The benefits of noise in neural systems: bridging theory and experiment

被引：543

作者：

McDonnell, Mark D. ^{[1
]}

Ward, Lawrence M. ^{[2
,3
]}

机构：

[1] Univ S Australia, Inst Telecommun Res, Computat & Theoret Neurosci Lab, Mawson Lakes, SA 5095, Australia

[2] Univ British Columbia, Dept Psychol, Vancouver, BC, Canada

[3] Univ British Columbia, Brain Res Ctr, Vancouver, BC, Canada

来源：

NATURE REVIEWS NEUROSCIENCE | 2011年 / 12卷 / 07期

基金：

澳大利亚研究理事会; 加拿大自然科学与工程研究理事会;

关键词：

SUPRATHRESHOLD STOCHASTIC RESONANCE; SIGNAL-TRANSDUCTION; COHERENCE RESONANCE; SYNAPTIC NOISE; NEURONS; DYNAMICS; MODEL; PERSPECTIVES; ENHANCEMENT; CHANNELS;

D O I：

10.1038/nrn3061

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

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.

引用

页码：415 / U89

页数：11

共 108 条

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