The Biophysical Basis of Firing Variability in Cortical Neurons - Computational Neuroscience: A Comprehensive Approach - page 160

5mV
2mV

500ms

Figure 6.2
An ensemble measurement of EPSPs in a layer 2/3 pyramidal neuron. Top 6 traces:
individual trials. Red trace, ensemble average. Dotted lines indicate times at which
presynaptic neuron is stimulated. Recording by Ingo Kleppe, Dept. of Physiology,
University of Cambridge. (See color insert.)

there is an increased probability of failure, and vice versa [59]. In other words, there
are significant correlations over time in the variability at individual synapses, as in-
deed there are in the mean synaptic response. These have been shown to extend
over surprisingly long time scales, of several minutes or more during natural-like
spike trains [35]. Further understanding of the variability or reliability of individual
synapses over time during complex, natural input, is an important goal. One might
think that the effect of synaptic fluctuations will be averaged away because there are
large numbers of synapses per cell. However even if many inputs are active, only
one completes the job of taking the voltage over threshold. As will be discussed fur-
ther below, the nonlinear threshold behaviour of neurons means that the properties
of essentially any input fluctuations, however small, can determine the firing pattern
of the cell - it all depends on the proximity of the spike generation mechanism to its
threshold.