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Noise enhancement of signal transduction by parallel arrays of nonlinear neurons with threshold and saturation

机译:具有阈值和饱和度的非线性神经元并行阵列增强信号传导的噪声

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A classic model neuron with threshold and saturation is used to form parallel uncoupled neuronal arrays in charge of the transduction of a periodic or aperiodic noisy input signal. The impact on the transduction efficacy of added noises is investigated. In isolated neurons, improvement by noise is possible only in the subthreshold and in the strongly saturating regimes of the neuronal response. In arrays, improvement by noise is always reinforced, and it becomes possible in all regimes of operation, i.e. in the threshold, in the saturation, and also in the intermediate curvilinear part of the neuronal response. All the configurations of improvement by noise apply equally to periodic and to aperiodic signals. These results extend the possible forms of stochastic resonance or improvement by noise accessible in neuronal systems for the processing of information.
机译:具有阈值和饱和度的经典模型神经元用于形成并行的未耦合神经元阵列,负责周期性或非周期性有噪声输入信号的转导。研究了添加噪声对转导效率的影响。在孤立的神经元中,仅在阈值以下和神经元反应的强烈饱和状态下,通过噪声改善是可能的。在阵列中,噪声的改善总是被加强,并且在所有操作方式中,即在阈值,饱和度以及神经元反应的中间曲线部分中,这都是可能的。所有通过噪声改善的配置均适用于周期性和非周期性信号。这些结果扩展了随机共振或通过在神经元系统中可访问的噪声处理信息而改善的可能形式。

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