A review on methods for offline removing of artifacts in electroencephalography induced by transcranial magnetic stimulation_Journal of Biomedical Engineering

Authors：

YIN Shan ¹ ,  LI Yingjie ^1,2

1. Institute of Biomedical Engineering, school of Communication and Information Engineering, Shanghai University, Shanghai 200444, P.R.China;
2. Qianweichang College, Shanghai University, Shanghai 200444, P.R.China;

Corresponding author：

Keywords：

transcranial magnetic stimulation; electroencephalogram; artifacts removing

DOI：

10.7507/1001-5515.201802011

Video：

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Transcranial magnetic stimulation (TMS) combined with electroencephalography(EEG) has become an important tool in brain research. However, it is difficult to remove the large artifacts in EEG signals caused by the online TMS intervention. In this paper, we summed up various types of artifacts. After introducing a variety of online methods, the paper emphasized on offline approaches, such as subtraction, principal component analysis and independent component analysis, which can remove or minimize TMS-induced artifacts according to their different characteristics. Although these approaches can deal with most of the artifacts induced by TMS, the removal of large artifacts still needs to be improved. This paper systematically summarizes the effective methods for artifacts removal in TMS-EEG studies. It is a good reference for TMS-EEG researchers while choosing the suitable artifacts removal methods.

Citation： YIN Shan, LI Yingjie. A review on methods for offline removing of artifacts in electroencephalography induced by transcranial magnetic stimulation. Journal of Biomedical Engineering, 2019, 36(1): 146-150. doi: 10.7507/1001-5515.201802011 Copy

