import numpy as np
from network_params import net_dict
stim_dict = {
# Turn thalamic input on or off (True or False).
'thalamic_input': False,
# Turn DC input on or off (True or False).
'dc_input': False,
# Number of thalamic neurons.
'n_thal': 902,
# Mean amplitude of the thalamic postsynaptic potential (in mV).
'PSP_th': 0.15,
# Standard deviation of the postsynaptic potential (in relative units).
'PSP_sd': 0.1,
# Start of the thalamic input (in ms).
'th_start': 700.0,
# Duration of the thalamic input (in ms).
'th_duration': 10.0,
# Rate of the thalamic input (in Hz).
'th_rate': 120.0,
# Start of the DC generator (in ms).
'dc_start': 0.0,
# Duration of the DC generator (in ms).
'dc_dur': 1000.0,
# Connection probabilities of the thalamus to the different populations.
# Order as in 'populations' in 'network_params.py'
'conn_probs_th':
np.array([0.0, 0.0, 0.0983, 0.0619, 0.0, 0.0, 0.0512, 0.0196]),
# Mean delay of the thalamic input (in ms).
'delay_th':
np.asarray([1.5 for i in list(range(len(net_dict['populations'])))]),
# Standard deviation of the thalamic delay (in ms).
'delay_th_sd':
np.asarray([0.75 for i in list(range(len(net_dict['populations'])))]),
# Amplitude of the DC generator (in pA).
'dc_amp': np.ones(len(net_dict['populations'])) * 0.3,
}