CA1 pyramidal neuron: nonlinear a5-GABAAR controls synaptic NMDAR activation (Schulz et al 2018)

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Accession:258867
The study shows that IPSCs mediated by a5-subunit containing GABAA receptors are strongly outward-rectifying generating 4-fold larger conductances above -50?mV than at rest. Experiments and modeling show that synaptic activation of these receptors can very effectively control voltage-dependent NMDA-receptor activation in a spatiotemporally controlled manner in fine dendrites of CA1 pyramidal cells. The files contain the NEURON code for Fig.8, Fig.S8 and Fig.S9 of the paper. The model is based on the model published by Bloss et al., 2017. Physiological properties of GABA synapses were modified as determined by optogenetic activation of inputs during voltage-clamp recordings in Schulz et al. 2018. Other changes include stochastic synaptic release and short-term synaptic plasticity. All changes of mechanisms and parameters are detailed in the Methods of the paper. Simulation can be run by starting start_simulation.hoc after running mknrndll. The files that model the individual figures have to be uncommented in start_simulation.hoc beforehand.
Reference:
1 . Schulz JM, Knoflach F, Hernandez MC, Bischofberger J (2018) Dendrite-targeting interneurons control synaptic NMDA-receptor activation via nonlinear a5-GABAA receptors. Nat Commun 9:3576 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Dendrite; Synapse;
Brain Region(s)/Organism: Hippocampus; Mouse;
Cell Type(s): Hippocampus CA1 pyramidal GLU cell;
Channel(s): I h; I A;
Gap Junctions:
Receptor(s): GabaA; GabaB; AMPA; NMDA;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s):
Implementer(s): Schulz, Jan M [j.schulz at unibas.ch];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; GabaA; GabaB; AMPA; NMDA; I A; I h; Gaba; Glutamate;
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Alpha5_NMDA_CA1_pyr
README.html
dists.mod *
eff.mod *
exc.mod *
gabab.mod
h.mod
id.mod *
inh.mod
kad.mod *
kap.mod *
kdr.mod *
na3.mod *
nmdaSyn.mod
syns.mod *
tonic.mod
activateExcitation.hoc
activateInhibition_JMS.hoc
addChannels_JMS.hoc
addExcitation_JMS.hoc
addVgatInhibition_JMS.hoc
channelParameters.hoc
Connect_Stimulator2ExcSyn.hoc
Connect_Stimulator2InhSyn.hoc
Fig8_tuft_NMDA_spike.hoc
FigS8_SR_SLM_burst_stim.hoc
FigS9_test_TI.hoc
flagVgatInhibition_JMS.hoc
Generate_Stimulator.hoc
getBranchOrder.hoc *
idMorph.hoc
inhibitionBiophysics_JMS.hoc
initializationAndRun.hoc *
loadMorph.hoc *
mosinit.hoc
naceaxon.nrn *
Print-to-File.hoc
processMorph.hoc *
proofreadMorph.hoc *
resetNSeg.hoc *
screenshot.png
start_simulation.hoc
synHelperScripts.hoc
SynStim_SR_SLM_control.hoc
SynStim_SR_SLM_noInh.hoc
SynStim_SR_SLM_redInh.hoc
SynStim_SR_SLM_TI.hoc
tuft_NMDA_spike_fast.hoc
tuft_NMDA_spike_noRect.hoc
twinApical.swc *
update_Synapses.hoc
                            
TITLE model of GABAB receptors

COMMENT
-----------------------------------------------------------------------------

	Kinetic model for GABA-B receptors
	==========================================

	Model of GABAB currents including nonlinear stimulus 
	dependency (fundamental to take into account for GABAB receptors).


	Features:

	  - peak at ~200 ms after burst activation (5@50 Hz); time course fit from experimental IPSPs recorded by J. Schulz
	  - NONLINEAR SUMMATION (psc is much stronger with bursts)
		due to cooperativity of G-protein binding on K+ channels

	Approximations:

	  - single binding site on receptor	
	  - model of alpha G-protein activation (direct) of K+ channel
	  - G-protein dynamics is second-order; simplified as follows:
		- saturating receptor
		- no desensitization
		- Michaelis-Menten of receptor for G-protein production
		- "resting" G-protein is in excess
		- Quasi-stat of intermediate enzymatic forms
	  - binding on K+ channel is fast


	Kinetic Equations of model:

	  dT/dt = -T/tauD -k1 * T * (Bm - B) + k_1 * B 
	  dB/dt = k1 * T * (Bm - B) - (k_1 + k2) * B
	  dR/dt = K1 * T * (1-R) - K2 * R
	  dG/dt = (K3 * R * (1-G) - K4 * G) *f

