Amnestic mild cognitive impairment (aMCI) can be classified into single domain (S-aMCI) and multiple domain (M-aMCI) subtypes. However, there have been no studies that specifically investigate the structural differences that support this classification. In an attempt to compare regional cortical thickness in two subtypes of aMCI, we aimed to map the distribution of cortical thinning using a surface based cortical analysis of magnetic resonance imaging. The cortical thickness across the entire brain was measured in 9 patients with S-aMCI, 22 patients with M-aMCI, and 61 normal healthy subjects. Differences in the patterns of cortical thinning between S-aMCI and M-aMCI were assessed using ANCOVA on a vertex-by-vertex basis, and statistical maps of differences in cortical thickness between the groups were constructed using a surface model. Relative to controls, S-aMCI patients showed cortical thinning in the left medial temporal lobe, and M-aMCI patients showed cortical thinning in the left medial temporal lobe, precuneus, and anterior and inferior basal temporal, insular, and temporal association cortices. When the two MCI groups were directly compared, M-aMCI patients showed cortical thinning in left precuneus. Our studies suggest that M-aMCI is a transitional state between S-aMCI and Alzheimer's disease, and that the cortical thinning is evidence that the precuneus is responsible for the multiple cognitive impairments in M-aMCI.

We proposed pattern classification based on principal components of cortical thickness between schizophrenic patients and healthy controls, which was trained using a leave-one-out cross-validation. The cortical thickness was measured by calculating the Euclidean distance between linked vertices on the inner and outer cortical surfaces. Principal component analysis was applied to each lobe for practical computational issues and stability of principal components. And, discriminative patterns derived at every vertex in the original feature space with respect to support vector machine were analyzed with definitive findings of brain abnormalities in schizophrenia for establishing practical confidence. It was simulated with 50 randomly selected validation set for the generalization and the average accuracy of classification was reported. This study showed that some principal components might be more useful than others for classification, but not necessarily matching the ordering of the variance amounts they explained. In particular, 40-70 principal components rearranged by a simple two-sample t-test which ranked the effectiveness of features were used for the best mean accuracy of simulated classification (frontal: (left(%)|right(%))=91.07|88.80, parietal: 91.40|91.53, temporal: 93.60|91.47, occipital: 88.80|91.60). And, discriminative power appeared more spatially diffused bilaterally in the several regions, especially precentral, postcentral, superior frontal and temporal, cingulate and parahippocampal gyri. Since our results of discriminative patterns derived from classifier were consistent with a previous morphological analysis of schizophrenia, it can be said that the cortical thickness is a reliable feature for pattern classification and the potential benefits of such diagnostic tools are enhanced by our finding.

Fractal dimension (FD) has been widely used to provide a quantitative description of structural complexity in the cerebral cortex. FD is an extremely compact measure of shape complexity, condensing all details into a single numeric value. We interpreted the variation of the FD in the cortical surface of normal controls through multiple regression analysis with cortical thickness, sulcal depth, and folding area related to cortical complexity. We used a cortical surface showing a reliable representation of folded gyri and manually parcellated it into frontal, parietal, temporal, and occipital regions for regional analysis. In both hemispheres the mean cortical thickness and folding area showed significant combination effects on cortical complexity and accounted for about 50% of its variance. The folding area was significant in accounting for the FD of the cortical surface, with positive coefficients in both hemispheres and several lobe regions, while sulcal depth was significant only in the left temporal region. The results may suggest that human cortex develops a complex structure through the thinning of cortical thickness and by increasing the frequency of folds and the convolution of gyral shape rather than by deepening sulcal regions. Through correlation analysis of FD with IQ and the number of years of education, the results showed that a complex shape of the cortical surface has a significant relationship with intelligence and education. Our findings may indicate the structural characteristics that are revealed in the cerebral cortex when the FD in human brain is increased, and provide important information about brain development.

We have examined gender differences of cortical thickness using a 3-D surface-based method that enables more accurate measurement in deep sulci and localized regional mapping compared to volumetric analyses. Cortical thickness was measured using a direct method for calculating the distance between corresponding vertices from inner and outer cortical surfaces. We normalized cortical surfaces using 2-D surface registration and performed diffusion smoothing to reduce the variability of folding patterns and to increase the power of the statistical analysis. In stereotaxic space, significant localized cortical thickening in women was found extensively in frontal, parietal and occipital lobes, including the superior frontal gyrus (SFG), superior parietal gyrus (SPG), inferior frontal gyrus (IFG) and postcentral gyrus (PoCG) in the left hemisphere and mostly in the parietal lobe, including the SPG in the right hemisphere. In the temporal lobe, small regions of the left and right caudal superior temporal gyrus (STG) and the left temporal pole showed significantly greater cortical thickness in women. The temporal lobe shows relatively less significant thickening than other lobes in both hemispheres. In native space, significantly greater cortical thickness in women was detected in left parietal region, including SPG and PoCG. No significant local increases of cortical thickness were observed in men in both spaces. These findings suggest statistically significant cortical thickening in women in localized anatomical regions, which is consistent with several previous studies and may support a hypothesis of sexual dimorphism.