In silico hippocampal modeling for multi-target pharmacotherapy in schizophrenia (Sherif et al 2020)

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Accession:258738
"Using a hippocampal CA3 computer model with 1200 neurons, we examined the effects of alterations in NMDAR, HCN (Ih current), and GABAAR on information flow (measured with normalized transfer entropy), and in gamma activity in local field potential (LFP). We found that altering NMDARs, GABAAR, Ih, individually or in combination, modified information flow in an inverted-U shape manner, with information flow reduced at low and high levels of these parameters. Theta-gamma phase-amplitude coupling also had an inverted-U shape relationship with NMDAR augmentation. The strong information flow was associated with an intermediate level of synchrony, seen as an intermediate level of gamma activity in the LFP, and an intermediate level of pyramidal cell excitability"
Reference:
1 . Sherif MA, Neymotin SA, Lytton WW (2020) In silico hippocampal modeling for multi-target pharmacotherapy in schizophrenia. NPJ Schizophr 6:25 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA3 pyramidal GLU cell; Hippocampus CA3 interneuron basket GABA cell; Hippocampus CA3 stratum oriens lacunosum-moleculare interneuron;
Channel(s): I h;
Gap Junctions:
Receptor(s): AMPA; NMDA;
Gene(s): NR2A GRIN2A;
Transmitter(s): Glutamate; Gaba;
Simulation Environment: NEURON;
Model Concept(s): Schizophrenia;
Implementer(s): Sherif, Mohamed [mohamed.sherif.md at gmail.com];
Search NeuronDB for information about:  Hippocampus CA3 pyramidal GLU cell; Hippocampus CA3 interneuron basket GABA cell; AMPA; NMDA; I h; Gaba; Glutamate;
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CA3modelCode_npjSchizophrenia_September2020--main
data
README.md
CA1ih.mod
CA1ika.mod *
CA1ikdr.mod *
CA1ina.mod *
cagk.mod *
caolmw.mod *
capr.mod *
expsynstdp.mod
Gfluctp.mod *
HCN1.mod *
HCN2.mod
IA.mod
icaolmw.mod *
icapr.mod *
iholmkop.mod *
iholmw.mod *
ihpyrkop.mod *
ihstatic.mod *
infot.mod *
kahppr.mod *
kaolmkop.mod *
kapyrkop.mod *
kcaolmw.mod *
kcpr.mod *
kdrbwb.mod *
kdrolmkop.mod *
kdrpr.mod *
kdrpyrkop.mod *
km.mod
misc.mod *
MyExp2Syn.mod *
MyExp2SynAlpha.mod *
MyExp2SynBB.mod *
MyExp2SynNMDA.mod *
MyExp2SynNMDABB.mod *
nafbwb.mod *
nafolmkop.mod *
nafpr.mod *
nafpyrkop.mod *
samnutils.mod
sampen.mod
stats.mod
updown.mod *
vecst.mod *
wrap.mod *
analysisPlottingCode.py
aux_fun.inc *
batch.py
conf.py
declist.hoc *
decmat.hoc *
decnqs.hoc *
decvec.hoc *
default.hoc *
drline.hoc *
fig1sample.png
fig1simulationConfig.cfg
geom.py
grvec.hoc *
init.hoc
labels.hoc *
local.hoc *
misc.h
network.py
nqs.hoc *
nqs_utils.hoc *
nrnoc.hoc *
params.py
psd.py
pyinit.py
pywrap.hoc *
run.py
runone.py
simctrl.hoc *
stats.hoc *
syncode.hoc *
updown.hoc
xgetargs.hoc *
                            
# $Id: geom.py,v 1.38 2012/11/09 21:00:26 samn Exp $ 

from pyinit import *
h.celsius = 37

from conf import *


########### the following allows for setting and reading the config file ###########
def setfcfg ():
  '''determine config file'''
  # fcfg = "netcfg.cfg" # default config file name
  fcfg = 'fig1simulationConfig.cfg'
  for i in range(len(sys.argv)):
    if sys.argv[i].endswith(".cfg") and os.path.exists(sys.argv[i]):
      fcfg = sys.argv[i]
  print ("config file is " , fcfg)
  return fcfg

fcfg=setfcfg() # config file name
dconf = readconf(fcfg)

