Unsupervised discrimination of patterns in spiking neural networks with excitatory and inhibitory synaptic plasticity

A spiking neural network model is described for learning to discriminate among spatial patterns in an unsupervised manner. The network anatomy consists of source neurons that are activated by external inputs, a reservoir that resembles a generic cortical layer with an excitatory-inhibitory (EI) netw...

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Detalles Bibliográficos
Autores principales: Srinivasa, Narayan, Cho, Youngkwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2014
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4266024/
https://www.ncbi.nlm.nih.gov/pubmed/25566045
http://dx.doi.org/10.3389/fncom.2014.00159

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4266024/
https://www.ncbi.nlm.nih.gov/pubmed/25566045
http://dx.doi.org/10.3389/fncom.2014.00159

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