Categorical encoding of decision variables in orbitofrontal cortex

Categorical encoding of decision variables in orbitofrontal cortex<br><br>These are the data and code accompanying the PLoS Computational Biology article "Categorical encoding of decision variables in orbitofrontal cortex" by Arno Onken, Jue Xie, Stefano Panzeri and Camillo Padoa-Schioppa.<br><br>Code<br><br>The code in the 'code' folder is written in Python and tested with version 3.6.6. The following additional packages are required:<br>- NumPy tested with version 1.16.5<br>- SciPy tested with version 1.1.0<br>- Scikit-learn tested with version 1.19.1<br>- spherecluster https://pypi.org/project/spherecluster/0.1.2/<br>- diptest https://github.com/alimuldal/diptest<br><br>To reproduce the figures, run the shell script 'plot_figures.sh'. The 'plot_*.py' scripts use the result data in the folders that are specified in the shell script. To reproduce the result data, use the appropriate 'calculate_*.py' script.<br><br>Data<br><br>The data are located in the 'data' folder.<br>- 'ofc_psth' contains the peri-stimulus time histograms for each cell. These are used for the PAIRS analysis only (corresponding script 'calculate_pairs.py'.<br>- 'ofc_rates_all' contains the rates for each cell and trial type in the files 'rates.mat' and a list of the trial types in 'trialtypes.mat'. The other files in the folder are result files generated by the corresponding 'calculate_*.py' scripts.<br>- 'ofc_rates_shuffled' like 'ofc_rates_all' but the rates where shuffled (see supplementary figure S2 Fig).<br>- 'ofc_rates_time_windows' contains sub folders for each time window. Each of these sub folders has the same structure as 'ofc_rates_all'.<br>- 'synthetic_banana' contains the synthetic data used for Figure 3.<br>- 'synthetic_uniform' contains the synthetic non-categorical data sampled uniformly from the hypersphere (see Figures 5 and 6).<br>- 'synthetic_variable' contains the synthetic categorical data (see Figures 4, 5 and 6).