Soft-bound synaptic plasticity increases storage capacity

Mark C W van Rossum, Maria Shippi, Adam B Barrett

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Accurate models of synaptic plasticity are essential to understand the adaptive properties of the nervous system and for realistic models of learning and memory. Experiments have shown that synaptic plasticity depends not only on pre- and post-synaptic activity patterns, but also on the strength of the connection itself. Namely, weaker synapses are more easily strengthened than already strong ones. This so called soft-bound plasticity automatically constrains the synaptic strengths. It is known that this has important consequences for the dynamics of plasticity and the synaptic weight distribution, but its impact on information storage is unknown. In this modeling study we introduce an information theoretic framework to analyse memory storage in an online learning setting. We show that soft-bound plasticity increases a variety of performance criteria by about 18% over hard-bound plasticity, and likely maximizes the storage capacity of synapses.
Original languageEnglish
Article numbere1002836
Number of pages11
JournalPLoS Computational Biology
Issue number12
Publication statusPublished - 2012

Keywords / Materials (for Non-textual outputs)

  • Information Theory
  • Learning
  • Long-Term Potentiation
  • Memory
  • Models, Theoretical
  • Neuronal Plasticity


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