Codes and data upload for Mesocircuit Model project

<h3>Information</h3> <p>This resource contains source codes and data required to produce the figures from:<br>Senk, J., Hagen, E., van Albada, S. J., &amp; Diesmann, M. (2024). Reconciliation of weak pairwise spike-train correlations and highly coherent local field potentials across space. <em>arXiv preprint arXiv:1805.10235v3<br><br></em>For only source codes, see:</p> <p>Senk, J., &amp; Hagen, E. (2024). Mesocircuit Model (v1.0.0). Zenodo.&nbsp;<a href="https://doi.org/10.5281/zenodo.13798936" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13798936</a></p> <div> <h3>Instructions</h3> To use this resource, download the mesocircuit-model-1.0.0.tar.gz file. Then, extract the contents of the archive and run the following command in the extracted directory:<br> <div>&nbsp;</div> <div>$ # unzip the archive</div> <div>$ tar -xzf mesocircuit-model-1.0.0.tar.gz</div> <br> <div>$ # create and activate the conda environment</div> <div>$ cd mesocircuit-model</div> <div>$ conda env create -f environment.yml</div> <div>$ conda activate mesocircuit</div> <br> <div>$ # run the figure-generation scripts</div> <div>$ cd scripts</div> <div>$ python ms_figures_simulations.py</div> <div>$ python run_mesocircuit_lfps.py</div> <div>&nbsp;</div> <div>$ # deactivate environment</div> <div>$ conda deactivate&nbsp;</div> </div> <div>&nbsp;</div> <div>Installers for conda may be obtained e.g., from https://github.com/conda-forge/miniforge.&nbsp;<br> <div>The figures produced by ms_figures_simulations.py will be saved in the `ms_figures` directory.</div> <div>The figures produced by run_mesocircuit_lfps.py will be saved in mesocircuit_data/mesocircuit_MAMV1/dd1dcbd4034fbd4f689fbdd2ff7abb3b/lfp/figures.</div> </div>