Definition
Neural oscillators can be reduced to simple one-dimensional models where the only variable is the time-like phase of the oscillator. If the inputs to the oscillator are small enough, this phase description remains valid even if the inputs are “noisy.” Using the noisy phase description of an oscillator allows us to do many otherwise difficult calculations. We review these calculations in this entry.
Detailed Description
Noise is ubiquitous in the nervous system and has been the subject of many experimental and theoretical studies (Laing and Lord 2009). Most of the techniques for analyzing the effects of noise depend on the use of very simple models such as the leaky integrate-and-fire model or other scalar models. Many neurons generate periodic firing (oscillations) when subjected to a tonic drive but because they are subjected to many uncontrolled environmental inputs, the oscillations are subjected to noise. In absence of any inputs a deterministic limit-cycle oscillator...
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References
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Ermentrout, G.B. (2014). Phase Models, Noisy. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_265-1
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DOI: https://doi.org/10.1007/978-1-4614-7320-6_265-1
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