Graph Theory Analysis of Functional Brain Networks and Mobility Disability in Older Adults

Much research on the effects of aging on mobility has focused on muscle strength and cardiovascular fitness. However, considerable variability in mobility function remains after accounting for these factors. Recently, it has been proposed that changes in the brain and nervous system might account for some of this variability (1). Behavior and neuroimaging evidence points to a role for the cortex in mobility. Epidemiological studies show that gait speed correlates with cognitive function and that low gait speed or gait abnormalities may precede cognitive decline (2,3). Furthermore, increased cognitive demand, particularly in the domain of executive function, slows gait speed (4), suggesting shared brain resources supporting cognition and mobility. Structural neuroimaging studies suggest that the prefrontal cortex, which is associated with executive function, is important for mobility, along with frontoparietal sensorimotor regions, basal ganglia, and cerebellum (5–9). Lower regional brain volumes, including in frontoparietal, frontal, and sensorimotor regions, are associated with poorer gait speed, gait characteristics, and balance (5–9). Mobility involves coordination of regions across the brain, and damage to the connections between these regions may contribute to declining mobility function. White matter lesions arising from cardiovascular disease are associated with mobility impairment, especially when they are severe and located in frontal lobe (for review see Zheng and colleagues (10)). Importantly, associations between brain changes and mobility are observed in the absence of frank disease, indicating that brain changes are relevant to even healthy-appearing older adults and may occur early on in mobility decline. The strong links between white matter health and mobility suggest that brain connectivity is important for mobility function. However, analysis of structural connectivity cannot directly assess how functional connections in the brain differ with mobility impairment. Functional network analyses have the potential to identify alterations in brain function prior to the development of irreparable tissue damage. Graph theory analysis of functional brain imaging data exploits the complexity of brain connections to characterize the overall functional architecture of the brain network. Rather than ascertaining whether individual brain regions are associated with mobility disability, graph theory analysis treats the brain as one integrated network and asks whether the architecture of communication patterns within that network is altered when mobility is impaired. Here, we analyze functional magnetic resonance imaging data using graph theory (11) to assess differences in functional brain connections across participants with high, mid, and low mobility function determined by Short Physical Performance Battery (SPPB) score (12).