Remove TMS-evoked muscle activity and other artifacts
Last updated
Last updated
Perhaps the most challenging issue with TMS-EEG research is recovering neural activity from the large TMS-evoked muscle artifact resulting from stimulation of scalp muscles. Ideally, these artifacts can be avoided by stimulating close to the mid-line away from scalp muscles. However, this is not always possible, especially if the region of interest for TMS stimulation is more lateral. The best methods for accurately recovering neural activity from such artifacts is currently an active area of research. TESA provides a collection of different methods for removing or minimising TMS-evoked muscle activity including: independent component analysis using the FastICA algorithm (we also provide a method for using rules to automatically classify artifact components), an alternative FastICA algorithm called the enhanced deflation method, principal component analysis and several ways of detrending the data.
Example 1 - comparison of methods for removing TMS-evoked muscle activity. For FastICA, three components were removed, for EDM three components were removed, and for PCA suppression one component was removed.
In addition to TMS-evoked artifacts, several other artifacts which are common to regular EEG recordings also distort the TMS-evoked neural signal. Such artifacts include: eye blinks, eye movement, persistent muscle activity and electrode noise. FastICA with automatic component classification available in TESA can also be used to remove these artifacts.
Example 2 - removal of additional artifacts using FastICA and automatic component selection. Of the 59 components, 3 residual TMS-evoked muscle activity artifacts, 3 eye blink/movement, 19 persistent muscle and 10 electrode noise components were removed.
