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;
0_kv.mod *
0_na.mod *
0_nmda.mod *
0_syn_g.mod *
BallStickCell.hoc *
makeSavestates.hoc *
Threshold_Template.hoc *

This simulation builds ball-and-stick neurons with several dendritic length (200 to 1,000 µm dendrites) with active sodium and potassium channels in the soma, AIS, and axon. It then delivers stochastic patterns of synaptic input iteratively to determine the threshold number of synapses necessary to initiate an action potential in the AIS for each dendritic location (typically at 10 µm intervals) and each of seven RMPs (-55 to -85 mV), for inputs having AMPA-only inputs, NMDA-only inputs, or synapses with both AMPA and NMDA conductance. 

1. Compile the .mod files for synaptic conductances and voltage-gated sodium and potassium channels.

2. Run either the "init_BallStick.hoc", "init_BallStick_NoSpines.hoc", or "init_BallStick_Active.hoc" files. They are similar, but the second file generates neurons without dendritic spines (synaptic inputs placed at 1 µm intervals on the dendritic shaft), while the third file generates neurons with active conductances in the dendrite. 

3. All "init" files will first run a "makeSavestates" file that will run the model for 1 second to allow active conductances to reach steady-state (these files begin with "BLen..." and include the dendritic length (e.g., "BLen1000..." for a 1,000 µm dendrite) and RMP ("...stdstt70.dat" for a -70 mV RMP). 

4. Then synaptic thresholds will be found for all dendritic locations and RMPs for ball-and-stick neurons of varying length (200 to 1,000 um). 

5. Output files begin with "Tr0ThLen..." followed by the dendritic length, the membrane potential ("Vxxx") and synaptic conductance type ("A" = AMPA-only, "N"= NMDA-only, and "B" = both AMPA and NMDA). Thus, output file "Tr0ThLen400V75A.dat" will include data for 10 patterns of AMPA-only input in a 400-µm dendrite at -75 mV. Each file returns synaptic thresholds for each of 10 patterns of input (columns) for every 50-µm span of dendritic tree (rows) iterated at 10-µm intervals. 

6. The script at the end of the file can be modified to limit the lengths of dendrites or the RMPs tested.