The Computational and Theoretical Neuroscience Laboratory, Institute for Telecommunications Research, University of South Australia, Mawson Lakes, SA 5095, Australia.
Nat Rev Neurosci. 2011 Jun 20;12(7):415-26. doi: 10.1038/nrn3061.
Although typically assumed to degrade performance, random fluctuations, or noise, can sometimes improve information processing in non-linear systems. One such form of 'stochastic facilitation', stochastic resonance, has been observed to enhance processing both in theoretical models of neural systems and in experimental neuroscience. However, the two approaches have yet to be fully reconciled. Understanding the diverse roles of noise in neural computation will require the design of experiments based on new theory and models, into which biologically appropriate experimental detail feeds back at various levels of abstraction.
虽然随机波动或噪声通常被认为会降低性能，但在非线性系统中，它们有时也可以改善信息处理。一种这样的“随机促进”形式，即随机共振，已经在神经系统的理论模型和实验神经科学中观察到可以增强处理。然而，这两种方法尚未完全协调一致。要理解噪声在神经计算中的多种作用，需要根据新的理论和模型设计实验，将生物上合适的实验细节在不同的抽象层次上反馈回来。
