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import numpy as np
from bmtk.builder import NetworkBuilder
from bmtk.builder.auxi.node_params import positions_columinar
def random_connections(source, target, p=0.1):
sid = source['node_id'] # Get source id
tid = target['node_id'] # Get target id
# Avoid self-connections.
if sid == tid:
return None
return np.random.binomial(1, p) # nsyns
LIF_models = {
'LIF_exc': {
'N': 80,
'ei': 'e',
'pop_name': 'LIF_exc',
'model_type': 'point_process',
'model_template': 'nest:iaf_psc_delta',
'dynamics_params': 'iaf_psc_delta_exc.json'
},
'LIF_inh': {
'N': 40,
'ei': 'i',
'pop_name': 'LIF_inh',
'model_type': 'point_process',
'model_template': 'nest:iaf_psc_delta',
'dynamics_params': 'iaf_psc_delta_inh.json'
}
}
net = NetworkBuilder('cortex')
for model in LIF_models:
params = LIF_models[model].copy()
positions = positions_columinar(N=LIF_models[model]['N'], center=[0, 10.0, 0], max_radius=50.0, height=200.0)
net.add_nodes(x=positions[:, 0], y=positions[:, 1], z=positions[:, 2],
**params)
net.add_edges(source={'ei': 'e'},
connection_rule=random_connections,
connection_params={'p': 0.1},
syn_weight=2.0,
delay=1.5,
dynamics_params='ExcToInh.json',
model_template='static_synapse')
net.add_edges(source={'ei': 'i'},
connection_rule=random_connections,
connection_params={'p': 0.1},
syn_weight=-1.5,
delay=1.5,
dynamics_params='InhToExc.json',
model_template='static_synapse')
net.build()
net.save_nodes(output_dir='network')
net.save_edges(output_dir='network')
input_network_model = {
'input_network': {
'N': 100,
'ei': 'e',
'pop_name': 'input_network',
'model_type': 'virtual'
}
}
inputNetwork = NetworkBuilder("thalamus")
inputNetwork.add_nodes(**input_network_model['input_network'])
inputNetwork.add_edges(target=net.nodes(),
connection_rule=random_connections,
connection_params={'p': 0.1},
syn_weight=4.2,
delay=1.5,
dynamics_params='ExcToExc.json',
model_template='static_synapse')
inputNetwork.build()
inputNetwork.save_nodes(output_dir='network')
inputNetwork.save_edges(output_dir='network')
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