Nonstationary Stochastic Resonance in a Single Neuron-Like System

Stochastic resonance holds much promise for the detection of weak signals in the presence of relatively loud noise. Following the discovery of nondynamical and of aperiodic stochastic resonance, it was recently shown that the phenomenon can manifest itself even in the presence of nonstationary signals. This was found in a composite system of differentiated trigger mechanisms mounted in parallel, which suggests that it could be realized in some elementary neural networks or nonlinear electronic circuits. Here, we find that even an individual trigger system may be able to detect weak nonstationary signals using stochastic resonance. The very simple modification to the trigger mechanism that makes this possible is reminiscent of some aspects of actual neuron physics. Stochastic resonance may thus become relevant to more types of biological or electronic systems injected with an ever broader class of realistic signals.Comment: Plain Latex, 7 figure

Nonstationary Stochastic Resonance

It is by now established that, remarkably, the addition of noise to a nonlinear system may sometimes facilitate, rather than hamper the detection of weak signals. This phenomenon, usually referred to as stochastic resonance, was originally associated with strictly periodic signals, but it was eventually shown to occur for stationary aperiodic signals as well. However, in several situations of practical interest, the signal can be markedly nonstationary. We demonstrate that the phenomenon of stochastic resonance extends to nonstationary signals as well, and thus could be relevant to a wider class of biological and electronic applications. Building on both nondynamic and aperiodic stochastic resonance, our scheme is based on a multilevel trigger mechanism, which could be realized as a parallel network of differentiated threshold sensors. We find that optimal detection is reached for a number of thresholds of order ten, and that little is gained by going much beyond that number. We raise the question of whether this is related to the fact that evolution has favored some fixed numbers of precisely this order of magnitude in certain aspects of sensory perception.Comment: Plain Latex, 6 figure

Evidence of stochastic resonance in the mating behavior of Nezara viridula (L.)

We investigate the role of the noise in the mating behavior between individuals of Nezara viridula (L.), by analyzing the temporal and spectral features of the non-pulsed type female calling song emitted by single individuals. We have measured the threshold level for the signal detection, by performing experiments with the calling signal at different intensities and analyzing the insect response by directionality tests performed on a group of male individuals. By using a sub-threshold signal and an acoustic Gaussian noise source, we have investigated the insect response for different levels of noise, finding behavioral activation for suitable noise intensities. In particular, the percentage of insects which react to the sub-threshold signal, shows a non-monotonic behavior, characterized by the presence of a maximum, for increasing levels of the noise intensity. This constructive interplay between external noise and calling signal is the signature of the non-dynamical stochastic resonance phenomenon. Finally, we describe the behavioral activation statistics by a soft threshold model which shows stochastic resonance. We find that the maximum of the ensemble average of the input-output cross-correlation occurs at a value of the noise intensity very close to that for which the behavioral response has a maximum.Comment: 6 pages, 4 figures, to appear in EPJ B (2008