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.
Diffusion weighted magnetic resonance imaging (DWI) data have been mostly acquired with single-shot echo-planar imaging (EPI) to minimize motion induced artifacts. The spatial resolution, however, is inherently limited in single-shot EPI, even when the parallel imaging (usually at an acceleration factor of 2) is incorporated. Multi-shot acquisition strategies could potentially achieve higher spatial resolution and fidelity, but they are generally susceptible to motion-induced phase errors among excitations that are exacerbated by diffusion sensitizing gradients, rendering the reconstructed images unusable. It has been shown that shot-to-shot phase variations may be corrected using navigator echoes, but at the cost of imaging throughput. To address these challenges, a novel and robust multi-shot DWI technique, termed multiplexed sensitivity-encoding (MUSE), is developed here to reliably and inherently correct nonlinear shot-to-shot phase variations without the use of navigator echoes. The performance of the MUSE technique is confirmed experimentally in healthy adult volunteers on 3 Tesla MRI systems. This newly developed technique should prove highly valuable for mapping brain structures and connectivities at high spatial resolution for neuroscience studies.
Many decisions are made under uncertainty; that is, with limited information about their potential consequences. Previous neuroimaging studies of decision making have implicated regions of the medial frontal lobe in processes related to the resolution of uncertainty. However, a different set of regions in dorsal prefrontal and posterior parietal cortices has been reported to be critical for selection of actions to unexpected or unpredicted stimuli within a sequence. In the current study, we induced uncertainty using a novel task that required subjects to base their decisions on a binary sequence of eight stimuli so that uncertainty changed dynamically over time (from 20 to 50%), depending on which stimuli were presented. Activation within prefrontal, parietal, and insular cortices increased with increasing uncertainty. In contrast, within medial frontal regions, as well as motor and visual cortices, activation did not increase with increasing uncertainty. We conclude that the brain response to uncertainty depends on the demands of the experimental task. When uncertainty depends on learned associations between stimuli and responses, as in previous studies, it modulates activation in the medial frontal lobes. However, when uncertainty develops over short time scales as information is accumulated toward a decision, dorsal prefrontal and posterior parietal contributions are critical for its resolution. The distinction between neural mechanisms subserving different forms of uncertainty resolution provides an important constraint for neuroeconomic models of decision making.
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.
Studies in experimental animals and humans have stressed the role of the cerebellum in motor skill learning. Yet, the relative importance of the cerebellar cortex and deep nuclei, as well as the nature of the dynamic functional changes occurring between these and other motor-related structures during learning, remains in dispute. Using functional magnetic resonance imaging and a motor sequence learning paradigm in humans, we found evidence of an experience-dependent shift of activation from the cerebellar cortex to the dentate nucleus during early learning, and from a cerebellar-cortical to a striatal-cortical network with extended practice. The results indicate that intrinsic modulation within the cerebellum, in concert with activation of motor-related cortical regions, serves to set up a procedurally acquired sequence of movements that is then maintained elsewhere in the brain.
As indicated by several recent studies, magnetic susceptibility of the brain is influenced mainly by myelin in the white matter and by iron deposits in the deep nuclei. Myelination and iron deposition in the brain evolve both spatially and temporally. This evolution reflects an important characteristic of normal brain development and ageing. In this study, we assessed the changes of regional susceptibility in the human brain in vivo by examining the developmental and ageing process from 1 to 83 years of age. The evolution of magnetic susceptibility over this lifespan was found to display differential trajectories between the gray and the white matter. In both cortical and subcortical white matter, an initial decrease followed by a subsequent increase in magnetic susceptibility was observed, which could be fitted by a Poisson curve. In the gray matter, including the cortical gray matter and the iron-rich deep nuclei, magnetic susceptibility displayed a monotonic increase that can be described by an exponential growth. The rate of change varied according to functional and anatomical regions of the brain. For the brain nuclei, the age-related changes of susceptibility were in good agreement with the findings from R2* measurement. Our results suggest that magnetic susceptibility may provide valuable information regarding the spatial and temporal patterns of brain myelination and iron deposition during brain maturation and ageing.
The core feature of an economic exchange is a decision to trade one good for another, based on a comparison of relative value. Economists have long recognized, however, that the value an individual ascribes to a good during decision making (i.e., their relative willingness to trade for that good) does not always map onto the reward they actually experience. Here, we show that experienced value and decision value are represented in distinct regions of ventromedial prefrontal cortex (VMPFC) during the passive consumption of rewards. Participants viewed two categories of rewards-images of faces that varied in their attractiveness and monetary gains and losses-while being scanned using functional magnetic resonance imaging. An independent market task, in which participants exchanged some of the money that they had earned for brief views of attractive faces, determined the relative decision value associated with each category. We found that activation of anterior VMPFC increased with increasing experienced value, but not decision value, for both reward categories. In contrast, activation of posterior VMPFC predicted each individual's relative decision value for face and monetary stimuli. These results indicate not only that experienced value and decision value are represented in distinct regions of VMPFC, but also that decision value signals are evident even in the absence of an overt choice task. We conclude that decisions are made by comparing neural representations of the value of different goods encoded in posterior VMPFC in a common, relative currency.
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