We describe the construction of a digital brain atlas composed of data from manually delineated MRI data. A total of 56 structures were labeled in MRI of 40 healthy, normal volunteers. This labeling was performed according to a set of protocols developed for this project. Pairs of raters were assigned to each structure and trained on the protocol for that structure. Each rater pair was tested for concordance on 6 of the 40 brains; once they had achieved reliability standards, they divided the task of delineating the remaining 34 brains. The data were then spatially normalized to well-known templates using 3 popular algorithms: AIR5.2.5's nonlinear warp (Woods et al., 1998) paired with the ICBM452 Warp 5 atlas (Rex et al., 2003), FSL's FLIRT (Smith et al., 2004) was paired with its own template, a skull-stripped version of the ICBM152 T1 average; and SPM5's unified segmentation method (Ashburner and Friston, 2005) was paired with its canonical brain, the whole head ICBM152 T1 average. We thus produced 3 variants of our atlas, where each was constructed from 40 representative samples of a data processing stream that one might use for analysis. For each normalization algorithm, the individual structure delineations were then resampled according to the computed transformations. We next computed averages at each voxel location to estimate the probability of that voxel belonging to each of the 56 structures. Each version of the atlas contains, for every voxel, probability densities for each region, thus providing a resource for automated probabilistic labeling of external data types registered into standard spaces; we also computed average intensity images and tissue density maps based on the three methods and target spaces. These atlases will serve as a resource for diverse applications including meta-analysis of functional and structural imaging data and other bioinformatics applications where display of arbitrary labels in probabilistically defined anatomic space will facilitate both knowledge-based development and visualization of findings from multiple disciplines.

We developed a novel brain atlas template to facilitate computational brain studies of Chinese subjects and populations using high quality magnetic resonance imaging (MRI) and well-validated image analysis techniques. To explore the ethnicity-based structural brain differences, we used the MRI scans of 35 Chinese male subjects (24.03±2.06yr) and compared them to an age-matched cohort of 35 Caucasian males (24.03±2.06yr). Global volumetric measures were used to identify significant group differences in the brain length, width, height and AC-PC line distance. Using the LONI BrainParser, 56 brain structures were automatically labeled and analyzed for all subjects. We identified significant ethnicity differences in brain structure volumes, suggesting that a population-specific brain atlas may be more appropriate for studies involving Chinese populations. To address this, we constructed a 3D Chinese brain atlas based on high resolution 3.0T MRI scans of 56 right-handed male Chinese volunteers (24.46±1.81yr). All Chinese brains were spatially normalized by using linear and nonlinear transformation via the “AIR Make Atlas” pipeline workflow within the LONI pipeline environment. This high-resolution Chinese brain atlas was compared to the ICBM152 template, which was constructed using Caucasian brains.

Background Hippocampal atrophy is a well reported feature of major depressive disorder, although the evidence has been mixed. The present study sought to examine hippocampal volume and subregional morphology in patients with major depressive disorder, who were all medication-free and in an acute depressive episode of moderate severity. Methods Structural magnetic resonance imaging scans were acquired in 37 patients (mean age 42 years) and 37 age, gender and IQ-matched healthy individuals. Hippocampal volume and subregional structural differences were measured by manual tracings and identification of homologous surface points to the central core of each hippocampus. Results Both right (P = 0.001) and left (P = 0.005) hippocampal volumes were reduced in patients relative to healthy controls (n = 37 patients and n = 37 controls), while only the right hippocampus (p = 0.016) showed a reduced volume in a subgroup of first episode depression patients (n = 13) relative to healthy controls. Shape analysis localised the subregional deformations to the subiculum and CA1 subfield extending into the CA2-3 subfields predominantly in the tail regions in the right (p = 0.017) and left (p = 0.011) hippocampi. Limitations As all patients were in an acute depressive episode, effects associated with depressive state cannot be distinguished from trait effects. Conclusions Subregional hippocampal deficits are present early in the course of major depression. The deformations may reflect structural correlates underlying functional memory impairments and distinguish depression from other psychiatric disorders.

Although structural changes of the basal ganglia are widely implicated in schizophrenia, prior findings in chronically medicated patients show that these changes relate to particular antipsychotic treatments. In unmedicated schizophrenia, local alterations in morphological parameters and their relationships with clinical measures remain unknown.Novel surface-based anatomical modelling methods were applied to magnetic resonance imaging data to examine regional changes in the shape and volume of the caudate, the putamen and the nucleus accumbens in 21 patients (19 males/2 females; mean age=30.7±7.3) who were either antipsychoticnaïve or antipsychotic-free for at least 1 year and 21 healthy comparison subjects (19 males/2 females; mean age=31.1±8.2). Clinical relationships of striatal morphology were based on exploratory analyses.Left and right global putamen volumes were significantly smaller in patients than controls; no significant global volume effects were observed for the caudate and the nucleus accumbens. However, surface deformation mapping results showed localized volume changes prominent bilaterally in medial/lateral anterior regions of the caudate, as well as in anterior and midposterior regions of the putamen, pronounced on the medial surface. A significant positive correlation was observed between right anterior putamen surface contractions and affective flattening, a core negative symptom of schizophrenia.The diagnostic effects of local surface deformations mostly pronounced in the associative striatum, as well as the correlation between anterior putamen morphology and affective flattening in unmedicated schizophrenia suggest disease-specific neuroanatomical abnormalities and distinct

There is some evidence of corpus callosum abnormalities in elderly depression, but it is not known whether these deficits are regionspecific or differ based on age at onset of depression. Twenty-four patients with early-onset depression (mean age ¼ 68.00, SD75.83), 22 patients with late-onset depression (mean age ¼ 74.50, SD78.09) and 34 elderly control subjects (mean age ¼ 72.38; SD76.93) were studied. Using 3D MRI data, novel mesh-based geometrical modeling methods were applied to compare the midsagittal thickness of the corpus callosum at high spatial resolution between groups. Neuropsychological correlates of midsagittal callosal area differences were additionally investigated in a subsample of subjects. Depressed patients exhibited significant callosal thinning in the genu and splenium compared to controls. Significant callosal thinning was restricted to the genu in early-onset patients, but patients with late-onset depression exhibited significant callosal thinning in both the genu and splenium relative to controls. The splenium of the corpus callosum was also significantly thinner in subjects with late-vs early-onset depression. Genu and splenium midsagittal areas significantly correlated with memory and attention functioning among late-onset depressed patients, but not early-onset depressed patients or controls. Circumscribed structural alterations in callosal morphology may distinguish late-from early-onset depression in the elderly. These findings suggest distinct abnormalities of cortical connectivity in late-and early-onset elderly depression with possible influence on the course of illness. Patients with a late onset of depression may be at higher risk of illness progression and eventually dementia conversion than earlyonset depression, with potentially important implications for research and therapy.