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Synaptic Rewiring for Topographic Map Formation

  • Simeon A. Bamford
  • Alan F. Murray
  • David J. Willshaw
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5164)

Abstract

A model of topographic map development is presented which combines both weight plasticity and the formation and elimination of synapses as well as both activity-dependent and -independent processes. We statistically address the question of whether an activity-dependent process can refine a mapping created by an activity-independent process. A new method of evaluating the quality of topographic projections is presented which allows independent consideration of the development of a projection’s preferred locations and variance. Synapse formation and elimination embed in the network topology changes in the weight distributions of synapses due to the activity-dependent learning rule used (spike-timing-dependent plasticity). In this model, variance of a projection can be reduced by an activity dependent mechanism with or without spatially correlated inputs, but the accuracy of preferred locations will not necessarily improve when synapses are formed based on distributions with on-average perfect topography.

Keywords

Prefer Location Ideal Location Average Absolute Deviation Ocular Dominance Lateral Connection 
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 2008

Authors and Affiliations

  • Simeon A. Bamford
    • 1
  • Alan F. Murray
    • 2
  • David J. Willshaw
    • 3
  1. 1.Doctoral Training Centre in Neuroinformatics 
  2. 2.Institute of Integrated Micro and Nano Systems 
  3. 3.Institute of Adaptive and Neural ComputationUniversity of Edinburgh 

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