# Neural Activation Down to the Spinal Cord during Action Language? A Transcranial Magnetic Stimulation and Peripheral Nerve Stimulation Study

William Dupont, Nicolas Amiez, Richard Palluel-Germain, Alain Martin, Marcela Perrone-Bertolotti, Carol Madden-Lombardi, Florent Lebon

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William Dupont, Nicolas Amiez, Richard Palluel-Germain, Alain Martin, Marcela Perrone-Bertolotti, et al.. Neural Activation Down to the Spinal Cord during Action Language? A Transcranial Magnetic Stimulation and Peripheral Nerve Stimulation Study. Journal of Cognitive Neuroscience, 2025, pp.1-11. 10.1162/jocn.a.83. hal-05264255

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Neural activation down to the spinal cord during action language? A transcranial magnetic stimulation and peripheral nerve stimulation study

Dupont W. ¹*, Amiez N. ², Palluel-Germain R. ¹, Martin A. ³, Perrone-Bertolotti M. ¹, Madden-Lombardi C. ³,⁴, Lebon F. ³,⁵

¹Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS LPNC UMR5105, 38000 Grenoble, France

²Universite Lyon 1, UCBL-Lyon 1, Laboratoire Interuniversitaire de Biologie de la Motricité, UR 7424, F-69622 Villeurbanne, France

³ Inserm UMR1093-CAPS, Université Bourgogne Europe, UFR des Sciences du Sport, F-21000, Dijon, France

⁴Centre National de la Recherche Scientifique (CNRS), Paris, France

⁵Institut Universitaire de France (IUF), Paris, France

* Corresponding author:

William Dupont, William.dupont@univ-grenoble-alpes.fr
**Keywords:** motor-evoked potential; cervicomedullary-evoked potential; action understanding; action imagining
## 57 Introduction

For decades, researchers postulated that linguistic processing operated independently of perceptual and motor systems, implying a fundamental separation between cognition and bodily movements (Fodor, 1980; Pylyshyn, 1984). Nevertheless, language comprehension may extend beyond this traditional linguistic system to encompass motor and perceptual processes (Barsalou, 2008; Bechtold et al., 2023; Pulvermüller, 2005; Pulvermüller and Fadiga, 2010).

Along those lines, the comprehension of action words is often accompanied by changes in the motor system, in both behavioral and neurophysiological aspects (Andres et al., 2015; Gentilucci et al., 2000; Klepp et al., 2019; Pulvermüller et al., 2001; Rabahi et al., 2013, 2012; Taylor and Zwaan, 2008; Zwaan and Taylor, 2006). For example, neuroimaging studies demonstrate that understanding action-related words is associated with increased activation in motor areas of the brain, such as premotor and primary motor cortices (Aziz-Zadeh et al., 2006; Hauk et al., 2004; Tettamanti et al., 2005; Van Dam et al., 2010; Wu et al., 2013). Furthermore, this neural activation is closely tied to an increase in corticospinal excitability, as measured by motor-evoked potential (MEP) amplitude in Transcranial Magnetic Stimulation (TMS) studies (Dupont et al., 2025, 2022; Innocenti et al., 2014; Labruna et al., 2011; Papeo et al., 2009). Taken together, these studies indicate that understanding action words can directly modulate the functional state of the motor system (for reviews, see Madden-Lombardi and Dupont, 2023; Papeo et al., 2013).

Over the past several decades, a growing literature has associated these results with spontaneous and unconscious motor simulations, providing sensory-motor features of the described action, and consequently improving understanding of the action (Barsalou 1999; Glenberg and Kaschak 2002; Gallese and Lakoff 2005; Tomasino et
al. 2008; Tomasino and Rumiati 2013; Dupont et al. 2024). These observations raise a fundamental question: could the influence of the comprehension of action words on our motor system extend beyond the cortical level? While this hypothesis may initially seem speculative, it aligns seamlessly with the well-established framework of motor imagery — a cognitive process defined as the explicit mental simulation of an action and its sensorimotor consequences, without concomitant movement. Like action word comprehension, motor imagery is associated with an activation of the motor network (Hardwick et al., 2018; Hétu et al., 2013; Lotze et al., 1999) and an increase in corticospinal excitability (Fadiga et al. 1998; Rossini et al. 1999; Tremblay et al. 2001; Facchini et al. 2002; Grosprêtre et al. 2016b; Dupont et al. 2024). Furthermore, recent research has highlighted the potential generation of a subliminal cortical output during motor imagery, suggesting that this cognitive process is not limited to the brain, but could eventually engage spinal structures. For instance, both motoneuronal excitability, reflected by the F-reflex, and cortico-motoneuronal transmission, measured by cervicomedullary-evoked potentials (CMEPs), increase during kinesthetic motor imagery (for F-reflex, see Bunno, 2019; Bunno et al., 2017; Fujisawa et al., 2011; Fukumoto et al., 2022; Hara et al., 2010; Suzuki et al., 2013; Taniguchi et al., 2008; for CMEPs, see Grosprêtre et al., 2016a).

Finally, growing evidence indicates that the neural mechanisms underlying action reading and motor imagery exhibit remarkable similarities, with the potential for reciprocal influence between these processes (Bonnet et al., 2022; Dupont et al., 2023; Gallese and Lakoff, 2005; Muraki et al., 2023; Yang and Shu, 2014). Both processes involve motor simulations associated not only with behavioral performance changes (e.g., reaction time, strength, or movement kinematics), but also with modulations of corticospinal excitability and motor cortex activity. In this regard, it remains unclear
whether motor system activation generated by action reading is limited to cortical
structures or if spinal activation is also engaged, as during motor imagery. Since MEP
amplitude reflects the excitability of the entire corticospinal pathway, comparing
changes in CMEP and MEP responses could help differentiate whether these neural
modulations originate at the cortical or spinal level (Mcneil et al., 2013; Taylor, 2006).
Therefore, the present research aims to shed new light on this issue by probing
whether action reading, like motor imagery, involves the modulation of physiological
measures at the spinal level. If action reading triggers a subliminal cortical output
similar to motor imagery, we would observe an increase of both corticospinal
excitability (MEP amplitude) and cortico-motoneuronal transmission (CMEP
amplitude) in comparison to rest.

118 **Material and methods**

119 **Participants**

We recruited 15 right-handed individuals in this cross-sectional study (9 women, mean age: 23; range: 18-34). A study conducted with young healthy participants (Grosprêtre et al. 2016) demonstrated increased CMEP during motor imagery, compared to rest. Based on the effect size observed in that study (1.64), assuming a 5% alpha level and 80% power, 6 analyzable participants were required. However, considering that we expect a smaller effect size (0.82) for action reading compared to motor imagery, 15 participants were required. We ensured right handedness laterality with the Edinburgh inventory (Oldfield 1971; range: 0.64-1). All participants were French native speakers without neurological, psychological or physical disorders. They completed the questionnaire by Lefaucheur et al. (2011) to determine whether they were eligible for transcranial magnetic stimulation, and confirmed their participation by providing written
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consent. All procedures were in accordance with the Declaration of Helsinki and were approved by an ethics committee (excluding pre-registration; Comité de Protection des Personnes Nord-Ouest I, ClinicalTrials.gov Identifier: NCT06478303-01/08/2024). In addition, a separate group of eight French native speakers (5 women, mean age: 47; range: 24-56; not involved in the main experiment) was recruited to perform an evaluation of the linguistic stimuli.

