Code for Phase of firing does not reflect temporal order in sequence memory of humans and recurrent neural networks
Install the conda environment and train an RNN model:
cd sequence-memory
conda env create -f sequence.yml
activate sequence
python rnn_model/rnn/run_single_model.py
Expected behavior: A trained RNN model performing a working-memory task should be obtained and saved.
Expected run-time: One single RNN model took on average around 5-6 hours to train on a Nvidea 2080-ti GPU.
Pull the model and data files from this repo, by first installing git lfs. Alternatively, retrain new RNNs using
python rnn_model/rnn/run_single_model.py
or
wandb sweep rnn_model/rnn/sweep.yml
rnn_model/rnn/run_sweep.py # after adding sweep ID to top of file
and obtain summary statistics over multiple models using
rnn_model/rnn/run_summary.py
Either-way, the figures can then be recreated by running the notebooks in: rnn_model/generate_figures.
Code tested on a Ubuntu system with package versions given in the sequence.yml file