Ribbon Synapse (Sikora et al 2005)

 Download zip file   Auto-launch 
Help downloading and running models
Accession:50997
A model of the ribbon synapse was developed to replicate both pre- and postsynaptic functions of this glutamatergic juncture. The presynaptic portion of the model is rich in anatomical and physiological detail and includes multiple release sites for each ribbon based on anatomical studies of presynaptic terminals, presynaptic voltage at the terminal, the activation of voltage-gated calcium channels and a calcium-dependent release mechanism whose rate varies as a function of the calcium concentration that is monitored at two different sites which control both an ultrafast, docked pool of vesicles and a release ready pool of tethered vesicles. See paper for more and details.
Reference:
1 . Sikora MA, Gottesman J, Miller RF (2005) A computational model of the ribbon synapse. J Neurosci Methods 145:47-61 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Synapse;
Brain Region(s)/Organism:
Cell Type(s): Retina ganglion GLU cell; Retina bipolar GLU cell;
Channel(s): I L high threshold;
Gap Junctions:
Receptor(s): AMPA; NMDA;
Gene(s):
Transmitter(s): Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Intrinsic plasticity; Calcium dynamics;
Implementer(s): Sikora, Michael [Sikora at umn.edu];
Search NeuronDB for information about:  Retina ganglion GLU cell; Retina bipolar GLU cell; AMPA; NMDA; I L high threshold; Glutamate;
load_file("nrngui.hoc")
objectvar save_window_, rvp_
objectvar scene_vector_[9]
objectvar ocbox_, ocbox_list_, scene_, scene_list_
{ocbox_list_ = new List()  scene_list_ = new List()}
{pwman_place(11,125,1)}
{
xpanel("RunControl", 0)
v_init = -65
xvalue("Init","v_init", 1,"stdinit()", 1, 1 )
xbutton("Init & Run","run()")
xbutton("Stop","stoprun=1")
runStopAt = 5000
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 = 5000
xvalue("t","t", 2 )
tstop = 5000
xvalue("Tstop","tstop", 1,"tstop_changed()", 0, 1 )
dt = 0.025
xvalue("dt","dt", 1,"setdt()", 0, 1 )
steps_per_ms = 40
xvalue("Points plotted/ms","steps_per_ms", 1,"setdt()", 0, 1 )
xcheckbox("Quiet",&stdrun_quiet,"")
realtime = 3241
xvalue("Real Time","realtime", 0,"", 0, 1 )
xpanel(14,556)
}
{
save_window_ = new Graph(0)
save_window_.size(0,5000,-67,23)
scene_vector_[2] = save_window_
{save_window_.view(0, -67, 5000, 90, 395, 831, 288.96, 90.88)}
graphList[0].append(save_window_)
save_window_.save_name("graphList[0].")
save_window_.label(0.786274, 0.190921, "Fig9-F", 2, 1, 0, 0, 1)
save_window_.addvar("soma.v( 0.5 )", 1, 1, 0.66901, 0.967093, 2)
}
{
save_window_ = new Graph(0)
save_window_.size(0,5000,0,0.014)
scene_vector_[3] = save_window_
{save_window_.view(0, 0, 5000, 0.014, 386, 188, 296.64, 96.64)}
graphList[2].append(save_window_)
save_window_.save_name("graphList[2].")
save_window_.addvar("preSyn.cai( 0.5 )", 1, 1, 0.617891, 0.943131, 2)
save_window_.addvar("preSyn2.cai( 0.5 )", 2, 1, 0.617891, 0.928754, 2)
save_window_.label(0.729965, 0.270624, "Fig9-B", 2, 1, 0, 0, 1)
}
{
save_window_ = new Graph(0)
save_window_.size(0,5000,-62,-25)
scene_vector_[4] = save_window_
{save_window_.view(0, -62, 5000, 37, 380, 26, 300.48, 102.4)}
graphList[0].append(save_window_)
save_window_.save_name("graphList[0].")
save_window_.addexpr("bpclamp.amp[0]", 1, 1, 0.640256, 0.986262, 2)
save_window_.addvar("bpclamp2.amp[0]", 2, 1, 0.640256, 0.985843, 2)
save_window_.label(0.757188, 0.393211, "Fig9-A", 2, 1, 0, 0, 1)
}
{
save_window_ = new Graph(0)
save_window_.size(0,5000,0,1.3)
scene_vector_[5] = save_window_
{save_window_.view(0, 0, 5000, 1.3, 389, 505, 288, 99.52)}
graphList[2].append(save_window_)
save_window_.save_name("graphList[2].")
save_window_.label(0.797033, 0.252202, "Fig9-D", 2, 1, 0, 0, 1)
save_window_.addvar("synapse[0].gluConc_dAMPA", 1, 1, 0.34544, 1.0087, 2)
save_window_.addvar("synapse[0].gluConc_NMDA", 1, 1, 0.362984, 1.01905, 2)
}
{
save_window_ = new Graph(0)
save_window_.size(0,5000,0,79)
scene_vector_[6] = save_window_
