# Negated actions are simulated within the primary motor cortex

W. Dupont, Charalambos Papaxanthis, L. Lurquin, Florent Lebon, C. Madden-Lombardi

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W. Dupont, Charalambos Papaxanthis, L. Lurquin, Florent Lebon, C. Madden-Lombardi. Negated actions are simulated within the primary motor cortex. Neuroscience, 2025, 565, pp.468-478. 10.1016/j.neuroscience.2024.12.018. hal-04952248

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Negated actions are simulated within the primary motor cortex

W. Dupont<sup>a, *</sup> <sup> ID </sup>, C. Papaxanthis<sup>a</sup>, L. Lurquin<sup>a</sup>, F. Lebon<sup>a,b,1</sup> <sup> ID </sup>, C. Madden-Lombardi<sup>a,c,1</sup> <sup> ID </sup>

ARTICLE INFO

Keywords:

Action language

Negation

TMS

Motor simulation

Embodied language

A B S T R A C T

Controversy persists regarding the representation of linguistically negated actions, specifically concerning activation and inhibitory mechanisms in the motor system, and whether negated action sentences evoke an initial motor simulation of the action to be negated. We conducted two experiments probing corticospinal excitability (CSE) and short-interval intracortical inhibition (SICI) in the primary motor cortex at different latencies while reading affirmative and negative action sentences.

In experiment one, twenty-six participants read action and non-action sentences in affirmative or negative forms. Using transcranial magnetic stimulation, we probed CSE in hand muscles at rest and at several latencies after verb presentation. We observed a greater CSE for action sentences compared to non-action sentences, regardless of verb form.

In experiment two, nineteen participants read affirmative and negative action sentences. We measured CSE and SICI at short and long latencies after verb presentation. CSE was greater for affirmative and negative action sentences at both latencies compared to rest. SICI did not change at the short latency but increased at longer latencies, regardless of verb form.

Negated action sentences showed the same motor excitability as affirmed action sentences with no additional inhibition at early latencies. These results lend support for the idea that actions to be negated are initially simulated within the motor system. Neural differences between affirmative and negative action sentences may occur outside the primary motor cortex.

Introduction

Over the past few decades, a growing body of research has estab-
lished a clear link between perceptual-motor and language processes
(Barsalou, 1999, 2008; Barsalou et al., 2003; Decety & Grèzes, 2006;
Fischer & Zwaan, 2008; Gallese & Lakoff, 2005; Glenberg & Gallese,
2012; Hoeben Mannaert et al., 2020; Jeannerod, 2008; Pulvermüller &
Fadiga, 2010; Zwaan & Taylor, 2006). Such research suggests that lan-
guage, along with other cognitive functions, is processed in a distributed
manner that includes areas of the brain that were thought to be reserved
for perception and action. Corroborating this recent distributed view of
language processing, the involvement of the motor system during the
comprehension of action language has been reported by a variety of
methodologies, such as fRMI (Hauk et al., 2004; Van Dam et al., 2010),
EEG (Beres, 2017; Kellenbach et al., 2002; Pulvermüller et al., 2001; Xu
et al., 2016), psychophysics (Andres et al., 2015; Klepp et al., 2019;

Pulvermüller et al., 2001; Rabahi et al., 2012, 2013), and Transcranial Magnetic Stimulation (TMS) (Dupont et al., 2022, 2024; Innocenti et al., 2014; Labruna et al., 2011; Papeo et al., 2009, 2015).

While it is clear that action language engages the motor system, this involvement seems to depend on various experimental elements, such as temporal factors (Borreggine & Kaschak, 2006; Kaschak & Borreggine, 2008), choice of stimuli (Papeo et al., 2009), and contextual factors (Beauprez et al., 2018; Gilead et al., 2013; Raposo et al., 2009; van Dam et al., 2010; Van Dam et al., 2012, 2014; Zwaan et al., 2010). One contextual factor that may modulate the activation of the motor system during action reading is linguistic negation. Negation is a linguistic operator used to reject, deny, or express non-existence. Processing negation seems to require additional resources, as negated sentences yield longer processing times and higher error rates than affirmative sentences (Carpenter & Just, 1975; Clark, 1974; Kaup, Zwaan, et al., 2007; Lüdtke, 2006; except in cases of contextually embedded negated

