STDP and BDNF in CA1 spines (Solinas et al. 2019)

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Accession:244412
Storing memory traces in the brain is essential for learning and memory formation. Memory traces are created by joint electrical activity in neurons that are interconnected by synapses and allow transferring electrical activity from a sending (presynaptic) to a receiving (postsynaptic) neuron. During learning, neurons that are co-active can tune synapses to become more effective. This process is called synaptic plasticity or long-term potentiation (LTP). Timing-dependent LTP (t-LTP) is a physiologically relevant type of synaptic plasticity that results from repeated sequential firing of action potentials (APs) in pre- and postsynaptic neurons. T-LTP is observed during learning in vivo and is a cellular correlate of memory formation. T-LTP can be elicited by different rhythms of synaptic activity that recruit distinct synaptic growth processes underlying t-LTP. The protein brain-derived neurotrophic factor (BDNF) is released at synapses and mediates synaptic growth in response to specific rhythms of t-LTP stimulation, while other rhythms mediate BDNF-independent t-LTP. Here, we developed a realistic computational model that accounts for our previously published experimental results of BDNF-independent 1:1 t-LTP (pairing of 1 presynaptic with 1 postsynaptic AP) and BDNF-dependent 1:4 t-LTP (pairing of 1 presynaptic with 4 postsynaptic APs). The model explains the magnitude and time course of both t-LTP forms and allows predicting t-LTP properties that result from altered BDNF turnover. Since BDNF levels are decreased in demented patients, understanding the function of BDNF in memory processes is of utmost importance to counteract Alzheimer’s disease.
Reference:
1 . Solinas SMG, Edelmann E, Leßmann V, Migliore M (2019) A kinetic model for Brain-Derived Neurotrophic Factor mediated spike timing-dependent LTP. PLoS Comput Biol 15:e1006975 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Synapse; Dendrite;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA1 pyramidal GLU cell;
Channel(s): I Na,t; I_KD; I K; I h; I A; I Calcium;
Gap Junctions:
Receptor(s): AMPA; NMDA;
Gene(s):
Transmitter(s): Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Facilitation; Long-term Synaptic Plasticity; Short-term Synaptic Plasticity; STDP;
Implementer(s): Solinas, Sergio [solinas at unipv.it]; Migliore, Michele [Michele.Migliore at Yale.edu];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; AMPA; NMDA; I Na,t; I A; I K; I h; I Calcium; I_KD; Glutamate;
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SolinasEtAl2019
mod_files
BDNF.mod
cad.mod
cagk.mod
cal2.mod
can2.mod
cat.mod
distr.mod *
ghknmda.mod
h.mod *
kadist.mod *
kaprox.mod *
kdrca1.mod *
na3n.mod *
naxn.mod *
netstims.mod *
RM_eCB.mod
Wghkampa_preML.mod
                            
TITLE decay of internal calcium concentration
:
: Internal calcium concentration due to calcium currents and pump.
: Differential equations.
:
: Simple model of ATPase pump with 3 kinetic constants (Destexhe 92)
:     Cai + P <-> CaP -> Cao + P  (k1,k2,k3)
: A Michaelis-Menten approximation is assumed, which reduces the complexity
: of the system to 2 parameters: 
:       kt = <tot enzyme concentration> * k3  -> TIME CONSTANT OF THE PUMP
:	kd = k2/k1 (dissociation constant)    -> EQUILIBRIUM CALCIUM VALUE
: The values of these parameters are chosen assuming a high affinity of 
: the pump to calcium and a low transport capacity (cfr. Blaustein, 
: TINS, 11: 438, 1988, and references therein).  
:
: Units checked using "modlunit" -> factor 10000 needed in ca entry
:
: VERSION OF PUMP + DECAY (decay can be viewed as simplified buffering)
:
: All variables are range variables
:
:
: This mechanism was published in:  Destexhe, A. Babloyantz, A. and 
: Sejnowski, TJ.  Ionic mechanisms for intrinsic slow oscillations in
: thalamic relay neurons. Biophys. J. 65: 1538-1552, 1993)
:
: Written by Alain Destexhe, Salk Institute, Nov 12, 1992
:
: This file was modified by Yiota Poirazi (poirazi@LNC.usc.edu) on April 18, 2001 to account for the sharp
: Ca++ spike repolarization observed in: Golding, N. Jung H-Y., Mickus T. and Spruston N
: "Dendritic Calcium Spike Initiation and Repolarization are controlled by distinct potassium channel
: subtypes in CA1 pyramidal neurons". J. of Neuroscience 19(20) 8789-8798, 1999.
:
:  factor 10000 is replaced by 10000/18 needed in ca entry
:  tauca --rate of calcium removal-- is replaced by tauca/7 (7 times faster) 
: It was 200ms, now it is 30ms.


INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}

NEURON {
	SUFFIX cad
	USEION ca READ ica, cai WRITE cai	
        RANGE ca
	RANGE depth,cainf,tauca
	: RANGE far
}

UNITS {
	(molar) = (1/liter)			: moles do not appear in units
	(mM)	= (millimolar)
	(um)	= (micron)
	(mA)	= (milliamp)
	(msM)	= (ms mM)
	FARADAY = (faraday) (coulomb)
}


PARAMETER {
	depth	= .1	(um)		: depth of shell
	tauca	= 30	(ms)		: rate of calcium removal
	cainf	= 100e-6(mM)
	cai		(mM)
}

STATE {
	ca		(mM) 
}

INITIAL {
    ca = cainf
    : far = FARADAY
}

ASSIGNED {
	ica		(mA/cm2)
	drive_channel	(mM/ms)
	: far
}
	
BREAKPOINT {
	SOLVE state METHOD euler
}

DERIVATIVE state { 

	drive_channel =  - (10000) * ica / (2 * FARADAY * depth)
	if (drive_channel <= 0.) { drive_channel = 0.  }   : cannot pump inward 
         
    ca' = drive_channel/18 + (cainf -ca)/tauca
	cai = ca
}

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