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Neurons in the central nervous system are affected by complex and noisysignals due to fluctuations in their cellular environment and in the inputsthey receive from many other cells 1,2. Such noise usually increases theprobability that a neuron will send out a signal to its target cells 2-5. Instochastic resonance, which occurs in many physical and biological systems, anoptimal response is found at a particular noise amplitude 6-9. We have foundthat in a classical neuronal model the opposite can occur - that noise cansubdue or turn off repetitive neuronal activity in both single cells andnetworks of cells. Recent experiments on regularly firing neurons with noisyinputs confirm these predictions 10,11. Surprisingly, we find that in somecases there is a noise level at which the response is a minimum, a phenomenonwhich is called inverse stochastic resonance. Suppression of rhythmic behaviorby noise and inverse stochastic resonance are predicted to occur not only inneuronal systems but more generally in diverse nonlinear dynamical systemswhere a stable limit cycle is attainable from a stable rest state.

The silencing of neuronal activity by noise and the phenomenon of inverse stochastic resonance