-
Notifications
You must be signed in to change notification settings - Fork 21
/
parameters_C.py
390 lines (281 loc) · 20.3 KB
/
parameters_C.py
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
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
'''
Parameters C:
Cells: Single compartment, conductance based cell models with HH like ion channels
Chem Synapses: Event based, ohmic; one rise & one decay constant
Gap junctions: Electrical connection; current linerly depends on difference in voltages
ASSESSMENT:
May be possible to use this to generate oscilliatory behaviour, but use of event based synapses normally requires
spiking in cells, so core neurons will have to have clear spikes.
'''
from neuroml import Cell
from neuroml import Morphology
from neuroml import Point3DWithDiam
from neuroml import Segment
from neuroml import BiophysicalProperties
from neuroml import IntracellularProperties
from neuroml import Resistivity
from neuroml import Species
from neuroml import MembraneProperties
from neuroml import InitMembPotential
from neuroml import SpecificCapacitance
from neuroml import ChannelDensity
from neuroml import SpikeThresh
from neuroml import FixedFactorConcentrationModel
from neuroml import ExpTwoSynapse
from neuroml import GapJunction
from neuroml import PulseGenerator
from c302.bioparameters import c302ModelPrototype
class ParameterisedModel(c302ModelPrototype):
def __init__(self):
super(ParameterisedModel, self).__init__()
self.level = "C"
self.custom_component_types_definitions = 'cell_C.xml'
self.set_default_bioparameters()
self.print_("Set default parameters for %s"%self.level)
def set_default_bioparameters(self):
self.add_bioparameter("cell_diameter", "5", "BlindGuess", "0.1")
self.add_bioparameter("muscle_length", "20", "BlindGuess", "0.1")
self.add_bioparameter("initial_memb_pot", "-45 mV", "BlindGuess", "0.1")
self.add_bioparameter("specific_capacitance", "1 uF_per_cm2", "BlindGuess", "0.1")
self.add_bioparameter("muscle_spike_thresh", "-20 mV", "BlindGuess", "0.1")
self.add_bioparameter("neuron_spike_thresh", "-20 mV", "BlindGuess", "0.1")
self.add_bioparameter("muscle_leak_cond_density", "5e-7 S_per_cm2", "BlindGuess", "0.1")
self.add_bioparameter("neuron_leak_cond_density", "0.005 mS_per_cm2", "BlindGuess", "0.1")
self.add_bioparameter("leak_erev", "-50 mV", "BlindGuess", "0.1")
self.add_bioparameter("muscle_k_slow_cond_density", "0.0006 S_per_cm2", "BlindGuess", "0.1")
self.add_bioparameter("neuron_k_slow_cond_density", "3 mS_per_cm2", "BlindGuess", "0.1")
self.add_bioparameter("k_slow_erev", "-60 mV", "BlindGuess", "0.1")
self.add_bioparameter("muscle_k_fast_cond_density", "0.0001 S_per_cm2", "BlindGuess", "0.1")
self.add_bioparameter("neuron_k_fast_cond_density", "0.0711643917483308 mS_per_cm2", "BlindGuess", "0.1")
self.add_bioparameter("k_fast_erev", "-60 mV", "BlindGuess", "0.1")
self.add_bioparameter("muscle_ca_boyle_cond_density", "0.0007 S_per_cm2", "BlindGuess", "0.1")
self.add_bioparameter("neuron_ca_boyle_cond_density", "3 mS_per_cm2", "BlindGuess", "0.1")
self.add_bioparameter("ca_boyle_erev", "40 mV", "BlindGuess", "0.1")
self.add_bioparameter("ca_conc_decay_time", "11.5943 ms", "BlindGuess", "0.1")
self.add_bioparameter("ca_conc_rho", "0.000238919 mol_per_m_per_A_per_s", "BlindGuess", "0.1")
self.add_bioparameter("neuron_to_neuron_chem_exc_syn_gbase", ".1 nS", "BlindGuess", "0.1")
self.add_bioparameter("neuron_to_muscle_chem_exc_syn_gbase", ".1 nS", "BlindGuess", "0.1")
self.add_bioparameter("chem_exc_syn_erev", "0 mV", "BlindGuess", "0.1")
