Noise benefits in spiking retinal and sensory neuron models

  title={Noise benefits in spiking retinal and sensory neuron models},
  author={Anand S Patel and Bart Kosko},
  journal={Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.},
  pages={410-415 vol. 1}
This paper presents two new theorems that give sufficient conditions (and necessary in the first case) for a noise benefit or stochastic-resonance effect in popular spiking models of retinal neurons and sensory neurons. Small amounts of additive white noise increase the neuron's input-output bit count or Shannon mutual information. This stochastic-resonance (SR) effect applies to standard Poisson spiking models of retinal neurons for all possible types of finite-variance noise and for all… CONTINUE READING
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