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通过非周期性随机共振增强大鼠SA1皮肤机械感受器中的信息传递

Noise-enhanced information transmission in rat SA1 cutaneous mechanoreceptors via aperiodic stochastic resonance.

作者信息

Collins J J, Imhoff T T, Grigg P

机构信息

NeuroMuscular Research Center, Boston University 02215, USA.

出版信息

J Neurophysiol. 1996 Jul;76(1):642-5. doi: 10.1152/jn.1996.76.1.642.

DOI:10.1152/jn.1996.76.1.642
PMID:8836253
Abstract
  1. Aperiodic stochastic resonance (ASR) is a phenomenon wherein the response of a nonlinear system to a weak aperiodic input signal is optimized by the presence of a particular, nonzero level of noise. Our objective was to demonstrate ASR experimentally in mammalian cutaneous mechanoreceptors. 2. Experiments were performed on rat slowly adapting type 1 (SA1) afferents. Each neuron was subjected to a perithreshold aperiodic stimulus plus noise. The variance of the noise was varied between trials. The coherence between the aperiodic input stimulus and the response of each SA1 afferent was computed. 3. Of the 12 neurons tested, 11 showed clear ASR behavior: as input noise variance was increased, the stimulus-response coherence rapidly increased to a peak and then slowly decreased. These findings were in contrast with those for the average firing rate, which increased monotonically as a function of input noise variance. 4. This work shows that noise can serve to enhance the response of a sensory neuron to a perithreshold aperiodic input signal. These results suggest a possible functional role for input noise in sensory systems. These findings also indicate that it may be possible to introduce noise artificially into sensory neurons to improve their abilities to detect arbitrary weak signals.
摘要
  1. 非周期随机共振(ASR)是一种现象,即非线性系统对微弱非周期输入信号的响应通过特定的非零噪声水平得到优化。我们的目标是在哺乳动物皮肤机械感受器中通过实验证明ASR。2. 对大鼠慢适应1型(SA1)传入神经进行实验。每个神经元都受到阈下非周期刺激加噪声。噪声的方差在各次试验中变化。计算非周期输入刺激与每个SA1传入神经反应之间的相干性。3. 在测试的12个神经元中,11个表现出明显的ASR行为:随着输入噪声方差增加,刺激-反应相干性迅速增加到峰值,然后缓慢下降。这些发现与平均放电率的情况相反,平均放电率随输入噪声方差单调增加。4. 这项工作表明,噪声可用于增强感觉神经元对阈下非周期输入信号的反应。这些结果表明输入噪声在感觉系统中可能具有功能性作用。这些发现还表明,有可能人为地向感觉神经元引入噪声,以提高它们检测任意微弱信号的能力。

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