The high prevalence of autism spectrum disorder (ASD) results in large costs to individuals, families, and society. Among diagnosed individuals, restrictive and repetitive behaviors (RRBs) correlate with functional impairments substantially impacting wellbeing but remain less studied than social and communication deficits. Brain resting-state functional connectivity (fc) measures intrinsic, potentially RRB-associated neural dynamics. Here, whole-brain (WB), and iterated seed-based (SB)fc guided by the preceding WBfc and a priori hypotheses was performed. Combined results were used to model a brain network beginning with qualitative assessment of its potential functional association with RRBs. Once rigorously defined, the network was used to inform construction of a dynamical systems model of brain activity hypothesized to correlate with RRB severity. Qualitative model behavior tracked expectations of real cortical activity in RRB presentation. Model numerical output was found to correlate with behavioral measures of RRBs to a significantly greater degree than the underlying brain connectivity values themselves did. Some summary measures of model output were also found to correlate significantly, though near threshold, with severity measures in the other two ASD core deficit domains, and particularly, far more extensively than should be expected given the underlying brain connectivity values themselves were apparently effectively wholly uncorrelated with the measures. Significant findings are: (1) dynamical modeling of brain activity can identify significant correlations with symptom manifestation that fc alone cannot; (2) dynamical modeling of brain activity could potentially increase understanding of ASD’s extensive heterogeneity across symptom domains; (3) extensive overlap between the constructed network and known RRB-implicated brain divisions was identified, with cerebellum, increasingly implicated in distributed neocortical functional differences in RRBs in humans and animal models, centrally connected to multiple such divisions; (4) further overlap is found via striatal circuitry, implicated in multiple RRB-like behaviors previously, and forming at least 1/3 of the functional basis for the network’s hypothetical relationship with RRBs; (5) ASD-associated angular gyrus, PFC, ACC overlap was found. This successful tandem application of fc, dynamical modeling, and neurocognitive network theory illustrates the need for broad theoretical approaches in illuminating ASD heterogeneity and the neurocognitive underpinnings of specific ASD presentations. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2021. / FAU Electronic Theses and Dissertations Collection