Formation of feedforward networks and frequency synchrony by spike-timing-dependent plasticity

Naoki Masuda, Hiroshi Kori

Research output: Contribution to journalArticlepeer-review

64 Citations (Scopus)

Abstract

Spike-timing-dependent plasticity (STDP) with asymmetric learning windows is commonly found in the brain and useful for a variety of spike-based computations such as input filtering and associative memory. A natural consequence of STDP is establishment of causality in the sense that a neuron learns to fire with a lag after specific presynaptic neurons have fired. The effect of STDP on synchrony is elusive because spike synchrony implies unitary spike events of different neurons rather than a causal delayed relationship between neurons. We explore how synchrony can be facilitated by STDP in oscillator networks with a pacemaker. We show that STDP with asymmetric learning windows leads to self-organization of feedforward networks starting from the pacemaker. As a result, STDP drastically facilitates frequency synchrony. Even though differences in spike times are lessened as a result of synaptic plasticity, the finite time lag remains so that perfect spike synchrony is not realized. In contrast to traditional mechanisms of large-scale synchrony based on mutual interaction of coupled neurons, the route to synchrony discovered here is enslavement of downstream neurons by upstream ones. Facilitation of such feedforward synchrony does not occur for STDP with symmetric learning windows.

Original languageEnglish
Pages (from-to)327-345
Number of pages19
JournalJournal of Computational Neuroscience
Volume22
Issue number3
DOIs
Publication statusPublished - 2007 Jun
Externally publishedYes

Keywords

  • Complex networks
  • Feedforward networks
  • Spike-timing-dependent plasticity
  • Synchronization

ASJC Scopus subject areas

  • Sensory Systems
  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience

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