Real-time posterior probabilistic TMS motor mapping with robust individualized stopping criteria
Renxiang Qiu, Zi‐Jian Feng, Ole Numssen, Yu‐Feng Zang, Florian Wilhelmy, Erdem Güresir, Thomas R. Knösche, Konstantin Weise
This paper develops a real-time TMS motor mapping method using rank correlation and posterior probability maps, improving efficiency and individualization over traditional sigmoid fitting.
bioRxiv · Oct 14, 2026 · PreprintNeuroscience