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Semi-automated motor hotspot search (SAMHS): a framework toward an optimised approach for motor hotspot identification. | LitMetric
Background : Motor hotspot identification represents the first step in the determination of the motor threshold and is the basis for the specification of stimulation intensity used for various Transcranial Magnetic Stimulation (TMS) applications. The level of experimenters' experience and the methodology of motor hotspot identification differ between laboratories. The need for an optimized and time-efficient technique for motor hotspot identification is therefore substantial.Objective : With the current work, we present a framework for an optimized and time-efficient semi-automated motor hotspot search (SAMHS) technique utilizing a neuronavigated robot-assisted TMS system (TMS-cobot). Furthermore, we aim to test its practicality and accuracy by a comparison with a manual motor hotspot identification method.Method : A total of 32 participants took part in this dual-center study. At both study centers, participants underwent manual hotspot search (MHS) with an experienced TMS researcher, and the novel SAMHS procedure with a TMS-cobot (hereafter, called cobot hotspot search, CHS) in a randomized order. Resting motor threshold (RMT), and stimulus intensity to produce 1 mV (SI1mV) peak-to-peak of motor-evoked potential (MEP), as well as MEPs with 120% RMT and SI1mV were recorded as outcome measures for comparison.Results : Compared to the MHS method, the CHS produced lower RMT, lower SI1mV and a trend-wise higher peak-to-peak MEP amplitude in stimulations with SI1mV. The duration of the CHS procedure was longer than that of the MHS (15.60 vs. 2.43 min on average). However, accuracy of the hotspot was higher for the CHS compared to the MHS.Conclusions : The SAMHS procedure introduces an optimized motor hotspot determination system that is easy to use, and strikes a fairly good balance between accuracy and speed. This new procedure can thus be deplored by experienced as well as beginner-level TMS researchers.
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