Redundancy as a neuroprotective mechanism against aging-related cognitive decline

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Recent years have seen a significant increase in the proportion of elderly individuals in the United States. This increase is translated to a growing prevalence of aging-related cognitive decline and mild cognitive impairment (MCI), leading to substantial individual and societal burden. Despite increasing research interest, the mechanisms that underlie aging-related cognitive decline remain poorly understood. In particular, it remains unknown why certain individuals are more susceptible to the adverse consequences of cognitive aging, while others appear to be protected from the same effects. A possible mechanism which may explain vulnerability to and resilience against the effects of aging on cognitive decline is redundancy. This design principle refers to the existence of duplicate elements within a system, which provide alternative functionality in case of failure. While numerous studies in systems engineering and biology have focused on the role of redundancy in artificial and organic systems, an empirical examination of redundancy as a possible neuroprotective mechanism against aging-related cognitive decline has not been conducted to date. The objective of the current study is to test if redundancy in functional and structural brain networks protects against aging-related cognitive decline and MCI. To that end, we will analyze cross-sectional and longitudinal neuroimaging and phenotypic data from existing large-scale datasets, where structural, diffusion and functional magnetic resonance imaging data were obtained, together with a battery of tests and scales tapping cognitive function. In Aim 1 of the study we will test the association between redundancy in large-scale functional and structural networks and performance in cognitive control and executive function tests across multiple age groups (ages 35 to 85). We hypothesize that in older subjects, redundancy will be associated with superior performance in measures of cognition. Further along the spectrum of cognitive decline are elderly individuals with MCI. Thus, in Aim 2, we will use cross-sectional neuroimaging data to test if subjects with MCI display altered network redundancy relative to normal controls in functional and structural networks. Finally, to establish if redundancy is neuroprotective against cognitive decline and MCI, in Aim 3 we will analyze longitudinal neuroimaging data, testing whether longitudinal changes in cognition are accompanied by corresponding changes in network redundancy, and whether network redundancy is predictive of future changes in cognitive function. Altogether, the study sets out to determine if aging-related cognitive decline relates to redundancy in structural and functional brain substrates. In doing so, this study aims to offer mechanistically vital information on human aging and the possible causes of aging-related cognitive decline.