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Thalamic network model of deep brain stimulation in essential tremor (Birdno et al. 2012)

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Accession:143633
"... Thus the decreased effectiveness of temporally irregular DBS trains is due to long pauses in the stimulus trains, not the degree of temporal irregularity alone. We also conducted computer simulations of neuronal responses to the experimental stimulus trains using a biophysical model of the thalamic network. Trains that suppressed tremor in volunteers also suppressed fluctuations in thalamic transmembrane potential at the frequency associated with cerebellar burst-driver inputs. Clinical and computational findings indicate that DBS suppresses tremor by masking burst-driver inputs to the thalamus and that pauses in stimulation prevent such masking. Although stimulation of other anatomic targets may provide tremor suppression, we propose that the most relevant neuronal targets for effective tremor suppression are the afferent cerebellar fibers that terminate in the thalamus."
References:
1 . Birdno MJ, Kuncel AM, Dorval AD, Turner DA, Gross RE, Grill WM (2012) Stimulus features underlying reduced tremor suppression with temporally patterned deep brain stimulation. J Neurophysiol 107:364-83 [PubMed]
2 . Yi G, Grill WM (2018) Frequency-dependent antidromic activation in thalamocortical relay neurons: effects of synaptic inputs. J Neural Eng 15:056001 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Axon;
Brain Region(s)/Organism:
Cell Type(s): Thalamus geniculate nucleus/lateral principal GLU cell;
Channel(s):
Gap Junctions:
Receptor(s): GabaA; GabaB; AMPA; NMDA; Glutamate; Gaba;
Gene(s):
Transmitter(s): Gaba; Ions;
Simulation Environment: NEURON; MATLAB;
Model Concept(s): Action Potential Initiation; Temporal Pattern Generation; Axonal Action Potentials; Therapeutics; Deep brain stimulation;
Implementer(s):
Search NeuronDB for information about:  Thalamus geniculate nucleus/lateral principal GLU cell; GabaA; GabaB; AMPA; NMDA; Glutamate; Gaba; Gaba; Ions;
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Birdno_et_al_2012
modfiles
ampa.mod *
ampacer.mod *
ampactx.mod *
asymtrain.mod *
AXNODE75mb.mod *
FakeExcSyn.mod *
gabaa.mod *
gababKG.mod *
ihshift.mod *
ik2.mod *
isikdr.mod *
isina.mod *
it.mod *
kdyn.mod *
leakdepol.mod *
mdltrdyn.mod *
nmda.mod *
nmdacer.mod *
nmdactx.mod *
PARAK75.mod *
                            
TITLE minimal model of GABAb receptors

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

M. Birdno added kinetic scheme for effects due to Adenosine &/or Muscarinic ACh March 2009.
See Steriade, Jones, and McCormick (1997) Thalamus, Volume I (pp. 727-730)


	Kinetic model of GABA-B receptors
	=================================

  MODEL OF SECOND-ORDER G-PROTEIN TRANSDUCTION AND FAST K+ OPENING
  WITH COOPERATIVITY OF G-PROTEIN BINDING TO K+ CHANNEL

  PULSE OF TRANSMITTER

  SIMPLE KINETICS WITH NO DESENSITIZATION

	Features:

	  - peak at 100 ms; time course fit to Tom Otis' PSC
	  - SUMMATION (psc is much stronger with bursts)


	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:

	  dR/dt = K1 * T * (1-R-D) - K2 * R

	  dS/dt = K5 * T * (1 - S) - K6 * S  

	  dG/dt = K3 * (R+S) - K4 * G

	  S : activated receptor due to neuromodulation by mACh &/or adenosine 
	  R : activated receptor
	  T : transmitter
	  G : activated G-protein
	  K1,K2,K3,K4,K5,K6 = kinetic rate cst

  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

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

  Parameters estimated from patch clamp recordings of GABAB PSP's in
  rat hippocampal slices (Otis et al, J. Physiol. 463: 391-407, 1993).

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

  PULSE MECHANISM

  Kinetic synapse with release mechanism as a pulse.  

  Warning: for this mechanism to be equivalent to the model with diffusion 
  of transmitter, small pulses must be used...

