Topographica 0.9.7

Developed by the Institute for Adaptive and Neural Computation at the University of Edinburgh and the Neural Networks Research Group at the University of Texas at Austin. The project is funded by the NIMH Human Brain Project under grant 1R01-MH66991. The goal is to help researchers understand brain function at the level of the topographic maps that make up sensory and motor systems.

Topographica is intended to complement the many good low-level neuron simulators that are available, such as Genesis and Neuron. Those simulators focus on modeling the detailed internal behavior of neurons and small networks of them. Topographica instead focuses on the large-scale structure and function that is visible only when many thousands of such neurons are connected into topographic maps containing millions of connections. Many important phenomena cannot be studied without such large networks, including the two-dimensional organization of visual orientation and motion direction maps, and object segmentation and grouping processes.

To make such models practical, in Topographica the fundamental unit is a sheet of neurons, rather than a neuron or a part of a neuron. For most simulations, the sheets can be implemented at a high level, consisting of abstract firing-rate or integrate-and-fire neurons. When required for validation or for specific phenomena, Topographica can easily be extended using a Sheet that interfaces to more detailed neuron models in other simulators. Less-detailed sheets can also be used temporarily, e.g. when interacting with the model in real time. Throughout, Topographica makes it simple to use an appropriate level of detail and complexity, as determined by the available computing power, phenomena of interest, and amount of biological data available for validation.