Synaptic information transfer in computer models of neocortical columns (Neymotin et al. 2010)

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Accession:136095
"... We sought to measure how the activity of the network alters information flow from inputs to output patterns. Information handling by the network reflected the degree of internal connectivity. ... With greater connectivity strength, the recurrent network translated activity and information due to contribution of activity from intrinsic network dynamics. ... At still higher internal synaptic strength, the network corrupted the external information, producing a state where little external information came through. The association of increased information retrieved from the network with increased gamma power supports the notion of gamma oscillations playing a role in information processing."
Reference:
1 . Neymotin SA, Jacobs KM, Fenton AA, Lytton WW (2011) Synaptic information transfer in computer models of neocortical columns. J Comput Neurosci. 30(1):69-84 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Neocortex V1 pyramidal corticothalamic L6 cell; Neocortex V1 pyramidal intratelencephalic L2-5 cell; Neocortex V1 interneuron basket PV cell; Neocortex fast spiking (FS) interneuron; Neocortex spiny stellate cell; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron;
Channel(s): I Na,t; I A; I K;
Gap Junctions:
Receptor(s): GabaA; AMPA; NMDA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Information transfer;
Implementer(s): Lytton, William [billl at neurosim.downstate.edu]; Neymotin, Sam [samn at neurosim.downstate.edu];
Search NeuronDB for information about:  Neocortex V1 pyramidal corticothalamic L6 cell; Neocortex V1 pyramidal intratelencephalic L2-5 cell; Neocortex V1 interneuron basket PV cell; GabaA; AMPA; NMDA; I Na,t; I A; I K;
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ncdemo
readme.txt
A.mod
AMPA.mod *
AMPAr.mod
clampex.mod *
cp.mod *
cp2.mod *
field.mod
GABAa.mod
GABAar.mod
GABAb.mod
GABAbr.mod
H.mod
Iahp.mod *
Ican.mod *
IL.mod
IL3.mod *
infot.mod *
intf_.mod
intfsw.mod *
kdr2.mod *
kmbg.mod
misc.mod *
naf2.mod *
nap.mod *
NMDA.mod *
NMDAr.mod
nthh.mod *
ntIh.mod *
ntt.mod *
OFThpo.mod
OFThresh.mod
pregencv.mod
stats.mod
updown.mod *
vecst.mod
bg_cvode.inc
misc.h *
mosinit.hoc
netcon.inc *
netrand.inc
ofc.inc
                            
: $Id: Iahp.mod,v 1.8 2000/01/05 19:55:19 billl Exp $
TITLE Slow Ca-dependent potassium current
:
:   Ca++ dependent K+ current IC responsible for slow AHP
:   Differential equations
:
:   Model of Destexhe, 1992.  Based on a first order kinetic scheme
:      <closed> + n cai <-> <open>	(alpha,beta)
:   Following this model, the activation fct will be half-activated at 
:   a concentration of Cai = (beta/alpha)^(1/n) = cac (parameter)
:   The mod file is here written for the case n=2 (2 binding sites)
:   ---------------------------------------------
:
:   This current models the "slow" IK[Ca] (IAHP): 
:      - potassium current
:      - activated by intracellular calcium
:      - NOT voltage dependent
:
:   A minimal value for the time constant has been added
:
:   Written by Alain Destexhe, Salk Institute, Nov 3, 1992
:

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

NEURON {
	SUFFIX iahp
	USEION k2 WRITE ik2 VALENCE 1
	USEION Ca READ Cai VALENCE 2
	USEION ca READ cai
        RANGE gkbar, i, g, ratc, ratC, minf, taum
	GLOBAL beta, cac, m_inf, tau_m, x
}


UNITS {
	(mA) = (milliamp)
	(mV) = (millivolt)
	(molar) = (1/liter)
	(mM) = (millimolar)
}


PARAMETER {
	v		(mV)
	celsius	= 36	(degC)
	erev = -95		(mV)
	Cai 	= 5e-5	(mM)		: initial [Ca]i = 50 nM
	cai 	= 5e-5	(mM)		: initial [Ca]i = 50 nM
	gkbar	= .001	(mho/cm2)
	beta	= 2.5	(1/ms)		: backward rate constant
	cac	= 1e-4	(mM)		: middle point of activation fct
	taumin	= 1	(ms)		: minimal value of the time cst
        ratc    = 0
        ratC    = 0
        x       = 2
}


STATE {
	m
}
ASSIGNED {
	ik2 	(mA/cm2)
	i	(mA/cm2)
	g       (mho/cm2)
	m_inf
	tau_m	(ms)
	minf
        taum
	tadj
}

BREAKPOINT { 
	SOLVE states METHOD cnexp
        minf=m_inf
        taum=tau_m
	g = gkbar * m*m
	i = g * (v - erev)
	ik2  = i
}

DERIVATIVE states { 
	evaluate_fct(v,Cai,cai)

	m' = (m_inf - m) / tau_m
}

UNITSOFF
INITIAL {
:
:  activation kinetics are assumed to be at 22 deg. C
:  Q10 is assumed to be 3
:
	VERBATIM
	cai = _ion_cai;
	Cai = _ion_Cai;
	ENDVERBATIM

	tadj = 3 ^ ((celsius-22.0)/10)

	evaluate_fct(v,Cai,cai)
	m = m_inf
        minf=m_inf
        taum=tau_m
}

PROCEDURE evaluate_fct(v(mV),Cai(mM), cai(mM)) {  LOCAL car, tcar

        tcar = ratC*Cai + ratc*cai
	car = (tcar/cac)^x

	m_inf = car / ( 1 + car )
	tau_m = 1 / beta / (1 + car) / tadj

        if(tau_m < taumin) { tau_m = taumin } 	: min value of time cst
}
UNITSON

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