Characterizing and minimizing the contribution of sensory inputs to TMS-evoked potentials

Biabani, Mana; Fornito, Alex; Mutanen, Tuomas P.; Morrow, James; Rogasch, Nigel C.

doi:10.1016/j.brs.2019.07.009

Cited by 132 publications

(151 citation statements)

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“…All subjects were screened for any contraindications to TMS [21], and provided written consent to the experimental procedure, which was approved by the Monash University Human Ethics Committee in accordance with the declaration of Helsinki. The TMS-EEG data from this study was also used in our recent publication investigating sensory contributions to TEPs [19]. Participants were seated comfortably in an adjustable chair, with their elbows resting on the armrests and forearms pronated and supported on a pillow on their laps.…”

Section: Participantsmentioning

confidence: 99%

“…Additionally, as a control condition, each participant received 100 suprathreshold TMS pulses over the left shoulder to elicit PEPs due to TMS coil clicks and tapping sensation, without transcranially stimulating the brain [19]. While this control is likely suboptimal for somatosensory activation (e.g.…”

Section: Tmsmentioning

confidence: 99%

“…While this control is likely suboptimal for somatosensory activation (e.g. shoulder vs scalp), we have previously demonstrated that the resulting sensory signal accounts for much of the fronto-central N100/P180 complex observed in motor TEPs [19,26]. For each participant, the block order was pseudo-randomized and regular breaks were given between blocks.…”

Section: Tmsmentioning

confidence: 99%

“…These scripts are available at: https://github.com/BMHLab/TEPs-PEPs and the pipeline has been described in detail in our recent publication [19]. For further analysis, we reduced the dimensionality of EEG by extracting the data from left and right M1.…”

Section: Eegmentioning

confidence: 99%

“…N45, N100) [13][14][15][16][17]; however, the evidence is far from conclusive [18]. Furthermore, recent evidence suggests that some of the TEP signal may result from indirect sensory input, evoked by the TMS pulse, further complicating interpretation of TEP peaks [19,20].…”

Section: Introductionmentioning

confidence: 99%

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The correspondence between EMG and EEG measures of changes in cortical excitability following transcranial magnetic stimulation

Biabani

Fornito

Coxon

et al. 2019

Preprint

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Introduction: Transcranial magnetic stimulation (TMS) is a powerful tool to investigate local cortical circuits and broader neural networks. Paired-pulse TMS (ppTMS) paradigms are commonly employed to study excitatory/inhibitory neurotransmissions in motor circuits across time by assessing changes in motor-evoked potentials (MEPs) using electromyography (EMG).The combination of TMS with electroencephalography (EEG) has the capacity to extend this work outside the motor system by focusing on TMS-evoked potentials (TEPs) across both space and time as the measurable output of brain stimulation. However, the relationship between these two putative outputs of TMS effects -MEPs and TEPs -remains unclear. Aim: To investigate whether the same neural populations are responsible for fluctuations in MEPs with ppTMS as the TEP waveform following single pulse TMS (spTMS). Methods: Twenty-four healthy participants received intra-hemispheric and interhemispheric (dual-coil) ppTMS, with different inter-pulse intervals, conditioning intensities, and TMS pulse waveforms over the motor cortex, while EMG was recorded from first dorsal interosseous muscles. EEG was also recorded in response to spTMS with the same intensity and location as the conditioning pulses in ppTMS-EMG. Additionally, TMS was applied to the shoulder as a multisensory control condition. The relationship between ppTMS-EMG and spTMS-EEG were evaluated using metrics sensitive to both the shape and amplitude of the signals. Results: The fluctuations in cortical excitability following suprathreshold TMS were correlated in shape, but not amplitude, when measured with ppTMS-EMG and TMS-EEG. This relationship was observable only after reversing the 2 polarity of short latency TEPs (<~60 ms). For interhemispheric measures, supressing sensory potentials in TEPs was required to discern the relationship between the two signals. Conclusion:The relationship between MEP and TEP measures suggests both signals reflect activity from overlapping neural populations. This finding establishes a fundamental link between TEP peaks and periods of net excitation/inhibition observed with ppTMS-EMG in both the stimulated motor cortex and connected cortical regions.

