def chirpForMulti(invar):
sec_num, loc, filename = invar
from getCells import HayCell
pt_cell = HayCell()
seg = pt_cell.apic[sec_num](loc)
from neuron import h
for sec in h.allsec():
try:
sec.uninsert('SK_E2')
except:
pass
from chirpUtils import applyChirp, getChirp
amp = 0.0025
f0, f1, t0, Fs, delay = 0.5, 20, 20, 1000, 5 # for looking at bimodal leading phase response in Hay cell
I, t = getChirp(f0, f1, t0, amp, Fs, delay)
print('running chirp on ' + str(seg))
applyChirp(I,
t,
seg,
pt_cell.soma[0](0.5),
t0,
delay,
Fs,
f1,
out_file_name=filename)
def chirpForMulti(invar):
model, sec_num, loc, filename = invar
if model == 'kole':
from getCells import KoleCell
cell, _ = KoleCell()
seg = cell.apic[sec_num](loc)
soma_seg = cell.soma(0.5)
if model == 'kolenoim':
from getCells import KoleCell
cell, _ = KoleCell()
from neuron import h
for sec in h.allsec():
try:
sec.uninsert('Km')
except:
pass
seg = cell.apic[sec_num](loc)
soma_seg = cell.soma(0.5)
elif model == 'neymotinkole':
from getCells import NeymotinKoleCell
cell = NeymotinKoleCell()
seg = cell.apic[sec_num](loc)
soma_seg = cell.soma(0.5)
elif model == 'neymotinharnett':
from getCells import NeymotinHarnettCell
cell = NeymotinHarnettCell()
seg = cell.apic[sec_num](loc)
soma_seg = cell.soma(0.5)
elif model == 'neymotinmigliore':
from getCells import NeymotinMiglioreCell
cell = NeymotinMiglioreCell()
seg = cell.apic[sec_num](loc)
soma_seg = cell.soma(0.5)
elif model == 'hay':
from getCells import HayCell
cell, _ = HayCell()
seg = cell.apic[sec_num](loc)
soma_seg = cell.soma[0](0.5)
elif model == 'ackerantic':
from getCells import AckerAnticCell
cell = AckerAnticCell()
seg = cell.apical[sec_num](loc)
soma_seg = cell.soma[0](0.5)
elif model == 'haymig':
from getCells import HayCellMig
cell, _ = HayCellMig()
seg = cell.apic[sec_num](loc)
soma_seg = cell.soma[0](0.5)
from chirpUtils import applyChirp, getChirp
amp = 0.025
f0, f1, t0, Fs, delay = 0.5, 10, 10, 1000, 5 # for looking at bimodal leading phase response in Hay cell
I, t = getChirp(f0, f1, t0, amp, Fs, delay)
print('running chirp on ' + str(seg))
applyChirp(I, t, seg, soma_seg, t0, delay, Fs, f1, out_file_name=filename)
print(str(sec) + ' ' + str(loc) + ': done')
def chirpForMulti(invar):
model, sec_num, loc, filename = invar
cell = HayCellSWC('../suter_shepherd/' + model)
seg = cell.apic[sec_num](loc)
soma_seg = cell.soma[0](0.5)
from chirpUtils import applyChirp, getChirp
amp = 0.025
f0, f1, t0, Fs, delay = 0.5, 10, 10, 1000, 5 # for looking at bimodal leading phase response in Hay cell
I, t = getChirp(f0, f1, t0, amp, Fs, delay)
print('running chirp on ' + str(seg))
applyChirp(I, t, seg, soma_seg, t0, delay, Fs, f1, out_file_name=filename)
print(str(seg) + ': done')
def chirpForMulti(invar):
sec_num, loc, filename = invar
from getCells import M1Cell
s = M1Cell()
seg = s.net.cells[0].secs[sec_num]['hObj'](loc)
soma_seg = s.net.cells[0].secs['soma']['hObj'](0.5)