self.add_bioparameter("chem_exc_syn_rise", "1 ms", "Bli ndGuess", "0.1")
self.add_bioparameter("chem_exc_syn_decay", "5 ms", "BlindGuess", "0.1")
self.add_bioparameter("neuron_to_neuron_chem_inh_syn_gbase", ".1 nS", "BlindGuess", "0.1")
self.add_bioparameter("neuron_to_muscle_chem_inh_syn_gbase", ".1 nS", "BlindGuess", "0.1")
self.add_bioparameter("chem_inh_syn_erev", "-60 mV", "BlindGuess", "0.1")
self.add_bioparameter("chem_inh_syn_rise", "2 ms", "BlindGuess", "0.1")
self.add_bioparameter("chem_inh_syn_decay", "40 ms", "BlindGuess", "0.1")
self.add_bioparameter("neuron_to_neuron_elec_syn_gbase", "0.0005 nS", "BlindGuess", "0.1")
self.add_bioparameter("neuron_to_muscle_elec_syn_gbase", "0.0005 nS", "BlindGuess", "0.1")
self.add_bioparameter("unphysiological_offset_current", "0 pA", "KnownError", "0") # Can be activated later
self.add_bioparameter("unphysiological_offset_current_del", "0 ms", "KnownError", "0")
self.add_bioparameter("unphysiological_offset_current_dur", "2000 ms", "KnownError", "0")
def create_models(self):
self.create_generic_muscle_cell()
self.create_generic_neuron_cell()
self.create_offsetcurrent_concentrationmodel()
self.create_neuron_to_neuron_syn()
self.create_neuron_to_muscle_syn()
def create_generic_muscle_cell(self):
self.generic_muscle_cell = Cell(id = "GenericMuscleCell")
morphology = Morphology()
morphology.id = "morphology_"+self.generic_muscle_cell.id
self.generic_muscle_cell.morphology = morphology
prox_point = Point3DWithDiam(x="0", y="0", z="0", diameter=self.get_bioparameter("cell_diameter").value)
dist_point = Point3DWithDiam(x="0", y=self.get_bioparameter("muscle_length").value, z="0", diameter=self.get_bioparameter("cell_diameter").value)
segment = Segment(id="0",
name="soma",
proximal = prox_point,
distal = dist_point)
morphology.segments.append(segment)
self.generic_muscle_cell.biophysical_properties = BiophysicalProperties(id="biophys_"+self.generic_muscle_cell.id)
mp = MembraneProperties()
self.generic_muscle_cell.biophysical_properties.membrane_properties = mp
mp.init_memb_potentials.append(InitMembPotential(value=self.get_bioparameter("initial_memb_pot").value))
mp.specific_capacitances.append(SpecificCapacitance(value=self.get_bioparameter("specific_capacitance").value))
mp.spike_threshes.append(SpikeThresh(value=self.get_bioparameter("muscle_spike_thresh").value))
mp.channel_densities.append(ChannelDensity(cond_density=self.get_bioparameter("muscle_leak_cond_density").value,
id="Leak_all",
ion_channel="Leak",
erev=self.get_bioparameter("leak_erev").value,
ion="non_specific"))
mp.channel_densities.append(ChannelDensity(cond_density=self.get_bioparameter("muscle_k_slow_cond_density").value,
id="k_slow_all",
ion_channel="k_slow",
erev=self.get_bioparameter("k_slow_erev").value,
ion="k"))
mp.channel_densities.append(ChannelDensity(cond_density=self.get_bioparameter("muscle_k_fast_cond_density").value,
id="k_fast_all",
ion_channel="k_fast",
erev=self.get_bioparameter("k_fast_erev").value,
ion="k"))
mp.channel_densities.append(ChannelDensity(cond_density=self.get_bioparameter("muscle_ca_boyle_cond_density").value,
id="ca_boyle_all",
ion_channel="ca_boyle",
erev=self.get_bioparameter("ca_boyle_erev").value,
ion="ca"))
ip = IntracellularProperties()
self.generic_muscle_cell.biophysical_properties.intracellular_properties = ip
# NOTE: resistivity/axial resistance not used for single compartment cell models, so value irrelevant!
ip.resistivities.append(Resistivity(value="0.1 kohm_cm"))
