Models that contain the Modeling Application : PyNN (Home Page)

(PyNN (pronounced 'pine' ) is a Python package for simulator- independent specification of neuronal network models. In other words, you can write the code for a model once, using the PyNN API, and then run it without modification on any simulator that PyNN supports (currently NEURON, NEST and PCSIM).)
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    Models
1.  Asynchronous irregular and up/down states in excitatory and inhibitory NNs (Destexhe 2009)
2.  Cortical Basal Ganglia Network Model during Closed-loop DBS (Fleming et al 2020)
3.  Mesoscopic dynamics from AdEx recurrent networks (Zerlaut et al JCNS 2018) (PyNN)
4.  Networks of spiking neurons: a review of tools and strategies (Brette et al. 2007)
5.  Single Trial Sequence learning: a spiking neurons model based on hippocampus (Coppolino et al 2021)

Re-display model names with descriptions