L5 pyr. cell spiking control by oscillatory inhibition in distal apical dendrites (Li et al 2013)

 Download zip file   Auto-launch 
Help downloading and running models
Accession:150538
This model examined how distal oscillatory inhibition influences the firing of a biophysically-detailed layer 5 pyramidal neuron model.
Reference:
1 . Li X, Morita K, Robinson HP, Small M (2013) Control of layer 5 pyramidal cell spiking by oscillatory inhibition in the distal apical dendrites: a computational modelling study. J Neurophysiol 109(11):2739-2756 [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: Neocortex;
Cell Type(s):
Channel(s): I K,Ca; I Na, leak;
Gap Junctions:
Receptor(s): AMPA;
Gene(s):
Transmitter(s): Dopamine;
Simulation Environment: NEURON; MATLAB;
Model Concept(s): Intrinsic plasticity;
Implementer(s): Moradi, Keivan [k.moradi at gmail.com]; Robinson, H.P.C. [hpcr at cam.ac.uk]; Small, Michael ; Li, Xiumin ;
Search NeuronDB for information about:  AMPA; I K,Ca; I Na, leak; Dopamine;
/
XiEtal2013
Codes for periodic inhibition
ReadMe.txt
cad2.mod
GABABsyn.mod
h.mod
kca.mod *
km.mod *
kv.mod *
na.mod *
NMDAr.mod
SlowCa.mod *
basal_soma_periodicgaba_stimulus.hoc
basal_soma_Poissongaba_stimulus.hoc
distal_distributed_periodic_gaba_stimulus.hoc
distal_distributed_periodic_gaba+gabab_stimulus.hoc
distal_distributed_Poisson_gaba_stimulus.hoc
distal_distributed_Poisson_GABAb_stimulus.hoc
j4a.hoc *
mainfile_stim_cyc.hoc
mosinit.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

km.mod

Potassium channel, Hodgkin-Huxley style kinetics
Based on I-M (muscarinic K channel)
Slow, noninactivating

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

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

NEURON {
	SUFFIX km
	USEION k READ ek WRITE ik
	RANGE n, gk, gbar
	RANGE ninf, ntau
	GLOBAL Ra, Rb
	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)
								
	tha  = -30	(mV)		: v 1/2 for inf
	qa   = 9	(mV)		: inf slope		
	
	Ra   = 0.001	(/ms)		: max act rate  (slow)
	Rb   = 0.001	(/ms)		: max deact rate  (slow)

	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 { 
	trates(v)
	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 
        trates(v)      :             at the current v and dt.
        n' = (ninf-n)/ntau

}

PROCEDURE trates(v) {  :Computes rate and other constants at current v.
                      :Call once from HOC to initialize inf at resting v.
        
        TABLE ninf, ntau
	DEPEND  celsius, temp, Ra, Rb, tha, qa
	
	FROM vmin TO vmax WITH 199

	rates(v): not consistently executed from here if usetable_hh == 1


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


PROCEDURE rates(v) {  :Computes rate and other constants at current v.
                      :Call once from HOC to initialize inf at resting v.

        a = Ra * (v - tha) / (1 - exp(-(v - tha)/qa))
        b = -Rb * (v - tha) / (1 - exp((v - tha)/qa))

        tadj = q10^((celsius - temp)/10)
        ntau = 1/tadj/(a+b)
	ninf = a/(a+b)
}


Loading data, please wait...