Okajima Y, Chino N, Tsubahara A, Kimura A
Department of Rehabilitation Medicine, Keio University School of Medicine, Tokyo, Japan.
Arch Phys Med Rehabil. 1994 Sep;75(9):960-4.
A compound nerve action potential (CNAP) recorded from surface of the skin is composed of single nerve fiber action potentials propagating at various conduction velocities (CVs). Based on this assumption, we constructed two CNAPs simulating those at the digit elicited by stimulation of the median nerve at the wrist (CNAP-Wr) and the elbow (CNAP-El). Distribution of the nerve fiber CVs used for the simulation was estimated from actual recordings of 12 healthy subjects. Mean ratio of the CNAP amplitude (CNAP-Wr/CNAP-El) was 2.2, and that of the duration was 0.76. First, to analyze how CV distributions affect CNAP waveforms artificially in our computer program, we altered mean CV or standard deviation (SD) of the estimated distribution, and reconstructed CNAPs. Results indicated that as the mean CV was made slower, the ratio of the CNAP amplitude increased and that of the duration decreased. Similar changes of the ratios were also shown when the SD of the CV distribution was increased without changing the mean CV. Secondly, to make constructed CNAPs more similar to actual recordings, we added artificial noise to the constructed waves and had 11 electromyographers read onset and peak latencies. The average of maximum CVs calculated from the onset latencies of CNAPs-Wr was 62m/sec, and that from the latency difference between CNAPs-Wr and -El was 70m/sec. Both CVs were slower than the genuine maximum (77m/sec) given to the simulation program. The mean CV calculated from latency difference of the major positive peaks of the CNAPs was 62m/sec being close to the mode (62m/sec) or mean (60m/sec) value of the given distribution.
从皮肤表面记录到的复合神经动作电位(CNAP)由以不同传导速度(CV)传播的单个神经纤维动作电位组成。基于这一假设,我们构建了两个CNAP,模拟通过刺激手腕(CNAP-Wr)和肘部(CNAP-El)的正中神经在手指处引发的电位。用于模拟的神经纤维CV分布是根据12名健康受试者的实际记录估算得出的。CNAP幅度的平均比值(CNAP-Wr/CNAP-El)为2.2,持续时间的平均比值为0.76。首先,为了在我们的计算机程序中人工分析CV分布如何影响CNAP波形,我们改变了估算分布的平均CV或标准差(SD),并重建了CNAP。结果表明,随着平均CV变慢,CNAP幅度的比值增加,持续时间的比值减小。在不改变平均CV的情况下增加CV分布的SD时,也显示出类似的比值变化。其次,为了使构建的CNAP更类似于实际记录,我们在构建的波形中添加了人工噪声,并让11名肌电图专家读取起始和峰值潜伏期。根据CNAP-Wr的起始潜伏期计算出的最大CV平均值为62m/秒,根据CNAP-Wr和-El之间的潜伏期差异计算出的最大CV平均值为70m/秒。这两个CV均慢于模拟程序给出的真实最大值(77m/秒)。根据CNAP主要正峰的潜伏期差异计算出的平均CV为62m/秒,接近给定分布的众数(62m/秒)或均值(60m/秒)。