Aug 2026· Journal of Neurophysiology· Vol 136, pp. 1058-1074· 0 citations
Medicine
TL;DR
Findings indicate that stimulus intensity shapes the pattern-level structure of corticospinal outputs and suggest that MEMs obtained from TMS complement well-established single-muscle MEP analyses and offer a novel perspective for investigating the motor system.
Abstract
As a noninvasive neuromodulation technique, transcranial magnetic stimulation (TMS) offers insights into motor system physiology through motor-evoked potentials (MEPs). In the present study, we applied a factorization approach to multimuscle MEPs to characterize the pattern-level structure of corticospinal outputs beyond conventional per-muscle amplitude measures. To evaluate this approach, we analyzed multimuscle MEP datasets from three experiments in healthy young adults focusing on different stimulus parameters: stimulus intensity (experiment 1: n = 40), motor mapping size (experiment 2: n = 35), and activation of intracortical circuits by a paired-pulse TMS paradigm (experiment 3: n = 20). We extracted motor-evoked modules (MEMs) using non-negative matrix factorization (NMF) and compared their structure across different stimulus conditions. MEM structure was impacted by stimulus intensity, and these findings indicate that stimulus intensity shapes the pattern-level structure of corticospinal outputs. Varying motor mapping size had only a minor impact on MEM structure, suggesting that the pattern-level structure of corticospinal outputs elicited by TMS was stable across mapping extents. Activation of intracortical inhibition appeared to alter MEM structure compared with single-pulse TMS. These findings suggest that paired-pulse activation of intracortical inhibition may alter the pattern-level structure of corticospinal outputs. The MEM framework allows us to characterize the pattern-level structure of corticospinal outputs beyond single-muscle MEPs; thus, MEMs obtained from TMS complement well-established single-muscle MEP analyses and offer a novel perspective for investigating the motor system.
Background Immediate transcranial evoked potentials (iTEPs) are ultra-early electroencephalographic responses elicited by single-pulse transcranial magnetic stimulation (TMS) of the primary motor cortical hand area (M1-HAND). Their characteristic latency, waveform, and sensitivity to short-interval intracortical inhibi...
M. Beck, Marten Nuyts, Laura Sakalauskaitė et al.· bioRxiv· 0 citations
Motor-evoked potentials (MEPs) recorded via surface electromyography (EMG) from peripheral muscles following transcranial magnetic stimulation (TMS) of the motor cortex reflect the integrity of the entire corticospinal pathway and are widely used in both basic neuroscience and clinical practice. However, the relative c...
Vincent S. C. Chien, Eleonora Bernasconi, E. Müller et al.· bioRxiv· 0 citations
Abstract Transcranial magnetic stimulation (TMS) elicits characteristic cortical responses known as TMS-evoked potentials (TEPs) measured via electroencephalography (EEG). An early negative peak can be consistently evoked over the motor cortex at around 15 ms (N15). It remains elusive whether N15 overlaps with the cort...
S. Van Hoornweder, M. Beck, J. D. Nielsen et al.· Imaging neuroscience· 0 citations
Single-pulse transcranial magnetic stimulation (spTMS) is widely used to investigate human corticospinal and cortical physiology, yet individual physiological measures provide only partial information about cortical function. This systematic review aimed to synthesize evidence on human physiological responses evoked by...
K. Mancheva, G. Atanasov· Applied Biosciences· 0 citations
An exploratory trial-by-trial analysis revealed an overall effect of trial-by-trial brain state on TEP amplitudes, confirming successful engagement of the sensorimotor network.
Motahare Delbari, Christoph S. Herrmann, Christian Grefkes et al.· bioRxiv· 0 citations
A comprehensive comparison of models across multiple cortical regions identified consistent mechanisms underlying the cortical response to TMS and contributes to the refinement of computational strategies for optimizing stimulation paradigms.
K. Kumaravelu, Ge-Ne J. Yu, A. Aberra et al.· bioRxiv· 0 citations
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