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Mother-child similarity in brain morphology: A comparison of structural characteristics of the brain’s reading network


Fehlbaum, Lynn V; Peters, Lien; Dimanova, Plamina; Roell, Margot; Borbás, Réka; Ansari, Daniel; Raschle, Nora Maria (2022). Mother-child similarity in brain morphology: A comparison of structural characteristics of the brain’s reading network. Developmental Cognitive Neuroscience, 53:101058.

Abstract

Background
Substantial evidence acknowledges the complex gene-environment interplay impacting brain development and learning. Intergenerational neuroimaging allows the assessment of familial transfer effects on brain structure, function and behavior by investigating neural similarity in caregiver-child dyads.
Methods
Neural similarity in the human reading network was assessed through well-used measures of brain structure (i.e., surface area (SA), gyrification (lG), sulcal morphology, gray matter volume (GMV) and cortical thickness (CT)) in 69 mother-child dyads (children’s age~11 y). Regions of interest for the reading network included left-hemispheric inferior frontal gyrus, inferior parietal lobe and fusiform gyrus. Mother-child similarity was quantified by correlation coefficients and familial specificity was tested by comparison to random adult-child dyads. Sulcal morphology analyses focused on occipitotemporal sulcus interruptions and similarity was assessed by chi-square goodness of fit.
Results
Significant structural brain similarity was observed for mother-child dyads in the reading network for lG, SA and GMV (r = 0.349/0.534/0.542, respectively), but not CT. Sulcal morphology associations were non-significant. Structural brain similarity in lG, SA and GMV were specific to mother-child pairs. Furthermore, structural brain similarity for SA and GMV was higher compared to CT.
Conclusion
Intergenerational neuroimaging techniques promise to enhance our knowledge of familial transfer effects on brain development and disorders.

Abstract

Background
Substantial evidence acknowledges the complex gene-environment interplay impacting brain development and learning. Intergenerational neuroimaging allows the assessment of familial transfer effects on brain structure, function and behavior by investigating neural similarity in caregiver-child dyads.
Methods
Neural similarity in the human reading network was assessed through well-used measures of brain structure (i.e., surface area (SA), gyrification (lG), sulcal morphology, gray matter volume (GMV) and cortical thickness (CT)) in 69 mother-child dyads (children’s age~11 y). Regions of interest for the reading network included left-hemispheric inferior frontal gyrus, inferior parietal lobe and fusiform gyrus. Mother-child similarity was quantified by correlation coefficients and familial specificity was tested by comparison to random adult-child dyads. Sulcal morphology analyses focused on occipitotemporal sulcus interruptions and similarity was assessed by chi-square goodness of fit.
Results
Significant structural brain similarity was observed for mother-child dyads in the reading network for lG, SA and GMV (r = 0.349/0.534/0.542, respectively), but not CT. Sulcal morphology associations were non-significant. Structural brain similarity in lG, SA and GMV were specific to mother-child pairs. Furthermore, structural brain similarity for SA and GMV was higher compared to CT.
Conclusion
Intergenerational neuroimaging techniques promise to enhance our knowledge of familial transfer effects on brain development and disorders.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Psychology
06 Faculty of Arts > Jacobs Center for Productive Youth Development
Dewey Decimal Classification:370 Education
Scopus Subject Areas:Life Sciences > Cognitive Neuroscience
Uncontrolled Keywords:Cognitive Neuroscience
Language:English
Date:1 February 2022
Deposited On:25 Feb 2022 14:05
Last Modified:27 Apr 2024 01:35
Publisher:Elsevier
ISSN:1878-9293
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1016/j.dcn.2022.101058
  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)