A model for stochastic resonance-type behavior in sensory perception

Yunfan Gong, Nestor Matthews, and Ning Qian, Physical Review E, 2002 (in press).
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Recently it was found that noise could help improve human detection of sensory stimuli via stochastic resonance-type behavior. Specifically, the ability of an individual to detect a weak tactile stimulus could be enhanced by adding a certain amount of noise. Here we propose, from the perspective of classic signal detection theory, a simple and general model to elucidate the mechanism underlying this novel phenomenon. We demonstrate that noise-mediated enhancements and decrements in human sensation can be well reproduced by our model. The predicted upper bound of the performance improvement by adding noise is also consistent with the experimental data. We suggest additional experiments to further test the model.

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