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Towards a Gold-Standard for Combined TMS and EEG Data Pre-Processing: A critical examination of the effectiveness and reliability of a two tiered independent components analysis approach

Lookup NU author(s): Nik Murphy, Dr Sara Graziadio, Dr Luis Peraza RodriguezORCiD, Professor Lynn Rochester, Professor John-Paul TaylorORCiD



This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).


Combining transcranial magnetic stimulation (TMS) & electroencephalography (EEG) has the potential to expand our understanding of cognitive processes, yet its progress is slowed by the effects of stimulation induced artefacts on the data. Of the methods for TMS artefact removal, independent components analysis (ICA) has seen the most advances. However, the lack of a standard protocol for ICA based TMS artefact removal hinders comparisons between studies. The aims of this study were to evaluate the efficacy of a standardised protocol for TMS artefact removal using ICA, and to determine its reliability. Methods Six participants received occipital TMS, using a figure of eight coil, whilst undergoing 128 channel EEG recorded on a standard amplifier. Two sequential rounds of ICA were applied. The first focussed on identification and removal of artefactual components explaining the greatest proportion of the variance between -40 and +40ms. These served as sources of the decay/recovery artefact, and early muscular responses to TMS. The second round of ICA was performed to identify and remove sources of smaller artefacts present up to 500ms post stimulation. To assess the effect of component removal on signal quality the amplitude of the global field power (GFP) 20ms post stimulus, and the number of GFP maxima associated with the TMS evoked potential (TEP) were recorded at each stage of the protocol. To test the efficacy and reliability of the method the protocol was performed three times per participant. The amplitudes and number of peaks were compared before cleaning and after each round of ICA, within and between cleanings using Friedman’s analysis of variance. Results Component removal reduced the amplitude of the signal within the pulse recovery period whilst maintaining the TEP structure. This effect was observed on all occasions for each participant, and achieved without significant differences in the number of components removed. Conclusions We present evidence for the effective and reliable removal of TMS artefacts from EEG data using a standardised ICA based protocol. We demonstrated that using this procedure yields a clean and unbiased TEP waveform, as indexed by the GFP, thus providing a viable methodology for dealing with artefacts in TMS-EEG.

Publication metadata

Author(s): Murphy N, Tomasevic L, Graziadio S, Peraza LR, Rochester L, Taylor J-P

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: BNA 2015: Festival of Neuroscience

Year of Conference: 2015

Print publication date: 15/04/2015

Date deposited: 13/04/2015

Publisher: British Neuroscience Association (BNA)