########### h currents for different cells ###########
hCurrent_g_pv_scaling = dconf['hCurrent_g_pv_scaling']
hCurrent_g_olm_scaling = dconf['hCurrent_g_olm_scaling']
hCurrent_g_pyr_scaling = dconf['hCurrent_g_pyr_scaling']
hCurrent_g_cck_scaling = dconf['hCurrent_g_cck_scaling']


########### code for defining cells and synapses ###########


# h('load_file("./hoc_files/pywrap.hoc")')

class Synapse:
    def __init__(self, sect, loc, tau1, tau2, e):
        self.syn        = h.MyExp2SynBB(loc, sec=sect)
        self.syn.tau1   = tau1
        self.syn.tau2   = tau2
        self.syn.e      = e 
        
class SynapseNMDA:
    def __init__(self, sect, loc, tau1, tau2, tau1NMDA, tau2NMDA, r, e):
        self.syn            = h.MyExp2SynNMDABB(loc, sec=sect)
        self.syn.tau1       = tau1
        self.syn.tau2       = tau2
        self.syn.tau1NMDA   = tau1NMDA
        self.syn.tau2NMDA   = tau2NMDA 
        self.syn.r          = r
        self.syn.e          = e 

class SynapseSTDP:
    def __init__(self, sect, loc, tau, e, dtau, ptau, d, p):
        self.syn    = h.ExpSynSTDP(loc, sec=sect)
        self.syn.tau    = tau
        self.syn.e      = e 
        self.syn.dtau   = dtau
        self.syn.ptau   = ptau
        self.syn.d      = d
        self.syn.p      = p
        
###############################################################################
#
# General Cell
#
###############################################################################
class Cell(object):
    "General cell"
    
    def __init__(self,x,y,z,id):
        self.x=x
        self.y=y
        self.z=z
        self.id=id
        self.all_sec = []
        self.add_comp('soma',True)
        self.set_morphology()
        self.set_conductances()
        self.set_synapses()
        self.set_inj()
        self.calc_area()

    def __repr__(self):
        return str(type(self)) + str(self.id)
        
    def set_morphology(self):
        pass
            
    def set_conductances(self):
        pass
        
    def set_synapses(self):
        pass
        
    def set_inj(self):
        self.somaInj = h.IClamp(0.5, sec=self.soma) 
        
    def add_comp(self, name, rec):
        self.__dict__[name] = h.Section()
        self.all_sec.append(self.__dict__[name])
        # Record voltage
        if rec:
            self.__dict__[name+"_volt"] = h.Vector(int(h.tstop/h.dt)+1)
            self.__dict__[name+"_volt"].record(self.__dict__[name](0.5)._ref_v)

    def plot_volt(self, name,  myax, *args, **kwargs):
          # figure(fig)
          volt = self.__dict__[name+"_volt"].to_python()
          myax.plot(arange(len(volt))*h.dt, volt, *args, **kwargs)
          myax.set_xlabel('time (ms)')
          myax.set_ylabel('voltage (mV)')

    def clear_volt(self):
        self.soma_volt.resize(0)
        
    def calc_area(self):
        self.total_area = 0
        self.n = 0
        for sect in self.all_sec:
            self.total_area += h.area(0.5,sec=sect)
            self.n+=1
    
    def insert_gfluct_noise(self):
        self.Gfluctp = h.Gfluctp(self.soma(0.5))
            
###############################################################################
#
# PV Basket Cell -- PVC
# (was called Bwb before)
#
###############################################################################

class PVC(Cell):
    "PV Basket cell"
    
    def set_morphology(self):
        total_area = 10000 # um2
        self.soma.nseg  = 1
        self.soma.cm    = 1      # uF/cm2
        diam = sqrt(total_area) # um
        L    = diam/pi  # um
            
        h.pt3dclear(sec=self.soma)
        h.pt3dadd(self.x, self.y, self.z,   diam, sec=self.soma)
        h.pt3dadd(self.x, self.y, self.z+L, diam, sec=self.soma)
            
    def set_conductances(self):
        self.soma.insert('pas')
        self.soma.e_pas = -65     # mV
        self.soma.g_pas = 0.1e-3 #*2.5 # default: 0.1e-3  # S/cm2 
      
