Enhancing aperiodic stochastic resonance through noise modulation.

We show that the conventional stochastic resonance (SR) effect for aperiodic signals in a model neuron can be enhanced by modulating the intensity of the input noise (which could be introduced artificially in bioengineering applications) with either the input signal or the unit's output rate signal. We analyze SR enhancement theoretically and numerically. We discuss how this work provides the theoretical foundation for the development of an optimal noise-based technique for enhancing sensory function.

Using electrical noise to enhance the ability of humans to detect subthreshold mechanical cutaneous stimuli.

Stochastic resonance (SR) is a phenomenon wherein the response of a nonlinear system to a weak input signal is optimized by the presence of a particular, nonzero level of noise. Our objective was to demonstrate cross-modality SR in human sensory perception. Specifically, we were interested in testing the hypothesis that the ability of an individual to detect a subthreshold mechanical cutaneous stimulus can be significantly enhanced by introducing a particular level of electrical noise.