      
	  R : fraction activated receptor
	  T : transmitter
      B : GABA transporter
	  G : fraction activated G-protein
	  K1,K2,K3,K4 = kinetic rate cst; from Thomson & Destexhe, 1999, Fig. 15 for n=2
      k1,k_1,k2 = kinetic rate cst; from Thomson & Destexhe, 1999
      tauD : decay due to diffusion; from Sanders et al., 2013
      f : factor f to G protein control dynamics
      
  f and K2 adjusted to reach max amplitude ~200 ms after burst start (5@50 Hz)

  n activated G-protein bind to a K+ channel:

	n G + C <-> O		(Alpha,Beta)

  If the binding is fast, the fraction of open channels is given by:

	O = G^n / ( G^n + KD )

  where KD = Beta / Alpha is the dissociation constant

-----------------------------------------------------------------------------

  Also see details in:

  Destexhe, A. and Sejnowski, T.J.	G-protein activation kinetics and
  spill-over of GABA may account for differences between inhibitory responses
  in the hippocampus and thalamus.	Proc. Natl. Acad. Sci. USA	92:
  9515-9519, 1995.

  Thompson, A.M. and Destexhe, A. DUAL INTRACELLULAR RECORDINGS AND COMPUTATIONAL
  MODELS OF SLOW INHIBITORY POSTSYNAPTIC POTENTIALS IN RAT NEOCORTICAL AND HIPPOCAMPAL 
  SLICES. Neuroscience 92: 1193-1215, 1999.
  
  Sanders, H., Berends, M., Major, G., Goldman, M.S. and Lisman, J.E. NMDA and 
  GABAB (KIR) conductances: the "perfect couple" for bistability. J Neurosci 33(2): 424-9, 2013.
  
  Taken from Poirazi, Brannon & Mel. Arithmetic of Subthreshold Synaptic
  Summation in a Model CA1 Pyramidal Cell. Neuron 2003 (Originally written by Alain Destexhe, Laval University, 1995)
  
  Modified by J. Schulz according to Thompson & Destexhe (1999) and Sanders, Berends et al. (2013) 

-----------------------------------------------------------------------------
ENDCOMMENT

NEURON {
	POINT_PROCESS GABABsyn
	RANGE C, R, G, B, g, gmax, tauD
	NONSPECIFIC_CURRENT i
	RANGE vgat,sst,npy,pv,xEff
	RANGE isOn
	GLOBAL K1, K2, K3, K4, KD, k1, k_1, k2, e, Bm
}

UNITS {
	(nA) = (nanoamp)
	(mV) = (millivolt)
	(molar) = (1/liter)
	(mM) = (millimolar)
	(uS) = (microsiemens)
}

PARAMETER {

	tauD = 10	(ms)		: decay of transmitter concentration
	K1	= 0.066	(/ms mM)	: forward binding rate to receptor
	K2	= 0.008 (/ms)		: backward (unbinding) rate of receptor
	K3	= 0.27 (/ms)		: rate of G-protein production
	K4	= 0.044 (/ms)		: rate of G-protein decay
	KD	= 0.5				: half maximal coductance at a level of ~0.7 activated G-protein
	n	= 2			: nb of binding sites of G-protein on K+
	e	= -95	(mV)		: reversal potential (E_K)
	gmax		(uS)		: maximum conductance
    f   = 0.1              : factor f controlling the G protein dynamics
	k1	= 30	(/ms mM)	: 30, forward binding rate to transporter
	k_1	= 0.1 (/ms)		: backward (unbinding) rate of transporter
	k2	= 0.02 (/ms)		: clearance of GABA
	Bm = 1 (mM)			: maximum binding capacity of transporter
	vgat=0
	sst=0
	npy=0
	pv=0
	xEff=-1
	isOn=0
}


ASSIGNED {
	v		(mV)		: postsynaptic voltage
	i		(nA)		: current = g*(v - e)
	g		(uS)		: conductance
	Gn
}


STATE {
	C	(mM)		: extracellular transmitter concentration
	R				: fraction of activated receptor
	G				: normalized concentration of activated G-protein
	B	(mM)		: bound GABA transporter
}


INITIAL {
	C = 0
	R = 0
	G = 0
	B = 0
}

BREAKPOINT {
	SOLVE state METHOD cnexp
	Gn = G^n
	g = isOn * gmax * Gn / (Gn+KD)
	i = g *(v - e)
}


DERIVATIVE state {

	C' = (-C/tauD -k1 * C * (Bm - B) + k_1 * B) 
	R' = (K1 * C * (1-R) - K2 * R) 
	G' = (K3 * R * (1-G) - K4 * G) * f
	B' = (k1 * C * (Bm - B) - (k_1 + k2) * B) 

}


NET_RECEIVE(weight (mM)) {
	C = C + weight
}