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.

Public Health Relevance

Adults over age 60 are the most rapidly growing segment of the population. More broadly, cognitive aging across the lifespan has profound implications for the health, quality of life and productivity of society. The proposed research program constitutes a major reevaluation of the methods and goals of the study of cognitive aging that should provide major new, integrative, and perhaps simplifying, insights into the neural basis of the most important and central features of cognitive aging.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
5R01AG038465-03
Application #
8526327
Study Section
Special Emphasis Panel (ZRG1-BBBP-E (03))
Program Officer
Wagster, Molly V
Project Start
2011-09-01
Project End
2016-05-31
Budget Start
2013-09-01
Budget End
2014-05-31
Support Year
3
Fiscal Year
2013
Total Cost
$909,186
Indirect Cost
$326,349
Name
Columbia University (N.Y.)
Department
Neurology
Type
Schools of Medicine
DUNS #
621889815
City
New York
State
NY
Country
United States
Zip Code
10032
Gazes, Yunglin; Bowman, F DuBois; Razlighi, Qolamreza R et al. (2016) White matter tract covariance patterns predict age-declining cognitive abilities. Neuroimage 125:53-60
Lee, Seonjoo; Habeck, Christian; Razlighi, Qolamreza et al. (2016) Selective association between cortical thickness and reference abilities in normal aging. Neuroimage 142:293-300
Habeck, C; Gazes, Y; Razlighi, Q et al. (2016) The Reference Ability Neural Network Study: Life-time stability of reference-ability neural networks derived from task maps of young adults. Neuroimage 125:693-704
Steffener, Jason; Habeck, Christian; O'Shea, Deirdre et al. (2016) Differences between chronological and brain age are related to education and self-reported physical activity. Neurobiol Aging 40:138-44
Steffener, Jason; Gazes, Yunglin; Habeck, Christian et al. (2016) The Indirect Effect of Age Group on Switch Costs via Gray Matter Volume and Task-Related Brain Activity. Front Aging Neurosci 8:162
Habeck, Christian; Steffener, Jason; Barulli, Daniel et al. (2015) Making cognitive latent variables manifest: distinct neural networks for fluid reasoning and processing speed. J Cogn Neurosci 27:1249-58
Salthouse, Timothy A; Habeck, Christian; Razlighi, Qolamreza et al. (2015) Breadth and age-dependency of relations between cortical thickness and cognition. Neurobiol Aging 36:3020-8
Gu, Yian; Razlighi, Qolamreza R; Zahodne, Laura B et al. (2015) Brain Amyloid Deposition and Longitudinal Cognitive Decline in Nondemented Older Subjects: Results from a Multi-Ethnic Population. PLoS One 10:e0123743
Huey, Edward D; Lee, Seonjoo; Brickman, Adam M et al. (2015) Neuropsychiatric effects of neurodegeneration of the medial versus lateral ventral prefrontal cortex in humans. Cortex 73:1-9
Stern, Yaakov; Habeck, Christian; Steffener, Jason et al. (2014) The Reference Ability Neural Network Study: motivation, design, and initial feasibility analyses. Neuroimage 103:139-51

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