Genetic Contributions to Multivariate Data-Driven Brain Networks Constructed via Source-Based Morphometry.
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ABSTRACT:
SUBMITTER: Rodrigue AL
PROVIDER: S-EPMC7391270 | biostudies-literature | 2020 Jul
REPOSITORIES: biostudies-literature
Publications
Genetic Contributions to Multivariate Data-Driven Brain Networks Constructed via Source-Based Morphometry.
Rodrigue Amanda L AL Alexander-Bloch Aaron F AF Knowles Emma E M EEM Mathias Samuel R SR Mollon Josephine J Koenis Marinka M G MMG Perrone-Bizzozero Nora I NI Almasy Laura L Turner Jessica A JA Calhoun Vince D VD Glahn David C DC
Cerebral cortex (New York, N.Y. : 1991) 20200701 9
Identifying genetic factors underlying neuroanatomical variation has been difficult. Traditional methods have used brain regions from predetermined parcellation schemes as phenotypes for genetic analyses, although these parcellations often do not reflect brain function and/or do not account for covariance between regions. We proposed that network-based phenotypes derived via source-based morphometry (SBM) may provide additional insight into the genetic architecture of neuroanatomy given its data ...[more]
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