#!/usr/bin/env python3
import numpy as np
import grid_generate
def izh(y,t):
v = y[0];
w = y[1];
v_prime = 0.04*v**2 + 5*v + 140 - w + 10
w_prime = 0.02 * (0.2*v - w)
return [v_prime, w_prime]
grid_generate.generate(izh, 0.1, 0.001, 1e-4, 'izh', -30.0, -50.0, 2.0, -85.0, -10.0, -15.0, 20.0, 500, 500)
'w_min': 0.0,
'w_max': 10.0,
'N_w': 20,
}
v = y[0]
w = y[1]
v_prime = (-(v - param_dict['E_r']) - w *
(v - param_dict['E_e'])) / param_dict['tau_m']
w_prime = -w / param_dict['tau_s']
return [v_prime, w_prime]
grid_generate.generate(cond,
1e-05,
1,
1e-12,
'cond',
-55.0e-3,
-65e-3,
0.0,
-67.0e-3,
-54.0e-3,
-0.2,
1.0,
100,
100,
efficacy_orientation='w')
#!/usr/bin/env python3
import numpy as np
import grid_generate
def adEx(y,t):
C = 281
g_l = 30
E_l = -70.6
v_t = -50.4
tau = 2.0
alpha = 4.0
tau_w = 144.0
v = y[0];
w = y[1];
v_prime = (-g_l*(v - E_l) + g_l*tau*np.exp((v - v_t)/tau) - w) / C
w_prime = (alpha*(v - E_l) - w) / tau_w
return [v_prime, w_prime]
grid_generate.generate(adEx, 0.001, 0.001, 1e-12, 'adex', -50.4, -70.6, 80.5, -75, -45, -50, 400, 100, 100)
theta_h = -55
#mV
sig_h = 7
#mV
k = 0.79
I = 0.0
#
I_h = 0
#
v = y[0]
h = y[1]
I_l = -g_l * (v - E_l)
I_na = -g_na * (v - E_na) * h * (((1 + np.exp((v + 35) / -7.8))**-1)**3)
I_k = -g_k * (v - E_k) * ((k - (1.06 * h))**4)
v_prime = ((I_l + I_na + I_k) / C) + I
h_prime = (((1 + (np.exp(
(v - theta_h) / sig_h)))**(-1)) - h) / (30 / (np.exp(
(v + 50) / 15) + np.exp(-(v + 50) / 16))) + I_h
return [v_prime, h_prime]
#grid_generate.generate(rybakInterneuron, 0.001, 0.001, 1e-3, 'rybak_interneuron', 60.0, -64.0, 0.0, -90, 60, -0.4, 1.0,300, 300)
grid_generate.generate(rybak, 0.1, 0.001, 1e-3, 'rybak_burster', -30, -56,
-0.004, -120, -20, -0.4, 1.0, 400, 300)
import grid_generate
def fn(y, t):
param_dict = {
'tau_m': 20e-3,
'E_r': -65e-3,
'E_e': 0e-3,
'tau_s': 5e-3,
'V_min': -66.0e-3,
'V_max': -55.0e-3,
'V_th': -55.0e-3, #'V_max', # sometimes used in other scripts
'N_V': 200,
'w_min': 0.0,
'w_max': 0.8,
'N_w': 20,
'I': 0, #0.5 to match FN mesh
}
v = y[0]
w = y[1]
v_prime = v - v**3 / 3 - w + param_dict['I']
w_prime = .08 * (v + .7 - .8 * w)
return [v_prime, w_prime]
grid_generate.generate(fn, 0.1, 1e-03, 1e-12, 'fn', 2.5, -2.5, 0.0, -2.5, 2.5,
-1.0, 1.2, 500, 500)
V_l = -0.5;
v_1 = 0.05;
v_2 = 0.15;
v_3 = 0;
v_4 = 0.1;
phi_d = 0.2;
v = y[0];
w = y[1];
tau_v = 0.001;
tau_w = 0.001;
I_l = -g_l * (v - V_l);
I_ca = -g_ca * (v - V_ca) * ((1/2)*(1 + (np.tanh((v - v_1)/v_2))));
I_k = -g_k * w * (v - V_k);
w_inf = ((1/2)*(1 + (np.tanh((v - v_3)/v_4))));
tau_s = (1 / np.cosh((v - v_3)/(2*v_4)));
v_prime = (I_l + I_ca + I_k)/tau_v;
w_prime = (phi_d * (w_inf - w) / tau_s)/tau_w;
return [v_prime, w_prime]
grid_generate.generate(BoothRinzelMNSoma, 0.0001, 1, 1e-8, 'soma', 0.98, -1.48, 0.0, -1.5, 1.0, -0.2, 1.2, 300, 300)
grid_generate.generate(BoothRinzelMNDendrite, 0.0001, 1, 1e-8, 'dendrite', 0.98, -1.48, 0.0, -1.5, 1.0, -0.2, 1.2, 300, 300)