- Poster presentation
- Open Access
STDP encodes oscillation frequencies in the connections of recurrent networks of spiking neurons
© Kerr et al; licensee BioMed Central Ltd. 2012
- Published: 16 July 2012
- Propagation Delay
- Neuron Model
- Basic Learning
- Input Frequency
- Synaptic Strength
Spike-timing-dependent plasticity (STDP) is a learning rule that updates synaptic strengths based on the relative timing of pre- and post-synaptic spikes. Unlike rate-based Hebbian learning, STDP can potentially encode fast temporal correlations in neuronal activity, such as oscillations, in the functional structure of networks of neurons that have axonal and dendritic propagation delays. The motivation behind this study was to understand the different ways that spatiotemporal patterns can be learnt by the recurrent connections in a network of neurons with STDP present. This understanding is vital to uncovering the mechanisms by which basic learning and information processing tasks are performed throughout the brain. A specific example in which these mechanisms may contribute is in explaining how the brain can perceive the pitch of complex sounds up to 300Hz. This work employs and builds upon the analytical framework for learning with STDP used in a previous study .
Funding is acknowledged from the Australian Research Council (ARC Discovery Project #DP1096699). The Bionics Institute acknowledges the support it receives from the Victorian Government through its Operational Infrastructure Support Program.
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