nbNeurons1, meanRates1, meanRatesStd1, s = simulate_selection_vs_neurons(
sel_interval_1, hz=20, load=True)
s = s + ' %s %5s %3s \n' % ('Sel thr:', str(SELECTION_THR), 'Hz')
s = s + ' \n%s %5s %3s \n' % ('Sel interval 1:', str(sel_interval_1),
'pA')
info_string = info_string + s
misc.pickle_save([nbNeurons1, meanRates1, meanRatesStd1, info_string],
save_result_at)
else:
print 'hej'
#nbNeurons1, meanRates1, meanRatesStd1, info_string = misc.pickle_load(save_result_at)
# DISPLAY
plot_settings.set_mode(pylab,
mode='by_fontsize',
w=1100.0,
h=450.0,
fontsize=12)
font_size_text = 8
fig = pylab.figure(facecolor='w')
ax_list = []
ax_list.append(MyAxes(fig, [.075, .37, .135, .26])) # text box
ax_list.append(MyAxes(fig, [.26, .6, .165, .34])) #
ax_list.append(MyAxes(fig, [.53, .6, .165, .34])) #
ax_list.append(MyAxes(fig, [.26, .1, .165 * 2.312, .34])) #
ax_list.append(MyAxes(fig, [.8, .6, .165, .34])) #
#ax_list.append( MyAxes(fig, [ .53, .1, .165, .34 ] ) ) #
ax_list.append(MyAxes(fig, [.8, .1, .165, .34])) #
# Text
frequenciesAll, steadyStateFacilitationAll = simulate_steady_state_freq(numpy.arange(1.,100.,1.))
# Max conductance all frequencies
if LOAD:
sname_nb=0
frequenciesAll, maxFacilitationAll = simulate_steady_state_freq(numpy.arange(1.,100.,1.),
flag='max')
# Recovery spike
revoceryTimes, relativeRecovery = simulate_recovery(numpy.arange(100,5000,200))
# Steady state conductance 0-1 frequencies
frequenciesZoom, relativeFacilitationZoom = simulate_steady_state_freq(numpy.arange(0.1,1.,.1))
# DISPLAY
plot_settings.set_mode(mode='by_fontsize', w = 750.0, h = 400.0, fontsize=12)
font_size_text = 9
fig = pylab.figure( facecolor = 'w' )
ax_list = []
ax_list.append( MyAxes(fig, [ .1, .4, .18, .26 ] ) ) # text box
ax_list.append( MyAxes(fig, [ .35, .6, .24, .34 ] ) ) #
ax_list.append( MyAxes(fig, [ .73, .6, .24, .34 ] ) ) #
ax_list.append( MyAxes(fig, [ .35, .1, .24, .34 ] ) ) #
ax_list.append( MyAxes(fig, [ .73, .1, .24, .34 ] ) ) #
# Text
ax=ax_list[0]
plot_text(ax)
# Example steady state all
return xopt sim_time=20000 save_at=OUTPUT_PATH+'/simulate_network_fmin.plk' x=fmin(0,save_at) #x=[215, 0.08] STN_target1, e1=restriction_1(gpe_rate, n_ctx, n_gpe, x, neuron_model, syn_models) STN_target2, e2=restriction_2(gpe_rate, n_ctx, n_gpe, x, neuron_model, syn_models) STN_target3 = GPE_46_hz(gpe_rate, n_ctx, n_gpe, x, neuron_model, syn_models) plot_settings.set_mode(pylab, mode='by_fontsize', w = 500.0, h = 500.0, fontsize=8) font_size_text = 8 fig = pylab.figure( facecolor = 'w') ax_list=[] ax_list.append( MyAxes(fig, [ .1, .7, .8, .2 ] ) ) # text box ax_list.append( MyAxes(fig, [ .1, .4, .8, .2 ] ) ) # ax_list.append( MyAxes(fig, [ .1, .1, .8, .2 ] ) ) # ax=ax_list[0] plot_example(ax, STN_target1,sim_time, x, type='No GPE') ax=ax_list[1] plot_example(ax, STN_target2, sim_time, x, type='Normal') ax=ax_list[2]
# input
sgs = my_nest.Create('spike_generator',
params={'spike_times': [float(sp) for sp in spike_times]})
syn_model = 'MSN_MSN_gaba_s'
my_nest.Connect(sgs, [MSN[0]], model=syn_model) # connect MSNs
T = 2000 # simulation time
my_nest.Simulate(T) # simulate
MSN.get_signal('v', 'V_m')
pylab.close('all') # display
# Create figure where figsize(width,height) and figure dimenstions window
# width = figsize(width) x dpi and window hight = figsize(hight) x dpi
plot_settings.set_mode(mode='dynamic', w=700.0, h=400.0)
font_size_text = 10
fig = pylab.figure(facecolor='w')
pylab.suptitle('MSN to MSN')
ax_list = []
ax_list.append(MyAxes(fig, [.1, .37, .2, .26])) # text box
ax_list.append(MyAxes(fig, [.50, .15, .40, .65])) # voltage trace
ds = my_nest.GetDefaults(syn_model)
sn = my_nest.GetStatus(MSN[:])[0]
ax = ax_list[0] # Text box
tb = ''
tb = tb + ' %6s %7s %3s \n' % ('Synapse model:', ds['synapsemodel'], ' ')
tb = tb + ' \n '
n_gpe = 32
stn_rate = 10.0
n_exp = 4.
SNR_target1, mr1, std1, e1 = restriction_1(msn_rate, gpe_rate, stn_rate, n_msn,
n_gpe, x, neuron_model, syn_models,
n_exp)
SNR_target2, mr2, std2, e2 = restriction_2(msn_rate, gpe_rate, stn_rate, n_msn,
n_gpe, x, neuron_model, syn_models,
n_exp)
SNR_target3, mr3, std3, e3 = restriction_3(msn_rate, gpe_rate, stn_rate, n_msn,
n_gpe, x, neuron_model, syn_models,
n_exp)
plot_settings.set_mode(pylab,
mode='by_fontsize',
w=1000.0,
h=1000.0,
fontsize=16)
font_size_text = 8
fig = pylab.figure(facecolor='w')
ax_list = []
ax_list.append(MyAxes(fig, [.1, .7, .8, .2])) # text box
ax_list.append(MyAxes(fig, [.1, .4, .8, .2])) #
ax_list.append(MyAxes(fig, [.1, .1, .8, .2])) #
ax = ax_list[0]
plot_example(ax, SNR_target1, sim_time, x, [mr1, std1], type='No GABA')
ax = ax_list[1]
plot_example(ax, SNR_target2, sim_time, x, [mr2, std2], type='No STN')