The maximum-likelihood strategy for determining transcranial magnetic stimulation motor threshold, using parameter estimation by sequential testing is faster than conventional methods with similar precision
The maximum-likelihood strategy for determining transcranial magnetic stimulation motor threshold, using parameter estimation by sequential testing is faster than conventional methods with similar precision
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DOI：
10.1097/00124509-200409000-00007
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发表时间：
2004-09-01
期刊：
影响因子：
2.5
通讯作者：
George, MS
中科院分区：
文献类型：
--
作者：
Mishory, A;Molnar, C;George, MS
静息运动阈值(RMT)是经颅磁刺激(TMS)给药的基本单位。确定RMT的传统方法包括寻找可见运动或肌电(EMG)运动诱发电位的阈值，通常从上到下逼近，然后求平均值。这种耗时的方法通常使用许多TMS脉冲。数学程序可以通过基于先前的结果计算所需的下一个强度来有效地确定阈值。在我们经验丰富的TMS研究人员团队中，我们试图进行一项说明性研究，以比较其中一个方案，即使用顺序测试参数估计的最大似然策略(MLS-PEST)方法，与传统的国际临床神经生理学联合会(IFCN)方法的修改，以确定RMT所需的时间和脉冲以及RMT值。
The resting motor threshold (rMT) is the basic unit of transcranial magnetic stimulation (TMS) dosing. Traditional methods of determining rMT involve finding a threshold of either visible movement or electromyography (EMG) motor-evoked potentials, commonly approached from above and below and then averaged. This time-consuming method typically uses many TMS pulses. Mathematical programs can efficiently determine a threshold by calculating the next intensity needed based on the prior results. Within our group of experienced TMS researchers, we sought to perform an illustrative study to compare one of these programs, the Maximum-Likelihood Strategy using Parameter Estimation by Sequential Testing (MLS-PEST) approach, to a modification of the traditional International Federation of Clinical Neurophysiology (IFCN) method for determining rMT in terms of the time and pulses required and the rMT value.