1.	Farzan F, Vernet M, Shafi M M, et al. Characterizing and modulating brain circuitry through transcranial magnetic stimulation combined with electroencephalography. Front Neural Circuits, 2016, 10: 73.
2.	Bergmann T O, Karabanov A, Hartwigsen G A, et al. Combining non-invasive transcranial brain stimulation with neuroimaging and electrophysiology: current approaches and future perspectives. Neuroimage, 2016, 140(8): 4-19.
3.	Ilmoniemi R J, Hernandezpavon J C, Makela N N, et al. Dealing with artifacts in TMS-evoked EEG//37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Milan: IEEE, 2015: 230.
4.	Ives J R, Rotenberg A, Poma R, et al. Electroencephalographic recording during transcranial magnetic stimulation in humans and animals. Clinical Neurophysiology, 2006, 117(8): 1870-1875.
5.	Mutanen T, Maki H, Ilmoniemi R J. The effect of stimulus parameters on TMS-EEG muscle artifacts. Brain Stimul, 2013, 6(3): 371-376.
6.	Ter Braack E M. de Vos C C, van Putten M J M J A M Masking the auditory evoked potential in TMS-EEG: a comparison of various methods. Brain Topogr, 2015, 28(3): 520-528.
7.	Rogasch N C, Fitzgerald P B. Assessing cortical network properties using TMS-EEG. Hum Brain Mapp, 2013, 34(7): 1652-1669.
8.	Rogasch N C, Sullivan C, Thomson R H, et al. Analysing concurrent transcranial magnetic stimulation and electroencephalographic data: a review and introduction to the open-source TESA software. Neuroimage, 2017, 147: 934-951.
9.	Tanner D, Morgan-Short K, Luck S J. How inappropriate high-pass filters can produce artifactual effects and incorrect conclusions in ERP studies of language and cognition. Psychophysiology, 2015, 52(8): 997-1009.
10.	Ruddy K L, Woolley D G, Mantini D, et al. Improving the quality of combined EEG-TMS neural recordings: introducing the coil spacer. J Neurosci Methods, 2018, 294: 34-39.
11.	Petrichella S, Johnson N, He B. The influence of corticospinal activity on TMS-evoked activity and connectivity in healthy subjects: a TMS-EEG study. PLoS One, 2017, 12(4): e0174879.
12.	Chung S W, Lewis B P, Rogasch N C, et al. Demonstration of short-term plasticity in the dorsolateral prefrontal cortex with theta burst stimulation: a TMS-EEG study. Clinical Neurophysiology, 2017, 128(7): 1117-1126.
13.	Reichenbach A, Whittingstall K, Thielscher A. Effects of transcranial magnetic stimulation on visual evoked potentials in a visual suppression task. Neuroimage, 2011, 54(2): 1375-1384.
14.	Rogasch N C, Thomson R H, Farzan F A, et al. Removing artefacts from TMS-EEG recordings using independent component analysis: importance for assessing prefrontal and motor cortex network properties. Neuroimage, 2014, 101: 425-439.
15.	Thut G, Northoff G, Ives J R, et al. Effects of single-pulse transcranial magnetic stimulation (TMS) on functional brain activity: a combined event-related TMS and evoked potential study. Clin Neurophysiol, 2003, 114(11): 2071-2080.
16.	Verhagen L, Dijkerman H C, Medendorp W . Cortical dynamics of sensorimotor integration during grasp planning. Journal of Neuroscience, 2012, 32(13): 4508-4519.
17.	Rose N S, Larocque J J, Riggall A C, et al. Reactivation of latent working memories with transcranial magnetic stimulation. Science, 2016, 354(6316): 1136-1139.
18.	Ter Braack E M. de Jonge Benjamin, van Putten M J A M Reduction of TMS induced artifacts in EEG using principal component analysis. IEEE Trans Neural Syst Rehabil Eng Publ, 2013, 21(3): 376-382.
19.	Mutanen T P, Kukkonen M, Nieminen J O, et al. Recovering TMS-evoked EEG responses masked by muscle artifacts. Neuroimage, 2016, 139: 157-166.
20.	Korhonen R J, Hernandez-Pavon J C, Metsomaa J, et al. Removal of large muscle artifacts from transcranial magnetic stimulation-evoked EEG by independent component analysis. Med Biol Eng Comput, 2011, 49(4): 397-407.
21.	Chaumon M, Bishop D V, Busch N A. A practical guide to the selection of independent components of the electroencephalogram for artifact correction. J Neurosci Methods, 2015, 250(SI): 47-63.
22.	Winkler I, Debener S, Mueller K . On the influence of high-pass filtering on ICA-based artifact reduction in EEG-ERP//2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015: 4101-4105.
23.	Groppe D M, Makeig S, Kutas M. Identifying reliable Independent components via split-half comparisons. Neuroimage, 2009, 45(4): 1199-1211.
24.	Fuertes J J, Travieso C M, Álvarez A, et al. Reducing artifacts in TMS-evoked EEG. Berlin Heidelberg: Springer, 2010: 302-310.
25.	Maki H, Ilmoniemi R J. Projecting out muscle artifacts from TMS-evoked EEG. Neuroimage, 2011, 54(4): 2706-2710.
26.	Lyzhko E, Hamid L, Makhortykh S, et al. Comparison of three ICA algorithms for ocular artifact removal from TMS-EEG recordings//2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015: 1926-1929.

