Scripts used for the single-compartment simulations of the plasticity in the post-synaptic spine using NEURON RxD simulator. Contains also the scripts for drawing the Figures of the paper.

N.B. Version 7.5 of NEURON needed. Some problems found with version 7.6-7.7: the line "reaction256 = rxd.Reaction(specs[195] > specs[195]*0, ks[404])" in model_nrn*.py should be replaced with an alternative reaction describing the decay of ACh, e.g. "specs.append(rxd.Species(cyt, name='null', charge=0, initial=0.0)); reaction256 = rxd.Reaction(specs[195] > specs[-1], ks[404])"

• The calculation of synaptic conductance based on types and numbers of GluR1s and GluR2s at the membrane. Used by drawfig6.py, other scripts include nested calculations.

• The calculation of synaptic conductance based on types and numbers of GluR1s and GluR2s at the membrane using a "dimer of like dimers" rule.

• Draws Figure 11. Before running this, run the simulations in script runfig11.sh in this folder.

• Draws Figure 2. Before running this, run the simulations in script runfig2.sh in this folder and runfig2_nrd.sh in ../NeuroRD.

• Draws Figure 3. Before running this, run the simulations in script runfig3-4.sh in this folder and runfig3-4_nrd.sh in ../NeuroRD.

• Draws Figure 3.1A-B and Figure 3.2A (Extended data set). Before running this, run the simulations in script runfig3_1.sh in this folder.

• Draws Figure 4. Before running this, run the simulations in script runfig3-4.sh in this folder and runfig3-4_nrd.sh in ../NeuroRD.

• Draws Figure 5. Before running this, run the simulations in script runfig5.sh in this folder.

• Draws Figure 9 panels A-C. Before running this, run the simulations in script runfig9.sh in this folder.

• A multi-objective optimization algorithm from Bahl et al. 2012 with slight modifications. Used for fitting the parameters for Fig. 9 - not needed here for fitting though.

• A python script that simulates the PKA activation given cAMP input. Runs the script model_nrn_testPKA_withdiss_williamson_varyrates.py and processes the results. Used for Fig. 1.

• Pre-saved parameters from the fittings. Needed by fitter_fewer1withCK_check_given.py and fitter_fewer_check_given.py.

• Pre-saved parameters from the fittings with many parameters. Needed by fitter_manyb_check_given.py.

• A python script that fits the parameters to cortical LTP/LTD data. A very heavy operation.

• A python script that runs a single simulation of the best given parameter sets from the fitting of cortical LTP/LTD data.

• A python script that re-runs the best models with the fitted parameters and saves the time courses in a high resolution. Needed for Fig. 9.

• A python script that re-runs the best given models with the fitted parameters and saves the time courses in a high resolution. Needed for Fig. 9.

• A python script that re-runs the best given models for the fitting where many parameters were optimized and saves the time courses in a high resolution. Needed for Fig. 9.

• A data file produced by NeuroRD simulator but used as an input in some of the files in this folder too.

• The main simulation script. Loads the model and runs the simulation using NEURON RxD. Used for almost all figures.

• The same as model_nrn_altered_noU.py, but saves the simulation data into an file name given as an argument. Records all species mentioned in protocols.py. Free Ca2+ recoded in high temporal resolution, others downsampled.

• The same as model_nrn_altered_noU.py, but saves the simulation data into an file name given as an argument. Records all species mentioned in protocols.py using a low resolution.

• The same as model_nrn_altered_noU.py, but does not down-sample the output data. Results in super large files.

• The same as model_nrn_altered_noU.py, but uses the old CaM activation model (as in Jedrzejewska-Szmek et al. 2017)

• The same as model_nrn_oldCaM_altered_noU.py, but save more stuff and use external file name.

• The same as model_nrn_altered_noU.py, but uses Ca fluxes that are determined by the NMDAR-conducted Ca currents in ../L23PC based on the paired stimulus protocol.

• A minimal model for testing the PKA activation as descrived in Jedrzejewska-Szmek et al. 2017. Used for Fig. 1.

• A minimal model for testing the PKA activation as descrived in Williamson et al. 2009. Used for Fig. 1.

• Generic tools

• Stimulation protocols used in Fig. 9 and species recorded for Fig. 3

• Stimulation protocols used in Fig. 9, two data sets being fitted without data on CK-blocked experiments

• Stimulation protocols used in Fig. 9, two data sets being fitted without data on CK-blocked experiments, and one data set with an additional CK-blocked experiment

• A graph made out of the reactions where the nodes are the species and the edges represent information whether there's a reaction affecting the two species.

• A script that runs NEURON simulations needed for Fig. 11

• A script that runs NEURON simulations needed for Fig. 2

• A script that runs NEURON simulations needed for Fig. 3-4

• A script that runs NEURON simulations needed for Extended data Fig. 3.1A-B and 3.2A

• A script that runs NEURON simulations needed for Fig. 5

• A script that runs NEURON simulations needed for Fig. 9 panels A-C

• Runs simulations with steady-state fluxes. Uses script model_nrn_altered_noU_extfilename_lowmem_recall.py with a range of Ca2+ flux amplitudes and a given neuromodulator flux $FLUX - saves to steadystate_flux${FLUX}.sav. Used for Fig. 3.

• Runs simulations with steady-state fluxes using the molecular species present in Li et al. 2020, Plos Comput Biol.

• The same as simsteadystate_li2020.py, but uses the old CaM activation model (as in Jedrzejewska-Szmek et al. 2017)