GLMCC validation neural network model (Kobayashi et al. 2019)


Network model of two populations of randomly connected inhibitory and excitatory neurons to validate method for reconstructing the neural circuitry developed in "Reconstructing Neuronal Circuitry from Parallel Spike Trains" by Ryota Kobayashi, Shuhei Kurita, Anno Kurth, Katsunori Kitano, Kenji Mizuseki, Markus Diesmann, Barry J. Richmond and Shigeru Shinomoto.

Model Type: Realistic Network

Cell Type(s): Abstract integrate-and-fire leaky neuron with exponential post-synaptic current

Model Concept(s): Methods

Simulation Environment: NEST

Implementer(s): Kurth, Anno [a.kurth at fz-juelich.de]

References:

Kobayashi R et al. (2019). Reconstructing neuronal circuitry from parallel spike trains. Nature communications. 10 [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.