Overview of TMS-EEG analysis

Combining TMS with EEG results in numerous different artifacts which severely distort underlying TMS-evoked neural activity. Here, artifacts are defined as any part of the signal that is not primarily of interest (e.g. TMS-evoked neural activity and other ongoing neural activity). Artifacts can result from interactions between the EEG recording equipment and the large, time-varying magnetic field generated by TMS (TMS pulse artifacts, decay artifacts, electrode noise) or from unwanted physiological signals resulting from TMS (TMS-evoked muscle activity, eye blinks, eye movement, auditory-evoked potentials). Some of these artifacts can be avoided or minimised with appropriate experimental arrangement (e.g. auditory masking to minimise auditory evoked potentials) and careful EEG preparation (e.g. low electrode impedences and cable arrangement to minimise decay artifacts). However, other artifacts are unavoidable. The goal of TMS-EEG cleaning is to remove these artifacts while maintaining the integrity of the neural signal.

Cleaning example. TMS-EEG data before and after cleaning using TESA.

Due to the specialised nature of TMS-EEG analysis, most commercial and open source EEG analysis software do not include the necessary analysis steps to deal with TMS-evoked artifacts. TESA is specifically designed to meet this need. In particular, TESA includes several state-of-the-art methods for removing TMS-evoked muscle activity, an artifact which is difficult to remove due to it's high amplitude. Importantly, TMS-EEG analysis continues to evolve as new and better methods become available. By making the TESA code and user manual open source and accessible through github, users can add new methods as they are developed. Therefore, TESA will serve as a repository for both current and developing methods for TMS-EEG analysis.

For an expanded discussion on artifacts and TMS-EEG analysis, readers are directed to the following papers:

• Rogasch NC & Fitzgerald PB. (2013) Assessing cortical network properties using TMS-EEG. Human Brain Mapping. 34:1652-69.

• Rogasch NC et al. (2013) Short-Latency artifacts associated with concurrent TMS-EEG. Brain Stimulation. 6:868-76.

• Rogasch NC et al. (2014) Removing artefacts from TMS-EEG recordings using independent component analysis: Importance for assessing prefrontal and motor cortex network properties. NeuroImage, 101:425-439.

• Korhonen, Hernandez-Pavon, et al (2011) Removal of large muscle artifacts from transcranial magnetic stimulation-evoked EEG by independent component analysis. Med Biol Eng Compt, 49:397-407.

• Hernandez-Pavon et al (2012) Uncovering neural independent components from highly artifactual TMS-evoked EEG data. J Neurosci Meth, 209:144-57.