Department of Neurology, University of Minnesota, Minneapolis, MN, United States.
Department of Neurology, University of Minnesota, Minneapolis, MN, United States.
J Neurosci Methods. 2021 Mar 1;351:109045. doi: 10.1016/j.jneumeth.2020.109045. Epub 2020 Dec 24.
In clinical practice, small myelinated sensory fibers, Aδ-fibers, conveying mainly pain and temperature sensations, cannot be examined with available nerve conduction study techniques. Currently, these fibers can only be examined with experimental or very specialized and not commonly available nerve conduction techniques, or only indirectly with cerebral evoked potentials.
This study uses equipment and methods available in clinical neurophysiology laboratories to record from human sensory nerves ≥1000 averaged responses to focal, non-painful stimuli applied by a special electrode to epidermal nerves. The averaged responses to odd numbered stimuli are compared to the averaged responses to even numbered stimuli. An algorithm identifies potentials common in both averages. The 99 and 99.9 percentiles for this algorithm are obtained from control records without stimulation and applied to records with stimulation to identify potentials resulting from stimulation of intraepidermal nerves.
The algorithm identifies numerous negative and positive potentials as being different from controls at the 99th and 99.9 percentile levels. The conduction velocities of the potentials range from of 1.3-29.9 m/s and are compatible with conduction velocities of Aδ-fibers.
COMPARISON WITH EXISTING METHOD(S): No existing methods.
The stimulation, recording and data analysis methods used in this study can be applied in the clinical EMG laboratory to identify Aδ-fibers in human sensory nerves.
在临床实践中,无法使用现有的神经传导研究技术来检查小髓鞘感觉纤维 Aδ 纤维,这些纤维主要传递疼痛和温度感觉。目前,这些纤维只能通过实验或非常特殊且不常用的神经传导技术进行检查,或者只能通过大脑诱发电位间接进行检查。
本研究使用临床神经生理学实验室中可用的设备和方法,记录来自人类感觉神经的≥1000 次平均响应,这些响应是对表皮神经施加特殊电极的局灶性、非疼痛刺激的响应。奇数刺激的平均响应与偶数刺激的平均响应进行比较。一个算法可以识别两个平均值中共同存在的电位。该算法的 99%和 99.9%百分位数是从没有刺激的对照记录中获得的,并应用于有刺激的记录中,以识别源自表皮内神经刺激的电位。
该算法以 99%和 99.9%的百分位数识别出许多与对照记录不同的负性和正性电位。电位的传导速度范围为 1.3-29.9 m/s,与 Aδ 纤维的传导速度相匹配。
没有现有的方法。
本研究中使用的刺激、记录和数据分析方法可应用于临床肌电图实验室,以识别人类感觉神经中的 Aδ 纤维。