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Reward modulated STDP (Legenstein et al. 2008)
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# # # Dejan Pecevski, dejan@igi.tugraz.at, # November, 2008 # # This model contains the scripts in Python and other necessary files to reproduce the results reported in: Legenstein R, Pecevski D, Maass W 2008 A Learning Theory for Reward-Modulated Spike-Timing-Dependent Plasticity with Application to Biofeedback. PLoS Computational Biology 4(10): e1000180, Oct, 2008 doi:10.1371/journal.pcbi.1000180 To perform the simulations and produce the figures you need to: 1. Install the Parallel Circuit SIMulator - PCSIM: See the instructions on http://www.igi.tugraz.at/pcsim on how to do that. Checkout the newest revision from the repository. 2. Set the RMSTDP_HOME environment variable to the directory where this README file resides. 3. Install additional python packages for scientific computing: numpy 1.1.1 scipy 0.6.0 matplotlib 0.98.3 pygsl 1.20 mpi4py 0.6.0 pytables 2.0.4 ipython 0.9.1 and all dependent packages from these. 4. You need to compile a pcsim extension module used in the simulations. To do this: - Goto the subdirectory "packages/reward_gen". - Edit the line 5 in module_recipe.cmake SET( PCSIM_SOURCE_DIR "$ENV{HOME}/pcsim" ) so that PCSIM_SOURCE_DIR variable is set to the location of your installation of PCSIM. The default already set value is ${HOME}/pcsim. - Execute: python pcsim_extension.py build 5. Now you are ready to go. Each directory contains the files for one simulation from 1 to 5, as they are enumerated in the paper, and also additional simulations reported in the supplementary figures. In each directory there is a README file explaining how to run the scripts in the directory and which figures are produced from the scripts.
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