ModelDB is moving. Check out our new site at https://modeldb.science. The corresponding page is https://modeldb.science/151126.

Effects of increasing CREB on storage and recall processes in a CA1 network (Bianchi et al. 2014)

 Download zip file 
Help downloading and running models
Accession:151126
Several recent results suggest that boosting the CREB pathway improves hippocampal-dependent memory in healthy rodents and restores this type of memory in an AD mouse model. However, not much is known about how CREB-dependent neuronal alterations in synaptic strength, excitability and LTP can boost memory formation in the complex architecture of a neuronal network. Using a model of a CA1 microcircuit, we investigate whether hippocampal CA1 pyramidal neuron properties altered by increasing CREB activity may contribute to improve memory storage and recall. With a set of patterns presented to a network, we find that the pattern recall quality under AD-like conditions is significantly better when boosting CREB function with respect to control. The results are robust and consistent upon increasing the synaptic damage expected by AD progression, supporting the idea that the use of CREB-based therapies could provide a new approach to treat AD.
Reference:
1 . Bianchi D, De Michele P, Marchetti C, Tirozzi B, Cuomo S, Marie H, Migliore M (2014) Effects of increasing CREB-dependent transcription on the storage and recall processes in a hippocampal CA1 microcircuit. Hippocampus 24:165-77 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Hippocampus CA1 pyramidal GLU cell; Hippocampus CA1 interneuron oriens alveus GABA cell; Hippocampus CA1 basket cell;
Channel(s): I Na,t; I A; I K; I M; I h; I K,Ca; I Calcium; I_AHP; I Cl, leak; Ca pump;
Gap Junctions:
Receptor(s): GabaA; GabaB; AMPA; NMDA;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): STDP; Aging/Alzheimer`s; Depolarization block; Storage/recall; CREB;
Implementer(s): Bianchi, Daniela [danielabianchi12 -at- gmail.com]; De Michele, Pasquale [pasquale.demichele at unina.it];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; Hippocampus CA1 interneuron oriens alveus GABA cell; GabaA; GabaB; AMPA; NMDA; I Na,t; I A; I K; I M; I h; I K,Ca; I Calcium; I_AHP; I Cl, leak; Ca pump; Gaba; Glutamate;
/
Bianchietal
Results
Weights
readme.txt
ANsyn.mod *
bgka.mod *
burststim2.mod *
cad.mod *
cagk.mod *
cal.mod *
calH.mod *
car.mod *
cat.mod *
ccanl.mod *
d3.mod *
gskch.mod *
h.mod *
IA.mod
ichan2.mod *
Ih.mod *
kadist.mod *
kaprox.mod *
Kaxon.mod *
kca.mod *
Kdend.mod *
kdr.mod *
kdrax.mod *
km.mod *
Ksoma.mod *
LcaMig.mod *
my_exp2syn.mod *
na3.mod *
na3dend.mod *
na3notrunk.mod *
Naaxon.mod *
Nadend.mod *
nap.mod *
Nasoma.mod *
nax.mod *
nca.mod *
nmdanet.mod *
regn_stim.mod *
somacar.mod *
STDPE2Syn2.mod *
axoaxonic_cell17S.hoc *
basket_cell17S.hoc *
bistratified_cell13S.hoc *
burst_cell.hoc *
HAM_SR1.ses
mosinit.hoc
olm_cell2.hoc
PureRec_phase.hoc
PureRec_phase_ser.hoc
pyramidal_cell4.hoc
ranstream.hoc *
stim_cell.hoc *
Sto_phase.hoc
Sto_phase_ser.hoc
                            
: STDP by Hines, changed to dual exponential (BPG 6-1-09)
: Modified by BPG 13-12-08
: Limited weights: max weight is wmax and min weight is wmin
: (initial weight is specified by netconn - usually set to wmin)
: Rhythmic GABAB suppresses conductance and promotes plasticity.
: When GABAB is low, conductance is high and plasticity is off.

NEURON {
	POINT_PROCESS STDPE2
	RANGE tau1, tau2, e, i, d, p, dtau, ptau, thresh, wmax, wmin
	RANGE g, gbdel, gblen, gbint, gscale, factor,dM,dV,B,C
	NONSPECIFIC_CURRENT i
}

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

PARAMETER {
	tau1=.1 (ms) <1e-9,1e9>
	tau2 = 10 (ms) <1e-9,1e9>
	e = 0	(mV)
     pi=3.14159
	wmax = 0.0015 (uS)
      :wmax = 0.005 (uS)
	wmin = 0.0005 (uS)	: not used - use netconn weight instead (BPG)
	d = 8 : depression factor (multiplicative to prevent < 0)
	p = 1.2 : potentiation factor (additive, non-saturating)
	
       dM = -22   (ms)
       dV= 5    (ms)
	 ptau = 10 (ms) : Nishiyama2000

	:thresh = -20 (mV)	: postsynaptic voltage threshold
      thresh = -55 (mV)	: postsynaptic voltage threshold
	gbdel = 50 (ms) <1e-9,1e9> : initial GABAB off interval (ms)
	gbint = 125 (ms) <1e-9,1e9> : GABAB off interval (ms)
	gblen = 125 (ms) <1e-9,1e9> : GABAB on length (ms)
	gscale = 0.4	: relative suppression by GABAB
      
}

ASSIGNED {
	v (mV)
	i (nA)
	tpost (ms)
	on
	g (uS)
	gs
	factor
}

STATE {
	C (uS)
	B (uS)
}

INITIAL {
	LOCAL tp
	if (tau1/tau2 > .9999) {
		tau1 = .9999*tau2
	}
	C = 0
	B = 0
	tp = (tau1*tau2)/(tau2 - tau1) * log(tau2/tau1)
	factor = -exp(-tp/tau1) + exp(-tp/tau2)
	factor = 1/factor    
	gs=1
	on=0	: initially not plastic
	tpost = -1e9
	net_send(0, 1)
	net_send(gbdel, 3)	: initial GABAB off period
}

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

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

NET_RECEIVE(w (uS), A, tpre (ms) ) {
	INITIAL { A = 0  tpre = -1e9 }
	if (flag == 0) { : presynaptic spike  (after last post so depress)
	:	printf("entry flag=%g t=%g w=%g A=%g tpre=%g tpost=%g\n", flag, t, w, A, tpre, tpost)
:		g = g + w + A	: only for single exp (BPG)
		C = C + (w + A)*factor
		B = B + (w + A)*factor
          	:printf(" B %f\t C %f\t w %f\n",B, C, w)
		tpre = t
		if (on == 1) {
			A = A * (1-(d*exp(-((tpost-t)-dM)^2/(2*dV*dV))) /(sqrt(2*pi)*dV))
		}
	}else if (flag == 2 && on == 1) { : postsynaptic spike
:		printf("entry flag=%g t=%g tpost=%g\n", flag, t, tpost)
		tpost = t
            FOR_NETCONS(w1, A1, tp) { : also can hide NET_RECEIVE args
			:printf("entry FOR_NETCONS w1=%g A1=%g tp=%g t=%g\n", w1, A1, tp, t)
			A1 = A1 + (wmax-w1-A1)*p*exp((tp - t)/ptau)
			}
	} else if (flag == 1) { : flag == 1 from INITIAL block
:		printf("entry flag=%g t=%g\n", flag, t)
		WATCH (v > thresh) 2
	}
	else if (flag == 3) { : plasticity control
		if (on == 0) { : start plasticity
			on = 1
			gs = gscale
			net_send(gblen, 3)
		}
		else { : end burst
			on = 0
			gs = 1
			net_send(gbint, 3)
		}
	}
}


Loading data, please wait...