Gamma genesis in the basolateral amygdala (Feng et al 2019)

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Accession:247968
Using in vitro and in vivo data we develop the first large-scale biophysically and anatomically realistic model of the basolateral amygdala nucleus (BL), which reproduces the dynamics of the in vivo local field potential (LFP). Significantly, it predicts that BL intrinsically generates the transient gamma oscillations observed in vivo. The model permitted exploration of the poorly understood synaptic mechanisms underlying gamma genesis in BL, and the model's ability to compute LFPs at arbitrary numbers of recording sites provided insights into the characteristics of the spatial properties of gamma bursts. Furthermore, we show how gamma synchronizes principal cells to overcome their low firing rates while simultaneously promoting competition, potentially impacting their afferent selectivity and efferent drive, and thus emotional behavior.
Reference:
1 . Feng F, Headley DB , Amir A, Kanta V, Chen Z, Pare D, Nair S (2019) Gamma oscillations in the basolateral amygdala: biophysical mechanisms and computational consequences eNeuro
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Extracellular; Synapse; Dendrite; Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Amygdala;
Cell Type(s): 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; I h; I Na,p; I K;
Gap Junctions: Gap junctions;
Receptor(s): AMPA; NMDA; Gaba; Dopaminergic Receptor;
Gene(s):
Transmitter(s): Dopamine; Norephinephrine;
Simulation Environment: NEURON;
Model Concept(s): Oscillations; Gamma oscillations; Short-term Synaptic Plasticity;
Implementer(s): Feng, Feng [ffvxb at mail.missouri.edu];
Search NeuronDB for information about:  AMPA; NMDA; Gaba; Dopaminergic Receptor; I Na,p; I Na,t; I L high threshold; I A; I K; I M; I h; I Sodium; I Calcium; I Potassium; I_AHP; Ca pump; Dopamine; Norephinephrine;
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FengEtAl2019
input
LFPs
volts
readme.txt
bg2pyr.mod
ca.mod *
cadyn.mod *
cal2.mod *
capool.mod
function_TMonitor.mod *
gap.mod *
Gfluct_new_exc.mod
Gfluct_new_inh.mod
h.mod *
halfgap.mod
im.mod *
interD2interD_STFD_new.mod
interD2pyrD_STFD_new.mod
kadist.mod
kaprox.mod *
kdrca1.mod *
kdrca1DA.mod *
kdrinter.mod *
leak.mod *
leakDA.mod *
leakinter.mod *
na3.mod *
na3DA.mod *
nainter.mod *
nap.mod *
nat.mod *
pyrD2interD_STFD.mod
pyrD2pyrD_STFD_new.mod
sahp.mod *
sahpNE.mod *
vecevent.mod
xtra.mod
xtra_imemrec.mod
BL_main.hoc
BLcells_template_LFP_segconsider_all_Iinject_recordingimembrane.hoc
function_calcconduc.hoc
function_ConnectInputs_invivo_op.hoc
function_ConnectInternal_gj_simplify.hoc
function_ConnectInternal_simplify_online_op.hoc
function_ConnectTwoCells.hoc
function_LoadMatrix.hoc
function_NetStimOR.hoc *
function_TimeMonitor.hoc *
interneuron_template_gj_LFP_Iinject_recordingimembrane.hoc
                            
:Background to Pyramidal Cells AMPA+NMDA 

NEURON {
	POINT_PROCESS bg2pyr
	NONSPECIFIC_CURRENT inmda
	NONSPECIFIC_CURRENT iampa
	RANGE taun1, taun2, factorn, normconstn
	RANGE taua1, taua2, factora, normconsta
	RANGE gnmda, gnmdas, gNMDAmax, enmda
	RANGE gampa, gampas, gAMPAmax, eampa
	RANGE initW
}

UNITS {
	(mV) = (millivolt)
        (nA) = (nanoamp)
	(uS) = (microsiemens)
}

PARAMETER {

	:W
	initW = 6.3 : 6.3 : 6.3 : 8 :6

	:NMDA
	taun1 = 5 (ms)
	taun2 = 125 (ms)
	gNMDAmax = 0.5e-3 (uS)
	enmda = 0 (mV)

	:AMPA
	taua1 = .5 (ms)
	taua2 = 7 (ms)
	gAMPAmax = 1e-3 (uS)
	eampa = 0 (mV)
	
}

ASSIGNED {
	v (mV)
	eca (mV)
	
	:NMDA
	inmda (nA)
	gnmda
	gnmdas
	factorn
	normconstn

	:AMPA
	iampa (nA)
	gampa
	gampas
	factora
	normconsta
}

STATE {

	:NMDA
	An
	Bn

	:AMPA
	Aa
	Ba
}

INITIAL {

	:NMDA
	An = 0
	Bn = 0
	factorn = taun1*taun2/(taun2-taun1)
	normconstn = -1/(factorn*(1/exp(log(taun2/taun1)/(taun1*(1/taun1-1/taun2)))-1/exp(log(taun2/taun1)/(taun2*(1/taun1-1/taun2)))))

	:AMPA
	Aa = 0
	Ba = 0
	factora = taua1*taua2/(taua2-taua1)
	normconsta = -1/(factora*(1/exp(log(taua2/taua1)/(taua1*(1/taua1-1/taua2)))-1/exp(log(taua2/taua1)/(taua2*(1/taua1-1/taua2)))))
}

BREAKPOINT {
	SOLVE states METHOD cnexp
	gnmda = normconstn*factorn*(Bn-An)
	gnmdas = gnmda
	if (gnmdas>1) {gnmdas=1}
	inmda = initW*gNMDAmax*gnmdas*(v-enmda)*sfunc(v)
	
	gampa = normconsta*factora*(Ba-Aa)
	gampas = gampa
	if (gampas > 1) {gampas = 1}
	iampa = initW*gAMPAmax*gampas*(v-eampa)
	
}

DERIVATIVE states {

	:NMDA
	An' = -An/taun1
	Bn' = -Bn/taun2
	

	:AMPA
	Aa' = -Aa/taua1
	Ba' = -Ba/taua2

}

NET_RECEIVE(wgt) {
        LOCAL x
	x = wgt
	state_discontinuity(An,An+x)
	state_discontinuity(Bn,Bn+x)
	state_discontinuity(Aa,Aa+x)
	state_discontinuity(Ba,Ba+x)
}

:::::::::::: FUNCTIONs and PROCEDUREs ::::::::::::
FUNCTION sfunc (v (mV)) {
	UNITSOFF
	sfunc = 1/(1+0.33*exp(-0.06*v))
	UNITSON
}