All sensors have a threshold, defined by the smallest signal amplitude that can be detected.
The detection of sub-threshold signals, however, is possible by using the principle of …

We investigate a novel class of neural stochastic resonance (SR) exhibiting error-free
information transfer. Unlike conventional neural SR, where the decrease of a system's …

Within the framework of information theory, we investigate the phenomenon of stochastic
resonance in a realistic stochastic model of central neurons. The essential point is that, for …

Multiple non-linear systems demonstrate the phenomenon where fluctuations enhance the
synchronization and periodic behaviors of the system. In the phenomenon induced by …

After a decade of doubts, for the first time in the history of stochastic resonance (SR), we
demonstrate that a simple stochastic resonator does greatly improve the signal-to-noise ratio …

In this paper, we evaluate the encoding efficiency of suprathreshold stochastic resonance
(SSR) based on a local information-theoretic measure of stimulus-specific information (SSI) …

The phenomenon of stochastic resonance has recently been found in many systems.
Despite the pre-conception of a destructive role of noise, its constructive role has been …

The random transitions of ion channels between open and closed states are a major source
of noise in neurons. In this study, we investigate the stochastic dynamics of a single Hodgkin …

In this paper I discuss how synchronisation among neurons is affected by noise.
Synchronisation of model neurons, which are basically autonomous relaxation oscillators, is …

Despite a slow start after being introduced in the 1980's, the idea of Stochastic Resonance
spurred since remarkable cross disciplinary interest in natural and social sciences. Ten …