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From parent to child: Intergenerational transmission of neural networks during language comprehension and calculation
Poster Session B, Friday, September 12, 4:30 - 6:00 pm, Field House
Chanyuan Gu1, Yi Wei2, Florence Bouhali3, Roeland Hancock4, Fumiko Hoeft1,5; 1University of Connecticut, 2University of Maryland, 3Aix-Marseille University, 4Yale University, 5Keio University
Competencies in language comprehension and calculation are essential for academic achievement. Previous work has demonstrated associations between children’s and parents’ abilities in these domains, reflecting intergenerational transmission (IGT) from parents to children. Despite behavioural evidence, the neural mechanism of IGT remains largely unknown. The hypothesis of functional specificity posits that the engagement of brain networks varies with cognitive functions. Building on this hypothesis, we aimed to test whether IGT displays network-specific patterns aligning with the demands of each domain. Furthermore, given emerging evidence of greater maternal than paternal IGT, we also investigated whether the parent’s gender influences IGT. The present study included 54 children aged 8–12 and 90 adults, comprising 54 mother-child and 54 father-child dyads, who listened to spoken stories and performed aurally presented calculation tasks in the MRI. Our data analytics hinge on the premise that linguistic and mathematical information is similarly represented in the brain across parents and children, allowing us to quantify fine-scale IGT. To this aim, we investigated spatial similarity within left and right-hemispheric functional networks of interest. Given the involvement of the language network (LN) in language comprehension and of the control network (CN) in mathematical processing respectively, we anticipated greater IGT in LN during language comprehension and in CN during calculation. We first established significant behavioral IGT across neuropsychological assessments of language and mathematics. Second, we observed significant IGT across both tasks, evidenced by significantly greater spatial similarity in parent-child dyads than unrelated adult-child pairs. Specifically, significant IGT was observed during language comprehension in the right LN (r = .14, p = .012) and CN (r = .06, p = .026). Additionally, IGT was found across both tasks in the left auditory (story: r = .10, p = .012; math: r = .12, p = .048), left visual (story: r = .03, p = .012; math: r = .04, p =.048), and right visual networks (story: r = .03, p = .048; math: r = .04, p = .009). We further trained a classifier to distinguish multivariate activations of stories and calculations across parents and children. The classifier revealed that this task distinction was similarly represented between parents and children in the right LN and CN. Third, we identified mother-child and father-child IGT in aforementioned brain networks across both tasks. We further quantified maternal-specific and paternal-specific IGT by controlling for the effect of the other parent. Results revealed (marginally) significant maternal-specific IGT in the right LN and CN during language comprehension, as well as in the right visual network and left auditory network across both tasks. In contrast, paternal-specific IGT did not reach significance. Collectively, this study reinforces evidence of parent-offspring IGT by uncovering its neurobiological basis across multiple brain networks, cognitive tasks, and both maternal and paternal contributions. To further disentangle the genetic and environmental influences, an ongoing analysis using a twin dataset will be used to substantiate these findings. Together, this work enriches our understanding of the familial role in shaping the neural underpinnings of child development across cognitive domains.
Topic Areas: Language Development/Acquisition, Genetics