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## Study design

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Participants came to the laboratory for a single session. During the experiment, the participants were comfortably seated in a chair with their right hand in a neutral position, their right upper arm vertically aligned along the trunk, and the forearm semi-pronated and flexed at approximately 90°. Using transcranial magnetic stimulation (TMS) and peripheral nerve stimulation (PNS), we elicited motor-evoked potentials (MEPs), cervicomedullary-evoked potentials (CMEPs) and maximal muscular responses ($M_{MAX}$) in the right Flexor Carpi Radialis (FCR) muscle (see below for details). These measurements — recorded while participants remained still, i.e., without pre-muscular contractions — allowed us to investigate the corticospinal excitability, the cortico-motoneuronal transmission and the maximal muscle action potential at rest, during motor imagery, and during the silent reading of action and non-action sentences. The experiment was performed in a counterbalanced block design, with two blocks for each condition: Rest, Motor Imagery, Action Reading, and Non-Action Reading. Each condition included two separate blocks: a TMS block with 16 MEPs, and an electrical stimulation block comprising 5 to 8 CMEPs (depending on the participant's tolerance and the reproducibility of responses) and $2 M_{MAX}$. To control for potential order effects, the sequence of the eight blocks was counterbalanced across participants. Volunteers read stimuli presented on a 19-inch LCD monitor via custom
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software, which synchronized TMS and PNS triggers and electromyographic
recordings.

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## Tasks and stimuli

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### Action and non-action reading conditions

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One hundred and four French sentences were generated; half referring to finger and wrist actions (e.g., "The pan is dirty, I scour it"; "La casserole est sale, je la récure") and half describing non-actions (e.g., "The pan is dirty, I see it"; "La casserole est sale, je la vois"). All sentences in both of these action and non-action conditions were presented in the first-person present tense and were created so that the target verb occurred at the end of the sentence. This final pronoun-verb segment was presented alone on a subsequent screen. Each trial started with a fixation cross (300 ms), followed by a black screen (500 ms) and a sentential context (3000 ms), and then the pronoun and target verb (2000 ms, Figure 1). All stimuli order was counterbalanced.

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Using the Lexique.org database (New et al., 2004), we controlled various psycholinguistic factors between action and non-actions verbs (e.g., written frequency, number of letters and syllables, spelling neighbors, number of homographs, and imageability). In addition, to confirm the distinction between action and non-action sentences, eight participants that did not participate in the TMS and CMS (cervicomedullary stimulation) study were asked to rate on a scale from 1 to 5 whether the sentence described a manual action or not (1 = absolutely not a hand action, and 5 = entirely a hand action). Statistical verb analyses are detailed in Appendix Table 1.

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First, we conducted a series of practice TMS trials to determine each participant's optimal latency for TMS, CMS and PNS administration during action and non-action reading (selecting from intervals of 200, 300, 400, or 500 ms after the target verb

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appeared). Since the delay between TMS/CMS stimulation and muscle response differs by only ~2 ms across these modalities (Taylor, 2006), the same latency was applied for all. This latency was identified as the one eliciting the highest and most consistent MEP amplitude across 12 stimulations for both action and non-action reading conditions (Dupont et al., 2025). Once established, the participant's individualized latency was used for the delivery of 16 TMS pulses (block TMS), along with 5 to 8 CMEP and 2 $M_{MAX}$ (block electrical stimulations), following the presentation of the target verb in each condition.

### Motor imagery condition

In the motor imagery condition, volunteers were asked to imagine maximum voluntary contractions of wrist and finger flexion movements held for 3 seconds in the kinesthetic modality. The instructions were as follows: "try to imagine yourself flexing your fingers and wrist, by feeling the sensations as if you were doing the movement". TMS pulses were delivered 2000 ms after the appearance of the imagery signal ("O" on the screen). The inter-trial interval was 7000 ms. As in the reading task, 16 TMS pulses (block TMS), 5 to 8 CMEP and 2 $M_{MAX}$ (block electrical stimulations) were administered during kinesthetic motor imagery.

### Rest condition

Finally, participants once again performed a silent reading task involving short sentences to ensure a level of engagement comparable to the other conditions. During presentation of the fixation cross, which occurred prior to sentence onset and served as the rest condition period, they received 16 TMS pulses (block TMS), along with 5 to 8 CMEPs and 2 $M_{MAX}$ stimulations (block electrical stimulation).
204 Neurophysiological parameters

205 Electromyography recording

206 We recorded surface electromyography (EMG) via 10-mm-diameter surface electrodes
207 (Contrôle Graphique Médical, Brice Comte-Robert, France) positioned over the right
208 Flexor Carpi Radialis (FCR) muscle. Before positioning the electrodes, the skin was
209 shaved and cleaned to reduce EMG signal noise. The EMG signal was amplified with
210 a bandpass filter (10-500 Hz) and then sampled at 5000 Hz (AcqKnowledge; Biopac
211 Systems, Inc., Goleta, CA). We computed the root mean square EMG signal (EMGrms)
212 100 ms prior to the stimulus artefact to ensure that MEP, CMEP and MMAX were not
213 biased by muscle pre-activation during action reading and motor imagery in
214 comparison to rest (see Appendix Table 3).

215 Transcranial magnetic stimulation

216 Using a figure-eight coil (70 mm diameter) connected to a Magstim 200 stimulator
217 (Magstim Company Ltd, Whitland), we administered single-pulse TMS over the motor
218 area of the right FCR muscle. The coil rested tangentially to the scalp with the handle
219 directed backward and laterally at a 45° angle from the midline. Using a
220 neuronavigation system (BrainSight, Rogue Research Inc.), the muscle hotspot was
221 identified as the location eliciting the highest and most consistent MEP amplitude for
222 the FCR muscle at rest. This hotspot was pinpointed through a regular grid of 4 by 4
223 coil positions with a spacing of 0.5 cm (centered above the FCR cortical area x=-44.7,
224 y=-13.8, z=85.7; Négyesi et al. 2020; Sondergaard et al. 2021). Then, the resting motor
225 threshold was estimated for each individual, corresponding to the minimal TMS
226 intensity required to evoke MEPs of 50µV peak-to-peak amplitude in the right FCR
227 muscle for 5 out of 10 trials (Rossini et al., 2015). The intensity of TMS pulses was set
228 at 120% of the resting motor threshold (mean intensity: 46 ±10.39 % of maximal stimulator output, range: 34-67%; Mean MEP amplitude at rest: 0.29 ±0.22 mV).
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230 *Electrical stimulation*

