def test_netstim_after_sim(self):
"""
NetStim created after simulation run has no effect, it won't go on this simulation at all.
However NetStim start is in the absolute time.
"""
# Record
rec = Record(self.soma(0.5))
# Run
sim = Simulation(init_v=-70, warmup=20)
sim.run(1)
# Netstim to synapse
stim = NetStimCell("stim").add_netstim(start=25, number=10, interval=2)
self.cell.add_synapse(source=stim, netcon_weight=0.5, mod_name="ExpSyn", delay=1,
seg=self.apic1(0.5))
sim.run(100)
r = rec.as_numpy(variable="v")
# Make assertions
self.assertEqual(4051, r.size)
self.assertEqual(-67.1917, round(r.records.max(), 4))
self.assertEqual(-70.0, round(r.records.min(), 4))
self.assertEqual(3, r.records.argmax())
# time in ms of max mV value
self.assertEqual(6, r.time[r.records.argmax()])
stim.remove_immediate_from_neuron()
sim.remove_immediate_from_neuron()
rec.remove_immediate_from_neuron()
def test_netstim_before_sim(self):
"""
NetStim run in a regular way before Simulation run, in this cale (netcon weight=1.0)
we have spike of the soma.
However NetStim start is in the absolute time.
"""
# Netstim to synapse
stim = NetStimCell("stim").add_netstim(start=25, number=10, interval=2)
self.cell.add_synapse(source=stim, netcon_weight=1.0, mod_name="ExpSyn", delay=1,
seg=self.apic1(0.5))
# Record
rec = Record(self.soma(0.5))
# Run
sim = Simulation(init_v=-70, warmup=20)
sim.run(1)
sim.run(100)
r = rec.as_numpy(variable="v")
stim.remove_immediate_from_neuron()
sim.remove_immediate_from_neuron()
rec.remove_immediate_from_neuron()
# Make assertions
self.assertEqual(4051, r.size)
self.assertEqual(34.5205, round(r.records.max(), 4))
self.assertEqual(-75.3053, round(r.records.min(), 4))
self.assertEqual(319, r.records.argmax())
# time in ms of max mV value
self.assertEqual(27.725, round(r.time[r.records.argmax()], 4))
def _prepare_epsp_protocol(self, epsp: EpspProtocol, global_time):
synapse = epsp.syn
current_time = global_time + epsp.init
netstim = NetStimCell(name="stim")
self.netstims.append(netstim)
stim = netstim.add_netstim(start=current_time, number=epsp.num, interval=epsp.int)
synapse.add_netcon(source=stim, weight=epsp.w, threshold=epsp.thr, delay=epsp.delay)
current_time += epsp.int * epsp.num
return current_time
def setUpClass(cls):
morpho_path = os.path.join(path, "..",
"commons/morphologies/swc/my.swc")
def cell_template():
cell = Cell(name="cell")
cell.load_morpho(filepath=morpho_path)
cell.insert("pas")
cell.insert("hh")
return cell
# Create NetStim
cls.netstim = NetStimCell("stim1").add_netstim(start=21,
number=100,
interval=2)
# Define connection probabilities
Dist.set_seed(13)
weight_dist = NormalDist(mean=0.01, std=0.024)
# Create population 1
cls.pop1 = Population("pop_0")
cls.pop1.add_cells(num=30, cell_function=cell_template)
connector = cls.pop1.connect(cell_connection_proba=0.6)
connector.set_source(cls.netstim)
connector.set_target([c.filter_secs("dend") for c in cls.pop1.cells])
syn_adder = connector.add_synapse("Exp2Syn")
syn_adder.add_netcon(weight=weight_dist)
connector.build()
# Create population 2
cls.pop2 = Population("pop_1")
cls.pop2.add_cells(num=40, cell_function=cell_template)
connector = cls.pop2.connect(cell_connection_proba=0.8)
connector.set_source(
[c.filter_secs("soma")(0.5) for c in cls.pop1.cells])
connector.set_target([c.filter_secs("dend") for c in cls.pop2.cells])
syn_adder = connector.add_synapse("Exp2Syn")
syn_adder.add_netcon(weight=weight_dist)
connector.build()
# Create population 3
cls.pop3 = Population("pop_2")
cls.pop3.add_cells(num=50, cell_function=cell_template)
connector = cls.pop3.connect(cell_connection_proba=0.3)
connector.set_source(
[c.filter_secs("soma")(0.5) for c in cls.pop2.cells])
connector.set_target([c.filter_secs("dend") for c in cls.pop3.cells])
syn_adder = connector.add_synapse("Exp2Syn")
syn_adder.add_netcon(weight=weight_dist)
connector.build()
