Recording brain responses to TMS of primary motor cortex by EEG – utility of an optimized sham procedure

Gordon, Pedro Caldana; Jovellar, D. Blair; Song, Yufei; Zrenner, Christoph; Belardinelli, Paolo; Siebner, Hartwig R.; Ziemann, Ulf

doi:10.1016/j.neuroimage.2021.118708

Cited by 46 publications

(81 citation statements)

References 62 publications

(133 reference statements)

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“…In keeping with a growing literature [27,[45][46][47][48], correlation analysis showed that TEPs generated by cortical stimulation and peripherally-evoked potentials (PEPs) generated by shoulder stimulation tended to show similarities from ~70 ms post-TMS. This correlation has been suggested to reflect increased sensory contamination of the later TEP components, principally due to the auditory and somatosensory stimulation generated by TMS [45,47].…”

Section: Considerations For Sensory Contamination Within the Tepsupporting

confidence: 65%

“…Consequently, it could be suggested that variations in sensory input within each experiment could contribute to differences in the response to CB stimulation. Given that variations in both somatosensory and auditory input appear to primarily modify the later TEP peaks [45, 47], which were intentionally omitted from the analysis of the current study, we believe that the influence of this potential confound is minimal. However, as we cannot completely exclude this possibility, it will be important for future studies deriving EEG measures of CB-C connectivity to also include direct comparisons between sham and real stimulation over CB.…”

Section: Discussionmentioning

confidence: 99%

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Utilising TMS-EEG to assess the response to cerebellar-brain inhibition

Sasaki

Hand

Liao

et al. 2022

Preprint

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Background: Cerebellar-brain inhibition (CBI) is a transcranial magnetic stimulation (TMS) paradigm indexing excitability of cerebellar projections to motor cortex (M1). Stimulation involved with CBI is often considered to be uncomfortable, and alternative ways to index connectivity between cerebellum and the cortex would be valuable. Utilising electroencephalography in conjunction with TMS (combined TMS-EEG) to record the response to CBI has the potential to achieve this, but has not been attempted previously. Objective: To investigate the utility of TMS-EEG for characterising cerebellar-cortical interactions recruited by CBI. Methods: A total of 33 volunteers (25.7 ± 4.9 years, 20 females) participated across three experiments. These investigated EEG responses to CBI induced with a figure-of-eight (F8; experiment 1) or double cone (DC; experiment 2) conditioning coil over cerebellum, in addition to multisensory sham stimulation (experiment 3). Results: Both F8 and DC coils suppressed early TMS-evoked EEG potentials (TEPs) produced by TMS to M1 (P < 0.05). Furthermore, the TEP produced by CBI stimulation was related to the motor inhibitory response to CBI recorded in a hand muscle (P < 0.05), but only when using the DC coil. Multisensory sham stimulation failed to modify the M1 TEP. Conclusions: Cerebellar conditioning produced changes in the M1 TEP that were not apparent following sham stimulation, and that were related to the motor inhibitory effects of CBI. Our findings therefore suggest it is possible to index the response to CBI using TMS-EEG. In addition, while both F8 and DC coils appear to recruit cerebellar projections, the nature of these may be different.

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Section: Considerations For Sensory Contamination Within the Tepsupporting

confidence: 65%

Section: Discussionmentioning

confidence: 99%

Utilising TMS-EEG to assess the response to cerebellar-brain inhibition

Sasaki

Hand

Liao

et al. 2022

Preprint

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“…Using data from two separate studies, we show effective and conservative extraction of AEP with younger adult as well as an older population, with variations of sham stimulation protocols, and with different TMS devices and EEG systems. Of note, one of the sham stimulation protocols included electrical stimulation of the skin, as this is increasingly considered an important element of an effective sham design 18 , 77 . We show this method may preserve residual TEP in early, mid and late latency windows.…”

