Somatosensory evoked potentials are a well-established tool for assessing volley conduction in afferent neural pathways. However, from a clinical perspective, recording of spinal signals is still a demanding task due to the low amplitudes compared to relevant noise sources. Computer modeling is a powerful tool for gaining insight into signal genesis and, thus, for promoting future innovations in signal extraction. However, due to the complex structure of neural pathways, modeling is computationally demanding. We present a theoretical framework which allows computing the electric potential generated by a single axon in a body surface lead by the convolution of the neural lead field function with a propagating action potential term. The signal generated by a large cohort of axons was obtained by convoluting a single axonal signal with the statistical distribution of temporal dispersion of individual axonal signals. For establishing the framework, analysis was based on an analytical model. Our approach was further adopted for a numerical computation of body surface neuropotentials employing the lead field theory. Double convolution allowed straightforward analysis in the frequency domain. The highest frequency components occurred at the cellular membrane. A bandpass type spectral shape and a peak frequency of 1800 Hz was observed. The volume conductor transmitting the signal to the recording lead acted as an additional bandpass reducing the axonal peak frequency from 200 Hz to 500 Hz. The superposition of temporally dispersed axonal signals acted as an additional low-pass filter further reducing the compound action potential peak frequency from 90 Hz to 170 Hz. Our results suggest that the bandwidth of spinal evoked potentials might be narrower than the bandwidth requested by current clinical guidelines. The present findings will allow the optimization of noise suppression. Furthermore, our theoretical framework allows the adaptation in numerical methods and application in anatomically realistic geometries in future studies.

中文翻译：

---

纵向神经道的前导场两域模型-分析框架和信号带宽的含义。

体感诱发电位是一种用于评估传入神经途径中凌空传导的公认工具。然而，从临床的角度来看，由于与相关噪声源相比振幅较低，因此记录脊柱信号仍然是一项艰巨的任务。计算机建模是一种强大的工具，可帮助您深入了解信号起源，从而促进信号提取方面的未来创新。然而，由于神经通路的复杂结构，建模在计算上是需要的。我们提出了一个理论框架，该框架允许通过神经导线场函数与传播动作电位项的卷积来计算由单个轴突在体表导线中产生的电位。由大量轴突产生的信号是通过将单个轴突信号与各个轴突信号的时间色散的统计分布进行卷积得到的。为了建立框架，分析基于分析模型。我们的方法被进一步采用铅场理论进行了体表神经电势的数值计算。双重卷积允许在频域中进行直接分析。最高频率的成分出现在细胞膜上。观察到带通型光谱形状和峰值频率为1800Hz。将信号传输到记录导线的体导体充当附加带通，将轴突峰频率从200 Hz降低到500 Hz。时间分散的轴突信号的叠加充当了一个附加的低通滤波器，进一步将复合动作电位的峰值频率从90 Hz降低到170 Hz。我们的结果表明，脊柱诱发电位的带宽可能比当前临床指南要求的带宽更窄。目前的发现将允许优化噪声抑制。此外，我们的理论框架允许对数值方法进行修改，并在未来的研究中应用于解剖学上实际的几何形状。