def two_stn_cell():
current_unit = b2.pA
par_sim['simulation_time'] = 2000 * b2.ms
start_time = time()
fig, ax = plt.subplots(3, figsize=(10, 5), sharex=True)
i_stim = [0.]
for ii in range(len(i_stim)):
st_mon = simulate_2_STN_cell_biexp(par, par_sim)
plot_data(st_mon, ax[ii], index=1)
ax[0].plot(st_mon.t / b2.ms, st_mon.vs[0] /
b2.mV, lw=2, c='b', label="0")
ax[0].plot(st_mon.t / b2.ms, st_mon.vs[1] /
b2.mV, lw=2, c='r', label="1")
ax[1].plot(st_mon.t/b2.ms, st_mon.s_ss[0], lw=2, c='b', label="0")
ax[1].plot(st_mon.t/b2.ms, st_mon.s_ss[1], lw=2, c='r', label="1")
ax[0].legend()
ax[1].legend()
ax[0].set_xlim(0, np.max(st_mon.t / b2.ms))
ax[0].set_ylabel("v [mV]", fontsize=14)
ax[1].set_ylabel("s_syn", fontsize=14)
ax[-1].plot(st_mon.t / b2.ms,
st_mon.i_syn_ss[1] / current_unit, lw=1, c='k', alpha=0.5)
ax[-1].set_xlabel("t [ms]", fontsize=14)
ax[-1].set_ylabel("I_syn [{}]".format(str(current_unit)), fontsize=14)
# ax[-1].set_xlim(300, 330)
print("Done in {}".format(time() - start_time))
plt.tight_layout()
plt.savefig('figure_2_stn.png')
plt.show()
def plot_details(filename='figure_1.png'):
par['record_from'] = [
"vg", "Iapp", "iNap", "iNaf", 'iKv2', 'iKv3', 'iKv4f', 'iKv4s',
'iCah', 'iSk', 'iKcnq'
]
par_sim['simulation_time'] = 100 * b2.ms
current_unit = b2.uA
start_time = time()
i_stim = [2.0]
_, ax = plt.subplots(len(i_stim) + 1, figsize=(6, 8), sharex=True)
# make_grid(nrows, ncols, left, right, hspace, wspace, bottom, top)
ax = make_grid(3, 1, 0.2, 0.95, 0.18, 0, 0.1, 0.95)
for ii in range(len(i_stim)):
input_current = get_step_current(50, 100, b2.ms,
i_stim[ii] * current_unit)
par['iapp'] = input_current
st_mon = simulate_GPe_cell(par, par_sim)
plot_data(st_mon, ax[ii], lw=1, c='k')
# plot_current(st_mon, ax[-2], current_unit)
plot_channel_currents(st_mon, ax[1:], current_unit)
ax[0].set_xlim(75, 90)
ax[1].set_xlim(75, 90)
ax[2].set_xlim(75, 90)
print("Done in {:.3f}".format(time() - start_time))
plt.savefig(filename)
plt.close()
def figure2():
fig = plt.figure(figsize=(10, 6))
gs = GridSpec(6, 1)
gs.update(left=0.1, right=0.95)
ax1 = plt.subplot(gs[:2])
ax2 = plt.subplot(gs[2])
ax3 = plt.subplot(gs[3:5])
ax4 = plt.subplot(gs[5])
ax = [ax1, ax2, ax3, ax4]
start_time = time()
I_sm1 = b2.TimedArray([0, 2, 0, 5, 0, 10, 0]*b2.pA, dt=100*b2.ms)
par_sim['I_sm'] = I_sm1
state_monitor = simulate_Thl_cell_fig2(par, par_sim)
plot_data(state_monitor, ax[0])
plot_current(state_monitor, ax[1])
I_sm2 = b2.TimedArray([0, 0, -0.5, 0, 0, -1, 0, 0]*b2.pA, dt=100*b2.ms)
par_sim['I_sm'] = I_sm2
par['i_ext'] = 0.0
state_monitor = simulate_Thl_cell_fig2(par, par_sim)
print("Done in {}".format(time() - start_time))
plot_data(state_monitor, ax[2])
plot_current(state_monitor, ax[3], xlabel="Time [ms]")
[ax[i].set_xticks([]) for i in range(3)]
[ax[i].set_xlim([0, 1000]) for i in range(4)]
plt.savefig(join("data", "figure2.png"))
plt.show()
def figure3():
fig, ax = plt.subplots(nrows=2, ncols=1, figsize=(10, 4), sharex=True)
start_time = time()
par_sim['I_sm'] = 0*b2.pA
par_sim['i_ext'] = 0.*b2.pA
par_ = {**par, **par_SM}
state_monitor = simulate_Thl_cell_fig3(par_, par_sim)
plot_data(state_monitor, ax[0])
plot_current(state_monitor, ax[1])
plt.savefig(join("data", "figure3.png"))
plt.show()
print("Done in {}".format(time() - start_time))
def plot_fig_1e():
start_time = time()
