A 1000 cell network model for Lateral Amygdala (Kim et al. 2013)

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Accession:150288
1000 Cell Lateral Amygdala model for investigation of plasticity and memory storage during Pavlovian Conditioning.
Reference:
1 . Kim D, Paré D, Nair SS (2013) Mechanisms contributing to the induction and storage of Pavlovian fear memories in the lateral amygdala. Learn Mem 20:421-30 [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; Dendrite;
Brain Region(s)/Organism: Amygdala;
Cell Type(s): Hippocampus CA1 pyramidal GLU cell; Hippocampus CA3 pyramidal GLU cell; Hodgkin-Huxley neuron;
Channel(s): I Na,t; I L high threshold; I A; I M; I Sodium; I Calcium; I Potassium; I_AHP; Ca pump;
Gap Junctions:
Receptor(s): AMPA; NMDA; Gaba; Dopaminergic Receptor;
Gene(s):
Transmitter(s): Dopamine; Norephinephrine;
Simulation Environment: NEURON;
Model Concept(s): Synaptic Plasticity; Short-term Synaptic Plasticity; Long-term Synaptic Plasticity; Learning; Neuromodulation;
Implementer(s): Kim, Dongbeom [dk258 at mail.missouri.edu];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; Hippocampus CA3 pyramidal GLU cell; AMPA; NMDA; Gaba; Dopaminergic Receptor; I Na,t; I L high threshold; I A; I M; I Sodium; I Calcium; I Potassium; I_AHP; Ca pump; Dopamine; Norephinephrine;
/
KimEtAl2013
README.txt
bg2inter.mod
bg2pyr.mod
ca.mod *
cadyn.mod
cal2.mod *
capool.mod *
function_TMonitor.mod *
h.mod *
im.mod
interD2pyrD_STFD.mod
interD2pyrDDA_STFD.mod
interD2pyrDDANE_STFD.mod
interD2pyrDNE_STFD.mod
interD2pyrV_STFD.mod
interD2pyrVDA_STFD.mod
interV2pyrD_STFD.mod
interV2pyrDDA_STFD.mod
interV2pyrDDANE_STFD.mod
interV2pyrDNE_STFD.mod
interV2pyrV_STFD.mod
interV2pyrVDA_STFD.mod
kadist.mod *
kaprox.mod
kdrca1.mod
kdrca1DA.mod
kdrinter.mod *
leak.mod *
leakDA.mod *
leakinter.mod *
na3.mod
na3DA.mod
nainter.mod *
pyrD2interD_STFD.mod
pyrD2interV_STFD.mod
pyrD2pyrD_STFD.mod
pyrD2pyrDDA_STFD.mod
pyrD2pyrV_STFD.mod
pyrD2pyrVDA_STFD.mod
pyrV2interD_STFD.mod
pyrV2interV_STFD.mod
pyrV2pyrD_STFD.mod
pyrV2pyrDDA_STFD.mod
pyrV2pyrV_STFD.mod
pyrV2pyrVDA_STFD.mod
sahp.mod
sahpNE.mod
shock2interD.mod
shock2interV.mod
shock2pyrD.mod
shock2pyrV.mod
tone2interD.mod
tone2interDNE.mod
tone2interV.mod
tone2interVNE.mod
tone2pyrD.mod
tone2pyrD_LAdv.mod
tone2pyrDNE.mod
tone2pyrDNE_LAdv.mod
tone2pyrV.mod
tone2pyrV_LAdd.mod
tone2pyrVNE.mod
tone2pyrVNE_LAdd.mod
BgGen.hoc
Cell_list.txt
Cell_type.txt
function_ConnectInternal.hoc
function_ConnectTwoCells.hoc
function_NetStimOR.hoc *
function_TimeMonitor.hoc *
function_ToneGen.hoc
function_ToneSignalGen_Ctx.hoc
function_ToneSignalGen_Th.hoc
interneuron_template.hoc
LA_model_main_file.hoc
LAcells_template.hoc
NM.txt
shock2Idd.txt
shock2Idv.txt
shock2LAdd.txt
shock2LAdv.txt
shockcondi.hoc
Syn_Matrix.txt
tone2Idd.txt
tone2Idd2.txt
tone2Idv.txt
tone2Idv2.txt
tone2LAdd.txt
tone2LAdd2.txt
tone2LAdv.txt
tone2LAdv2.txt
                            
: spike-generating sodium channel (interneuron)

NEURON {
	SUFFIX nainter
	USEION na READ ena WRITE ina
	RANGE gnabar, ina, gnaer
	RANGE minf, hinf, mtau, htau
}

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

PARAMETER {
	v (mV)
	dt (ms)
	gnabar = 0.035 (mho/cm2) <0,1e9>
	ena = 45 (mV)
}

STATE {
	m h
}

ASSIGNED {
	ina (mA/cm2)
	minf hinf 
	mtau (ms)
	htau (ms)
	gna (mho/cm2)
}

INITIAL {
	rate(v)
	m = minf
	h = hinf
}

BREAKPOINT {
	SOLVE states METHOD cnexp
	gna = gnabar*m*m*m*h
	ina = gna*(v-ena)
}

DERIVATIVE states {
	rate(v)
	m' = (minf-m)/mtau
	h' = (hinf-h)/htau
}

UNITSOFF

FUNCTION malf(v(mV)) {
	malf = 2.1*exp((v+18.5)/11.75)   :malf = 2.1*exp((v+18.5)/11.57)
}

FUNCTION mbet(v(mV)) {
	mbet = 2.1*exp(-(v+18.5)/27)
}	

FUNCTION half(v(mV)) {
	half = 0.045*exp(-(v+29)/33)
}

FUNCTION hbet(v(mV)) {
	hbet = 0.045*exp((v+29)/12.2)
}

PROCEDURE rate(v(mV)) { LOCAL msum, hsum, ma, mb, ha, hb

	ma = malf(v) mb = mbet(v) ha = half(v) hb = hbet(v)
	
	msum = ma+mb
	minf = ma/msum
	mtau = 1/(msum)
	
	hsum = ha+hb
	hinf = ha/hsum
	htau = 1/(hsum)
}

UNITSON

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