# NOTE: Ca reversal potential not calculated by Nernst, so initial_ext_concentration value irrelevant!
species = Species(id="ca",
ion="ca",
concentration_model="CaPool",
initial_concentration="0 mM",
initial_ext_concentration="2E-6 mol_per_cm3")
ip.species.append(species)
def create_generic_neuron_cell(self):
self.generic_neuron_cell = Cell(id = "GenericNeuronCell")
morphology = Morphology()
morphology.id = "morphology_"+self.generic_neuron_cell.id
self.generic_neuron_cell.morphology = morphology
prox_point = Point3DWithDiam(x="0", y="0", z="0", diameter=self.get_bioparameter("cell_diameter").value)
dist_point = Point3DWithDiam(x="0", y="0", z="0", diameter=self.get_bioparameter("cell_diameter").value)
segment = Segment(id="0",
name="soma",
proximal = prox_point,
distal = dist_point)
morphology.segments.append(segment)
self.generic_neuron_cell.biophysical_properties = BiophysicalProperties(id="biophys_"+self.generic_neuron_cell.id)
mp = MembraneProperties()
self.generic_neuron_cell.biophysical_properties.membrane_properties = mp
mp.init_memb_potentials.append(InitMembPotential(value=self.get_bioparameter("initial_memb_pot").value))
mp.specific_capacitances.append(SpecificCapacitance(value=self.get_bioparameter("specific_capacitance").value))
mp.spike_threshes.append(SpikeThresh(value=self.get_bioparameter("neuron_spike_thresh").value))
mp.channel_densities.append(ChannelDensity(cond_density=self.get_bioparameter("neuron_leak_cond_density").value,
id="Leak_all",
ion_channel="Leak",
erev=self.get_bioparameter("leak_erev").value,
ion="non_specific"))
mp.channel_densities.append(ChannelDensity(cond_density=self.get_bioparameter("neuron_k_slow_cond_density").value,
id="k_slow_all",
ion_channel="k_slow",
erev=self.get_bioparameter("k_slow_erev").value,
ion="k"))
mp.channel_densities.append(ChannelDensity(cond_density=self.get_bioparameter("neuron_k_fast_cond_density").value,
id="k_fast_all",
ion_channel="k_fast",
erev=self.get_bioparameter("k_fast_erev").value,
ion="k"))
mp.channel_densities.append(ChannelDensity(cond_density=self.get_bioparameter("neuron_ca_boyle_cond_density").value,
id="ca_boyle_all",
ion_channel="ca_boyle",
erev=self.get_bioparameter("ca_boyle_erev").value,
ion="ca"))
ip = IntracellularProperties()
self.generic_neuron_cell.biophysical_properties.intracellular_properties = ip
# NOTE: resistivity/axial resistance not used for single compartment cell models, so value irrelevant!
ip.resistivities.append(Resistivity(value="0.1 kohm_cm"))
# NOTE: Ca reversal potential not calculated by Nernst, so initial_ext_concentration value irrelevant!
species = Species(id="ca",
ion="ca",
concentration_model="CaPool",
initial_concentration="0 mM",
initial_ext_concentration="2E-6 mol_per_cm3")
ip.species.append(species)
def create_offsetcurrent_concentrationmodel(self):
self.offset_current = PulseGenerator(id="offset_current",
delay=self.get_bioparameter("unphysiological_offset_current_del").value,
duration=self.get_bioparameter("unphysiological_offset_current_dur").value,
amplitude=self.get_bioparameter("unphysiological_offset_current").value)
self.concentration_model = FixedFactorConcentrationModel(id="CaPool",
ion="ca",
resting_conc="0 mM",
decay_constant=self.get_bioparameter("ca_conc_decay_time").value,
rho=self.get_bioparameter("ca_conc_rho").value)
def create_neuron_to_neuron_syn(self):
self.neuron_to_neuron_exc_syn = ExpTwoSynapse(id="neuron_to_neuron_exc_syn",
gbase = self.get_bioparameter("neuron_to_neuron_chem_exc_syn_gbase").value,
erev = self.get_bioparameter("chem_exc_syn_erev").value,
tau_decay = self.get_bioparameter("chem_exc_syn_decay").value,
tau_rise = self.get_bioparameter("chem_exc_syn_rise").value)
self.neuron_to_neuron_inh_syn = ExpTwoSynapse(id="neuron_to_neuron_inh_syn",
gbase = self.get_bioparameter("neuron_to_neuron_chem_inh_syn_gbase").value,
erev = self.get_bioparameter("chem_inh_syn_erev").value,
tau_decay = self.get_bioparameter("chem_inh_syn_decay").value,
tau_rise = self.get_bioparameter("chem_inh_syn_rise").value)
self.neuron_to_neuron_elec_syn = GapJunction(id="neuron_to_neuron_elec_syn",