  For a detailed model of GABAB:

  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.

  For a review of models of synaptic currents:

  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.

  This simplified model was introduced in:

  Destexhe, A., Bal, T., McCormick, D.A. and Sejnowski, T.J.
  Ionic mechanisms underlying synchronized oscillations and propagating
  waves in a model of ferret thalamic slices. Journal of Neurophysiology
  76: 2049-2070, 1996.  

  See also http://cns.iaf.cnrs-gif.fr

  Alain Destexhe, Salk Institute and Laval University, 1995
  27-11-2002: the pulse is implemented using a counter, which is more
       stable numerically (thanks to Yann LeFranc)

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



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

NEURON {
	POINT_PROCESS GABAbKG
	POINTER pre, vext, pmodyn
	USEION k READ ek WRITE ik
	RANGE C, R, S, G, g, gmax, lastrelease, TimeCount, ek, K1, K2, K5, K6, nsm, i
	GLOBAL Cmax, Cdur, Prethresh, Deadtime
	GLOBAL K3, K4, KD
}
UNITS {
	(nA) = (nanoamp)
	(mV) = (millivolt)
	(umho) = (micromho)
	(mM) = (milli/liter)
}

PARAMETER {
	dt		(ms)
	Cmax	= 0.5	(mM)		: max transmitter concentration
	Cdur	= 0.3	(ms)		: transmitter duration (rising phase)
	Prethresh = 0 			: voltage level nec for release
	Deadtime = 1	(ms)		: mimimum time between release events
	stimon = 0
	nsm = 1
:
:	From Kfit with long pulse (5ms 0.5mM)
:
	K1	= 0.52   (/ms mM) : 	: forward binding rate to receptor
	K2	= 0.0013 (/ms)	: 	: backward (unbinding) rate of receptor
	K3	= 0.098 (/ms)		: 	: rate of G-protein production
	K4	= 0.033 (/ms)		: 	: rate of G-protein decay
	K5	= 0.52   (/ms) : 	: forward binding rate to adenosine/mACh receptor
	K6	= 0.00013 (/ms)	: 	: backward (unbinding) rate of adenosine/mACh receptor
	KD	= 100			: dissociation constant of K+ channel
	n	= 4			: nb of binding sites of G-protein on K+
	gmax		(umho)		: maximum conductance
}

ASSIGNED {
	ek 		(mV)
	v		(mV)		: postsynaptic voltage
	ik 		(nA)		: current = g*(v - ek)
	g 		(umho)		: conductance
	C		(mM)		: transmitter concentration
	Gn
	pre 				: pointer to presynaptic variable
	lastrelease	(ms)		: time of last spike
	TimeCount	(ms)		: time counter
	vext				: vext turns into a dummy variable to determine whether a stim pulse is ON
	pmodyn
	i 		(nA)
}


STATE {
	R				: fraction of activated GABAb receptor
	S				: fraction of activated adenosine/mACh receptor evoked by STIMULATION
	G				: fraction of activated G-protein
}


INITIAL {
	C = 0
	lastrelease = -1000

	R = 0
	S = 0
	G = 0
	TimeCount=-1
}

BREAKPOINT {
	SOLVE bindkin METHOD euler
	Gn = G^n
	g = gmax * Gn / (Gn+KD)
	i = g*(v - ek) 
	ik = i
}


DERIVATIVE bindkin {

	release()		: evaluate the variable C

	R' = K1 * C * (1-R) - K2 * R
	S' = K5 * pmodyn * (1-S) - K6 * S
	G' = K3 * (R + 2 * nsm * S) - K4 * G
}


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

	TimeCount=TimeCount-dt			: time since last release ended

						: ready for another release?
	if (TimeCount < -Deadtime) {
		if (pre > Prethresh) {		: spike occured?
			C = Cmax			: start new release
			lastrelease = t
			TimeCount=Cdur
		}
						
	} else if (TimeCount > 0) {		: still releasing?
	
		: do nothing
	
	} else if (C == Cmax) {			: in dead time after release
		C = 0.
	}
	
	if(vext==0) {      : vext turns into a dummy variable to determine whether a stim pulse is ON
		stimon=0
	}else{
		stimon=1
	}


}

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