Modeling dentate granule cells heterosynaptic plasticity using STDP-BCM rule (Jedlicka et al. 2015)

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Accession:185350
... Here we study how key components of learning mechanisms in the brain, namely spike timing-dependent plasticity and metaplasticity, interact with spontaneous activity in the input pathways of the neuron. Using biologically realistic simulations we show that ongoing background activity is a key determinant of the degree of long-term potentiation and long-term depression of synaptic transmission between nerve cells in the hippocampus of freely moving animals. This work helps better understand the computational rules which drive synaptic plasticity in vivo. ...
Reference:
1 . Jedlicka P, Benuskova L, Abraham WC (2015) A Voltage-Based STDP Rule Combined with Fast BCM-Like Metaplasticity Accounts for LTP and Concurrent "Heterosynaptic" LTD in the Dentate Gyrus In Vivo. PLoS Comput Biol 11:e1004588 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Synapse;
Brain Region(s)/Organism:
Cell Type(s): Dentate gyrus granule GLU cell;
Channel(s):
Gap Junctions:
Receptor(s): AMPA;
Gene(s):
Transmitter(s): Glutamate;
Simulation Environment: NEURON;
Model Concept(s): STDP; Homeostasis;
Implementer(s): Jedlicka, Peter [jedlicka at em.uni-frankfurt.de];
Search NeuronDB for information about:  Dentate gyrus granule GLU cell; AMPA; Glutamate;
COMMENT
This is a synaptic mechanism implementing a form of stream-specific spike-timing-dependent plasticity (STDP).
The mechanism uses simple STDP rule that depends entirely on the interval between the pre- and postsynaptic spikes. This is the nearest-neighbor multiplicative implementation of STDP, that is PRESYNAPTIC CENTRED (Morrison et al. 2008):
each presynaptic spike is paired with the last postsynaptic spike and the next postsynaptic spike.

When a postsynaptic spike occurs, the mechanism receives an event with flag == 2. The FOR_NETCONS loop iterates over all
NetCons that target this particular instance of the synaptic mechanism. It increases each NetCon's weight by
a multiplicative factor that depends on the latency between the time of the most recent event (presyn. spike) that was
delivered by that NetCon and the time of the postsynaptic spike.

When a presynaptic spike occurs, the mechanism receives an event with flag == 0. The weight wE associated with the NetCon
that delivered the spike event is depressed by a multiplicative factor that depends on tpost-t, which is the length of time
that has elapsed since the most recent postsynaptic spike.

The mechanism shown here is a functional model of STDP as opposed to a mechanistic model, which would involve some
representation of the biological processes that account for the plasticity. If you need a mechanistic model of STDP that
involves processes in the presynaptic terminal, then the equations that describe those processes must be explicitly
included in the implementation.

This NMODL code also has a WATCH keyword that can be used to monitor membrane potential at the postsynaptic site for
occurrence of an action potential (helpful for implementing STDP), and a FOR_NETCONS keyword
so that a single instance of an STDP mechanism can deal properly with multiple input streams.

FOR_NETCONS(same, args, as, netreceive) { stmt } iterates over all NetCon objects that have this POINT_PROCESS
or ARTIFICIAL_CELL as the target. The arglist must have the same number of args as the NET_RECEIVE arg list and must have
the same units. If the units are missing, they are inherited by the corresponding arg of the NET_RECEIVE block.
If an arg has the same name, it hides the NET_RECEIVE arg. The purpose is to allow straightforward specification of certain
kinds of plasticity based on post synaptic state in the context of generalized synapses or artificial cells.

ExpSynSTDP is event target, not event source. NetCons convey the fact that an event happened, plus a weight vector and
a flag variable. The flag variable is set by code in the target mechanism's NET_RECEIVE block.


Two state kinetic scheme synapse described by rise time tau1,
and decay time constant tau2. The normalized peak condunductance is 1.
Decay time MUST be greater than rise time.

The solution of A->G->bath with rate constants 1/tau1 and 1/tau2 is
 A = a*exp(-t/tau1) and
 G = a*tau2/(tau2-tau1)*(-exp(-t/tau1) + exp(-t/tau2))
	where tau1 < tau2

If tau2-tau1 -> 0 then we have a alphasynapse.
and if tau1 -> 0 then we have just single exponential decay.

The "factor" is evaluated in the
initial block such that an event of weight 1 generates a
peak conductance of 1.

Because the solution is a sum of exponentials, the
coupled equations can be solved as a pair of independent equations
by the more efficient cnexp method.

ENDCOMMENT

NEURON {
	POINT_PROCESS Exp2SynSTDP_multNNb_globBCM_intscount_precentred
	RANGE tau1, tau2, e, i, dtau, ptau
	RANGE wMax 	:hard bound 
	POINTER d, p	: depression/potentiation factor (additive, non-saturating)
	NONSPECIFIC_CURRENT i
	RANGE g, tpost, start
	:GLOBAL d, p
}

DEFINE EpspTimes 10000	:to store presynaptic epsp times into an array

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

PARAMETER {
	tau1=.1 (ms) <1e-9,1e9>
	tau2 = 10 (ms) <1e-9,1e9>
	e=0	(mV)
	dtau = 36 (ms) 			: depression effectiveness time constant (time it takes to fall from 1->0.37)
	ptau = 26 (ms) 			: Lin et al. (Eur J Neurosci 2006) dtau 36 ms, ptau 26 ms, Bi & Poo (1998, 2001) dtau 34 ms, ptau 17 ms
	wMax = 0.01 (uS)		: hard upper bound 
	start = 30000 (ms)		: synapses are allowed to start changing after start ms
}

