Shaping NMDA spikes by timed synaptic inhibition on L5PC (Doron et al. 2017)

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Accession:231427
This work (published in "Timed synaptic inhibition shapes NMDA spikes, influencing local dendritic processing and global I/O properties of cortical neurons", Doron et al, Cell Reports, 2017), examines the effect of timed inhibition over dendritic NMDA spikes on L5PC (Based on Hay et al., 2011) and CA1 cell (Based on Grunditz et al. 2008 and Golding et al. 2001).
Reference:
1 . Doron M, Chindemi G, Muller E, Markram H, Segev I (2017) Timed Synaptic Inhibition Shapes NMDA Spikes, Influencing Local Dendritic Processing and Global I/O Properties of Cortical Neurons. Cell Rep 21:1550-1561 [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;
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Neocortex L5/6 pyramidal GLU cell;
Channel(s): I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I M; I h; I K,Ca; I Calcium; I A, slow;
Gap Junctions:
Receptor(s): NMDA; GabaA; AMPA;
Gene(s):
Transmitter(s): Glutamate; Gaba;
Simulation Environment: NEURON;
Model Concept(s): Active Dendrites; Detailed Neuronal Models;
Implementer(s): Doron, Michael [michael.doron at mail.huji.ac.il];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; GabaA; AMPA; NMDA; I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I M; I h; I K,Ca; I Calcium; I A, slow; Gaba; Glutamate;
/
reproduction
readme.txt
ampa.mod
Ca_HVA.mod
Ca_LVAst.mod *
cad.mod *
cadiffus.mod
CaDynamics_E2.mod *
canmda.mod *
car.mod *
gabaa.mod *
gabab.mod *
Ih.mod *
Im.mod *
K_Pst.mod *
K_Tst.mod *
Nap_Et2.mod *
NaTa_t.mod *
NaTs2_t.mod *
nmda.mod *
ProbAMPA.mod
ProbAMPANMDA2_ratio.mod *
ProbUDFsyn2_lark.mod *
SK_E2.mod *
SKv3_1.mod *
SynExp5NMDA.mod *
cell1.asc *
cellmorphology.hoc *
create_data_for_figure_01.py
create_data_for_figure_02.py
create_data_for_figure_03.py *
create_data_for_figure_03_control.py
create_data_for_figure_03_Dt_10.py *
create_data_for_figure_03_Dt_40.py *
data_same_excitation.pickle
iniparameter.hoc
L5PCbiophys3.hoc
L5PCbiophys3_noActive.hoc
mosinit.hoc
plot_figure_01.py
plot_figure_02.py
plot_figure_03.py
plot_figure_04.py
plot_figure_05.py
plot_figure_06.py
spikes_num.pickle
spine.hoc
TTC.hoc
                            
TITLE minimal model of GABAa receptors

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

	Minimal kinetic model for GABA-A receptors
	==========================================

  Model of Destexhe, Mainen & Sejnowski, 1994:

	(closed) + T <-> (open)

  The simplest kinetics are considered for the binding of transmitter (T)
  to open postsynaptic receptors.   The corresponding equations are in
  similar form as the Hodgkin-Huxley model:

	dr/dt = alpha * [T] * (1-r) - beta * r

	I = gmax * [open] * (V-Erev)

  where [T] is the transmitter concentration and r is the fraction of 
  receptors in the open form.

  If the time course of transmitter occurs as a pulse of fixed duration,
  then this first-order model can be solved analytically, leading to a very
  fast mechanism for simulating synaptic currents, since no differential
  equation must be solved (see Destexhe, Mainen & Sejnowski, 1994).

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

  Based on voltage-clamp recordings of GABAA receptor-mediated currents in rat
  hippocampal slices (Otis and Mody, Neuroscience 49: 13-32, 1992), this model
  was fit directly to experimental recordings in order to obtain the optimal
  values for the parameters (see Destexhe, Mainen and Sejnowski, 1996).

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

  This mod file includes a mechanism to describe the time course of transmitter
  on the receptors.  The time course is approximated here as a brief pulse
  triggered when the presynaptic compartment produces an action potential.
  The pointer "pre" represents the voltage of the presynaptic compartment and
  must be connected to the appropriate variable in oc.

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

  See details in:

  Destexhe, A., Mainen, Z.F. and Sejnowski, T.J.  An efficient method for
  computing synaptic conductances based on a kinetic model of receptor binding
  Neural Computation 6: 10-14, 1994.  

  Destexhe, A., Mainen, Z.F. and Sejnowski, T.J.  Kinetic models of 
  synaptic transmission.  In: Methods in Neuronal Modeling (2nd edition; 
  edited by Koch, C. and Segev, I.), MIT press, Cambridge, 1996.


  Written by Alain Destexhe, Laval University, 1995

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



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

NEURON {
	POINT_PROCESS GABAa
	POINTER pre
	RANGE C, R, R0, R1, g, gmax, lastrelease
	NONSPECIFIC_CURRENT i
	GLOBAL Cmax, Cdur, Alpha, Beta, Erev, Prethresh, Deadtime, Rinf, Rtau
}
UNITS {
	(nA) = (nanoamp)
	(mV) = (millivolt)
	(umho) = (micromho)
	(mM) = (milli/liter)
}

PARAMETER {

	Cmax	= 1	(mM)		: max transmitter concentration
	Cdur	= 1	(ms)		: transmitter duration (rising phase)
	Alpha	= 5	(/ms mM)	: forward (binding) rate
	Beta	= 0.18	(/ms)		: backward (unbinding) rate
	Erev	= -80	(mV)		: reversal potential
	Prethresh = 0 			: voltage level nec for release
	Deadtime = 1	(ms)		: mimimum time between release events
	gmax		(umho)		: maximum conductance
}


ASSIGNED {
	v		(mV)		: postsynaptic voltage
	i 		(nA)		: current = g*(v - Erev)
	g 		(umho)		: conductance
	C		(mM)		: transmitter concentration
	R				: fraction of open channels
	R0				: open channels at start of release
	R1				: open channels at end of release
	Rinf				: steady state channels open
	Rtau		(ms)		: time constant of channel binding
	pre 				: pointer to presynaptic variable
	lastrelease	(ms)		: time of last spike
}

INITIAL {
	R = 0
	C = 0
	Rinf = Cmax*Alpha / (Cmax*Alpha + Beta)
	Rtau = 1 / ((Alpha * Cmax) + Beta)
	lastrelease = -1000
}

BREAKPOINT {
	SOLVE release
	g = gmax * R
	i = g*(v - Erev)
}

PROCEDURE release() { LOCAL q
	:will crash if user hasn't set pre with the connect statement 

	q = ((t - lastrelease) - Cdur)		: time since last release ended

						: ready for another release?
	if (q > Deadtime) {
		if (pre > Prethresh) {		: spike occured?
			C = Cmax			: start new release
			R0 = R
			lastrelease = t
		}
						
	} else if (q < 0) {			: still releasing?
	
		: do nothing
	
	} else if (C == Cmax) {			: in dead time after release
		R1 = R
		C = 0.
	}



	if (C > 0) {				: transmitter being released?

	   R = Rinf + (R0 - Rinf) * exptable (- (t - lastrelease) / Rtau)
				
	} else {				: no release occuring

  	   R = R1 * exptable (- Beta * (t - (lastrelease + Cdur)))
	}

	VERBATIM
	return 0;
	ENDVERBATIM
}

FUNCTION exptable(x) { 
	TABLE  FROM -10 TO 10 WITH 2000

	if ((x > -10) && (x < 10)) {
		exptable = exp(x)
	} else {
		exptable = 0.
	}
}