        self.soma.insert('Nafbwb')
        self.soma(0.5).Nafbwb.gna = 35  # default == 35
        self.soma.insert('Kdrbwb')
        self.soma(0.5).Kdrbwb.gkdr = 9 #*1.2# *2 # default is 9        

        self.soma.insert('HCN1')
        self.soma(0.5).HCN1.htaufactor = 1
        self.soma(0.5).HCN1.gbar = 0.0001 * 0.2 * hCurrent_g_pv_scaling # (0.074 / 0.175) * 0.5
       
    def set_synapses(self):
        self.somaAMPAf  = Synapse(sect=self.soma, loc=0.5, tau1=0.05, tau2=5.3, e=0)
        self.somaGABAf  = Synapse(sect=self.soma, loc=0.5, tau1=0.07, tau2=9.1, e=-80)
        self.somaGABAss = Synapse(sect=self.soma, loc=0.5, tau1=20,   tau2=40, e=-80)#only for septal input
        self.somaNMDA   = SynapseNMDA(sect=self.soma, loc=0.5, tau1=0.05, tau2=5.3, tau1NMDA=15, tau2NMDA=150, r=1, e=0)
        self.somaAMPASTDP = SynapseSTDP(sect=self.soma,loc=0.5,tau=5.35,e=0,dtau=34,ptau=17,d=0.5,p=0.5)
        
###############################################################################
#
# CCK Basket Cell -- Cck
#
###############################################################################
class CCKC(Cell):
    "CCK Basket cell"
    
    def set_morphology(self):
        total_area = 10000 # um2
        self.soma.nseg  = 1
        self.soma.cm    = 1      # uF/cm2
        diam = sqrt(total_area) # um
        L    = diam/pi  # um
            
        h.pt3dclear(sec=self.soma)
        h.pt3dadd(self.x, self.y, self.z,   diam, sec=self.soma)
        h.pt3dadd(self.x, self.y, self.z+L, diam, sec=self.soma)
            
    def set_conductances(self):
        self.soma.insert('pas')
        self.soma.e_pas = -65     # mV
        self.soma.g_pas = 0.1e-3 # 0.3e-3 # S/cm2 
      
        self.soma.insert('Nafbwb')
        self.soma(0.5).Nafbwb.gna = 35 * 1.5  # 2 # default == 35
        self.soma.insert('Kdrbwb')
        self.soma.insert('Iholmw')
        self.soma(0.5).Iholmw.gbar = 0.00015 * hCurrent_g_cck_scaling # default in mod file is 0.00015
        self.soma.insert('Caolmw')
        self.soma(0.5).Caolmw.tau = 400 
        self.soma.insert('ICaolmw')
        self.soma.insert('KCaolmw')
        self.soma(0.5).KCaolmw.gkca = 3 # 10 * 0.3 # default is 10
        self.soma.insert('km')
        self.soma(0.5).km.gbar = 10* 0.5 # 2 #* 1.5 # default is 10 
   
    def set_synapses(self):
        self.somaAMPAf  = Synapse(sect=self.soma, loc=0.5, tau1=0.05, tau2=5.3, e=0)
        self.somaGABAf  = Synapse(sect=self.soma, loc=0.5, tau1=0.07, tau2=9.1, e=-80)
        self.somaGABAss = Synapse(sect=self.soma, loc=0.5, tau1=20,   tau2=40, e=-80)#only for septal input
        self.somaNMDA   = SynapseNMDA(sect=self.soma, loc=0.5, tau1=0.05, tau2=5.3, tau1NMDA=15, tau2NMDA=150, r=1, e=0)
        self.somaAMPASTDP = SynapseSTDP(sect=self.soma,loc=0.5,tau=5.35,e=0,dtau=34,ptau=17,d=0.5,p=0.5)

