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Python files for the model: 

Justinas J Dainauskas, Helene Marie, Michele Migliore and Ausra Saudargiene.  
GluN2B-NMDAR subunit contribution on synaptic plasticity: a phenomenological model for CA3-CA1 synapses.
Frontiers in Synaptic Neuroscience 2023 DOI: 10.3389/fnsyn.2023.1113957.

This Python code implements a phenomenological NMDA receptor-based voltage-dependent synaptic plasticity model for synaptic modifications
at hippocampal CA3-CA1 synapse on a two-compartmental hippocampal CA1 pyramidal neuron and shows weight changes for spike timing dependent synaptic plasticity (STDP) and frequency-dependent synaptic plasticity stimulation protocols. The developed model predicts altered learning rules in synapses formed on the apical dendrites of the detailed compartmental model of CA1 pyramidal neuron in the presence of the GluN2B-NMDA receptor hypofunction.

This model should run in Python 3.7.

The code reproduces Fig2, Fig3A, Fig3B, Fig3C, Fig3D, Fig4A, Fig4B, Fig5.    

Run the code: python main.py 

Cooresponding author: ausra.saudargiene at lsmuni.lt

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CA1 pyr cell: phenomenological NMDAR-based model of synaptic plasticity (Dainauskas et al 2023)

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