Date of Award

Fall 1-1-2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Biomedical Engineering (ENAS)

First Advisor

Scheinost, Dustin

Abstract

In early infancy, the human brain undergoes rapid network construction and remodeling. Advances in neuroimaging have made non-invasive, in-vivo observation of these brain changes possible during the perinatal period. However, how the brain develops to support dynamic activity and cognitive function remains unclear. In this thesis, I leverage the network control theory to model brain controllability - the capacity to drive activity changes - and examine its role in neurodevelopment. I first outline the developmental trajectories of controllability during the perinatal period and link them to synaptogenesis with cross-species models. Next, I introduce a machine-learning framework to explore how white matter connections at birth support emerging social and language functions. Additionally, I investigate individual deviations from normative brain development, highlighting environmental impacts and influences on long-term cognitive outcomes. Together, our findings illuminate the development of structural connectome controllability during the perinatal period. Early-life trajectories of brain development shape the neurobiological pathways underlying cognitive functions, while on the individual level, deviations from these trajectories are associated with early maternal exposures and later behavioral outcomes.

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