Neuroscientists have obtained vast amounts of experimental data about the organization and function of the cerebral cortex in non-human primates, especially the macaque monkey. To cope with this flood of information, new tools and strategies are necessary in order to adequately analyze and communicate these findings. To this end, we propose a collaborative effort that brings together scientists with complementary expertise in neuroanatomy and image processing and capitalizes on access to high performance parallel computing resources and high-speed networking capacities. Our common goal is to develop and apply a family of interrelated computer graphics programs to be used for representing information about cortical structure and organization. The integrated system will allow visualization of three-dimensional (3-D) reconstructions of the entire cerebral hemisphere that are based either on volumetric representations or on selected surface contours. These reconstructions will be used to display information about the location of different cortical areas as well as data from specific experimental procedures. To compensate for the marked differences between individual brains, we will develop warping algorithms that can accurately transform one brain into the shape of another. These transformations will be based on probabilistic approaches to shape modeling that have had considerable success in other domains of biology. We will also develop computerized techniques for making unfolded representations of the cortex. These techniques will be used to generate comprehensive, easily updatable summaries of different schemes for the layout of various areas throughout the cerebral cortex. These will in turn be used as the framework for a graphically oriented database of the connectivity of different areas. Collectively, these approaches will greatly enhance the accuracy, speed, and flexibility with which many types of information about cortical organization can be represented and communicated. In addition, it will provide a much-needed framework for more accurate comparisons with the human brain.