from neuronpp.cells.ebner2019_cell import Ebner2019Cell
from neuronpp.core.cells.netstim_cell import NetStimCell
path = os.path.dirname(os.path.abspath(__file__))
WEIGHT = 0.0035 # µS, conductance of (single) synaptic potentials
WARMUP = 200
if __name__ == '__main__':
# define cell
cell = Ebner2019Cell(name="cell")
filepath = os.path.join(path, "..", "commons/morphologies/asc/cell1.asc")
cell.load_morpho(filepath=filepath)
# stimulation
stim = NetStimCell("stim_cell").add_netstim(start=WARMUP + 1,
number=300,
interval=1)
cell.add_random_synapses_with_spine(source=stim,
secs=cell.secs,
mod_name="Syn4P",
netcon_weight=WEIGHT,
delay=1,
head_nseg=10,
neck_nseg=10,
number=10,
**cell.params_4p_syn)
# add mechanisms
cell.make_default_mechanisms()
cell.make_apical_mechanisms(sections='dend head neck')
from neuronpp.utils.record import Record
from neuronpp.utils.iclamp import IClamp
from neuronpp.utils.utils import make_shape_plot
from neuronpp.core.cells.netstim_cell import NetStimCell
# Create cell
cell = Cell(name="cell")
path = os.path.dirname(os.path.abspath(__file__))
morpho_path = os.path.join(path, "..", "commons/morphologies/asc/cell2.asc")
cell.load_morpho(filepath=morpho_path)
cell.insert("pas")
cell.insert("hh")
# Create stim and synapses
ns_cell = NetStimCell("stim_cell")
ns = ns_cell.make_netstim(start=30, number=5, interval=10)
syns = cell.add_synapses_with_spine(source=ns,
secs=cell.filter_secs("apic"),
mod_name="ExpSyn",
netcon_weight=0.01,
delay=1,
number=100)
soma = cell.filter_secs("soma")
# Create IClamp
ic = IClamp(segment=soma(0.5))
ic.stim(delay=100, dur=10, amp=0.1)
# prepare plots and spike detector
path = os.path.dirname(os.path.abspath(__file__))
WEIGHT = 0.0035 # µS, conductance of (single) synaptic potentials
WARMUP = 200
if __name__ == '__main__':
# define cell
cell = Ebner2019AChDACell(name="cell")
filepath = os.path.join(path, "..",
"commons/morphologies/swc/my.swc")
cell.load_morpho(filepath=filepath)
# make NetStim stims
ns_cell = NetStimCell("netstim_cell")
stim1 = ns_cell.make_netstim(start=WARMUP + 1, number=1)
# make VecStim
vs_cell = VecStimCell("vecstim_cell")
stim2 = vs_cell.make_vecstim(np.array([WARMUP+50]))
# make synapses with spines
syns_4p, heads = cell.add_synapses_with_spine(source=None, secs=cell.secs, number=100, netcon_weight=WEIGHT,
mod_name="Syn4PAChDa", delay=1, **cell.params_4p_syn)
for s, h in zip(syns_4p, heads):
syn_ach = cell.add_synapse(source=stim1, mod_name="SynACh", seg=h(1.0), netcon_weight=0.1, delay=1)
syn_da = cell.add_synapse(source=stim2, mod_name="SynDa", seg=h(1.0), netcon_weight=0.1, delay=1)
cell.set_synaptic_pointers(s, syn_ach, syn_da)
# add mechanisms
def make_protocol(self,
protocol: str,
start,
isi=1,
iti=1,
epsp_synapse: [Synapse, ComplexSynapse] = None,
i_clamp_section: Sec = None,
train_number=1,
copy_netconn_params=True):
"""
Create an experimental protocol of EPSPs and APs.
Each element of the experiment (EPSP or AP) is separated by isi (in ms).
:param protocol:
string eg. 3xEPSP[int=10,w=2.5,thr=5,del=2] 3xAP[int=10,dur=3,amp=1.6]
Params ofr EPSP and AP:
int - interval between in ms
Params for EPSP only:
w - weight for netconn (default is 1.0) -> used only when copy_netconn_params=False
del - delay for netconn (default is 1.0) -> used only when copy_netconn_params=False
thr - threshold for netconn (default is 10) -> used only when copy_netconn_params=False
Params for AP only:
dur - duration of AP in ms
amp - amplitude in nA
:param epsp_synapse:
synapse to stimulate. Default is None if you don't want to stimulate synapse
:param i_clamp_section:
section to input IClamp. Default is None if you don't want to stimulate any section by electrode (eg. making AP)
It is assumed that IClamp stimulate i_clamp_section(0.5) segment.
:param start:
start time of the first stimuli in ms, it is absolute time, so bear in mind warmup time.