from chirpUtils import applyChirp, getChirp
amp = 0.025
f0, f1, t0, Fs, delay = 0.5, 10, 10, 1000, 5 # for looking at bimodal leading phase response in Hay cell
I, t = getChirp(f0, f1, t0, amp, Fs, delay)
print('running chirp on ' + str(seg))
applyChirp(I, t, seg, soma_seg, t0, delay, Fs, f1, out_file_name=filename)
print(str(seg) + ': done')
# f0, f1, t0, Fs, delay = 0.5, 100, 100, 1000, 5 # for looking at bimodal leading phase response in Hay cell
I, t = getChirp(f0, f1, t0, amp, Fs, delay)
# define output variables
#main loop
for sec in secList:
nseg = sec.nseg
if nseg == 1:
loc = 0.5
applyChirp(
I,
t,
sec(loc),
soma_seg,
t0,
delay,
Fs,
f1,
out_file_name=
'/home/craig_kelley_downstate_edu/L5PYR_Resonance/allen_phase/' +
str(sec(loc)))
else:
for loc in np.linspace(1 / (nseg + 1), nseg / (nseg + 1), nseg):
applyChirp(
I,
t,
sec(loc),
soma_seg,
t0,
delay,
Fs,
## record voltages
from neuron import h, gui
soma_v = h.Vector().record(soma_seg._ref_v)
dend_v = h.Vector().record(seg._ref_v)
time = h.Vector().record(h._ref_t)
## parameters of the chirp stimulus
from chirpUtils import applyChirp, getChirp
amp = 0.025 # amplitude of chirp stim
f0, f1, t0, Fs, delay = 0.5, 20, 20, 1000, 5 # initial and final frequencies, duration, sampling freq, delay
I, t = getChirp(f0, f1, t0, amp, Fs, delay) # defines current clamp
## run simulation
print('Running chirp on ' + str(seg))
out = applyChirp(I, t, seg, soma_seg, t0, delay, Fs, f1)
## plotting
from matplotlib import pyplot as plt
### traces
trace_fig = plt.figure(figsize=(8,10))
plt.subplot(3,1,1)
plt.plot(t,I)
plt.title('Chirp Sitmulation', fontsize=14)
plt.ylabel('Current (mA)', fontsize=14)
plt.xticks(fontsize=12)
plt.yticks(fontsize=12)
plt.xlim(4000,16000)
plt.subplot(3,1,2)
plt.plot(time, dend_v)
plt.title(r'Local V$_{memb}$', fontsize=14)
ZinPeakPhaseFreq = []
ZinLeadPhaseBW = []
ZinLeadPhaseMinFreq = []
ZinSynchFreq = []
ZinLeadPhaseBool = []
ZcPeakPhaseFreq = []
ZcLeadPhaseBW = []
ZcLeadPhaseMinFreq = []
ZcSynchFreq = []
ZcLeadPhaseBool = []
#main loop
nseg = sec.nseg
if nseg == 1:
loc = 0.5
out = applyChirp(I, t, sec(loc), soma_seg, t0, delay, Fs, f1)
ZinResAmp.append(out['ZinResAmp'])
ZinResFreq.append(out['ZinResFreq'])
ZcResAmp.append(out['ZcResAmp'])
ZcResFreq.append(out['ZcResFreq'])
dist.append(out['dist'])
QfactorIn.append(out['QfactorIn'])
QfactorTrans.append(out['QfactorTrans'])
fVarIn.append(out['fVarIn'])
fVarTrans.append(out['fVarTrans'])
freqs = out['Freq'][np.argwhere(out['ZinPhase'] > 0)]
if len(freqs) > 0:
ZinPeakPhaseFreq.append(out['Freq'][np.argwhere(
out['ZinPhase'] == np.max(out['ZinPhase']))])
ZinLeadPhaseBW.append(freqs[-1] - freqs[0])
def chirpForMulti(invar):
sec_num, loc, filename = invar
from getCells import AllenCell
pt_cell = AllenCell('./497232419')
seg = pt_cell.apical[sec_num](loc)
from neuron import h
for sec in h.allsec():
try:
sec.uninsert('SK')
except:
pass