conductance = self.get_bioparameter("neuron_to_neuron_elec_syn_gbase").value)
def create_neuron_to_muscle_syn(self):
self.neuron_to_muscle_exc_syn = ExpTwoSynapse(id="neuron_to_muscle_exc_syn",
gbase = self.get_bioparameter("neuron_to_muscle_chem_exc_syn_gbase").value,
erev = self.get_bioparameter("chem_exc_syn_erev").value,
tau_decay = self.get_bioparameter("chem_exc_syn_decay").value,
tau_rise = self.get_bioparameter("chem_exc_syn_rise").value)
self.neuron_to_muscle_inh_syn = ExpTwoSynapse(id="neuron_to_muscle_inh_syn",
gbase = self.get_bioparameter("neuron_to_muscle_chem_inh_syn_gbase").value,
erev = self.get_bioparameter("chem_inh_syn_erev").value,
tau_decay = self.get_bioparameter("chem_inh_syn_decay").value,
tau_rise = self.get_bioparameter("chem_inh_syn_rise").value)
self.neuron_to_muscle_elec_syn = GapJunction(id="neuron_to_muscle_elec_syn",
conductance = self.get_bioparameter("neuron_to_muscle_elec_syn_gbase").value)
def get_elec_syn(self, pre_cell, post_cell, type):
self.found_specific_param = False
if type == 'neuron_to_neuron':
gbase = self.get_conn_param(pre_cell, post_cell, '%s_to_%s_elec_syn_%s', 'neuron_to_neuron_elec_syn_%s', 'gbase')
conn_id = 'neuron_to_neuron_elec_syn'
elif type == 'neuron_to_muscle':
gbase = self.get_conn_param(pre_cell, post_cell, '%s_to_%s_elec_syn_%s', 'neuron_to_muscle_elec_syn_%s', 'gbase')
conn_id = 'neuron_to_muscle_elec_syn'
if self.found_specific_param:
conn_id = '%s_to_%s_elec_syn' % (pre_cell, post_cell)
return GapJunction(id=conn_id, conductance=gbase)
def get_exc_syn(self, pre_cell, post_cell, type):
self.found_specific_param = False
specific_param_template = '%s_to_%s_chem_exc_syn_%s'
if type == 'neuron_to_neuron':
gbase = self.get_conn_param(pre_cell, post_cell, specific_param_template,
'neuron_to_neuron_chem_exc_syn_%s', 'gbase')
erev = self.get_conn_param(pre_cell, post_cell, specific_param_template,
'chem_exc_syn_%s', 'erev')
decay = self.get_conn_param(pre_cell, post_cell, specific_param_template,
'chem_exc_syn_%s', 'decay')
rise = self.get_conn_param(pre_cell, post_cell, specific_param_template,
'chem_exc_syn_%s', 'rise')
conn_id = 'neuron_to_neuron_exc_syn'
elif type == 'neuron_to_muscle':
gbase = self.get_conn_param(pre_cell, post_cell, specific_param_template,
'neuron_to_muscle_chem_exc_syn_%s', 'gbase')
erev = self.get_conn_param(pre_cell, post_cell, specific_param_template,
'chem_exc_syn_%s', 'erev')
decay = self.get_conn_param(pre_cell, post_cell, specific_param_template,
'chem_exc_syn_%s', 'decay')
rise = self.get_conn_param(pre_cell, post_cell, specific_param_template,
'chem_exc_syn_%s', 'rise')
conn_id = 'neuron_to_muscle_exc_syn'
if self.found_specific_param:
conn_id = '%s_to_%s_exc_syn' % (pre_cell, post_cell)
return ExpTwoSynapse(id=conn_id,
gbase=gbase,
erev=erev,
tau_decay=decay,
tau_rise=rise)
def get_inh_syn(self, pre_cell, post_cell, type):
self.found_specific_param = False
specific_param_template = '%s_to_%s_chem_inh_syn_%s'
if type == 'neuron_to_neuron':
gbase = self.get_conn_param(pre_cell, post_cell, specific_param_template,
'neuron_to_neuron_chem_inh_syn_%s', 'gbase')
erev = self.get_conn_param(pre_cell, post_cell, specific_param_template,
'chem_inh_syn_%s', 'erev')
decay = self.get_conn_param(pre_cell, post_cell, specific_param_template,
'chem_inh_syn_%s', 'decay')
rise = self.get_conn_param(pre_cell, post_cell, specific_param_template,
'chem_inh_syn_%s', 'rise')
conn_id = 'neuron_to_neuron_inh_syn'
elif type == 'neuron_to_muscle':
gbase = self.get_conn_param(pre_cell, post_cell, specific_param_template,
'neuron_to_muscle_chem_inh_syn_%s', 'gbase')
erev = self.get_conn_param(pre_cell, post_cell, specific_param_template,
'chem_inh_syn_%s', 'erev')
decay = self.get_conn_param(pre_cell, post_cell, specific_param_template,
'chem_inh_syn_%s', 'decay')
rise = self.get_conn_param(pre_cell, post_cell, specific_param_template,
'chem_inh_syn_%s', 'rise')
conn_id = 'neuron_to_muscle_inh_syn'
if self.found_specific_param:
conn_id = '%s_to_%s_inh_syn' % (pre_cell, post_cell)
return ExpTwoSynapse(id=conn_id,
gbase=gbase,
erev=erev,
tau_decay=decay,
tau_rise=rise)