fig, ax = plt.subplots(4, figsize=(10, 6), sharex=True)
t_stim = [300, 450, 600]
for ii in range(len(t_stim)):
input_current = get_step_current(500,
500 + t_stim[ii],
b2.ms,
-25 * b2.pA)
par['i_ext'] = input_current
st_mon = simulate_STN_cell(par, par_sim)
plot_data(st_mon, ax[ii])
plot_current(st_mon, ax[3])
print("Done in {}".format(time() - start_time))
plt.tight_layout()
plt.savefig('figure_1e.png')
plt.close()
def plot_fig_1f():
current_unit = b2.pA
start_time = time()
fig, ax = plt.subplots(4, figsize=(10, 6), sharex=True)
i_stim = [-20, -30, -40]
for ii in range(len(i_stim)):
input_current = get_step_current(500,
800,
b2.ms,
i_stim[ii] * current_unit)
par['i_ext'] = input_current
st_mon = simulate_STN_cell(par, par_sim)
plot_data(st_mon, ax[ii])
plot_current(st_mon, ax[3], current_unit)
print("Done in {}".format(time() - start_time))
plt.tight_layout()
plt.savefig('figure_1f.png')
plt.close()
def plot():
current_unit = b2.uA
start_time = time()
i_stim = [2, 4, 6]
_, ax = plt.subplots(len(i_stim)+1, figsize=(10, 6), sharex=True)
for ii in range(len(i_stim)):
input_current = get_step_current(200,
700,
b2.ms,
i_stim[ii] * current_unit)
par['i_ext'] = input_current
st_mon = simulate_FSI_cell(par, par_sim)
plot_data(st_mon, ax[ii])
plot_current(st_mon, ax[3], current_unit)
print("Done in {:.3f}".format(time() - start_time))
plt.tight_layout()
plt.savefig('data/figure_1.png')
plt.close()
def plot(filename="figure_0.png"):
par['record_from'] = ["vg", "Iapp"]
par_sim['simulation_time'] = 500.0 * b2.ms
current_unit = b2.uA
start_time = time()
i_stim = [2.0]
_, ax = plt.subplots(len(i_stim) + 1, figsize=(10, 5), sharex=True)
for ii in range(len(i_stim)):
input_current = get_step_current(100, 300, b2.ms,
i_stim[ii] * current_unit)
par['iapp'] = input_current
st_mon = simulate_GPe_cell(par, par_sim)
plot_data(st_mon, ax[ii], lw=1, c='k')
plot_current(st_mon, ax[-1], current_unit)
# plot_channel_currents(st_mon, ax[-1], current_unit)
ax[0].set_xlim(0, 500)
print("Done in {:.3f}".format(time() - start_time))
plt.tight_layout()
plt.savefig(filename)
plt.close()
def simulate_2_gpe_cell():
start_time = time()
current_unit = b2.pA
par_sim['simulation_time'] = 300 * b2.ms
fig, ax = plt.subplots(3, figsize=(10, 6), sharex=True)
par_g['iapp'] = -0.5 * b2.pA
st_mon = simulate_two_GPe_cell(par_g, par_sim)
plot_data(st_mon, ax[0])
ax[0].plot(st_mon.t / b2.ms,
st_mon.vg[0] / b2.mV,
lw=2,
c='b',
label="0")
ax[0].plot(st_mon.t / b2.ms,
st_mon.vg[1] / b2.mV,
lw=2,
c='r',
label="1")
ax[1].plot(st_mon.t / b2.ms, st_mon.s_gg[0], lw=2, c='b', label="0")
ax[1].plot(st_mon.t / b2.ms, st_mon.s_gg[1], lw=2, c='r', label="1")
ax[0].legend()
ax[1].legend()
ax[0].set_xlim(0, np.max(st_mon.t / b2.ms))
ax[0].set_ylabel("v [mV]", fontsize=14)
ax[1].set_ylabel("s_syn", fontsize=14)
ax[-1].plot(st_mon.t / b2.ms,
st_mon.i_syn_gg[1] / current_unit,
lw=1,
c='k',
alpha=0.5)
ax[-1].set_xlabel("t [ms]", fontsize=14)
ax[-1].set_ylabel("I_syn [{}]".format(str(current_unit)), fontsize=14)
# ax[-1].set_xlim(290, 310)
print("Done in {} seconds".format(time() - start_time))
plt.tight_layout()
plt.savefig('figure_2_gpe.png')
plt.close()
def simulate_1_gpe_cell():
start_time = time()
current_unit = b2.pA
# Figure 2 ------------------------------------------------------
fig, ax = plt.subplots(5, figsize=(10, 8))
i_stim = [20, 0, -0.5, 170.]
