-
Notifications
You must be signed in to change notification settings - Fork 1
Expand file tree
/
Copy pathbasket.py
More file actions
228 lines (150 loc) · 6.56 KB
/
basket.py
File metadata and controls
228 lines (150 loc) · 6.56 KB
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
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
from neuron import h
import math
import numpy as np
from Synapses import Synapses
import random
class Basket:
def __init__(self,record_all = 1):
h.load_file('stdlib.hoc')
h.load_file('import3d.hoc')
cell = h.Import3d_Neurolucida3()
cell.input('morphology/01bc.ASC')
i3d = h.Import3d_GUI(cell, 0)
i3d.instantiate(self)
self.soma[0].nseg = 1 + (2*int(self.soma[0].L/40))
self.soma[0].Ra = 122
self.soma[0].cm = 1
self.soma[0].insert('Leak')
self.soma[0].gmax_Leak = 0.00004
self.soma[0].e_Leak = -55
self.soma[0].insert('Nav1_1')
self.soma[0].gbar_Nav1_1 = 0.2
self.soma[0].ena = 60
self.soma[0].insert('Cav3_2')
self.soma[0].gcabar_Cav3_2 = 0.0001
self.soma[0].insert('Cav12')
self.soma[0].gbar_Cav12 = 0.0007
self.soma[0].insert('Cav13')
self.soma[0].gbar_Cav13 = 0.000005
self.soma[0].insert('Kir2_3')
self.soma[0].gkbar_Kir2_3 = 0.0001
self.soma[0].insert('Kv3_4')
self.soma[0].gkbar_Kv3_4 = 0.097
self.soma[0].insert('Kv4_3')
self.soma[0].gkbar_Kv4_3 = 0.01
self.soma[0].insert('Kca3_1')
self.soma[0].gkbar_Kca3_1 = 0.001
self.soma[0].ek = -80
self.soma[0].insert('HCN1_PC')
self.soma[0].gbar_HCN1_PC = 0.001
self.soma[0].eh = -34
self.soma[0].insert('cdp5StCmod')
self.soma[0].TotalPump_cdp5StCmod = 2e-9
self.soma[0].push()
self.soma[0].eca = 137.5
h.pop_section()
self.whatami = "bc"
for i in self.dend:
i.nseg = 1 + 2*int(i.L/40)
i.Ra = 122
i.cm = 1
i.insert('Leak')
i.gmax_Leak = 0.00001
i.e_Leak = -55
i.insert('Cav3_2')
i.gcabar_Cav3_2 = 0.00005
i.insert('Cav12')
i.gbar_Cav12 = 0.0002
i.insert('Cav13')
i.gbar_Cav13 = 0.000005
i.insert('Kv4_3')
i.gkbar_Kv4_3 = 0.00987201764943
i.insert('Kca2_2')
i.gkbar_Kca2_2 = 0.0065
i.ek = -80
i.insert('cdp5StCmod')
i.TotalPump_cdp5StCmod = 2e-9
i.push()
i.eca = 137.5
h.pop_section()
for i, d in enumerate(self.axon):
if i == 0:
#print('ais:', i)
self.axon[i].nseg = 1 + 2*int(self.axon[i].L/40)
self.axon[i].Ra = 122
self.axon[i].cm = 1
self.axon[i].insert('Leak')
self.axon[i].gmax_Leak = 0.00001
self.axon[i].e_Leak = -55
self.axon[i].insert('Nav1_6')
self.axon[i].gbar_Nav1_6 = 0.3
self.axon[i].ena = 60
self.axon[i].insert('Kv3_4')
self.axon[i].gkbar_Kv3_4 = 0.002
self.axon[i].ek = -80
self.axon[i].insert('HCN1_PC')
self.axon[i].gbar_HCN1_PC = 0.001
self.axon[i].eh = -34
self.axon[i].insert('Kca1_1')
self.axon[i].gbar_Kca1_1 = 0.01
self.axon[i].insert('Cav2_1')
self.axon[i].pcabar_Cav2_1 = 2.2e-4
self.axon[i].insert('cdp5StCmod')
self.axon[i].TotalPump_cdp5StCmod = 2e-9
self.axon[i].push()
self.axon[i].eca = 137.5
h.pop_section()
else:
self.axon[i].nseg = 1 + 2*int(self.axon[i].L/40)
self.axon[i].Ra = 122
self.axon[i].cm = 1
self.axon[i].insert('Leak')
self.axon[i].gmax_Leak = 0.000001
self.axon[i].e_Leak = -55
self.axon[i].insert('Nav1_6')
self.axon[i].gbar_Nav1_6 = 0.001
self.axon[i].ena = 60
self.axon[i].insert('Kv3_4')
self.axon[i].gkbar_Kv3_4 = 0.001
self.axon[i].ek = -80
self.axon[i].insert('Kv1_1')
self.axon[i].gbar_Kv1_1 = 0.0005
self.axon[i].insert('HCN1_PC')
self.axon[i].gbar_HCN1_PC = 0.0001
self.axon[i].eh = -34
self.axon[i].insert('Kca1_1')
self.axon[i].gbar_Kca1_1 = 0.001
self.axon[i].insert('Cav2_1')
self.axon[i].pcabar_Cav2_1 = 0.00008
self.axon[i].insert('cdp5StCmod')
self.axon[i].TotalPump_cdp5StCmod = 2e-9
self.axon[i].push()
self.axon[i].eca = 137.5
h.pop_section()
self.voltage = h.Vector()
self.voltage.record(self.soma[0](0.5)._ref_v)
self.time = h.Vector()
self.time.record(h._ref_t)
##Synapses
def createsyn(self, npf): #temporaneo
self.pf_bc = []
self.pf_bcnmda = []
self.bc_bc = []
self.pf_bc_nmda_axon = []
self.new_dend = []
for i in self.dend:
if i.L <= 60:
self.new_dend.append(i)
n = len(self.new_dend)
self.pfrand = []
for j in range(npf):
n -= 1
i = random.randint(0, n)
self.new_dend[i], self.new_dend[n] = self.new_dend[n], self.new_dend[i]
self.pfrand.append(self.new_dend[n])
self.pf_bc.append(Synapses('pf',self,self.pfrand[j]))
self.pf_bcnmda.append(Synapses('pfnmda',self,self.pfrand[j]))
self.dendinhib = [2, 3, 4, 5, 6, 7, 8, 9, 10, 11,12,13,14,15,16,17,18,19,20,21]
for e in self.dendinhib:
self.bc_bc.append(Synapses('gaba_bc',self,self.dend[e]))
print('BC_BC', len(self.bc_bc))