Active and resting motor threshold are efficiently obtained with adaptive threshold hunting

Abstract

Transcranial magnetic studies typically rely on measures of active and resting motor threshold (i.e. AMT, RMT). Previous work has demonstrated that adaptive threshold hunting approaches are efficient for estimating RMT. To date, no study has compared motor threshold estimation approaches for measures of AMT, yet this measure is fundamental in transcranial magnetic stimulation (TMS) studies that probe intracortical circuits. The present study compared two methods for acquiring AMT and RMT: the Rossini-Rothwell (R-R) relative-frequency estimation method and an adaptive threshold-hunting method based on maximum-likelihood parameter estimation by sequential testing (ML-PEST). AMT and RMT were quantified via the R-R and ML-PEST methods in 15 healthy right-handed participants in an experimenter-blinded within-subject study design. AMT and RMT estimations obtained with both the R-R and ML-PEST approaches were not different, with strong intraclass correlation and good limits of agreement. However, ML-PEST required 17 and 15 fewer stimuli than the R-R method for the AMT and RMT estimation, respectively. ML-PEST is effective in reducing the number of TMS pulses required to estimate AMT and RMT without compromising the accuracy of these estimates. Using ML-PEST to estimate AMT and RMT increases the efficiency of the TMS experiment as it reduces the number of pulses to acquire these measures without compromising accuracy. The benefits of using the ML-PEST approach are amplified when multiple target muscles are tested within a session.

Effects of lorazepam and baclofen on short‐ and long‐latency afferent inhibition

“…Twenty stimuli were delivered to accurately determine the RMT (Siebner & Rothwell, ; Ah Sen et al . ).…”

No changes in corticospinal excitability, biochemical markers, and working memory after six weeks of high‐intensity interval training in sedentary males

“…Resting motor threshold (RMT) and AMT for FDI were determined at the motor hotspot using the maximum‐likelihood parameter estimation by the sequential testing (ML‐PEST) method (Ah Sen et al. ). The freeware for ML‐PEST (TMS Motor Threshold Assessment Tool, MTAT 2.0) was obtained online (http://www.clinicalresearcher.org/software.html), and the assessment without a priori information option was used.…”

“…The ML‐PEST algorithm was stopped after 20 stimuli (Ah Sen et al. ). During AMT acquisition, the horizontal target line on the oscilloscope provided a visual feedback to participants while they maintained a contraction with their right FDI of 10% MVC.…”

Differences in high-definition transcranial direct current stimulation over the motor hotspot versus the premotor cortex on motor network excitability

“…These results suggest that there is large inter-individual variability in the left motor hotspot and the premotor cortex anatomical localization using canonical methods employed in a majority of tDCS studies (e.g., TMS-defined motor hotspot 6-10,12,38-44 and PMd defined as 2.5 cm anterior to the motor hotspot 45-48 ). In particular, many individuals in the Motor Hotspot group had stimulation sites that were bordering or overlapping with the standard PMd ROIs, or somewhere between the standard M1 and PMd ROIs.…”

“…We defined the left motor hotspot using a canonical definition of the spot at which the maximal MEP peak-to-peak amplitude was recorded in the FDI muscle using a single TMS pulse at a given suprathreshold intensity (starting at 50% of the maximum stimulator output) 38-43 . At this location, we defined the RMT as the intensity of the stimulator that induced an MEP of at least 50 µV peak-to-peak amplitude in 5 out of 10 trials 64 and the TS0.75mV peak-to-peak amplitude in 5 out of 10 trials 62,63 .…”