P086 A data-driven method for TMS pulse artefact reduction from EEG data: sPCA. Issue 3 (March 2017) - Tomasevic, L.
Abstract : Question: Electroencephalographic recording during transcranial magnetic stimulation (EEG/TMS) is used to investigate the state of cortical activity and connectivity (EEG) relative to the non-invasive stimulation of the cortex (TMS). Amplifiers with high dynamics are used to acquire EEG while TMS is performed, but they record also the whole dynamic of the pulse artefact. This is many orders of magnitude higher than the cortical activity, and here we present the procedure that is able to deal with this artefact: 'the squared principal component analysis (sPCA)'. Methods: First principal component analysis (PCA) was applied on raw data. There the time interval related to the artefact was identified by the derivative. Using the newly identified interval, a second PCA is applied on trials that maximally correlate among them. Finally, the artefact is reduced by selecting the principal component that maximally represents the pulse-related artefact. Results: This pre-processing procedure applied on single subject dataset minimizes the pulse artefact without impacting the recorded cortical activity. The cleaned data are then approachable with standard procedures used in TMS/EEG analysis.. Conclusions: sPCA is an automatic procedure completely data-driven and operator independent. This approach combined with other techniques could give new possibilities to unveil first cortical responses covered by TMS- related artefacts.