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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Abstract
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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