Encyclopedia of Computational Neuroscience

Living Edition
| Editors: Dieter Jaeger, Ranu Jung

Topographica

Living reference work entry
DOI: https://doi.org/10.1007/978-1-4614-7320-6_263-5

Synonyms

Definition

Topographica is a simulator for large-scale neural models, with special support for neurons organized into topographic maps and for modelling activity-dependent development. A typical Topographica model will cover a complete pathway from the sensory periphery to regions in the cortex, modelling at least several square millimeters of cortical tissue. To make working at this scale practical, Topographica groups neurons into Sheets, which each typically correspond to a large subpopulation of cells organized in two dimensions across the surface of a neural area. Using this abstraction, Topographica can implement a very large variety of possible models with relatively little coding and thus provides a platform for understanding properties that emerge only when large numbers of neurons are interconnected. The Topographica project also provides reusable, general-purpose components for other scientific...

Keywords

Connection Pattern Version Control System Neural Simulation Firing Rate Model Neuron Simulation Environment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References

  1. Bednar JA (2009) Topographica: building and analyzing map-level simulations from Python, C/C++, MATLAB, NEST, or NEURON components. Front Neuroinform 3:8PubMedCentralPubMedCrossRefGoogle Scholar
  2. Bednar JA, Kelkar A, Miikkulainen R (2004) Scaling self-organizing maps to model large cortical networks. Neuroinformatics 2:275–302PubMedCrossRefGoogle Scholar

Further Reading

  1. Miikkulainen R, Bednar JA, Choe Y, Sirosh J (2005) Computational maps in the visual cortex. Springer, BerlinGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Institute for Adaptive and Neural Computation, School of InformaticsThe University of EdinburghEdinburghUK