ModelDB is moving. Check out our new site at https://modeldb.science. The corresponding page is https://modeldb.science/185858.

Ca+/HCN channel-dependent persistent activity in multiscale model of neocortex (Neymotin et al 2016)

 Download zip file 
Help downloading and running models
Accession:185858
"Neuronal persistent activity has been primarily assessed in terms of electrical mechanisms, without attention to the complex array of molecular events that also control cell excitability. We developed a multiscale neocortical model proceeding from the molecular to the network level to assess the contributions of calcium regulation of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels in providing additional and complementary support of continuing activation in the network. ..."
Reference:
1 . Neymotin SA, McDougal RA, Bulanova AS, Zeki M, Lakatos P, Terman D, Hines ML, Lytton WW (2016) Calcium regulation of HCN channels supports persistent activity in a multiscale model of neocortex. Neuroscience 316:344-66 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell; Synapse; Channel/Receptor; Molecular Network;
Brain Region(s)/Organism: Neocortex;
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 spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron; Neocortex layer 2-3 interneuron; Neocortex layer 5 interneuron; Neocortex layer 6a interneuron;
Channel(s): I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca; I CAN; I Calcium; I_AHP; I_KD; Ca pump;
Gap Junctions:
Receptor(s): mGluR1; GabaA; GabaB; AMPA; NMDA; mGluR; Glutamate; Gaba; IP3;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Ion Channel Kinetics; Oscillations; Spatio-temporal Activity Patterns; Signaling pathways; Working memory; Attractor Neural Network; Calcium dynamics; Laminar Connectivity; G-protein coupled; Rebound firing; Brain Rhythms; Dendritic Bistability; Reaction-diffusion; Beta oscillations; Persistent activity; Multiscale;
Implementer(s): Neymotin, Sam [Samuel.Neymotin at nki.rfmh.org]; McDougal, Robert [robert.mcdougal at yale.edu];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; Neocortex L2/3 pyramidal GLU cell; Neocortex V1 interneuron basket PV GABA cell; mGluR1; GabaA; GabaB; AMPA; NMDA; mGluR; Glutamate; Gaba; IP3; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca; I CAN; I Calcium; I_AHP; I_KD; Ca pump; Gaba; Glutamate;
/
CaHDemo
readme.html
cagk.mod
cal.mod *
calts.mod *
can.mod *
cat.mod *
gabab.mod *
IC.mod *
icalts.mod *
Ih.mod
ihlts.mod *
IKM.mod *
kap.mod
kcalts.mod *
kdmc.mod
kdr.mod
kdrbwb.mod
km.mod *
mglur.mod *
misc.mod
MyExp2SynBB.mod *
MyExp2SynNMDABB.mod
nafbwb.mod
nax.mod
vecst.mod *
aux_fun.inc *
conf.py
declist.hoc *
decnqs.hoc *
decvec.hoc *
default.hoc *
drline.hoc *
geom.py
ghk.inc *
grvec.hoc
init.hoc
labels.hoc
labels.py *
local.hoc *
misc.h
mpisim.py
netcfg.cfg
nqs.hoc
nqs.py
nrnoc.hoc *
onepyr.cfg
onepyr.py
pyinit.py *
python.hoc *
pywrap.hoc *
screenshot.png
screenshot1.png
simctrl.hoc *
simdat.py
syncode.hoc *
xgetargs.hoc *
                            
TITLE Cortical M current
:
:   M-current, responsible for the adaptation of firing rate and the 
:   afterhyperpolarization (AHP) of cortical pyramidal cells
:
:   First-order model described by hodgkin-Hyxley like equations.
:   K+ current, activated by depolarization, noninactivating.
:
:   Model taken from Yamada, W.M., Koch, C. and Adams, P.R.  Multiple 
:   channels and calcium dynamics.  In: Methods in Neuronal Modeling, 
:   edited by C. Koch and I. Segev, MIT press, 1989, p 97-134.
:
:   See also: McCormick, D.A., Wang, Z. and Huguenard, J. Neurotransmitter 
:   control of neocortical neuronal activity and excitability. 
:   Cerebral Cortex 3: 387-398, 1993.
:
:   Written by Alain Destexhe, Laval University, 1995
:

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

NEURON {
	SUFFIX im
	USEION k READ ek WRITE ik
        RANGE gkbar, m_inf, tau_m
	GLOBAL taumax

}

UNITS {
	(mA) = (milliamp)
	(mV) = (millivolt)
}


PARAMETER {
	v		(mV)
	celsius = 36    (degC)
	ek		(mV)
	gkbar	= 1e-6	(mho/cm2)
	taumax	= 1000	(ms)		: peak value of tau
}



STATE {
	m
}

ASSIGNED {
	ik	(mA/cm2)
	m_inf
	tau_m	(ms)
	tau_peak	(ms)
	tadj
}

BREAKPOINT {
	SOLVE states METHOD cnexp
	ik = gkbar * m * (v - ek)
}

DERIVATIVE states { 
	evaluate_fct(v)

	m' = (m_inf - m) / tau_m
}

UNITSOFF
INITIAL {
	evaluate_fct(v)
	m = 0
:
:  The Q10 value is assumed to be 2.3
:
        tadj = 2.3 ^ ((celsius-36)/10)
	tau_peak = taumax / tadj
}

PROCEDURE evaluate_fct(v(mV)) {

	m_inf = 1 / ( 1 + exptable(-(v+35)/10) )
	tau_m = tau_peak / ( 3.3 * exptable((v+35)/20) + exptable(-(v+35)/20) )
}
UNITSON


FUNCTION exptable(x) { 
	TABLE  FROM -25 TO 25 WITH 10000

	if ((x > -25) && (x < 25)) {
		exptable = exp(x)
	} else {
		exptable = 0.
	}
}

Loading data, please wait...