Fast information transfer in neuronal systems rests on series of action potentials, the spike trains, conducted along axons. Methods that compare spike trains are crucial for characterizing different neuronal coding schemes. In this paper we review recent results on the notion of spiking randomness, and discuss its properties with respect to the rate and temporal coding schemes. This method is compared with other widely used characteristics of spiking activity, namely the variability of interspike intervals, and it is shown that randomness and variability provide two distinct views. We demonstrate that estimation of spiking randomness from simulated and experimental data is capable of capturing characteristics that would otherwise be difficult to obtain with conventional methods.

Spontaneous firing of olfactory receptor neurons (ORNs) was recently shown to be required for the survival of ORNs and the maintenance of their appropriate synaptic connections with mitral cells in the olfactory bulb. ORN spontaneous activity has never been described or characterized quantitatively in mammals. To do so we have made extracellular single unit recordings from ORNs of freely breathing (FB) and tracheotomized (TT) rats. We show that the firing behavior of TT neurons was relatively simple: they tended to fire spikes at the same average frequency according to purely random (Poisson) or simple (Gamma or Weibull) statistical laws. A minority of them were bursting with relatively infrequent and short bursts. The activity of FB neurons was less simple: their firing rates were more diverse, some of them showed trends or were driven by breathing. Although more of them were regular, only a minority could be described by simple laws; the majority displayed random bursts with more spikes than the bursts of TT neurons. In both categories bursts and isolated spikes (outside bursts) occurred completely at random. The spontaneous activity of ORNs in rats resembles that of frogs, but is higher, which may be due to a difference in body temperature. These results suggest that, in addition to the intrinsic thermal noise, spontaneous activity is provoked in part by mechanical, thermal, or chemical (odorant molecules) effects of air movements due to respiration, this extrinsic part being naturally larger in FB neurons. It is suggested that spontaneous activity may be modulated by respiration. Because natural sampling of odors is synchronized with breathing, such modulation may prepare and keep olfactory bulb circuits tuned to process odor stimuli.

The concept of coding efficiency holds that sensory neurons are adapted, through both evolutionary and developmental processes, to the statistical characteristics of their natural stimulus. Encouraged by the successful invocation of this principle to predict how neurons encode natural auditory and visual stimuli, we attempted its application to olfactory neurons. The pheromone receptor neuron of the male moth Antheraea polyphemus, for which quantitative properties of both the natural stimulus and the reception processes are available, was selected. We predicted several characteristics that the pheromone plume should possess under the hypothesis that the receptors perform optimally, i.e., transfer as much information on the stimulus per unit time as possible. Our results demonstrate that the statistical characteristics of the predicted stimulus, e.g., the probability distribution function of the stimulus concentration, the spectral density function of the stimulation course, and the intermittency, are in good agreement with those measured experimentally in the field. These results should stimulate further quantitative studies on the evolutionary adaptation of olfactory nervous systems to odorant plumes and on the plume characteristics that are most informative for the ‘sniffer’. Both aspects are relevant to the design of olfactory sensors for odour-tracking robots.