Reconstructing cerebellar granule layer evoked LFP using convolution (ReConv) (Diwakar et al. 2011)

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Accession:139883
The model allows reconstruction of evoked local field potentials as seen in the cerebellar granular layer. The approach uses a detailed model of cerebellar granule neuron to generate data traces and then uses a "ReConv" or jittered repetitive convolution technique to reproduce post-synaptic local field potentials in the granular layer. The algorithm was used to generate both in vitro and in vivo evoked LFP and reflected the changes seen during LTP and LTD, when such changes were induced in the underlying neurons by modulating release probability of synapses and sodium channel regulated intrinsic excitability of the cells.
Reference:
1 . Diwakar S, Lombardo P, Solinas S, Naldi G, D'Angelo E (2011) Local field potential modeling predicts dense activation in cerebellar granule cells clusters under LTP and LTD control. PLoS One 6:e21928 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Extracellular;
Brain Region(s)/Organism:
Cell Type(s): Cerebellum interneuron granule cell;
Channel(s): I K; I M; I K,Ca; I Sodium; I Calcium; I Cl, leak;
Gap Junctions:
Receptor(s): GabaA; AMPA; NMDA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; MATLAB; Octave;
Model Concept(s): Extracellular Fields; Evoked LFP;
Implementer(s): Diwakar, Shyam [shyam at amrita.edu];
Search NeuronDB for information about:  Cerebellum interneuron granule cell; GabaA; AMPA; NMDA; I K; I M; I K,Ca; I Sodium; I Calcium; I Cl, leak;
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ReConv
data
readme.html
AmpaCOD.mod *
GRC_CA.mod *
GRC_CALC.mod *
GRC_GABA.mod *
GRC_KA.mod *
GRC_KCA.mod *
GRC_KIR.mod *
GRC_KM.mod *
GRC_KV.mod *
GRC_LKG1.mod *
GRC_LKG2.mod *
GRC_NA.mod *
NmdaS.mod *
Pregen.mod *
ComPanel.hoc
Grc_Cell.hoc
mosinit.hoc
Parametri.hoc
ReConv_GrC.jpg
ReConv_invitro.jpg
ReConv_invivo.jpg
Record_vext.hoc
Start.hoc
                            
TITLE AMPACOD  

COMMENT
	AMPA model from Paper (version 15 sept 2004).
	
ENDCOMMENT

NEURON {
	POINT_PROCESS AmpaCOD	
	NONSPECIFIC_CURRENT i	
	RANGE r1FIX,r2,r3,r4,r5,r1,r6,r6FIX
	RANGE g,gmax,kB,Cdur,Erev 
	RANGE gg1,gg2,gg3,Tdiff
	RANGE T,Tmax,Trelease 	
	RANGE tau_1,tau_rec,tau_facil,U,u0	
	RANGE A1,A2,A3,tau_dec1,tau_dec2,tau_dec3		: comes from fit 
	RANGE tdelay,ton	 
}

UNITS {
	(nA) = (nanoamp)
	(mV) = (millivolt)	
	(mM) = (milli/liter)
	(pS) = (picosiemens)
	(nS) = (nanosiemens)
	(um) = (micrometer)
	PI   = (pi)(1)
}

PARAMETER {
	: Parametri Postsinaptici
	r1FIX		= 5.4		(/ms/mM) 	 
	r2		= 0.82		(/ms)		 
	r3		= 0		(/ms)		 
	r4		= 0		(/ms)		 
	r5		= 0.013		(/ms)		
	r6FIX		= 1.12		(/ms/mM)	
	gmax		= 700 		(nS)		 
	Cdur		= 0.3		(ms)		 
	Erev		= 0		(mV)
	kB		= 0.44		(mM)
		
	: Diffusion: M=21500, R=1.033, D=0.223, lamd=0.02			
	A1 			= 0.131837 
	A2			= 0.0555027	 
	A3 			= 0.0135232	 
	tau_dec1 		= 3.4958	 
	tau_dec2 		= 16.6317	 
	tau_dec3 		= 128.983	