231 *Cervico-medullary stimulation*

232 In order to probe whether a subliminal motor output extended beyond the brain and reaches spinal structures, we recorded CMEP in the FCR muscle. This approach 233 employed cervicomedullary stimulation to directly probe the cortico-motoneuronal 234 transmission by generating a single volley in descending axons at the pyramidal 235 decussation level (Mcneil et al., 2013; Taylor, 2006). Interestingly, CMEP primarily 236 exhibits a monosynaptic component without influence of presynaptic inhibition. 237
238 Cervicomedullary stimulations were administered using a DS7R constant current research stimulator (Digitimer, Hertfordshire, UK) with 200 µs-width pulses, via two 239 AgCl electrodes positioned 1-2cm posterior to the superior tips of the mastoid 240 processes (left cathode and right anode). The cervico-medullary stimulation intensity 241 was set to match the MEP response at rest with the TMS intensity set at 120% of the 242 resting motor threshold (mean intensity: 123 ±21.19 mA, range 99-170 mA; mean 243 CMEP amplitude at rest: 0.23 ±0.12 mV). Interestingly, alpha motoneurons targeted 244 by this technique largely overlap with those of MEP (Mcneil et al., 2013; Taylor, 2006; 245 Taylor et al., 2002), as long as the MEP and CMEP amplitude is matched. We ensured 246 that MEP and CMEP amplitude at rest recruited the same amount of motor units for 247 each participant, characterized by the percentage of MMAX amplitude (see Appendix 248 Table 2). 249

250 *Median nerve stimulation*

251 To evoke MMAX in the FCR muscle, we employed the same constant current stimulator 252 (Digitimer DS7R) to deliver 1 ms-width monophasic rectangular pulses over the
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median nerve. Electrodes for stimulation were meticulously positioned along the median nerve, close to the cubital fossa, just below the muscle belly of the biceps, with the anode distally positioned. After securing the stimulation electrodes with straps, we determined the stimulation intensity eliciting the maximum response amplitude ($M_{MAX}$) using a recruitment curve initially incremented by 2 mA, and then adjusted to 1 mA when nearing the maximum response. To ensure supramaximal stimulation, the intensity was increased to 130% (mean intensity: 14.24 ±5.45 mA, range 6-27 mA; mean $M_{MAX}$ amplitude: 10.8 ±4.63 mA). Subsequently, the $M_{MAX}$ was measured in each experimental condition and used to normalize the MEPs (MEP/$M_{MAX}$) and CMEPs (CMEP/$M_{MAX}$).
A.

<figure><img src="image_2.png" /></figure>

B.

<figure><img src="image_3.png" /></figure>

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**Figure 1.** Experimental procedure. (A) Schematic illustration of the position of participants and stimulation devices. (B) Experimental procedure. Each trial started with an attentional fixation cross indicating the beginning of a trial. Action and non-action reading: the participants silently read sentences describing action or non-action
concepts. We delivered TMS pulses and electrical stimulation at the optimal individual
latency after the target verb presentation. Motor imagery: the participants imagined
maximum voluntary contractions of wrist and finger flexion. We delivered TMS pulses
and electrical stimulation 2000 ms after the appearance of the imagery onset ('O').

Rest: the participants silently read sentences, but both TMS pulses and electrical
stimulation were delivered during the attentional fixation cross, before the sentence
appeared on the screen. TMS= transcranial magnetic stimulation; PNS= peripheral
nerve stimulation; CMS= cervicomedullary stimulation; MEP= motor-evoked
potentials; MMAX= maximal muscular response; CMEP= cervicomedullary-evoked
potentials; EMG= electromyography.

## Data and statistical analysis:

### Data extraction and analysis

Matlab (The MathWorks, Natick, Massachusetts, USA) was employed to extract EMG
and we measured peak-to-peak MMAX, CMEP and MEP amplitude. Then, we discarded
outliers falling outside the range of +/- 2 SDs from individual means for each condition
(5.57% of MEP data and 5.29% of CMEP data). MEP and CMEP peak-to-peak
amplitude was normalized to the mean MMAX (%MMAX) obtained within each block,
ensuring control over potential changes in peripheral neuromuscular excitability and
allowing interindividual comparison.

### Statistical analysis

Normality and sphericity of the data were evaluated with Shapiro-Wilk and Mauchly
tests, respectively. Given that the assumptions of normality and sphericity were
violated, non-parametric statistical tests were employed throughout the analysis.

To analyze modulations of corticospinal excitability (MEP/MMAX), cortico-motoneuronal
transmission (CMEP/MMAX), and MMAX, separate Friedman ANOVAs were conducted
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for each dependent variable, with Condition (rest, motor imagery, action reading, non-action reading) as a within-subject factor. If the Friedman ANOVAs yielded significant results, post hoc analyses were performed using multiple paired Wilcoxon signed-rank tests to compare across all conditions (for each dependent variable). Finally, Bayesian factor analyses with a prior Cauchly scale of .707 (Morey and Rouder, 2011) were performed to complete our interpretation, offering a measure of the strength of evidence in support of either the alternative or the null hypothesis. To illustrate, a BF<sub>10</sub> of 1 indicates no evidence to support either hypothesis, whereas a BF<sub>10</sub> between 1 and 3, or between 3 and 10, provides marginal and moderate support for the alternative hypothesis, respectively.

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We also applied Friedman ANOVAs to compare the EMGrms before the stimulation artefact in all conditions (see Appendix Table 3) to ensure that MEP, CMEP and $M_{MAX}$ amplitudes were not biased by muscle activation preceding stimulation. Furthermore, we applied Friedman ANOVAs to compare the target positioning, angular alignment, and twist of the TMS coil across conditions, to ensure that MEP amplitude was not biased by variations in TMS coil placement relative to the hotspot (see Appendix Tables 4 and 5).

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We performed statistics with Statistica (Stat Soft, France) and JASP software, and the data are presented with mean values (±SD). The alpha value was set at .05. For paired sample Wilcoxon tests, Cohen's d thresholds for small, moderate, and large effects were set at .2, .5, and .8, respectively (Cohen, 1988). All post hoc analyses were performed using Benjamini and Hochberg correction (Benjamini and Hochberg, 1995), which adjusts significance thresholds according to the number of comparisons, and the ranked p-values in ascending order: .01, .02, .03, .04, and .05.

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318 **Results**

319 **MMAX amplitude**

320 No main effect of Condition was found [Friedman ANOVA: r(3) = -.016, p = .510,
321 Kendall's W = 0.05], suggesting no significant differences in MMAX amplitude among
322 rest (11.07 ±5.03 mV), kinesthetic motor imagery (11.04 ±5.05 mV), action (11.10
323 ±5.09 mV) and non-action reading (11.08 ±5.05 mV). While MEP and CMEP were
324 normalized to MMAX (%MMAX) to control for potential changes in peripheral
325 neuromuscular excitability demonstrating no change in muscular excitability across
326 conditions, this enable to probe the proportion of motor units activated by TMS and
327 CMS.