{save_window_.view(0, 0, 5000, 79, 386, 348, 295.68, 94.72)}
graphList[2].append(save_window_)
save_window_.save_name("graphList[2].")
save_window_.addexpr("synapse[0].Orate", 1, 1, 0.611502, 0.919169, 2)
save_window_.label(0.74165, 0.380472, "Fig9-C", 2, 1, 0, 0, 1)
}
{
ocbox_ = new VBox()
ocbox_list_.prepend(ocbox_)
ocbox_.intercept(1)
}
{
xpanel("Single Release Site", 0)
GMAX = 0.00256
xvalue("dAMPA gmax","GMAX", 1,"set_stim()", 0, 0 )
GMAXN = 0.00011
xvalue("NMDA gmax","GMAXN", 1,"set_stim()", 0, 0 )
xpanel()
}
{
ocbox_ = ocbox_list_.object(0)
ocbox_.intercept(0)
ocbox_.map("nrniv", 30, 409, 237.12, 88.32)
}
objref ocbox_
{
xpanel("VClamp[2] at soma(0.5)", 0)
xlabel("VClamp[2] at soma(0.5)")
soma_clamp.dur[0] = 0
xvalue("dur[0]","soma_clamp.dur[0]", 1,"", 0, 1 )
soma_clamp.dur[1] = 0
xvalue("dur[1]","soma_clamp.dur[1]", 1,"", 0, 1 )
soma_clamp.dur[2] = 0
xvalue("dur[2]","soma_clamp.dur[2]", 1,"", 0, 1 )
soma_clamp.amp[0] = -65
xvalue("amp[0]","soma_clamp.amp[0]", 1,"", 0, 1 )
soma_clamp.amp[1] = 0
xvalue("amp[1]","soma_clamp.amp[1]", 1,"", 0, 1 )
soma_clamp.amp[2] = 0
xvalue("amp[2]","soma_clamp.amp[2]", 1,"", 0, 1 )
soma_clamp.gain = 100000
xvalue("gain","soma_clamp.gain", 1,"", 0, 1 )
soma_clamp.rstim = 1
xvalue("rstim","soma_clamp.rstim", 1,"", 0, 1 )
soma_clamp.tau1 = 0.001
xvalue("tau1","soma_clamp.tau1", 1,"", 0, 1 )
soma_clamp.tau2 = 0
xvalue("tau2","soma_clamp.tau2", 1,"", 0, 1 )
soma_clamp.e0 = -31.863
xvalue("e0","soma_clamp.e0", 1,"", 0, 1 )
soma_clamp.vo0 = 3.1863e+06
xvalue("vo0","soma_clamp.vo0", 1,"", 0, 1 )
soma_clamp.vi0 = -65
xvalue("vi0","soma_clamp.vi0", 1,"", 0, 1 )
soma_clamp.fac = 0
xvalue("fac","soma_clamp.fac", 1,"", 0, 1 )
soma_clamp.i = 0
xvalue("i","soma_clamp.i", 0,"", 0, 1 )
soma_clamp.e = -31.8627
xvalue("e","soma_clamp.e", 0,"", 0, 1 )
soma_clamp.vo = 3.18627e+06
xvalue("vo","soma_clamp.vo", 0,"", 0, 1 )
soma_clamp.vi = -65
xvalue("vi","soma_clamp.vi", 0,"", 0, 1 )
xpanel(747,57)
}
{
save_window_ = new Graph(0)
save_window_.size(0,5000,-0.05,-9.31323e-10)
scene_vector_[7] = save_window_
{save_window_.view(0, -0.05, 5000, 0.05, 393, 667, 288.96, 99.52)}
graphList[1].append(save_window_)
save_window_.save_name("graphList[1].")
save_window_.label(0.272425, 0.144695, "for VClamp set dur[0] to 5000ms.", 2, 1, 0, 0, 1)
save_window_.label(0.777409, 0.414791, "Fig9-E", 2, 1, 0, 0, 1)
save_window_.addvar("soma_clamp.i", 1, 1, 0.8, 0.9, 2)
}
{
save_window_ = new Graph(0)
save_window_.size(0,5000,0,1)
scene_vector_[8] = save_window_
{save_window_.view(0, 0, 5000, 1, 227, 282, 696, 227.2)}
graphList[2].append(save_window_)
save_window_.save_name("graphList[2].")
save_window_.label(0.110247, 0.905968, "This simulation replicates Fig.9 in the paper. Fig.9-E is obtained using a soma voltage clamp", 2, 1, 0, 0, 1)
save_window_.label(0.109809, 0.448124, "Note that the rate expressed in Fig9-C here is for the entire 10 release sites of the synapse.", 2, 1, 0, 0, 1)
save_window_.label(0.111554, 0.735579, "Fig10-P in the paper will by default be replicated in Fig9-F here where AMPA conductance ", 2, 1, 0, 0, 1)
save_window_.label(0.112777, 0.655473, "is set at 256nS. and NMDA at 110pS.", 2, 1, 0, 0, 1)
save_window_.label(0.111878, 0.57134, "Fig10-E,F and O may also be replicated by changing the AMPA and NMDA gmax", 2, 1, 0, 0, 1)
save_window_.label(0.111692, 0.815819, "A total of 96 ribbon synapses are positioned on a traced ON ganglion cell.", 2, 1, 0, 0, 1)
save_window_.label(0.108966, 0.253521, "The lower trace in Fig. 11 may be replicated by setting gnabar_spike = 0.", 2, 1, 0, 0, 1)
save_window_.label(0.107586, 0.177465, "The upper trace will require commenting-in the AMPA modulator rates in ribbon_tiger.mod", 2, 1, 0, 0, 1)
save_window_.label(0.108966, 0.376056, "In the paper rate is expressed for one release site.", 2, 1, 0, 0, 1)
save_window_.label(0.108966, 0.09, "Adjust the parameters as desired and then press \"Init & Run\".", 2, 1, 0, 0, 1)

save_window_.xaxis(3)
}
objectvar scene_vector_[1]
{doNotify()}

Loading data, please wait...