	: Parametri Presinaptici
	tau_1 		= 3 (ms) 	< 1e-9, 1e9 >
	tau_rec 	= 35.1 (ms) 	< 1e-9, 1e9 > 	
	tau_facil 	= 10.8 (ms) 	< 0, 1e9 > 	

	U 		= 0.416 (1) 	< 0, 1 >
	u0 		= 0 (1) 	< 0, 1 >	: se u0=0 al primo colpo y=U
	Tmax		= 1  (mM)
}


ASSIGNED {
	v		(mV)		: postsynaptic voltage
	i 		(nA)		: current = g*(v - Erev)
	g 		(pS)		: conductance
	r1		(/ms)
	r6		(/ms)
	T		(mM)
	Trelease	(mM)
	Tdiff		(mM)
	tdelay		(ms)
	Tdiff_0		(mM)
	ton		(ms)	
	
	x
	PRE
}

STATE {	
	C
	O
	D
	gg1
	gg2
	gg3
	sink
}	
	

INITIAL {
	C		=	1
	O		=	0
	D		=	0
	T		=	0 	(mM)
	Tdiff		=	0	(mM)
	Trelease	=	0 	(mM)
	Tdiff_0		=	0	(mM)
	gg1		=	0
	gg2		=	0
	gg3		=	0   
	ton		=  	-1   (ms)
	PRE		=	0
}

FUNCTION SET_tdelay(R,D){ tdelay=0.25*R*R/D } 

BREAKPOINT {
	if( (t-ton)>tdelay  ){
		Tdiff=gg1+gg2+gg3
		Tdiff_0 = Tdiff
	}else{
		Tdiff=Tdiff_0+(A1+A2+A3)*PRE*(t-ton)/tdelay
	}
	Trelease=T+Tdiff
	SOLVE kstates METHOD sparse
	g =gmax * O
	i = (1e-6) * g * (v - Erev) 
}


KINETIC kstates {
	: Postsynaptic scheme
	r1 = r1FIX * Trelease^2 / (Trelease + kB)^2
	r6 = r6FIX * Trelease^2 / (Trelease + kB)^2
	~ C  <-> O	(r1,r2)
	~ O  <-> D	(r3,r4)
	~ D  <-> C	(r5,r6)
	CONSERVE C+O+D = 1
	: Glutamate diffusion wave
	~ gg1 <-> sink (1/tau_dec1,0)
	~ gg2 <-> sink (1/tau_dec2,0)
	~ gg3 <-> sink (1/tau_dec3,0)
}


NET_RECEIVE(weight, on, nspike, flagtdel,t0 (ms),y, z, u, tsyn (ms)) {
	INITIAL {
		flagtdel=1
		nspike = 1
		Tdiff=0
		y=0
		z=0
		u=u0
		tsyn=t
	}
   	if (flag == 0) { 
		nspike = nspike + 1
		if (!on) {
			ton=t
			t0=t
			on=1				
			z=z*exp(-(t-tsyn)/tau_rec)
			z=z+(y*(exp(-(t - tsyn)/tau_1)-exp(-(t-tsyn)/tau_rec))/(tau_1/tau_rec-1))
			y=y*exp(-(t-tsyn)/tau_1)			
			x=1-y-z
			if(tau_facil>0){ 
				u=u*exp(-(t-tsyn)/tau_facil)
				u=u+U*(1-u)							
			}else{u=U}
			y=y+x*u
			PRE=y
			T=Tmax*y
			tsyn=t						
		}
		net_send(Cdur,nspike)
		net_send(tdelay,flagtdel)						
    	}
	if(flag==nspike){ 		
		T = 0
		on = 0
	}
	if (flag == flagtdel){
		flagtdel = flagtdel+1
		state_discontinuity(gg1,gg1+A1*x*u)	 
		state_discontinuity(gg2,gg2+A2*x*u)	 
		state_discontinuity(gg3,gg3+A3*x*u)	 
	}
}	 

 

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