Diffusion tensor imaging (DTI) measures diffusion of molecular water, which can be used to calculate indices of white matter integrity. Early DTI studies of aging primarily focused on two global measures of integrity; the average rate (mean diffusivity, MD) and orientation coherence (fractional anisotropy, FA) of diffusion. More recent studies have added measures of water movement parallel (axial diffusivity, AD) and perpendicular (radial diffusivity, RD) to the primary diffusion direction, which are thought to reflect the neural bases of age differences in diffusion (i.e., axonal shrinkage and demyelination, respectively). In the present study, patterns of age differences in white matter integrity were assessed by comparing younger and healthy older adults on multiple measures of integrity (FA, AD, RD). Results revealed two commonly reported patterns (Radial Increase Only and Radial/Axial Increase), and one relatively novel pattern (Radial Increase/Axial Decrease) that varied by brain region and may reflect differential aging of microstructural (e.g., degree of myelination) and macrostructural (e.g., coherence of fiber orientation) properties of white matter. In addition, larger age differences in FA in frontal white matter were consistent with the anterior-posterior gradient of age differences in white matter integrity. Together, these findings complement other recent studies in providing information about patterns of diffusivity that are characteristic of healthy aging. KeywordsAging; axial diffusivity; DTI; fractional anisotropy; radial diffusivity Brain aging research has been dominated by examinations of age-related differences in the structure and function of gray matter (Cabeza, et al. 2005), with the other half of the brainwhite matter-having been largely ignored. The lack of attention to white matter aging in the past likely resulted from limitations in imaging technology, because the relatively recent Address correspondence to: Ilana J. Bennett, Georgetown University, Department of Psychology, 301 N White Gravenor Building, Washington, DC 20057, PH: 202-687-4099, FX: 202-687-6050, ijb5@georgetown.edu. Preliminary findings from this project were presented at the Society for Neuroscience Conferences in San Diego, CA in November, 2007 and Washington, DC in November, 2008; NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript advent of diffusion tensor imaging (DTI) has led to widespread in interest in age-related changes in white matter.DTI is a magnetic resonance imaging (MRI) technique that measures the diffusion of molecular water (Basser, et al. 1994;. Water diffuses 3-7 times more rapidly along the length of axons aligned in white matter tracts compared to movement perpendicular to the axons (Le Bihan 2003; because the latter is restricted by axonal cell membranes, myelin sheaths, and neurofilaments (Beaulieu 2002). Various properties of water diffusion can be calculated from DTI-based eigenvalue measures (λ1, λ2, and λ3; which indicate the rate of diffusion along the...

In this article we review recent research on diffusion tensor imaging (DTI) of white matter (WM) integrity and the implications for age-related differences in cognition. Neurobiological mechanisms defined from DTI analyses suggest that a primary dimension of age-related decline in WM is a decline in the structural integrity of myelin, particularly in brain regions that myelinate later developmentally. Research integrating behavioral measures with DTI indicates that WM integrity supports the communication among cortical networks, particularly those involving executive function, perceptual speed, and memory (i.e., fluid cognition). In the absence of significant disease, age shares a substantial portion of the variance associated with the relation between WM integrity and fluid cognition. Current data are consistent with one model in which age-related decline in WM integrity contributes to a decreased efficiency of communication among networks for fluid cognitive abilities. Neurocognitive disorders for which older adults are at risk, such as depression, further modulate the relation between WM and cognition, in ways that are not as yet entirely clear. Developments in DTI technology are providing new insight into both the neurobiological mechanisms of aging WM and the potential contribution of DTI to understanding functional measures of brain activity.

Cognition arises as a result of coordinated processing among distributed brain regions and disruptions to communication within these neural networks can result in cognitive dysfunction. Cortical disconnection may thus contribute to the declines in some aspects of cognitive functioning observed in healthy aging. Diffusion tensor imaging (DTI) is ideally suited for the study of cortical disconnection as it provides indices of structural integrity within interconnected neural networks. The current review summarizes results of previous DTI aging research with the aim of identifying consistent patterns of age-related differences in white matter integrity, and of relationships between measures of white matter integrity and behavioral performance as a function of adult age. We outline a number of future directions that will broaden our current understanding of these brain-behavior relationships in aging. Specifically, future research should aim to (1) investigate multiple models of age-brain-behavior relationships; (2) determine the tract-specificity versus global effect of aging on white matter integrity; (3) assess the relative contribution of normal variation in white matter integrity versus white matter lesions to age-related differences in cognition; (4) improve the definition of specific aspects of cognitive functioning related to age-related differences in white matter integrity using information processing tasks; and (5) combine multiple imaging modalities (e.g., resting-state and task-related functional magnetic resonance imaging; fMRI) with DTI to clarify the role of cerebral white matter integrity in cognitive aging.

