def synapse_vclamp_test(label, syntype, cell, w, v_holding, v_init, indexes,
section):
vv = h.Vector()
vv.append(0, 0, 0, 0, 0, 0)
se = h.SEClamp(cell.sections[section](0.5))
h('objref synlst')
h.synlst = h.List()
for i in indexes:
h.synlst.append(cell.syns.o(i))
if syntype == syn_type_excitatory:
v = cell.syntest_exc(h.synlst, se, w, v_holding, v_init)
else:
v = cell.syntest_inh(h.synlst, se, w, v_holding, v_init)
vv = vv.add(v)
amp = vv.x[0]
t_10_90 = vv.x[1]
t_20_80 = vv.x[2]
t_all = vv.x[3]
t_50 = vv.x[4]
t_decay = vv.x[5]
print("%s synapse: \n" % label)
print(" Amplitude %f\n" % amp)
print(" 10-90 Rise Time %f\n" % t_10_90)
print(" 20-80 Rise Time %f\n" % t_20_80)
print(" Decay Time Constant %f\n" % t_decay)
def __init__(self, mechname):
#set variables in case of exception so that __del__ still works.
self.nc = None
self.stim = None
self.syn = None
self.vc = None
self.s = None
self.mechname = mechname
constructor = h.__getattribute__(mechname)
self.soma = h.Section(name='soma')
s = self.soma
s.L = 10.
s.diam = 10. / h.PI
s.insert('pas')
seg = s(0.5)
seg.e_pas = -65.0
seg.g_pas = 0.0001
self.syn = constructor(seg)
self.stim = h.NetStim()
self.stim.number = 2
self.stim.interval = 5
self.stim.start = 1
self.nc = h.NetCon(self.stim, self.syn)
self.nc.delay = 1
self.nc.weight[0] = .001
if use_voltage_clamp:
self.vc = h.SEClamp(seg)
self.vc.amp1 = -65.0
self.vc.dur1 = 1e9
def run(self, vcrange, cell, dt=0.025):
"""
Run voltage-clamp I/V curve.
Parameters:
vmin : float
Minimum voltage step value
vmax :
Maximum voltage step value
vstep :
Voltage difference between steps
cell :
The Cell instance to test.
"""
self.reset()
self.cell = cell
try:
(vmin, vmax, vstep) = vcrange # unpack the tuple...
except:
raise TypeError(
"run_iv argument 1 must be a tuple (imin, imax, istep)")
vstim = h.SEClamp(0.5, cell.soma) # set up a single-electrode clamp
vstim.dur1 = 50.0
vstim.amp1 = -60
vstim.dur2 = 500.0
vstim.amp2 = -60.0
vstim.dur3 = 400
vstim.amp3 = -60.0
vstim.rs = 0.01
cell.soma.cm = 0.001 # reduce capacitative transients (cap compensation)
self.durs = [vstim.dur1, vstim.dur2, vstim.dur3]
self.amps = [vstim.amp1, vstim.amp2, vstim.amp3]
self.voltage_cmd = []
tend = 900.0
iv_nstepv = int(np.ceil((vmax - vmin) / vstep))
iv_minv = vmin
iv_maxv = vmax
vstep = (iv_maxv - iv_minv) / iv_nstepv
for i in range(iv_nstepv):
self.voltage_cmd.append(float(i * vstep) + iv_minv)
nreps = iv_nstepv
h.dt = dt
self.dt = h.dt
for i in range(nreps):
# Connect recording vectors
self['v_soma'] = cell.soma(0.5)._ref_v
self['i_inj'] = vstim._ref_i
self['time'] = h._ref_t
vstim.amp2 = self.voltage_cmd[i]
custom_init(v_init=-60.)
