Mechanisms of magnetic stimulation of central nervous system neurons (Pashut et al. 2011)

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Accession:138321
Transcranial magnetic stimulation (TMS) is a widely applied tool for probing cognitive function in humans and is one of the best tools for clinical treatments and interfering with cognitive tasks. Surprisingly, while TMS has been commercially available for decades, the cellular mechanisms underlying magnetic stimulation remain unclear. Here we investigate these mechanisms using compartmental modeling. We generated a numerical scheme allowing simulation of the physiological response to magnetic stimulation of neurons with arbitrary morphologies and active properties. Computational experiments using this scheme suggested that TMS affects neurons in the central nervous system (CNS) primarily by somatic stimulation.
Reference:
1 . Pashut T, Wolfus S, Friedman A, Lavidor M, Bar-Gad I, Yeshurun Y, Korngreen A (2011) Mechanisms of magnetic stimulation of central nervous system neurons. PLoS Comput Biol 7:e1002022 [PubMed]
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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; Squid axon;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; MATLAB;
Model Concept(s): Action Potential Initiation; Magnetic stimulation;
Implementer(s): Korngreen, Alon [alon.korngreen at gmail.com]; Pashut, Tamar [tamar.pashut at gmail.com];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell;
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pashut2011
TwoDimensions
Neuron
cells
cad2.mod *
child.mod *
childa.mod *
epsp.mod *
it2.mod *
kaprox.mod *
kca.mod *
km.mod *
kv.mod *
na.mod *
SlowCa.mod *
xtra.mod *
alon.ses
BACModel.hoc
BACModel_mag.hoc
Display.ses *
magstim.hoc
                            
COMMENT

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
	gk = tadj*gbar*n
	ik = (1e-4) * gk * (v - ek)
} 

LOCAL nexp

PROCEDURE states() {   :Computes state variable n 
        rates(cai)      :             at the current v and dt.
        n = n + nexp*(ninf-n)

        VERBATIM
        return 0;
        ENDVERBATIM
}

PROCEDURE rates(cai(mM)) {  

        LOCAL tinc

        a = Ra * cai^caix
        b = Rb
        ntau = 1/(a+b)
	ninf = a*ntau

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

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