Characterising structural brain development trajectories between childhood and adulthood and their relationship with mental health outcomes

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Identifying brain development trajectories between childhood and adulthood is a core task in neuroscience. Although recent evidence has provided insight into trajectories of brain development at the group-level, inter-individual differences in structural brain changes during adolescence remain poorly understood (1). Two main factors have impeded progress in this research area: 1) a paucity of high-resolution temporal neuroimaging data, precluding our ability to characterise protracted individual changes in brain structure over time, and 2) the use of linear modelling techniques to capture structural brain changes that are known to be non-linear, such as cortical thickness (1-3). To address these limitations, recent studies have begun to use novel modelling techniques to delineate brain maturation at the individual level (2, 3). Fuhrmann et al. (2022) demonstrate that changes in cortical thickness during adolescence can be quantified with precision across individuals and brain regions by fitting a non-linear mixed model to a 12-wave neuroimaging dataset. This approach allowed for the extraction of a novel parameter of structural brain development, the midpoint of cortical thinning (MCT), referring to the time-point in adolescence where cortical thinning is most rapid. The MCT showed differences of several years between individuals. This raises the question of whether different environmental factors influence the pace of brain maturation, as well as how the pace of brain maturation relates to future mental health outcomes (1, 4). The current PhD project aims to address this gap in the literature, using non-linear modelling approaches and emerging longitudinal datasets (i.e., HUBU, N = 90 (5), Adolescent Brain and Cognitive Development Study/ABCD, N ~ 11,000)(6) to characterise individual trajectories of structural brain development (i.e., cortical thickness, white matter development). This PhD project will identify important environmental predictors and mental health outcomes of inter-individual variability in the pace of cortical thinning. This will advance current methodological approaches in the field, inform theory development, and, ultimately, guide future prevention work.This PhD project aims to 1) characterise inter-individual variability in structural brain development from childhood to adulthood, and 2) identify important predictors and outcomes of structural brain development trajectories. Four projects will be conducted, examining the following four research questions: 1) Do developmental trajectories of white matter integrity differ between individuals and white matter tracts? 2) Do developmental trajectories of cortical thickness and white matter myelination differ between individuals and brain regions? 3) How does socio-economic deprivation relate to mental health outcomes later in development?4) Is there a developmental cascade where environmental stressors predict inter-individual variability in the pace of brain development, which, in turn, predict mental health outcomes?