| [](https://zenodo.org/badge/latestdoi/217773694) |
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| # Grid cells in RNNs trained to path integrate |
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| Code to reproduce the trained RNN in [**a unified theory for the origin of grid cells through the lens of pattern formation (NeurIPS '19)**](https://papers.nips.cc/paper/9191-a-unified-theory-for-the-origin-of-grid-cells-through-the-lens-of-pattern-formation) and additional analysis described in this [**preprint**](https://www.biorxiv.org/content/10.1101/2020.12.29.424583v1). |
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| Quick start: |
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| <img src="./docs/poisson_spiking.gif" width="300" align="right"> |
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| * [**inspect_model.ipynb**](inspect_model.ipynb): |
| Train a model and visualize its hidden unit ratemaps. |
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| * [**main.py**](main.py): |
| or, train a model from the command line. |
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| * [**pattern_formation.ipynb**](pattern_formation.ipynb): |
| Numerical simulations of pattern-forming dynamics. |
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| Includes: |
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| * [**trajectory_generator.py**](trajectory_generator.py): |
| Generate simulated rat trajectories in a rectangular environment. |
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| * [**place_cells.py**](place_cells.py): |
| Tile a set of simulated place cells across the training environment. |
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| * [**model.py**](model.py): |
| Contains the vanilla RNN model architecture, as well as an LSTM. |
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| * [**trainer.py**](model.py): |
| Contains model training loop. |
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| * [**models/example_trained_weights.npy**](models/example_trained_weights.npy) |
| Contains a set of pre-trained weights. |
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| ## Running |
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| We recommend creating a virtual environment: |
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| ```shell |
| $ virtualenv env |
| $ source env/bin/activate |
| $ pip install --upgrade pip |
| ``` |
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| Then, install the dependencies automatically with `pip install -r requirements.txt` |
| or manually with: |
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| ```shell |
| $ pip install --upgrade numpy==1.17.2 |
| $ pip install --upgrade tensorflow==2.0.0rc2 |
| $ pip install --upgrade scipy==1.4.1 |
| $ pip install --upgrade matplotlib==3.0.3 |
| $ pip install --upgrade imageio==2.5.0 |
| $ pip install --upgrade opencv-python==4.1.1.26 |
| $ pip install --upgrade tqdm==4.36.0 |
| $ pip install --upgrade opencv-python==4.1.1.26 |
| $ pip install --upgrade torch==1.10.0 |
| ``` |
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| If you want to train your own models, make sure to properly set the default |
| save directory in `main.py`! |
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| ## Result |
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|  |
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