuroscience","volume":"32","author":"Kringelbach","year":"2020","journal-title":"Cell Reports"},{"key":"2026061515561152400_IMAG.a.1269-b172","doi-asserted-by":"crossref","DOI":"10.1117\/12.2654369","article-title":"Normative modeling using multimodal variational autoencoders to identify abnormal brain volume deviations in Alzheimer\u2019s disease","volume-title":"Proceedings of SPIE\u2013the International Society for Optical Engineering","author":"Kumar","year":"2023"},{"key":"2026061515561152400_IMAG.a.1269-b173","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1002\/9781118432501.ch26","article-title":"Potentials and paradigms: Event-related brain potentials and neuropsychology","volume-title":"The handbook of the neuropsychology of language","author":"Kutas","year":"2012","edition":"1st"},{"issue":"5","key":"2026061515561152400_IMAG.a.1269-b174","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1080\/03014467800003071","article-title":"Analysis of the adolescent growth spurt using smoothing spline functions","volume":"5","author":"Largo","year":"1978","journal-title":"Annals of Human Biology"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b175","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1038\/s42003-024-06391-3","article-title":"Normative modelling of molecular-based functional circuits captures clinical heterogeneity transdiagnostically in psychiatric patients","volume":"7","author":"Lawn","year":"2024","journal-title":"Communications Biology"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b176","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1186\/s13195-025-01753-3","article-title":"Deep normative modelling reveals insights into early-stage Alzheimer\u2019s disease using multi-modal neuroimaging data","volume":"17","author":"Lawry Aguila","year":"2025","journal-title":"Alzheimer\u2019s Research & Therapy"},{"key":"2026061515561152400_IMAG.a.1269-b177","doi-asserted-by":"crossref","first-page":"1540040","DOI":"10.3389\/fnagi.2025.1540040","article-title":"Normative characterization of age-related periodic and aperiodic activity in resting-state real-world clinical EEG recordings","volume":"17","author":"Leroy","year":"2025","journal-title":"Frontiers in Aging Neuroscience"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b178","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1146\/annurev-clinpsy-032813-153653","article-title":"Emotional and behavioral symptoms in neurodegenerative disease: A model for studying the neural bases of psychopathology","volume":"10","author":"Levenson","year":"2014","journal-title":"Annual Review of Clinical Psychology"},{"key":"2026061515561152400_IMAG.a.1269-b179","doi-asserted-by":"crossref","first-page":"1211273","DOI":"10.3389\/fncel.2023.1211273","article-title":"Editorial: Understanding the heterogeneity and spatial brain environment of neurodegenerative diseases through conventional and future methods","volume":"17","author":"Li","year":"2023","journal-title":"Frontiers in Cellular Neuroscience"},{"issue":"3","key":"2026061515561152400_IMAG.a.1269-b180","doi-asserted-by":"crossref","first-page":"384","DOI":"10.3390\/brainsci13030384","article-title":"Machine learning techniques reveal aberrated multidimensional EEG characteristics in patients with depression","volume":"13","author":"Li","year":"2023","journal-title":"Brain Sciences"},{"key":"2026061515561152400_IMAG.a.1269-b181","doi-asserted-by":"crossref","first-page":"119190","DOI":"10.1016\/j.neuroimage.2022.119190","article-title":"Harmonized-Multinational qEEG norms (HarMNqEEG)","volume":"256","author":"Li","year":"2022","journal-title":"NeuroImage"},{"key":"2026061515561152400_IMAG.a.1269-b182","first-page":"1","article-title":"Behavioral and psychological symptoms in Alzheimer\u2019s Disease","volume":"2014","author":"Li","year":"2014","journal-title":"BioMed Research International"},{"key":"2026061515561152400_IMAG.a.1269-b183","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.bodyim.2022.01.013","article-title":"Examining the utility of nonlinear machine learning approaches versus linear regression for predicting body image outcomes: The U.S. Body Project I","volume":"41","author":"Liang","year":"2022","journal-title":"Body Image"},{"issue":"6","key":"2026061515561152400_IMAG.a.1269-b184","doi-asserted-by":"crossref","first-page":"1845","DOI":"10.1002\/hbm.20785","article-title":"Comparing MEG and fMRI views to naming actions and objects","volume":"30","author":"Liljestr\u00f6m","year":"2009","journal-title":"Human Brain Mapping"},{"key":"2026061515561152400_IMAG.a.1269-b185","unstructured":"Lipman, Y., Chen, R. T. Q., Ben-Hamu, H., Nickel, M., & Le, M. (2023). Flow matching for generative modeling (arXiv:2210.02747). arXiv. https:\/\/doi.org\/10.48550\/arXiv.2210.02747"},{"key":"2026061515561152400_IMAG.a.1269-b186","doi-asserted-by":"crossref","unstructured":"Little, B., Alyas, N., Surtees, A., Winston, G. P., Duncan, J. S., Cousins, D. A., Taylor, J.