h.tstop = tend
self.cell.check_all_mechs()
while h.t < h.tstop:
h.fadvance()
self.voltage_traces.append(self['v_soma'])
self.current_traces.append(self['i_inj'])
self.time_values = np.array(self['time'])
def addVClamp(self, loc, e_c, dur):
loc = MorphLoc(loc, self)
# add the voltage clamp
vclamp = h.SEClamp(self.sections[loc['node']](loc['x']))
vclamp.rs = 0.01
vclamp.dur1 = dur
vclamp.amp1 = e_c
# store the vclamp
self.vclamps.append(vclamp)
def __init__(self):
self.soma = h.Section(name="soma", cell=self)
self.soma.diam = 10.0
self.soma.L = 10.0
self.soma.insert("na_ion") # can use nai as transfer source
# can use POINT_PROCESS range variable as targets
self.ic = h.IClamp(self.soma(0.5))
self.vc = h.SEClamp(self.soma(0.5))
self.vc.rs = 1e9 # no voltage clamp current
self.hgap = [None for _ in range(2)] # filled by mkgaps
def placeVoltageClamp(self, sec, D):
"""Put a voltage clamp at a specific location"""
print('....adding a voltage clamp electrode')
self.settings.v_init = self.settings.Hold1
self.vClamp = h.SEClamp(sec(D))
self.vClamp.dur1 = self.settings.ChangeClamp
self.vClamp.dur2 = self.settings.tstop - self.settings.ChangeClamp
self.vClamp.amp1 = self.settings.Hold1
self.vClamp.amp2 = self.settings.Hold2
self.recordings['iClamp'] = h.Vector().record(self.vClamp._ref_i)
def get_synapse_iv(self,
synpase_type='ampa',
p_conc=0,
ampa_gmax=5000,
nmda_gmax=5000,
t_rel=40.0,
vc_range=np.arange(-90.0, 50.0, 5.0),
nmda_mech='h.NMDA_Mg_T',
vshift=None):
'''
Method for generating large IV curves... Not sure if best, use synapse __ref__i
'''
self.clamp = h.SEClamp(0.5, sec=self.root)
self.clamp.dur1 = 10
self.clamp.dur2 = 60
self.clamp.dur3 = 10
self.clamp.amp1 = -70
self.clamp.amp2 = -70
self.clamp.amp3 = -70
self.clamp.rs = 0.0001
pre = h.Section()
pre.diam = 1.0
pre.L = 1.0
pre.insert('rel')
pre.dur_rel = 0.5
pre.amp_rel = 3.0
pre.del_rel = t_rel
if synpase_type.lower() == 'ampa':
print('running simulation of AMPAR IV with', p_conc,
'µM polyamines')
cpampa = h.cpampa12st(0.5, sec=self.root)
cpampa.pconc = p_conc
cpampa.gmax = ampa_gmax
h.setpointer(pre(0.5).rel._ref_T, 'C', cpampa)
if synpase_type.lower() == 'nmda':
print('running simulation of NMDA IV')
nmda = eval(nmda_mech + '(0.5,sec=self.root)')
print('inserted: ' + nmda_mech + '(0.5,sec=self.root)')
#nmda = h.NMDA_Mg_T(0.5,sec=self.root)
if vshift:
print('vshift: ' + str(vshift))
nmda.vshift = vshift
nmda.gmax = nmda_gmax
h.setpointer(pre(0.5).rel._ref_T, 'C', nmda)
v, i, t = self.run_vclamp(vc_range, tstop=80)
i_list, v_list = self.calc_iv_relationship(v, i, t)
return i_list, v_list,
def add_vclamp(self):
clamp = h.SEClamp(0.5, sec=self.soma)
clamp.dur1 = 10
clamp.dur2 = 10
clamp.dur3 = 10
clamp.amp1 = -70
clamp.amp2 = -70
clamp.amp3 = -70
clamp.rs = 0.0001
self.clamp = clamp
def setup_dynamic_clamp(sec, pos, vm, t, dt=h.dt):
"""Create a dynamic clamp on section `sec` at position `pos` and play
the voltage `vm` over time `t`. The sample points are selected at
`dt` interval.
"""
clamp = h.SEClamp(sec(pos))
clamp.rs = 1e-3
clamp.dur1 = 1e9
vsample = np.interp(np.arange(t[0], t[-1], dt), t, vm)
vplay = h.Vector(vsample)
vplay.play(clamp._ref_amp1, dt)
return clamp, vplay
def attach_current(self, cell):
self._stim = h.SEClamp(cell.hobj.soma[0](0.5))
self._stim.dur1 = self._seclamp_durs[0]
self._stim.dur2 = self._seclamp_durs[1]
self._stim.dur3 = self._seclamp_durs[2]
self._stim.amp1 = self._seclamp_amps[0]
self._stim.amp2 = self._seclamp_amps[1]
self._stim.amp3 = self._seclamp_amps[2]
if self._seclamp_rs != None:
self._stim.rs = self._seclamp_rs
return self._stim
def vclamp_seg(seg, durs, amps, rs=None):
clamp = SEClamp(amps, durs, rs=rs)
clamp._stim = h.SEClamp(seg)
clamp._stim.dur1 = durs[0]
clamp._stim.dur2 = durs[1]
clamp._stim.dur3 = durs[2]
clamp._stim.amp1 = amps[0]
clamp._stim.amp2 = amps[1]
clamp._stim.amp3 = amps[2]
if rs != None:
clamp._stim.rs = rs
return clamp
def inject_SEClamp(parameters, injectsite):
"""Injects SEClamp for `NEURON <https://neuron.yale.edu/neuron/>`_
**Keyword Arguments:**
+----------------+--------------------------------------------------------------+
| Keys | Value type |
+================+==============================================================+
| ``parameters`` | - list such that each element is a dictionary [ {}, {}, {} ] |
| | - Eg: [ {"amp1": 0.0, "dur1": 50.0, "rs": 1E-6}, |
| | {"amp2": 10.0, "dur2": 100.0}, |
| | {"amp3": 20.0, "dur3": 150.0} ] |
| |**NOTE** There is no "amp>3" (therefore no "dur>3") |
| | - To add the electrode/pipette resistance do it just once |
| | with key "rs". This should be the same for all because its |
| | the same setup, just the amplitudes differ. |
| | - Since "Clamp is on at time 0, off at time dur1+dur2+dur3" |
| |if you don't want to start the simulation with it just set |
| |"amp1": 0.0 |
+----------------+--------------------------------------------------------------+
| ``injectsite`` | ``neuron`` ``section``, for e.g., ``cell.soma`` |
+----------------+--------------------------------------------------------------+
**Returned values:** list of currents where each element is a ``hoc`` object ``h.SEClamp``.
**NOTE:**
- The ``h.SEClamp`` function is available in NEURON as `SEClamp <https://neuron.yale.edu/neuron/static/new_doc/modelspec/programmatic/mechanisms/mech.html#SEClamp>`_ by default.
