Multiscale simulation of the striatal medium spiny neuron (Mattioni & Le Novere 2013)

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Accession:150284
"… We present a new event-driven algorithm to synchronize different neuronal models, which decreases computational time and avoids superfluous synchronizations. The algorithm is implemented in the TimeScales framework. We demonstrate its use by simulating a new multiscale model of the Medium Spiny Neuron of the Neostriatum. The model comprises over a thousand dendritic spines, where the electrical model interacts with the respective instances of a biochemical model. Our results show that a multiscale model is able to exhibit changes of synaptic plasticity as a result of the interaction between electrical and biochemical signaling. …"
Reference:
1 . Mattioni M, Le Novère N (2013) Integration of biochemical and electrical signaling-multiscale model of the medium spiny neuron of the striatum. PLoS One 8:e66811 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Synapse;
Brain Region(s)/Organism: Striatum;
Cell Type(s): Neostriatum medium spiny direct pathway neuron;
Channel(s): I Na,p; I Na,t; I T low threshold; I A; I K,Ca; I CAN; I Calcium; I A, slow; I Krp; I R; I Q;
Gap Junctions:
Receptor(s):
Gene(s): Kv4.2 KCND2; Kv1.2 KCNA2; Cav1.3 CACNA1D; Cav1.2 CACNA1C; Kv2.1 KCNB1;
Transmitter(s):
Simulation Environment: NEURON; Python;
Model Concept(s): Synaptic Plasticity; Signaling pathways; Calcium dynamics; Multiscale;
Implementer(s): Mattioni, Michele [mattioni at ebi.ac.uk];
Search NeuronDB for information about:  Neostriatum medium spiny direct pathway neuron; I Na,p; I Na,t; I T low threshold; I A; I K,Ca; I CAN; I Calcium; I A, slow; I Krp; I R; I Q;
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TimeScales-master
mod
AMPA.mod
bkkca.mod *
cadyn.mod
caL.mod *
caL13.mod *
caldyn.mod
caltrack.mod
can.mod *
caq.mod *
car.mod *
cat.mod *
catrack.mod
GABA.mod *
kaf.mod *
kas.mod *
kir.mod *
krp.mod *
naf.mod *
nap.mod *
NMDA.mod
rubin.mod
skkca.mod
stim.mod *
vecevent.mod
test_input.py
test_vecstim.py
                            
TITLE Kir potassium current for nucleus accumbens (IRK1 = Kir 2.1 - see Mermelstein)

COMMENT 

Mermelstein PG, Song WJ, Tkatch T, Yan Z, Surmeier DJ (1998) Inwardly
rectifying potassium (IRK) currents are correlated with IRK subunit
expression in rat nucleus accumbens medium spiny neurons. J Neurosci
18:6650-6661.

Uchimura N, Cherubini E, North RA (1989).  Inward rectification
in rat nucleus accumbens neurons. J Neurophysiol 62, 1280-1286.

Kubo Y, Murata Y (2001).  Control of rectification and permeation by two
distinct sites after the second transmembrane region in Kir2.1 K+
channel. J Physiol 531, 645-660.

Hayashi H, Fishman HM (1988). Inward rectifier K+ channel kinetics from
analysis of the complex conductance of aplysia neuronal membrane.
Biophys J 53, 747-757. 

Jason Moyer 2004 jtmoyer@seas.upenn.edu
ENDCOMMENT


UNITS {
        (mA) = (milliamp)
        (mV) = (millivolt)
        (S)  = (siemens)
        (molar) = (1/liter)
        (mM) = (millimolar)
}
 
NEURON {
        SUFFIX kir
        USEION k READ ek WRITE ik
        RANGE  gkbar, ik, mvhalf, mslope, mshift, qfact
}
 
PARAMETER {
	gkbar  = 0.00015 		(S/cm2)	: 

	mvhalf = -52		(mV)	: fit to Hayashi 1988 fig 14; minf = alpha/(alpha+beta)
	mslope = 13		(mV)	: fit to Hayashi 1988 fig 14
	mshift = 30			(mV)	: fit to Kubo 2001 fig 2B left - with ek = -84.3,
						:  mshift can range from 20 to 30 to fit slope of IR
	qfact = 0.5				: match in vitro data
}
 
STATE { m }
 
ASSIGNED {
		ki				(mM)
		ko				(mM)
        v 				(mV)
        ik 				(mA/cm2)
        gk				(S/cm2)
        minf		
        ek				(mV)
   }
 
BREAKPOINT {
        SOLVE state METHOD cnexp
        gk = gkbar * m
        ik = gk * ( v - ek )
}
  
INITIAL {
	rates(v)
	m = minf
}

FUNCTION_TABLE taumkir (v(mV))  (ms)		: Hayashi

DERIVATIVE state { 
        rates(v)
        m' = (minf - m) / ( taumkir(v)/qfact )
}
 
PROCEDURE rates( v(mV) ) {  : Boltzman adjusted to give proper Erev dependency 
	TABLE minf DEPEND mvhalf, mshift, mslope
		FROM -200 TO 200 WITH 201
			minf = 1  /  ( 1 + exp( (v - mvhalf + mshift) / mslope) )
}
 
 

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