-P., Taylor, P., Leiberg, K., & Wang, Y. (2024). Brain Morphology Normative modelling platform for abnormality and Centile estimation: Brain MoNoCle (arXiv:2406.01107). arXiv. http:\/\/arxiv.org\/abs\/2406.01107","DOI":"10.1162\/imag_a_00438"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b187","doi-asserted-by":"crossref","first-page":"8","DOI":"10.25122\/jml-2019-0085","article-title":"The role of quantitative EEG in the diagnosis of neuropsychiatric disorders","volume":"13","author":"Livint Popa","year":"2020","journal-title":"Journal of Medicine and Life"},{"issue":"3","key":"2026061515561152400_IMAG.a.1269-b188","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1007\/s13311-012-0131-z","article-title":"Clinical utility of EEG in attention-deficit\/hyperactivity disorder: A research update","volume":"9","author":"Loo","year":"2012","journal-title":"Neurotherapeutics"},{"issue":"3\u20134","key":"2026061515561152400_IMAG.a.1269-b189","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1300\/J184v07n03_03","article-title":"Quantitative EEG normative databases: A comparative investigation","volume":"7","author":"Lorensen","year":"2003","journal-title":"Journal of Neurotherapy"},{"key":"2026061515561152400_IMAG.a.1269-b190","doi-asserted-by":"crossref","first-page":"121637","DOI":"10.1016\/j.neuroimage.2025.121637","article-title":"Quantitative neuroimaging meets normative modelling: The last mile for precision medicine applications","volume":"325","author":"Maccioni","year":"2026","journal-title":"NeuroImage"},{"key":"2026061515561152400_IMAG.a.1269-b191","first-page":"895","article-title":"Self-supervised transformers for fMRI representation","volume-title":"Proceedings of the 5th International Conference on Medical Imaging with Deep Learning","author":"Malkiel","year":"2022"},{"issue":"9","key":"2026061515561152400_IMAG.a.1269-b192","doi-asserted-by":"crossref","first-page":"1104","DOI":"10.1111\/j.1651-2227.2000.tb03359.x","article-title":"Topographic mapping of brain potentials in the newborn infant: The establishment of normal values and utility in assessing infants with neurological injury","volume":"89","author":"Mandelbaum","year":"2000","journal-title":"Acta Paediatrica"},{"key":"2026061515561152400_IMAG.a.1269-b194","doi-asserted-by":"crossref","first-page":"e71774","DOI":"10.7554\/eLife.71774","article-title":"The OpenNeuro resource for sharing of neuroscience data","volume":"10","author":"Markiewicz","year":"2021","journal-title":"eLife"},{"issue":"10","key":"2026061515561152400_IMAG.a.1269-b195","doi-asserted-by":"crossref","first-page":"1415","DOI":"10.1038\/s41380-019-0441-1","article-title":"Conceptualizing mental disorders as deviations from normative functioning","volume":"24","author":"Marquand","year":"2019","journal-title":"Molecular Psychiatry"},{"issue":"7","key":"2026061515561152400_IMAG.a.1269-b196","doi-asserted-by":"crossref","first-page":"552","DOI":"10.1016\/j.biopsych.2015.12.023","article-title":"Understanding heterogeneity in clinical cohorts using normative models: Beyond case-control studies","volume":"80","author":"Marquand","year":"2016","journal-title":"Biological Psychiatry"},{"key":"2026061515561152400_IMAG.a.1269-b197","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1016\/B978-0-443-13480-7.00014-4","article-title":"Chapter 11\u2014Normative modeling for clinical neuroscience","volume-title":"Computational and network modeling of neuroimaging data","author":"Marquand","year":"2024"},{"key":"2026061515561152400_IMAG.a.1269-b198","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1007\/978-3-642-77087-6_42","article-title":"Neurometric quantitative electroencephalogram subtyping of obsessive compulsive disorders","volume-title":"Imaging of the brain in psychiatry and related fields","author":"Mas","year":"1993"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b199","doi-asserted-by":"crossref","first-page":"3","DOI":"10.3892\/br.2017.922","article-title":"Personalized medicine could transform healthcare","volume":"7","author":"Mathur","year":"2017","journal-title":"Biomedical Reports"},{"issue":"6","key":"2026061515561152400_IMAG.a.1269-b200","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1016\/0013-4694(73)90213-7","article-title":"Automatic evaluation of EEG background activity by means of age-dependent EEG quotients","volume":"35","author":"Matou\u0161ek","year":"1973","journal-title":"Electroencephalography and Clinical Neurophysiology"},{"key":"2026061515561152400_IMAG.a.1269-b201","doi-asserted-by":"crossref","first-page":"e153","DOI":"10.1017\/S2045796020000633","article-title":"Comorbidity within mental disorders: A comprehensive analysis based on 145 990 survey respondents from 27 countries","volume":"29","author":"McGrath","year":"2020","journal-title":"Epidemiology and Psychiatric Sciences"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b202","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1007\/BF03345422","article-title":"The use of local reference growth charts for clinical use or a universal standard: A balanced appraisal","volume":"35","author":"Milani","year":"2012","journal-title":"Journal of Endocrinological Investigation"},{"issue":"12","key":"2026061515561152400_IMAG.a.1269-b203","doi-asserted-by":"crossref","first-page":"e1000609","DOI":"10.1371\/journal.pcbi.1000609","article-title":"Power-law scaling in the brain surface electric potential","volume":"5","author":"Miller","year":"2009","journal-title":"PLoS Computational Biology"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b204","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1027\/0269-8803\/a000286","article-title":"Test-retest reliability of event-related potentials across three tasks","volume":"36","author":"Morand-Beaulieu","year":"2022","journal-title":"Journal of Psychophysiology"},{"key":"2026061515561152400_IMAG.a.1269-b205","first-page":"248","volume-title":"The cerebral cortex of man: A clinical study of localization of function","author":"Morgan","year":"1950"},{"key":"2026061515561152400_IMAG.a.1269-b206","doi-asserted-by":"crossref","unstructured":"Neves, C., Zeng, Y., & Xiao, Y. (2024). Parkinson\u2019s disease detection from resting state EEG using multi-head graph structure learning with gradient weighted graph attention explanations (arXiv:2408.00906). arXiv. http:\/\/arxiv.org\/abs\/2408.00906","DOI":"10.1007\/978-3-031-78761-4_1"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b207","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1212\/WNL.49.1.277","article-title":"Assessment