A model of clipped hebbian learning in a neocortical pyramidal cell

  • Bruce Graham
  • David Willshaw
Part I: Coding and Learning in Biology
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1327)


A detailed compartmental model of a cortical pyramidal cell is used to determine the effect of the spatial distribution of synapses across a dendritic tree on the pattern recognition capability of the neuron. By setting synaptic strengths according to the clipped Hebbian learning rule used in the associative net neural network model, the cell is able to recognise input patterns, but with a one to two order of magnitude decrease in performance compared to the computing units in the network model. Performance of the cell is optimised by particular forms of input signal, but is not altered by different pattern recognition criteria.


Pyramidal Cell Spike Train Input Pattern Associative Memory Output Unit 
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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Bruce Graham
    • 1
  • David Willshaw
    • 1
  1. 1.Centre for Cognitive ScienceUniversity of EdinburghScotlandUK

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