ArticleBrain and behavior2021
Large-scale collaboration in ENIGMA-EEG: A perspective on the meta-analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity.
Article in Brain and behavior, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 31 citations in OpenAlex.
- Lifespan Trajectories of Resting State EEG power.bioRxiv : the preprint server for biology · 2026Article
- High-density EEG network analysis in MCI: an exploratory study of electrode density and cognitive performance.Frontiers in aging neuroscience · 2026Article
- Comprehensive methodology for sample enrichment in EEG biomarker studies for Alzheimer's risk classification.PloS one · 2026Article
- Electrophysiological resting-state signatures link polygenic scores to general intelligence.Scientific reports · 2025Observational
- fNIRS reproducibility varies with data quality, analysis pipelines, and researcher experience.Communications biology · 2025Article
- Common Genomic and Proteomic Alterations Related to Disturbed Neural Oscillatory Activity in Schizophrenia.International journal of molecular sciences · 2025Review
- Childhood Trauma andmedRxiv : the preprint server for health sciences · 2025Article
- Unraveling the enigma of mental disorders: a genetics-first approach and the role of mouse models based on rare disease-susceptible genome variants.Nagoya journal of medical science · 2025Review
- Reporting checklists in neuroimaging: promoting transparency, replicability, and reproducibility.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024Review
- Advances, challenges, and prospects of electroencephalography-based biomarkers for psychiatric disorders: a narrative review.Journal of Yeungnam medical science · 2024Article
- The collaborative study on the genetics of alcoholism: Brain function.Genes, brain, and behavior · 2023Review
- The collaborative study on the genetics of alcoholism: Genetics.Genes, brain, and behavior · 2023Review
- Developmental changes in individual alpha frequency: Recording EEG data during public engagement events.Imaging neuroscience (Cambridge, Mass.) · 2023Article
- Genome-wide association studies: utility and limitations for research in physiology.The Journal of physiology · 2023Article
- Experimental Medicine Approaches in Early-Phase CNS Drug Development.Advances in neurobiology · 2023Article
- Relation of Brain Perfusion Patterns to Sudden Unexpected Death Risk Stratification: A Study in Drug Resistant Focal Epilepsy.Behavioral sciences (Basel, Switzerland) · 2022Article
- The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain-behavior relationships after stroke.Human brain mapping · 2022Review
- The Musical Abilities, Pleiotropy, Language, and Environment (MAPLE) Framework for Understanding Musicality-Language Links Across the Lifespan.Neurobiology of language (Cambridge, Mass.) · 2022Review
- A scoping review of electroencephalographic (EEG) markers for tracking neurophysiological changes and predicting outcomes in substance use disorder treatment.Frontiers in human neuroscience · 2022Article
- The Big Five Personality Traits and Brain Arousal in the Resting State.Brain sciences · 2021Article
Corrections and comments
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Authors and funding
28 authors at 19 institutions in 8 countries.
Funding
Abstract
background and purposeThe ENIGMA-EEG working group was established to enable large-scale international collaborations among cohorts that investigate the genetics of brain function measured with electroencephalography (EEG). In this perspective, we will discuss why analyzing the genetics of functional brain activity may be crucial for understanding how neurological and psychiatric liability genes affect the brain.
methodsWe summarize how we have performed our currently largest genome-wide association study of oscillatory brain activity in EEG recordings by meta-analyzing the results across five participating cohorts, resulting in the first genome-wide significant hits for oscillatory brain function located in/near genes that were previously associated with psychiatric disorders. We describe how we have tackled methodological issues surrounding genetic meta-analysis of EEG features. We discuss the importance of harmonizing EEG signal processing, cleaning, and feature extraction. Finally, we explain our selection of EEG features currently being investigated, including the temporal dynamics of oscillations and the connectivity network based on synchronization of oscillations.
resultsWe present data that show how to perform systematic quality control and evaluate how choices in reference electrode and montage affect individual differences in EEG parameters.
conclusionThe long list of potential challenges to our large-scale meta-analytic approach requires extensive effort and organization between participating cohorts; however, our perspective shows that these challenges are surmountable. Our perspective argues that elucidating the genetic of EEG oscillatory activity is a worthwhile effort in order to elucidate the pathway from gene to disease liability.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.