of digital EEG, quantitative EEG, and EEG brain mapping: Report of the American Academy of Neurology and the American Clinical Neurophysiology Society","volume":"49","author":"Nuwer","year":"1997","journal-title":"Neurology"},{"key":"2026061515561152400_IMAG.a.1269-b208","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2011\/156869","article-title":"FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data","volume":"2011","author":"Oostenveld","year":"2011","journal-title":"Computational Intelligence and Neuroscience"},{"key":"2026061515561152400_IMAG.a.1269-b209","unstructured":"OpenNeuro. (n.d.). Retrieved June 4, 2025, from https:\/\/openneuro.org\/"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b210","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1007\/s11682-012-9210-3","article-title":"Volunteerism and self-selection bias in human positron emission tomography neuroimaging research","volume":"7","author":"Oswald","year":"2013","journal-title":"Brain Imaging and Behavior"},{"issue":"10","key":"2026061515561152400_IMAG.a.1269-b211","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1016\/j.earlhumdev.2011.05.010","article-title":"QEEG norms for the first year of life","volume":"87","author":"Otero","year":"2011","journal-title":"Early Human Development"},{"key":"2026061515561152400_IMAG.a.1269-b212","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.conb.2020.10.016","article-title":"Towards precise resting-state fMRI biomarkers in psychiatry: Synthesizing developments in transdiagnostic research, dimensional models of psychopathology, and normative neurodevelopment","volume":"65","author":"Parkes","year":"2020","journal-title":"Current Opinion in Neurobiology"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b213","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/0167-8760(84)90014-X","article-title":"Low resolution electromagnetic tomography: A new method for localizing electrical activity in the brain","volume":"18","author":"Pascual-Marqui","year":"1994","journal-title":"International Journal of Psychophysiology"},{"issue":"1\u20132","key":"2026061515561152400_IMAG.a.1269-b214","doi-asserted-by":"crossref","first-page":"89","DOI":"10.3109\/00207458808985730","article-title":"A parametric model for multichannel EEG spectra","volume":"40","author":"Pascual-Marqui","year":"1988","journal-title":"International Journal of Neuroscience"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b215","doi-asserted-by":"crossref","first-page":"167","DOI":"10.3390\/brainsci13020167","article-title":"Normative structure of resting-state EEG in bipolar derivations for daily clinical practice: A pilot study","volume":"13","author":"Pastor","year":"2023","journal-title":"Brain Sciences"},{"issue":"9","key":"2026061515561152400_IMAG.a.1269-b216","doi-asserted-by":"crossref","first-page":"2050","DOI":"10.1016\/j.clinph.2006.05.029","article-title":"Quantitative topographic differentiation of the neonatal EEG","volume":"117","author":"Paul","year":"2006","journal-title":"Clinical Neurophysiology"},{"issue":"11","key":"2026061515561152400_IMAG.a.1269-b217","doi-asserted-by":"crossref","first-page":"2745","DOI":"10.1111\/epi.17368","article-title":"Wearable OPM-MEG: A changing landscape for epilepsy","volume":"63","author":"Pedersen","year":"2022","journal-title":"Epilepsia"},{"key":"2026061515561152400_IMAG.a.1269-b218","first-page":"1","article-title":"Learning meta-stable state transition representation of brain function for ADHD identification","volume":"72","author":"Pei","year":"2023","journal-title":"IEEE Transactions on Instrumentation and Measurement"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b219","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1038\/s41597-019-0104-8","article-title":"EEG-BIDS, an extension to the brain imaging data structure for electroencephalography","volume":"6","author":"Pernet","year":"2019","journal-title":"Scientific Data"},{"key":"2026061515561152400_IMAG.a.1269-b220","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/S0079-6123(08)62443-7","article-title":"The quantitative analysis of EEG data","volume":"33","author":"Petsche","year":"1970","journal-title":"Progress in Brain Research"},{"issue":"3","key":"2026061515561152400_IMAG.a.1269-b221","doi-asserted-by":"crossref","first-page":"944","DOI":"10.1002\/hbm.24423","article-title":"Using deep autoencoders to identify abnormal brain structural patterns in neuropsychiatric disorders: A large-scale multi-sample study","volume":"40","author":"Pinaya","year":"2019","journal-title":"Human Brain Mapping"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b222","doi-asserted-by":"crossref","first-page":"15746","DOI":"10.1038\/s41598-021-95098-0","article-title":"Using normative modelling to detect disease progression in mild cognitive impairment and Alzheimer\u2019s disease in a cross-sectional multi-cohort study","volume":"11","author":"Pinaya","year":"2021","journal-title":"Scientific Reports"},{"key":"2026061515561152400_IMAG.a.1269-b223","doi-asserted-by":"crossref","first-page":"17","DOI":"10.3389\/fninf.2011.00017","article-title":"The cognitive atlas: Toward a knowledge foundation for cognitive neuroscience","volume":"5","author":"Poldrack","year":"2011","journal-title":"Frontiers in Neuroinformatics"},{"key":"2026061515561152400_IMAG.a.1269-b224","doi-asserted-by":"crossref","DOI":"10.1162\/imag_a_00103","article-title":"The past, present, and future of the brain imaging data structure (BIDS)","volume":"2","author":"Poldrack","year":"2024","journal-title":"Imaging