# Excitatory-Inhibitory Recurrent Neural Network (Song et al.; 2016)

In this exhibit, we create, simulate, and visualize the dynamics and adaptation of the excitatory-inhibitory 
recurrent neural network (EI-RNN) originally proposed in (Song et al., 2016) [1]. 

The model code for this exhibit can be found 
[here](https://github.com/NACLab/ngc-museum/tree/main/exhibits/ei_rnn).

```{eval-rst}
.. table::
   :align: center

   +-----------------------------------------------------------------+
   | .. image:: ../images/museum/ei_rnn/ei_rnn_arch.jpg              |
   |   :scale: 65%                                                   |
   |   :align: center                                                |
   +-----------------------------------------------------------------+
```

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## References
<b>[1]</b> Song, H. F., Yang, G. R., & Wang, X. J. Training excitatory-inhibitory recurrent neural networks 
for cognitive tasks: a simple and flexible framework. PLoS computational biology, 12(2), e1004792 (2016).