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

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-c...

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Detalles Bibliográficos
Autores principales: Fehlbaum, Lynn V., Peters, Lien, Dimanova, Plamina, Roell, Margot, Borbás, Réka, Ansari, Daniel, Raschle, Nora M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8749220/
https://www.ncbi.nlm.nih.gov/pubmed/34999505
http://dx.doi.org/10.1016/j.dcn.2022.101058
Descripción
Sumario: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.