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Trace feature map: a model of episodic associative memory

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Abstract

An approach to episodic associative memory is presented, which has several desirable properties as a human memory model. The design is based on topological feature map representation of data. An ordinary feature map is a classifier, mapping an input vector onto a topologically meaningful location on the map. A trace feature map, in addition, creates a memory trace on that location. The traces can be stored episodically in a single presentation, and retrieved with a partial cue. Nearby traces overlap, which results in plausible memory interference behavior. Performance degrades gracefully as the memory is overloaded. More recent traces are easier to recall as are traces that are unique in the memory.

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Author notes

  1. R. Miikkulainen

    Present address: Department of Computer Sciences, The University of Texas at Austin, Taylor Hall 2.124, 78712-1188, Austin, TX, USA

Authors and Affiliations

  1. Department of Computer Sciences, University of Texas, 78712-1188, Austin, TX, USA

    R. Miikkulainen

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  1. R. Miikkulainen
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Additional information

This research was supported in part by an ITA Foundation grant and by fellowships from the Academy of Finland, the Emil Aaltonen Foundation and the Foundation for the Advancement of Technology (Finland) when the author was at UCLA

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Miikkulainen, R. Trace feature map: a model of episodic associative memory. Biol. Cybern. 66, 273–282 (1992). https://doi.org/10.1007/BF00198481

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  • DOI: https://doi.org/10.1007/BF00198481

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