The Effect of Different Forms of Synaptic Plasticity on Pattern Recognition in the Cerebellar Cortex

  • Giseli de Sousa
  • Rod Adams
  • Neil Davey
  • Reinoud Maex
  • Volker Steuber
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5495)


Many cerebellar learning theories assume that long-term depression (LTD) of synapses between parallel fibres (PFs) and Purkinje cells (PCs) provides the basis for pattern recognition in the cerebellum. Previous work has suggested that PCs can use a novel neural code based on the duration of silent periods. These simulations have used a simplified learning rule, where the synaptic conductance was halved each time a pattern was learned. However, experimental studies in cerebellar slices show that the synaptic conductance saturates and is rarely reduced to less than 50% of its baseline value. Moreover, the previous simulations did not include plasticity of the synapses between inhibitory interneurons and PCs. Here we study the effect of LTD saturation and inhibitory synaptic plasticity on pattern recognition in a complex PC model. We find that the PC model is very sensitive to the value at which LTD saturates, but is unaffected by inhibitory synaptic plasticity.


Associative memory Long-term depression Purkinje cell Cerebellum 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Giseli de Sousa
    • 1
  • Rod Adams
    • 1
  • Neil Davey
    • 1
  • Reinoud Maex
    • 1
  • Volker Steuber
    • 1
  1. 1.Science and Technology Research InstituteUniversity of HertfordshireHatfieldUK

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