from chirpUtils import applyChirp, getChirp
amp = 0.0025
f0, f1, t0, Fs, delay = 0.5, 20, 20, 1000, 5
I, t = getChirp(f0, f1, t0, amp, Fs, delay)
print('running chirp on ' + str(seg))
# applyChirp(I, t, seg, pt_cell.soma[0](0.5), t0, delay, Fs, f1, out_file_name=filename)
out = applyChirp(I, t, seg, pt_cell.soma[0](0.5), t0, delay, Fs, f1)
ZinResAmp = []
ZinResFreq = []
ZcResAmp = []
ZcResFreq = []
dist = []
QfactorIn = []
QfactorTrans = []
fVarIn = []
fVarTrans = []
ZinPeakPhaseFreq = []
ZinLeadPhaseBW = []
ZinLeadPhaseMinFreq = []
ZinSynchFreq = []
ZinLeadPhaseBool = []
ZcPeakPhaseFreq = []
ZcLeadPhaseBW = []
ZcLeadPhaseMinFreq = []
ZcSynchFreq = []
ZcLeadPhaseBool = []
ZinResAmp.append(out['ZinResAmp'])
ZinResFreq.append(out['ZinResFreq'])
ZcResAmp.append(out['ZcResAmp'])
ZcResFreq.append(out['ZcResFreq'])
dist.append(out['dist'])
QfactorIn.append(out['QfactorIn'])
QfactorTrans.append(out['QfactorTrans'])
fVarIn.append(out['fVarIn'])
fVarTrans.append(out['fVarTrans'])
freqs = out['Freq'][np.argwhere(out['ZinPhase'] > 0)]
if len(freqs) > 0:
ZinPeakPhaseFreq.append(out['Freq'][np.argwhere(
out['ZinPhase'] == np.max(out['ZinPhase']))])
ZinLeadPhaseBW.append(freqs[-1] - freqs[0])
ZinLeadPhaseMinFreq.append(freqs[0])
ZinSynchFreq.append(freqs[-1])
ZinLeadPhaseBool.append(out['ZinPhase'] > 0)
else:
ZinPeakPhaseFreq.append(nan)
ZinLeadPhaseBW.append(0)
ZinLeadPhaseMinFreq.append(nan)
ZinSynchFreq.append(nan)
ZinLeadPhaseBool.append(out['ZinPhase'] > 0)
freqs = out['Freq'][np.argwhere(out['ZcPhase'] > 0)]
if len(freqs) > 0:
ZcPeakPhaseFreq.append(
out['Freq'][np.argwhere(out['ZcPhase'] == np.max(out['ZcPhase']))])
ZcLeadPhaseBW.append(freqs[-1] - freqs[0])
ZcLeadPhaseMinFreq.append(freqs[0])
ZcSynchFreq.append(freqs[-1])
ZcLeadPhaseBool.append(out['ZcPhase'])
else:
ZcPeakPhaseFreq.append(nan)
ZcLeadPhaseBW.append(0)
ZcLeadPhaseMinFreq.append(nan)
ZcSynchFreq.append(nan)
ZcLeadPhaseBool.append(out['ZcPhase'])
print(str(sec) + ' ' + str(loc) + ': done')
output = {
'ZinResAmp': ZinResAmp,
'ZinResFreq': ZinResFreq,
'ZcResAmp': ZcResAmp,
'ZcResFreq': ZcResFreq,
'dist': dist,
'QfactorIn': QfactorIn,
'QfactorTrans': QfactorTrans,
'fVarIn': fVarIn,
'fVarTrans': fVarTrans,
'ZinPeakPhaseFreq': ZinPeakPhaseFreq,
'ZinLeadPhaseBW': ZinLeadPhaseBW,
'ZinLeadPhaseMinFreq': ZinLeadPhaseMinFreq,
'ZinSynchFreq': ZinSynchFreq,
'ZinLeadPhaseBool': ZinLeadPhaseBool,
'ZcPeakPhaseFreq': ZcPeakPhaseFreq,
'ZcLeadPhaseBW': ZcLeadPhaseBW,
'ZcLeadPhaseMinFreq': ZcLeadPhaseMinFreq,
'ZcSynchFreq': ZcSynchFreq,
'ZcLeadPhaseBool': ZcLeadPhaseBool
}
savemat(filename + '.mat', output)
from getCells import AckerAnticCell
import numpy as np
import sys
from scipy.io import savemat
from math import nan
pt_cell = AckerAnticCell()
sec_list = [pt_cell.apical[15], pt_cell.apical[34], pt_cell.basal[8]]
soma_seg = pt_cell.soma[0](0.5)
from chirpUtils import applyChirp
from chirpUtils import getChirp
amp = 0.0025