Neuroscience"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b225","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1177\/155005940503600207","article-title":"Use of normative databases and statistical methods in demonstrating clinical utility of QEEG: Importance and cautions","volume":"36","author":"Prichep","year":"2005","journal-title":"Clinical EEG and Neuroscience"},{"issue":"11\u201312","key":"2026061515561152400_IMAG.a.1269-b226","doi-asserted-by":"crossref","first-page":"3266","DOI":"10.1111\/ejn.15450","article-title":"Forgotten rhythms? Revisiting the first evidence for rhythms in cognition","volume":"55","author":"Quigley","year":"2022","journal-title":"The European Journal of Neuroscience"},{"key":"2026061515561152400_IMAG.a.1269-b227","doi-asserted-by":"crossref","first-page":"1347082","DOI":"10.3389\/fnhum.2024.1347082","article-title":"A systematic review of EEG based automated schizophrenia classification through machine learning and deep learning","volume":"18","author":"Rahul","year":"2024","journal-title":"Frontiers in Human Neuroscience"},{"key":"2026061515561152400_IMAG.a.1269-b228","doi-asserted-by":"crossref","first-page":"797","DOI":"10.37349\/emed.2024.00256","article-title":"Functional connectivity and cognitive decline: A review of rs-fMRI, EEG, MEG, and graph theory approaches in aging and dementia","volume":"5","author":"Ranasinghe","year":"2024","journal-title":"Exploration of Medicine"},{"key":"2026061515561152400_IMAG.a.1269-b229","doi-asserted-by":"crossref","DOI":"10.1002\/9781119068129","volume-title":"Biomedical signal analysis","author":"Rangayyan","year":"2015","edition":"1st"},{"key":"2026061515561152400_IMAG.a.1269-b230","doi-asserted-by":"crossref","first-page":"RP95823","DOI":"10.7554\/eLife.95823.4","article-title":"Using normative models pre-trained on cross-sectional data to evaluate intra-individual longitudinal changes in neuroimaging data","volume":"13","author":"Reh\u00e1k Bu\u010dkov\u00e1","year":"2025","journal-title":"eLife"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b231","doi-asserted-by":"crossref","first-page":"e2212776120","DOI":"10.1073\/pnas.2212776120","article-title":"Spontaneous cortical dynamics from the first years to the golden years","volume":"120","author":"Rempe","year":"2023","journal-title":"Proceedings of the National Academy of Sciences of the United States of America"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b232","doi-asserted-by":"crossref","first-page":"1056","DOI":"10.1038\/s41467-019-08999-0","article-title":"Metastable brain waves","volume":"10","author":"Roberts","year":"2019","journal-title":"Nature Communications"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b233","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1016\/S1549-3741(04)30001-8","article-title":"Standardization as a mechanism to improve safety in health care","volume":"30","author":"Rozich","year":"2004","journal-title":"The Joint Commission Journal on Quality and Safety"},{"key":"2026061515561152400_IMAG.a.1269-b234","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.biopsycho.2018.06.008","article-title":"Fractal dimension of EEG signals and heart dynamics in discrete emotional states","volume":"137","author":"Ruiz-Padial","year":"2018","journal-title":"Biological Psychology"},{"key":"2026061515561152400_IMAG.a.1269-b235","doi-asserted-by":"crossref","first-page":"e85082","DOI":"10.7554\/eLife.85082","article-title":"Evidence for embracing normative modeling","volume":"12","author":"Rutherford","year":"2023","journal-title":"eLife"},{"key":"2026061515561152400_IMAG.a.1269-b236","doi-asserted-by":"crossref","first-page":"e72904","DOI":"10.7554\/eLife.72904","article-title":"Charting brain growth and aging at high spatial precision","volume":"11","author":"Rutherford","year":"2022","journal-title":"eLife"},{"issue":"7","key":"2026061515561152400_IMAG.a.1269-b237","doi-asserted-by":"crossref","first-page":"1711","DOI":"10.1038\/s41596-022-00696-5","article-title":"The normative modeling framework for computational psychiatry","volume":"17","author":"Rutherford","year":"2022","journal-title":"Nature Protocols"},{"key":"2026061515561152400_IMAG.a.1269-b238","unstructured":"Rutherford, S., Wolfers, T., Fraza, C., Harrnet, N. G., Beckmann, C. F., Ruhe, H. G., & Marquand, A. F. (2024). To which reference class do you belong? Measuring racial fairness of reference classes with normative modeling (arXiv:2407.19114). arXiv. http:\/\/arxiv.org\/abs\/2407.19114"},{"key":"2026061515561152400_IMAG.a.1269-b239","doi-asserted-by":"crossref","DOI":"10.1162\/IMAG.a.1135","article-title":"Multiple partially overlapping neural modules orchestrate conflict processing","volume":"4","author":"Sabo","year":"2026","journal-title":"Imaging Neuroscience"},{"issue":"11","key":"2026061515561152400_IMAG.a.1269-b240","doi-asserted-by":"crossref","first-page":"1525","DOI":"10.3390\/brainsci11111525","article-title":"Neural decoding of EEG signals with machine learning: A systematic review","volume":"11","author":"Saeidi","year":"2021","journal-title":"Brain Sciences"},{"key":"2026061515561152400_IMAG.a.1269-b241","doi-asserted-by":"crossref","unstructured":"Sampaio, I. W., Tassi, E., Bellani, M., Benedetti, F., Nenadic, I., Phillips, M., Piras, F., Yatham, L., Bianchi, A. M., Brambilla, P., & Maggioni, E. (2024). A generalizable normative deep autoencoder for brain morphological anomaly detection: Application to the multi-site StratiBip dataset on bipolar disorder in an external validation framework (p. 2024.09.04.611239). bioRxiv. https:\/\/doi.org\/10.1101\/2024.09.04.611239","DOI":"10.1101\/2024.09.04.611239"},{"key":"2026061515561152400_IMAG.a.1269-b242","doi-asserted-by":"crossref","unstructured":"Sase, T., & Kitajo, K. (2019). The