Lifting the veil on the dynamics of neuronal activities evoked by transcranial magnetic stimulation

Li, Bingshuo; Virtanen, Juha; Oeltermann, A; Schwarz, Cornelius; Giese, Martin A.; Ziemann, Ulf; Benali, Alia

doi:10.7554/elife.30552

Cited by 62 publications

(71 citation statements)

References 65 publications

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“…As decay constant increases, the silent period also increases. This agrees with experimental results, but overall the modeled CSP is somewhat longer than typical measured CSPs [24]. The CSP reflects the long period in which the layer 5 pulse rate ( Fig.…”

Section: Paired-pulse Protocolssupporting

confidence: 89%

“…2(b) shows mean activity across a population, the peaks and troughs of the plot should not be considered as the I-waves per se; rather we may expect such waves to be possible during the times where the activity is large. Changes in layer 5 firing rate are consistent with recent invasive recordings in rodents [24] and non-human primates [38].…”

Section: Motor Evoked Potential At Restsupporting

confidence: 87%

“…The sum of these fibre responses produces a MEP. The latter components are modeled with the approach of Li et al [24].…”

Section: Neural Field Componentsmentioning

confidence: 99%

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Modeling motor-evoked potentials from neural field simulations of transcranial magnetic stimulation

Wilson

Moezzi

Rogasch

2019

Preprint

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Introduction: Understanding how transcranial magnetic stimulation (TMS) interacts with cortical circuits is enhanced by application of biophysical models. Population-based models of cortical activity have captured plasticity responses due to TMS, but these have not calculated changes in motor-evoked potentials (MEPs), standard electromyographic measures inferring the cortical response to TMS.Objectives: To develop a population-based biophysical model of MEPs following TMS.Methods: We use an existing MEP model in conjunction with population-based modeling of the cortex. We consider populations of layer 2/3 excitatory and inhibitory neurons, stimulated by TMS pulses. These populations feed a population of layer 5 corticospinal neurons, with both excitatory and inhibitory connections. The layer 5 population also couples directly but weakly to the TMS pulses. The layer 5 output controls the mean motoneuron response, and from that a series of single motounit action potentials are generated and summed to give a MEP.Results: A realistic MEP waveform was generated by the model comparable to those observed in real experiments. The model captured TMS phenomena including a sigmoidal shaped input-output curve with increasing stimulation intensity, common paired-pulse effects (SICI, ICF, LICI) including responses to pharmacological interventions, and a cortical silent period. Changes in MEP amplitude following theta burst paradigms were also observed including variability in outcome direction.Conclusions: The model enables better interpretation of population-based TMS modeling approaches by interpreting output in terms of MEPs, thus providing a quantitative link between the cortical circuits activated by TMS and functional outcomes.

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Section: Paired-pulse Protocolssupporting

confidence: 89%

Section: Motor Evoked Potential At Restsupporting

confidence: 87%

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Modeling motor-evoked potentials from neural field simulations of transcranial magnetic stimulation

Wilson

Moezzi

Rogasch

2019

Preprint

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“…The loss of EEG signal for up to 15 ms after the TMS pulse therefore represents a limitation of our study. We cannot exclude that significant changes in TMS-evoked or induced EEG responses have occurred in this very early time window, especially because excitation of pyramidal neurons projecting to the spinal cord and responsible for the MEP generation occurs in the very first milliseconds after the TMS pulse (Li et al 2017). This limitation could be possibly overcome in future studies using faster sampling rates and more focal coils that minimize the activation of scalp muscles and produce smaller TMS-related artifacts.…”

Section: Figure 6 Topographical Plots Of Average Teps and Results Ofmentioning

confidence: 99%

Phase of sensorimotor μ‐oscillation modulates cortical responses to transcranial magnetic stimulation of the human motor cortex

Desideri

Zrenner

Ziemann

et al. 2019

The Journal of Physiology

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Key points Oscillatory brain activity coordinates the response of cortical neurons to synaptic inputs in a phase‐dependent manner. Larger motor‐evoked responses are obtained in a hand muscle when transcranial magnetic stimulation (TMS) is synchronized to the phase of the sensorimotor μ‐rhythm. In this study we further showed that TMS applied at the negative vs. positive peak of the μ‐rhythm is associated with higher absolute amplitude of the evoked EEG potential at 100 ms after stimulation. This demonstrates that cortical responses are sensitive to excitability fluctuation with brain oscillations Our results indicate that brain state‐dependent stimulation is a new useful technique for the investigation of stimulus‐related cortical dynamics. Abstract Oscillatory brain activity coordinates the response of cortical neurons to synaptic inputs in a phase‐dependent manner. Transcranial magnetic stimulation (TMS) of the human primary motor cortex elicits larger motor‐evoked potentials (MEPs) when applied at the negative vs. positive peak of the sensorimotor μ‐rhythm recorded with EEG, demonstrating that this phase represents a state of higher excitability of the cortico‐spinal system. Here, we investigated the influence of the phase of the μ‐rhythm on cortical responses to TMS as measured by EEG. We tested different stimulation intensities above and below resting motor threshold (RMT), and a realistic sham TMS condition. TMS at 110% RMT applied at the negative vs. positive peak of the μ‐rhythm was associated with higher absolute amplitudes of TMS‐evoked potentials at 70 ms (P70) and 100 ms (N100). Enhancement of the N100 was confirmed with negative peak‐triggered 90% RMT TMS, while phase of the μ‐rhythm did not influence evoked responses elicited by sham TMS. These findings extend the idea that TMS applied at the negative vs. positive peak of the endogenous μ‐oscillation recruits a larger portion of neurons as a function of stimulation intensity. This further corroborates that brain oscillations determine fluctuations in cortical excitability and establishes phase‐triggered EEG‐TMS as a sensitive tool to investigate the effects of brain oscillations on stimulus‐related cortical dynamics.

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“…A large body of evidence from both human ppTMS-EMG studies [6,7,36,37] and intracellular recordings in animal [38,39] has demonstrated that a suprathreshold TMS pulse to primary motor cortex results in a period of strong net excitation lasting between 10-30 ms followed by a period of net inhibition lasting approximately 50-200 ms at the site of stimulation. However, it is unclear whether the same pattern of response is present in other methods recording the cortical response to TMS, such as EEG, as these methods are sensitive to different scales of neural activity.…”

Section: Emg and Eeg Measures Of Local Cortical Responses To Tmsmentioning

confidence: 99%

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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Lifting the veil on the dynamics of neuronal activities evoked by transcranial magnetic stimulation

Cited by 62 publications

References 65 publications

Modeling motor-evoked potentials from neural field simulations of transcranial magnetic stimulation

Modeling motor-evoked potentials from neural field simulations of transcranial magnetic stimulation

Phase of sensorimotor μ‐oscillation modulates cortical responses to transcranial magnetic stimulation of the human motor cortex

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

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