"""
Simulation code for Fig 5. - Model 2
Test the effects of different syanptic input locations
for the generation of plateau potential
For Major's model (Model 2), same setting, but needs bigger input strength to
measure the plateau amplitude and duration.
Author: Peng Penny Gao
<penggao.1987@gmail.com>
"""
import CA229 as de # from CA229 import *
import matplotlib.pyplot as plt
from neuron import h
import numpy as np
import utils as ut #from utils import *
import json
import itertools
import time
import pdb # For python debugging
# from random import *
h.load_file('stdrun.hoc') # for initialization
def random_2(low, high, size):
time_random = np.linspace(low, high, size)
np.random.shuffle(time_random)
return time_random
################### Test the ratio of different repceptors
def Glu_Stim(Bnum = 34, TTX = False, Pool1_num = 9, Pool2_num = 9,
Syn_w1 = 0.01, Syn_w2 = 0.01, Loc = [0.2, 0.6], DenLoc = 0.5):
"""
Model the Glumate Stimulation.
Model the Receptors in 2 pools:
Pool 1: AMPA + NMDA (same synaptic weight, represent spine conductance)
Pool 2: NMDA only (represent the extrasyanptic NMDARs)
Parameters:
-----------
Bnum: the number of basal branch to explore
TTX: True or False.
True: setting all the sodium channel conductance to 0.
False: default
Pool1_num: syanptic AMPA/NMDA numbers
Pool2_num: extrasyanptic NMDA numbers
Syn_w1: the syanptic weight of AMPA/NMDA receptors in pool1
Syn_w2: the syanptic weight of AMPA/NMDA receptors in pool2
Loc: the stimulation location
DenLoc: the targeted recording location on dendrite
-----------
Outputs:
Figures: recording from soma and 3 different locations from basal dendrites
json: soma and dendritc voltage recording and parameters info
"""
Cell = de.CA229()
timestr = time.strftime("%Y%m%d-%H%M")
data = time.strftime("%m_%d")
directory_root = "Fig5/Major/"
L1 = "{:.2f}".format(Loc[0])
L2 = "{:.2f}".format(Loc[1])
if (TTX == True):
Cell.TTX()
directory = directory_root + "B" + str(Bnum) + "/Loc" + L1 + "_" + L2 + "/TTX/"
title = "TTX_Pool1_"+ \
str(Pool1_num) + "_Pool2_" + str(Pool2_num) + \
"_Pool1_W_" + str(Syn_w1) + \
"_Pool2_W_" + str(Syn_w2) + "_"+ timestr
else:
directory = directory_root + "B" + str(Bnum) + "/Loc" + L1 + "_" + L2 + "/N/"
title = "Pool1_"+ \
str(Pool1_num) + "_Pool2_" + str(Pool2_num) + \
"_Pool1_W_" + str(Syn_w1) + \
"_Pool2_W_" + str(Syn_w2) + "_"+ timestr
###########################################
# Adding Pool 1
###########################################
##### AMPA
SynAMPA = []
nc_AMPA = []
SynNMDA = []
nc_NMDA = []
loc1 = list(np.linspace(Loc[0], Loc[1], Pool1_num))
###########################################
delay1 = random_2(10, 20 + int(Syn_w1*50), Pool1_num)
ns = h.NetStim()
ns.interval = 20
ns.number = 1
ns.start = 190
ns.noise = 0
for i in range(Pool1_num):
###########################
# Adding AMPA
SynAMPA.append(h.AMPA(Cell.basal[Bnum](loc1[i])))
SynAMPA[-1].gmax = 0.05
nc_AMPA.append(h.NetCon(ns, SynAMPA[i]))
nc_AMPA[-1].delay = delay1[i]
nc_AMPA[-1].weight[0] = Syn_w1
###########################
for i in range(Pool1_num):
tempNMDA = h.nmda(Cell.basal[Bnum](loc1[i]))
tempNMDA.gmax = 0.005*Syn_w1
tempNMDA.onset= delay1[i] + ns.start
SynNMDA.append(tempNMDA)
###########################################
# Adding Pool 2
###########################################
