# Modified MorrisLecar model
# modified from ml_salka.ode
dV/dt = (i_dcgna*minf(V)*(VVna)gk*y*(VVK)gl*(VVl)gsub*z*(VVsub))/c
dy/dt = phi_y*(yinf(V)y)/tauy(V)
dz/dt = phi_z*(zinf(V)z)/tauz(V)
param c=2
# HERE IS EVERYTHING YOU NEED TO KNOW ABOUT THE STIMULuS
# DC OFFSET
# this is controlled by i_dc
param i_dc=0
## noise not included here.
## To add it, uncomment lines below by removing one "#" per line, and add "i_noise" to line 3 (dv/dt=...) above
## NOISE
## This is modeled as an OrnsteinUhlenbeck process, gives new noise on each trial
## Here is the Wiener variable
#wiener nz
## With scale=0 you get no noise
## effects of changing dt are automatically controlled for in XPP
## However, variance of i_noise also depends on tau_inoise (variance = sigma^2*tau/2)
## Therefore, if you want to keep the same variance, you must manually change sigma_inoise if you change tau_inoise
#di_noise/dt=1/tau_inoise*(i_noisei_avg)+sigma*nz
#param sigma=0, tau_inoise=5, i_avg=0
## frozen noise can be repeated on multiple trials by saving i_noise to a .tab file and playing it back
## see xpp documentation about tables
# HERE IS EVERYTHING YOU NEED TO KNOW ABOUT INTRINSIC CURRENTS
# Initial conditions
V(0)=70
y(0)=0.000025
z(0)=0
# if you want to make sure initial conditions are at steady state
# run trial with no stim, then select "initial conditions/last" from main menu... this will start you at the conditions at the end of your previous trial
# FAST INWARD CURRENT (INa or activation variable)
# This is assumed to activate instantaneously with changes in voltage
# voltagedependent activation curve is described by m
minf(V)=.5*(1+tanh((Vbeta_m)/gamma_m))
# maximal conductance and reversal potential
param beta_m=1.2, gamma_m=18
param gna=20, vna=50
# DELAYED RECTIFIER CURRENT (IKdr or recovery variable)
# this current activates more slowly than INa, but is still faster than Isub or Iadapt (not included here)
# In this code, activation of IKdr is controlled by y
yinf(V)=.5*(1+tanh((Vbeta_y)/gamma_y))
tauy(V)=1/cosh((Vbeta_y)/(2*gamma_y))
# in the 2D model, varying beta_w shifts the w activation curve (w=y here) and can convert the neuron between class 1, 2, and 3
param beta_y=10, gamma_y=10
# maximal conductance and reversal potential
param gk=20, vk=100, phi_y=0.15
# LEAK CURRENT (Il)
# just a passive leak conductance
param gl=2, vl=70
# SLOW SUBTHRESHOLD INWARD OR OUTWARD CURRENT (Isub)
zinf(V)=.5*(1+tanh((Vbeta_z)/gamma_z))
tauz(V)=1/cosh((Vbeta_z)/(2*gamma_z))
param beta_z=21, gamma_z=15
# parameters below are for outward current
param gsub=7, Vsub=100, phi_z=0.15
# for inward current, change to gsub=3, Vsub=50, phi_z=0.5
# these parameters for Isub correspond to those used in Figure 4 of the paper
# slow adaptation is not included in this 3D model.
# following parameters control duration of simulation and axes of default plot
@ total=100000,dt=.1,xlo=100,xhi=60,ylo=.125,yhi=.6,xp=v,yp=y
@ meth=euler
@ MAXSTOR=1000000
done