- By default the electrode resistance (Re but SEClamp attribute is ``rs``) is made very small ``1E-6``. This is because the input resistance (Rin) for the voltmeter (i.e, the measuring circuit) must be very large (i.e, infinite resistance) so that the voltage drop across the voltmeter (given by the voltage divider equation, the resistance is Rin/(Rin+Re)) is as close as possible to the membrane voltage it is supposed to be clamping. By making the electrode resistance very small it is the same as infinite Rin.
"""
# NOTE: Do not insert several instances of this model at the same location
# to make level changes. That is equivalent to independent clamps and they
# will have incompatible internal state values.
no_of_voltages = len(parameters)
clampingvoltages = h.SEClamp(0.5, sec=injectsite)
clampingvoltages.rs = 1E-6
for i in range(no_of_voltages):
for key, value in parameters[i].items():
if key in clampingvoltages.__dict__:
setattr(clampingvoltages, key, value)
else:
raise AttributeError(key +
" is not an attribute in h.SEClamp.")
return clampingvoltages
def get_iv(self,
synpase_type='ampa',
p_conc=0,
ampa_gmax=5000,
nmda_gmax=5000,
t_rel=40.0):
self.clamp = h.SEClamp(0.5, sec=self.root)
self.clamp.dur1 = 10
self.clamp.dur2 = 60
self.clamp.dur3 = 10
self.clamp.amp1 = -70
self.clamp.amp2 = -70
self.clamp.amp3 = -70
self.clamp.rs = 0.0001
pre = h.Section()
pre.diam = 1.0
pre.L = 1.0
pre.insert('rel')
pre.dur_rel = 0.5
pre.amp_rel = 3.0
pre.del_rel = t_rel
if synpase_type.lower() == 'ampa':
print('running simulation of AMPAR IV with', p_conc,
'µM polyamines')
cpampa = h.cpampa12st(0.5, sec=self.root)
cpampa.pconc = p_conc
cpampa.gmax = ampa_gmax
h.setpointer(pre(0.5).rel._ref_T, 'C', cpampa)
if synpase_type.lower() == 'nmda':
print('running simulation of NMDA IV')
nmda = h.NMDA_Mg_T(0.5, sec=self.root)
nmda.gmax = nmda_gmax
h.setpointer(pre(0.5).rel._ref_T, 'C', nmda)
vc_range = np.arange(-90.0, 50.0, 10.0)
v, i, t = self.run_vclamp(vc_range, tstop=80)
i_list, v_list = self.calc_iv_relationship(v, i, t)
return i_list, v_list
def voltage_clamp(self, voltages, series_resistance=1e-3):
"""
Clamps the voltage of a segment
Parameters
----------
voltage : neo.AnalogSignal (voltage)
The voltages to clamp the segment to
series_resistance : float (??)
The series resistance of the voltage clamp
"""
seclamp = h.SEClamp(0.5, sec=self._sec)
seclamp.rs = series_resistance
seclamp.dur1 = 1e12
seclamp_amps = h.Vector(pq.Quantity(voltages, 'mV'))
seclamp_times = h.Vector(voltages.times.rescale(pq.ms))
seclamp_amps.play(seclamp._ref_amp, seclamp_times)
self._inputs['seclamp'] = seclamp
self._input_auxs.extend((seclamp_amps, seclamp_times))
def get_nmda_ampa_ratio(self,
p_conc,
ampa_gmax,
nmda_gmax,
t_rel=40.0,
vc_range=[-60, 60]):
self.clamp = h.SEClamp(0.5, sec=self.root)
self.clamp.dur1 = 10
self.clamp.dur2 = 150
self.clamp.dur3 = 10
self.clamp.amp1 = -70
self.clamp.amp2 = -70
self.clamp.amp3 = -70
self.clamp.rs = 0.0001
pre = h.Section()
pre.diam = 1.0
pre.L = 1.0
pre.insert('rel')
pre.dur_rel = 0.5
pre.amp_rel = 3.0
pre.del_rel = t_rel
syn_list = []
locs = np.linspace(0, 1, 35)
for l in locs:
cpampa = h.cpampa12st(l, sec=self.root)
cpampa.pconc = p_conc
cpampa.gmax = ampa_gmax
h.setpointer(pre(0.5).rel._ref_T, 'C', cpampa)
nmda = h.NMDA_Mg_T(l, sec=self.root)
nmda.gmax = nmda_gmax
h.setpointer(pre(0.5).rel._ref_T, 'C', nmda)
syn_list.append((nmda, cpampa))
v, i, t = self.run_vclamp(vc_range, tstop=170)
return v, i, t
def run_sim(h, section_name, v_peak, tau_raise, tau_fall, onset=100):
tstop = 500
h.dt = dt = 0.1
h.load_file("stdrun.hoc")
soma, sec = fetch_soma_sec(section_name)
v_rest = -75.711 # find_vrest(h, section_name)
h.init()
h.cvode.re_init()
s_v, a_v = fetch_soma_apic_pots()
vv = voltage_clamp(tstop, dt, v_rest, v_peak, tau_raise, tau_fall, onset)
vc = h.SEClamp(sec(0.5))
vc.rs = 0.001
vc.dur1 = tstop
vamp = h.Vector(vv)
vamp.play(vc._ref_amp1, h.dt)
t_vec, soma_vm, sec_vm = record(soma, sec)
h.execute('tstop = ' + str(tstop))
h.run()
diff_v = np.array(a_v) - np.array(s_v)
return t_vec, soma_vm, sec_vm, diff_v, vv
def addVClamp(self, loc, e_c, dur):
"""
Adds a voltage clamp at a given location
Parameters
----------
loc: dict, tuple or :class:`neat.MorphLoc`
The location of the conductance.
