Contrast invariance by LGN synaptic depression (Banitt et al. 2007)

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Accession:114637
"Simple cells in layer 4 of the primary visual cortex of the cat show contrast-invariant orientation tuning, in which the amplitude of the peak response is proportional to the stimulus contrast but the width of the tuning curve hardly changes with contrast. This study uses a detailed model of spiny stellate cells (SSCs) from cat area 17 to explain this property. The model integrates our experimental data, including morphological and intrinsic membrane properties and the number and spatial distribution of four major synaptic input sources of the SSC: the dorsal lateral geniculate nucleus (dLGN) and three cortical sources. ... The model response is in close agreement with experimental results, in terms of both output spikes and membrane voltage (amplitude and fluctuations), with reasonable exceptions given that recurrent connections were not incorporated."
References:
1 . Banitt Y, Martin KA, Segev I (2007) A biologically realistic model of contrast invariant orientation tuning by thalamocortical synaptic depression. J Neurosci 27:10230-9 [PubMed]
2 . Anderson JC, Douglas RJ, Martin KA, Nelson JC (1994) Map of the synapses formed with the dendrites of spiny stellate neurons of cat visual cortex. J Comp Neurol 341:25-38 [PubMed]
3 . Anderson JC, Douglas RJ, Martin KA, Nelson JC (1994) Synaptic output of physiologically identified spiny stellate neurons in cat visual cortex. J Comp Neurol 341:16-24 [PubMed]
4 . Banitt Y, Martin KA, Segev I (2005) Depressed responses of facilitatory synapses. J Neurophysiol 94:865-70 [PubMed]
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:
Cell Type(s): Neocortex spiny stellate cell;
Channel(s): I Na,t; I A; I K; I K,Ca; I Calcium;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Pattern Recognition; Activity Patterns; Parameter Fitting; Active Dendrites; Synaptic Integration; Vision;
Implementer(s):
Search NeuronDB for information about:  I Na,t; I A; I K; I K,Ca; I Calcium;
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SSC_model
ReadMe.html
ReadMe_orig
iA.mod
iap.mod
ic.mod
ical.mod
VectorSynNS.mod
axon.hoc
InitArrays.hoc
InitSSCArrays.hoc
InitSynapses.hoc
j3886d_sdt.hoc
MeasureDist.hoc
mosinit.hoc
ssc.hoc
sscDistCl1
sscDistCl2
sscDistCl3
sscDistCl4
sscProxCl1
sscProxCl2
sscProxCl3
sscProxCl4
sscSomaCl1 *
sscSomaCl2 *
sscSomaCl3 *
sscSomaCl4 *
                            
DEFINE SYN_MAX_NUM 6000 :maximal number of synapses per VectorSynNS

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

NEURON{ 
	POINT_PROCESS VectorSynNS

	GLOBAL eI,eE :driving forces
	GLOBAL gmax1,gmax2,gmax3,gmaxI :maximal conductances
	GLOBAL factor1,factor2,factor3,factorI
	GLOBAL CL3f :frequency of class 3 synapses
	
	GLOBAL CL1tau1,CL2tau1,CL3tau1,CLItau1,CL1tau2,CL2tau2,CL3tau2,CLItau2: rise and decay time constants
	GLOBAL tau_FCL3,tau_FCLI :facilitation time constants
	GLOBAL tau_DCL1,tau_DCL3,tau_DCLI :depression time constants
	GLOBAL FCL3,FCLI,DCL1,DCL3,DCLI :stp parameters
	
	:RANGE CL1_count,CL2_count,CL3_count,CLI_count :numbers of synapses of each type
	:RANGE CL1array,CL2array,CL3array,CLIarray
	RANGE intrains_CL1,intrains_CL2,intrains_CL3,intrains_CLI :number of synchronized train
	
	RANGE F,D,time
	RANGE syntype,syncount :type of synapse
	
	RANGE tsyn
	RANGE count
	RANGE k
	
	RANGE g1,g2,g3,gi
	
	NONSPECIFIC_CURRENT i
	
}
	
PARAMETER {

	syncount	 :synapse count.
	syntype[SYN_MAX_NUM]	:types of synapses
	tsyn[SYN_MAX_NUM]		:last time the syn was active.
	count[SYN_MAX_NUM]	:activations counter
  	F[SYN_MAX_NUM]		:extra spaces here. F & D dont exist for all synapses
  	D[SYN_MAX_NUM]		:extra spaces here. F & D dont exist for all synapses
  	
  	eI=-75
  	eE=0
  	gmax1=0.0015 (umho)
  	CL1tau1=0.4 (ms)
	CL1tau2=0.5 (ms)
  	DCL1=0.17946757
  	tau_DCL1=121.34669 (ms)
  	
  	gmax2=0.0008 (umho)	
  	CL2tau1=0.589999 (ms)
  	CL2tau2=0.59 (ms)
  	
