Time-varying Sources and Vascular Contributions to Age-accompanied Functional Brain Network Re-organization

The brain is a complex network of interacting brain areas that can be further divided into segregated functional systems. Resting-state system segregation is a feature of brain network organization that has relevance to brain function in both health and disease across adult lifespan. It is unclear what gives rise to system segregation and the individual differences in this brain network measure. In this dissertation, two aspects of this important question are investigated: (1) Do vascular factors contribute to relationships between age and system segregation across the adult lifespan? and (2) Can sources of time-varying information help account for relationships between aging and system segregation? The interplay between these questions reveals how the temporal evolution of system re-configuration at a short time scale impacts more stable individual features of large-scale network organization, in the context of differences in vascular health of adult individuals. This dissertation was accomplished by incorporating data from a total of 894 unique participants, over 3 independent studies (age range: 20 – 100 years) and including multiple neuroimaging modalities and measures of participant health and demographics. The contribution of vascular factors towards relationships between age and resting-state system segregation is first investigated. There exist relationships between age and vascular measures, including cardiovascular health (CVH) and cerebrovascular reactivity (CVR). Age-related decreases of system segregation persist after controlling for vascular-related variance. This is demonstrated by (i) computing system segregation regional CVR-corrected signals within each participant, and (ii) including CVH as a participant-level covariate in the models. These results demonstrate that age-related differences in system segregation cannot be fully attributed to differences in cerebrovascular and cardiovascular factors. To examine the contribution of time-varying information to system segregation, I examine the relationship between resting-state BOLD signal variability and system segregation. After controlling for vascular confounds by (i) estimating BOLD variability using CVR-corrected signals, (ii) including CVH as a covariate in the model, there is an absence of a relationship between age and BOLD variability, revealing that vascular factors serve as a major source of variance explaining previously reported relationships between age and resting-state BOLD signal variability. Further, with correction of vascular factors, BOLD variability does not relate to system segregation. An additional source of time-varying information is evaluated in relation to system segregation, focused on co-fluctuation amplitude of the resting-state time-series. Moments of greater co- fluctuation pattern across edges are identified (events), during which functional brain networks are highly modular relative to non-event moments. I demonstrate that the number of events that are present in an individual’s resting-state time-series is related to their system segregation. However, I next demonstrate that age-accompanied decreases of system segregation are evident across all the moments, irrespective of co-fluctuation amplitude of edges. Collectively, these findings reveal that while high co-fluctuation moments (events) may contribute towards establishing an individual’s system segregation, brain network re-organization exists across all time points of a resting-state scan. In sum, this dissertation provides important support that resting-state system segregation measures brain network re-organization across the adult lifespan. This measure is independent from vascular differences within individuals, and provides critical evidence of brain aging that is consistently evident across periods of rest. Serving as a biomarker of functional brain network integrity, system segregation further supports the application of this approach towards measuring individual brain health across the lifespan.