Simulated RNN data for "Linking neural population formatting to function"

Simulated test data (trial parameters, recurrent unit activity, and model outputs) generated by the two-module recurrent neural network (RNN) model described in: Ruff, D.A., Markman, S.K., Kim, J.Z., Cohen, M.R. "Linking neural population formatting to function." bioRxiv (2025). https://doi.org/10.1101/2025.01.03.631242 This dataset accompanies the code repository: https://github.com/solkm/formattingRNN Contents: python_model_data.zip — unzip into python_code_data/figure_code/testdata/ in the git repository. All-conditions, zero-noise test data (pickled) used for the population-geometry (PCA) and model-behavior figures. matlab_model_data.zip — unzip into matlab_code_data/modeltestdata/ in the git repository. The same all-conditions test data plus microstimulation test data (.mat format) used by the MATLAB figure scripts. See the repository README for details on how each file was generated and which analyses/figures it feeds.