328 **MEP amplitude - Corticospinal excitability**

329 We observed a main effect of Condition [Friedman ANOVA: r(3) = 0.35, p < .001,
330 Kendall's W = 0.39] with greater MEP amplitude for kinesthetic motor imagery (5.08
331 ±3.35 %MMAX; see Table 1) and action reading (4.08 ±3.02 %MMAX) compared to rest
332 (3.41 ±2.76 %MMAX). Additionally, MEP amplitude during action reading was
333 significantly higher than during non-action reading (3.14 ±2.59 %MMAX). As expected,
334 MEP amplitude during non-action reading did not differ from rest (for similar results,
335 see Dupont et al., 2025, 2022; Labruna et al., 2011). Finally, no significant difference
336 in MEP amplitude was found between kinesthetic motor imagery and action reading
337 (Fig.2). Bayesian factor analysis provides moderate evidence supporting the
338 alternative hypothesis for both kinesthetic motor imagery and action reading,
339 strengthening the idea of significantly increased MEP amplitude in these conditions
340 compared to rest.
<table><caption>**Table 1.** Statistical values for corticospinal excitability</caption><thead><tr><th>Comparisons</th><th>P values</th><th>Corrected threshold</th><th>Bayes factor<sub>10</sub></th><th>Cohen's d</th></tr></thead><tbody><tr><td>Action reading vs. Non-action reading</td><td>.002*</td><td>.01</td><td>7.859</td><td>.823</td></tr><tr><td>Action reading vs. Rest</td><td>.008*</td><td>.02</td><td>3.179</td><td>.678</td></tr><tr><td>Motor imagery vs. Rest</td><td>.020*</td><td>.03</td><td>3.735</td><td>.705</td></tr><tr><td>Action reading vs. Motor imagery</td><td>.280</td><td>.04</td><td>.754</td><td>.416</td></tr><tr><td>Non-action reading vs. Rest</td><td>.460</td><td>.05</td><td>.492</td><td>.315</td></tr></tbody></table>

Note: An asterisk (*) indicates P-values that are significant according to the corrected threshold with the Benjamini-Hochberg procedure.

### CMEP amplitude - Cortico-motoneuronal transmission

We observed a main effect of Condition [Friedman ANOVA: $r(3) = 0.116$, $p = .048$, Kendall's W = 0.18] with greater CMEP amplitude during kinesthetic motor imagery (3.90 ±3.51 %M<sub>MAX</sub>) compared to rest (2.95 ±2.43 %M<sub>MAX</sub>; see Table 2). However, CMEP amplitude did not differ significantly between rest, action reading (3.97 ±3.75 %M<sub>MAX</sub>), and non-action reading (3.31 ±3.31 %M<sub>MAX</sub>, Fig.2). Furthermore, Bayesian factor analysis provides marginal evidence supporting the alternative hypothesis for both kinesthetic motor imagery and action reading, suggesting that CMEP amplitude might be increased during motor imagery, and to a lesser extent, during action reading.

<table><caption>**Table 2.** Statistical values for cortico-motoneuronal transmission</caption><thead><tr><th>Comparisons</th><th>P values</th><th>Corrected threshold</th><th>Bayes factor<sub>10</sub></th><th>Cohen's d</th></tr></thead><tbody><tr><td>Motor imagery vs. Rest</td><td>.004*</td><td>.01</td><td>2.435</td><td>.634</td></tr><tr><td>Action reading vs. Rest</td><td>.036</td><td>.02</td><td>1.487</td><td>.548</td></tr><tr><td>Action reading vs. non-action reading</td><td>.088</td><td>.03</td><td>.708</td><td>.402</td></tr><tr><td>Non-action reading vs. Rest</td><td>.211</td><td>.04</td><td>.438</td><td>.283</td></tr><tr><td>Motor imagery vs. Action reading</td><td>.691</td><td>.05</td><td>.267</td><td>.052</td></tr></tbody></table>

Note: An asterisk (*) indicates P-values that are significant according to the corrected threshold with the Benjamini-Hochberg procedure.
<figure><img src="image_4.png" /><figcaption>**Figure 2.** MEP (A) and CMEP (B) amplitude expressed as a percentage of maximal muscular response (%MMAX) at rest, during motor imagery, and during the silent reading of action and non-action sentences. The left side of the figure displays individual data points, with each condition represented by a unique color. Blue circles indicate the mean value for each condition. The right side of the panel illustrates the MEP and CMEP modulations. The asterisks denote statistically significant p-values after applying the Benjamini-Hochberg correction.</figcaption></figure>
362 Discussion

363 The present study presents several noteworthy findings regarding motor simulations, 364 whether elicited by motor imagery or action reading. First, we successfully replicated 365 the well-established observation that motor imagery leads to a marked increase in 366 corticospinal excitability compared to rest. Similarly, action-related language also 367 resulted in greater corticospinal excitability compared to rest and to non-action reading 368 (which did not differ from rest). Second, we found that cortico-motoneuronal 369 transmission was significantly enhanced only during kinesthetic motor imagery relative 370 to rest.

371 Regarding the first point, we confirmed the increase in corticospinal excitability, by 372 means of MEP amplitude changes during kinesthetic motor imagery compared to rest 373 (Dupont et al., 2024b, 2023; Facchini et al., 2002; Fadiga et al., 1998; Grosprêtre et 374 al., 2016b; Kasai et al., 1997; Lebon et al., 2012; Rossini et al., 1999; Tremblay et al., 375 2001). In a similar vein, we observed that action reading — when compared to rest and 376 non-action sentences — also resulted in an enhancement of corticospinal excitability 377 (for similar results, see Dupont et al., 2025, 2024a, 2022; Innocenti et al., 2014; 378 Labruna et al., 2011; for reviews, see Madden-Lombardi and Dupont, 2023). Thus, 379 motor simulations generated during motor imagery and action reading may influence 380 the excitability of the corticospinal pathway.

381 Regarding the second point, our findings provide further support for previous research 382 demonstrating modulations at the motoneuronal level during kinesthetic motor 383 imagery. More specifically, our results align with a previous study reporting that cortico- 384 motoneuronal transmission increases during kinesthetic motor imagery, as measured 385 by CMEP amplitude (Grosprêtre et al., 2016a). These findings lend further credence 386 to the idea of a potential subliminal cortical output, suggesting that motor imagery may
387 extend beyond the brain, potentially engaging subcortical and even spinal structures
388 (Grosprêtre et al. 2016a; Grosprêtre et al. 2019). While the striking similarity between
389 motor imagery and action reading in terms of corticospinal excitability is noteworthy, it
390 is important to highlight that action reading did not significantly increase cortico-
391 motoneuronal transmission. At first glance, this observation might indicate that the
392 increase in corticospinal excitability triggered during action reading is likely primarily
393 cortical in origin, rather than being driven by subcortical or spinal structures.

394 This absence of motoneuronal changes during action reading can be interpreted from
395 two perspectives. First, the simulation of concepts evoked by action language may be
396 restricted to the brain, without engaging the subliminal cortical output that reaches
397 spinal structures, potentially indicating distinct underlying mechanisms compared to
398 motor imagery. Second, one could argue that a subliminal motor output may still be
399 present but to a lesser extent — more subliminal than during motor imagery — making
400 it more challenging to activate high-threshold motoneurons. In other words, the motor
401 simulation can be evoked at varying levels of richness and intensity, with motor
402 imagery at a higher end of this continuum than action language. Indeed, although we
403 did not observe a significant difference in MEP amplitude between motor imagery and
404 action reading, previous studies have shown that MEP amplitude during motor imagery
405 is greater when imagining a 60% force level compared to a 10% force level (Helm et
406 al., 2015; Mizuguchi et al., 2013). While participants were instructed to imagine
407 maximal contractions (100% force level) during motor imagery, the actions described
408 in the sentences did not necessarily imply the same intensity. This difference in force
409 intensity might explain the statistically non-significant increase in CMEP during action
410 reading. To explore this hypothesis further, it would be interesting to investigate spinal
411 structures with lower activation thresholds than motoneurons, such as presynaptic
interneurons, which could be more responsive to this subtler activation triggered by
action reading. For instance, recent studies have highlighted that imagined foot
movement modulated the activity of interneurons involved in spinal presynaptic
inhibition (Grosprêtre et al. 2016a; Grosprêtre et al. 2019). These interneurons — with
activation thresholds lower than those of motoneurons — may be more susceptible to
the subliminal activation potentially induced by action reading.

