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

This is a detailed neuron model of non-parametric near-optimal latent model acquisition using multisynaptic connections between pre- and postsynaptic neurons.

Model Type: Neuron or other electrically excitable cell

Cell Type(s): Neocortex L2/3 pyramidal GLU cell

Model Concept(s): Synaptic Plasticity

Simulation Environment: NEURON; Python

Implementer(s): Hiratani,Naoki [N.Hiratani at gmail.com]


Hiratani N, Fukai T. (2018). Redundancy in synaptic connections enables neurons to learn optimally. Proceedings of the National Academy of Sciences of the United States of America. 115 [PubMed]

This website requires cookies and limited processing of your personal data in order to function. By continuing to browse or otherwise use this site, you are agreeing to this use. See our Privacy policy and how to cite and terms of use.