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Removing artefacts from TMS-EEG recordings using independent component analysis: importance for assessing prefrontal and motor cortex network properties.
Neuroimage. 2014 Nov 01; 101:425-39.N

Abstract

INTRODUCTION

The combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) is emerging as a powerful tool for causally investigating cortical mechanisms and networks. However, various artefacts contaminate TMS-EEG recordings, particularly over regions such as the dorsolateral prefrontal cortex (DLPFC). The aim of this study was to substantiate removal of artefacts from TMS-EEG recordings following stimulation of the DLPFC and motor cortex using independent component analysis (ICA).

METHODS

36 healthy volunteers (30.8 ± 9 years, 9 female) received 75 single TMS pulses to the left DLPFC or left motor cortex while EEG was recorded from 57 electrodes. A subset of 9 volunteers also received 50 sham pulses. The large TMS artefact and early muscle activity (-2 to ~15 ms) were removed using interpolation and the remaining EEG signal was processed in two separate ICA runs using the FastICA algorithm. Five sub-types of TMS-related artefacts were manually identified: remaining muscle artefacts, decay artefacts, blink artefacts, auditory-evoked potentials and other noise-related artefacts. The cause of proposed blink and auditory-evoked potentials was assessed by concatenating known artefacts (i.e. voluntary blinks or auditory-evoked potentials resulting from sham TMS) to the TMS trials before ICA and evaluating grouping of resultant independent components (ICs). Finally, we assessed the effect of removing specific artefact types on TMS-evoked potentials (TEPs) and TMS-evoked oscillations.

RESULTS

Over DLPFC, ICs from proposed muscle and decay artefacts correlated with TMS-evoked muscle activity size, whereas proposed TMS-evoked blink ICs combined with voluntary blinks and auditory ICs with auditory-evoked potentials from sham TMS. Individual artefact sub-types characteristically distorted each measure of DLPFC function across the scalp. When free of artefact, TEPs and TMS-evoked oscillations could be measured following DLPFC stimulation. Importantly, characteristic TEPs following motor cortex stimulation (N15, P30, N45, P60, N100) could be recovered from artefactual data, corroborating the reliability of ICA-based artefact correction.

CONCLUSIONS

Various different artefacts contaminate TMS-EEG recordings over the DLPFC and motor cortex. However, these artefacts can be removed with apparent minimal impact on neural activity using ICA, allowing the study of TMS-evoked cortical network properties.

Authors+Show Affiliations

Monash Alfred Psychiatry Research Centre, Central Clinical School, The Alfred and Monash University, Melbourne, Australia; Monash Clinical and Imaging Neuroscience, School of Psychological Science and Monash Biomedical Imaging, Monash University, Melbourne, Australia. Electronic address: nigel.rogasch@monash.edu.Monash Alfred Psychiatry Research Centre, Central Clinical School, The Alfred and Monash University, Melbourne, Australia.Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada.Monash Alfred Psychiatry Research Centre, Central Clinical School, The Alfred and Monash University, Melbourne, Australia.Monash Alfred Psychiatry Research Centre, Central Clinical School, The Alfred and Monash University, Melbourne, Australia.Department of Biomedical Engineering and Computational Science (BECS), Aalto University School of Science, Espoo, Finland.Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada.Monash Alfred Psychiatry Research Centre, Central Clinical School, The Alfred and Monash University, Melbourne, Australia.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

