Firing patterns in delayed feedforward networks with STDP rules

We investigate the evolution of a delayed feedforward network model with plasticity. It is found that desynchronized and synchronized firing patterns both exist in the feedforward network (FFN) with different synaptic delays. Synaptic delays may play a significant role in bridging rate coding and ti...

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Bibliographic Details
Main Authors: Yan-Qiu Che, Ying-Mei Qin, Jia Zhao, Chun-xiao Han
Format: Conference Proceeding
Language:English
Subjects:
Biological neural networks
Couplings
Delays
Encoding
Feedforward network
Feedforward neural networks
Firing rate propagation
Neurons
STDP rules
Synchronization
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Description
Summary:We investigate the evolution of a delayed feedforward network model with plasticity. It is found that desynchronized and synchronized firing patterns both exist in the feedforward network (FFN) with different synaptic delays. Synaptic delays may play a significant role in bridging rate coding and time coding. Then we focus on the evolution of firing rate and synaptic weights in the FFN network based on the spike-timing dependent plasticity (STDP) rules. The firing rates can be reliably transmitted after the evolution based on STDP rules. The mean synaptic weights tend to be saturated after certain time of evolution. Furthermore, the firing information can be shifted by the changes of network connection and STDP rules through the FFN network.
ISSN:2161-2927
DOI:10.23919/ChiCC.2017.8027648