e_c: float
The clamping voltage (mV)
dur: float, ms
The duration of the voltage clamp
"""
loc = MorphLoc(loc, self)
# add the voltage clamp
vclamp = h.SEClamp(self.sections[loc['node']](loc['x']))
vclamp.rs = 0.01
vclamp.dur1 = dur
vclamp.amp1 = e_c
# store the vclamp
self.vclamps.append(vclamp)
def addVoltageClamp(self, weightMap, dur):
# WeightMap is (treeNum, Sec, Seg):weight
# treeNum specifies apical or basal, 0 is apical, 1 is basal
# inds is an array of tuples of (sectionNum, segNum)
# Window for stimulus inputs
tstart = self.stimStart
tstop = self.stimStop
for tuple in weightMap:
print tuple
loc = tuple[0]
synapseWeight = tuple[1]
treeNum = loc[0]
tree = self.trees[treeNum]
section = tree[loc[1]]
segLoc = self.getSegLoc(loc)
clamp = h.SEClamp(segLoc, sec=section)
clamp.dur1 = dur
clamp.amp1 = synapseWeight
clamp.rs = 0.00000001
self.SEClamps[loc] = clamp
def vclamp(v, t, sec, celsius):
# create SEClamp
v_clamp = h.Vector()
v_clamp.from_python(v)
t_clamp = h.Vector()
t_clamp.from_python(np.concatenate(
(np.array([0]),
t))) # shifted because membrane potential lags behind vclamp
clamp = h.SEClamp(0.5, sec=sec)
clamp.rs = 1e-15 # series resistance should be as small as possible
clamp.dur1 = 1e9
v_clamp.play(clamp._ref_amp1, t_clamp)
# simulate
h.celsius = celsius
dt = t[1] - t[0]
h.tstop = t[-1]
h.steps_per_ms = 1 / dt
h.dt = dt
h.v_init = v[0]
h.run()
def run_democlamp(cell, dend, vsteps=[-60,-70,-60], tsteps=[10,50,100]):
"""
Does some stuff.
"""
f1 = pylab.figure(1)
gs = GS.GridSpec(2, 2,
width_ratios=[1, 1],
height_ratios=[1, 1])
# note numbering for insets goes from 1 (upper right) to 4 (lower right)
# counterclockwise
pA = f1.add_subplot(gs[0])
pAi = INSETS.inset_axes(pA, width="66%", height="40%", loc=2)
pB = f1.add_subplot(gs[1])
pBi = INSETS.inset_axes(pB, width="66%", height="40%", loc=4)
pC = f1.add_subplot(gs[2])
pCi = INSETS.inset_axes(pC, width="66%", height="40%", loc=2)
pD = f1.add_subplot(gs[3])
pDi = INSETS.inset_axes(pD, width="66%", height="40%", loc=1)
#h.topology()
Ld = 0.5
Ld2 = 1.0
VClamp = h.SEClamp(0.5, cell)
VClamp.dur1 = tsteps[0]
VClamp.amp1 = vsteps[0]
VClamp.dur2 = tsteps[1]
VClamp.amp2 = vsteps[1]
VClamp.dur3 = tsteps[2]
VClamp.amp3 = vsteps[2]
Rs0 = 10.
