Neuroscience Program Seminar
Michigan State University
Metabolic health predicts differences in white matter microstructure and cognition in adulthood
Identifying relationships between neuroimaging parameters and cognition in population-based cohorts can be challenging for multiple reasons: the inherent heterogeneity in the population, the poor specificity of brain imaging parameters, or the insensitivity of standardized neuropsychological tests to more subtle variations in cognition. Because brain–cognition associations are more strongly manifest in the presence of pathological processes, population-based cohorts may afford sufficient statistical power to detect brain–cognition relationships that vary as a function of subclinical differences in physiological processes – i.e., physical health.
To address these issues, my research has incorporated neuroimaging methods chosen for increased specificity with alternative statistical modeling of neuropsychological tests to yield more sensitive markers of cognition that vary with physiological parameters in healthy adults. To achieve this, much of my work utilizes structural equation modeling to estimate cognition, brain parameters, and physiological health as latent factors – statistical composites free of measurement error. This approach permits modeling multivariate inter-relationships, estimating indirect effects for variance partitioning and characterizing the sample along multiple dimensions, and model/sample respecification for sensitivity analyses.
In this seminar, I present recent findings that demonstrate that associations between cerebral white matter microstructure and cognition – speeded processing, and verbal learning, vary as a function of metabolic health. Using data from a U.S.-based study of healthy aging in metro Detroit and a population-based cohort study of younger and older German adults in Berlin, I demonstrate that age and metabolic health exert independent and combined effects on white matter microstructure and cognition. These results show that metabolic health is associated with reduced white matter integrity, even in younger adulthood. Moreover, even subclinical increases in metabolic risk are associated with differences in white matter microstructure and poorer cognitive performance, and these effects are compounded by age-related declines.
Dr. Jim Galligan
Thursday, February 14, 2019 at 12:30pm
1425 BPS, East Lansing
This seminar is also available for viewing in 1102 A&B Grand Rapids Research Center