Please use this identifier to cite or link to this item: https://doi.org/10.1093/cercor/bhz271
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dc.titleNeural Transcription Correlates of Multimodal Cortical Phenotypes during Development
dc.contributor.authorPecheva D.
dc.contributor.authorLee A.
dc.contributor.authorPoh J.S.
dc.contributor.authorChong Y.-S.
dc.contributor.authorShek L.P.
dc.contributor.authorGluckman P.D.
dc.contributor.authorMeaney M.J.
dc.contributor.authorFortier M.V.
dc.contributor.authorQiu A.
dc.date.accessioned2021-01-27T07:35:16Z
dc.date.available2021-01-27T07:35:16Z
dc.date.issued2020
dc.identifier.citationPecheva D., Lee A., Poh J.S., Chong Y.-S., Shek L.P., Gluckman P.D., Meaney M.J., Fortier M.V., Qiu A. (2020). Neural Transcription Correlates of Multimodal Cortical Phenotypes during Development. Cerebral Cortex 30 (5) : 2740 - 2754. ScholarBank@NUS Repository. https://doi.org/10.1093/cercor/bhz271
dc.identifier.issn10473211
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/185861
dc.description.abstractDuring development, cellular events such as cell proliferation, migration, and synaptogenesis determine the structural organization of the brain. These processes are driven in part by spatiotemporally regulated gene expression. We investigated how the genetic signatures of specific neural cell types shape cortical organization of the human brain throughout infancy and childhood. Using a transcriptional atlas and in vivo magnetic resonance imaging (MRI) data, we demonstrated time-dependent associations between the expression levels of neuronal and glial genes and cortical macro- and microstructure. Neonatal cortical phenotypes were associated with prenatal glial but not neuronal gene expression. These associations reflect cell migration and proliferation during fetal development. Childhood cortical phenotypes were associated with neuronal and astrocyte gene expression related to synaptic signaling processes, reflecting the refinement of cortical connections. These findings indicate that sequential developmental stages contribute to distinct MRI measures at different time points. This helps to bridge the gap between the genetic mechanisms driving cellular changes and widely used neuroimaging techniques. @ 2019 The Author(s) 2019. Published by Oxford University Press. All rights reserved.
dc.language.isoen
dc.publisherOxford University Press
dc.sourceScopus
dc.subjectcortical microstructure
dc.subjectcortical thickness
dc.subjectearly development
dc.subjectgene expression
dc.subjectMRI
dc.typeArticle
dc.contributor.departmentBIOMEDICAL ENGINEERING
dc.contributor.departmentOBSTETRICS & GYNAECOLOGY
dc.contributor.departmentPAEDIATRICS
dc.contributor.departmentDUKE-NUS MEDICAL SCHOOL
dc.description.doi10.1093/cercor/bhz271
dc.description.sourcetitleCerebral Cortex
dc.description.volume30
dc.description.issue5
dc.description.page2740 - 2754
dc.description.codenCECOE
dc.description.seriesGUSTO (Growing up towards Healthy Outcomes)
dc.description.seriesGUSTO (Growing up towards Healthy Outcomes)
dc.description.seriesGUSTO (Growing up towards Healthy Outcomes)
dc.published.statePublished
dc.grant.idNMRC/TCR/004-NUS/2008
dc.grant.idNMRC/TCR/012-NUHS/2014
dc.grant.fundingagencyNational Medical Research Council
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