Exploring Cognitive Aging Using Reference Ability Neural Networks

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DESCRIPTION (provided by applicant): It has been repeatedly demonstrated that performance across the age span on large batteries of diverse cognitive tests can be parsimoniously represented by a set of four reference abilities: episodic memory, perceptual speed, fluid ability, and vocabulary. Based on these findings, Salthouse et al. have argued that a productive and efficient approach to cognitive aging research is to try to understand how aging impacts performance of this small set of reference abilities than on specific tasks. In contrast, neuroimaging researchers typically evaluate age differences in neural activation associated with the performance of a single specific task that may or may not be fully representative of these reference abilities. We propose to identify the latent brain networks associated with each of Salthouse's 4 reference abilities across adulthood. While undergoing functional imaging, we will test 375 healthy adults (50 per decade from age 20 to 50, 75 per decade for 50 to 80) with a series of 12 cognitive tasks that represent four reference abilities (3 per construct). Using unique expertise in spatial covariance and other analyses of the fMRI imaging data, we will derive the latent spatial, brain-wide fMRI networks that are associated with the latent cognitive structure of the reference abilities across adulthood. Successful identification of these "reference ability neural networks" may lead to a paradigm shift in research on the neural bases of age differences in cognition by focusing on the broad and replicable aspects common to several tasks rather than the possibly idiosyncratic features of individual tasks. After identifying these reference ability neural networks, we will use multimodal imaging to evaluate potential mediators of age-related differences in the utilization of the networks. These potential mediators will include change in brain volume and cortical thickness; white matter hyperintensity burden; integrity of white matter tracts; resting CBF; and the default network. The proposed fMRI study will develop a completely new and more focused imaging approach to the study of cognitive aging. In combination with the multimodal imaging of age-related brain changes and pathology, this project has the potential to provide key insights into the nature and causes of the neural changes that underlie cognitive aging.