amp = amp * 10 # as per srdjan's suggestion
f0, f1, t0, Fs, delay = 0.5, 50, 50, 1000, 5 # 12 # original for all cells
I, t = getChirp(f0, f1, t0, amp, Fs, delay)
loc = 0.5
for sec in sec_list:
out = applyChirp(I,
t,
sec(loc),
soma_seg,
t0,
delay,
Fs,
f1,
out_file_name='/u/craig/L5PYR_Resonance/amplitude_test/' +
str(sec))
import multiprocessing
from math import nan
from scipy.io import savemat
from getCells import M1Cell
s = M1Cell()
sec_num = 'apic_22'
loc = 0.5
Ks = float(sys.argv[-1])
Kh = float(sys.argv[-2])
from neuron import h
for sec in h.allsec():
for seg in sec.allseg():
try:
seg.hd.Ks = Ks
seg.hd.Kh = Kh
except:
pass
seg = s.net.cells[0].secs[sec_num]['hObj'](loc)
soma_seg = s.net.cells[0].secs['soma']['hObj'](0.5)
from chirpUtils import applyChirp, getChirp
amp = 0.025
f0, f1, t0, Fs, delay = 0.5, 20, 20, 1000, 5 # for looking at bimodal leading phase response in Hay cell
I, t = getChirp(f0, f1, t0, amp, Fs, delay)
print('running chirp on ' + str(seg))
filename = 'M1_PTcell/vary_ih_ilk/' + sec_num + '_kh_' + sys.argv[
-2] + '_ks_' + sys.argv[-1]
applyChirp(I, t, seg, soma_seg, t0, delay, Fs, f1, out_file_name=filename)
def chirpForMulti(invar):
sec_num, loc, morph_file, filename = invar
from getCells import HayCellSWC
pt_cell = HayCellSWC(morphology_file=morph_file)
seg = pt_cell.apic[sec_num](loc)
from chirpUtils import applyChirp, getChirp
amp = 0.0025
f0, f1, t0, Fs, delay = 0.5, 30, 30, 1000, 5 # for looking at bimodal leading phase response in Hay cell
I, t = getChirp(f0, f1, t0, amp, Fs, delay)
print('running chirp on ' + str(seg))
out = applyChirp(I, t, seg, pt_cell.soma[0](0.5), t0, delay, Fs, f1)
ZinResAmp = []
ZinResFreq = []
ZcResAmp = []
ZcResFreq = []
dist = []
QfactorIn = []
QfactorTrans = []
fVarIn = []
fVarTrans = []
ZinPeakPhaseFreq = []
ZinLeadPhaseBW = []
ZinLeadPhaseMinFreq = []
ZinSynchFreq = []
ZinLeadPhaseBool = []
ZcPeakPhaseFreq = []
ZcLeadPhaseBW = []
ZcLeadPhaseMinFreq = []
ZcSynchFreq = []
ZcLeadPhaseBool = []
ZinResAmp.append(out['ZinResAmp'])
ZinResFreq.append(out['ZinResFreq'])
ZcResAmp.append(out['ZcResAmp'])
ZcResFreq.append(out['ZcResFreq'])
dist.append(out['dist'])
QfactorIn.append(out['QfactorIn'])
QfactorTrans.append(out['QfactorTrans'])
fVarIn.append(out['fVarIn'])
fVarTrans.append(out['fVarTrans'])
freqs = out['Freq'][np.argwhere(out['ZinPhase'] > 0)]
if len(freqs) > 0:
ZinSynchFreq.append(freqs[-1])
else:
ZinSynchFreq.append(nan)
freqs = out['Freq'][np.argwhere(out['ZcPhase'] > 0)]
if len(freqs) > 0:
freqs = freqs[freqs < 10]
ZcSynchFreq.append(freqs[-1])
else:
ZcSynchFreq.append(nan)
print(str(sec) + ' ' + str(loc) + ': done')
output = {
'ZinResAmp': ZinResAmp,
'ZinResFreq': ZinResFreq,
'ZcResAmp': ZcResAmp,
'ZcResFreq': ZcResFreq,
'dist': dist,
'QfactorIn': QfactorIn,
'QfactorTrans': QfactorTrans,
'fVarIn': fVarIn,
'fVarTrans': fVarTrans,
'ZinSynchFreq': ZinSynchFreq,
'ZcSynchFreq': ZcSynchFreq
}
savemat(filename + '.mat', output)
