The quest for identification of brain mechanisms underlying the inexorable age-related decline in complex cognitive and motor functioning has recently shifted from single structures and loci to brain systems and circuits. Imaging studies have motivated this shift and have regularly confirmed that multiple brain regions are invoked to execute even ostensibly simple tasks. With this shift is the recognition of the relevance of connecting elements of brain circuitry and the possibility that disruption of the connections may be as effective as lesions in gray matter nodes in producing functional impairment. In parallel with the emphasis on neural systems has been the refinement of diffusion tensor imaging (DTI) as a non-invasive, in vivo method for characterizing the integrity of microstructure of brain white matter tissue and tracking of its fibers. With advancing age, waning brain integrity is especially notable in prefrontal regions. To maintain youthful performance levels, older individuals may recruit brain regions, often bilaterally distributed, not invoked by the young. Given the far-reaching circuitry of frontal systems, we speculate that the cerebellum may be an additional source of compensation for age-compromised executive or attentional functions. DTI and MRI coupled with probes of cognitive and motor functions selectively degraded in aging provides a powerful approach for identifying white and gray matter substrates of functional declines. Building on our prior studies, we will apply a regression model of aging to quantitative neuroimaging and neuropsychological data to identify regions of brain microstructure and macrostructure underlying age-related decline in attention and working memory. We will recruit, scan, and test healthy men and women, 50 to 90 years old, carefully screened for conditions that can impair function or disturb brain structure. We propose to test three principal hypotheses of aging brain structure and function: the anteroposterior gradient of aging, bilateral recruitment of brain systems via the corpus callosum for frontally-based task execution, and frontocerebellar synergism.
The specific aims of this revised proposal are to 1. Specify loci and quantify extent of age-related degradation of the corpus callosum and its regional connections to frontal and parietal white matter systems using DTI;2. Identify selective functional correlates of degradation of the microstructure of prefrontal, parietal, and callosal white matter systems in the aging brain;3. Quantify age-related decline in integrity of the cerebellum, prefrontal and parietal cortices, and frontocerebellar connections and specify functional correlates of structural degradation;4. Initiate longitudinal 4-year follow-up data collection to test hypotheses regarding selective accelerated deterioration of frontally-based brain systems in normal aging.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
5R01AG017919-09
Application #
7626298
Study Section
Cognition and Perception Study Section (CP)
Program Officer
Wagster, Molly V
Project Start
2000-06-15
Project End
2011-05-31
Budget Start
2009-06-01
Budget End
2010-05-31
Support Year
9
Fiscal Year
2009
Total Cost
$380,326
Indirect Cost
Name
Stanford University
Department
Psychiatry
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
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Pfefferbaum, Adolf; Rohlfing, Torsten; Rosenbloom, Margaret J et al. (2012) Combining atlas-based parcellation of regional brain data acquired across scanners at 1.5 T and 3.0 T field strengths. Neuroimage 60:940-51
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Sullivan, Edith V; Pfefferbaum, Adolf; Rohlfing, Torsten et al. (2011) Developmental change in regional brain structure over 7 months in early adolescence: comparison of approaches for longitudinal atlas-based parcellation. Neuroimage 57:214-24
Pfefferbaum, Adolf; Chanraud, Sandra; Pitel, Anne-Lise et al. (2011) Cerebral blood flow in posterior cortical nodes of the default mode network decreases with task engagement but remains higher than in most brain regions. Cereb Cortex 21:233-44

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