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- import scipy as sp
- import pylab as plt
- from scipy.integrate import odeint
- from scipy import stats
- import scipy.linalg as lin
- ## Hodgkin-Huxley Model For L-Type Voltage-dependent Ca2+ Channel EGL-19
- ## Jospin M. et.al V.S. Boyle and Cohen
- # Constants
- g_Ca1 = 220.0 # maximum conducances, in mS/cm^2
- g_Ca = 199
- #g_Ca = 127
- a_Ca = 0.283
- E_Ca1 = 49.1 # Nernst reversal potentials, in mV
- E_Ca = 50.0
- #E_Ca = 59.0
- E_half_Ca = 0.9
- #E_half_Ca = 6.4
- E_half_e = -3.4
- E_half_f = 25.2 #5.2 is much better
- Ca_half_h = 64.1 * sp.power(10,-9)
- k_Ca = 4.9 #mV
- #k_Ca = 7.9 #mV
- k_e = 6.7
- k_f = 5.0 #
- k_h = -0.01 #mM
- Ca_Con = 2.39 * sp.power(10,-6)
- # Channel currents (in mA/cm^2)
- def I_Ca_boyle(V): return g_Ca1 * e(V)**2 * f(V) * (1 + (h - 1) * a_Ca) * (V - E_Ca1) / 1000
- def I_Ca(V): return g_Ca * (V - E_Ca) / ((1 + sp.exp((E_half_Ca - V) / k_Ca)) * 1000)
- # The voltage to integrate over
- V = sp.arange(-70, 80, 1)
- # Gating Kinetics
- def X_inf(V, V_half_x, k_x): return 1 / (1 + sp.exp((V_half_x - V) / k_x))
- def e(V): return X_inf(V, E_half_e, k_e)
- def f(V): return X_inf(V, E_half_f, k_f)
- h = X_inf(Ca_Con, Ca_half_h, k_h)
- icab = I_Ca_boyle(V)
- ica = I_Ca(V)
- plt.figure()
- plt.subplot(1,1,1)
- plt.plot(V, ica, 'r', label='$I_{Ca}$')
- plt.plot(V, icab, 'y', label='$I_{Ca}-Boyle$')
- plt.ylabel('I (A/F)')
- plt.xlabel('Em (mV)')
- plt.legend()
- plt.show()
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