During adolescence, the human brain undergoes marked structural and functional refinements to support rapid cognitive and behavioral development. However, the relationship between developing white matter architecture and emergent functional connectivity remains poorly understood. It is imperative to elucidate developmental mechanisms underlying structure-function coupling in youth, as devastating mental disorders such as psychosis have been linked to the disruption of evolving brain connectivity during this epoch. Specifically, psychosis has been characterized by the anomalous functional integration of brain processes. This could result from the aberrant wiring of white matter connections during brain development, from aberrant processes of functional plasticity (activity-dependent myelination of axons linking neurons within functionally-relevant circuits), or both. This proposal will apply cutting-edge network science and machine learning tools to longitudinal neuroimaging and rich clinical phenotyping data acquired as a part of the Philadelphia Neurodevelopmental Cohort (n=503, ages 9-25 years old), a large community-based study of brain development. Moreover, the goal of this proposal is to (1) systematically characterize whether structural connectivity drives developmental changes in functional connectivity within brain modules, or vice versa, and (2) identify abnormalities of structure-function coupling associated with the longitudinal burden of psychosis spectrum symptoms. This work will test the overarching hypothesis that structural connectivity precedes and drives developmental changes in functional connectivity within distinct brain modules, and further, that the aberrant development of structure-function coupling will be associated with increased burden of psychosis spectrum symptoms. Successful completion of the proposed aims will provide critical new insights regarding both typical brain maturation and the neurodevelopmental etiology of psychosis. Notably, as diverse types of psychopathology are increasingly linked to atypical brain maturation, findings generated by this study could lead to earlier diagnosis and enhanced treatment for individuals at risk for developing mental disorders.
It remains largely unknown how human white matter connectivity develops during adolescence to support brain function, and how abnormalities of structure-function coupling during this critical period may presage major psychiatric illnesses such as psychosis. By applying sophisticated network science and machine learning tools to longitudinal diffusion and functional neuroimaging data (n=503, ages 9-25 years), this study will provide important new insights regarding both healthy brain maturation and the neurodevelopmental underpinnings of psychosis. The findings generated by this study may allow for the development of earlier and more effective treatments for psychosis, which would benefit public health by reducing the great disability and cost associated with psychosis in youth.
