Recurrent neural networks of integrate-and-fire cells simulating short-term memory and wrist movement tasks derived from continuous dynamic networks.

@article{Maier2003RecurrentNN,
  title={Recurrent neural networks of integrate-and-fire cells simulating short-term memory and wrist movement tasks derived from continuous dynamic networks.},
  author={M. A. Maier and Larry E. Shupe and Eberhard E. Fetz},
  journal={Journal of physiology, Paris},
  year={2003},
  volume={97 4-6},
  pages={601-12}
}
Dynamic recurrent neural networks composed of units with continuous activation functions provide a powerful tool for simulating a wide range of behaviors, since the requisite interconnections can be readily derived by gradient descent methods. However, it is not clear whether more realistic integrate-and-fire cells with comparable connection weights would perform the same functions. We therefore investigated methods to convert dynamic recurrent neural networks of continuous units into networks… CONTINUE READING

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