Endocannabinoid dynamics gate spike-timing dependent depression and potentiation (Cui et al 2016)

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The endocannabinoid (eCB) system is considered involved in synaptic depression. Recent reports have also linked eCBs to synaptic potentiation. However it is not known how eCB signaling may support such bidirectionality. To question the mechanisms of this phenomena in spike-timing dependent plasticity (STDP) at corticostriatal synapses, we combined electrophysiology experiments with biophysical modeling. We demonstrate that STDP is controlled by eCB levels and dynamics: prolonged and moderate levels of eCB lead to eCB-mediated long-term depression (eCB-tLTD) while short and large eCB transients produce eCB-mediated long-term potentiation (eCB-tLTP). Therefore, just like neurotransmitters glutamate or GABA, eCB form a bidirectional system.
1 . Cui Y, Prokin I, Xu H, Delord B, Genet S, Venance L, Berry H (2016) Endocannabinoid dynamics gate spike-timing dependent depression and potentiation. Elife 5:e13185 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Synapse; Channel/Receptor;
Brain Region(s)/Organism:
Cell Type(s): Neostriatum medium spiny direct pathway GABA cell; Neostriatum medium spiny indirect pathway GABA cell; Neostriatum spiny neuron;
Channel(s): I L high threshold; I Calcium; I_SERCA; I Cl, leak; Ca pump;
Gap Junctions:
Receptor(s): AMPA; NMDA; mGluR; Glutamate; IP3;
Simulation Environment: FORTRAN; Python;
Model Concept(s): Ion Channel Kinetics; Coincidence Detection; Parameter Fitting; Synaptic Plasticity; Long-term Synaptic Plasticity; Signaling pathways; STDP; Calcium dynamics; Parameter sensitivity; G-protein coupled; Neuromodulation;
Search NeuronDB for information about:  Neostriatum medium spiny direct pathway GABA cell; Neostriatum medium spiny indirect pathway GABA cell; AMPA; NMDA; mGluR; Glutamate; IP3; I L high threshold; I Calcium; I_SERCA; I Cl, leak; Ca pump;
!    -*- f95 -*-
! (c) 2016 - Ilya Prokin - isprokin@gmail.com - https://sites.google.com/site/ilyaprokin
! INRIA Rhone-Alpes
! STDP model : An implementation of simple AMPAR model of Destexhe, A, Z F Mainen, and T J Sejnowski. “Synthesis of Models for
! Excitable Membranes, Synaptic Transmission and Neuromodulation Using a Common Kinetic Formalism.” Journal of Computational
! Neuroscience 1, no. 3 (August 1994): 195–230.

module AMPA

    use pars_mod
    implicit none


    real*8 function i_AMPA_func(V, o_AMPA, gAMPAmax)
        implicit none
        real*8 :: gAMPAmax,o_AMPA,V
        i_AMPA_func = gAMPAmax*o_AMPA*V
    end function i_AMPA_func

    subroutine o_d_AMPA_IC_setup(glu_bl, pars,  o_AMPA0, d_AMPA0)
        implicit none
        real*8, intent(in) :: glu_bl
        type(pars_type), intent(in) :: pars
        real*8 :: gameps, Ab
        real*8, intent(out) :: o_AMPA0, d_AMPA0
        gameps = pars%AMPA%Gamma/pars%AMPA%Epsilon
        Ab = (pars%AMPA%Beta+pars%AMPA%Gamma)/pars%AMPA%Alpha
        o_AMPA0 = glu_bl/(Ab+(1+gameps)*glu_bl)
        d_AMPA0 = o_AMPA0*gameps
    end subroutine o_d_AMPA_IC_setup

    subroutine do_dd_AMPA(Glu,o_AMPA,d_AMPA,pars,  do_AMPA,dd_AMPA)
        implicit none
        real*8, intent(in) :: Glu,o_AMPA,d_AMPA
        type(pars_type), intent(in) :: pars
        real*8 :: c_AMPA
        real*8, intent(out) :: do_AMPA, dd_AMPA
        ! o_AMPA - open state probatility
        ! d_AMPA - desensetisized state probatility
        ! c_AMPA - closed state probatility
        ! C <-alpha,beta-> O -gamma-> D -Epsilon-> C
        do_AMPA = pars%AMPA%Alpha*Glu*c_AMPA - (pars%AMPA%Beta+pars%AMPA%Gamma)*o_AMPA
        dd_AMPA = -pars%AMPA%Epsilon*d_AMPA + pars%AMPA%Gamma*o_AMPA
    end subroutine do_dd_AMPA

end module AMPA

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