A model of optimal learning with redundant synaptic connections (Hiratani & Fukai 2018)

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Accession:225075
This is a detailed neuron model of non-parametric near-optimal latent model acquisition using multisynaptic connections between pre- and postsynaptic neurons.
Reference:
1 . Hiratani N, Fukai T (2018) Redundancy in synaptic connections enables neurons to learn optimally. Proc Natl Acad Sci U S A 115:E6871-E6879 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Neocortex L2/3 pyramidal GLU cell;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; Python;
Model Concept(s): Synaptic Plasticity;
Implementer(s): Hiratani,Naoki [N.Hiratani at gmail.com];
Search NeuronDB for information about:  Neocortex L2/3 pyramidal GLU cell;
 
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HirataniFukai2018
data
nrn_simul_vkappas_RA100_gm0.0025_dm_active.txt
                            
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