The biological function of cortical neurons can often be understood only in the context of large, highly interconnected networks. These networks typically form two-dimensional topographic maps, such as the retinotopic maps in the visual system. Computational simulations of these areas have led to valuable insights about how cortical topography develops and functions, but further progress is difficult because appropriate simulation tools are not available. This paper introduces the freely available Topographica map-level simulator, currently under development at the University of Texas at Austin. Topographica is designed to make large-scale, detailed models practical. The goal is to allow neuroscientists and computational scientists to understand how topographic maps and their connections organize and operate. This understanding will be crucial for integrating experimental observations into a comprehensive theory of cortical function.

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In Computational Neuroscience: Trends in Research, 2004, 1129-1135, 2004.

@Article{bednar:neurocomputing04-sw, title={Modeling Cortical Maps with Topographica}, author={James A. Bednar and Yoonsuck Choe and Judah De Paula and Risto Miikkulainen and Jefferson Provost and Tal Tversky}, booktitle={Computational Neuroscience: Trends in Research, 2004}, journal={Neurocomputing}, pages={1129-1135}, url="http://www.cs.utexas.edu/users/ai-lab/?bednar:neurocomputing04-topographica", year={2004} }