metastable human brain associated with autistic-like traits. bioRxiv. https:\/\/doi.org\/10.1101\/855502","DOI":"10.1101\/855502"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b243","doi-asserted-by":"crossref","first-page":"e1008929","DOI":"10.1371\/journal.pcbi.1008929","article-title":"The metastable brain associated with autistic-like traits of typically developing individuals","volume":"17","author":"Sase","year":"2021","journal-title":"PLoS Computational Biology"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b244","doi-asserted-by":"crossref","first-page":"888","DOI":"10.1038\/s42003-024-06573-z","article-title":"Dissecting task-based fMRI activity using normative modelling: An application to the Emotional Face Matching Task","volume":"7","author":"Savage","year":"2024","journal-title":"Communications Biology"},{"issue":"9","key":"2026061515561152400_IMAG.a.1269-b245","doi-asserted-by":"crossref","first-page":"1779","DOI":"10.14778\/3538598.3538602","article-title":"Anomaly detection in time series: A comprehensive evaluation","volume":"15","author":"Schmidl","year":"2022","journal-title":"Proceedings of the VLDB Endowment"},{"issue":"9","key":"2026061515561152400_IMAG.a.1269-b246","doi-asserted-by":"crossref","first-page":"1613","DOI":"10.1038\/s41593-023-01404-6","article-title":"Regional, circuit and network heterogeneity of brain abnormalities in psychiatric disorders","volume":"26","author":"Segal","year":"2023","journal-title":"Nature Neuroscience"},{"issue":"11","key":"2026061515561152400_IMAG.a.1269-b247","doi-asserted-by":"crossref","first-page":"1440","DOI":"10.1038\/nn.3839","article-title":"Putting big data to good use in neuroscience","volume":"17","author":"Sejnowski","year":"2014","journal-title":"Nature Neuroscience"},{"issue":"12","key":"2026061515561152400_IMAG.a.1269-b248","doi-asserted-by":"crossref","first-page":"2116","DOI":"10.1016\/S1388-2457(00)00440-5","article-title":"Normal EEG in very premature infants: Reference criteria","volume":"111","author":"Selton","year":"2000","journal-title":"Clinical Neurophysiology"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b249","doi-asserted-by":"crossref","first-page":"1225","DOI":"10.1016\/j.neuroimage.2007.03.066","article-title":"The advantage of combining MEG and EEG: Comparison to fMRI in focally stimulated visual cortex","volume":"36","author":"Sharon","year":"2007","journal-title":"NeuroImage"},{"key":"2026061515561152400_IMAG.a.1269-b250","doi-asserted-by":"crossref","first-page":"1072801","DOI":"10.3389\/frai.2022.1072801","article-title":"Trends in EEG signal feature extraction applications","volume":"5","author":"Singh","year":"2023","journal-title":"Frontiers in Artificial Intelligence"},{"issue":"11","key":"2026061515561152400_IMAG.a.1269-b251","doi-asserted-by":"crossref","first-page":"3786","DOI":"10.3390\/s21113786","article-title":"A review of EEG signal features and their application in driver drowsiness detection systems","volume":"21","author":"Stancin","year":"2021","journal-title":"Sensors"},{"issue":"3\u20134","key":"2026061515561152400_IMAG.a.1269-b252","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1177\/1471082X18759144","article-title":"GAMLSS: A distributional regression approach","volume":"18","author":"Stasinopoulos","year":"2018","journal-title":"Statistical Modelling"},{"key":"2026061515561152400_IMAG.a.1269-b253","doi-asserted-by":"crossref","first-page":"1334508","DOI":"10.3389\/fnins.2024.1334508","article-title":"A normative modeling approach to quantify white matter changes and predict functional outcomes in stroke patients","volume":"18","author":"Su","year":"2024","journal-title":"Frontiers in Neuroscience"},{"issue":"3","key":"2026061515561152400_IMAG.a.1269-b254","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1007\/BF01187711","article-title":"High resolution quantitative EEG analysis","volume":"6","author":"Szava","year":"1994","journal-title":"Brain Topography"},{"key":"2026061515561152400_IMAG.a.1269-b255","first-page":"221","article-title":"Quantitative EEG norms for the Cuban Population between the ages of 5 and 97 years","volume":"49","author":"Szava","year":"1989","journal-title":"Intern J Neuroscience"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b256","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1038\/s41531-025-00957-6","article-title":"Characterizing the heterogeneity of neurodegenerative diseases through EEG normative modeling","volume":"11","author":"Tabbal","year":"2025","journal-title":"Npj Parkinson\u2019s Disease"},{"key":"2026061515561152400_IMAG.a.1269-b257","doi-asserted-by":"crossref","unstructured":"Tang, Y. Y., Rothbart, M. K., & Posner, M. I. (2012). Neural correlates of establishing, maintaining, and switching brain states. Trends in Cognitive Sciences, 16(6), 330\u2013337. https:\/\/www.cell.com\/cognitive-sciences\/abstract\/S1364-6613(12)00107-6","DOI":"10.1016\/j.tics.2012.05.001"},{"key":"2026061515561152400_IMAG.a.1269-b258","doi-asserted-by":"crossref","first-page":"1143","DOI":"10.1016\/j.neuroimage.2015.08.042","article-title":"Open science CBS neuroimaging repository: Sharing ultra-high-field MR images of the brain","volume":"124","author":"Tardif","year":"2016","journal-title":"NeuroImage"},{"key":"2026061515561152400_IMAG.a.1269-b260","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1016\/j.neuroimage.2015.09.018","article-title":"The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data repository: Structural and functional MRI, MEG, and cognitive data from a cross-sectional adult lifespan