NMDA receptors enhance the fidelity of synaptic integration (Li and Gulledge 2021)

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Excitatory synaptic transmission in many neurons is mediated by two co-expressed ionotropic glutamate receptor subtypes, AMPA and NMDA receptors, that differ in their kinetics, ion-selectivity, and voltage-sensitivity. AMPA receptors have fast kinetics and are voltage-insensitive, while NMDA receptors have slower kinetics and increased conductance at depolarized membrane potentials. Here we report that the voltage-dependency and kinetics of NMDA receptors act synergistically to stabilize synaptic integration of excitatory postsynaptic potentials (EPSPs) across spatial and voltage domains. Simulations of synaptic integration in simplified and morphologically realistic dendritic trees revealed that the combined presence of AMPA and NMDA conductances reduces the variability of somatic responses to spatiotemporal patterns of excitatory synaptic input presented at different initial membrane potentials and/or in different dendritic domains. This moderating effect of the NMDA conductance on synaptic integration was robust across a wide range of AMPA-to-NMDA ratios, and results from synergistic interaction of NMDA kinetics (which reduces variability across membrane potential) and voltage-dependence (which favors stabilization across dendritic location). When combined with AMPA conductance, the NMDA conductance balances voltage- and impedance-dependent changes in synaptic driving force, and distance-dependent attenuation of synaptic potentials arriving at the axon, to increase the fidelity of synaptic integration and EPSP-spike coupling across neuron state (i.e., initial membrane potential) and dendritic location of synaptic input. Thus, synaptic NMDA receptors convey advantages for synaptic integration that are independent of, but fully compatible with, their importance for coincidence detection and synaptic plasticity.
1 . Li C, Gulledge AT (2021) NMDA receptors enhance the fidelity of synaptic integration eNeuro
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Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Dentate gyrus granule GLU cell; Hippocampus CA3 pyramidal GLU cell;
Channel(s): I K; I Na,t;
Gap Junctions:
Receptor(s): AMPA; NMDA;
Transmitter(s): Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Synaptic Integration;
Search NeuronDB for information about:  Dentate gyrus granule GLU cell; Hippocampus CA3 pyramidal GLU cell; AMPA; NMDA; I Na,t; I K; Glutamate;
Figure_4_and_5_modified conductances
0_kv.mod *
0_na.mod *
0_syn_g.mod *
BallStickCell.hoc *
makeSavestates.hoc *
Threshold_Template.hoc *

This simulation is identical to that for Figure 2, but incorporates modified conductances:

"0_syn_g.mod" = the normal AMPA conductance (g_max modified to 400 or 250 pS in the "init_BallStick.hoc" file). Point process name is syn_g.

"0_nmda.mod" = the normal NMDA conductance (1 nS max conductance). Point process name is "nmda".

"0_FastNMDA1dot25nS.mod" and "0_FastNMDA3dot15nS.mod" = fast NMDA conductance (point process name for each is "nmda"). These are the NMDA conductance with AMPA-like kinetics, titrated to 1.25 nS and 3.15 nS to add to AMPA conductances of 400 and 250 pS, respectively.

"0_SlowAMPA22.mod" and "0_SlowAMPA45.mod" = slow AMPA conductance (point process name for each is "nmda"). Each is an AMPA conductance with slow, NMDA-like kinetics, but with max conductances set to 22 or 45 pS, respectively, for adding to 400 pS AMPA or 250 pS AMPA, respectively.

"0_nmda345pS.mod" and "0_nmda735pS.mod" = NMDA conductances ("nmda") with g_max set to 345 pS or 735 pS, which are titrated to pair with the 400 pS and 250 pS AMPA conductance, respectively. 

1. For each run type, compile only the relevant mod files ("syn_g.mod" plus one of the other modified conductances) together with the "0_na.mod" and "0_kv.mod" files. 

2. Open "init_BallStick.hoc" and modify 5th line ("AMPA = 2.5" or "AMPA = 4") such that the AMPA (syn_g) conductance is set to 250 or 400 pS, as appropriate for the modified conductances being used. 

3. Run "init_BallStick.hoc". Data output will use the same name convention as in simulations for Figure 2, generating the threshold number of synapses for each dendritic location over ten patterns of stochastic input. Only "B.dat" files (pairing the AMPA conductance with one of the modified conductances) will be generated.