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Currently, one of the most challenging issues in modern neuroscience is learning-induced neural plasticity. Many researchers have identified activation-dependent structural brain plasticity in gray and white matter. The game of Baduk is known to require many cognitive processes, and long-term training in such processes would be expected to cause structural changes in related brain areas. We conducted voxel-based analyses of diffusion-tensor imaging (DTI) data and found that, compared to inexperienced controls, long-term trained Baduk players developed larger regions of white matter with increased fractional anisotropy (FA) values in the frontal, cingulum, and striato-thalamic areas that are related to attentional control, working memory, executive regulation, and problem-solving. In addition, inferior temporal regions with increased FA indicate that Baduk experts tend to develop a task-specific template for the game, as compared to controls. In contrast, decreased FA found in dorsolateral premotor and parietal areas indicate that Baduk experts were less likely than were controls to use structures related to load-dependent memory capacity. Right-side dominance in Baduk experts suggests that the tasks involved are mainly spatial processes. Altogether, long-term Baduk training appears to cause structural brain changes associated with many of the cognitive aspects necessary for game play, and investigation of the mechanism underpinning such changes might be helpful for improving higher-order cognitive capacities, such as learning, abstract reasoning, and self-control, which can facilitate education and cognitive therapies.

Analyzing gray matter diffusion properties can be challenging due to possible measurement biases originating from averaging of gray matter (GM) and cerebrospinal fluid (CSF) signals. Therefore, a better characterization of CSF contamination effects in different cortical regions is required in order to disentangle actual changes in microstructure of GM itself from changes due to other effects such as macroscopic morphological changes. We propose a localized analysis framework for the CSF contamination effect on GM mean diffusivity measurement and applied this framework to measurements on 15 subjects. Our proposed modeling framework was compared to fluid-attenuated inversion recovery (FLAIR) DTI technique from the same subjects. The results of our studies suggest that GM mean diffusivity value was significantly biased by the CSF contamination effect, and that the amount of contamination strongly depended on the local morphology of the peripheral brain. Expected biases had their maxima in the motor and the somatosensory association cortex, and their minima in mid and inferior temporal areas of the brain where the cortical thicknesses are particularly pronounced. We conclude from our studies that regional differences in tissue compounding ratio must be taken into account when assessing localized GF diffusivity differences.

Spatial smoothing is an important post-processing procedure that is used to increase the signal-to-noise ratio (SNR) of blood oxygenation level-dependent signals (BOLD) in common functional magnetic resonance imaging (fMRI) applications. However, recent studies have shown that smoothing artificially shifts probabilistic local maxima of fMRI activations. In this study, we show shifting of the localization of functional centers in hand motor areas of the cerebral cortex by three-dimensional isotropic Gaussian kernel smoothing or two-dimensional heat kernel smoothing in volume- and surface-based fMRI analyses. Activation maps derived from smoothed echo planar imaging (EPI) data by volume- and surface-based analyses were assigned to the nodes of individual cortical surface models, and local maxima in the primary motor area (M1) and the primary somatosensory cortex (S1) were compared with those derived from non-smoothed risk map analysis, which is commonly used in presurgical applications. For each analysis, the Euclidean and geodesic distances between the correlation coefficients of local maxima derived from smoothed and non-smoothed EPI data were measured. The results show that the correlation coefficients derived from the volume- and surface-based analyses were about 29.4% and 42.9% higher for smoothed than for non-smoothed risk map analyses, and show minimum shifting of localizations by 12.1 mm and 6.9 mm on average in Euclidean distance, respectively, and about 9.5 mm and 5.7 mm on average in geodesic distance, respectively.