ExNMDA = []
nc_ExNMDA = []
loc2 = list(np.linspace(Loc[0], Loc[1], Pool2_num))
delay2 = random_2(15, 25 + int(Syn_w2*60), Pool2_num)
for i in range(Pool2_num):
###########################
# Adding extrasyanptic NMDA
tempNMDA2 = h.nmda(Cell.basal[Bnum](loc2[i]))
tempNMDA2.gmax = 0.005*Syn_w2
tempNMDA2.onset= delay2[i] + ns.start
ExNMDA.append(tempNMDA2)
###########################################
### Recording
###########################################
t_vec = h.Vector()
t_vec.record(h._ref_t)
v_vec_soma = h.Vector()
v_vec_dend1 = h.Vector()
v_vec_dend2 = h.Vector()
v_vec_dend3 = h.Vector()
v_vec_dend = h.Vector()
v_vec_soma.record(Cell.soma[2](0.5)._ref_v)
v_vec_dend1.record(Cell.basal[Bnum](0.8)._ref_v)
v_vec_dend2.record(Cell.basal[Bnum](0.5)._ref_v)
v_vec_dend3.record(Cell.basal[Bnum](0.3)._ref_v)
v_vec_dend.record(Cell.basal[Bnum](DenLoc)._ref_v)
###########################################
### Run & Plot
###########################################
h.celsius = 32
h.v_init = -73.6927850677
h.init()
h.tstop = 1000
h.run()
# pdb.set_trace() #Debugging
# plt.figure(figsize = (16, 6), dpi = 100)
# plt.plot(t_vec, v_vec_soma, label = 'soma(0.5)', color = 'black')
# plt.plot(t_vec, v_vec_dend1, label = 'Basal['+str(Bnum)+'](0.8)', color = 'red')
# plt.plot(t_vec, v_vec_dend2, label = 'Basal['+str(Bnum)+'](0.5)', color = 'blue')
# plt.plot(t_vec, v_vec_dend3, label = 'Basal['+str(Bnum)+'](0.3)', color = 'green')
# plt.ylim([-90, 40])
# plt.xlim([0, 700])
# plt.legend(loc = 'best')
# plt.ylabel('mV')
# plt.xlabel('Time (ms)')
# plt.title ("Glumate Receptor Activated Plateau Potential")
# save(title, directory, ext="png", close=True, verbose=True)
data = ut.Vividict()
data['TTX'] = TTX
data['SynAMPA']['num'] = Pool1_num
data['SynAMPA']['locs'] = Loc
data['SynAMPA']['weight'] = Syn_w1
data['SynNMDA']['num'] = Pool1_num
data['SynNMDA']['locs'] = Loc
data['SynNMDA']['weight'] = Syn_w1
data['ExNMDA']['num'] = Pool2_num
data['ExNMDA']['locs'] = Loc
data['ExNMDA']['weight'] = Syn_w2
data['recording']['time'] = list(t_vec)
data['recording']['soma']['voltage'] = list(v_vec_soma)
data['recording']['basal']['voltage_0.8'] = list(v_vec_dend1)
data['recording']['basal']['voltage_0.5'] = list(v_vec_dend2)
data['recording']['basal']['voltage_0.3'] = list(v_vec_dend3)
data['recording']['basal']['voltage_input'] = list(v_vec_dend)
ut.savejson(data, title, directory, ext = "json", verbose = False)
######################################################
if __name__ == "__main__":
print("Running the model")
start_time = time.time()
Pool_num = 12
# weight = [1.5] # For generating multiple APs - Fig 5. E3
# weight = [0.1, 0.3, 0.5, 0.7] # For the demo traces
weight = [0.9]
# weight = [0.1, 0.3, 0.5, 0.7, 0.9]
basal_num = [15, 34, 14, 22, 25, 31]
# The information of input locations for each branch
with open('data.json', 'r') as fp:
data = json.load(fp)
with open('dend_measure_data.json', 'r') as fp1:
Ndata = json.load(fp1)
for b in basal_num:
loc = data[str(b)]
DenLoc = Ndata[str(b)]
for l1, l2 in zip(loc, DenLoc):
for w in weight:
Glu_Stim(b, False, Pool_num, Pool_num, w, w, l1, l2)
Glu_Stim(b, True, Pool_num, Pool_num, w, w, l1, l2)
print("Finished.")
print("--- %s seconds ---" % (time.time() - start_time))