The integrity of cerebral white matter is critical for efficient cognitive functioning, but little is known regarding the role of white matter integrity in age-related differences in cognition. Diffusion tensor imaging (DTI) measures the directional displacement of molecular water and as a result can characterize the properties of white matter that combine to restrict diffusivity in a spatially coherent manner. This review considers DTI studies of aging and their implications for understanding adult age differences in cognitive performance. Decline in white matter integrity contributes to a disconnection among distributed neural systems, with a consistent effect on perceptual speed and executive functioning. The relation between white matter integrity and cognition varies across brain regions, with some evidence suggesting that age-related effects exhibit an anterior-posterior gradient. With continued improvements in spatial resolution and integration with functional brain imaging, DTI holds considerable promise, both for theories of cognitive aging and for translational application.

Previous research has identified subcortical (caudate, putamen, hippocampus) and cortical (dorsolateral prefrontal cortex, DLPFC; frontal motor areas) regions involved in implicit sequence learning, with mixed findings for whether these neural substrates differ with aging. The present study used diffusion tensor imaging (DTI) tractography to reconstruct white matter connections between the known gray matter substrates, and integrity of these tracts was related to learning in the alternating serial reaction time task (ASRT) in younger and healthy older adults. Both age groups showed significant sequence learning (better performance to predictable, frequently occurring versus less frequent events), with an age-related difference in the late learning stage. Caudate-DLPFC and hippocampus-DLPFC tract integrity were related to ASRT sequence learning, and these brain-behavior relationships did not differ significantly between age groups. Additionally, age-related decreases in caudate-DLPFC tract integrity mediated age-related differences in late stage sequence learning. Together, these findings complement studies of gray matter substrates underlying implicit sequence learning, and provide evidence for similar white matter integrity-sequence learning relationships in younger and healthy older adults.

Accurate memory for discrete events is thought to rely on pattern separation to orthogonalize the representations of similar events. Previously, we reported that a behavioral index of pattern separation was correlated with activity in the hippocampus (dentate gyrus, CA3) and with integrity of the perforant path, which provides input to the hippocampus. If the hippocampus operates as part of a broader neural network, however, pattern separation would likely also relate to integrity of limbic tracts (fornix, cingulum bundle, and uncinate fasciculus) that connect the hippocampus to distributed brain regions. In this study, healthy adults (20-89 years) underwent diffusion tensor imaging and completed the Behavioral Pattern Separation Task-Object Version (BPS-O) and Rey Auditory Verbal Learning Test (RAVLT). After controlling for global effects of brain aging, exploratory skeleton-wise and targeted tractography analyses revealed that fornix integrity (fractional anisotropy, mean diffusivity, and radial diffusivity; but not mode) was significantly related to pattern separation (measured using BPS-O and RAVLT tasks), but not to recognition memory. These data suggest that hippocampal disconnection, via individual- and age-related differences in limbic tract integrity, contributes to pattern separation performance. Extending our earlier work, these results also support the notion that pattern separation relies on broad neural networks interconnecting the hippocampus.

Structural connections between brain regions are thought to influence neural processing within those regions. It follows that alterations to the quality of structural connections should influence the magnitude of neural activity. The quality of structural connections may also be expected to differentially influence activity in directly versus indirectly connected brain regions. To test these predictions, we reviewed studies that combined diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) in younger and older adults. By surveying studies that examined relationships between DTI measures of white matter integrity and fMRI measures of neural activity, we identified variables that accounted for variability in these relationships. Results revealed that relationships between white matter integrity and neural activity varied with (1) aging (i.e., positive and negative DTI-fMRI relationships in younger and older adults, respectively) and (2) spatial proximity of the neural measures (i.e., positive and negative DTI-fMRI relationships when neural measures were extracted from adjacent and non-adjacent brain regions, respectively). Together, the studies reviewed here provided support for both of our predictions.

Locus coeruleus (LC) and substantia nigra pars compacta (SNpc) degrade with normal aging, but not much is known regarding how these changes manifest in MRI images, or whether these markers predict aspects of cognition. Here, we use high-resolution diffusion-weighted MRI to investigate microstructural and compositional changes in LC and SNpc in young and aged cohorts, as well as their relationship with cognition. In LC, the older cohort exhibited a significant reduction in mean and radial diffusivity, but a significant increase in fractional anisotropy compared to the young cohort. We observed a significant correlation between the decrease in LC mean and radial diffusivities and measured examining delayed recall. This observation suggests that LC is involved in retaining cognitive abilities. In addition, we observed that iron deposition in SNpc occurs early in life and continues during normal aging. Since neuronal loss occurs in both LC and SNpc in Parkinson's disease, but occurs only in the LC in Alzheimer's disease, our results may lead to early stage imaging biomarkers for these diseases.