This study has some limitations that should be considered. First, the relative peak-to-
peak amplitude, expressed as a percentage of the MMAX wave for each stimulation,
differed across participants, suggesting that the proportion of alpha motoneurons
recruited was not consistent among individuals. However, the fact that we matched
MEP and CMEP amplitude at rest, thereby recruiting the same amount of motor units
for each participant during TMS blocks (range MEP amplitude at rest: 0.10-0.77 mV;
mean MEP amplitude at rest : 0.29 mV) and CMS blocks (range CMEP amplitude at
rest : 0.11-0.52 mV; mean CMEP amplitude at rest : 0.23 mV), provides reassurance
regarding this variability. Lastly, a limitation concerning the linguistic stimuli arises from
the fact that some sentences describing hand actions focused more on finger flexion
rather than wrist flexion, which is the optimal movement for engaging the FCR muscle.
Consequently, we speculate that these sentences may have resulted in less
pronounced increases in MEP and CMEP amplitude following action reading.
Furthermore, future studies could benefit from systematically categorizing action-
related sentences based on the level of physical effort required to perform the
described actions. Considering previous fMRI findings showing that action language
processing recruits motor representations with a degree of specificity — and that the
implied intensity of the action can modulate activity in motor-related regions (Moody
and Gennari, 2010) — it is plausible that variations in the effortfulness of the described actions might have influenced the extent of spinal modulations observed in our study.

To conclude, our results shed significant insights into the effects of motor imagery and action reading on both cortical and spinal structures. They support the notion that motor simulations involved in motor imagery may trigger a subliminal motor output initiated at the cortical level, with the potential to influence spinal activities. Furthermore, our results suggest that the impact of action words comprehension on the motor system may be restricted to cortical aspects, without engaging the subliminal cortical output that reaches spinal structures. Nonetheless, further investigations are needed to explore spinal structures with lower activation thresholds than motoneurons, as these may be more responsive to a subtler subliminal activation triggered by action reading.

## Data availability

All data and linguistic items from this study are available at https://osf.io/t75fr/?view_only=a47a7f9125df4e0f8c33ed86acfcdf8e

## Funding

This study was supported by the Agence Nationale de la Recherche, grant/award number: LAMI-ANR-22-CE28-0026.

## Author contributions

L.F., M-L.C., P-B.M. and P-G.R. funding acquisition; D.W. and A.N. designed research; D.W. and A.N. recorded data; D.W. analyzed data; D.W. wrote the draft of the paper; L.F., M-L.C., M.A, P-G.R. and P-B.M. supervised research; A.N., P-G.R., A.M., P-B.M., M-L.C. and L.F. edited the paper.

## Declaration of Competing Interest

The authors report no competing interests.

## Acknowledgements
461 The authors are very grateful to Cyril Sirandré for help with the custom Neurostim

462 software and the experimental setup.
463 References

464

465

action verb processing. Cognition 134, 174–184.

466

https://doi.org/10.1016/j.cognition.2014.10.004

467

468

1818–1823. https://doi.org/10.1016/j.cub.2006.07.060

470

Barsalou, L.W., 2008. Grounded Cognition. Annual Review of Psychology 59, 617–645.

471

https://doi.org/10.1146/annurev.psych.59.103006.093639

472

Barsalou, L.W., 1999. Perceptual symbol systems. Behavioral and Brain Sciences 22, 577–609.

473

https://doi.org/10.1017/S0140525X99002149

474

475

consensus paper. Journal of Cognition 6. https://doi.org/10.5334/joc.237

476

477

Benjamini, Y., Hochberg, Y., 1995. Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B

478

(Methodological) 57, 289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x

479

480

Bonnet, C., Bayram, M., El Bouzaïdi Tiali, S., Lebon, F., Harquel, S., Palluel-Germain, R., Perrone-

481

Bertolotti, M., 2022. Kinesthetic motor-imagery training improves performance on lexical-

482

semantic access. PLoS One 17, e0270352. https://doi.org/10.1371/journal.pone.0270352

483

Bunno, Y., 2019. Imagery strategy affects spinal motor neuron excitability: using kinesthetic and somatosensory imagery. NeuroReport 30, 463.

484

https://doi.org/10.1097/WNR.0000000000001218

485

486

Bunno, Y., Fukumoto, Y., Marina, T., Onigata, C., Bunno, Y., Fukumoto, Y., Marina, T., Onigata, C.,

487

2017. The Effect of motor imagery on spinal motor neuron excitability and its clinical use in physical therapy, in: Neurological Physical Therapy. IntechOpen.

488

https://doi.org/10.5772/67471

489

490

Cohen, J., 1988. Statistical power analysis for the behavioral sciences, 2nd ed. Routledge, New York.

491

https://doi.org/10.4324/9780203771587

492

493

261–271. https://doi.org/10.1162/jocn_a_02084

494

495

496

processing. Neuroscience. https://doi.org/10.1016/j.neuroscience.2022.10.022

497

498

simulated within the primary motor cortex. Neuroscience 565, 468–478.

499

https://doi.org/10.1016/j.neuroscience.2024.12.018

500

501

Dupont, W., Papaxanthis, C., Madden-Lombardi, C., Lebon, F., 2024b. Explicit and implicit motor simulations are impaired in individuals with aphantasia. Brain Communications 6, fcae072.

502

https://doi.org/10.1093/braincomms/fcae072

503

504

Towards similar motor representations. Heliyon 9.

505

https://doi.org/10.1016/j.heliyon.2023.e13426

506

507

Facchini, S., Muellbacher, W., Battaglia, F., Boroojerdi, B., Hallett, M., 2002. Focal enhancement of motor cortex excitability during motor imagery: A transcranial magnetic stimulation study.

