The structure and function of the human brain are highly stereotyped, implying a conserved molecular program responsible for its development, cellular structure, and function. We applied a correlation-based metric of “differential stability” (DS) to assess reproducibility of gene expression patterning across 132 structures in six individual brains, revealing meso-scale genetic organization. The highest DS genes are highly biologically relevant, with enrichment for brain-related biological annotations, disease associations, drug targets, and literature citations. Using high DS genes we identified 32 anatomically diverse and reproducible gene expression signatures, which represent distinct cell types, intracellular components, and/or associations with neurodevelopmental and neurodegenerative disorders. Genes in neuron-associated compared to non-neuronal networks showed higher preservation between human and mouse; however, many diversely-patterned genes displayed dramatic shifts in regulation between species. Finally, highly consistent transcriptional architecture in neocortex is correlated with resting state functional connectivity, suggesting a link between conserved gene expression and functionally relevant circuitry.

The cerebral cortex of the human infant at term is complexly folded in a similar fashion to adult cortex but has only one third the total surface area. By comparing 12 healthy infants born at term with 12 healthy young adults, we demonstrate that postnatal cortical expansion is strikingly nonuniform: regions of lateral temporal, parietal, and frontal cortex expand nearly twice as much as other regions in the insular and medial occipital cortex. This differential postnatal expansion may reflect regional differences in the maturity of dendritic and synaptic architecture at birth and/or in the complexity of dendritic and synaptic architecture in adults. This expression may also be associated with differential sensitivity of cortical circuits to childhood experience and insults. By comparing human and macaque monkey cerebral cortex, we infer that the pattern of human evolutionary expansion is remarkably similar to the pattern of human postnatal expansion. To account for this correspondence, we hypothesize that it is beneficial for regions of recent evolutionary expansion to remain less mature at birth, perhaps to increase the influence of postnatal experience on the development of these regions or to focus prenatal resources on regions most important for early survival.T he human cerebral cortex is characterized by regional nonuniformities in cellular structure that change with age. Near term, there are regional variations in synaptic density (1, 2), dendritic length, and dendritic spine density (3). Postnatally, synaptic density increases dramatically, reaches a peak density in early childhood, and then undergoes synaptic pruning with a 2-fold or greater reduction (4). The time course of these synaptic changes differs across regions, with primary sensory areas attaining peak density and adult levels earlier than higher order "association" areas (2, 5). In adults, there are large regional nonuniformities in neuronal density (6), dendritic size, branching complexity, and spine density (7).This evidence for cellular nonuniformities provides grounds for anticipating regional differences in macroscopic aspects of postnatal cortical maturation. Indeed, studies of gray matter volume and overall brain growth provide evidence for complex regional patterns of morphological change during childhood and adolescence (8, 9). We recently used a surface-based approach to compare cortical structure in human term infants to adults. That analysis suggested that although many adult cortical shape characteristics are well established at birth, there may be regional differences in the maturity of cortical folding in term infants compared with adults (10).Comparisons with nonhuman primates, especially the intensively studied macaque monkey, provide another basis for evaluating regional differences in cortical maturation. Since the evolutionary divergence between humans and macaques ∼25 million years ago (11), cortical expansion has been far greater in human lineage than in the macaque lineage. Compared with the macaque cortex, the human c...

We report on surface-based analyses that enhance our understanding of human cortical organization, including its convolutions and its parcellation into many distinct areas. The surface area of human neocortex averages 973 cm(2) per hemisphere, based on cortical midthickness surfaces of 2 cohorts of subjects. We implemented a method to register individual subjects to a hybrid version of the FreeSurfer "fsaverage" atlas whose left and right hemispheres are in precise geographic correspondence. Cortical folding patterns in the resultant population-average "fs_LR" midthickness surfaces are remarkably similar in the left and right hemispheres, even in regions showing significant asymmetry in 3D position. Both hemispheres are equal in average surface area, but hotspots of surface area asymmetry are present in the Sylvian Fissure and elsewhere, together with a broad pattern of asymmetries that are significant though small in magnitude. Multiple cortical parcellation schemes registered to the human atlas provide valuable reference data sets for comparisons with other studies. Identified cortical areas vary in size by more than 2 orders of magnitude. The total number of human neocortical areas is estimated to be ∼150 to 200 areas per hemisphere, which is modestly larger than a recent estimate for the macaque.

The cerebral cortex is anatomically organized at many physical scales starting at the level of single neurons and extending up to functional systems. Current functional magnetic resonance imaging (fMRI) studies often focus at the level of areas, networks, and systems. Except in restricted domains, (e.g. topographically-organized sensory regions), it is difficult to determine area boundaries in the human brain using fMRI. The ability to delineate functional areas non-invasively would enhance the quality of many experimental analyses allowing more accurate across-subject comparisons of independently identified functional areas. Correlations in spontaneous BOLD activity, often referred to as resting state functional connectivity (rs-fcMRI), are especially promising as a way to accurately localize differences in patterns of correlated activity across large expanses of cortex. In the current report, we applied a novel set of image analysis tools to explore the utility of rs-fcMRI for defining wide-ranging functional area boundaries. We find that rs-fcMRI patterns show sharp transitions in correlation patterns and that these putative areal boundaries can be reliably detected in individual subjects as well as in group data. Additionally, combining surface-based analysis techniques with image processing algorithms allows automated mapping of putative areal boundaries across large expanses of cortex without the need for prior information about a region's function or topography. Our approach reliably produces maps of bounded regions appropriate in size and number for putative functional areas. These findings will hopefully stimulate further methodological refinements and validations.CORRESPONDING AUTHORS: Alexander

Brain atlases play an increasingly important role in neuroimaging, as they are invaluable for analysis, visualization, and comparison of results across studies. For both humans and macaque monkeys, digital brain atlases of many varieties are in widespread use, each having its own strengths and limitations. For studies of cerebral cortex there is particular utility in hybrid atlases that capitalize on the complementary nature of surface and volume representations, are based on a population average rather than an individual brain, and include measures of variation as well as averages. Linking different brain atlases to one another and to online databases containing a growing body of neuroimaging data will enable powerful forms of data mining that accelerate discovery and improve research efficiency.