25067813

Citation

Rogasch, Nigel C., et al. "Removing Artefacts From TMS-EEG Recordings Using Independent Component Analysis: Importance for Assessing Prefrontal and Motor Cortex Network Properties." NeuroImage, vol. 101, 2014, pp. 425-39.
Rogasch NC, Thomson RH, Farzan F, et al. Removing artefacts from TMS-EEG recordings using independent component analysis: importance for assessing prefrontal and motor cortex network properties. Neuroimage. 2014;101:425-39.
Rogasch, N. C., Thomson, R. H., Farzan, F., Fitzgibbon, B. M., Bailey, N. W., Hernandez-Pavon, J. C., Daskalakis, Z. J., & Fitzgerald, P. B. (2014). Removing artefacts from TMS-EEG recordings using independent component analysis: importance for assessing prefrontal and motor cortex network properties. NeuroImage, 101, 425-39. https://doi.org/10.1016/j.neuroimage.2014.07.037
Rogasch NC, et al. Removing Artefacts From TMS-EEG Recordings Using Independent Component Analysis: Importance for Assessing Prefrontal and Motor Cortex Network Properties. Neuroimage. 2014 Nov 1;101:425-39. PubMed PMID: 25067813.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Removing artefacts from TMS-EEG recordings using independent component analysis: importance for assessing prefrontal and motor cortex network properties. AU - Rogasch,Nigel C, AU - Thomson,Richard H, AU - Farzan,Faranak, AU - Fitzgibbon,Bernadette M, AU - Bailey,Neil W, AU - Hernandez-Pavon,Julio C, AU - Daskalakis,Zafiris J, AU - Fitzgerald,Paul B, Y1 - 2014/07/25/ PY - 2014/04/02/received PY - 2014/06/19/revised PY - 2014/07/17/accepted PY - 2014/7/29/entrez PY - 2014/7/30/pubmed PY - 2015/5/28/medline KW - Artefacts KW - Dorsolateral prefrontal cortex KW - Electroencephalography KW - Independent component analysis KW - Motor cortex KW - Transcranial magnetic stimulation SP - 425 EP - 39 JF - NeuroImage JO - Neuroimage VL - 101 N2 - INTRODUCTION: The combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) is emerging as a powerful tool for causally investigating cortical mechanisms and networks. However, various artefacts contaminate TMS-EEG recordings, particularly over regions such as the dorsolateral prefrontal cortex (DLPFC). The aim of this study was to substantiate removal of artefacts from TMS-EEG recordings following stimulation of the DLPFC and motor cortex using independent component analysis (ICA). METHODS: 36 healthy volunteers (30.8 ± 9 years, 9 female) received 75 single TMS pulses to the left DLPFC or left motor cortex while EEG was recorded from 57 electrodes. A subset of 9 volunteers also received 50 sham pulses. The large TMS artefact and early muscle activity (-2 to ~15 ms) were removed using interpolation and the remaining EEG signal was processed in two separate ICA runs using the FastICA algorithm. Five sub-types of TMS-related artefacts were manually identified: remaining muscle artefacts, decay artefacts, blink artefacts, auditory-evoked potentials and other noise-related artefacts. The cause of proposed blink and auditory-evoked potentials was assessed by concatenating known artefacts (i.e. voluntary blinks or auditory-evoked potentials resulting from sham TMS) to the TMS trials before ICA and evaluating grouping of resultant independent components (ICs). Finally, we assessed the effect of removing specific artefact types on TMS-evoked potentials (TEPs) and TMS-evoked oscillations. RESULTS: Over DLPFC, ICs from proposed muscle and decay artefacts correlated with TMS-evoked muscle activity size, whereas proposed TMS-evoked blink ICs combined with voluntary blinks and auditory ICs with auditory-evoked potentials from sham TMS. Individual artefact sub-types characteristically distorted each measure of DLPFC function across the scalp. When free of artefact, TEPs and TMS-evoked oscillations could be measured following DLPFC stimulation. Importantly, characteristic TEPs following motor cortex stimulation (N15, P30, N45, P60, N100) could be recovered from artefactual data, corroborating the reliability of ICA-based artefact correction. CONCLUSIONS: Various different artefacts contaminate TMS-EEG recordings over the DLPFC and motor cortex. However, these artefacts can be removed with apparent minimal impact on neural activity using ICA, allowing the study of TMS-evoked cortical network properties. SN - 1095-9572 UR - https://www.unboundmedicine.com/medline/citation/25067813/Removing_artefacts_from_TMS_EEG_recordings_using_independent_component_analysis:_importance_for_assessing_prefrontal_and_motor_cortex_network_properties_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S1053-8119(14)00620-X DB - PRIME DP - Unbound Medicine ER -