Exploring Cognitive Aging Using Reference Ability Neural Networks

项目总结:

PROJECT SUMMARY: This study focus on the optimal functional and structural imaging characterization of the cognitive aging and preclinical Alzheimer's disease (AD). 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. 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. 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. We have identified the latent brain networks associated with each of the four reference abilities across adulthood. While undergoing functional imaging, we tested large group of healthy adults aged 20 to 80 with a series of 12 cognitive tasks that represent the four reference abilities (3 per construct). Using unique expertise in spatial covariance and other analyses of the fMRI imaging data, we have derived 4 latent spatial, brain-wide fMRI networks that are associated with the latent cognitive structure of the reference abilities across adulthood. We are presently following up this group at 5 years and beginning to delineate how expression of these networks changes with aging and with the onset of mild cognitive impairment and AD. We use multimodal imaging to evaluate potential mediators of age and dementia-related differences in the utilization of the networks. These include change in brain volume, cortical thickness, white matter hyperintensity burden; integrity of white matter tracts; resting CBF; and resting BOLD networks. Importantly, we use PET to assess amyloid and tau burden. We now propose to extend the follow up of this important cohort to 10 years. The proposed study develops a completely new imaging approach to the study of cognitive aging and preclinical AD and is also unique in its age span. It has the potential to provide key insights into the nature and causes of the neural changes that underlie cognitive aging and to more accurately describe the preclinical phase of AD.