sample","volume":"144","author":"Taylor","year":"2017","journal-title":"NeuroImage"},{"issue":"3","key":"2026061515561152400_IMAG.a.1269-b261","doi-asserted-by":"crossref","first-page":"939","DOI":"10.1093\/brain\/awab380","article-title":"Normative brain mapping of interictal intracranial EEG to localize epileptogenic tissue","volume":"145","author":"Taylor","year":"2022","journal-title":"Brain"},{"key":"2026061515561152400_IMAG.a.1269-b262","doi-asserted-by":"crossref","first-page":"1505297","DOI":"10.3389\/fpsyt.2025.1505297","article-title":"Entropy, complexity, and spectral features of EEG signals in autism and typical development: A quantitative approach","volume":"16","author":"Tenev","year":"2025","journal-title":"Frontiers in Psychiatry"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b265","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1300\/J184v02n04_02","article-title":"Normative EEG databases and EEG biofeedback","volume":"2","author":"Thatcher","year":"1998","journal-title":"Journal of Neurotherapy"},{"key":"2026061515561152400_IMAG.a.1269-b266","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/B978-0-12-374534-7.00002-2","article-title":"History of the scientific standards of QEEG normative databases","volume-title":"Introduction to Quantitative EEG and Neurofeedback","author":"Thatcher","year":"2009"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b267","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1177\/155005940503600211","article-title":"Evaluation and validity of a LORETA normative EEG database","volume":"36","author":"Thatcher","year":"2005","journal-title":"Clinical EEG and Neuroscience"},{"issue":"3\u20134","key":"2026061515561152400_IMAG.a.1269-b268","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1300\/J184v07n03_05","article-title":"Quantitative EEG normative databases: Validation and clinical correlation","volume":"7","author":"Thatcher","year":"2003","journal-title":"Journal of Neurotherapy"},{"issue":"4805","key":"2026061515561152400_IMAG.a.1269-b269","doi-asserted-by":"crossref","first-page":"1110","DOI":"10.1126\/science.3576224","article-title":"Human cerebral hemispheres develop at different rates and ages","volume":"236","author":"Thatcher","year":"1987","journal-title":"Science"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b270","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1093\/oxfordjournals.epirev.a036143","article-title":"Statistical analysis of case-control studies","volume":"16","author":"Thompson","year":"1994","journal-title":"Epidemiologic Reviews"},{"key":"2026061515561152400_IMAG.a.1269-b271","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.seizure.2017.06.002","article-title":"Current clinical magnetoencephalography practice across Europe: Are we closer to use MEG as an established clinical tool?","volume":"50","author":"Ti\u00e8ge","year":"2017","journal-title":"Seizure"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b272","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1007\/s12021-011-9126-x","article-title":"The cognitive paradigm ontology: Design and application","volume":"10","author":"Turner","year":"2012","journal-title":"Neuroinformatics"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b314","first-page":"281","article-title":"High resolution spectral EEG norms topography","volume":"3","author":"Vald\u00e9s","year":"1990","journal-title":"Brain Topography"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b273","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1007\/BF01135563","article-title":"QEEG in a public health system","volume":"4","author":"Vald\u00e9s","year":"1992","journal-title":"Brain Topography"},{"issue":"9","key":"2026061515561152400_IMAG.a.1269-b315","first-page":"e100","article-title":"Cuban human brain mapping project","volume":"119","author":"Vald\u00e9s Sosa","year":"2008","journal-title":"Clinical Neurophysiology"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b274","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1038\/s41597-021-00829-7","article-title":"The Cuban Human Brain Mapping Project, a young and middle age population-based EEG, MRI, and cognition dataset","volume":"8","author":"Valdes-Sosa","year":"2021","journal-title":"Scientific Data"},{"issue":"S6","key":"2026061515561152400_IMAG.a.1269-b275","doi-asserted-by":"crossref","first-page":"e059945","DOI":"10.1002\/alz.059945","article-title":"EEG in the Global Brain Consortium, aiming to strengthen linkages between neuroscientists across borders and disciplines to advance equitable solutions to priority health challenges worldwide","volume":"18","author":"Valdes-Sosa","year":"2022","journal-title":"Alzheimer\u2019s & Dementia"},{"issue":"6","key":"2026061515561152400_IMAG.a.1269-b276","doi-asserted-by":"crossref","first-page":"522","DOI":"10.1016\/S0013-4694(97)00147-8","article-title":"Volume conduction effects in EEG and MEG","volume":"106","author":"Van Den Broek","year":"1998","journal-title":"Electroencephalography and Clinical Neurophysiology"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b277","doi-asserted-by":"crossref","first-page":"1073","DOI":"10.3758\/s13428-012-0305-y","article-title":"Establishing normative data for repeated cognitive assessment: A comparison of different statistical methods","volume":"45","author":"Van der Elst","year":"2013","journal-title":"Behavior Research Methods"},{"key":"2026061515561152400_IMAG.a.1269-b278","doi-asserted-by":"crossref","first-page":"1522675","DOI":"10.3389\/fnins.2025.1522675","article-title":"osl-ephys: A Python toolbox for the analysis of electrophysiology data","volume":"19","author":"Van Es","year":"2025","journal-title":"Frontiers in Neuroscience"},{"key":"2026061515561152400_IMAG.a.1269-b279","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.neuroimage.2013.05.041","article-title":"The