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Publication Detail
TMS-evoked long-lasting artefacts: A new adaptive algorithm for EEG signal correction.
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Article
  • Authors:
    Casula EP, Bertoldo A, Tarantino V, Maiella M, Koch G, Rothwell JC, Toffolo GM, Bisiacchi PS
  • Publication date:
    09/2017
  • Pagination:
    1563, 1574
  • Journal:
    Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
  • Volume:
    128
  • Issue:
    9
  • Medium:
    Print-Electronic
  • Print ISSN:
    1388-2457
  • Language:
    eng
  • Addresses:
    Non-invasive Brain Stimulation Unit, IRCCS Santa Lucia Foundation, Rome, Italy; Department of General Psychology, University of Padua, Padua, Italy; Sobell Department of Motor Neuroscience and Movement Disorders, University College London, London, United Kingdom. Electronic address: elias.casula@gmail.com.
Abstract
During EEG the discharge of TMS generates a long-lasting decay artefact (DA) that makes the analysis of TMS-evoked potentials (TEPs) difficult. Our aim was twofold: (1) to describe how the DA affects the recorded EEG and (2) to develop a new adaptive detrend algorithm (ADA) able to correct the DA.We performed two experiments testing 50 healthy volunteers. In experiment 1, we tested the efficacy of ADA by comparing it with two commonly-used independent component analysis (ICA) algorithms. In experiment 2, we further investigated the efficiency of ADA and the impact of the DA evoked from TMS over frontal, motor and parietal areas.Our results demonstrated that (1) the DA affected the EEG signal in the spatiotemporal domain; (2) ADA was able to completely remove the DA without affecting the TEP waveforms; (3). ICA corrections produced significant changes in peak-to-peak TEP amplitude.ADA is a reliable solution for the DA correction, especially considering that (1) it does not affect physiological responses; (2) it is completely data-driven and (3) its effectiveness does not depend on the characteristics of the artefact and on the number of recording electrodes.We proposed a new reliable algorithm of correction for long-lasting TMS-EEG artifacts.
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