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Novel approaches to the characterization of coding carried by spike trains are discussed. Measuring firing frequency alone may only partially reflect spike patterning, and can only quantify changes of the most obvious kind. We have devised a method that combines probabilistic and information approaches to quantify the variability of the interspike intervals in a way that is independent of spike frequency. To illustrate the technique, the firing of an oxytocin cell and a vasopressin cell were compared before and after osmotic stimulation. A bimodal lognormal function was fitted to the interspike interval histograms. The entropy of the log interval histogram was used to measure the variability of intervals and to reflect the coding capacity of the cell per spike. A perfect metronome shows no variability in interval and thus has no greater coding capacity than is conveyed by its frequency, whereas the variability of intervals of magnocellular neurones means that their irregular activity has greater potential for coding. While the mean spike frequency increased in both the oxytocin and vasopressin cells in response to osmotic stimulation, the changes in their irregularity showed differences. Osmotic stimulation reduced the entropy of the oxytocin cell, reflecting an increase in the regularity of its spike activity. Conversely, osmotic stimulation had little effect on the entropy of the vasopressin cell. Such differences are not evident from a simple inspection of ratemeter activity. The comparison highlights the limitations of mean spike frequency as a measure of spike coding. Parameters based on the interspike intervals constitute informative measures of spike activity that allow objective comparisons to be made between the activity under different physiological conditions.