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

ModelDB is moving. Check out our new site at https://modeldb.science. The corresponding page is https://modeldb.science/225075.

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

Download zip file
Help downloading and running models

Model Information
Model File
Citations
Versions on GitHub

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];