Parametric computation and persistent gamma in a cortical model (Chambers et al. 2012)

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Accession:144579
Using the Traub et al (2005) model of the cortex we determined how 33 synaptic strength parameters control gamma oscillations. We used fractional factorial design to reduce the number of runs required to 4096. We found an expected multiplicative interaction between parameters.
Reference:
1 . Chambers JD, Bethwaite B, Diamond NT, Peachey T, Abramson D, Petrou S, Thomas EA (2012) Parametric computation predicts a multiplicative interaction between synaptic strength parameters that control gamma oscillations. Front Comput Neurosci 6:53 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Axon; Synapse; Channel/Receptor; Dendrite;
Brain Region(s)/Organism:
Cell Type(s): Neocortex L5/6 pyramidal GLU cell; Neocortex L2/3 pyramidal GLU cell; Neocortex V1 interneuron basket PV GABA cell; Neocortex fast spiking (FS) interneuron; Neocortex spiny stellate cell; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron;
Channel(s): I A; I K; I K,leak; I K,Ca; I Calcium; I_K,Na;
Gap Junctions: Gap junctions;
Receptor(s): GabaA; AMPA; NMDA;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Oscillations; Parameter sensitivity;
Implementer(s): Thomas, Evan [evan at evan-thomas.net]; Chambers, Jordan [jordandchambers at gmail.com];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; Neocortex L2/3 pyramidal GLU cell; Neocortex V1 interneuron basket PV GABA cell; GabaA; AMPA; NMDA; I A; I K; I K,leak; I K,Ca; I Calcium; I_K,Na; Gaba; Glutamate;
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FRBGamma
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TITLE Sodium transient current for RD Traub et al 2003, 2005

COMMENT

	Implemented by Maciej Lazarewicz 2003 (mlazarew@seas.upenn.edu)
	fastNashift init to 0 and removed from arg modification Tom Morse 3/8/2006
	(for Traub et al 2005)
	Also further changed to match naf in tcr.
ENDCOMMENT

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

UNITS { 
	(mV) = (millivolt) 
	(mA) = (milliamp) 
} 
NEURON { 
	SUFFIX naf_tcr
	USEION na READ ena WRITE ina
	RANGE gbar, ina,m, h, df, shift_mnaf, minf, mtau
	RANGE shift_hnaf, shift_mnaf_init, shift_mnaf_run, hinf, htau
	RANGE shift_hnaf_run
}
PARAMETER { 
	shift_mnaf_init =-3 (mV) : these two variable names suggest where they came from
	shift_mnaf_run = -2.5 (mV) : in the fortran code
	shift_hnaf = -7.0 (mV)
	gbar = 0.0 	   (mho/cm2)
	v (mV) ena 		   (mV)  
} 
ASSIGNED { 
	shift_mnaf (mV)
	ina 		   (mA/cm2) 
	minf (1)
	hinf (1)
	mtau (ms)
	htau (ms)
	df (mV)
} 
STATE {
	m h
}
BREAKPOINT { 
	SOLVE states METHOD cnexp
	ina = gbar * m * m * m * h * ( v - ena ) 
	df = v - ena
}
INITIAL { 
	settables( v )
	m = minf
	m = 0
	h  = hinf
} 
DERIVATIVE states { 
	settables( v ) 
	m' = ( minf - m ) / mtau 
	h' = ( hinf - h ) / htau
}

UNITSOFF 

PROCEDURE settables(v1(mV)) {

	TABLE minf, hinf, mtau, htau  FROM -120 TO 40 WITH 641

	shift_mnaf = shift_mnaf_init + shift_mnaf_run
	minf  = 1 / ( 1 + exp( ( - ( v1 + shift_mnaf ) - 38 ) / 10 ) )
	if( ( v1 + shift_mnaf ) < -30.0 ) {
		mtau = 0.025 + 0.14 * exp( ( ( v1 + shift_mnaf ) + 30 ) / 10 )
	} else{
		mtau = 0.02 + (0.145) * exp( ( - ( v1 + shift_mnaf ) - 30 ) / 10 ) 
	}

	: hinf, and htau are shifted 3.5 mV comparing to the paper

	hinf  = 1.0 / ( 1.0 + exp( ( v1 + shift_hnaf + 62.9 ) / 10.7 ) )
	htau = 0.15 + 1.15 / ( 1.0 + exp( ( v1 + 37.0 ) / 15.0 ) )
}

UNITSON

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