Released 2004

The LISSOM package contains the C++, Python, and Scheme source code and examples for training and testing firing-rate LISSOM models, specifically RF-LISSOM, CRF-LISSOM, and HLISSOM. These self-organizing models support detailed simulations of the development and function of the mammalian visual system. This package is now obsolete; all of the simulations can be done in the currently supported simulator Topographica.

The simulator includes a graphical user interface (GUI), a command language for scripts, and a command-line interface. Sample command files are provided for running a variety of orientation, ocular dominance, motion direction, and face perception simulations. Extensive documentation is also included on disk and via online help at the command line. For more details about LISSOM-based models, see this paper on RF-LISSOM (and others under Visual Cortex and Self-Organization), and the Visual Cortex and Self-Organization research descriptions.

In addition to the supplied sample simulations, the simulator allows you to define arbitrary networks of maps that you can arrange into a hierarchy representing the visual system. Currently-supported map types include input regions (e.g. a Retina), convolving regions (e.g. ON/OFF cell layers), and RF-LISSOM regions (with modifiable afferent and lateral connections.) Environmental input is controlled by a simple but flexible language that allows arbitrary patterns and natural images to be rendered, scaled, rotated, combined, etc. This language makes it possible to use LISSOM for many of your own projects without having to write any new simulator code. However, we strongly recommend that you use Topographica for new projects, because it supports many more types of models (including LISSOM) in a much more flexible way.

The installation instructions, GUI documentation, command language documentation, and code documentation for the current version are available online.

(1/2003): A short LISSOM tutorial is now available.

(6/2005): More recent changes are now available via CVS; you might want to try the CVS version if you are having problems with the official release. See README.CVS for more information. Note however that these changes will not make the code compile on GCC 4.x.

Note: As of GCC 3.x and 4.x (e.g. in Fedora Core 3, 4, and 5 releases), the GNU compiler has gotten more strict about certain formerly accepted template code, and LISSOM will no longer compile with these compilers. If you are interested in contributing patches, please contact the author. In the meantime, binaries compiled under earlier compiler versions (GCC 3.4.x and below) can be used on any system, or you can install GCC 3.4.x and use that to compile LISSOM.

Comments to jbednar at inf dot ed dot ac dot uk.


v1.0 07/08/1994  

- Initial public K&R C release, without RFs.  

v2.0 10/28/1998,  

- Reimplemented in ANSI C supporting RF-LISSOM, interactive prompt, 

  picture generation, and online help.  

v2.1  11/09/1998  

- ANSI C release with enhanced command language, orientation handling, etc.  

v3.0a1 08/21/2000  

- Now C++;  added input command language; last version with full Cray T3E support.  

v3.0b1 04/08/2001  

- Added support for multiple maps, arbitrary map sizes, and map scaling.  

v3.0 11/25/2001  

- Fully released version of 3.0a1 (alpha) and 3.0b1 (beta).  

v4.0 01/19/2003  

- Added Tk-based GUI interface written in Scheme.  

- Additional sample orientation, ocular dominance, direction, and face 


- Added support for back-projection, transparent input images, and Matlab 

  plot output. 

v5.0 09/29/2004

- Added python Tkinter version of GUI.

- Allowed support for color opponent cells and others

  with incoming weights from multiple areas.

- Added sample red/green color map simulation.

- Updated to work with GCC 3.3.

See Topographica for more recent software supporting these algorithms.
James A. Bednar Postdoctoral Alumni jbednar [at] inf ed ac uk
Judah De Paula Ph.D. Alumni
Wilson S. Geisler Former Collaborator geisler [at] psy utexas edu
Jefferson Provost Ph.D. Alumni jefferson provost [at] gmail com
Joseph Sirosh Ph.D. Alumni joseph sirosh [at] gmail com
     [Expand to show all 16][Minimize]
Contour Integration and Segmentation with Self-Organized Lateral Connections Yoonsuck Choe and Risto Miikkulainen Biological Cybernetics 90:75-88 2004

Prenatal and Postnatal Development of Laterally Connected Orientation Maps James A. Bednar and Risto Miikkulainen In Computational Neuroscience: Trends in Research, 2004, 58-60, 985-992, 2004. 2004

Learning Innate Face Preferences James A. Bednar and Risto Miikkulainen Neural Computation, 15(7):1525-1557, 2003. 2003

Modeling Large Cortical Networks With Growing Self-Organizing Maps James A. Bednar, Amol Kelkar, and Risto Miikkulainen In Computational Neuroscience, 44--46, 315-321, 2002. 2002

Scaling Self-Organizing Maps To Model Large Cortical Networks James A. Bednar, Amol Kelkar, and Risto Miikkulainen Neuroinformatics:275-302, 2001. 2001

Tilt Aftereffects In A Self-Organizing Model Of The Primary Visual Cortex James A. Bednar and Risto Miikkulainen Neural Computation, 12:1721-1740, 2000. 2000

Self-Organization And Segmentation In A Laterally Connected Orientation Map Of Spiking Neurons Yoonsuck Choe and Risto Miikkulainen Neurocomputing:139-157, 1998. 1998

Self-Organization, Plasticity, and Low-Level Visual Phenomena in a Laterally Connected Map Model of the Primary Visual Cortex Risto Miikkulainen, James A. Bednar, Yoonsuck Choe, and Joseph Sirosh In R. L. Goldstone and P. G. Schyns and D. L. Medin, editors, Perceptual Learning, Psychology... 1997

Tilt Aftereffects in a Self-Organizing Model of the Primary Visual Cortex James A. Bednar Masters Thesis, Department of Computer Sciences, The University of Texas at Austin, Austin, TX, 1997... 1997

Laterally Interconnected Self-Organizing Maps In Hand-Written Digit Recognition Yoonsuck Choe, Joseph Sirosh, and Risto Miikkulainen In David S. Touretzky and Michael C. Mozer and Michael E. Hasselmo, editors, Advances in Neural ... 1996

Self-Organization of Orientation Maps, Lateral Connections, and Dynamic Receptive Fields in the Primary Visual Cortex Joseph Sirosh, Risto Miikkulainen and James A. Bednar In Joseph Sirosh and Risto Miikkulainen and Yoonsuck Choe, editors, {P}roceedings of the {I}nter... 1996

A Self-Organizing Neural Network Model Of The Primary Visual Cortex Joseph Sirosh PhD Thesis, Department of Computer Sciences, The University of Texas at Austin, Austin, TX, 1995. Te... 1995

Laterally Interconnected Self-Organizing Feature Map In Handwritten Digit Recognition Yoonsuck Choe Masters Thesis, Department of Computer Sciences, The University of Texas at Austin, Austin, TX, 1995... 1995

Modeling Cortical Plasticity Based On Adapting Lateral Interaction Joseph Sirosh and Risto Miikkulainen In James M. Bower, editors, The Neurobiology of Computation: {T}he Proceedings of the Third Annu... 1995

Cooperative Self-Organization Of Afferent And Lateral Connections In Cortical Maps Joseph Sirosh and Risto Miikkulainen Biological Cybernetics:66-78, 1994. 1994

Self-Organizing Feature Maps With Lateral Connections: Modeling Ocular Dominance Joseph Sirosh and Risto Miikkulainen In M. C. Mozer and P. Smolensky and D. S. Touretzky and J. L. Elman and A. S. Weigend, editors, ... 1994