Executive function (EF) undergoes dramatic development during adolescence, and is impaired across multiple psychiatric disorders such as ADHD and psychosis. Despite this fact, the neural substrates of EF development remain incompletely understood. Here, we propose to study the development of EF using cutting- edge techniques from network science. In this proposal, we will recruit 140 participants ages 10-16. This sample will include 50 with ADHD, 50 with psychosis-spectrum diagnoses, and 40 typically developing comparators. Using an accelerated longitudinal design, all participants will be followed and undergo cognitive testing, clinical assessment, and advanced multi-modal neuroimaging at 18 month intervals, yielding an average of 2.5 sessions per participant. This design will allow us to chart the development of structural and functional brain networks during adolescence, and delineate how abnormalities of brain network development are associated with deficits in EF performance, activation, and dynamics. Our overarching hypothesis is that the development of modular yet integrated brain networks during adolescence allows for specific patterns of EF activation and dynamics, and represents a fundamental mechanism for EF development. We posit that abnormalities of network development will be associated with executive dysfunction that is dimensionally present across psychiatric disorders such as ADHD and psychosis. Accordingly, in Aim 1 of this proposal, we will chart the longitudinal development of both structural and functional brain networks, and define how abnormalities of network development are associated with dimensional EF deficits in youth with ADHD and psychosis.
In Aim 2, we will define how abnormal development of brain network topology is associated with alterations of executive activation and dynamics.
In Aim 3, we will integrate high-dimensional imaging data using advanced multivariate analytic techniques to create a dimensional predictor of executive dysfunction. Finally, in Aim 4, we will share both raw and processed data, creating a valuable new resource for the neuroscience community. This proposal capitalizes on complementary skills of the PIs and the research team, including expertise in brain development, network science, psychopathology, cognitive science, and high dimensional imaging statistics. Through the proposed multi-level analysis, this innovative research will provide a substantial advance in our understanding of the neurodevelopmental substrates of executive dysfunction across psychiatric disorders in adolescence.
Executive function is an important domain of cognition that develops rapidly during adolescence, and is impacted by multiple psychiatric disorders including ADHD and psychosis. Greater understanding of how abnormalities in brain network development produce executive dysfunction in psychiatric disorders may be critical for the development of earlier and more effective treatments. This would benefit public health by reducing disability and limiting the costs to society at large.
|Sizemore, Ann E; Karuza, Elisabeth A; Giusti, Chad et al. (2018) Knowledge gaps in the early growth of semantic feature networks. Nat Hum Behav 2:682-692|
|Bassett, Danielle S; Xia, Cedric Huchuan; Satterthwaite, Theodore D (2018) Understanding the Emergence of Neuropsychiatric Disorders With Network Neuroscience. Biol Psychiatry Cogn Neurosci Neuroimaging 3:742-753|
|Xia, Cedric Huchuan; Ma, Zongming; Ciric, Rastko et al. (2018) Linked dimensions of psychopathology and connectivity in functional brain networks. Nat Commun 9:3003|
|Cornblath, Eli J; Tang, Evelyn; Baum, Graham L et al. (2018) Sex differences in network controllability as a predictor of executive function in youth. Neuroimage 188:122-134|
|Garcia, Javier O; Ashourvan, Arian; Muldoon, Sarah F et al. (2018) Applications of community detection techniques to brain graphs: Algorithmic considerations and implications for neural function. Proc IEEE Inst Electr Electron Eng 106:846-867|
|Gu, Shi; Yang, Muzhi; Medaglia, John D et al. (2017) Functional hypergraph uncovers novel covariant structures over neurodevelopment. Hum Brain Mapp 38:3823-3835|