Date of Award

Spring 5-15-2020

Author's School

Graduate School of Arts and Sciences

Author's Department


Degree Name

Doctor of Philosophy (PhD)

Degree Type



Considering individual differences in task activation functional magnetic resonance imaging (t-fMRI) can be challenging because they may arise from variability in activity in brain regions, in the tasks themselves, or some combination thereof. Delineating sources of between-subjects variance is particularly important for cognitive control where task goals are at the forefront. Here we applied structural equation modeling (SEM) to the Human Connectome Project to examine if activity could be partitioned into separable brain and task individual difference dimensions. A series of SEMs were defined with varying numbers of latent factors, where the inputs were parcels of two cognitive control-related brain networks measured during two cognitive control-related task paradigms. Model comparisons favored the SEM where each network and task were specified separately. The same analyses were repeated with additional higher-order brain networks and tasks, and still the best-fitting model had latent factors for each task and network. Brain networks and task contexts are thus critical sources of individual differences, especially in the realm of cognitive control, and the t-fMRI signal can be decoupled accordingly. We further discuss the ramifications of considering different aspects of neuroimaging signals when interrogating brain-behavior relationships.


English (en)

Chair and Committee

Todd S. Braver

Committee Members

Joshua J. Jackson, Deanna M. Barch, Patrick L. Hill, Janine Bijsterbosch,