@misc{cogprints5711,
          volume = {3},
          number = {8},
           month = {August},
          author = {Mathias Franzius and Henning Sprekeler and Prof. Dr. Laurenz Wiskott},
            note = {This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.},
          editor = {Karl J. Friston},
           title = {Slowness and Sparseness Lead to Place, Head-Direction, and Spatial-View Cells},
            year = {2007},
         journal = {PLoS Computational Biology},
           pages = {e166},
        keywords = {Place Cell, Head Direction Cell, Spatial View Cell, Grid Cell, SFA, Hierarchical Model, Slowness, Sparse Coding},
             url = {http://cogprints.org/5711/},
        abstract = {We present a model for the self-organized formation of place cells, head-direction cells, and spatial-view cells in the hippocampal formation based on unsupervised learning on quasi-natural visual stimuli. The model comprises a hierarchy of Slow Feature Analysis (SFA) nodes, which were recently shown to reproduce many properties of complex cells in the early visual system. The system extracts a distributed grid-like representation of position and orientation, which is transcoded into a localized place-field, head-direction, or view representation, by sparse coding. The type of cells that develops depends solely on the relevant input statistics, i.e., the movement pattern of the simulated animal. The numerical simulations are complemented by a mathematical analysis that allows us to accurately predict the output of the top SFA layer}
}

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