for ii in range(len(i_stim)):
input_current = get_step_current(0, 1000, b2.ms,
i_stim[ii] * current_unit)
if ii == 3:
input_current = get_step_current(100, 250, b2.ms,
i_stim[ii] * current_unit)
par_sim['simulation_time'] = 350 * b2.ms
par_g['i_ext'] = input_current
st_mon = simulate_GPe_cell(par_g, par_sim)
plot_data(st_mon, ax[ii], title=str(i_stim[ii]))
plot_current(st_mon, current_unit, ax[-1], [-1, 22])
print("Done in {} seconds".format(time() - start_time))
plt.tight_layout()
plt.savefig('figure_2.png')
plt.close()
def plot():
current_unit = b2.uA
start_time = time()
i_stim = [1.67]
_, ax = plt.subplots(len(i_stim) + 3, figsize=(10, 7), sharex=True)
for ii in range(len(i_stim)):
input_current = b2.TimedArray([0, i_stim[ii], 0, i_stim[ii], 0] *
b2.uA,
dt=200 * b2.ms)
# input_current = get_step_current(50,
# 200,
# b2.ms,
# i_stim[ii] * current_unit)
par['iapp'] = input_current
st_mon = simulate_MSN_cell(par, par_sim)
plot_data(st_mon, ax[ii], lw=1, c='k')
plot_h(st_mon, ax[-2])
plot_m(st_mon, ax[-3])
plot_current(st_mon, ax[-1], current_unit)
print("Done in {:.3f}".format(time() - start_time))
plt.tight_layout()
plt.savefig('data/figure_1.png')
plt.close()
'tau_peak_i': tau_peak_i * b2.ms,
}
par_syn = {
'v_rev_e': 0 * b2.mV,
'v_rev_i': -75 * b2.mV,
'w_ei': 1,
'w_ie': 1,
'w_ee': 1,
'w_ii': 1,
'p_ie': p_ie,
'p_ei': p_ei,
'p_ee': p_ee,
'p_ii': p_ii,
}
par_e['tau_dq_e'] = tau_d_q_function(tau_d_e, tau_r_e, tau_peak_e) * b2.ms
par_i['tau_dq_i'] = tau_d_q_function(tau_d_i, tau_r_i, tau_peak_i) * b2.ms
par_syn['g_ei'] = g_hat_ei / (num_e * p_ei) * b2.msiemens
par_syn['g_ee'] = g_hat_ee / (num_e * p_ee) * b2.msiemens
par_syn['g_ie'] = g_hat_ie / (num_i * p_ei) * b2.msiemens
par_syn['g_ii'] = g_hat_ii / (num_i * p_ii) * b2.msiemens
par_e['I_e'] = 1.4 * np.ones(num_e) * (1 + sigma_e * randn(num_e)) * b2.uA
par_i['I_i'] = 0.0 * np.ones(num_i) * (1 + sigma_i * randn(num_i)) * b2.uA
par_sim = {'simulation_time': 200 * b2.ms, 'integration_method': 'rk4'}
monitors = simulate_PING(par_e, par_i, par_syn, par_sim)
print("done in {}".format(time.time() - start_time))
plot_data(monitors, num_e, num_i)