                
###############################################################################
#
# OLM Cell -- Ow
#
###############################################################################
class Ow(Cell):
    "OLM cell"
   
    def set_morphology(self):
        total_area = 10000 # um2
        self.soma.nseg  = 1
        self.soma.cm    = 1      # uF/cm2
        diam = sqrt(total_area) # um
        L    = diam/pi  # um

        h.pt3dclear(sec=self.soma)
        h.pt3dadd(self.x, self.y, self.z,   diam, sec=self.soma)
        h.pt3dadd(self.x, self.y, self.z+L, diam, sec=self.soma)
    
    def set_conductances(self):
        self.soma.insert('pas')
        self.soma.e_pas = -65     # mV
        self.soma.g_pas = 0.1e-3  # S/cm2 

        self.soma.insert('Nafbwb')
        self.soma.insert('Kdrbwb')
        self.soma.insert('Iholmw')
        self.soma(0.5).Iholmw.gbar = 0.00015 * hCurrent_g_olm_scaling # default in mod file is 0.00015
        # self.soma.insert('HCN1')
        # self.soma.insert('HCN2')
        self.soma.insert('Caolmw')
        self.soma.insert('ICaolmw')
        self.soma.insert('KCaolmw')

    def set_synapses(self):
        self.somaGABAf  = Synapse(sect=self.soma, loc=0.5, tau1=0.07, tau2=9.1, e=-80)
        self.somaAMPAf  = Synapse(    sect=self.soma, loc=0.5, tau1=0.05, tau2=5.3, e=0)
        self.somaGABAss = Synapse(    sect=self.soma, loc=0.5, tau1=20,   tau2=40, e=-80)#only for septal input
        self.somaNMDA   = SynapseNMDA(sect=self.soma, loc=0.5, tau1=0.05, tau2=5.3, tau1NMDA=15, tau2NMDA=150, r=1, e=0)
        self.somaAMPASTDP = SynapseSTDP(sect=self.soma,loc=0.5,tau=5.35,e=0,dtau=34,ptau=17,d=0.5,p=0.5)
        
###############################################################################
#
# Pyramidal Cell -- KopAdr
#
###############################################################################
class PyrAdr(Cell):
    "Pyramidal cell"

    def set_morphology(self):
        self.add_comp('Bdend',True)
        self.add_comp('Adend1',False)
        self.add_comp('Adend2',False)
        self.add_comp('Adend3',True)

        h.pt3dclear(sec=self.soma)
        h.pt3dadd(self.x, self.y, self.z,          20, sec=self.soma)
        h.pt3dadd(self.x, self.y, self.z+20,       20, sec=self.soma)

        h.pt3dclear(sec=self.Bdend)
        h.pt3dadd(self.x, self.y, self.z,          2, sec=self.Bdend)
        h.pt3dadd(self.x, self.y, self.z-200,      2, sec=self.Bdend)

        h.pt3dclear(sec=self.Adend1)
        h.pt3dadd(self.x, self.y, self.z+20,       2, sec=self.Adend1)
        h.pt3dadd(self.x, self.y, self.z+20+150,   2, sec=self.Adend1)

        h.pt3dclear(sec=self.Adend2)
        h.pt3dadd(self.x, self.y, self.z+20+150,   2, sec=self.Adend2)
        h.pt3dadd(self.x, self.y, self.z+20+150*2, 2, sec=self.Adend2)

        h.pt3dclear(sec=self.Adend3)
        h.pt3dadd(self.x, self.y, self.z+20+150*2, 2, sec=self.Adend3)
        h.pt3dadd(self.x, self.y, self.z+20+150*3, 2, sec=self.Adend3)

        self.Bdend.connect(self.soma,      0, 0)
        self.Adend1.connect(self.soma,   0.5, 0)
        self.Adend2.connect(self.Adend1,   1, 0)
        self.Adend3.connect(self.Adend2,   1, 0)

    def clear_volt(self):
        self.soma_volt.resize(0)
        self.Bdend_volt.resize(0)
        self.Adend3_volt.resize(0)

    def set_conductances(self):
        for sect in self.all_sec:
            sect.insert('pas')
            sect(0.5).pas.g = 0.0000357
            sect.insert('nacurrent')
            sect.insert('kacurrent')
            sect.insert('kdrcurrent')
            sect.insert('hcurrent')
            # sect.insert('HCN2')
            sect(0.5).pas.e = -70     # mV
            sect.cm = 1
            sect.Ra = 150
            # sect(0.5).HCN2.v50 = -92
            # sect(0.5).HCN2.gbar = 0.0007

