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

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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;
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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
                            
TITLE Ca L-type channel with high treshold of activation
: inserted in distal dendrites to account for distally
: restricted initiation of Ca++ spikes
: uses channel conductance (not permeability)
: written by Yiota Poirazi, 1/8/00 poirazi@LNC.usc.edu

NEURON {
	SUFFIX calH
	USEION ca READ eca WRITE ica
        RANGE gcalbar, m, h
	RANGE inf, fac, tau, mytau
}

UNITS {
	(mA) = (milliamp)
	(mV) = (millivolt)
}



PARAMETER {          : parameters that can be entered when function is called in cell-setup
        v               (mV)
        celsius = 34	(degC)
	dt              (ms)
        gcalbar = 0     (mho/cm2) : initialized conductance
	eca = 140       (mV)      : Ca++ reversal potential
      mytau (ms)
        }

STATE {	m h }                     : unknown activation and inactivation parameters to be solved in the DEs  

ASSIGNED {
	ica (mA/cm2)
      inf[2]
	tau[2]

        
}


INITIAL {
      m = 0    : initial activation parameter value
	h = 1    : initial inactivation parameter value
	rate(v)
	
}

BREAKPOINT {
	SOLVE state METHOD cnexp
	ica = gcalbar*m*m*m*h*(v - eca)

}



DERIVATIVE state {  
        rate(v)
        m' = (inf[0]-m)/tau[0]
	  h' = (inf[1]-h)/tau[1]

}

PROCEDURE rate(v (mV)) { :callable from hoc
       FROM i=0 TO 1 {
		tau[i] = vartau(v,i)
		inf[i] = varss(v,i)
	}

     
	
}


FUNCTION varss(v, i) {
	if (i==0) { 
             varss = 1 / (1 + exp((v+37)/(-1)))  : Ca activation 
	}
	else if (i==1) { 
             varss = 1 / (1 + exp((v+41)/(0.5))) : Ca inactivation 
	}
}

FUNCTION vartau(v, i) {
	if (i==0) {
          vartau = mytau  : activation variable time constant
         

        }
	else if (i==1) {
:           vartau = 25   : inactivation variable time constant
           vartau = 29   : inactivation variable time constant
        }
}	


















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