def _addRates(self, params):
from .. import sim
for label, param in params.items():
dynamicVars = {'sim': sim, 'rxd': rxd}
# species
if 'species' not in param:
print(' Error creating Rate %s: "species" parameter was missing' %
(label))
continue
if isinstance(param['species'], basestring):
speciesStr = self._replaceRxDStr(param['species'])
exec('species = ' + speciesStr, dynamicVars)
if 'species' not in dynamicVars:
dynamicVars['species'] # fix for python 2
else:
print(
' Error creating Rate %s: "species" parameter should be a string'
% (param['species']))
continue
# rate
if 'rate' not in param:
print(' Error creating Rate %s: "rate" parameter was missing' %
(label))
continue
if isinstance(param['rate'], basestring):
rateStr = self._replaceRxDStr(param['rate'])
exec('rate = ' + rateStr, dynamicVars)
if 'rate' not in dynamicVars:
dynamicVars['rate'] # fix for python 2
# regions
if 'regions' not in param:
param['regions'] = [None]
elif not isinstance(param['regions'], list):
param['regions'] = [param['regions']]
try:
nrnRegions = [
self.rxd['regions'][region]['hObj']
for region in param['regions'] if region is not None
and self.rxd['regions'][region]['hObj'] != None
]
except:
print(' Error creating Rate %s: could not find regions %s' %
(label, param['regions']))
# membrane_flux
if 'membrane_flux' not in param:
param['membrane_flux'] = False
self.rxd['rates'][label]['hObj'] = rxd.Rate(
dynamicVars['species'],
dynamicVars['rate'],
regions=nrnRegions,
membrane_flux=param['membrane_flux'])
print(' Created Rate %s' % (label))
def create_ca_rxd(self):
cainf = 100e-6
taur = self.p_all['L5Pyr_dend_taur_cad'] # temporary
# drive_channel = -(10000) * self.ica_soma / (.2)
# [sec for sec in h.allsec() if 'soma' in sec.name()]
ca_reg = rxd.Region(h.allsec(),
nrn_region='i',
name='ca_reg',
geometry=rxd.Shell(0.9848, 1))
ca = rxd.Species(ca_reg, d=0.3, name='ca', charge=2, initial=cainf)
ca_pump = rxd.Rate(ca, (cainf - ca) / taur)
self.ca = ca
self.ca_reg = ca_reg
self.ca_pump = ca_pump
d=1.0,
charge=1,
initial=0,
)
Xcyt = x[cyt]
Xorg = x[org]
Xecs = x[ecs]
# What? - produce X in cell 1
# parameter to limit production to cell 1
cell1_param = rxd.Parameter(org,
initial=lambda node: 1.0
if node.segment.sec == cell1 else 0)
# production with a rate following Michaels Menton kinetics
createX = rxd.Rate(Xorg, cell1_param[org] * 1.0 / (10.0 + Xorg))
# leak between organelles and cytosol
cyt_org_leak = rxd.MultiCompartmentReaction(Xcyt,
Xorg,
1e4,
1e4,
membrane=cyt_org_membrane,
membrane_flux=False)
from math import pi
e = 1.60217662e-19
scale = 1e-14 / e
cyt_ecs_pump1 = rxd.MultiCompartmentReaction(
Xcyt,
Xecs,
# the species and other states
ca = rxd.Species([cyt, er], d=caDiff, name='ca', charge=2, initial=cac_init)
ip3 = rxd.Species(cyt, d=ip3Diff, initial=ip3_init)
ip3r_gate_state = rxd.State(cyt_er_membrane, initial=0.8)
h_gate = ip3r_gate_state[cyt_er_membrane]
# pumps and channels between ER and Cytosol
serca = rxd.MultiCompartmentReaction(ca[cyt]>ca[er], gserca/((kserca / (1000. * ca[cyt])) ** 2 + 1), membrane=cyt_er_membrane, custom_dynamics=True)
