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Functional balanced networks with synaptic plasticity (Sadeh et al, 2015)

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The model investigates the impact of learning on functional sensory networks. It uses large-scale recurrent networks of excitatory and inhibitory spiking neurons equipped with synaptic plasticity. It explains enhancement of orientation selectivity and emergence of feature-specific connectivity in visual cortex of rodents during development, as reported in experiments.
1 . Sadeh S, Clopath C, Rotter S (2015) Emergence of Functional Specificity in Balanced Networks with Synaptic Plasticity. PLoS Comput Biol 11:e1004307 [PubMed]
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:
Transmitter(s): Gaba; Glutamate;
Simulation Environment: Python;
Model Concept(s): Synaptic Plasticity; Long-term Synaptic Plasticity; Learning; Sensory processing; Homeostasis; Orientation selectivity; Vision;
Implementer(s): Sadeh, Sadra [s.sadeh at];
Search NeuronDB for information about:  Gaba; Glutamate;
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