The brain requires a consistent supply of oxygenated blood to meet its high metabolic energy demands. Through a process termed neurovascular coupling, neural activity increases local cerebral blood flow to meet regional metabolic energy demands. Functional magnetic resonance imaging (fMRI) is a non-invasive tool capable of indirectly quantifying brain activity through the blood oxygenation level dependent (BOLD) response. Interestingly, spatially distinct brain regions that are functionally connected while performing a task maintain their synchronized BOLD response time courses at baseline in the absence of a task. Regions that exhibit these highly correlated BOLD responses at rest are grouped together and referred to as a resting state network (RSN). Studies that focus on resting-state fMRI (rs-fMRI), a task-free adaptation of fMRI, have found RSNs to hold predictive power in a wide range of neurodevelopmental and neurodegenerative disorders. However, there are no set standards for conducting rs-fMRI research. Further investigation into optimizing rs-fMRI methodology is beneficial to ensure reproducibility of results, particularly those of clinical significance. To assist with this, this dissertation will examine the effects of various rest conditions used during rs-fMRI data acquisition on RSN functional connectivity and introduce a novel age-appropriate functional atlas for older adults. Rest conditions can vary between studies. This often includes entirely different sets of instructions to the subjects which can impact the data. Aim 1 of this dissertation investigates the effects of rest conditions with differing levels of cognitive load on a complete set of predefined RSNs. Rs-fMRI datasets were obtained from twenty-two healthy college students (22 ± 4 years old, 12 females) on a 3T MRI scanner. Each subject was scanned under four different conditions: (1) eyes open in dim light (Eyes-Open), (2) eyes closed and awake (Eyes-Closed), (3) eyes closed while remembering four numbers through the scan session (Eyes-Closed-Number) and (4) asked to watch a movie (Movie). Overall, we found conditions with more external stimulation led to more global changes in functional connectivity during rs-fMRI. However, when considering each RSN of an existing functional atlas individually, there were differential changes between conditions. The results of this study can aid in future study interpretation and design. Next, we address the disproportion of functional atlases available for older adults. A functional atlas is a predefined set of recognizable RSNs that can be used to define regions in studies with subjects of a similar demographic. Most functional atlases that are currently available were derived from young and healthy populations. While often used to study RSNs in older adults, these atlases do not account for age-related brain atrophy and changes in RSN connectivity. Here, our goal was to use the baseline anatomical and rs-fMRI scans from the recently completed Risk Reduction for Alzheimer’s Disease (rrAD) clinical trial to create a robust functional atlas that is better-matched to study older populations. The rrAD sample is comprised of 420 hypertensive older adults (60 to 84 years, 68.8±5.9) scanned across five different 3T MRI scanners. Using a combination of seed-based and data-driven approaches, we created a functional atlas of recognizable RSNs that more adequately describes RSN functional connectivity of the rrAD cohort. We expect the rrAD420 rs-fMRI atlas to be directly applicable to study outcomes related to the functional connectivity of the rrAD population. However, we also believe the rrAD420 functional atlas would also be a suitable option for older populations in general. As such, our functional atlas can assist in the identification of RSN deviations with potential to serve as age-related biomarkers of disease in the future
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