:param isi:
Inter Stimulus Interval, eg. 3xEPSP,2xAP -isi- 3xEPSP,2xAP
:param iti:
Inter Train Interval eg. 3xEPSP,2xAP -isi- 3xEPSP,2xAP -iti- 3xEPSP,2xAP-isi-3xEPSP,2xAP
:param train_number:
number of trains. Default is 1
:param copy_netconn_params:
If copy_netconn_params=True it will copy NetConn params from the last NetConn added to the synapse.
:return:
tuple(NetStim, IClamp).
If epsp_synapse is None NetStim will be None
If i_clamp_section is None IClamp will be None
"""
#if start < h.t:
# raise ValueError("Experimental protocol 'start' param must > h.t (time of the simulation), but your "
# "start=%s and h.t=%s. Bear in mind that 'start' param is the absolute time" % (start, h.t))
protocol = protocol.lower()
protocols = protocol.split(" ")
netstim = None
if epsp_synapse:
netstim = NetStimCell(name="stim")
self.netstims.append(netstim)
iclamp = None
if i_clamp_section:
iclamp = IClamp(i_clamp_section(0.5))
self.iclamps.append(iclamp)
event_time = start
for train_no in range(train_number):
for p in protocols:
event_time = self._prepare_protocol(p, netstim, iclamp,
event_time, epsp_synapse,
copy_netconn_params)
event_time += isi
event_time += iti
return netstim, iclamp
from neuronpp.core.distributions import Dist, NormalTruncatedDist, NormalTruncatedSegDist
path = os.path.dirname(os.path.abspath(__file__))
if __name__ == '__main__':
def cell_function():
cell = Cell(name="cell")
morpho_path = os.path.join(path, "..", "commons/morphologies/asc/cell1.asc")
cell.load_morpho(filepath=morpho_path)
cell.insert("pas")
cell.insert("hh")
cell.make_spike_detector(seg=cell.filter_secs("soma")(0.5))
return cell
# Create NetStim
netstim = NetStimCell("stim").add_netstim(start=21, number=100, interval=2)
# Define connection probabilities
Dist.set_seed(13)
connection_proba = NormalConnectionProba(mean=0.8, std=0.1, threshold=0.6)
weight_dist = NormalTruncatedDist(mean=0.1, std=0.2)
# Create population 1
pop1 = Population("pop_1")
pop1.add_cells(num=4, cell_function=cell_function)
connector = pop1.connect(cell_connection_proba=connection_proba)
connector.set_source(netstim)
connector.set_target([d(0.5) for c in pop1.cells for d in c.filter_secs("dend")])
syn_adder = connector.add_synapse("Exp2Syn")
syn_adder.add_netcon(weight=weight_dist)
freq = 50 # freqs.append(10, 20, 40, 50)
interval = 1000 / freq
delta_t = 10 # LTP
if __name__ == '__main__':
cell = Ebner2019Cell(name="cell")
filepath = os.path.join(path, "..", "commons/morphologies/asc/cell1.asc")
cell.load_morpho(filepath=filepath)
cell.make_default_mechanisms()
soma = cell.filter_secs("soma")
# Netstim to synapse
stim = NetStimCell("stim").add_netstim(start=WARMUP,
number=REPS,
interval=interval)
syn = cell.add_synapse(source=stim,
netcon_weight=WEIGHT,
mod_name="Syn4P",
delay=1,
seg=cell.filter_secs('apic[1]')(0.5))
# IClamp to soma
iclamp = IClamp(segment=cell.filter_secs("soma")(0.5))
for i in range(REPS):
start_t = WARMUP + delta_t + i * interval
iclamp.stim(delay=start_t, dur=DUR, amp=AMP)
# Record
rec = Record([s(0.5) for s in cell.filter_secs("apic[1],apic[50]")])
from neuronpp.core.cells.netstim_cell import NetStimCell
path = os.path.dirname(os.path.abspath(__file__))
model_path1 = os.path.join(path, "..", "commons/mods/ebner2019")
model_path2 = os.path.join(path, "..", "commons/morphologies/swc/my.swc")
# Prepare cell
cell = Cell(name="cell", compile_paths=model_path1)
cell.load_morpho(filepath=model_path2)
cell.add_sec("dend[1]", diam=10, l=10, nseg=10)
cell.connect_secs(source="dend[1]", target="soma")
cell.insert("pas")
cell.insert("hh")
# Two examples of synapses with NetStim:
stim_cell = NetStimCell("stim_cell")
stim = stim_cell.make_netstim(start=250, number=30, interval=1)
soma = cell.filter_secs("soma")
# 1) Hoc-style synapse
pp = cell.add_point_process(mod_name="ExpSyn", seg=soma(0.5))
cell.add_netcon(source=stim, point_process=pp, netcon_weight=0.01, delay=1)
# 2) Recommended synapse
syn1 = cell.add_synapse(source=stim,
seg=soma(0.5),
netcon_weight=0.01,
mod_name="Syn4P",
delay=1)
# 3) Event synapse
