Motivated by the vast amount of information that is rapidly accumulating about the human brain in digital form, we embarked upon a program in 1992 to develop a four-dimensional probabilistic atlas and reference system for the human brain. Through an International Consortium for Brain Mapping (ICBM) a dataset is being collected that includes 7000 subjects between the ages of eighteen and ninety years and including 342 mono-and dizygotic twins. Data on each subject includes detailed demographic, clinical, behavioural and imaging information. DNA has been collected for genotyping from 5800 subjects. A component of the programme uses post-mortem tissue to determine the probabilistic distribution of microscopic cyto-and chemoarchitectural regions in the human brain. This, combined with macroscopic information about structure and function derived from subjects in vivo, provides the ¢rst large scale opportunity to gain meaningful insights into the concordance or discordance in micro-and macroscopic structure and function. The philosophy, strategy, algorithm development, data acquisition techniques and validation methods are described in this report along with database structures. Examples of results are described for the normal adult human brain as well as examples in patients with Alzheimer's disease and multiple sclerosis. The ability to quantify the variance of the human brain as a function of age in a large population of subjects for whom data is also available about their genetic composition and behaviour will allow for the ¢rst assessment of cerebral genotype^phenotype^behavioural correlations in humans to take place in a population this large. This approach and its application should provide new insights and opportunities for investigators interested in basic neuroscience, clinical diagnostics and the evaluation of neuropsychiatric disorders in patients.

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.

Here we report on detailed three-dimensional maps revealing how brain structure is influenced by individual genetic differences. A genetic continuum was detected in which brain structure was increasingly similar in subjects with increasing genetic affinity. Genetic factors significantly influenced cortical structure in Broca's and Wernicke's language areas, as well as frontal brain regions (r2(MZ) > 0.8, p < 0.05). Preliminary correlations were performed suggesting that frontal gray matter differences may be linked to Spearman's g, which measures successful test performance across multiple cognitive domains (p < 0.05). These genetic brain maps reveal how genes determine individual differences, and may shed light on the heritability of cognitive and linguistic skills, as well as genetic liability for diseases that affect the human cortex.

Prior studies show positive correlations between full-scale intelligence quotient (FSIQ) and cerebral gray matter measures. Few imaging studies have addressed whether general intelligence is related to regional variations in brain tissue and the associated influences of sex. Cortical thickness may more closely reflect cytoarchitectural characteristics than gray matter density or volume estimates. To identify possible localized relationships, we examined FSIQ associations with cortical thickness at high spatial resolution across the cortex in healthy young adult (age 17-44 years) men (n = 30) and women (n = 35). Positive relationships were found between FSIQ and intracranial gray and white matter but not cerebrospinal fluid volumes. Significant associations with cortical thickness were evident bilaterally in prefrontal (Brodmann's areas [BAs] 10/11, 47) and posterior temporal cortices (BA 36/37) and proximal regions. Sex influenced regional relationships; women showed correlations in prefrontal and temporal association cortices, whereas men exhibited correlations primarily in temporal-occipital association cortices. In healthy adults, greater intelligence is associated with larger intracranial gray matter and to a lesser extent with white matter. Variations in prefrontal and posterior temporal cortical thickness are particularly linked with intellectual ability. Sex moderates regional relationships that may index dimorphisms in cognitive abilities, overall processing strategies, or differences in structural organization.

We mapped regional changes in cortical thickness and intensity-based cortical gray matter concentration in first episode schizophrenia. High-resolution magnetic resonance images were obtained from 72 (51 male, 21 female) first episode patients and 78 (37 male, 41 female) healthy subjects similar in age. Cortical pattern matching methods allowed comparisons of cortical thickness and gray matter concentration at thousands of homologous cortical locations between subjects in three dimensions. Principal components analyses reduced measures obtained across the cortex to identify global differences in cortical thickness/gray matter concentration. First principal component factor scores showed significant effects of diagnosis, sex and age for both cortical measures. Diagnosis and age effects remained significant after brain size correction. Cortical thickness and gray matter concentration values were highly correlated. Statistical maps showed significant regional gray matter thinning in frontal, temporal and parietal heteromodal association cortices bilaterally in first episode patients. Regional reductions in cortical gray matter concentration were similar but pronounced in the superior temporal lobe. Regional reductions in cortical thickness and gray matter concentration are present at disease onset in brain regions linked with functional disturbances in schizophrenia. Cortical thickness and gray matter concentration mapping produce similar results, although the concentration metric may be influenced by diagnostic differences in extra-cortical cerebrospinal fluid and surface curvature/complexity.

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Background Electroconvulsive therapy (ECT) elicits a rapid and robust clinical response in patients with refractory depression. Neuroimaging measures of structural plasticity relating to and predictive of ECT response may point to the mechanisms underlying rapid antidepressant effects and establish biomarkers to inform other treatments. Here, we determine the effects of 1) diagnosis and 2) ECT on global and local variations of hippocampal and amygdalar structure in major depression and predictors of ECT-related clinical response Methods Longitudinal changes in hippocampal and amygdala structure were examined in patients with major depression (N= 43, scanned thrice; prior to ECT, after the 2nd ECT session, and within one week of completing the ECT treatment series) referred for ECT as part of their standard clinical care. Cross-sectional comparisons with demographically similar controls (N= 32, scanned twice) established effects of diagnosis. Results Patients showed smaller hippocampal volumes compared to controls at baseline (p<.04). Both hippocampal and amygdalar volumes increased with ECT (p<.001) and in relation to symptom improvement (p<.01). Hippocampal volume at baseline predicted subsequent clinical response (p<.05). Shape analysis revealed pronounced morphometric changes in the anterior hippocampus and basolateral and centromedial amygdala. All structural measures remained stable across time in controls. Conclusions ECT induced neuroplasticity in the hippocampus and amygdala relates to improved clinical response and is pronounced in regions with prominent connections to ventromedial prefrontal cortex and other limbic structures. Smaller hippocampal volumes at baseline predict a more robust clinical response. Neurotrophic processes including neurogenesis shown in preclinical studies may underlie these structural changes.

The authors describe the development of a four-dimensional atlas and reference system that includes both macroscopic and microscopic information on structure and function of the human brain in persons between the ages of 18 and 90 years. Given the presumed large but previously unquantified degree of structural and functional variance among normal persons in the human population, the basis for this atlas and reference system is probabilistic. Through the efforts of the International Consortium for Brain Mapping (ICBM), 7,000 subjects will be included in the initial phase of database and atlas development. For each subject, detailed demographic, clinical, behavioral, and imaging information is being collected. In addition, 5,800 subjects will contribute DNA for the purpose of determining genotype- phenotype-behavioral correlations. The process of developing the strategies, algorithms, data collection methods, validation approaches, database structures, and distribution of results is described in this report. Examples of applications of the approach are described for the normal brain in both adults and children as well as in patients with schizophrenia. This project should provide new insights into the relationship between microscopic and macroscopic structure and function in the human brain and should have important implications in basic neuroscience, clinical diagnostics, and cerebral disorders.