Analysis of fluctuations of "minimal" excitatory postsynaptic potentials during long-term potentiation in guinea pig hippocampal slices

Noise deconvolution based on the L1-metric and decomposition of discrete distributions of postsynaptic responses

A statistical approach to analysis of amplitude fluctuations of postsynaptic responses is described. This includes (1) using a L1-metric in the space of distribution functions for minimisation with application of linear programming methods to decompose amplitude distributions into a convolution of Gaussian and discrete distributions; (2) deconvolution of the resulting discrete distribution with determination of the release probabilities and the quantal amplitude for cases with a small number (< 5) of discrete components. The methods were tested against simulated data over a range of sample sizes and signal-to-noise ratios which mimicked those observed in physiological experiments. In computer simulation experiments, comparisons were made with other methods of 'unconstrained' (generalized) and constrained reconstruction of discrete components from convolutions. The simulation results provided additional criteria for improving the solutions to overcome 'over-fitting phenomena' and to constrain the number of components with small probabilities. Application of the programme to recordings from hippocampal neurones demonstrated its usefulness for the analysis of amplitude distributions of postsynaptic responses.

Changes in quantal parameters of EPSCs in rat CA1 neurones in vitro after the induction of long-term potentiation

1. Long-term potentiation (LTP) was induced in EPSCs evoked in CA1 pyramidal neurones of young rats in vitro by extracellular stimulation of stratum radiatum. Low frequency stimulation was paired with postsynaptic depolarization to induce LTP, using whole-cell recording techniques. 2. Sufficient control and potentiated records were obtained under stable recording conditions to allow a quantal analysis of eleven EPSCs. The fluctuations in amplitude of all eleven EPSCs were quantized before conditioning stimulation, and they remained quantized after LTP induction, usually with an increased quantal variance. 3. Quantal current was increased by conditioning for nine out of eleven EPSCs. The increase in quantal current was correlated with the percentage increase in the EPSC. For only two EPSCs could the entire potentiation be attributed to an increase in quantal current. 4. The amplitude fluctuations of five control EPSCs could be described by binomial statistics, but after conditioning the binomial description held for only one of these EPSCs. For this EPSC, conditioning caused the release probability to increase from 0.39 +/- 0.05 to 0.47 +/- 0.02. 5. Quantal content was increased by conditioning stimulation for ten out of eleven EPSCs. The increase in quantal content was correlated with the percentage increase in the EPSC. However, for only four EPSCs could the entire potentiation be attributed to an increase in quantal content. 6. Most EPSCs were evoked with a high proportion of response failures. The probability of response failures decreased in eight out of eleven EPSCs following the induction of LTP. There was a negative correlation between the change in the probability of response failures and the amount of LTP. 7. The minimal number of sites at which transmission occurred increased for ten out of eleven EPSCs following LTP induction. Increases in the minimal number of active sites following conditioning were associated with decreases in the probability of response failures for seven out of eleven EPSCs. 8. The induction of LTP usually resulted in changes in the time course of the EPSCs. Cable analysis using a passive compartmental model of a CA1 pyramidal cell suggested that these time course changes were associated with shifts in the average electrotonic location of the active sites following LTP induction, rather than being caused by an increased duration of synaptic current. 9. LTP expression involves postsynaptic modifications to enhance the synaptic current at active sites. New sites are recruited, and our data cannot be used to determine if this is a result of a pre- or a postsynaptic change. Evidence for an increase in release probability was found for one EPSC.

Quantal parameters of "minimal" excitatory postsynaptic potentials in guinea pig hippocampal slices: binomial approach

Binomial distributions of amplitudes of excitatory postsynaptic potentials (EPSPs) mixed with Gaussian noise were simulated. The objective of Monte Carlo simulations was, firstly, to study influences of sampling size (N) and noise standard deviation (Sn) on estimates of mean quantal content (m), quantal size (v) and binomial parameters (n and p) by four methods of quantal analysis (histogram, variance, failures and combined method) based on the binomial model and, secondly, to modify these methods on the basis of comparison of estimated with simulated parameters. Reliable estimates (within +/- 10% of the simulated values) were obtained for large sample sizes (N = 500-1000) with Sn less than or equal to v by the histogram (deconvolution) method and with Sn less than or equal to 2v by the other three methods. Similar results were obtained by averages from about 10 simulations if smaller samples were used (N = 50-200). In electrophysiological experiments on slices, "minimal" EPSPs were recorded from CA1 pyramidal cells after low-intensity stimuli to stratum radiatum or stratum oriens. Amplitudes of minimal EPSPs fluctuated in a manner predicted by the quantum hypothesis. Amplitude distributions of EPSPs in the non-facilitated state were adequately described either by binomial statistics with an average p equal to about 0.4 (a range of 0.3-0.7) and an average n of about 3 (range 2-6) or by Poisson statistics with m of about 1. The quantal analysis suggests that typical values of m and v for a single activated fibre in stratum radiatum might be about 0.5-1 and 300-400 microV, respectively, with low p (0.1-0.3) and n (2-4). However, the estimates of binomial parameters should be considered as coarse approximations in view of the simulation results and a possible nonuniformity of parameter p. The comparison of results of various methods based on the binomial model, in both simulation and physiological experiments, indicates the reliability of estimates of basic quantal parameters (m and v) under realistic conditions of physiological experiments. The methods are considered to be sufficiently sensitive to make use of them for studies on mechanisms of long-term synaptic plasticity.