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Section: Participantsmentioning

confidence: 99%

Section: Tmsmentioning

confidence: 99%

Section: Tmsmentioning

confidence: 99%

Section: Eegmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The correspondence between EMG and EEG measures of changes in cortical excitability following transcranial magnetic stimulation

Biabani

Fornito

Coxon

et al. 2019

Preprint

Self Cite

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Probing regional cortical excitability via input–output properties using transcranial magnetic stimulation and electroencephalography coupling

Raffin

Harquel

Passera

et al. 2020

Human Brain Mapping

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The modular organization of the cortex refers to subsets of highly interconnected nodes, sharing specific cytoarchitectural and dynamical properties. These properties condition the level of excitability of local pools of neurons. In this study, we described TMS evoked potentials (TEP) input–output properties to provide new insights into regional cortical excitability. We combined robotized TMS with EEG to disentangle region‐specific TEP from threshold to saturation and describe their oscillatory contents. Twenty‐two young healthy participants received robotized TMS pulses over the right primary motor cortex (M1), the right dorsolateral prefrontal cortex (DLPFC) and the right superior occipital lobe (SOL) at five stimulation intensities (40, 60, 80, 100, and 120% resting motor threshold) and one short‐interval intracortical inhibition condition during EEG recordings. Ten additional subjects underwent the same experiment with a realistic sham TMS procedure. The results revealed interregional differences in the TEPs input–output functions as well as in the responses to paired‐pulse conditioning protocols, when considering early local components (<80 ms). Each intensity in the three regions was associated with complex patterns of oscillatory activities. The quality of the regression of TEPs over stimulation intensity was used to derive a new readout for cortical excitability and dynamical properties, revealing lower excitability in the DLPFC, followed by SOL and M1. The realistic sham experiment confirmed that these early local components were not contaminated by multisensory stimulations. This study provides an entirely new analytic framework to characterize input–output relations throughout the cortex, paving the way to a more accurate definition of local cortical excitability.

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Experimental suppression of transcranial magnetic stimulation‐electroencephalography sensory potentials

Ross

Sarkar

Keller

2022

Human Brain Mapping

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The sensory experience of transcranial magnetic stimulation (TMS) evokes cortical responses measured in electroencephalography (EEG) that confound interpretation of TMS-evoked potentials (TEPs). Methods for sensory masking have been proposed to minimize sensory contributions to the TEP, but the most effective combination for suprathreshold TMS to dorsolateral prefrontal cortex (dlPFC) is unknown. We applied sensory suppression techniques and quantified electrophysiology and perception from suprathreshold dlPFC TMS to identify the best combination to minimize the sensory TEP. In 21 healthy adults, we applied single pulse TMS at 120% resting motor threshold (rMT) to the left dlPFC and compared EEG vertex N100-P200 and perception. Conditions included three protocols: No masking (no auditory masking, no foam, and jittered interstimulus interval [ISI]), Standard masking (auditory noise, foam, and jittered ISI), and our ATTENUATE protocol (auditory noise, foam, over-the-ear protection, and unjittered ISI). ATTENUATE reduced vertex N100-P200 by 56%, "click" loudness perception by 50%, and scalp sensation by 36%. We show that sensory prediction, induced with predictable ISI, has a suppressive effect on vertex N100-P200, and that combining standard suppression protocols with sensory prediction provides the best N100-P200 suppression. ATTENUATE was more effective than Standard masking, which only reduced vertex N100-P200 by 22%, loudness by 27%, and scalp sensation by 24%. We introduce a sensory suppression protocol superior to Standard masking and demonstrate that using an unjittered ISI can contribute to minimizing sensory confounds. ATTENUATE provides superior sensory suppression to increase TEP signal-to-noise and contributes to a growing understanding of TMS-EEG sensory neuroscience.

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Characterizing and minimizing the contribution of sensory inputs to TMS-evoked potentials

Cited by 132 publications

References 50 publications

The correspondence between EMG and EEG measures of changes in cortical excitability following transcranial magnetic stimulation

The correspondence between EMG and EEG measures of changes in cortical excitability following transcranial magnetic stimulation

Probing regional cortical excitability via input–output properties using transcranial magnetic stimulation and electroencephalography coupling

Experimental suppression of transcranial magnetic stimulation‐electroencephalography sensory potentials

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