  	gmax3=0.0009 (umho)	
  	CL3tau1=0.4 (ms)
  	CL3tau2=0.6 (ms)
  	FCL3=2.6705809
  	tau_FCL3=21.896552 (ms)
  	DCL3=0.0017831198
  	tau_DCL3=11.319578 (ms)
	
  	gmaxI=0.00053 (umho)
  	CLItau1=0.55 (ms)
  	CLItau2=6.5 (ms)
  	FCLI=2.6370474
  	DCLI=0.56560689
  	tau_DCLI=45.241561 (ms)
	tau_FCLI=6.6086312 (ms)
	
	factor1
	factor2
	factor3
	factorI
	time
	CL3f
	k
}

VERBATIM
	double *hoc_pgetarg();
	double *Syntimes[150];  //spike times arrays for all synapses
ENDVERBATIM

STATE {
	A1 (umho)
	B1 (umho)
	A2 (umho)
	B2 (umho)
	A3 (umho)
	B3 (umho)
	AI (umho)
	BI (umho)
}

ASSIGNED {
	v (mV)
	i (nA)
	g1
	g2
	g3
	gi
}

PROCEDURE addspiketrain() {
VERBATIM
	int x=(int)*getarg(1);
	Syntimes[x]=hoc_pgetarg(2);
ENDVERBATIM
}

INITIAL {LOCAL ari,tp1,tp2,tp3,tpI
	A1 =0
	B1 =0
	A2 =0
	B2 =0
	A3 =0
	B3 =0
	AI =0
	BI =0
	g1=0
	g2=0
	g3=0
	gi=0
	:k=0
	
	if (CL1tau1/CL1tau2 > 0.9999) {CL1tau1 = 0.9999*CL1tau2}
	if (CL2tau1/CL2tau2 > 0.9999) {CL2tau1 = 0.9999*CL2tau2}
	if (CL3tau1/CL3tau2 > 0.9999) {CL3tau1 = 0.9999*CL3tau2}
	if (CLItau1/CLItau2 > 0.9999) {CLItau1 = 0.9999*CLItau2}
	
	tp1 = (CL1tau1*CL1tau2)/(CL1tau2 - CL1tau1) * log(CL1tau2/CL1tau1)
	factor1 = -exp(-tp1/CL1tau1) + exp(-tp1/CL1tau2)
	factor1 = 1/factor1
	
	tp2 = (CL2tau1*CL2tau2)/(CL2tau2 - CL2tau1) * log(CL2tau2/CL2tau1)
	factor2 = -exp(-tp2/CL2tau1) + exp(-tp2/CL2tau2)
	factor2 = 1/factor2
	
	tp3 = (CL3tau1*CL3tau2)/(CL3tau2 - CL3tau1) * log(CL3tau2/CL3tau1)
	factor3 = -exp(-tp3/CL3tau1) + exp(-tp3/CL3tau2)
	factor3 = 1/factor3
	
	tpI = (CLItau1*CLItau2)/(CLItau2 - CLItau1) * log(CLItau2/CLItau1)
	factorI = -exp(-tpI/CLItau1) + exp(-tpI/CLItau2)
	factorI = 1/factorI
		
	FROM ari=0 TO syncount-1{
	    F[ari]=1
		D[ari]=1
		tsyn[ari]=-1000
		time=0
		:printf("syn#=%g, type=%g\n",ari,syntype[ari])
	}
	:	if (syntype[ari]==3) {
	:		while (time<3) {time=exprand(CL3f)} :refractory period
	:		net_send(time,ari)
	:	}
	:	else {
	:		VERBATIM
	:			int j=(int)(ari);
	:			time=Syntimes[j][0];
	:		ENDVERBATIM
	:		net_send(time,ari)
	:	}
	:	count[ari]=1
	:	:printf("initial next spikes=%g id=%g\n",Syntimes[0],id)
    :   }
}

BREAKPOINT{
	SOLVE state METHOD cnexp
	g1=B1 - A1
	g2=B2 - A2
	g3=B3 - A3
	gi=BI - AI
	i=((g1+g2+g3)*(v-eE)) + gi*(v-eI)
	:i = (((B1 - A1)+(B2 - A2)+ (B3 - A3))*(v-eE))+((BI - AI)*(v-eI))
}

DERIVATIVE state{
	:go over all synapses in all arrays and compute A & B
	A1'=-A1/CL1tau1
	B1'=-B1/CL1tau2
	
