作者: John K. Douglass , Lon Wilkens , Eleni Pantazelou , Frank Moss
DOI: 10.1038/365337A0
关键词: Information theory 、 Signal 、 Stochastic resonance (sensory neurobiology) 、 Stochastic modelling 、 Sensory system 、 Noise (signal processing) 、 Computer science 、 Information transfer 、 Nonlinear system 、 Biological system
摘要: IN linear information theory, electrical engineering and neurobiology, random noise has traditionally been viewed as a detriment to transmission. Stochastic resonance (SR) is nonlinear, statistical dynamics whereby flow in multistate system enhanced by the presence of optimized, noise1–4. A major consequence SR for signal reception that it makes possible substantial improvements detection weak periodic signals. Although recently demonstrated several artificial physical systems5,6, may also occur naturally, an intriguing possibility biological systems have evolved capability exploit optimizing endogenous sources noise. Sensory are obvious place look SR, they excel at detecting signals noisy environment. Here we demonstrate using external applied crayfish mechanoreceptor cells. Our results show individual neurons can provide physiological substrate sensory systems.