model of DCN pyramidal neuron
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from __future__ import print_function
import numpy as np
import pyqtgraph as pg
from neuron import h
import cnmodel.util as util
from .protocol import Protocol
from ..util import custom_init
from cnmodel.util import sound
class PopulationTest(Protocol):
def reset(self):
super(PopulationTest, self).reset()
def run(
self, pops, cf=16e3, temp=34.0, dt=0.025, stim="sound", simulator="cochlea"
):
"""
1. Connect pop1 => pop2
2. Instantiate a single cell in pop2
3. Automatically generate presynaptic cells and synapses from pop1
4. Stimulate presynaptic cells and record postsynaptically
"""
pre_pop, post_pop = pops
pre_pop.connect(post_pop)
self.pre_pop = pre_pop
self.post_pop = post_pop
# start with one cell, selected from the user-selected population, that has
# a cf close to the center CF
post_cell_ind = post_pop.select(1, cf=cf, create=True)[0]
post_cell = post_pop.get_cell(post_cell_ind)
post_pop.resolve_inputs(depth=1)
post_sec = post_cell.soma
self.post_cell_ind = post_cell_ind
self.post_cell = post_cell
pre_cell_inds = post_pop.cell_connections(post_cell_ind)[pre_pop]
pre_cells = [pre_pop.get_cell(i) for i in pre_cell_inds]
pre_secs = [cell.soma for cell in pre_cells]
self.pre_cells = pre_cells
self.pre_cell_inds = pre_cell_inds
self.stim = sound.TonePip(
rate=100e3,
duration=0.1,
f0=cf,
dbspl=60,
ramp_duration=2.5e-3,
pip_duration=0.05,
pip_start=[0.02],
)
##
## voltage clamp the target cell
##
# clampV = 40.0
# vccontrol = h.VClamp(0.5, sec=post_cell.soma)
# vccontrol.dur[0] = 10.0
# vccontrol.amp[0] = clampV
# vccontrol.dur[1] = 100.0
# vccontrol.amp[1] = clampV
# vccontrol.dur[2] = 20.0
# vccontrol.amp[2] = clampV
#
# set up stimulation of the presynaptic cells
#
self.stim_params = []
self.istim = []
for i, pre_cell in enumerate(pre_cells):
if stim == "sound":
pre_cell.set_sound_stim(self.stim, seed=i, simulator=simulator)
amp = 0.0
else:
amp = 3.0
istim = h.iStim(0.5, sec=pre_cell.soma)
stim = {}
stim["NP"] = 10
stim["Sfreq"] = 100.0 # stimulus frequency
stim["delay"] = 10.0
stim["dur"] = 0.5
stim["amp"] = amp
stim["PT"] = 0.0
stim["dt"] = dt
(secmd, maxt, tstims) = util.make_pulse(stim)
self.stim_params.append(stim)
# istim current pulse train
i_stim_vec = h.Vector(secmd)
i_stim_vec.play(istim._ref_i, dt, 0, pre_cell.soma(0.5))
self.istim.append((istim, i_stim_vec))
self["istim"] = istim._ref_i
# record presynaptic Vm
self["v_pre%d" % i] = pre_cell.soma(0.5)._ref_v
self["t"] = h._ref_t
self["v_post"] = post_cell.soma(0.5)._ref_v
#
# Run simulation
#
h.dt = dt
self.dt = dt
h.celsius = post_cell.status["temperature"]
self.temp = h.celsius
post_cell.cell_initialize() # proper initialization.
h.dt = self.dt
custom_init(v_init=post_cell.vm0)
h.t = 0.0
h.tstop = 200.0
while h.t < h.tstop:
h.fadvance()
def show(self):
print(
"Connected %d presynaptic cells to 1 postsynaptic cell."
% len(self.pre_cell_inds)
)
print("Postsynaptic CF = %0.2f" % self.post_pop.cells[self.post_cell_ind]["cf"])
print("Presynaptic CF = %s" % self.pre_pop.cells[self.pre_cell_inds]["cf"])
self.win = pg.GraphicsWindow()
self.win.resize(1000, 1000)
cmd_plot = self.win.addPlot(title="Stim")
try:
cmd_plot.plot(self["t"], self["istim"])
except:
pass
self.win.nextRow()
pre_plot = self.win.addPlot(title=self.pre_cells[0].type + " Vm")
for i in range(len(self.pre_cells)):
pre_plot.plot(
self["t"],
self["v_pre%d" % i],
pen=pg.mkPen(
pg.intColor(i, len(self.pre_cells)),
hues=len(self.pre_cells),
width=1.0,
),
)
self.win.nextRow()
post_plot = self.win.addPlot(title="Post Cell: %s" % self.post_cell.type)
post_plot.plot(self["t"], self["v_post"])