Scripts for simulating the neuron and cardiac cell models and producing Figure 1 and 2.
(CC BY 3.0) Tuomo Maki-Marttunen 2016
To run the scripts, run command 'runme' in MATLAB. Note that you may have to run the
NEURON simulations from command line instead of running them through MATLAB. This can
be done by runnning 'sh runme.sh' in folders hay/ and almog/.
Folders included:
hay/: Scripts and files for running the Hay model (Hay E, Hill S, Schuermann F, Markram H, and Segev I (2011): Models of neocortical layer 5b pyramidal cells capturing a wide range of dendritic and perisomatic active properties, PLoS Comput Biol 7: e1002107)
-Most of the files based on the implementation given in https://senselab.med.yale.edu/modeldb/showModel.cshtml?model=139653
-Files specific to this entry:
hay/calcifcurves.py: Python script with NEURON interface to calculate the f-I curves
hay/calcsteadystates.py: Python script with NEURON interface to calculate the membrane potential time courses for steady-state firing
hay/findDCshortthreshold.py: Python script with NEURON interface to find the smallest DC amplitudes for inducing a spike
hay/mutation_stuff.py: Table of mutations
hay/mytools.py: Generic tools for e.g. determining spike times
hay/collectfig1.py: Script for refining the results for Figure 1
hay/collectfig2.py: Script for refining the results for Figure 2
hay/runme.sh: Shell script for running the Hay-model simulation part from runme.m
-Pre-calculated data:
hay/fig1_curves.mat: MATLAB data file for plotting the Hay model results for Figure 1 (only the results that are heaviest to simulate are included)
hay/fig2_curves.mat: MATLAB data file for plotting the Hay model results for Figure 2 (only the results that are heaviest to simulate are included)
almog/: Scripts and files for running the Almog model (Almog M and Korngreen A (2014): A quantitative description of dendritic conductances and its application to dendritic excitation in layer 5 pyramidal neurons, J Neurosci 34.1: 182-196)
-Most of the files based on the implementation given in https://senselab.med.yale.edu/modeldb/showModel.cshtml?model=151825
-Files specific to this entry:
almog/calcifcurves.py: Python script with NEURON interface to calculate the f-I curves
almog/calcsteadystates.py: Python script with NEURON interface to calculate the membrane potential time courses for steady-state firing
almog/findDCshortthreshold.py: Python script with NEURON interface to find the smallest DC amplitudes for inducing a spike
almog/mutation_stuff.py: Table of mutations
almog/mytools.py: Generic tools for e.g. determining spike times
almog/collectfig1.py: Script for refining the results for Figure 1
almog/collectfig2.py: Script for refining the results for Figure 2
almog/runme.sh: Shell script for running the Almog-model simulation part from runme.m
-Pre-calculated data:
almog/fig1_curves.mat: MATLAB data file for plotting the Almog model results for Figure 1 (only the results that are heaviest to simulate are included)
almog/fig2_curves.mat: MATLAB data file for plotting the Almog model results for Figure 2 (only the results that are heaviest to simulate are included)
kharche/: Scripts and files for running the Kharche model (Kharche S, Yu J, Lei M, and Zhang H (2011): A mathematical model of action potentials of mouse sinoatrial node cells with molecular bases, Am J Physiol-Heart Circ Physiol 301.3: H945-H963)
-Model implementation based on the previous entry (C-code) https://senselab.med.yale.edu/ModelDB/ShowModel.cshtml?model=141274
-Order of certain variable updates changed in kharche_SA.m w.r.t. the original code in order to give a state update that is consistent across different dt
calcrates_kharche.m: MATLAB script for simulating the cells implemented with variants
getDefVals_kharche.m: MATLAB function that returns the default model parameters
getMT_kharche.m: MATLAB function that returns the table of mutations
kharche_SA.m: MATLAB function that simulates the SANC model and returns the membrane potential time courses and other data
runcontrol_kharche.m: MATLAB script for running the control SANC model
severi/: Scripts and files for running the Severi model (Severi S, Fantini M, Charawi LA, and DiFrancesco D (2012): An updated computational model of rabbit sinoatrial action potential to investigate the mechanisms of heart rate modulation, J Physiol 590.18: 4483-4499)
-Model implementation based on the CellML entry https://models.physiomeproject.org/w/sseveri/severi_fantini_charawi_difrancesco_2012
calcrates_severi.m: MATLAB script for simulating the cells implemented with variants
getDefVals_severi.m: MATLAB function that returns the default model parameters
getMT_severi.m: MATLAB function that returns the table of mutations
severi_SA.m: MATLAB function that simulates the SANC model and returns the membrane potential time courses and other data
runcontrol_severi.m: MATLAB script for running the control SANC model
Files in the main folder:
runme.m: Script for running all required simulations to draw Figure 1 and 2
drawfig1: Script for drawing Figure 1
drawfig2: Script for drawing Figure 2
getMT_kharche.m, getgenenames.m: Auxiliary MATLAB files for the mutation data
interpolate.m, interpolate_multidim.m, membpotderivs.m, subplottight2.m: Auxiliary MATLAB tools