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Synaptic Scaling Balances Learning in a Spiking Model of Neocortex

Neurons and Cognition 2013-04-09 v1 Neural and Evolutionary Computing

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.

Keywords

Cite

@article{arxiv.1304.2266,
  title  = {Synaptic Scaling Balances Learning in a Spiking Model of Neocortex},
  author = {Mark Rowan and Samuel Neymotin},
  journal= {arXiv preprint arXiv:1304.2266},
  year   = {2013}
}

Comments

10 pages

R2 v1 2026-06-21T23:55:46.987Z