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CNS: Cortical Network Simulator
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CNS is a general, GPU-based framework for the fast simulation of cortically-organized networks. Written by Jim Mutch.
Documentation and Support
- The following technical report provides an overview of CNS:
Jim Mutch, Ulf Knoblich, and Tomaso Poggio. CNS: a GPU-based framework for simulating cortically-organized networks. MIT-CSAIL-TR-2010-013 / CBCL-286, Massachusetts Institute of Technology, Cambridge, MA, February 26, 2010. [pdf] [bib]
- Installation Instructions
- Full Programming Guide
- Forum (Please ask how-to questions here rather than via email. Author will be notified of new posts.)
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CNS is distributed under the terms of the GNU General Public License (version 3).
In addition, we request that authors cite the following technical report in publications describing work carried out using CNS:
Jim Mutch, Ulf Knoblich, and Tomaso Poggio. CNS: a GPU-based framework for simulating cortically-organized networks. MIT-CSAIL-TR-2010-013 / CBCL-286, Massachusetts Institute of Technology, Cambridge, MA, February 26, 2010. [pdf] [bib]
Available versions:
Revision history
Note: unless you intend to develop a package of cell types from scratch, you will probably want to also download one of the packages listed below (or obtain one from a third party).
A CNS package that can be used to instantiate a broad class of feedforward object recognition models. Written by Jim Mutch.
Documentation and Support
Download
Note: this package is a reorganized and renamed version of the Feature Hierarchy package (fhpkg). The last version of the FH package can be downloaded here. The download also contains a compatible version of CNS.
A CNS package for creating 3-D convolutional networks and training them via the backpropagation algorithm. Written by Jim Mutch and Srini Turaga.
Documentation and Support
Download
A CNS package that defines several types of spiking cells using Hodgkin-Huxley dynamics. Written by Ulf Knoblich.
Documentation and Support
Download