Cortical pyramidal neuron, phase response curve (Stiefel et al 2009)

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Accession:144372
Three models of increasing complexity all showing a switch from type II (biphasic) to type I (monophasic) phase response curves with a cholinergic down-modulation of K+ conductances.
Reference:
1 . Stiefel KM, Gutkin BS, Sejnowski TJ (2009) The effects of cholinergic neuromodulation on neuronal phase-response curves of modeled cortical neurons. J Comput Neurosci 26:289-301 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type:
Brain Region(s)/Organism:
Cell Type(s): Neocortex L2/3 pyramidal GLU cell;
Channel(s): I Na,p; I Na,t; I M;
Gap Junctions:
Receptor(s): Muscarinic;
Gene(s):
Transmitter(s): Acetylcholine;
Simulation Environment: NEURON;
Model Concept(s): Action Potentials;
Implementer(s): Stiefel, Klaus [stiefel at salk.edu];
Search NeuronDB for information about:  Neocortex L2/3 pyramidal GLU cell; Muscarinic; I Na,p; I Na,t; I M; Acetylcholine;
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StiefelEtAl2009
README.txt
ca.mod *
cacum.mod
cad.mod *
H.mod
iahp2.mod *
il.mod *
im.mod *
KA.mod
kca.mod *
Kdr.mod
km.mod *
Ks.mod
kv.mod *
Na.mod *
NaP.mod
cell.ses
displayshape.hoc
fig4A.hoc
fig4A_new.hoc
fig5A.hoc
fig5B.hoc
fig5C.hoc
gui.hoc
j8.hoc *
ksprc.ses
makeIF.hoc
multi.hoc
PRC.hoc
PRCsweep.hoc
PY-golomb_original.hoc
PY-golomb_plus.hoc
PY-golomb_simple.hoc
PyMainen.hoc
single.hoc
single_plus.hoc
single1.ses
surface.hoc
synproxy_cch.hoc
synproxy_sweeps.hoc
                            
// Single compartment neuron in NEURON
// K.Stiefel, Salk, 2004

// NEURON standard files, soma

load_file("stdgui.hoc")
load_file("nrngui.hoc")

nrnmainmenu()

load_file("PyMainen.hoc")

// changes in Mainen's parameters

forsec dendritic {
		gbar_km	= 2
		g_pas	= 2e-5
		e_pas = -60		
		gbar_ca= .1				
		gbar_na = 20
		gbar_kca = 3	
//		nseg = int(L/8)+1
		}
	
soma { 		gkv = 100 }

objref spikesin[4], input, spikesout, nix
objref spikesouttimes, synapse[4], Iinject

soma synapse[0] = new ExpSyn(.5)
a2_1211 synapse[1] = new ExpSyn(.5)
// a2_121121 synapse[2] = new ExpSyn(.5)
// a2_1211212
a2_12112122 synapse[2] = new ExpSyn(.5)
a3_12122221 synapse[3] = new ExpSyn(.5)
for y = 0, 3 { synapse[y].tau=0.01 }

input = new NetStim(.5)
input.number=1
input.start=10000

for w = 0, 3 {spikesin[w] = new NetCon(input, synapse[w], 0.5, 0, 0 ) }
spikesin[0].weight = 0
spikesin[1].weight = 0
spikesin[2].weight = 0
spikesin[3].weight = 0

soma spikesout = new NetCon(&v(.5), nix, 0, 0, 0)// Output spike train
spikesouttimes = new Vector()
spikesout.record(spikesouttimes)

// load_file("single1.ses")// display

// comment out from here on
// to get the theta neuron only 
// without PRC determination
// -----------------------------
load_file("displayshape.hoc")
load_file("makeIF.hoc") // current vs firing rate curve
load_file("PRC.hoc") // determine phase reset curves
// load_file("synproxy_cch.hoc") 
// load_file("synproxy_sweeps.hoc")
// load_file("fig5A.hoc") // uniform gm change, 3 synapse locations, PRC
// load_file("fig5C.hoc") // gm change in a spot, 3 synapse locations, PRCs
// load_file("surface.hoc")