VClamp.rs = Rs0
compensation = [0., 70., 95.]
cms = [cell.cm*(100.-c)/100. for c in compensation]
vrec = h.iStim(Ld, sec=dend[0])
vrec.delay = 0
vrec.dur = 1e9 # these actually do not matter...
vrec.iMax = 0.0
vrec2 = h.iStim(Ld2, sec=dend[0])
vrec2.delay = 0
vrec2.dur = 1e9 # these actually do not matter...
vrec2.iMax = 0.0
stim = {}
stim['NP'] = 1
stim['Sfreq'] = 20 # stimulus frequency
stim['delay'] = tsteps[0]
stim['dur'] = tsteps[1]
stim['amp'] = vsteps[1]
stim['PT'] = 0.0
stim['hold'] = vsteps[0]
# (secmd, maxt, tstims) = make_pulse(stim)
tend = 79.5
linetype = ['-', '-', '-']
linethick = [0.5, 0.75, 1.25]
linecolor = [[0.66, 0.66, 0.66], [0.4, 0.4, 0.3], 'k']
n = 0
vcmds = [-70, -20]
vplots = [(pA, pAi, pC, pCi), (pB, pBi, pD, pDi)]
for m, VX in enumerate(vcmds):
stim['amp'] = VX
pl = vplots[m]
print m, VX
(secmd, maxt, tstims) = make_pulse(stim)
for n, rsc in enumerate(compensation):
vec={}
for var in ['VCmd', 'i_inj', 'time', 'Vsoma', 'Vdend',
'Vdend2', 'VCmdR']:
vec[var] = h.Vector()
VClamp.rs = Rs0*(100.-rsc)/100.
cell.cm = cms[n]
# print VClamp.rs, cell.cm, VClamp.rs*cell.cm
vec['VCmd'] = h.Vector(secmd)
vec['Vsoma'].record(cell(0.5)._ref_v, sec=cell)
vec['Vdend'].record(dend[0](Ld)._ref_v, sec=dend[0])
vec['time'].record(h._ref_t)
vec['i_inj'].record(VClamp._ref_i, sec=cell)
vec['VCmdR'].record(VClamp._ref_vc, sec=cell)
VClamp.amp2 = VX
# vec['VCmd'].play(VClamp.amp2, h.dt, 0, sec=cell)
h.tstop = tend
h.init()
h.finitialize(-60)
h.run()
vc = np.asarray(vec['Vsoma'])
tc = np.asarray(vec['time'])
# now plot the data, raw and as insets
for k in [0, 1]:
pl[k].plot(vec['time'], vec['i_inj'], color=linecolor[n], linestyle = linetype[n], linewidth=linethick[n])
yl = pl[k].get_ylim()
if k == 0:
pass
#pl[k].set_ylim([1.5*yl[0], -1.5*yl[1]])
else:
pass
for k in [2,3]:
pl[k].plot(vec['time'], vec['Vsoma'], color=linecolor[n], linestyle = linetype[n], linewidth=linethick[n])
pl[k].plot(vec['time'], vec['VCmdR'], color=linecolor[n], linestyle = '--', linewidth=1, dashes=(1,1))
pl[k].plot(vec['time'], vec['Vdend'], color=linecolor[n], linestyle = linetype[n], linewidth=linethick[n], dashes=(3,3))
if VX < vsteps[0]:
pl[k].set_ylim([-72, -40])
else:
pl[k].set_ylim([-62,VX+30])
ptx = 10.8
pBi.set_xlim([9.8, ptx])
pAi.set_xlim([9.8, ptx])
PH.setX(pAi, pCi)
PH.setX(pBi, pDi)
pD.set_ylim([-65, 10])
# PH.setY(pC, pCi) # match Y limits
PH.cleanAxes([pA, pAi, pB, pBi, pC, pCi, pD, pDi])
PH.formatTicks([pA, pB, pC, pD], axis='x', fmt='%d')
PH.formatTicks([pC, pD], axis='y', fmt='%d')
PH.calbar(pAi, [ptx-1, 0, 0.2, 2.])
PH.calbar(pCi, [ptx-1, -50., 0.2, 10])
PH.calbar(pBi, [ptx-1, 0, 0.2, 10])
PH.calbar(pDi, [ptx-1, -50., 0.2, 20])
pylab.draw()
pylab.show()
def get_nmda_iv_2017(self,
nmda_gmax,
vc_range=[-60, 60],
tstop=220,
t_rel=40.0):
self.clamp = h.SEClamp(0.5, sec=self.root)
self.clamp.dur1 = 10
self.clamp.dur2 = 200
self.clamp.dur3 = 10
self.clamp.amp1 = -70
self.clamp.amp2 = -70
self.clamp.amp3 = -70
self.clamp.rs = 0.0001
pre = h.Section()
pre.diam = 1.0
pre.L = 1.0
pre.insert('rel')
pre.dur_rel = 0.5
pre.amp_rel = 3.0
pre.del_rel = t_rel
nmda = h.NMDA_Mg_T(0.5, sec=self.root)
# overwriting briefly... testing difference before changing to ampa properly 2017_05_26
# also for comapring presyantuic glutamte
#print('overwritten for glu!')