508

Acta Neurologica Scandinavica 105, 146–151. https://doi.org/10.1034/j.1600-

509

0404.2002.1o004.x

510
511 Fadiga, L., Buccino, G., Craighero, L., Fogassi, L., Gallese, V., Pavesi, G., 1998. Corticospinal excitability
512 is specifically modulated by motor imagery: A magnetic stimulation study. Neuropsychologia
513 37, 147–158. https://doi.org/10.1016/S0028-3932(98)00089-X

514 Fodor, J.A., 1980. The language of thought. 1st ed. Harvard University Press.

515 Fujisawa, R., Kimura, J., Taniguchi, S., Ichikawa, H., Hara, M., Shimizu, H., Iida, H., Yamada, T., Tani, T.,
516 2011. Effect of volitional relaxation and motor imagery on F wave and MEP: do these tasks
517 affect excitability of the spinal or cortical motor neurons? Clin Neurophysiol 122, 1405–1410.
518 https://doi.org/10.1016/j.clinph.2010.12.041

519 Fukumoto, Y., Todo, M., Bizen, H., Kimura, D., Suzuki, T., 2022. Causal relationships between brain
520 and spinal motor neuron excitability during motor imagery: Using NIRS and evoked
521 electromyogram study. Neuroimage: Reports 2, 100083.
522 https://doi.org/10.1016/j.ynirp.2022.100083

523 Gallese, V., Lakoff, G., 2005. The brain's concepts: The role of the sensory-motor system in
524 conceptual knowledge. Cognitive Neuropsychology 22, 455–479.
525 https://doi.org/10.1080/02643290442000310

526 Gentilucci, M., Benuzzi, F., Bertolani, L., Daprati, E., Gangitano, M., 2000. Language and motor
527 control. Experimental Brain Research 133, 468–490. https://doi.org/10.1007/s002210000431
528 Glenberg, A.M., Kaschak, M.P., 2002. Grounding language in action. Psychonomic Bulletin and Review
529 9, 558–565. https://doi.org/10.3758/BF03196313

530 Grosprêtre, S., Lebon, F., Papaxanthis, C., Martin, A., 2019. Spinal plasticity with motor imagery
531 practice. Journal of Physiology 597, 921–934. https://doi.org/10.1113/JP276694

532 Grosprêtre, S., Lebon, F., Papaxanthis, C., Martin, A., 2016a. New evidence of corticospinal network
533 modulation induced by motor imagery. Journal of Neurophysiology 115, 1279–1288.
534 https://doi.org/10.1152/jn.00952.2015

535 Grosprêtre, S., Ruffino, C., Lebon, F., 2016b. Motor imagery and cortico-spinal excitability: A review.
536 European Journal of Sport Science 16, 317–324.
537 https://doi.org/10.1080/17461391.2015.1024756

538 Hara, M., Kimura, J., Walker, D.D., Taniguchi, S., Ichikawa, H., Fujisawa, R., Shimizu, H., Abe, T.,
539 Yamada, T., Kayamori, R., Mizutani, T., 2010. Effect of motor imagery and voluntary muscle
540 contraction on the F wave. Muscle Nerve 42, 208–212. https://doi.org/10.1002/mus.21667

541 Hardwick, R.M., Caspers, S., Eickhoff, S.B., Swinnen, S.P., 2018. Neural correlates of action:
542 Comparing meta-analyses of imagery, observation, and execution. Neuroscience and
543 Biobehavioral Reviews 94, 31–44. https://doi.org/10.1016/j.neubiorev.2018.08.003

544 Hauk, O., Johnsrude, I., Pulvermüller, F., 2004. Somatotopic representation of action words in human
545 motor and premotor cortex. Neuron 41, 301–307. https://doi.org/10.1016/S0896-
546 6273(03)00838-9

547 Helm, F., Marinovic, W., Krüger, B., Munzert, J., Riek, S., 2015. Corticospinal excitability during
548 imagined and observed dynamic force production tasks: Effortfulness matters. Neuroscience
549 290, 398–405. https://doi.org/10.1016/j.neuroscience.2015.01.050

550 Hétu, S., Grégoire, M., Saimpont, A., Coll, M.P., Eugène, F., Michon, P.E., Jackson, P.L., 2013. The
551 neural network of motor imagery: An ALE meta-analysis. Neuroscience and Biobehavioral
552 Reviews 37, 930–949. https://doi.org/10.1016/j.neubiorev.2013.03.017

553 Innocenti, A., De Stefani, E., Sestito, M., Gentilucci, M., 2014. Understanding of action-related and
554 abstract verbs in comparison: a behavioral and TMS study. Cognitive processing 15, 85–92.
555 https://doi.org/10.1007/s10339-013-0583-z

556 Kasai, T., Kawai, S., Kawanishi, M., Yahagi, S., 1997. Evidence for facilitation of motor evoked
557 potentials (MEPs) induced by motor imagery. Brain Research 744, 147–150.
558 https://doi.org/10.1016/S0006-8993(96)01101-8

559 Klepp, A., van Dijk, H., Niccolai, V., Schnitzler, A., Biermann-Ruben, K., 2019. Action verb processing
560 specifically modulates motor behaviour and sensorimotor neuronal oscillations. Scientific
561 reports 9, 15985. https://doi.org/10.1038/s41598-019-52426-9
562 Labruna, L., Fernández-Del-Olmo, M., Landau, A., Duqué, J., Ivry, R.B., 2011. Modulation of the motor
563 system during visual and auditory language processing. Experimental Brain Research 211,
564 243-250. https://doi.org/10.1007/s00221-011-2678-z
565 Lebon, F., Byblow, W.D., Collet, C., Guillot, A., Stinear, C.M., 2012. The modulation of motor cortex
566 excitability during motor imagery depends on imagery quality. European Journal of
567 Neuroscience 35, 323-331. https://doi.org/10.1111/j.1460-9568.2011.07938.x
568 Lefaucheur, J.P., André-Obadia, N., Poulet, E., Devanne, H., Haffen, E., Londero, A., Cretin, B., Leroi,
569 A.M., Radtchenko, A., Saba, G., Thai-Van, H., Litré, C.F., Vercueil, L., Bouhassira, D., Ayache,
570 S.S., Farhat, W.H., Zouari, H.G., Mylius, V., Nicolier, M., Garcia-Larrea, L., 2011. French
571 guidelines on the use of repetitive transcranial magnetic stimulation (rTMS): Safety and
572 therapeutic indications. Neurophysiologie Clinique 41, 221-295.
573 https://doi.org/10.1016/j.neucli.2011.10.062
574 Lotze, M., Montoya, P., Erb, M., Hülsmann, E., Flor, H., Klose, U., Birbaumer, N., Grodd, W., 1999.
575 Activation of cortical and cerebellar motor areas during executed and imagined hand
576 movements: An fMRI study. Journal of Cognitive Neuroscience 11, 491-501.
577 https://doi.org/10.1162/089892999563553
578 Madden-Lombardi, C., Dupont, W., 2023. Experimental methods to study distributed comprehension
579 of action language, in: The Routledge Handbook of Experimental Linguistics. Routledge.
580 Mcneil, C., Butler, J., Taylor, J., Gandevia, S., 2013. Testing the excitability of human motoneurons.
581 Frontiers in Human Neuroscience 7.
582 Mizuguchi, N., Umehara, I., Nakata, H., Kanosue, K., 2013. Modulation of corticospinal excitability
583 dependent upon imagined force level. Experimental Brain Research 230, 243-249.
584 https://doi.org/10.1007/s00221-013-3649-3
585 Moody, C.L., Gennari, S.P., 2010. Effects of implied physical effort in sensory-motor and pre-frontal
586 cortex during language comprehension. NeuroImage 49, 782-793.
587 https://doi.org/10.1016/j.neuroimage.2009.07.065
588 Morey, R.D., Rouder, J.N., 2011. Bayes factor approaches for testing interval null hypotheses. Psychol
589 Methods 16, 406-419. https://doi.org/10.1037/a0024377
590 Muraki, E.J., Dahm, S.F., Pexman, P.M., 2023. Meaning in hand: Investigating shared mechanisms of
591 motor imagery and sensorimotor simulation in language processing. Cognition 240, 105589.
592 https://doi.org/10.1016/j.cognition.2023.105589
593 Négyesi, J., Mori, T., Ataka, K., Izumi, S., Hortobágyi, T., Nagatomi, R., 2020. Navigated transcranial
594 magnetic stimulation of the primary somatosensory cortex evokes motor potentials in
595 healthy humans' flexor carpi radialis muscle - A pilot study. Brazilian Journal of Motor
596 Behavior 14, 110-120. https://doi.org/10.20338/bjmb.v14i3.173
597 New, B., Pallier, C., Brysbaert, M., Ferrand, L., 2004. Lexique 2: A new French lexical database.
598 Behavior Research Methods, Instruments, and Computers 36, 516-524.
599 https://doi.org/10.3758/BF03195598
600 Oldfield, R.C., 1971. The assessment and analysis of handedness: The Edinburgh inventory.
601 Neuropsychologia 9, 97-113. https://doi.org/10.1016/0028-3932(71)90067-4
602 Papeo, L., Pascual-Leone, A., Caramazza, A., 2013. Disrupting the brain to validate hypotheses on the
603 neurobiology of language. Frontiers in Human Neuroscience 7.
604 https://doi.org/10.3389/fnhum.2013.00148
605 Papeo, L., Vallesi, A., Isaja, A., Rumiati, R.I., 2009. Effects of TMS on different stages of motor and
606 non-motor verb processing in the primary motor cortex. PloS one 4, e4508.
607 https://doi.org/10.1371/journal.pone.0004508
608 Pulvermüller, F., 2005. Brain mechanisms linking language and action. Nature Reviews Neuroscience
609 6, 576-582. https://doi.org/10.1038/nrn1706
610 Pulvermüller, F., Fadiga, L., 2010. Active perception: Sensorimotor circuits as a cortical basis for
611 language. Nature Reviews Neuroscience 11, 351-360. https://doi.org/10.1038/nrn2811
612

