Giannì Matteo, Liberti Micaela, Apollonio Francesca, D'Inzeo Guglielmo
ICEmB at Department of Electronic Engineering, La Sapienza University of Rome, 00184 Rome, Italy.
Biol Cybern. 2006 Feb;94(2):118-27. doi: 10.1007/s00422-005-0029-5. Epub 2005 Dec 21.
Noise has already been shown to play a constructive role in neuronal processing and reliability, according to stochastic resonance (SR). Here another issue is addressed, concerning noise role in the detectability of an exogenous signal, here representing an electromagnetic (EM) field. A Hodgkin-Huxley like neuronal model describing a myelinated nerve fiber is proposed and validated, excited with a suprathreshold stimulation. EM field is introduced as an additive voltage input and its detectability in neuronal response is evaluated in terms of the output signal-to-noise ratio. Noise intensities maximizing spiking activity coherence with the exogenous EM signal are clearly shown, indicating a stochastic resonant behavior, strictly connected to the model frequency sensitivity. In this study SR exhibits a window of occurrence in the values of field frequency and intensity, which is a kind of effect long reported in bioelectromagnetic experimental studies. The spatial distribution of the modeled structure also allows to investigate possible effects on action potentials saltatory propagation, which results to be reliable and robust over the presence of an exogenous EM field and biological noise. The proposed approach can be seen as assessing biophysical bases of medical applications funded on electric and magnetic stimulation where the role of noise as a cooperative factor has recently gained growing attention.
根据随机共振(SR)理论,噪声已被证明在神经元处理和可靠性方面发挥着建设性作用。本文探讨了另一个问题,即噪声在外源信号(这里表示为电磁场)可检测性中的作用。提出并验证了一个类似霍奇金 - 赫胥黎的神经元模型,该模型描述了有髓神经纤维,并由阈上刺激激发。将电磁场作为附加电压输入引入,并根据输出信噪比对其在神经元反应中的可检测性进行评估。清楚地显示了使尖峰活动与外源电磁信号的相干性最大化的噪声强度,表明存在严格与模型频率敏感性相关的随机共振行为。在本研究中,随机共振在场频率和强度值中呈现出一个出现窗口,这是生物电磁实验研究中长期报道的一种效应。所建模型结构的空间分布还允许研究对外源电磁场和生物噪声存在时动作电位跳跃传播的可能影响,结果表明这种传播是可靠且稳健的。所提出的方法可被视为评估基于电和磁刺激的医学应用的生物物理基础,其中噪声作为协同因素的作用最近受到越来越多的关注。