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Hippocampal formation trains independent components via forcing input reconstruction

  • András Lőrincz
Part I: Coding and Learning in Biology
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1327)

Abstract

It is assumed that higher order concept formation utilizes independent components (ICs). It is argued that ICs require dynamic input reconstruction networks (RNs) to form a reliable internal representation. Input reconstruction, however, can be slow and poor with ICs on substrates with lossy dynamics. A model of the hippocampal formation is proposed that develops the ICs on lossy RNs by means of locking inputs to the internal representation and thus forcing fast reconstruction and cancelling losses. It is assumed that upon training ICs can lock themselves, thus hippocampal lesion mostly affects anterograde memories.

Keywords

Internal Representation Independent Component Entorhinal Cortex Independent Component Analysis Control Architecture 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • András Lőrincz
    • 1
    • 2
  1. 1.Department of Chemical PhysicsInstitute of Isotopes of the Hungarian Academy of Sciences BudapestHungary
  2. 2.Department of Adaptive SystemsAttila József University, SzegedHungary

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