Tutorial: TMS resting motor threshold automatic estimation
![](https://hnp.fcbg.ch/wp-content/uploads/2020/02/HNP_neuromod.png)
This page describes the necessary setup, software and steps to automatically and rapidly estimate the resting motor threshold (RMT) of any individual at the NMOD facility at Campus Biotech.
![](https://hnp.fcbg.ch/wp-content/uploads/2021/10/RMTsetup.png)
Bibliography
Check out the following publications for context and details on the TMS amplitude adjustment method:
- Friedemann Awiszus, TMS and Threshold Hunting, Supplements to Clinical Neurophysiology Volume 56, 2003, Pages 13-23; https://www.sciencedirect.com/science/article/abs/pii/S1567424X09702053
- HR Lieberman and AP Pentland, Microcomputer-based estimation of psychophysical thresholds: The Best PEST, Behavior Research Methods & Instrumentation 1982, Vol. 14 (1),21-25; https://link.springer.com/article/10.3758/BF03202110
- AP Pentland, Maximum Likelihood Estimation: the best PEST, Perception & Psychophysics 1980, 28 (4), 377-79; https://pubmed.ncbi.nlm.nih.gov/7465322/
- Ah Sen CB, Fassett HJ, El-Sayes J, Turco CV, Hameer MM, Nelson AJ (2017) Active and resting motor threshold are efficiently obtained with adaptive threshold hunting. PLoS ONE 12(10): e0186007. https://doi.org/10.1371/journal.pone.0186007
Setup
- Connect the TMS (MagVenture/MagStim) to the NMOD desktop computer using the vendor serial cable.
- Turn on the EMG desktop WIFI receiver and activate one EMG sensor – with a 156ms delay.
- Turn on the CED Power3 1401 and connect the relevant EMG to the first digital port “0”.
- Connect the TMS Trigger Out coaxial ourput to the “Trigger” port of the CED Power3 1401.
Software
- Start Matlab 2017b on the NMOD facility desktop computer.
- Run the code MTAT_fcbg_rest.m, a modified version of the program written by Prof. Dr. F. Awiszus (friedemann.awiszus@med.ovgu.de) compatible with the hardware available inside the NMOD facility.
- The matlab program MTAT_fcbg_rest connects to the TMS and iteratively:
- adjust the TMS amplitude to minimize the uncertainty on the RMT
- wait for the TMS air trigger pedal to deliver the TMS pulse
- record the EMG
- accepts / repeats the measurement based on the EMG baseline level before the TMS pulse
- analyzes the EMG data and calculates the 95% confidence interval on the RMT
- Exit the loop if RMT is certain.
Note:
- This process converges rapidly towards the RMT (~40 sec).
- If necessary, the default threshold (200 uV) can be easily modified in the code MTAT_fcbg_rest.m
- Do not start Signal in order to avoid CED control issues between Matlab and Signal.
Display
![](https://hnp.fcbg.ch/wp-content/uploads/2021/11/Tuto_MTAT_1.png)
Example of Matlab-based EMG data recording.
Counting the number of positive MEP (ie above RMT) is extremely time consuming and requires user interaction to count and/or adjust the TMS amplitude.
By contrast, the automatic MTAT_fcbg_rest program is fast and fully automatic. The experimenter only needs to press the TMS pedal every 3 seconds to send the adjusted TMS pulse.
![](https://hnp.fcbg.ch/wp-content/uploads/2021/11/Tuto_MTAT_2.png)