ASSIGNED {
	v (mV)
	i (nA)
	g (uS)
	factor
	tpost (ms)
	presyntime[EpspTimes] (ms)	: array to store epsp times
	counter						: to count epsps until first post-AP comes
	total (uS)
	flagOLD
	d							: depression factor (multiplicative to prevent < 0)
	p							: potentiation factor (multiplicative)
}

STATE {
	A (uS)
	B (uS)
}

INITIAL {
	LOCAL tp
	total = 0
	if (tau1/tau2 > .9999) {
		tau1 = .9999*tau2
	}
	A = 0
	B = 0
	tp = (tau1*tau2)/(tau2 - tau1) * log(tau2/tau1)
	factor = -exp(-tp/tau1) + exp(-tp/tau2)
	factor = 1/factor
	tpost = -100000

	FROM i=0 TO EpspTimes-1 {
		presyntime[i]=-1e9
	}
	counter = 0
	
:flag is an implicit argument to NET_RECEIVE. It is an integer, zero by default but a nonzero value can be specified via the second argument to :net_send(). net_send() is used to launch self-events. A self-event comes back to the mechanism that launched it, no NetCon required. 
	net_send(0, 1)
	flagOLD = 1
}

BREAKPOINT { 
	SOLVE state METHOD cnexp
	g = B - A
	i = g*(v - e)
}

DERIVATIVE state {
	A' = -A/tau1
	B' = -B/tau2
}

:The items in the argument list in the NET_RECEIVE statement of a synaptic mechanism are actually the elements of a
:weight vector.  ExpSyn has only one argument in its NET_RECEIVE statement, so a NetCon nc that targets an ExpSyn
:has a weight vector with length 1, which may be called nc.weight or nc.weight[0]. A NetCon called nc that targets
:an ExpSynSTDP or an Exp2SynSTDP has a weight vector with length 2.  The first element, which is called nc.weight[0],
:corresponds to the first item in the NET_RECEIVE argument list--w--which remains constant during a simulation.
:The second element is called nc.weight[1], and it corresponds to wE.
:The value of this second element DOES change as a consequence of STDP.

NET_RECEIVE(w (uS), wE (uS), tpre (ms), X) {
	INITIAL { wE = w  tpre = -1e9	 X=0 }

:When a presynaptic spike occurs, the mechanism receives an event with flag == 0. 
:The printf statements are purely for diagnostic purposes and can be commented out.

	if (flag == 0) { : presynaptic spike  (after last post so depress)
		:printf("entry flag=%g t=%g wInitial=%g wE=%g X=%g tpre=%g tpost=%g\n", flag, t, w, wE, X, tpre, tpost)
		
		A = A + wE*factor
		B = B + wE*factor
		tpre = t
		counter=counter+1				:counting consecutive epsps
		presyntime[counter-1]=tpre		:storing epsp time into an array

:X*w is the amount by which weight is perturbed from its previous level
:"pre before post" spiking potentiates, and "post before pre" spiking depresses.
:Effective synaptic weight is wE 
:The weight wE associated with the NetCon that delivered the spike 
:event is depressed by a multiplicative factor that depends on tpost-t, which is 
:the length of time that has elapsed since the most recent postsynaptic spike.
		 
		if (t>start) {
			X = d*exp((tpost - t)/dtau)
			:wE = wE + X*w	:w is initial weight (uS)
			wE = wE*(1-X)
			if (wE>0) {} else {wE=0}
		}
		flagOLD = flag
	}else if (flag == 2) { : postsynaptic spike
		:printf("entry flag=%g t=%g tpost=%g\n", flag, t, tpost)

:The FOR_NETCONS loop iterates over all NetCons that target this particular instance of the synaptic mechanism. It changes each NetCon's X
: so that it becomes a potentiation factor depending on the latency between the time of the most recent event (spike) that was delivered by that 
: NetCon and the time of the postsynaptic spike.

		FOR_NETCONS(w1, wE1, tpres, X1) { : also can hide NET_RECEIVE args
		:printf("entry FOR_NETCONS w1=%g wE1=%g tpres=%g X1=%g\n", w1, wE1, tpres, X1)
		 
		if (flagOLD==flag) {} else {	:for each postsynaptic spike, only 1 presynaptic spike is considered
							if (t>start) {
								FROM i=0 TO counter-1 {
									X1 = p*exp((presyntime[i] - t)/ptau)
									wE1 = wE1*(1+X1)
								}
								:if (presyntime[counter-1]==tpres) {printf("Yes the last epsp time is correct-it is %g ms", presyntime[counter-1])}	
								if (wE1<wMax) {} else {wE1=wMax}	:hard bounds 
								: postsynaptic spike so clear the epsp times array and set counter to 0
								FROM i=0 TO counter-1 {
									presyntime[i]=-1e9
								}
								counter = 0	
							}
						    } 
		}
		tpost = t 
		:printf("scount=%g at time t=tpost=%g\n", scount, tpost)
		flagOLD=flag
	} else { : flag == 1 from INITIAL block

		:printf("entry flag=%g t=%g\n", flag, t)

:WATCH (var > thresh) flagvalue is used in a NET_RECEIVE block to specify a condition in the postsynaptic cell
:that will generate a self-event with latency 0 and a specified flag value. Generally, WATCH is used to make NEURON
:monitor a variable for threshold crossing, and generates a self event with the specified flag value when the threshold
:is crossed. If the postsynaptic cell is a biophysical model cell, var is usually local membrane potential (or cai or some
:other concentration); if the postsynaptic cell is an artificial spiking cell, var is one of that cell's state variables.
:But WATCH could in principle be anything, such as the total number of spikes that a cell has fired, or perhaps even t (time)

		WATCH (v > -37) 2 	:This mechanism watches postsynaptic membrane potential at the location of the synapse
							:When a postsynaptic spike occurs, the mechanism receives an event with flag == 2
	}
}

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