BACKGROUND: In Transcranial Magnetic Stimulation (TMS), the Motor Threshold (MT) is the minimum intensity required to evoke a liminal response in the target muscle. Because the MT reflects cortical excitability, the TMS intensity needs to be adjusted according to the subject's MT at the beginning of every TMS session. OBJECTIVE: Shorten the MT estimation process compared to existing methods without compromising accuracy. METHODS: We propose a Bayesian adaptive method for MT determination that incorporates prior MT knowledge and uses a stopping criterion based on estimation of MT precision. We compared the number of TMS pulses required with this new method with existing MT determination methods. RESULTS: The proposed method achieved the accuracy of existing methods with as few as seven TMS pulses on average when using a common prior and three TMS pulses on average when using subject-specific priors. CONCLUSIONS: Our adaptive Bayesian method is effective in reducing the number of pulses to estimate the MT. Copyright Â
BACKGROUND: In Transcranial Magnetic Stimulation (TMS), the Motor Threshold (MT) is the minimum intensity required to evoke a liminal response in the target muscle. Because the MT reflects cortical excitability, the TMS intensity needs to be adjusted according to the subject's MT at the beginning of every TMS session. OBJECTIVE: Shorten the MT estimation process compared to existing methods without compromising accuracy. METHODS: We propose a Bayesian adaptive method for MT determination that incorporates prior MT knowledge and uses a stopping criterion based on estimation of MT precision. We compared the number of TMS pulses required with this new method with existing MT determination methods. RESULTS: The proposed method achieved the accuracy of existing methods with as few as seven TMS pulses on average when using a common prior and three TMS pulses on average when using subject-specific priors. CONCLUSIONS: Our adaptive Bayesian method is effective in reducing the number of pulses to estimate the MT. Copyright Â
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: Stefan M Goetz; Bruce Luber; Sarah H Lisanby; David L K Murphy; I Cassie Kozyrkov; Warren M Grill; Angel V Peterchev Journal: Brain Stimul Date: 2015-09-01 Impact factor: 8.955
Authors: Stefan M Goetz; S M Mahdi Alavi; Zhi-De Deng; Angel V Peterchev Journal: IEEE Trans Neural Syst Rehabil Eng Date: 2019-07-03 Impact factor: 3.802
Authors: Seyed Mohammad Mahdi Alavi; Stefan M Goetz; Angel V Peterchev Journal: IEEE Trans Neural Syst Rehabil Eng Date: 2019-05-03 Impact factor: 3.802