Synaptic Scaling Balances Learning in a Spiking Model of Neocortex

  • Mark Rowan
  • Samuel Neymotin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7824)

Abstract

Learning in the brain requires complementary mechanisms: potentiation and activity-dependent homeostatic scaling. We introduce synaptic scaling to a biologically-realistic spiking model of neocortex which can learn changes in oscillatory rhythms using STDP, and show that scaling is necessary to balance both positive and negative changes in input from potentiation and atrophy. We discuss some of the issues that arise when considering synaptic scaling in such a model, and show that scaling regulates activity whilst allowing learning to remain unaltered.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Mark Rowan
    • 1
  • Samuel Neymotin
    • 2
  1. 1.School of Computer ScienceUniversity of BirminghamUK
  2. 2.Dept. NeurobiologyYale University School of MedicineNew HavenUSA

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