WU-Minn Human Connectome Project: An overview","volume":"80","author":"Van Essen","year":"2013","journal-title":"NeuroImage"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b280","doi-asserted-by":"crossref","first-page":"2222","DOI":"10.1016\/j.neuroimage.2012.02.018","article-title":"The Human Connectome Project: A data acquisition perspective","volume":"62","author":"Van Essen","year":"2012","journal-title":"NeuroImage"},{"issue":"24","key":"2026061515561152400_IMAG.a.1269-b281","doi-asserted-by":"crossref","first-page":"e2442","DOI":"10.1212\/WNL.0000000000207298","article-title":"Revealing individual neuroanatomical heterogeneity in Alzheimer disease using neuroanatomical normative modeling","volume":"100","author":"Verdi","year":"2023","journal-title":"Neurology"},{"issue":"10","key":"2026061515561152400_IMAG.a.1269-b282","doi-asserted-by":"crossref","first-page":"2946","DOI":"10.1093\/brain\/awab165","article-title":"Beyond the average patient: How neuroimaging models can address heterogeneity in dementia","volume":"144","author":"Verdi","year":"2021","journal-title":"Brain"},{"issue":"48","key":"2026061515561152400_IMAG.a.1269-b283","doi-asserted-by":"crossref","first-page":"12827","DOI":"10.1073\/pnas.1705120114","article-title":"Brain network dynamics are hierarchically organized in time","volume":"114","author":"Vidaurre","year":"2017","journal-title":"Proceedings of the National Academy of Sciences of the United States of America"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b284","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1007\/s12264-022-00952-4","article-title":"Charting normative brain variability across the human lifespan","volume":"39","author":"Wei","year":"2023","journal-title":"Neuroscience Bulletin"},{"key":"2026061515561152400_IMAG.a.1269-b285","volume-title":"Length\/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age; methods and development","author":"Weltgesundheitsorganisation (with Weltgesundheitsorganisation)","year":"2006"},{"key":"2026061515561152400_IMAG.a.1269-b286","doi-asserted-by":"crossref","first-page":"656092","DOI":"10.1155\/2009\/656092","article-title":"EEG\/MEG source imaging: Methods, challenges, and open issues","volume":"2009","author":"Wendel","year":"2009","journal-title":"Computational Intelligence and Neuroscience"},{"key":"2026061515561152400_IMAG.a.1269-b287","doi-asserted-by":"crossref","unstructured":"Wens, V., Bourguignon, M., Vander Ghinst, M., Mary, A., Marty, B., Coquelet, N., Naeije, G., Peigneux, P., Goldman, S., & De Ti\u00e8ge, X. (2019). Synchrony, metastability, dynamic integration, and competition in the spontaneous functional connectivity of the human brain. NeuroImage, 199, 313. https:\/\/www.sciencedirect.com\/science\/article\/pii\/S105381191930477X","DOI":"10.1016\/j.neuroimage.2019.05.081"},{"key":"2026061515561152400_IMAG.a.1269-b288","doi-asserted-by":"crossref","unstructured":"Werner, G.\n           (2007). Metastability, criticality and phase transitions in brain and its models. Biosystems, 90(2), 496\u2013508. https:\/\/www.sciencedirect.com\/science\/article\/pii\/S030326470600284X","DOI":"10.1016\/j.biosystems.2006.12.001"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b289","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.earlhumdev.2005.07.009","article-title":"Quantitative electroencephalographic patterns in normal preterm infants over the first week after birth","volume":"82","author":"West","year":"2006","journal-title":"Early Human Development"},{"issue":"9","key":"2026061515561152400_IMAG.a.1269-b290","doi-asserted-by":"crossref","first-page":"879","DOI":"10.1001\/jamapsychiatry.2022.1780","article-title":"Quantifying deviations of brain structure and function in major depressive disorder across neuroimaging modalities","volume":"79","author":"Winter","year":"2022","journal-title":"JAMA Psychiatry"},{"key":"2026061515561152400_IMAG.a.1269-b291","unstructured":"Wolfers, T.\n           (2019). Towards precision medicine in psychiatry [PhD Thesis]. https:\/\/repository.ubn.ru.nl\/bitstream\/handle\/2066\/201200\/201200pub.pdf"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b292","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1017\/S0033291719000084","article-title":"Individual differences v. The average patient: Mapping the heterogeneity in ADHD using normative models","volume":"50","author":"Wolfers","year":"2020","journal-title":"Psychological Medicine"},{"issue":"11","key":"2026061515561152400_IMAG.a.1269-b293","doi-asserted-by":"crossref","first-page":"1146","DOI":"10.1001\/jamapsychiatry.2018.2467","article-title":"Mapping the heterogeneous phenotype of schizophrenia and bipolar disorder using normative models","volume":"75","author":"Wolfers","year":"2018","journal-title":"JAMA Psychiatry"},{"issue":"8","key":"2026061515561152400_IMAG.a.1269-b294","doi-asserted-by":"crossref","first-page":"2546","DOI":"10.1002\/hbm.25386","article-title":"Replicating extensive brain structural heterogeneity in individuals with schizophrenia and bipolar disorder","volume":"42","author":"Wolfers","year":"2021","journal-title":"Human Brain Mapping"},{"issue":"7","key":"2026061515561152400_IMAG.a.1269-b295","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1007\/s00429-025-02988-4","article-title":"Multi-centre normative brain mapping of intracranial EEG lifespan patterns in the human brain","volume":"230","author":"Woodhouse","year":"2025","journal-title":"Brain Structure and Function"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b296","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1109\/TMI.2003.823065","article-title":"Fully Bayesian spatio-temporal modeling of