ArticleHuman brain mapping2019
Discovering heritable modes of MEG spectral power.
Article in Human brain mapping, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
11 citing papers in PubMed, 22 citations in OpenAlex.
- Trait-like individual signatures dominate sleep EEG over insomnia-specific features.Scientific reports · 2026Article
- Capturing individual variation in children's electroencephalograms during nREM sleep.PLoS computational biology · 2026Article
- Penalized canonical correlation analysis reveals a relationship between temperament traits and brain oscillations during mind wandering.Brain and behavior · 2024Article
- Human Sensorimotor Beta Event Characteristics and Aperiodic Signal Are Highly Heritable.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Brain criticality predicts individual levels of inter-areal synchronization in human electrophysiological data.Nature communications · 2023Article
- Intelligent digital tools for screening of brain connectivity and dementia risk estimation in people affected by mild cognitive impairment: the AI-Mind clinical study protocol.Frontiers in neurorobotics · 2023Article
- Genetic polymorphisms iniScience · 2022Article
- Brief segments of neurophysiological activity enable individual differentiation.Nature communications · 2021Observational
- The Open Brain Consent: Informing research participants and obtaining consent to share brain imaging data.Human brain mapping · 2021Article
- Issues and recommendations from the OHBM COBIDAS MEEG committee for reproducible EEG and MEG research.Nature neuroscience · 2020Review
- Discovering heritable modes of MEG spectral power.Human brain mapping · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 3 countries.
Funding
Abstract
Brain structure and many brain functions are known to be genetically controlled, but direct links between neuroimaging measures and their underlying cellular-level determinants remain largely undiscovered. Here, we adopt a novel computational method for examining potential similarities in high-dimensional brain imaging data between siblings. We examine oscillatory brain activity measured with magnetoencephalography (MEG) in 201 healthy siblings and apply Bayesian reduced-rank regression to extract a low-dimensional representation of familial features in the participants' spectral power structure. Our results show that the structure of the overall spectral power at 1-90 Hz is a highly conspicuous feature that not only relates siblings to each other but also has very high consistency within participants' own data, irrespective of the exact experimental state of the participant. The analysis is extended by seeking genetic associations for low-dimensional descriptions of the oscillatory brain activity. The observed variability in the MEG spectral power structure was associated with SDK1 (sidekick cell adhesion molecule 1) and suggestively with several other genes that function, for example, in brain development. The current results highlight the potential of sophisticated computational methods in combining molecular and neuroimaging levels for exploring brain functions, even for high-dimensional data limited to a few hundred participants.
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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.