Determining the Activation Time Course of Synaptic AMPA Receptors from Openings of Colocalized NMDA Receptors

Abstract

Excitatory postsynaptic currents (EPSCs) in most mammalian central neurons have a fast alpha-amino-3-hydroxy-5-methyl-4-isoazole-proprionic acid (AMPA) receptor-mediated component, lasting a few milliseconds, and a slow N-methyl-D-aspartic acid (NMDA)-receptor-mediated component, lasting hundreds of milliseconds. The time course of the AMPA phase is crucial in the integrative function of neurons, but measuring it accurately is often confounded by cable filtering between the recording electrode and the synapse. We describe a method for recovering the AMPA phase of individual EPSCs by determining the impulse response of the cable filter from single NMDA channel transitions in the slow tails of the same EPSC, then deconvolving the measured AMPA current. Using simulations, we show that filtering of an AMPA conductance transient in a voltage-clamped dendrite behaves in an almost perfectly linear fashion. Expressions are derived for the time course of single channel transitions and the AMPA phase filtered through a voltage-clamped cable or a single exponential filter, using a kinetic model for AMPA receptor activation. Fitting these expressions to experimental records directly estimates the underlying kinetics of the AMPA phase. Example measurements of spontaneous EPSCs in cultured nonpyramidal rat cortical neurons yielded rising time constants of 0.2-0.8 ms, and decay time constants of 1.3-2 ms at 23-25 degrees C.

Contribution of NMDA receptor channels to the expression of LTP in the hippocampal dentate gyrus

“…Each spine was assumed to have only one synapse. The model for the non-NMDAR (AMPAR) conductance was adopted from Kleppe and Robinson (1999):…”

Computational Neurogenetic Modeling: A Methodology to Study Gene Interactions Underlying Neural Oscillations

“…All neuronal parameters and their correspondence to particular proteins in the model presented in this paper are summarized in Table I. They are selected based on their relevance to the spiking activity of a neuron [10][11][12]. Several parameters like the amplitude and time constants of one postsynaptic potential (PSP) are linked to one protein level however their initial values for Eq.…”

“…(3) to choose from are listed in Table II. The value ranges were selected based on neurobiological studies and models [10][11][12] and were further adjusted by experimentation so that the resulting SNN activity was neither too low (no spikes) or too high (too many spikes). In order to find an optimal GRN so that the frequency characteristics of the LFP of the associated SNN are similar to the brain EEG characteristics, we use the following simple optimization procedure: 1.…”

Random dispersion in excitatory synapse response

“…Experimental data and modeling/computational investigations made this field more and more clear, but the synaptic function still remains difficult to understand. Mathematical models-with related computer simulations analyzed almost all the known structural elements of the synapse to stress out how they contribute to shape its response (Agmon and Edelstein 1997;Diamond and Jahr 1997;Freche et al 2011;Kleppe and Robinson 1999;Rabie et al 2006;Savtchenko and Rusakov 2007;Stevens 2003;Trommershäuser et al 2001;Uteshev and Pennefather 1996;Wahl et al 1997). In a series of papers Di Maio 2000, 2003;Ventriglia 2004Ventriglia , 2011Ventriglia and Di Maio 2013a, b), we formulated and investigated a mathematical model of an (hippocampal) excitatory synapse.…”