ModelDB is moving. Check out our new site at https://modeldb.science. The corresponding page is https://modeldb.science/108459.

STDP depends on dendritic synapse location (Letzkus et al. 2006)

 Download zip file 
Help downloading and running models
Accession:108459
This model was published in Letzkus, Kampa & Stuart (2006) J Neurosci 26(41):10420-9. The simulation creates several plots showing voltage and NMDA current and conductance changes at different apical dendritic locations in layer 5 pyramidal neurons during STDP induction protocols. Created by B. Kampa (2006).
Reference:
1 . Letzkus JJ, Kampa BM, Stuart GJ (2006) Learning rules for spike timing-dependent plasticity depend on dendritic synapse location. J Neurosci 26:10420-9 [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): Neocortex L5/6 pyramidal GLU cell;
Channel(s): I L high threshold; I T low threshold; I A; I M; I K,Ca; I Sodium; I Calcium; I Potassium;
Gap Junctions:
Receptor(s): NMDA;
Gene(s):
Transmitter(s): Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Dendritic Action Potentials; Bursting; Active Dendrites; Synaptic Plasticity; Long-term Synaptic Plasticity; Action Potentials; STDP; Calcium dynamics;
Implementer(s): Kampa, Bjorn M [Bjoern.Kampa at anu.edu.au];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; NMDA; I L high threshold; I T low threshold; I A; I M; I K,Ca; I Sodium; I Calcium; I Potassium; Glutamate;
//====================================================================================
//
// 	Ri18 model that includes Ih (Kole 2006) and reproduces dendritic spikes in
//	response to somatic AP burst. This version includes Schaefer et al mod files
//	and Maarten's Ih mod file and init_vm. The firing threshold was set to -63 mV
//	(Gulledge 2003). Changes to Ca channels were adopted from Schaefer et al (2003).
//	No change to it channel parameters. No slow Ca channels (HVA) were included.
//
//	Simulation plots distal NMDA conductance as in figure 8 in Letzkus (2006) 
//	J Neurosci 26(41):10420–10429.
//
//	B. Kampa, Zurich 02-04-2006
//
//=====================================================================================

// program to get geometry and initialise properties of Ri18//

xopen("Ri18geo.hoc")
xopen("Ri18organise.hoc")
xopen("Ri18init_active.hoc")

init_params()
init_spine()
init_vm() 
hexp() 
init_active_params() 
init_active() 
boost_ca()
InitDistal()
EPSPstim_time		= 1060
access dend1[21]    	/* soma*/
steps_per_ms 		= 10
dt 				= 0.1


// ==========================================
// insert synapse
// ==========================================

objref syn,dendSec
dend1[425] dendSec 	= new SectionRef() // at 800 um from soma, dend1[64] is 200 um from soma
dendSec.sec syn 		= new epsp(0.5)
syn.onset			= EPSPstim_time
syn.imax			= 0.2
syn.tau0			= 0.2
syn.tau1			= 2

xopen("insert_nmda.hoc")
PRE.del_rel 		= EPSPstim_time
syn.onset			= EPSPstim_time
xopen("menu.ses")
xopen("panel.hoc")
nmda.gmax			= 80000  //to match NMDA-AMPA ratio of 0.22 (Watts 2004) as measured in 0.05 mM Mg
dendSec.sec syn.loc(.5)
dendSec.sec nmda.loc(.5)
steps_per_ms 		= 1
dt 				= 0.1
access dend1[21]
distance()
xopen("init.hoc")
print "Ri18 successfully built\n"




Loading data, please wait...