Discovering heritable modes of MEG spectral power.


Journal

Human brain mapping
ISSN: 1097-0193
Titre abrégé: Hum Brain Mapp
Pays: United States
ID NLM: 9419065

Informations de publication

Date de publication:
01 04 2019
Historique:
received: 11 07 2018
revised: 27 09 2018
accepted: 19 10 2018
pubmed: 3 1 2019
medline: 9 4 2020
entrez: 3 1 2019
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 30600573
doi: 10.1002/hbm.24454
pmc: PMC6590382
doi:

Substances chimiques

Cell Adhesion Molecules 0
SDK1 protein, human 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1391-1402

Subventions

Organisme : Academy of Finland: Finnish Center of Excellence in Computational Inference Research COIN
ID : 127401
Pays : International
Organisme : Academy of Finland: Finnish Center of Excellence in Computational Inference Research COIN
ID : 255349
Pays : International
Organisme : Academy of Finland: Finnish Center of Excellence in Computational Inference Research COIN
ID : 256459
Pays : International
Organisme : Academy of Finland: Finnish Center of Excellence in Computational Inference Research COIN
ID : 277655
Pays : International
Organisme : Academy of Finland: Finnish Center of Excellence in Computational Inference Research COIN
ID : 283071
Pays : International
Organisme : Academy of Finland: Finnish Center of Excellence in Computational Inference Research COIN
ID : 292334
Pays : International
Organisme : Academy of Finland: Finnish Center of Excellence in Computational Inference Research COIN
ID : 294238
Pays : International
Organisme : Academy of Finland: Finnish Center of Excellence in Computational Inference Research COIN
ID : 315553
Pays : International
Organisme : Biocentrum Helsinki
Pays : International
Organisme : Ella and Georg Ehrnrooth Foundation
Pays : International
Organisme : Finnish Cultural Foundation
Pays : International
Organisme : Jenny and Antti Wihuri Foundation
Pays : International
Organisme : Sigrid Jusélius Foundation, Swedish Research Council
Pays : International

Informations de copyright

© 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.

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Auteurs

Eemeli Leppäaho (E)

Department of Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Helsinki, Finland.

Hanna Renvall (H)

Department of Neuroscience and Biomedical Engineering, Aalto University, Helsinki, Finland.
Aalto NeuroImaging, Aalto University, Helsinki, Finland.

Elina Salmela (E)

Department of Biosciences, University of Helsinki, Helsinki, Finland.

Juha Kere (J)

Molecular Neurology Research Program, University of Helsinki, Folkhälsan Institute of Genetics, Helsinki, Finland.
Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden.
School of Basic and Medical Biosciences, King's College London, Guy's Hospital, London, United Kingdom.

Riitta Salmelin (R)

Department of Neuroscience and Biomedical Engineering, Aalto University, Helsinki, Finland.
Aalto NeuroImaging, Aalto University, Helsinki, Finland.

Samuel Kaski (S)

Department of Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Helsinki, Finland.

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Classifications MeSH