Literature DB >> 32959043

The Heritability of Cortical Folding: Evidence from the Human Connectome Project.

J Eric Schmitt1, Armin Raznahan2, Siyuan Liu2, Michael C Neale3.   

Abstract

The mechanisms underlying cortical folding are incompletely understood. Prior studies have suggested that individual differences in sulcal depth are genetically mediated, with deeper and ontologically older sulci more heritable than others. In this study, we examine FreeSurfer-derived estimates of average convexity and mean curvature as proxy measures of cortical folding patterns using a large (N = 1096) genetically informative young adult subsample of the Human Connectome Project. Both measures were significantly heritable near major sulci and primary fissures, where approximately half of individual differences could be attributed to genetic factors. Genetic influences near higher order gyri and sulci were substantially lower and largely nonsignificant. Spatial permutation analysis found that heritability patterns were significantly anticorrelated to maps of evolutionary and neurodevelopmental expansion. We also found strong phenotypic correlations between average convexity, curvature, and several common surface metrics (cortical thickness, surface area, and cortical myelination). However, quantitative genetic models suggest that correlations between these metrics are largely driven by nongenetic factors. These findings not only further our understanding of the neurobiology of gyrification, but have pragmatic implications for the interpretation of heritability maps based on automated surface-based measurements. Published by Oxford University Press 2020.

Entities:  

Keywords:  FreeSurfer; MRI; average convexity; mean curvature; twin

Mesh:

Year:  2021        PMID: 32959043      PMCID: PMC7727360          DOI: 10.1093/cercor/bhaa254

Source DB:  PubMed          Journal:  Cereb Cortex        ISSN: 1047-3211            Impact factor:   5.357


  88 in total

1.  Principles underlying mammalian neocortical scaling.

Authors:  M A Changizi
Journal:  Biol Cybern       Date:  2001-03       Impact factor: 2.086

2.  An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

Authors:  Rahul S Desikan; Florent Ségonne; Bruce Fischl; Brian T Quinn; Bradford C Dickerson; Deborah Blacker; Randy L Buckner; Anders M Dale; R Paul Maguire; Bradley T Hyman; Marilyn S Albert; Ronald J Killiany
Journal:  Neuroimage       Date:  2006-03-10       Impact factor: 6.556

3.  Prediction for human intelligence using morphometric characteristics of cortical surface: partial least square analysis.

Authors:  J-J Yang; U Yoon; H J Yun; K Im; Y Y Choi; K H Lee; H Park; M G Hough; J-M Lee
Journal:  Neuroscience       Date:  2013-04-30       Impact factor: 3.590

Review 4.  How Cells Fold the Cerebral Cortex.

Authors:  Víctor Borrell
Journal:  J Neurosci       Date:  2018-01-24       Impact factor: 6.167

5.  Quantitative genetic modeling of variation in human brain morphology.

Authors:  W F Baaré; H E Hulshoff Pol; D I Boomsma; D Posthuma; E J de Geus; H G Schnack; N E van Haren; C J van Oel; R S Kahn
Journal:  Cereb Cortex       Date:  2001-09       Impact factor: 5.357

6.  Genetic Complexity of Cortical Structure: Differences in Genetic and Environmental Factors Influencing Cortical Surface Area and Thickness.

Authors:  Lachlan T Strike; Narelle K Hansell; Baptiste Couvy-Duchesne; Paul M Thompson; Greig I de Zubicaray; Katie L McMahon; Margaret J Wright
Journal:  Cereb Cortex       Date:  2019-03-01       Impact factor: 5.357

7.  Differences in genetic and environmental influences on the human cerebral cortex associated with development during childhood and adolescence.

Authors:  Rhoshel K Lenroot; James E Schmitt; Sarah J Ordaz; Gregory L Wallace; Michael C Neale; Jason P Lerch; Kenneth S Kendler; Alan C Evans; Jay N Giedd
Journal:  Hum Brain Mapp       Date:  2009-01       Impact factor: 5.038

8.  Adolescent maturation of the relationship between cortical gyrification and cognitive ability.

Authors:  Yu Sun Chung; Christopher J Hyatt; Michael C Stevens
Journal:  Neuroimage       Date:  2017-07-01       Impact factor: 6.556

Review 9.  The Human Connectome Project: a data acquisition perspective.

Authors:  D C Van Essen; K Ugurbil; E Auerbach; D Barch; T E J Behrens; R Bucholz; A Chang; L Chen; M Corbetta; S W Curtiss; S Della Penna; D Feinberg; M F Glasser; N Harel; A C Heath; L Larson-Prior; D Marcus; G Michalareas; S Moeller; R Oostenveld; S E Petersen; F Prior; B L Schlaggar; S M Smith; A Z Snyder; J Xu; E Yacoub
Journal:  Neuroimage       Date:  2012-02-17       Impact factor: 6.556

10.  MSM: a new flexible framework for Multimodal Surface Matching.

Authors:  Emma C Robinson; Saad Jbabdi; Matthew F Glasser; Jesper Andersson; Gregory C Burgess; Michael P Harms; Stephen M Smith; David C Van Essen; Mark Jenkinson
Journal:  Neuroimage       Date:  2014-06-02       Impact factor: 6.556

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  3 in total

Review 1.  Machine learning in neuroimaging: from research to clinical practice.

Authors:  Karl-Heinz Nenning; Georg Langs
Journal:  Radiologie (Heidelb)       Date:  2022-08-31

2.  Differences in Degree and Form.

Authors:  Dorothea L Floris; Derek S Andrews
Journal:  Biol Psychiatry Cogn Neurosci Neuroimaging       Date:  2021-09

Review 3.  Mapping the genetic architecture of cortical morphology through neuroimaging: progress and perspectives.

Authors:  Dennis van der Meer; Tobias Kaufmann
Journal:  Transl Psychiatry       Date:  2022-10-14       Impact factor: 7.989

  3 in total

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