Pulvermüller, F., Härle, M., Hummel, F., 2001. Walking or talking?: Behavioral and neurophysiological

613

correlates of action verb processing. Brain and Language 78, 143–168.

614

https://doi.org/10.1006/brln.2000.2390

615

Pylyshyn, Z., 1984. Computation and cognition: Towards a foundation for cognitive science.

616

Rabahi, T., Fargier, P., Rifai Sarraj, A., Clouzeau, C., Massarelli, R., 2013. Effect of action verbs on the

617

performance of a complex movement. PLoS ONE 8, e68687.

618

https://doi.org/10.1371/journal.pone.0068687

619

Rabahi, T., Sarraj, A.R., Fargier, P., Clouzeau, C., Massarelli, R., 2012. Action verb and motor

620

performance. Kinesitherapie 12, 42–46. https://doi.org/10.1016/j.kine.2012.04.003

621

Rossini, P.M., Burke, D., Chen, R., Cohen, L.G., Daskalakis, Z., Di Iorio, R., Di Lazzaro, V., Ferreri, F.,

622

Fitzgerald, P.B., George, M.S., Hallett, M., Lefaucheur, J.P., Langguth, B., Matsumoto, H.,

623

Miniussi, C., Nitsche, M.A., Pascual-Leone, A., Paulus, W., Rossi, S., Rothwell, J.C., Siebner,

624

H.R., Ugawa, Y., Walsh, V., Ziemann, U., 2015. Non-invasive electrical and magnetic

625

stimulation of the brain, spinal cord, roots and peripheral nerves: Basic principles and

626

procedures for routine clinical and research application. An updated report from an I.F.C.N.

627

Committee. Clinical neurophysiology : official journal of the International Federation of

628

Clinical Neurophysiology 126, 1071–1107. https://doi.org/10.1016/J.CLINPH.2015.02.001

629

Rossini, P.M., Rossi, S., Pasqualetti, P., Tecchio, F., 1999. Corticospinal excitability modulation to hand

630

muscles during movement imagery. Cerebral Cortex 9, 161–167.

631

https://doi.org/10.1093/cercor/9.2.161

632

Sondergaard, R.E., Martino, D., Kiss, Z.H.T., Condliffe, E.G., 2021. TMS motor mapping methodology

633

and reliability: A structured review. Frontiers in Neuroscience 15, 970.

634

https://doi.org/10.3389/FNINS.2021.709368/BIBTEX

635

Sparing, R., Buelte, D., Meister, I.G., Pauš, T., Fink, G.R., 2008. Transcranial magnetic stimulation and

636

the challenge of coil placement: A comparison of conventional and stereotaxic

637

neuronavigational strategies. Human Brain Mapping 29, 82–96.

638

https://doi.org/10.1002/hbm.20360

639

Suzuki, T., Bunno, Y., Onigata, C., Tani, M., Uragami, S., 2013. Excitability of spinal neural function

640

during several motor imagery tasks involving isometric opponents' activity.

641

NeuroRehabilitation 33, 171–176. https://doi.org/10.3233/NRE-130942

642

Taniguchi, S., Kimura, J., Yamada, T., Ichikawa, H., Hara, M., Fujisawa, R., Shimizu, H., Tani, T., 2008.

643

Effect of motion imagery to counter rest-induced suppression of F-wave as a measure of

644

anterior horn cell excitability. Clin Neurophysiol 119, 1346–1352.

645

https://doi.org/10.1016/j.clinph.2007.11.179

646

Taylor, J.L., 2006. Stimulation at the cervicomedullary junction in human subjects. J Electromyogr

647

Kinesiol 16, 215–223. https://doi.org/10.1016/j.jelekin.2005.07.001

648

Taylor, J.L., Petersen, N.T., Butler, J.E., Gandevia, S.C., 2002. Interaction of transcranial magnetic

649

stimulation and electrical transmastoid stimulation in human subjects. J Physiol 541, 949–

650

958. https://doi.org/10.1113/jphysiol.2002.016782

651

Taylor, L.J., Zwaan, R.A., 2008. Motor resonance and linguistic focus. Quarterly Journal of

652

Experimental Psychology 61, 896–904. https://doi.org/10.1080/17470210701625519

653

Tettamanti, M., Buccino, G., Saccuman, M.C., Gallese, V., Danna, M., Scifo, P., Fazio, F., Rizzolatti, G.,

654

Cappa, S.F., Perani, D., 2005. Listening to action-related sentences activates fronto-parietal

655

motor circuits. Journal of Cognitive Neuroscience 17, 273–281.

656

https://doi.org/10.1162/0898929053124965

657

Tomasino, B., Fink, G.R., Sparing, R., Dafotakis, M., Weiss, P.H., 2008. Action verbs and the primary

658

motor cortex: a comparative TMS study of silent reading, frequency judgments, and motor

659

imagery. Neuropsychologia 46, 1915–26.

660

https://doi.org/10.1016/j.neuropsychologia.2008.01.015

661

Tomasino, B., Rumiati, R.I., 2013. At the Mercy of Strategies: The Role of Motor Representations in

662

Language Understanding. Frontiers in Psychology 4.