	A2'=-A2/CL2tau1
	B2'=-B2/CL2tau2
	
	A3'=-A3/CL3tau1
	B3'=-B3/CL3tau2
	
	AI'=-AI/CLItau1
	BI'=-BI/CLItau2
}

NET_RECEIVE(w){ LOCAL x,j
        k = w
		:printf("lpsp. flag=%g\tt=%g\n",k,t)
		if (syntype[k] == 1){				:LGN
			:printf("tsyn[k]=%g\n",tsyn[k])
			:F[k] = 1 + (F[k]-1)*exp(-(t - tsyn[k])/tau_FCL1)
        	D[k] = 1 - (1-D[k])*exp(-(t - tsyn[k])/tau_DCL1)
	        tsyn[k] = t
	        :printf("here, LGN. D[k]= %g\n",D[k])
			state_discontinuity(A1, A1 + gmax1*factor1*D[k]):*F[k])
			state_discontinuity(B1, B1 + gmax1*factor1*D[k]):*F[k])
	        :F[k] = F[k] + FCL1
	        D[k] = D[k] * DCL1
	        :printf("next spikes. t=%g\n",t)
	        :VERBATIM
	        :	int j=(int)(k);
	        :	int x=(int)(count[j]);
	        :	double ti=Syntimes[j][x]-Syntimes[j][x-1];
	        :ENDVERBATIM
	        :if (ti<0) {
	        :	ti=1e9
	        :	printf("\n\n\nnext spike time<0, stop spike train.\n\n")
	        :}
	        :printf("next spikes. j=%g\n",ti)
	        :net_send(ti,k)
		} else if (syntype[k] == 2){			:L4 non dynamic synapse
			:F[k] = 1 + (F[k]-1)*exp(-(t - tsyn[k])/tau_FCL2)
       		:D[k] = 1 - (1-D[k])*exp(-(t - tsyn[k])/tau_DCL2)
        	:tsyn[k] = t
			state_discontinuity(A2, A2 + gmax2*factor2):*F[k]*D[k])
			state_discontinuity(B2, B2 + gmax2*factor2):*F[k]*D[k])
			:VERBATIM
        	:	int j=(int)(k);
        	:	int x=(int)(count[j]);
        	:	double ti=Syntimes[j][x]-Syntimes[j][x-1];
        	:ENDVERBATIM
        	:net_send(ti,k)
        	:F[k] = F[k] + f[k]
        	:D = D[k] * d1[k]
	    } else if (syntype[k] == 3){			:L6 
			F[k] = 1 + (F[k]-1)*exp(-(t - tsyn[k])/tau_FCL3)
       		D[k] = 1 - (1-D[k])*exp(-(t - tsyn[k])/tau_DCL3)
        	tsyn[k] = t
			:printf("here, L6. D[k]= %g\tF[k]=%g\n",D[k],F[k])			
			state_discontinuity(A3, A3 + gmax3*factor3*F[k]*D[k]) 
			state_discontinuity(B3, B3 + gmax3*factor3*F[k]*D[k])
        	F[k] = F[k] + FCL3
        	D[k] = D[k] * DCL3
        	:while (time<3) { time = exprand(CL3f) }  :refractory period
			:net_send(time,k)
	    } else if (syntype[k] == 4){				:Inhibitory
			F[k] = 1 + (F[k]-1)*exp(-(t - tsyn[k])/tau_FCLI)
        	D[k] = 1 - (1-D[k])*exp(-(t - tsyn[k])/tau_DCLI)
	       	tsyn[k] = t
			state_discontinuity(AI, AI + gmaxI*factorI*F[k]*D[k])
			state_discontinuity(BI, BI + gmaxI*factorI*F[k]*D[k])
	       	F[k] = F[k] + FCLI
	       	D[k] = D[k] * DCLI
	       	:printf("inhi syn,k/id=%g \n",k)
	       	:VERBATIM
	       	:	int j=(int)(k);
	       	:	int x=(int)(count[j]);
	       	:	double ti=Syntimes[j][x]-Syntimes[j][x-1];
	       	:ENDVERBATIM
	       	:net_send(ti,k)
	    }
            :printf("next spikes=%g %g id=%g t=%g flag=%g\n",Syntimes[count[k]],Syntimes[count[k]-1],id,t,flag)
    count[k]=count[k]+1	
}

PROCEDURE add(x){
	if (syncount<SYN_MAX_NUM-1) {
		syntype[syncount]=x
		syncount=syncount+1
	} else {
		printf("\n\n\n EXCEEDING ALLOCATED # OF SYNAPSES\n\n\n")
	}
}

COMMENT
//usage:
load_file("nrngui.hoc")
nrncontrolmenu()
newPlotV(0.5)
create soma
access soma
objref syn
syn=new LogicalSynNS(0.5)
syn.add(1)
objref n,s
s=new NetStim(0.5)
s.start=10
s.interval=10
s.number=5
n=new NetCon(s,syn,0,0,0)//last is the number of synapse on the logical synapse
tstop=70
init()
run()

//for a vector of spike times:
/*objref vec
syn=new LogicalSyn(0.5)
syn.add(1)
add(1)
syn.addspiketrain(0,&vec[0])
syn.addspiketrain(&vec[0])
*/


ENDCOMMENT

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