AIMS: Motor threshold (MT) is an important parameter for the practice of transcranial magnetic stimulation. Our goal was to compare three methods to estimate MT in a clinical setting. METHODS: Comparison of three MT estimation algorithms: 1) the Rossini-Rothwell method consists in lowering stimulus intensity until only five positive responses out of 10 trials are recorded, defining MT; 2) the Mills-Nithi method considers the MT as the mean of an upper threshold (10 positive out of 10 trials) and a lower threshold (0 out of 10 trials); 3) the supervised parametric method estimates the MT by fitting (mathematically and graphically) a sigmoid function on raw data obtained by stimulation at variable intensities. Six MT estimations (two per method) were recorded in a single session in 10 healthy subjects. RESULTS: The within-subject variation of MT (expressed as % of the mean MT+/-standard deviation) during a single session was of 8.5+/-7.2% for the Rossini-Rothwell method, 8.7+/-5.7% for the Mills-Nithi method and 9.5+/-4.0% for the supervised parametric method. No significant differences in variability of MT estimation were found between the methods, but the Rossini-Rothwell method was significantly shorter (half the number of stimuli compared to the two other methods). CONCLUSION: In our setting, Rossini-Rothwell method was superior to the two other methods. The variability of MT estimation measured in our study is important, yet acceptable for clinical applications. However, this variability can be a source of considerable errors in excitability studies and should be a focus of future research.
AIMS: Motor threshold (MT) is an important parameter for the practice of transcranial magnetic stimulation. Our goal was to compare three methods to estimate MT in a clinical setting. METHODS: Comparison of three MT estimation algorithms: 1) the Rossini-Rothwell method consists in lowering stimulus intensity until only five positive responses out of 10 trials are recorded, defining MT; 2) the Mills-Nithi method considers the MT as the mean of an upper threshold (10 positive out of 10 trials) and a lower threshold (0 out of 10 trials); 3) the supervised parametric method estimates the MT by fitting (mathematically and graphically) a sigmoid function on raw data obtained by stimulation at variable intensities. Six MT estimations (two per method) were recorded in a single session in 10 healthy subjects. RESULTS: The within-subject variation of MT (expressed as % of the mean MT+/-standard deviation) during a single session was of 8.5+/-7.2% for the Rossini-Rothwell method, 8.7+/-5.7% for the Mills-Nithi method and 9.5+/-4.0% for the supervised parametric method. No significant differences in variability of MT estimation were found between the methods, but the Rossini-Rothwell method was significantly shorter (half the number of stimuli compared to the two other methods). CONCLUSION: In our setting, Rossini-Rothwell method was superior to the two other methods. The variability of MT estimation measured in our study is important, yet acceptable for clinical applications. However, this variability can be a source of considerable errors in excitability studies and should be a focus of future research.
Authors: S Groppa; A Oliviero; A Eisen; A Quartarone; L G Cohen; V Mall; A Kaelin-Lang; T Mima; S Rossi; G W Thickbroom; P M Rossini; U Ziemann; J Valls-Solé; H R Siebner Journal: Clin Neurophysiol Date: 2012-02-19 Impact factor: 3.708
Authors: Arman Abrahamyan; Colin W G Clifford; Manuela Ruzzoli; Dan Phillips; Ehsan Arabzadeh; Justin A Harris Journal: PLoS One Date: 2011-07-22 Impact factor: 3.240