Attractor neural networks storing multiple space representations: a model for hippocampal place fields

@inproceedings{Battaglia1998AttractorNN,
  title={Attractor neural networks storing multiple space representations: a model for hippocampal place fields},
  author={Francesco P. Battaglia and Alessandro Treves},
  year={1998}
}
A recurrent neural network model storing multiple spatial maps, or ‘‘charts,’’ is analyzed. A network of this type has been suggested as a model for the origin of place cells in the hippocampus of rodents. The extremely diluted and fully connected limits are studied, and the storage capacity and the information capacity are found. The important parameters determining the performance of the network are the sparsity of the spatial representations and the degree of connectivity, as found already… CONTINUE READING
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