<footnote><sup>a</sup> INSERM UMR1093-CAPS, Université de Bourgogne, UFR des Sciences du Sport, F-21000, Dijon, France</footnote>

<footnote><sup>b</sup> Institut Universitaire de France (IUF), Paris, France</footnote>

<footnote><sup>c</sup> Centre National de la Recherche Scientifique (CNRS), Paris, France</footnote>

<footnote>* Corresponding author.
E-mail address: William.dupont@u-bourgogne.fr (W. Dupont).</footnote>

<footnote n="1">¹ Equal contribution</footnote>
sentences, Glenberg et al., 1999; Orenes et al., 2016). Traditional (amodal, non-distributed) theories of language comprehension could easily explain these results in terms of the negation operator as an extra-linguistic processing step. Distributed theories of language comprehension have also offered explanations for negation processing in terms of a simulation of the negated situation. Some researchers posit that the negated situation can be simulated in a single step (Mayo et al., 2004; Nieuwland & Kuperberg, 2008), whereas others postulate a two-step process to account for the negated information (Kaup, Yaxley, et al., 2007; Lüdtke et al., 2008).

According to one-step models, the representation of the negated
action is immediately obstructed, as reflected in decreased behavioral
performance and reduced activation of the primary motor and premotor
cortices for negative compared to affirmative sentences (Aravena et al.,
2012; Bartoli et al., 2013; Carpenter et al., 1999; Christensen, 2009;
Foroni & Semin, 2013; García-Marco et al., 2019; Tettamanti et al.,
2008; Tomasino et al., 2010). Two-step models stipulate that both
affirmative and negative representations are engaged after reading
negative sentences, necessitating additional cognitive effort and
possible competition (Kaup, Yaxley, et al., 2007; Lüdtke et al., 2008).
Specifically, the representation of the action to be negated is engaged in
the first step (as in affirmed actions), whereas the representation of the
actual situation with the negated action is engaged in a second step. For
instance, reading “not smoking” in a sentence would first activate a
simulation of smoking, and then a simulation without smoking. The
initial representation of the to-be-negated information allows compre-
hension of what has been negated. Without this step, it would be less
straightforward to comprehend the difference between, for example,
“not smoking” and “not swimming,” as the second-step simulation
without the initial representation of smoking might be identical to a
second-step simulation of “not swimming” without the initial repre-
sentation of swimming. This idea is based on studies reporting initial
faster reaction times for the negated content, followed later by faster
reaction times for the actual situation described in the sentence
(Anderson et al., 2010; Fischler et al., 1983; Kaup et al., 2005, 2006;
Kaup, Yaxley, et al., 2007; Lüdtke et al., 2008; Scappini & Delfitto,
2015). Furthermore, contextual and pragmatic aspects might influence
the presence of both affirmative and negative representations upon
reading negative sentences (see “question under discussion”, Roberts,
2012; Tian et al., 2010; Tian & Breheny, 2016).

In comparison to fMRI, the high temporal resolution of TMS provides a relevant tool to probe the involvement of the motor system in language processing, and it may help to shed light on the neural mechanisms underlying negation. TMS studies showed that corticospinal excitability, a marker of the motor system’s activation, increases during affirmative action verb reading (Innocenti et al., 2014; Labruna et al., 2011; Papeo et al., 2009). Furthermore, Papeo et al. (2016) reported that action verbs presented in the affirmative form elicited greater corticospinal excitability than their negative counterparts at 250, 400, and 550 ms after presentation. These findings suggest early inhibitory mechanisms during the reading of negative action sentences, extending the findings of previous EEG studies (Beltrán et al., 2018, 2019, 2021; De Vega et al., 2016; Liu et al., 2020).

