Oscillations, phase-of-firing coding and STDP: an efficient learning scheme (Masquelier et al. 2009)

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The model demonstrates how a common oscillatory drive for a group of neurons formats and reliabilizes their spike times - through an activation-to-phase conversion - so that repeating activation patterns can be easily detected and learned by a downstream neuron equipped with STDP, and then recognized in just one oscillation cycle.
1 . Masquelier T, Hugues E, Deco G, Thorpe SJ (2009) Oscillations, Phase-of-Firing Coding and Spike Timing-Dependent Plasticity: an Efficient Learning Scheme. J. Neurosci. 29(43):13484-13493 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Abstract integrate-and-fire leaky neuron;
Gap Junctions:
Simulation Environment: Brian; Python;
Model Concept(s): Pattern Recognition; Activity Patterns; Coincidence Detection; Temporal Pattern Generation; Oscillations; Synchronization; Spatio-temporal Activity Patterns; Synaptic Plasticity; Long-term Synaptic Plasticity; Unsupervised Learning; STDP;
Implementer(s): Masquelier, Tim [timothee.masquelier at alum.mit.edu];
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