Diffusion tensor imaging of adult age differences in cerebral white matter: relation to response time.

Published

Journal Article

Diffusion tensor imaging (DTI) measures the displacement of water molecules across tissue components, thus providing information regarding the microstructure of cerebral white matter. Fractional anisotropy (FA), the degree to which diffusion is directionally dependent, is typically higher for compact, homogeneous fiber bundles such as the corpus callosum. Previous DTI studies in adults have demonstrated an age-related decline in white matter FA, but whether the relation between FA and behavioral performance varies as a function of age has not been determined. We investigated adult age differences in FA, and age-related changes in the relation between FA and response time (RT), in a visual target-detection task. The results confirmed that, independently of age, FA is higher in the corpus callosum than in other brain regions. We also observed an age-related decline in FA that did not vary significantly across the brain regions. For both age groups, a lower level of integrity of the cerebral white matter (as indexed by FA), in specific brain regions, was associated with slower responses in the visual task. An age-related change in this relation was evident, however, in that the best predictor of RT for younger adults was FA in the splenium of the corpus callosum, whereas for older adults the best predictor was FA in the anterior limb of the internal capsule. This pattern is consistent with measures of the task-related cortical activation obtained from these same individuals and suggests an age-related increase in the attentional control of responses mediated by corticostriatal or corticothalamic circuits.

Full Text

Duke Authors

Cited Authors

  • Madden, DJ; Whiting, WL; Huettel, SA; White, LE; MacFall, JR; Provenzale, JM

Published Date

  • March 2004

Published In

Volume / Issue

  • 21 / 3

Start / End Page

  • 1174 - 1181

PubMed ID

  • 15006684

Pubmed Central ID

  • 15006684

International Standard Serial Number (ISSN)

  • 1053-8119

Digital Object Identifier (DOI)

  • 10.1016/j.neuroimage.2003.11.004

Language

  • eng

Conference Location

  • United States