#nmda = h.cpampa12st(0.5,sec=self.root)
#nmda.pconc = 0
nmda.gmax = nmda_gmax
h.setpointer(pre(0.5).rel._ref_T, 'C', nmda)
h.load_file('stdrun.hoc')
rec = {}
for label in 't', 'v', 'i_nmda', 'g_nmda':
rec[label] = h.Vector()
rec['t'].record(h._ref_t)
rec['i_nmda'].record(nmda._ref_i)
rec['g_nmda'].record(nmda._ref_g)
rec['v'].record(self.root(0.5)._ref_v)
v_list, i_list, t_list, g_list = [], [], [], []
h.tstop = tstop
h.celsius = 32.0
for vc in vc_range:
h.init()
#h.finitialize(v_init)
self.clamp.amp2 = vc
h.run()
i = rec['i_nmda'].to_python()
g = rec['g_nmda'].to_python()
v = rec['v'].to_python()
t = rec['t'].to_python()
v_list.append(v)
i_list.append(i)
t_list.append(t)
g_list.append(g)
v = np.array(v_list).transpose()
i = np.array(i_list).transpose() * 1000 # for pA
t = np.array(t_list).transpose()
g = np.array(g_list).transpose()
return t, i, v, g # in pA
def get_ampa_iv_2017(self,
ampa_gmax,
p_conc=0,
vc_range=[-60, 60],
tstop=220,
t_rel=40.0):
self.clamp = h.SEClamp(0.5, sec=self.root)
self.clamp.dur1 = 10
self.clamp.dur2 = 200
self.clamp.dur3 = 10
self.clamp.amp1 = -70
self.clamp.amp2 = -70
self.clamp.amp3 = -70
self.clamp.rs = 0.0001
pre = h.Section()
pre.diam = 1.0
pre.L = 1.0
pre.insert('rel')
pre.dur_rel = 0.5
pre.amp_rel = 3.0
pre.del_rel = t_rel
print('amp 3')
cpampa = h.cpampa12st(0.5, sec=self.root)
cpampa.pconc = p_conc
cpampa.gmax = ampa_gmax
h.setpointer(pre(0.5).rel._ref_T, 'C', cpampa)
h.load_file('stdrun.hoc')
rec = {}
for label in 't', 'v', 'i_ampa', 'g_ampa':
rec[label] = h.Vector()
rec['t'].record(h._ref_t)
rec['i_ampa'].record(cpampa._ref_i)
rec['g_ampa'].record(cpampa._ref_g)
rec['v'].record(self.root(0.5)._ref_v)
v_list, i_list, t_list, g_list = [], [], [], []
h.tstop = tstop
h.celsius = 32.0
for vc in vc_range:
h.init()
#h.finitialize(v_init)
self.clamp.amp2 = vc
h.run()
i = rec['i_ampa'].to_python()
g = rec['g_ampa'].to_python()
v = rec['v'].to_python()
t = rec['t'].to_python()
v_list.append(v)
i_list.append(i)
t_list.append(t)
g_list.append(g)
v = np.array(v_list).transpose()
i = np.array(i_list).transpose() * 1000 # for pA
t = np.array(t_list).transpose()
g = np.array(g_list).transpose(
) * 1 * 10**6 # this is defined as microSiemens in the mod file: 1000000, so for pico 1e-6
return t, i, v, g # in pA
# icc1.L = 5000 # icc1.diam=1 # icc1.connect(icc(1)) # icc1.cm=25 v_e = h.Vector() v_e1 = h.Vector() v_e2 = h.Vector() v_e3 = h.Vector() v_e4 = h.Vector() v_e.record(icc(0.6)._ref_v) v_e1.record(icc(0.7)._ref_v) v_e2.record(icc(.8)._ref_v) v_e3.record(icc(.9)._ref_v) v_e4.record(icc(1)._ref_v) vclamp = h.SEClamp(icc(0.5)) vclamp.dur1 = tstop vclamp.amp1 = -50.0 vclamp.rs = .00001 h.v_init = -80 run_and_record(icc, *variables) t = np.array(t.to_python()) ina = h.area(0.5) * 10 * np.array(ina.to_python()) ik = h.area(0.5) * 10 * np.array(ik.to_python()) ik_ERG = h.area(0.5) * 10 * np.array(ik_ERG.to_python()) ik_Kb = h.area(0.5) * 10 * np.array(ik_Kb.to_python()) ik_kv11 = h.area(0.5) * 10 * np.array(ik_kv11.to_python()) ica_vddr = h.area(0.5) * 10 * np.array(ica_vddr.to_python()) ik_bk = h.area(0.5) * 10 * np.array(ik_bk.to_python())
def measure_psc(gid,
pop_name,
presyn_name,
env,
v_init,
v_holding,
load_weights=False,
cell_dict={}):
biophys_cell = init_biophys_cell(env,
pop_name,
gid,
register_cell=False,
load_weights=load_weights,
cell_dict=cell_dict)
hoc_cell = biophys_cell.hoc_cell
h.dt = env.dt
stimdur = 1000.0
tstop = stimdur
tstart = 0.
