Efficient simulation environment for modeling large-scale cortical processing (Richert et al. 2011)


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Accession:142062
"We have developed a spiking neural network simulator, which is both easy to use and computationally efficient, for the generation of large-scale computational neuroscience models. The simulator implements current or conductance based Izhikevich neuron networks, having spike-timing dependent plasticity and short-term plasticity. ..."
Reference:
1 . Richert M, Nageswaran JM, Dutt N, Krichmar JL (2011) An efficient simulation environment for modeling large-scale cortical processing. Front Neuroinform 5:19 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Neocortex;
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s): GabaA; GabaB; AMPA; NMDA;
Gene(s):
Transmitter(s):
Simulation Environment: C or C++ program (web link to model);
Model Concept(s): Short-term Synaptic Plasticity; Long-term Synaptic Plasticity; Methods; STDP;
Implementer(s):
Search NeuronDB for information about:  GabaA; GabaB; AMPA; NMDA;
(located via links below)
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