Multitarget pharmacology for Dystonia in M1 (Neymotin et al 2016)

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Accession:189154
" ... We developed a multiscale model of primary motor cortex, ranging from molecular, up to cellular, and network levels, containing 1715 compartmental model neurons with multiple ion channels and intracellular molecular dynamics. We wired the model based on electrophysiological data obtained from mouse motor cortex circuit mapping experiments. We used the model to reproduce patterns of heightened activity seen in dystonia by applying independent random variations in parameters to identify pathological parameter sets. ..."
Reference:
1 . Neymotin SA, Dura-Bernal S, Lakatos P, Sanger TD, Lytton WW (2016) Multitarget Multiscale Simulation for Pharmacological Treatment of Dystonia in Motor Cortex. Front Pharmacol 7:157 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Molecular Network;
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Neocortex V1 pyramidal corticothalamic L6 cell; Neocortex U1 pyramidal intratelencephalic L2-6 cell; Neocortex V1 interneuron basket PV cell; Neocortex fast spiking (FS) interneuron; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron; Neocortex layer 4 neuron; Neocortex layer 2-3 interneuron; Neocortex layer 4 interneuron; Neocortex layer 5 interneuron; Neocortex layer 6a interneuron;
Channel(s): I A; I h; I_SERCA; Ca pump; I K,Ca; I Calcium; I L high threshold; I T low threshold; I N; I_KD; I M; I Na,t;
Gap Junctions:
Receptor(s): GabaA; GabaB; AMPA; mGluR;
Gene(s): HCN1;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON; Python;
Model Concept(s): Oscillations; Activity Patterns; Beta oscillations; Reaction-diffusion; Calcium dynamics; Pathophysiology; Multiscale;
Implementer(s): Neymotin, Sam [samn at neurosim.downstate.edu]; Dura-Bernal, Salvador [salvadordura at gmail.com];
Search NeuronDB for information about:  Neocortex V1 pyramidal corticothalamic L6 cell; Neocortex V1 interneuron basket PV cell; Neocortex U1 pyramidal intratelencephalic L2-6 cell; GabaA; GabaB; AMPA; mGluR; I Na,t; I L high threshold; I N; I T low threshold; I A; I M; I h; I K,Ca; I Calcium; I_SERCA; I_KD; Ca pump; Gaba; Glutamate;
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dystdemo
readme.txt
cagk.mod
cal.mod *
calts.mod *
can.mod *
cat.mod *
gabab.mod
h_winograd.mod
HCN1.mod
IC.mod *
icalts.mod *
ihlts.mod *
kap.mod
kcalts.mod *
kdmc.mod
kdr.mod
km.mod *
mglur.mod *
misc.mod *
MyExp2SynBB.mod *
MyExp2SynNMDABB.mod
nax.mod
stats.mod *
vecst.mod *
aux_fun.inc *
conf.py
declist.hoc *
decnqs.hoc *
decnqs.hoc'A=0
decvec.hoc *
default.hoc *
drline.hoc *
geom.py
ghk.inc *
grvec.hoc
init.hoc
labels.hoc
labels.py *
local.hoc *
misc.h
mpisim.py
mpisim.py'A=0
netcfg.cfg
nqs.hoc *
nqs.py
nrnoc.hoc *
pyinit.py *
python.hoc *
pywrap.hoc *
simctrl.hoc *
simdat.py
simdat.py'A=0
syn.py
syncode.hoc *
vector.py *
xgetargs.hoc *
                            
from neuron import h

# metabotropic glutamate receptor
class SynapsemGLUR:
  def __init__(self,sect,loc):
    self.syn = h.mGLUR(loc, sec=sect)

# AMPA synapse with calcium influx -- mechanism defined in mod/ampa_forti.mod
class SynapseAMPACA:
  def __init__(self, sect, loc, e):
    self.syn		= h.AmpaSyn(loc, sec=sect)
    self.syn.e		= e 

# NMDA synapse with calcium influx -- mechanism defined in mod/nmda_andr.mod
class SynapseNMDACA:
  def __init__(self, sect, loc, e):
    self.syn		= h.NmdaSyn(loc, sec=sect)
    self.syn.e		= e 

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, tau1NMDA, tau2NMDA, r, e):
    self.syn			= h.MyExp2SynNMDABB(loc, sec=sect)
    self.syn.tau1NMDA	= tau1NMDA
    self.syn.tau2NMDA	= tau2NMDA 
    self.syn.r			= r
    self.syn.e			= e 

# gabab based on 1995 PNAS paper by Destexhe
class SynapseGABAB:
  def __init__(self, sect, loc):
    self.syn = h.GABAB(loc, sec=sect)

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

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