Analysing concurrent transcranial magnetic stimulation and electroencephalographic data: A review and introduction to the open‐source TESA software
By Nigel C. Rogasch, Caley Sullivan, Richard H. Thomson, Nathan S. Rose, Neil W. Bailey, Paul B. Fitzgerald, Faranak Farzan, Julio C. Hernandez-Pavon. NeuroImage, 2017
354 citations recorded by the source corpus.
ABSTRACT The concurrent use of transcranial magnetic stimulation with electroencephalography (TMS–EEG) is growing in popularity as a method for assessing various cortical properties such as excitability, oscillations and connectivity. However, this combination of methods is technically challenging, resulting in artifacts both during recording and following typical EEG analysis methods, which can distort the underlying neural signal. In this article, we review the causes of artifacts in EEG recordings resulting from TMS, as well as artifacts introduced during analysis (e.g. as the result of filtering over high‐frequency, large amplitude artifacts). We then discuss methods for removing artifacts, and ways of designing pipelines to minimise analysis‐related artifacts. Finally, we introduce the TMS–EEG signal analyser (TESA), an open‐source extension for EEGLAB, which includes functions that are specific for TMS–EEG analysis, such as removing and interpolating the TMS pulse artifact, removing and minimising TMS‐evoked muscle activity, and analysing TMS‐evoked potentials. The aims of TESA are to provide users with easy access to current TMS–EEG analysis methods and to encourage direct comparisons of these methods and pipelines. It is hoped that providing open‐source functions will aid in both improving and standardising analysis across the field of TMS–EEG research. HIGHLIGHTSTMS pulses result in numerous artifacts in concurrent EEG recordings.We review the origins of these artifacts and methods for removing them.We also introduce TESA, an open‐source EEGLAB extension for TMS‐EEG analysis.
Subfields: Cognitive Neuroscience, Neurology
View Paper: https://www.semanticscholar.org/paper/4a212729a06f4775b114f1c1205088f7ffb49823
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Citations in the corpus
- A practical preprocessing pipeline for concurrent TMS-iEEG: Critical steps and methodological considerations (2025, unknown): “The third order was further motivated by enhancing the subsequent filtering by early removal of decay artifacts (Rogasch et al., 2017).”
- Cognitive state dependent enhancement of cognitive control with transcranial magnetic stimulation (2026, unknown): “EEG data from -2 to +15 ms around TMS pulses were removed and interpolated to mitigate high amplitude TMS pulse artifacts, as recommended in standard TMS-EEG procedures 60 .”
- Tuning out emotional distractors by tuning in theta rhythm: improving visual working memory using transcranial magnetic stimulation (2026, unknown): “Then, data were exported in MATLAB 2021b (MathWorks, USA) to utilize the TMS-EEG Signal Analyzer (TESA) EEGLAB plug-in and the TMS artifact correction protocol described by Rogasch et al .”
- Cortical dynamics and network alterations in Parkinson’s disease with mild cognitive impairment: TMS-EEG study of the posterior parietal cortex (2025, unknown): “Pre-processing was performed using MATLAB (Version 2020b, The Math-Works, Natick, MA, United States), the open-source toolbox EEGLAB, and TMS-EEG Signal Analyzer (TESA) 45 , following an established artifact attenuation protocol: Epochs ( − 300 to 500 ms relative to pulse onset) underwent baseline c”
- Top-down and bottom-up interactions rely on nested brain oscillations to shape rhythmic visual attention sampling (2025, unknown): “TMS artifacts were identified and removed using an open-source EEGLab extension, the TMS-EEG signal analyzer [76].”
- Inferring Causality from Noninvasive Brain Stimulation in Cognitive Neuroscience (2020, background): “Unfortunately, direct proof of neuronal entrainment during rhythmic NIBS is currently difficult to impossible because of the strong NIBS-related artifacts (Gebodh et al., 2019; Rogasch et al., 2017; Noury, Hipp, & Siegel, 2016; Herring et al., 2015; Ilmoniemi & Kičić, 2010).”