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.

Significance How diverse functional cortical regions develop is an important neuroscience question. Animal experiments show that regional differentiation is controlled by genes that express in a graded and regionalized pattern; however, such investigation in humans is scarce. Using noninvasive imaging techniques to acquire brain structure data of genetically related subjects (i.e., twins), we estimated the spatial pattern of genetic influences on cortical structure. We developed a genetic parcellation of cortical thickness to delineate the boundaries of cortical divisions that are—within each division—maximally under control of shared genetic influences. We also found differences in genetic influences on cortical surface area and thickness along two orthogonal axes. The concept of gradations is crucial for understanding the organization of the human brain.

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In this paper, the global tourism network (GTN) is studied in order to gain insight about its structure and the interactions between source and destination markets. To concentrate on the main source and destination markets for each country, only its top k inbound and outbound flows are considered. The distribution of these most important ties in international tourism seems to be scale-free, with some occurrence of reciprocity, large transitivity, and high-degree centralization. The GTN shows a clustered structure determined by geographical as well as trade and cultural factors.Each major global and regional power seems to have a certain tourism sphere of influence. The network has a small world character and a high degree of geographic homophily, with more links within continents than between continents. Exponential random graph models have been fit to explain the observed global structure of the network based on its local interactions, and a number of significant motifs have been identified. The picture that results is a GTN that emerges from superimposed local processes in which tourism flows between countries is determined from multiple independent individual decisions made at the local level. This insight that global tourism patterns are driven by local processes is a major contribution of this research and can help develop strategic plans and cooperation partnerships at the national and regional levels, involving private and public stakeholders and targeting specific source and destination markets. The indicators computed using network analysis of global tourism flows can also be used to complement and enrich the information provided by current tourism statistics. KEYWORDS clustered structure, emergent structure, geographic homophily, scale-free, small world, top inbound/outbound flows

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