Section: Discussionmentioning

confidence: 99%

A structured ICA-based process for removing auditory evoked potentials

Ross

Ozdemir

Lian

et al. 2022

Sci Rep

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Transcranial magnetic stimulation (TMS)-evoked potentials (TEPs), recorded using electroencephalography (EEG), reflect a combination of TMS-induced cortical activity and multi-sensory responses to TMS. The auditory evoked potential (AEP) is a high-amplitude sensory potential—evoked by the “click” sound produced by every TMS pulse—that can dominate the TEP and obscure observation of other neural components. The AEP is peripherally evoked and therefore should not be stimulation site specific. We address the problem of disentangling the peripherally evoked AEP of the TEP from components evoked by cortical stimulation and ask whether removal of AEP enables more accurate isolation of TEP. We hypothesized that isolation of the AEP using Independent Components Analysis (ICA) would reveal features that are stimulation site specific and unique individual features. In order to improve the effectiveness of ICA for removal of AEP from the TEP, and thus more clearly separate the transcranial-evoked and non-specific TMS-modulated potentials, we merged sham and active TMS datasets representing multiple stimulation conditions, removed the resulting AEP component, and evaluated performance across different sham protocols and clinical populations using reduction in Global and Local Mean Field Power (GMFP/LMFP) and cosine similarity analysis. We show that removing AEPs significantly reduced GMFP and LMFP in the post-stimulation TEP (14 to 400 ms), driven by time windows consistent with the N100 and P200 temporal characteristics of AEPs. Cosine similarity analysis supports that removing AEPs reduces TEP similarity between subjects and reduces TEP similarity between stimulation conditions. Similarity is reduced most in a mid-latency window consistent with the N100 time-course, but nevertheless remains high in this time window. Residual TEP in this window has a time-course and topography unique from AEPs, which follow-up exploratory analyses suggest could be a modulation in the alpha band that is not stimulation site specific but is unique to individual subject. We show, using two datasets and two implementations of sham, evidence in cortical topography, TEP time-course, GMFP/LMFP and cosine similarity analyses that this procedure is effective and conservative in removing the AEP from TEP, and may thus better isolate TMS-evoked activity. We show TEP remaining in early, mid and late latencies. The early response is site and subject specific. Later response may be consistent with TMS-modulated alpha activity that is not site specific but is unique to the individual. TEP remaining after removal of AEP is unique and can provide insight into TMS-evoked potentials and other modulated oscillatory dynamics.

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“…Movement associated with TMS-evoked scalp muscle contraction can cause additional decay artifacts which persist for longer (>50 ms) and are often hard to distinguish from decay artifacts associated with charges stored within the skin-electrode-amplifier circuit (Rogasch et al, 2014). The often-strong sensations resulting from TMS-evoked muscle activity or from stimulation of other cranial nerves running across the scalp, may also result in somatosensory-evoked potentials (Conde et al, 2019;Gordon et al, 2021). There is some debate as to whether these potentials are directly visible in the scalp EEG (Paus et al, 2001;Rocchi et al, 2021), however other work has shown an increase in potentials around 100-200 ms with increasing electrical stimulation to the scalp (Gordon et al, 2021).…”

Section: Concurrent Tms-eeg: the Challenge Of Artifactsmentioning

confidence: 99%

“…The often-strong sensations resulting from TMS-evoked muscle activity or from stimulation of other cranial nerves running across the scalp, may also result in somatosensory-evoked potentials (Conde et al, 2019;Gordon et al, 2021). There is some debate as to whether these potentials are directly visible in the scalp EEG (Paus et al, 2001;Rocchi et al, 2021), however other work has shown an increase in potentials around 100-200 ms with increasing electrical stimulation to the scalp (Gordon et al, 2021). The discomfort caused by TMS-evoked muscle activity can also result in jaw or facial tension, which causes high levels of ongoing muscle activity in the EEG signal, particularly in lateral electrodes overlying muscles.…”

Section: Concurrent Tms-eeg: the Challenge Of Artifactsmentioning

confidence: 99%

Designing and comparing cleaning pipelines for TMS-EEG data: a theoretical overview and practical example

Rogasch

Biabani

Mutanen

2021

Preprint

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Combining transcranial magnetic stimulation (TMS) with electroencephalography (EEG) is growing in popularity as a method for probing the reactivity and connectivity of neural circuits in basic and clinical research. However, using EEG to measure the neural responses to TMS is challenging due to the unique artifacts introduced by combining the two techniques. In this paper, we overview the artifacts present in TMS-EEG data and the offline cleaning methods used to suppress these unwanted signals. We then describe how open science practices, including the development of open-source toolboxes designed for TMS-EEG analysis (e.g., TESA - the TMS-EEG signal analyser), have improved the availability and reproducibility of TMS-EEG cleaning methods. We provide theoretical and practical considerations for designing TMS-EEG cleaning pipelines and then give an example of how to compare different pipelines using TESA. We show that changing even a single step in a pipeline designed to suppress decay artifacts results in TMS-evoked potentials (TEPs) with small differences in amplitude and spatial topography. The variability in TEPs resulting from the choice of cleaning pipeline has important implications for comparing TMS-EEG findings between research groups which use different online and offline approaches. Finally, we discuss the challenges of validating cleaning pipelines and recommend that researchers compare outcomes from TMS-EEG experiments using multiple pipelines to ensure findings are not related to the choice of cleaning methods. We conclude that the continued improvement, availability, and validation of cleaning pipelines is essential to ensure TMS-EEG reaches its full potential as a method for studying human neurophysiology.HighlightsConcurrent TMS-EEG is challenging due to artifacts in the recorded signals.We overview offline methods for cleaning TEPs and provide tips on pipeline design.We use TESA to compare pipelines and show changing a single step alters TEPs.We discuss the challenges in validating pipelines for TMS-EEG analysis.We suggest using multiple pipelines to minimise the impact of method choice on TEPs.

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Recording brain responses to TMS of primary motor cortex by EEG – utility of an optimized sham procedure

Cited by 46 publications

References 62 publications

Utilising TMS-EEG to assess the response to cerebellar-brain inhibition

Utilising TMS-EEG to assess the response to cerebellar-brain inhibition

A structured ICA-based process for removing auditory evoked potentials

Designing and comparing cleaning pipelines for TMS-EEG data: a theoretical overview and practical example

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