        self.soma(0.5).hcurrent.gbar = 0.0001 * hCurrent_g_pyr_scaling  # default from CA1ih.mod file is 0.0001

        self.Adend1(0.5).nacurrent.ki = 0.5
        self.Adend1(0.5).kacurrent.g  = 0.072
        self.Adend1(0.5).hcurrent.v50 = -82
        self.Adend1(0.5).hcurrent.gbar   = 0.0002 * hCurrent_g_pyr_scaling
        
        self.Adend2(0.5).nacurrent.ki = 0.5
        self.Adend2(0.5).kacurrent.g  = 0
        self.Adend2(0.5).kacurrent.gd = 0.120
        self.Adend2(0.5).hcurrent.v50 = -90
        self.Adend2(0.5).hcurrent.gbar   = 0.0004 * hCurrent_g_pyr_scaling
        
        self.Adend3(0.5).cm           = 2
        self.Adend3(0.5).pas.g        = 0.0000714
        self.Adend3(0.5).nacurrent.ki = 0.5
        self.Adend3(0.5).kacurrent.g  = 0
        self.Adend3(0.5).kacurrent.gd = 0.200       
        self.Adend3(0.5).hcurrent.v50 = -90
        self.Adend3(0.5).hcurrent.gbar   = 0.0007 * hCurrent_g_pyr_scaling
        
        self.Bdend(0.5).nacurrent.ki  = 1
        self.Bdend(0.5).hcurrent.gbar = 0.0001 * hCurrent_g_pyr_scaling # default from CA1ih.mod file is 0.0001

    def set_synapses(self):
        self.somaGABAf   = Synapse(    sect=self.soma,   loc=0.5, tau1=0.07, tau2=9.1,    e=-80)
        self.somaAMPAf   = Synapse(    sect=self.soma,   loc=0.5, tau1=0.05, tau2=5.3,     e=0)
        self.BdendAMPA   = Synapse(    sect=self.Bdend,  loc=0.5, tau1=0.05, tau2=5.3,     e=0)
        self.BdendNMDA   = SynapseNMDA(sect=self.Bdend,  loc=0.5, tau1=0.05, tau2=5.3, tau1NMDA=15, tau2NMDA=150, r=1, e=0)
        # insert synapses into the middle segment of apical dendrites which will be targeted by recurrent collateral fibres - added by mohdsh on 2016Jan26 (molpsychistb@gmail.com)
        self.Adend2AMPA   = Synapse(    sect=self.Adend2,  loc=0.5, tau1=0.05, tau2=5.3,     e=0)
        self.Adend2NMDA   = SynapseNMDA(sect=self.Adend2,  loc=0.5, tau1=0.05, tau2=5.3, tau1NMDA=15, tau2NMDA=150, r=1, e=0)
        self.Adend2GABAf = Synapse(    sect=self.Adend1, loc=0.5, tau1=0.07, tau2=9.1,    e=-80) # for CCK_Adend2Pyr cells
        self.Adend2GABAs = Synapse(    sect=self.Adend2, loc=0.5, tau1=0.2,  tau2=20,   e=-80) # was used for OLM cells - now OLM cells will target Adend3 # either Adend2GABAs or Adend3GABAs are used
        self.Adend3GABAs = Synapse(    sect=self.Adend3, loc=0.5, tau1=0.2,  tau2=20,   e=-80) # added by mohdsh 2016jan22 - for olm to target distal dendrites
        self.Adend3GABAf = Synapse(    sect=self.Adend3, loc=0.5, tau1=0.07, tau2=9.1,   e=-80)
        self.Adend3AMPAf = Synapse(    sect=self.Adend3, loc=0.5, tau1=0.05, tau2=5.3,    e=0)
        self.Adend3NMDA  = SynapseNMDA(sect=self.Adend3, loc=0.5, tau1=0.05, tau2=5.3, tau1NMDA=15, tau2NMDA=150, r=1, e=0)
        self.Adend3AMPASTDP = SynapseSTDP(sect=self.Adend3,loc=0.5,tau=5.35,e=0,dtau=34,ptau=17,d=0.5,p=0.5)







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