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]


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

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