This program runs the simulations and plots the figures for the manuscript 'Hierarchy of prediction errors shapes the learning of context-dependent sensory representations'. This means simulating models of mice with S1 L2/3 sensory pyramidal neurons. learning a go/no-go sensory discrimination task with possible rule reversals.
These are instructions to set up a functioning conda environment (~10 min). If conda is not installed yet, do so following these instructions (linux recommended). Then make sure conda is up-to-date.
conda update conda --all
Create a conda environment with your favorite name, here myenv
conda create -n myenv python=3.10.8
Activate the conda environment
conda activate myenv
Install the required libraries
pip install -r requirements.txt
Setup the simulation library
python setup.py install
Before rerunning the simulations, you can test whether the installation was successful (circa 1-2 min run time). Just enter
python main.py plot
This will plot all the simulation panels (in the folder figures) and assemble all the panels into the full figures (figures/figures.pdf). To rerun all the simulations (circa 1 hour run time), enter
python main.py simulate
This will overwrite the current simulation outcomes in the results/simulation folder, which are the files used for the plots. These simulations use the parameter values optimized from parameter scans. These optimized values are in database files in the folder results/scan. These scan database files mostly only contain the final optimized parameters. The full scans can be reproduced by running the command:
python main.py scan
However, be warned! This is computationally extensive and could take a very long time. Also starting them and interrupting the scanning before completion might corrupt the files in results/scan. We therefore strongly advise to avoid this command unless you know what you are doing. If you mess up and corrupt your files, you can recover them from the github.