1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
|
import os
import sys
from optparse import OptionParser
import numpy as np
import pandas as pd
import h5py
from bmtk.builder.networks import NetworkBuilder
# Create 10 identical cells where 5 of the receive inputs of synaptic type 'a' and 5 of synaptic type 'b'.
# This setup will allow comparing results between two different synaptic types
firing_rate = [10,20,50,100,200]
def build_net():
net = NetworkBuilder("slice")
net.add_nodes(N=5, pop_name='Scnn1a',
synapse_model='a',
firing_rate=firing_rate,
model_type='biophysical',
model_template='ctdb:Biophys1.hoc',
dynamics_params='472363762_fit.json',
morphology='Scnn1a-Tg3-Cre_Ai14_IVSCC_-177300.01.02.01_473845048_m.swc',
rotation_angle_zaxis=-3.646878266,
model_processing='aibs_perisomatic,extracellular')
net.add_nodes(N=5, pop_name='Scnn1a',
synapse_model='b',
firing_rate=firing_rate,
model_type='biophysical',
model_template='ctdb:Biophys1.hoc',
model_processing='aibs_perisomatic,extracellular',
dynamics_params='472363762_fit.json',
morphology='Scnn1a-Tg3-Cre_Ai14_IVSCC_-177300.01.02.01_473845048_m.swc',
rotation_angle_zaxis=-3.646878266)
net.build()
net.save_nodes(nodes_file_name='network/slice_nodes.h5', node_types_file_name='network/slice_node_types.csv')
return net
# Create 5 external cells each stimulating at different frequency 10,20,50,100,200.
# Connect them to the nodes such that each cell connects to one cell of synaptic type 'a' and one cell of type 'b'.
def build_ext5_nodes():
if not os.path.exists('network'):
os.makedirs('network')
EXT = NetworkBuilder("EXT")
# need 5 cells to stimulate at 5 different frequencies
EXT.add_nodes(N=5, pop_name='EXT', model_type='virtual', firing_rate=firing_rate)
# Save cells.csv and cell_types.csv
EXT.save_nodes(nodes_file_name='network/ext_nodes.h5', node_types_file_name='network/ext_node_types.csv')
net = NetworkBuilder('slice')
net.import_nodes(nodes_file_name='network/slice_nodes.h5', node_types_file_name='network/slice_node_types.csv')
net.add_edges(source=EXT.nodes(firing_rate=10), target=net.nodes(firing_rate=10,synapse_model='a'),
connection_rule=5,
**({'syn_weight': 0.002, 'weight_function': 'wmax', 'distance_range': [0.0, 50.0],
'target_sections': ['somatic','basal', 'apical'], 'delay': 2.0, 'dynamics_params': 'AMPA_ExcToExc.json',
'model_template': 'expsyn'}))
net.add_edges(source=EXT.nodes(firing_rate=20), target=net.nodes(firing_rate=20,synapse_model='a'),
connection_rule=5,
**({'syn_weight': 0.002, 'weight_function': 'wmax', 'distance_range': [0.0, 50.0],
'target_sections': ['somatic','basal', 'apical'], 'delay': 2.0, 'dynamics_params': 'AMPA_ExcToExc.json',
'model_template': 'expsyn'}))
net.add_edges(source=EXT.nodes(firing_rate=50), target=net.nodes(firing_rate=50,synapse_model='a'),
connection_rule=5,
**({'syn_weight': 0.002, 'weight_function': 'wmax', 'distance_range': [0.0, 50.0],
'target_sections': ['somatic','basal', 'apical'], 'delay': 2.0, 'dynamics_params': 'AMPA_ExcToExc.json',
'model_template': 'expsyn'}))
net.add_edges(source=EXT.nodes(firing_rate=100), target=net.nodes(firing_rate=100,synapse_model='a'),
connection_rule=5,
**({'syn_weight': 0.002, 'weight_function': 'wmax', 'distance_range': [0.0, 50.0],
'target_sections': ['somatic','basal', 'apical'], 'delay': 2.0, 'dynamics_params': 'AMPA_ExcToExc.json',
'model_template': 'expsyn'}))
net.add_edges(source=EXT.nodes(firing_rate=200), target=net.nodes(firing_rate=200,synapse_model='a'),
connection_rule=5,
**({'syn_weight': 0.002, 'weight_function': 'wmax', 'distance_range': [0.0, 50.0],
'target_sections': ['somatic','basal', 'apical'], 'delay': 2.0, 'dynamics_params': 'AMPA_ExcToExc.json',
'model_template': 'expsyn'}))
net.add_edges(source=EXT.nodes(firing_rate=10), target=net.nodes(firing_rate=10,synapse_model='b'),
connection_rule=5,
**({'syn_weight': 0.002, 'weight_function': 'wmax', 'distance_range': [0.0, 50.0],
'target_sections': ['somatic','basal', 'apical'], 'delay': 2.0, 'dynamics_params': 'pvalb_pvalb.json',
'model_template': 'stp2syn'}))
net.add_edges(source=EXT.nodes(firing_rate=20), target=net.nodes(firing_rate=20,synapse_model='b'),
connection_rule=5,
**({'syn_weight': 0.002, 'weight_function': 'wmax', 'distance_range': [0.0, 50.0],
'target_sections': ['somatic','basal', 'apical'], 'delay': 2.0, 'dynamics_params': 'pvalb_pvalb.json',
'model_template': 'stp2syn'}))
net.add_edges(source=EXT.nodes(firing_rate=50), target=net.nodes(firing_rate=50,synapse_model='b'),
connection_rule=5,
**({'syn_weight': 0.002, 'weight_function': 'wmax', 'distance_range': [0.0, 50.0],
'target_sections': ['somatic','basal', 'apical'], 'delay': 2.0, 'dynamics_params': 'pvalb_pvalb.json',
'model_template': 'stp2syn'}))
net.add_edges(source=EXT.nodes(firing_rate=100), target=net.nodes(firing_rate=100,synapse_model='b'),
connection_rule=5,
**({'syn_weight': 0.002, 'weight_function': 'wmax', 'distance_range': [0.0, 50.0],
'target_sections': ['somatic','basal', 'apical'], 'delay': 2.0, 'dynamics_params': 'pvalb_pvalb.json',
'model_template': 'stp2syn'}))
net.add_edges(source=EXT.nodes(firing_rate=200), target=net.nodes(firing_rate=200,synapse_model='b'),
connection_rule=5,
**({'syn_weight': 0.002, 'weight_function': 'wmax', 'distance_range': [0.0, 50.0],
'target_sections': ['somatic','basal', 'apical'], 'delay': 2.0, 'dynamics_params': 'pvalb_pvalb.json',
'model_template': 'stp2syn'}))
net.build()
net.save_edges(edges_file_name='network/ext_to_slice_edges.h5',
edge_types_file_name='network/ext_to_slice_edge_types.csv')
if __name__ == '__main__':
parser = OptionParser()
parser.add_option("--force-overwrite", dest="force_overwrite", action="store_true", default=False)
parser.add_option("--out-dir", dest="out_dir", default='./output/')
parser.add_option("--percentage", dest="percentage", type="float", default=1.0)
parser.add_option("--with-stats", dest="with_stats", action="store_true", default=False)
(options, args) = parser.parse_args()
my_network = build_net()
build_ext5_nodes()
|
