Source-based artifact-rejection techniques available in TESA, an open-source TMS –EEG toolbox

Two recently published artifact-rejection techniques [1,2]; designed for analyzing electroencephalography (EEG) data following transcranial magnetic stimulation (TMS), are now included in an open-source data-analysis toolbox TESA [3]. The new implementations of signal-space-projection –source-informed-reconstruction (SSP–SIR) [1] and source-utilized noise-discarding algorithm (SOUND) [2] are computationally efficient and easy to use, allowing the TMS–EEG researchers to suppress unwanted signal components, such as the TMS-evoked muscle artifact and TMS-pulse-elicited auditor y or somatosensory responses [1,2,4].

Source: BRAIN STIMULATION: Basic, Translational, and Clinical Research in Neuromodulation - July 9, 2020 Category: Neurology Authors: Tuomas P. Mutanen, Mana Biabani, Jukka Sarvas, Risto J. Ilmoniemi, Nigel C. Rogasch Source Type: research