leak = rxd.MultiCompartmentReaction(ca[er]!=ca[cyt], gleak, gleak, membrane=cyt_er_membrane)
minf = ip3[cyt] * 1000. * ca[cyt] / (ip3[cyt] + kip3) / (1000. * ca[cyt] + kact)
k = gip3r * (minf * h_gate) ** 3
ip3r = rxd.MultiCompartmentReaction(ca[er]!=ca[cyt], k, k, membrane=cyt_er_membrane)
ip3rg = rxd.Rate(h_gate, (1. / (1 + 1000. * ca[cyt] / (0.3)) - h_gate) / ip3rtau)
cae_init = (0.0017 - cac_init * fc) / fe
ca[er].concentration = cae_init
#ip3.nodes.concentration = 2
for node in ip3.nodes:
if node.x < .2:
node.concentration = 2
h.CVode().re_init()
ki, ko, nai, nao, xi, xo = k[cyt], k[ecs], na[cyt], na[ecs], x[cyt], x[ecs]
# gates
ngate = rxd.State([cyt, mem], name='ngate', initial=0.24458654944007166)
mgate = rxd.State([cyt, mem], name='mgate', initial=0.028905534475191907)
hgate = rxd.State([cyt, mem], name='hgate', initial=0.7540796658225246)
# somaA parameter
pA = rxd.Parameter([cyt, mem],
name='paramA',
initial=lambda nd: 1 if nd.segment in somaA else 0)
#What
# gates
m_gate = rxd.Rate(mgate, (minf - mgate) / mtau)
h_gate = rxd.Rate(hgate, (hinf - hgate) / htau)
n_gate = rxd.Rate(ngate, (ninf - ngate) / ntau)
# Nernst potentials
ena = 1e3 * h.R * (h.celsius + 273.15) * log(nao / nai) / h.FARADAY
ek = 1e3 * h.R * (h.celsius + 273.15) * log(ko / ki) / h.FARADAY
gna = pA * gnabar * mgate**3 * hgate
gk = pA * gkbar * ngate**4
na_current = rxd.MultiCompartmentReaction(nai,
nao,
gna * (v - ena),
mass_action=False,
membrane=mem,
gserca / ((kserca /
(1000. * ca[cyt]))**2 + 1),
membrane=cyt_er_membrane,
custom_dynamics=True)
leak = rxd.MultiCompartmentReaction(ca[er],
ca[cyt],
gleak,
gleak,
membrane=cyt_er_membrane)
ip3r = rxd.MultiCompartmentReaction(ca[er],
ca[cyt],
k,
k,
membrane=cyt_er_membrane)
ip3rg = rxd.Rate(h_gate, (1. / (1 + rescale_v * v * ca[cyt] /
(0.3)) - h_gate) / ip3rtau)
h.finitialize()
cacyt_trace = h.Vector()
cacyt_trace.record(ca[cyt].nodes(sec)(.5)[0]._ref_concentration)
caer_trace = h.Vector()
caer_trace.record(ca[er].nodes(sec)(.5)[0]._ref_concentration)
ip3_trace = h.Vector()
ip3_trace.record(ip3.nodes(sec)(.5)[0]._ref_concentration)
times = h.Vector()
times.record(h._ref_t)
dend2.connect(dend1)
diff_constant = 1
h.cvode_active(True)
r = rxd.Region(h.allsec(), dx=0.25)
rxd.set_solve_type([dend1], dimension=3)
ca = rxd.Species(
r,
d=diff_constant,
atolscale=0.1,
initial=lambda node: 1 if (0.8 < node.x and node.segment in dend1) or
(node.x < 0.2 and node.segment in dend2) else 0,
)
bistable_reaction = rxd.Rate(ca, -ca * (1 - ca) * (0.01 - ca))
h.finitialize()
for i in range(2):
h.fadvance()
rxd.nthread(2)
for i in range(2, 4):
h.fadvance()
rxd.nthread(3)
for i in range(4, 6):
h.fadvance()
rxd.nthread(4)
for i in range(6, 8):
h.fadvance()
rxd.nthread(1)
for i in range(8, 11):
from neuron import h, crxd as rxd, gui from neuron.crxd import initializer h.CVode().active(1) rxdsec = [h.Section(), h.Section()] cyt = rxd.Region(rxdsec) er = rxd.Region(rxdsec) ca = rxd.Species([cyt, er]) caextrude = rxd.Rate(ca, 1) # test for forced initialization before model fully described initializer._do_init() ip3 = rxd.Species(cyt) h.tstop = 1000 h.run()