1. Farzan F, Vernet M, Shafi M M, et al. Characterizing and modulating brain circuitry through transcranial magnetic stimulation combined with electroencephalography. Front Neural Circuits, 2016, 10: 73.
2. Bergmann T O, Karabanov A, Hartwigsen G A, et al. Combining non-invasive transcranial brain stimulation with neuroimaging and electrophysiology: current approaches and future perspectives. Neuroimage, 2016, 140(8): 4-19.
3. Ilmoniemi R J, Hernandezpavon J C, Makela N N, et al. Dealing with artifacts in TMS-evoked EEG//37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Milan: IEEE, 2015: 230.
4. Ives J R, Rotenberg A, Poma R, et al. Electroencephalographic recording during transcranial magnetic stimulation in humans and animals. Clinical Neurophysiology, 2006, 117(8): 1870-1875.
5. Mutanen T, Maki H, Ilmoniemi R J. The effect of stimulus parameters on TMS-EEG muscle artifacts. Brain Stimul, 2013, 6(3): 371-376.
6. Ter Braack E M. de Vos C C, van Putten M J M J A M Masking the auditory evoked potential in TMS-EEG: a comparison of various methods. Brain Topogr, 2015, 28(3): 520-528.
7. Rogasch N C, Fitzgerald P B. Assessing cortical network properties using TMS-EEG. Hum Brain Mapp, 2013, 34(7): 1652-1669.
8. Rogasch N C, Sullivan C, Thomson R H, et al. Analysing concurrent transcranial magnetic stimulation and electroencephalographic data: a review and introduction to the open-source TESA software. Neuroimage, 2017, 147: 934-951.
9. Tanner D, Morgan-Short K, Luck S J. How inappropriate high-pass filters can produce artifactual effects and incorrect conclusions in ERP studies of language and cognition. Psychophysiology, 2015, 52(8): 997-1009.
10. Ruddy K L, Woolley D G, Mantini D, et al. Improving the quality of combined EEG-TMS neural recordings: introducing the coil spacer. J Neurosci Methods, 2018, 294: 34-39.
11. Petrichella S, Johnson N, He B. The influence of corticospinal activity on TMS-evoked activity and connectivity in healthy subjects: a TMS-EEG study. PLoS One, 2017, 12(4): e0174879.
12. Chung S W, Lewis B P, Rogasch N C, et al. Demonstration of short-term plasticity in the dorsolateral prefrontal cortex with theta burst stimulation: a TMS-EEG study. Clinical Neurophysiology, 2017, 128(7): 1117-1126.
13. Reichenbach A, Whittingstall K, Thielscher A. Effects of transcranial magnetic stimulation on visual evoked potentials in a visual suppression task. Neuroimage, 2011, 54(2): 1375-1384.
14. Rogasch N C, Thomson R H, Farzan F A, et al. Removing artefacts from TMS-EEG recordings using independent component analysis: importance for assessing prefrontal and motor cortex network properties. Neuroimage, 2014, 101: 425-439.
15. Thut G, Northoff G, Ives J R, et al. Effects of single-pulse transcranial magnetic stimulation (TMS) on functional brain activity: a combined event-related TMS and evoked potential study. Clin Neurophysiol, 2003, 114(11): 2071-2080.
16. Verhagen L, Dijkerman H C, Medendorp W . Cortical dynamics of sensorimotor integration during grasp planning. Journal of Neuroscience, 2012, 32(13): 4508-4519.
17. Rose N S, Larocque J J, Riggall A C, et al. Reactivation of latent working memories with transcranial magnetic stimulation. Science, 2016, 354(6316): 1136-1139.
18. Ter Braack E M. de Jonge Benjamin, van Putten M J A M Reduction of TMS induced artifacts in EEG using principal component analysis. IEEE Trans Neural Syst Rehabil Eng Publ, 2013, 21(3): 376-382.
19. Mutanen T P, Kukkonen M, Nieminen J O, et al. Recovering TMS-evoked EEG responses masked by muscle artifacts. Neuroimage, 2016, 139: 157-166.
20. Korhonen R J, Hernandez-Pavon J C, Metsomaa J, et al. Removal of large muscle artifacts from transcranial magnetic stimulation-evoked EEG by independent component analysis. Med Biol Eng Comput, 2011, 49(4): 397-407.
21. Chaumon M, Bishop D V, Busch N A. A practical guide to the selection of independent components of the electroencephalogram for artifact correction. J Neurosci Methods, 2015, 250(SI): 47-63.
22. Winkler I, Debener S, Mueller K . On the influence of high-pass filtering on ICA-based artifact reduction in EEG-ERP//2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015: 4101-4105.
23. Groppe D M, Makeig S, Kutas M. Identifying reliable Independent components via split-half comparisons. Neuroimage, 2009, 45(4): 1199-1211.
24. Fuertes J J, Travieso C M, Álvarez A, et al. Reducing artifacts in TMS-evoked EEG. Berlin Heidelberg: Springer, 2010: 302-310.
25. Maki H, Ilmoniemi R J. Projecting out muscle artifacts from TMS-evoked EEG. Neuroimage, 2011, 54(4): 2706-2710.
26. Lyzhko E, Hamid L, Makhortykh S, et al. Comparison of three ICA algorithms for ocular artifact removal from TMS-EEG recordings//2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015: 1926-1929.

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