Even in the absence of disease, healthy human aging is characterized by changes in broad domains of cognitive function. Behavioral constructs representing executive control, speed of processing, and long-term memory begin to decline as early as the third decade of life, whereas ability in other constructs representing verbal aptitude and world knowledge can exhibit maintenance and in some cases increases throughout later adulthood. These cognitive abilities are mediated by information processing across distributed brain areas that interact in a large-scale brain network. Accordingly, many influential ideas in aging research have often directly or indirectly invoked metaphors referring to networks to characterize and explain age-related brain and behavioral changes (e.g., ‘scaffolds’, ‘reserve’, ‘efficiency’, ‘disconnection’, ‘dis-integration’). Despite the intuitive appeal of thinking about age-related changes as a process of changes in the brain network, the absence of a formal framework for studying aging networks has prohibited deep exploration of age-related cognitive decline (and maintenance) from a network-based systems neuroscience perspective.
A number of observations suggest that aging brain networks may share features comparable to other real-world networks that make them simultaneously efficient but also vulnerable to sudden, ostensibly unpredictable events that can render the network disabled. For example, healthy aging is accompanied by progressive anatomical and functional degradation. While some of these changes mirror changes in cognitive ability, it is clear that some individuals are able to tolerate seemingly comparable burden more gracefully than others. Do the progressive changes that accompany healthy aging result in subtle changes in brain network organization? If so, might those individuals that are able to harbor greater age-related degeneration exhibit greater fault tolerance in their brain networks? Conversely, might sudden cognitive decline that seems to inflict some individuals be best understood in terms of a ‘tipping-point’ that follows continuous network insult?
The goal of my research program is to develop and apply a formal network-analysis approach towards studying the healthy aging brain and its changing cognitive abilities. This goal relies on the application of mathematical approaches such as graph theory to measurements of brain connectivity derived from functional brain imaging (both at rest and during task performance). Combining observations from single individuals scanned across multiple time points (longitudinal data) with observations from large groups of individuals spanning the adult lifespan (cross-sectional data), we will describe the changes in areal brain network organization across the healthy adult lifespan. This information will be integrated with additional imaging-based brain measurements (e.g., grey matter thickness, white matter integrity, amyloid- and tau-protein deposition) to understand the impact of focal changes in measurements of brain integrity to changes in network organization, and their joint relationship to changes in cognitive ability. As a final objective for this program of research, the network-framework of aging will be used to guide initial studies aimed at understanding age-related changes in information processing. By thoroughly characterizing age related brain-network and cognitive change in health, we hope to take initial steps towards creating well-described points of reference for understanding age-related disease.