fMRI data","volume":"23","author":"Woolrich","year":"2004","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"2026061515561152400_IMAG.a.1269-b297","volume-title":"Mental Health Atlas 2020","author":"World Health Organization","year":"2021","edition":"1st"},{"key":"2026061515561152400_IMAG.a.1269-b298","volume-title":"Child growth standards: Publications and peer-reviewed articles","author":"World Health Organization","year":"2024"},{"issue":"2","key":"2026061515561152400_IMAG.a.1269-b299","doi-asserted-by":"crossref","first-page":"351","DOI":"10.3390\/brainsci13020351","article-title":"The resting state of Taiwan EEG normative database: Z-scores of patients with major depressive disorder as the cross-validation","volume":"13","author":"Wu","year":"2023","journal-title":"Brain Sciences"},{"key":"2026061515561152400_IMAG.a.1269-b300","doi-asserted-by":"crossref","first-page":"117822","DOI":"10.1016\/j.neuroimage.2021.117822","article-title":"Estimating brain age from structural MRI and MEG data: Insights from dimensionality reduction techniques","volume":"231","author":"Xifra-Porxas","year":"2021","journal-title":"NeuroImage"},{"issue":"4","key":"2026061515561152400_IMAG.a.1269-b301","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3626235","article-title":"Diffusion models: A comprehensive survey of methods and applications","volume":"56","author":"Yang","year":"2024","journal-title":"ACM Computing Surveys"},{"key":"2026061515561152400_IMAG.a.1269-b302","article-title":"A normative reference for large-scale human brain dynamics across the lifespan","author":"Yang","year":"2026","journal-title":"bioRxiv."},{"key":"2026061515561152400_IMAG.a.1269-b303","doi-asserted-by":"crossref","first-page":"101312","DOI":"10.1016\/j.dcn.2023.101312","article-title":"Neurophysiological mechanisms of cognition in the developing brain: Insights from intracranial EEG studies","volume":"64","author":"Yin","year":"2023","journal-title":"Developmental Cognitive Neuroscience"},{"key":"2026061515561152400_IMAG.a.1269-b304","first-page":"7561","article-title":"Leads: Learning dynamical systems that generalize across environments","volume":"34","author":"Yin","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"key":"2026061515561152400_IMAG.a.1269-b305","doi-asserted-by":"crossref","first-page":"121442","DOI":"10.1016\/j.neuroimage.2025.121442","article-title":"Conditional deep generative normative modeling for structural and developmental anomaly detection in the fetal brain","volume":"319","author":"You","year":"2025","journal-title":"NeuroImage"},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b306","doi-asserted-by":"crossref","first-page":"4273","DOI":"10.1038\/s41467-018-05892-0","article-title":"Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference","volume":"9","author":"Young","year":"2018","journal-title":"Nature Communications"},{"key":"2026061515561152400_IMAG.a.1269-b307","article-title":"Latent representations of early brain development: A multivariate normative model of brain structure and behaviour","author":"Zabihi","journal-title":"bioRxiv."},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b308","doi-asserted-by":"crossref","first-page":"384","DOI":"10.1038\/s41398-020-01057-0","article-title":"Fractionating autism based on neuroanatomical normative modeling","volume":"10","author":"Zabihi","year":"2020","journal-title":"Translational Psychiatry"},{"key":"2026061515561152400_IMAG.a.1269-b309","article-title":"Explanatory latent representation of heterogeneous spatial maps of task-fMRI in large-scale datasets","author":"Zabihi","year":"2021","journal-title":"bioRxiv."},{"issue":"1","key":"2026061515561152400_IMAG.a.1269-b310","doi-asserted-by":"crossref","first-page":"604","DOI":"10.1038\/s42003-026-09825-2","article-title":"Normative modeling of MEG brain oscillations across the human lifespan","volume":"9","author":"Zamanzadeh","year":"2026","journal-title":"Communications Biology"},{"key":"2026061515561152400_IMAG.a.1269-b311","unstructured":"Zamanzadeh, M., Verduyn, Y., & Kia, S. M. (2025). MEGaNorm: A Python package for normative modeling on MEG and EEG data (Version v0.1.0) [Computer software]. Zenodo. https:\/\/doi.org\/10.5281\/ZENODO.15441320"},{"key":"2026061515561152400_IMAG.a.1269-b312","doi-asserted-by":"crossref","unstructured":"Zavatone-Veth, J. A., & Pehlevan, C. (2024). Nadaraya-Watson kernel smoothing as a random energy model. arXiv. https:\/\/doi.org\/10.48550\/ARXIV.2408.03769","DOI":"10.1088\/1742-5468\/ada49a"},{"issue":"8","key":"2026061515561152400_IMAG.a.1269-b313","doi-asserted-by":"crossref","first-page":"1629","DOI":"10.1017\/S0033291723003525","article-title":"Dynamic structure\u2013function coupling across three major psychiatric disorders","volume":"54","author":"Zhang","year":"2024","journal-title":"Psychological Medicine"}],"container-title":["Imaging Neuroscience"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/direct.mit.edu\/imag\/article-pdf\/doi\/10.1162\/IMAG.a.1269\/2600782\/imag.a.1269.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/direct.mit.edu\/imag\/article-pdf\/doi\/10.1162\/IMAG.a.1269\/2600782\/imag.a.1269.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T19:56:57Z","timestamp":1781553417000},"score":1,"resource":{"primary":{"URL":"https:\/\/direct.mit.edu\/imag\/article\/doi\/10.1162\/IMAG.a.1269\/136768\/From-early-to-contemporary-normative-modeling"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":308,"URL":"https:\/\/doi.org\/10.1162\/imag.a.1269","relation":{},"ISSN":["2837-6056"],"issn-type":[{"value":"2837-6056","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2026]]},"published":{"date-parts":[[2026]]},"article-number":"IMAG.a.1269"}}