VTA neurons: Morphofunctional alterations in acute opiates withdrawal (Enrico et al. 2016)

 Download zip file   Auto-launch 
Help downloading and running models
Accession:185330
" ... Here we present a biophysical model of a DA VTA neuron based on 3D morphological reconstruction and electrophysiological data, showing how opiates withdrawal-driven morphological and electrophysiological changes could affect the firing rate and discharge pattern...."
Reference:
1 . Enrico P, Migliore M, Spiga S, Mulas G, Caboni F, Diana M (2016) Morphofunctional alterations in ventral tegmental area dopamine neurons in acute and prolonged opiates withdrawal. A computational perspective. Neuroscience 322:195-207 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Ventral tegmental area dopamine neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Addiction;
Implementer(s): Enrico, Paolo [enrico at uniss.it];
/
EnricoEtAl2016
README.html
cabal.mod *
cachan.mod
capump.mod *
dop.mod *
hh3.mod
IhDA.mod
kca.mod
nabalan.mod
netstimd.mod
newleak.mod
nmdanet.mod *
pump.mod *
CellDef.hoc
ctrlfiring_cnt.txt
DA_release.ses
DA_release_final.hoc
DA_release_withdrawal_final.hoc
DA_release_withdrawal_final_noGLU.hoc
firing_cnt.txt
fixnseg.hoc *
mosinit.hoc
screenshot.png
screenshot2.png
                            
{load_file("nrngui.hoc")}
objectvar save_window_, rvp_
objectvar scene_vector_[4]
objectvar ocbox_, ocbox_list_, scene_, scene_list_
{ocbox_list_ = new List()  scene_list_ = new List()}
{pwman_place(0,0,0)}
{
xpanel("Model conductances", 0)
gna = 0.005
xvalue("gnabar","gna", 1,"na()", 0, 0 )
gkdr = 0.003
xvalue("gkdrbar","gkdr", 1,"kdel()", 0, 0 )
gkas = 0.00057
xvalue("soma_gkabar","gkas", 1,"ka()", 0, 0 )
gkap = 0.00057
xvalue("prox_gkabar","gkap", 1,"ka()", 0, 0 )
gkad = 0.000285
xvalue("dist_gkabar","gkad", 1,"ka()", 0, 0 )
gca = 1e-05
xvalue("gcabar","gca", 1,"gcal()", 0, 0 )
gkca = 0.0008
xvalue("gkcabar","gkca", 1,"gkcal()", 0, 0 )
xpanel(-4,120)
}
{
save_window_ = new Graph(0)
save_window_.size(0,10000,-80,50)
scene_vector_[2] = save_window_
{save_window_.view(0, -80, 10000, 130, 999, 19, 845.76, 446.08)}
graphList[0].append(save_window_)
save_window_.save_name("graphList[0].")
save_window_.addexpr("v(.5)", 1, 1, 0.8, 0.9, 2)
}
{
save_window_ = new Graph(0)
save_window_.size(0,10000,-2.98023e-08,1.5)
scene_vector_[3] = save_window_
{save_window_.view(0, -2.98023e-08, 10000, 1.5, 999, 550, 845.76, 270.4)}
graphList[0].append(save_window_)
save_window_.save_name("graphList[0].")
save_window_.label(0.4, 0.92, " Dopamine Level - Fast Decay", 2, 1, 0, 0, 1)
save_window_.addexpr("syn_DA0.dop", 1, 1, 2.99, 2.99, 2)
save_window_.addexpr("syn_DA1.dop", 2, 1, 2.99, 2.99, 2)
}
{
xpanel("RunControl", 0)
v_init = -65
xvalue("Init","v_init", 1,"stdinit()", 1, 1 )
xbutton("Init & Run","run()")
xbutton("Stop","stoprun=1")
runStopAt = 5
xvalue("Continue til","runStopAt", 1,"{continuerun(runStopAt) stoprun=1}", 1, 1 )
runStopIn = 1
xvalue("Continue for","runStopIn", 1,"{continuerun(t + runStopIn) stoprun=1}", 1, 1 )
xbutton("Single Step","steprun()")
t = 0
xvalue("t","t", 2 )
tstop = 10000
xvalue("Tstop","tstop", 1,"tstop_changed()", 0, 1 )
dt = 0.00625
xvalue("dt","dt", 1,"setdt()", 0, 1 )
steps_per_ms = 40
xvalue("Points plotted/ms","steps_per_ms", 1,"setdt()", 0, 1 )
screen_update_invl = 0.05
xvalue("Scrn update invl","screen_update_invl", 1,"", 0, 1 )
realtime = 0
xvalue("Real Time","realtime", 0,"", 0, 1 )
xpanel(20,413)
}
objectvar scene_vector_[1]
{doNotify()}

Loading data, please wait...