663

https://doi.org/10.3389/fpsyg.2013.00027
664 Tremblay, F., Tremblay, L.E., Colcer, D.E., 2001. Modulation of corticospinal excitability during

665 imagined knee movements. Journal of Rehabilitation Medicine 33, 230–234.

666 https://doi.org/10.1080/165019701750419635

667 Van Dam, W.O., Rueschemeyer, S.A., Bekkering, H., 2010. How specifically are action verbs

668 represented in the neural motor system: An fMRI study. NeuroImage 53, 1318–1325.

669 https://doi.org/10.1016/j.neuroimage.2010.06.071

670 Wu, H., Mai, X., Tang, H., Ge, Y., Luo, Y.J., Liu, C., 2013. Dissociable somatotopic representations of

671 Chinese action verbs in the motor and premotor cortex. Scientific Reports 3.

672 https://doi.org/10.1038/srep02049

673 Yang, J., Shu, H., 2014. Passive reading and motor imagery about hand actions and tool-use actions:

674 An fMRI study. Experimental Brain Research 232, 453–467. https://doi.org/10.1007/s00221-

675 013-3753-4

676 Zwaan, R.A., Taylor, L.J., 2006. Seeing, acting, understanding: Motor resonance in language

677 comprehension. Journal of Experimental Psychology: General 135, 1–11.

678 https://doi.org/10.1037/0096-3445.135.1.1

679

680
## Appendix

<table><caption>Table A1: T-test results concerning the linguistic and psycholinguistic characteristics of stimuli.</caption><thead><tr><th rowspan="2">Factors</th><th>Means</th><th>Means</th><th>T-tests</th></tr><tr><th>Action</th><th>Abstract</th><th>(corrected p-value)</th></tr></thead><tbody><tr><td>Written frequency</td><td>8.57±13.58</td><td>17.42±40.87</td><td>P = 0.99</td></tr><tr><td>Number of characters</td><td>6.23±1.29</td><td>6.56±1.47</td><td>P = 1</td></tr><tr><td>Number of syllables</td><td>1.69±0.58</td><td>1.87±0.56</td><td>P = 0.87</td></tr><tr><td>Spelling neighbors</td><td>5.46±4.64</td><td>4.13±4.37</td><td>P = 0.95</td></tr><tr><td>Number of homographs</td><td>1.48±0.64</td><td>1.33±0.58</td><td>P = 1</td></tr><tr><td>Hand related (/5)</td><td>4.54±0.42</td><td>0.78±0.58</td><td>P < 0.01</td></tr><tr><td>Imageability</td><td>2.84±0.27</td><td>2.35±0.36</td><td>P < 0.01</td></tr></tbody></table>

<table><caption>Table A2: Comparison of the MEP and CMEP (%M<sub>MAX</sub>) at rest. A paired Wilcoxon signed-rank confirmed that the MEP and CMEP recruited the same amount of motor units (t = .722, p = .481).</caption><thead><tr><th>MEP</th><th>CMEP</th></tr></thead><tbody><tr><td>3.43±2.78</td><td>2.95±2.43</td></tr></tbody></table>
Table A3: EMGrms activity (mean ±SD) in µV recorded for the Flexor Carpi Radialis before the TMS, CMS and $M_{MAX}$ artifact for each condition (window of 200ms prior the artifact). The absence of muscular pre-activity was confirmed by separate Friedman ANOVAs revealing no significant difference in EMGrms before the MEP ($p = 0.118$; $r = 0.069$, Kendall's W = 0.13), CMEP ($p = 0.313$; $r = 0.013$, Kendall's W = 0.08), or $M_{MAX}$ ($p = 0.114$; $r = 0.070$, Kendall's W = 0.13) between rest, motor imagery, action and non-action reading conditions.

<table><thead><tr><th></th><th>Rest</th><th>Action reading</th><th>Abstract reading</th><th>Motor imagery</th></tr></thead><tbody><tr><th>MEP</th><td>1.10±0.50</td><td>1.31±0.69</td><td>1.13±0.51</td><td>1.21±0.48</td></tr><tr><th>CMEP</th><td>1.41±0.67</td><td>1.61±0.84</td><td>1.45±0.61</td><td>1.52±0.77</td></tr><tr><th>M<sub>MAX</sub></th><td>1.24±0.44</td><td>1.34±0.53</td><td>1.36±0.83</td><td>1.44±0.69</td></tr></tbody></table>

Table A4: Differences in target positioning (mm), angular alignment (°), and twist (°) of the TMS coil relative to the hotspot were assessed for each condition. Separate Friedman ANOVAs confirmed the absence of significant coil movement, revealing no significant differences in target positioning ($p = 0.379$; $r = 0.001$, Kendall's W = 0.07), angular alignment ($p = 0.240$; $r = 0.029$, Kendall's W = 0.09), or twist ($p = 0.379$; $r = 0.002$, Kendall's W = 0.07) of the TMS coil across conditions.

<table><thead><tr><th></th><th>Rest</th><th>Action reading</th><th>Abstract reading</th><th>Motor imagery</th></tr></thead><tbody><tr><th>Target positioning</th><td>0.35±0.06</td><td>0.34±0.07</td><td>0.33±0.07</td><td>0.32±0.06</td></tr><tr><th>Angular alignment</th><td>0.68±0.19</td><td>0.58±0.23</td><td>0.60±0.18</td><td>0.57±0.23</td></tr><tr><th>Twist</th><td>-0.16±0.68</td><td>-0.04±0.61</td><td>-0.24±0.68</td><td>-0.18±0.51</td></tr></tbody></table>
<table><caption>Table A5: MNI coordinates (x, y, z) of TMS stimulations localization averaged for each participant.</caption><thead><tr><th></th><th>X</th><th>Y</th><th>Z</th></tr></thead><tbody><tr><td>S01</td><td>-36.830</td><td>-8.721</td><td>67.085</td></tr><tr><td>S02</td><td>-33.727</td><td>-11.493</td><td>69.690</td></tr><tr><td>S03</td><td>-33.705</td><td>-11.651</td><td>69.745</td></tr><tr><td>S04</td><td>-39.969</td><td>-12.696</td><td>66.306</td></tr><tr><td>S05</td><td>-39.949</td><td>-12.769</td><td>66.346</td></tr><tr><td>S06</td><td>-39.846</td><td>-12.678</td><td>66.388</td></tr><tr><td>S07</td><td>-36.914</td><td>-15.605</td><td>68.902</td></tr><tr><td>S08</td><td>-36.965</td><td>-8.913</td><td>67.060</td></tr><tr><td>S09</td><td>-37.110</td><td>-8.697</td><td>67.284</td></tr><tr><td>S10</td><td>-40.006</td><td>-12.765</td><td>66.305</td></tr><tr><td>S11</td><td>-40.095</td><td>-12.736</td><td>66.231</td></tr><tr><td>S12</td><td>-33.913</td><td>-11.772</td><td>69.662</td></tr><tr><td>S13</td><td>-36.995</td><td>-15.875</td><td>68.901</td></tr><tr><td>S14</td><td>-37.108</td><td>-8.933</td><td>66.974</td></tr><tr><td>S15</td><td>-37.028</td><td>-15.808</td><td>68.868</td></tr></tbody></table>