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Scientific Understanding of Consciousness |
Hierarchical Organization of Cortical Surface Area
Science 30 March 2012: Vol. 335 no. 6076 pp. 1634-1636 Hierarchical Genetic Organization of Human Cortical Surface Area Chi-Hua Chen1, E. D. Gutierrez2, Wes Thompson1, Matthew S. Panizzon1, Terry L. Jernigan1,2, Lisa T. Eyler1,3, Christine Fennema-Notestine1,4, Amy J. Jak1,5, Michael C. Neale6, Carol E. Franz1,7, Michael J. Lyons8, Michael D. Grant8, Bruce Fischl9, Larry J. Seidman10, Ming T. Tsuang1,5,6, William S. Kremen1,5,6, Anders M. Dale1,4,11 1Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA. 2Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92093, USA. 3Veterans Administration (VA) San Diego Healthcare System, San Diego, CA 92161, USA. 4Department of Radiology, University of California, San Diego, La Jolla, CA 92093, USA. 5VA Center of Excellence for Stress and Mental Health, San Diego, CA 92093, USA. 6Departments of Psychiatry and Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA 23219, USA. 7Center for Behavioral Genomics, University of California, San Diego, La Jolla, CA 92093, USA. 8Department of Psychology, Boston University, Boston, MA 02215, USA. 9Department of Radiology, Harvard Medical School and Massachusetts General Hospital, Boston, MA 02115, USA. 10Department of Psychiatry, Harvard Medical School, Boston, MA 02215, USA. 11Department of Neurosciences, University of California, San Diego, La Jolla, CA 92093, USA. [paraphrase] Surface area of the cerebral cortex is a highly heritable trait, yet little is known about genetic influences on regional cortical differentiation in humans. Using a data-driven, fuzzy clustering technique with magnetic resonance imaging data from 406 twins, we parceled cortical surface area into genetic subdivisions, creating a human brain atlas based solely on genetically informative data. Boundaries of the genetic divisions corresponded largely to meaningful structural and functional regions; however, the divisions represented previously undescribed phenotypes different from conventional (non–genetically based) parcellation systems. The genetic organization of cortical area was hierarchical, modular, and predominantly bilaterally symmetric across hemispheres. We also found that the results were consistent with human-specific regions being subdivisions of previously described, genetically based lobar regionalization patterns. We sought to develop a brain atlas of human cortical surface area that was based entirely on genetic correlations, rather than a priori structural or functional information. Using the twin design, which compares monozygotic and dizygotic twins, we then estimated genetic correlations between different points on the cortical surface. These genetic correlations represent shared genetic influences on relative areal expansion between cortical regions. To demarcate the genetic topography of cortical surface area based on the genetic correlations of relative surface area measures, we determined the appropriate number of clusters, computed the widely used silhouette coefficients and identified 12 natural clusters. These clusters correspond closely to meaningful structural and functional regions. Subdivisions of the frontal cortex include the motor-premotor, dorsolateral prefrontal cortex extending to the anterior and superior parts, dorsomedial frontal, and orbitofrontal. Another cluster is found between the frontal and parietal cortices, extending from pars opercularis to the subcentral region, including the inferior pre- and post-central gyri. The temporal cortex includes the superior temporal, posterolateral temporal cortex extending to temporal and parietal junction, and anteromedial temporal cortex. The parietal cortex includes the inferior parietal cortex, superior parietal cortex, and precuneus. The occipital cortex constitutes a single cluster. Some anatomical boundaries of these clusters map onto traditionally parcellated regions, such as cytoarchitectural areas or gyrus patterns; however, others do not follow classically defined boundaries (such as Brodmann areas). For example, there is no natural sulcal-gyral boundary between our dorsomedial and orbitofrontal clusters, but they still correspond reasonably well to the division between Brodmann areas 10 and 11. Conversely, the well-defined cytoarchitectural differentiation between Brodmann areas 17 and 18 is not manifest as separate genetically based clusters in our analyses. The genetically based clusters presented a spatially contiguous pattern within hemispheres. After identifying the boundaries of the genetically based parcellation, we next sought to examine the genetic relations between the 12 clusters; in particular, we searched for underlying organizational principles among these genetic subdivisions. We calculated the genetic similarity matrix to determine the genetic relatedness between clusters. We found that genetic correlations are higher between clusters within the same lobe than between clusters in different lobes. We also examined the progression of cluster solutions, from 2 to 12 clusters, using fuzzy clustering. If the structure of the data are hierarchical, then successive clusters will tend to be subdivisions of previous clusters. The sequentially unfolding pattern revealed that the emerging clusters tended to respect the boundaries of preceding clusters and appeared to be nested subdivisions. The convergence of results of this analysis and the dendogram method thus provide further evidence for a hierarchical structure of genetic patterning that is intrinsic to the data. We described a previously unidentified parcellation system for the human cortex that reflects shared genetic influences on cortical areal expansion. This system constitutes the first human brain atlas based solely on genetically informative data, which may provide presently undescribed phenotypes that will have greater statistical power for genome-wide genetic association studies in comparison with traditional cortical parcellations. We found evidence for a hierarchical, modular, and bilaterally symmetric genetic architecture. Genetically based lobar regions have been demonstrated across mammalian species, and our results are consistent with genetically based regions of human specialization being increasingly differentiated subdivisions of these lobar regions. Our findings may thus be useful for translating results from model organisms into functional and clinical insights about human specializations, so as to understand both order and disorder in the human brain. [end of paraphrase]
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