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
                            
COMMENT
26 Ago 2002 Modification of original channel to allow variable time step and to correct an initialization error.
    Done by Michael Hines(michael.hines@yale.e) and Ruggero Scorcioni(rscorcio@gmu.edu) at EU Advance Course in Computational Neuroscience. Obidos, Portugal

kca.mod

Calcium-dependent potassium channel
Based on
Pennefather (1990) -- sympathetic ganglion cells
taken from
Reuveni et al (1993) -- neocortical cells

Author: Zach Mainen, Salk Institute, 1995, zach@salk.edu
	
ENDCOMMENT

INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}

NEURON {
	SUFFIX kca
	USEION k READ ek WRITE ik
	USEION ca READ cai
	RANGE n, gk, gbar
	RANGE ninf, ntau
	GLOBAL Ra, Rb, caix
	GLOBAL q10, temp, tadj, vmin, vmax
}

UNITS {
	(mA) = (milliamp)
	(mV) = (millivolt)
	(pS) = (picosiemens)
	(um) = (micron)
} 

PARAMETER {
	gbar = 10   	(pS/um2)	: 0.03 mho/cm2
	v 		(mV)
	cai  		(mM)
	caix = 1	
									
	Ra   = 0.01	(/ms)		: max act rate  
	Rb   = 0.02	(/ms)		: max deact rate 

	dt		(ms)
	celsius		(degC)
	temp = 23	(degC)		: original temp 	
	q10  = 2.3			: temperature sensitivity

	vmin = -120	(mV)
	vmax = 100	(mV)
} 


ASSIGNED {
	a		(/ms)
	b		(/ms)
	ik 		(mA/cm2)
	gk		(pS/um2)
	ek		(mV)
	ninf
	ntau 		(ms)	
	tadj
}
 

STATE { n }

INITIAL { 
	rates(cai)
	n = ninf
}

BREAKPOINT {
        SOLVE states METHOD cnexp
	gk = tadj*gbar*n
	ik = (1e-4) * gk * (v - ek)
} 

LOCAL nexp

DERIVATIVE states {   :Computes state variable n 
        rates(cai)      :             at the current v and dt.
        n' =  (ninf-n)/ntau

}

PROCEDURE rates(cai(mM)) {  

        

        a = Ra * cai^caix
        b = Rb

        tadj = q10^((celsius - temp)/10)

        ntau = 1/tadj/(a+b)
	ninf = a/(a+b)

 
:        tinc = -dt * tadj
:        nexp = 1 - exp(tinc/ntau)
}