Biological Cybernetics

, Volume 69, Issue 1, pp 77–86 | Cite as

Pattern association and retrieval in a continuous neural system

  • Hung-Jen Chang
  • Joydeep Ghosh
Article

Abstract

This paper studies the behavior of a large body of neurons in the continuum limit. A mathematical characterization of such systems is obtained by approximating the inverse input-output nonlinearity of a cell (or an assembly of cells) by three adjustable linearized sections. The associative spatio-temporal patterns for storage in the neural system are obtained by using approaches analogous to solving space-time field equations in physics. A noise-reducing equation is also derived from this neural model. In addition, conditions that make a noisy pattern retrievable are identified. Based on these analyses, a visual cortex model is proposed and an exact characterization of the patterns that are storable in this cortex is obtained. Furthermore, we show that this model achieves pattern association that is invariant to scaling, translation, rotation and mirror-reflection.

Keywords

Large Body Visual Cortex Field Equation Neural System Continuum Limit 
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Copyright information

© Springer-Verlag 1993

Authors and Affiliations

  • Hung-Jen Chang
    • 1
  • Joydeep Ghosh
    • 1
  1. 1.Department of Electrical and Computer EngineeringThe University of Texas at AustinAustinUSA

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