soma = list(hoc_cell.soma)[0]
se = h.SEClamp(soma(0.5))
se.rs = 10
se.dur = stimdur
se.amp1 = v_holding
h('objref nil, tlog, ilog, Vlog')
h.tlog = h.Vector()
h.tlog.record(h._ref_t)
h.Vlog = h.Vector()
h.Vlog.record(soma(0.5)._ref_v)
h.ilog = h.Vector()
ilog.record(se._ref_i)
h.tstop = tstop
neuron_utils.simulate(v_init, 0., stimdur)
vec_i = h.ilog.to_python()
vec_v = h.Vlog.to_python()
vec_t = h.tlog.to_python()
idx = np.where(vec_t > tstart)[0]
vec_i = vec_i[idx]
vec_v = vec_v[idx]
vec_t = vec_t[idx]
t_holding = vec_t[0]
i_holding = vec_i[0]
i_peak = np.max(np.abs(vec_i[1:]))
peak_index = np.where(np.abs(vec_i) == i_peak)[0][0]
t_peak = vec_t[peak_index]
logger.info("measure_psc: t_peak = %f i_holding = %f i_peak = %f" %
(t_peak, i_holding, i_peak))
amp_i = abs(i_peak - i_holding) * 1000
logger.info("measure_psc: amp_i = %f" % amp_i)
return amp_i
def runsim_vclamp(
tstop=15.0,
dt=0.01,
temp=21.0,
dur1=5.0,
dur2=5.0,
dur3=5.0,
amp1=-70.0,
amp2=0.0,
amp3=-70.0,
tea=False,
ttx=False,
):
Soma = h.Section()
Soma.L = 15
Soma.nseg = 7
Soma.diam = 15
area = np.pi * 15.0 * 15.0 #in µm²
Soma.insert("hh")
Soma.ena = 50
if ttx:
Soma.gnabar_hh = 1e-9
else:
Soma.gnabar_hh = 0.12
if tea:
Soma.gkbar_hh = 1e-9
else:
Soma.gkbar_hh = 0.023
# GENERAL SETTINGS
h.dt = dt # simulation (or "sampling") rate
h.celsius = temp # simulation global temperature
SEC = h.SEClamp(Soma(0.5))
SEC.rs = 0.1
SEC.dur1 = dur1
SEC.dur2 = dur2
SEC.dur3 = dur3
SEC.amp1 = amp1
SEC.amp2 = amp2
SEC.amp3 = amp3
Vm = h.Vector()
Vm.record(Soma(0.5)._ref_v)
INa = h.Vector()
IK = h.Vector()
IL = h.Vector()
INa.record(Soma(0.5)._ref_ina)
IK.record(Soma(0.5)._ref_ik)
IL.record(Soma(0.5)._ref_il_hh)
Ie = h.Vector()
Ie.record(SEC._ref_i)
hhm = h.Vector()
hhm.record(Soma(0.5)._ref_m_hh)
hhn = h.Vector()
hhn.record(Soma(0.5)._ref_n_hh)
hhh = h.Vector()
hhh.record(Soma(0.5)._ref_h_hh)
Im = h.Vector()
Im.record(SEC._ref_i)
nrngo(tstop, -70.0)
# PACK AND EXPORT DATA
t = np.linspace(0, tstop - dt, int(np.round(tstop / dt)))
Vm = np.array(Vm)
Im = np.array(INa) + np.array(IK) + np.array(IL)
#mA/cm2 be multiplied by (area in µm² * 0.01) to get nA
Im = Im * (area * 0.01)
Ie = np.array(Ie)
hhm = np.array(hhm)
hhn = np.array(hhn)
hhh = np.array(hhh)
return (t, Im, Ie, Vm, hhm, hhn, hhh)
dend.insert('pas')
dend.g_pas = 0.001 # Passive conductance in S/cm2
dend.e_pas = -65 # Leak reversal potential mV
# Change the maximum sodium conductance of the middle segment of the soma to 0.13
soma(0.5).hh.gnabar = 0.13
# Change the equilibrium potential of the passive mechanism in the middle segment of the dend to -65
dend(0.5).pas.e = -65
for sec in h.allsec():
for seg in sec:
for mech in seg:
print sec.name(), seg.x, mech.name()
vstim = h.SEClamp(dend(1.0))
vstim.dur1 = 2
vstim.amp1 = -30
# add synapse (custom channel)
syn = h.AlphaSynapse(dend(1.0))
syn.e = 0 # equilibrium potential in mV
syn.onset = 20 # turn on after this time in ms
syn.gmax = 0.1 # set conductance in uS
syn.tau = 0.1 # set time constant
# add current clamp stimulus
stim = h.IClamp(dend(1.0))
stim.amp = 0.3 # input current in nA
stim.delay = 40 # turn on after this time in ms
stim.dur = 1 # duration of 1 ms
from neuron import h
import matplotlib.pyplot as plt
import numpy as np
h.load_file('init_models_with_ca/init_model2.hoc')
h.delete_section(sec=h.axon)
h.delete_section(sec=h.iseg)
h.delete_section(sec=h.hillock)
# Set up stimulus
stim = h.SEClamp(h.apical(1))
stim.amp1 = -70
stim.amp2 = -40
stim.amp3 = -70
stim.dur1 = 500
stim.dur3 = 100
