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 Changelog --------- 2022-12: Fix 9.0.0 upcoming error: curr used as both variable and function in file epsp.mod