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import os
import numpy as np
from bmtk.builder import NetworkBuilder
from bmtk.utils.io.spike_trains import PoissonSpikesGenerator
build_virtual_net = True
cell_models = [
{
'model_name': 'Scnn1a', 'ei': 'e', 'morphology': 'Scnn1a_473845048_m.swc',
'model_template': 'ctdb:Biophys1.hoc',
'dynamics_params': '472363762_fit.json',
},
{
'model_name': 'Rorb', 'ei': 'e', 'morphology': 'Rorb_325404214_m.swc',
'model_template': 'ctdb:Biophys1.hoc',
'dynamics_params': '473863510_fit.json',
},
{
'model_name': 'Nr5a1', 'ei': 'e', 'morphology': 'Nr5a1_471087815_m.swc',
'model_template': 'ctdb:Biophys1.hoc',
'dynamics_params': '473863035_fit.json',
},
{
'model_name': 'PV1', 'ei': 'i', 'morphology': 'Pvalb_470522102_m.swc',
'model_template': 'ctdb:Biophys1.hoc',
'dynamics_params': '472912177_fit.json',
},
{
'model_name': 'PV2', 'ei': 'i', 'morphology': 'Pvalb_469628681_m.swc',
'model_template': 'ctdb:Biophys1.hoc',
'dynamics_params': '473862421_fit.json',
}
]
bio_net = NetworkBuilder("bio")
radius = 100.0
dx = 2*np.pi/float(len(cell_models))
for i, model_props in enumerate(cell_models):
positions = [(radius*np.cos(i*dx), radius*np.sin(i*dx), 0.0)] # place cells in wheel around origin
bio_net.add_nodes(model_type='biophysical', model_processing='aibs_perisomatic', positions=positions,
**model_props)
bio_net.build()
bio_net.save_nodes(output_dir='network')
if build_virtual_net:
# Build a separate network of virtual cells to synapse onto the biophysical network
virt_net = NetworkBuilder('virt')
virt_net.add_nodes(N=10, model_type='virtual', ei='e') # 10 excitatory virtual cells
virt_net.add_edges(target=bio_net.nodes(), # Connect every virt cells onto every bio cell
connection_rule=lambda *_: np.random.randint(4, 12), # 4 to 12 synapses per source/target
dynamics_params='AMPA_ExcToExc.json',
model_template='Exp2Syn',
syn_weight=3.4e-4,
delay=2.0,
target_sections=['soma', 'basal', 'apical'], # target soma and all dendritic sections
distance_range=[0.0, 1.0e20])
virt_net.build()
virt_net.save(output_dir='network')
# Create spike trains to use for our virtual cells
if not os.path.exists('inputs'):
os.mkdir('inputs')
psg = PoissonSpikesGenerator(range(10), 10.0, tstop=4000.0)
psg.to_hdf5('inputs/exc_spike_trains.h5')
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