# Set up recording vectors
apical_end_v_vec = h.Vector()
apical_end_v_vec.record(h.apical(1)._ref_v)
tuft_v_vec = h.Vector()
tuft_v_vec.record(h.tuft(.5)._ref_v)
t_vec = h.Vector()
t_vec.record(h._ref_t)
# Simulation parameters
dt = 0.025
h.tstop = 1000 - dt
h.tuft.gbar_sca = 0
def test_is_point_process(self):
section = h.Section()
clamp = h.SEClamp(section(0.5))
assert simulator.is_point_process(clamp)
section.insert('hh')
assert not simulator.is_point_process(section(0.5).hh)
soma = h.Section()
soma.insert('hh')
soma.insert('pas')
#soma.insert('hcno')
soma.L = 20
soma.diam = 20
soma(0.5).pas.g = 2e-5
#soma(0.5).hcno.gbar = 15e-4
ic = h.IClamp(soma(0.5))
ic.dur = 1e9
ic.delay = 0
icRec = h.Vector()
icRec.record(soma(0.5)._ref_v)
vc = h.SEClamp(soma(0.5))
vc.dur1 = 1e9
vc.rs = 5 # Rs, in megohms
#vc.amp1 = 0
#vc.dur2 = 1e9
vcrs = vc.rs
vcRec = h.Vector()
vcRec.record(vc._ref_i)
# add an alpha synapse, reversal -7 mV
# note that synaptic current will appear in the SEClamp or IClamp
syn = h.AlphaSynapse(soma(0.5))
t = 0
def simulate(tau_facil,
tau_rec,
stim_freq,
celltype,
tau_1=0.3,
tau_2=0.6,
u0=0.078,
sampling_interval=0.5,
v_clamp=-70.42,
sec='proxd'):
"""Simulates a frequency stimulation of the tmgexp2syn meachnism onto a
neuron and measure the conductance at the soma.
Parameters
----------
tau_facil : numeric
facilitation time constant of the tmgexp2syn mechanism
tau_rec : numeric
recovery time constant of the tmgexp2syn mechanism
stim_freq : numeric
stimulation frequency in Hz
celltype : ouropy.GenNeuron
A class that inherits from ouropy.GenNeuron
tau_1 : numeric
Synaptic rise time
tau_2 : numeric
Synaptic decay time
u0 : float
The u0 parameters as specified in tmgexp2syn
sampling_interval : numeric
The sampling interval in ms
v_clamp : numeric
Holding potential of the
Returns
-------
peaks_norm : ndarray
Peak conductances normalized to first peak
garr_norm : ndarray
Conductance array normalized to first peak
"""
# Resolve simulation hyperparameters
left_pad, right_pad = 50, 100 # in ms
simdur = left_pad + right_pad + 10 * (1000 / stim_freq)
# Create cell
mycell = celltype()
# Create synapse
syn = h.tmgexp2syn(mycell.get_segs_by_name(sec)[0](0.5))
syn.tau_1 = tau_1
syn.tau_2 = tau_2
syn.tau_facil = tau_facil
syn.tau_rec = tau_rec
syn.u0 = u0
syn.e = 0
# Create stimulation
stim_period_ms = 1000 / stim_freq
stim = h.NetStim()
stim.interval = stim_period_ms
stim.start = left_pad
stim.number = 10
nc = h.NetCon(stim, syn)
nc.weight[0] = 0.001
# Create voltage clamp
c = h.SEClamp(mycell.soma(0.5))
c.dur1 = simdur
c.amp1 = v_clamp
c.rs = 0.1
# Create recording vector
ivec = h.Vector()
ivec.record(c._ref_i)
# Start simulation
sample_period_ms = sampling_interval
h.cvode.active(0)
h.finitialize(-70.42)
h.t = -2000
h.secondorder = 0
h.dt = 10
while h.t < -100:
h.fadvance()
h.secondorder = 0
h.t = 0
h.dt = sample_period_ms
h.steps_per_ms = 1.0 / h.dt
h.frecord_init() # Necessary after changing t to restart the vectors
while h.t < simdur:
h.fadvance()
# Get Peaks from output
iarr = np.array(ivec)
garr = (iarr - iarr[0:50].mean()) / v_clamp
stim_dtp = int(np.around(stim.interval / sampling_interval))
pad_dtp = int(left_pad / sampling_interval)
t_stim = np.arange(pad_dtp, stim_dtp * 11 + pad_dtp, stim_dtp)
#dtp_stim = np.array(t_stim / sampling_interval, dtype=np.int)
dtp_stim = np.array(t_stim, dtype=np.int)
gvec_split = np.array(np.split(garr, dtp_stim)[1:-1])
peaks = gvec_split.max(axis=1)
peaks_norm = peaks / peaks[0]
garr_norm = garr / peaks[0]
return peaks_norm, garr_norm
