def run_simulation_NET(tauE_, wE_, tauI_, wI_, Group, Target, G_CPU1A, G_CPU1B,
G_PONTINE, G_MOTOR, S_TB1_CPU4, S_TN2_CPU4, S_TB1_CPU1A,
S_CPU4_PONTINE, S_CPU4_CPU1A, S_PONTINE_CPU1A,
S_TB1_CPU1B, S_CPU4_CPU1B, S_PONTINE_CPU1B,
S_CPU1A_MOTOR, S_CPU1B_MOTOR, time, dt_, delta,
rate_correction):
restore('initialised')
# set the parameters
Group.set_states({'tauE': tauE_ * ms, 'tauI': tauI_ * ms})
print(f'taueE: {tauE_} - tauI {tauI_}')
G_CPU1A.set_states({'tauE': tauE_ * ms, 'tauI': tauI_ * ms})
G_CPU1B.set_states({'tauE': tauE_ * ms, 'tauI': tauI_ * ms})
G_PONTINE.set_states({'tauE': tauE_ * ms, 'tauI': tauI_ * ms})
G_MOTOR.set_states({'tauE': tauE_ * ms, 'tauI': tauI_ * ms})
S_TB1_CPU4.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
S_TN2_CPU4.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
S_TB1_CPU1A.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
S_CPU4_PONTINE.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
S_CPU4_CPU1A.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
S_PONTINE_CPU1A.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
S_TB1_CPU1B.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
S_CPU4_CPU1B.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
S_PONTINE_CPU1B.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
S_CPU1A_MOTOR.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
S_CPU1B_MOTOR.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
print(f'wE: {wE_} - wI {wI_}')
_, model_spike_monitor_CPU4 = nc.add_monitors(Group)
target_spike_monitor_CPU4 = SpikeMonitor(Target,
name='CPU4_target_spike_monitor')
_, model_spike_monitor_motor = nc.add_monitors(G_MOTOR)
target_spike_monitor_motor = SpikeMonitor(
Target, name='MOTOR_target_spike_monitor')
run(time)
gf_CPU4 = metric.compute_gamma_factor(model_spike_monitor_CPU4,
target_spike_monitor_CPU4,
time,
dt_=dt_,
delta=delta,
rate_correction=rate_correction)
gf_motor = metric.compute_gamma_factor(model_spike_monitor_motor,
target_spike_monitor_motor,
time,
dt_=dt_,
delta=delta,
rate_correction=rate_correction)
print(f'Gamma factor: {gf_CPU4} - {gf_motor}')
gf = gf_CPU4 + gf_motor
return gf
def run_simulation_TL2(tauE_, wE_, tauI_, wI_, Group, Synapses, Target, time,
dt_, delta, rate_correction):
restore('initialised')
# set the parameters
Group.set_states({'tauE': tauE_ * ms, 'tauI': tauI_ * ms})
print(f'taueE: {tauE_} - tauI {tauI_}')
Synapses.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
print(f'wE: {wE_} - wI {wI_}')
_, model_spike_monitor = nc.add_monitors(Group)
target_spike_monitor = SpikeMonitor(Target,
name='TL2_target_spike_monitor')
run(time)
gf = metric.compute_gamma_factor(model_spike_monitor,
target_spike_monitor,
time,
dt_=dt_,
delta=delta,
rate_correction=rate_correction)
print(f'Gamma factor: {gf}')
return gf
def run_simulation_NET(net, cx_log, tauE_, wE_, tauI_, wI_, Group, Target,
G_CPU1A, G_CPU1B, G_PONTINE, G_MOTOR, S_TB1_CPU1A,
S_CPU4_M_PONTINE, S_CPU4_M_CPU1A, S_PONTINE_CPU1A,
S_TB1_CPU1B, S_CPU4_M_CPU1B, S_PONTINE_CPU1B,
S_CPU1A_MOTOR, S_CPU1B_MOTOR, time, dt_, delta,
rate_correction):
net.restore('initialised')
global CPU4_memory, CPU4_memory_history, CPU4_memory_stimulus
# set the parameters
Group.set_states({'tauE': tauE_ * ms, 'tauI': tauI_ * ms})
print(f'taueE: {tauE_} - tauI {tauI_}')
G_CPU1A.set_states({'tauE': tauE_ * ms, 'tauI': tauI_ * ms})
G_CPU1B.set_states({'tauE': tauE_ * ms, 'tauI': tauI_ * ms})
G_PONTINE.set_states({'tauE': tauE_ * ms, 'tauI': tauI_ * ms})
#G_MOTOR.set_states({'tauE' : tauE_*ms, 'tauI' : tauI_*ms})
S_TB1_CPU1A.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
S_TB1_CPU1B.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
S_CPU4_M_PONTINE.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
S_CPU4_M_CPU1A.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
S_CPU4_M_CPU1B.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
S_PONTINE_CPU1A.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
S_PONTINE_CPU1B.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
S_CPU1A_MOTOR.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
S_CPU1B_MOTOR.set_states({'wE': wE_ * nS, 'wI': wI_ * nS})
print(f'wE: {wE_} - wI {wI_}')
model_spike_monitor_motor = SpikeMonitor(Group,
name='MOTOR_source_spike_monitor')
target_spike_monitor_motor = SpikeMonitor(
Target, name='MOTOR_target_spike_monitor')
net.add(model_spike_monitor_motor, target_spike_monitor_motor)
net.run(time)
if np.sum(model_spike_monitor_motor.count) == 0 or np.sum(
target_spike_monitor_motor.count) == 0:
print('model count = ', model_spike_monitor_motor.count)
print('target count = ', target_spike_monitor_motor.count)
gf_motor = 10000
else:
gf_motor = metric.compute_gamma_factor(model_spike_monitor_motor,
target_spike_monitor_motor,
time,
dt_=dt_,
delta=delta,
rate_correction=rate_correction)
motors_rate_model = cx_spiking.inputs.compute_motors(cx_log.cpu1)
rotations_rate_model = np.sign(motors_rate_model[0, :1500] -
motors_rate_model[1, :1500])
MOTOR_spikes = cx_spiking.inputs.get_spikes_rates(
target_spike_monitor_motor, 2, 1500, 20)
rotations_spike_model = np.sign(
(MOTOR_spikes[0, :1500] - MOTOR_spikes[1, :1500]))
measure = np.sum(np.abs(rotations_rate_model - rotations_spike_model))
net.remove(model_spike_monitor_motor, target_spike_monitor_motor)
print(f'Gamma factor: {gf_motor} - {measure}')
gf = gf_motor
return gf