LTP in cerebellar mossy fiber-granule cell synapses (Saftenku 2002)

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Accession:51196
We simulated synaptic transmission and modified a simple model of long-term potentiation (LTP) and long-term depression (LTD) in order to describe long-term plasticity related changes in cerebellar mossy fiber-granule cell synapses. In our model, protein autophosphorylation, leading to the maintenance of long-term plasticity, is controlled by Ca2+ entry through the NMDA receptor channels. The observed nonlinearity in the development of long-term changes of EPSP in granule cells is explained by the difference in the rate constants of two independent autocatalytic processes.
Reference:
1 . Saftenku EE (2002) A simplified model of long-term plasticity in cerebellar mossy fiber-granule cell synapses. Neurophysiology/Neirofiziologiya 34:216-218
Model Information (Click on a link to find other models with that property)
Model Type: Synapse;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s): AMPA; NMDA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Simplified Models; Long-term Synaptic Plasticity; Maintenance;
Implementer(s): Saftenku, Elena [esaft at biph.kiev.ua];
Search NeuronDB for information about:  AMPA; NMDA;
// Lester and Jahr (1992) kinetic scheme of NMDA receptors

objref NMDAMenu
NMDAMenu = new VBox()
NMDAMenu.intercept(1)

Nmda_C1C2=GrCell[0].nmda[0].cnm_4_3
Nmda_C2C1= GrCell[0].nmda[0].cnm_3_4
Nmda_C2C3= GrCell[0].nmda[0].cnm_3_2
Nmda_C3C2= GrCell[0].nmda[0].cnm_2_3
Nmda_C3O= GrCell[0].nmda[0].cnm_2_1
Nmda_OC3= GrCell[0].nmda[0].cnm_1_2
Nmda_C3D= GrCell[0].nmda[0].cnm_2_5
Nmda_DC3= GrCell[0].nmda[0].cnm_5_2
Nmda_Gmax2= GrCell[0].nmda[0].gbarnmda
Nmda_v02= GrCell[0].nmda[0].v0_block
Nmda_alpha= GrCell[0].nmda[0].alpha_vspom
Nmda_Erev= GrCell[0].nmda[0].Erev
xpanel("1")
xlabel("NMDA")
xvalue("C1C2 (ms^-1 uM^1)","Nmda_C1C2",1,"UpDateNMDA()", 0, 0 )
xvalue("C2C1 (ms^-1)","Nmda_C2C1",1,"UpDateNMDA()", 0, 0 )
xvalue("C2C3 (ms^-1 uM^1)","Nmda_C2C3",1,"UpDateNMDA()", 0, 0 )
xvalue("C3C2 (ms^-1)","Nmda_C3C2",1,"UpDateNMDA()", 0, 0 )
xvalue("C3O (ms^-1)","Nmda_C3O",1,"UpDateNMDA()", 0, 0 )
xvalue("OC3 (ms^-1)","Nmda_OC3",1,"UpDateNMDA()", 0, 0 )
xvalue("C3D (ms^-1)","Nmda_C3D",1,"UpDateNMDA()", 0, 0 )
xvalue("DC3 (ms^-1)","Nmda_DC3",1,"UpDateNMDA()", 0, 0 )
xvalue("Gmax2 (pS)","Nmda_Gmax", 1,"UpDateNMDA()", 0, 0 )
xvalue("V0 Block (mV)","Nmda_v02", 1,"UpDateNMDA()", 0, 0 )
xvalue("Alpha Block (mV)","Nmda_alpha", 1,"UpDateNMDA()", 0, 0 )
xvalue("Erev (mV)","Nmda_Erev", 1,"UpDateNMDA()", 0, 0 )
xpanel()

NMDAMenu.intercept(0)
NMDAMenu.map("NMDA model")

proc UpDateNMDA(){
	for (i=0;i<=3;i=i+1) {
GrCell[0].nmda[i].cnm_4_3= Nmda_C1C2
GrCell[0].nmda[i].cnm_3_4= Nmda_C2C1
GrCell[0].nmda[i].cnm_3_2= Nmda_C2C3
GrCell[0].nmda[i].cnm_2_3= Nmda_C3C2
GrCell[0].nmda[i].cnm_2_1= Nmda_C3O 
GrCell[0].nmda[i].cnm_1_2= Nmda_OC3
GrCell[0].nmda[i].cnm_2_5= Nmda_C3D 
GrCell[0].nmda[i].cnm_5_2= Nmda_DC3
GrCell[0].nmda[i].gbarnmda= Nmda_Gmax2
GrCell[0].nmda[i].v0_block= Nmda_v02
GrCell[0].nmda[i].alpha_vspom= Nmda_alpha 
GrCell[0].nmda[i].Erev= Nmda_Erev 
}
}	


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