In sum, the existing literature on negation processing provides con-
flicting results concerning the existence of an initial simulation of the to-
be negated action (similar to affirmed action sentences). As corticospinal
excitability was not normalized to a rest condition in previous studies,
comparisons are limited to affirmation versus negation, or action versus
non-action conditions. Therefore, it cannot be concluded that negated
and affirmed sentences modulate corticospinal excitability differently
compared to a resting state. Furthermore, while the literature suggests
that inhibitory mechanisms modulate the motor system's involvement
in processing negated sentences (Papeo et al., 2016), it remains unclear
how facilitatory and inhibitory mechanisms might interact within the
primary motor cortex (M1) upon reading a negative action sentence, and
more importantly, when these mechanisms become active within this

region. In the current study, we aim to directly test whether a motor
simulation of the action to be negated is initially engaged upon reading
negative action sentences, and how inhibitory mechanisms might
interact within the motor system at early and late intervals. We per-
formed two TMS experiments to investigate the neural modulation along
the corticospinal track and within M1 during the reading of affirmative
and negative action sentences. In a first experiment, we measured
motor-evoked potentials (MEP) amplitude, by means of single-pulse
TMS, at different latencies after verb presentation to determine
whether the corticospinal excitability increased or/and temporally
shifted for negated, affirmed, and non-action sentences. In a second
experiment, we probed the modulation of corticospinal excitability and
short-interval intracortical inhibition (SICI), by means of single and
paired-pulse TMS respectively, delivered at short and long latencies
after verb presentation in negated and affirmed action sentences.

In the case of one-step processing, we would expect an increase of corticospinal excitability only for affirmed action sentences but not for negated or non-action sentences in Experiment 1, and an immediate inhibition for negated sentences compared to affirmed sentences, i.e., greater SICI, in Experiment 2. In the case of two-step processing, we would expect both the negated and the affirmed sentences to show an increase of corticospinal excitability in comparison to non-action sentences at early latencies, followed by possible inhibition for negated sentences only at longer latencies.

Material and method

Experiment 1

Participants

Twenty-six healthy right-handed individuals (13 women; mean age = 22.8 years-old; range 18–28) participated in experiment 1. Participants’ handedness was assessed by the Edinburgh inventory (range 0.25–1; Oldfield 1971). All participants were French native speakers and had normal or corrected-to-normal vision, without neurological, physical, or psychiatric pathology. Volunteers were first approved for participation by a medical doctor and confirmed their participation with written consent. The experimental protocol and procedures were in accordance with the Declaration of Helsinki and were granted ethics committee approval (excluding pre-registration; Comité de Protection des Personnes Sud-Ouest et Outre Mer III, ClinicalTrials.gov Identifier: NCT03334526-07/11/2017).

Stimuli

One hundred and sixty (n = 160) French sentences were created; half (n = 80) referring to hand actions (e.g., “The potato is cooked, I peel it”) and half (n = 80) describing non-actions (e.g., “The potato is cooked, I leave it”), corresponding to the experimental conditions Action and Non-Action, respectively. As our hypotheses (and TMS measure) concerned only actions implicating the right hand, our Non-Action stimuli also included few actions not implicating the hand (e.g., “The hammer is on the ground, I kick it”). We considered it appropriate to include non-manual actions in the non-action list, given that previous TMS and fMRI experiments have reported distinct and somatotopic modulations of corticospinal excitability or brain activity in the primary motor cortex for hand actions and non-hand actions (Aziz-Zadeh et al., 2006; Hauk et al., 2004; Papeo et al., 2009), so these non-manual actions should not engage our region of interest. Any residual excitation for non-manual actions could only hurt our chances of observing the predicted difference between manual actions and non-actions.

All sentences were presented in the first-person present tense and
were created so that the target verb appeared at the end of the sentence.
The final pronoun-verb segment was presented alone on a subsequent
screen (Fig. 1). This presentation format was chosen for three reasons; 1)
to control the timing between the presentation of the target action word
and the TMS measure, 2) to avoid any additional words from interfering
<figure><img src="image_2.png" /><figcaption>Fig. 1. Experimental procedure showing an affirmative, a negative, and a rest trial. Sentences were presented in a Negative or Affirmative form. Single-pulse TMS was triggered over the left hemisphere at rest or at various delays after the verb presentation, yielding motor-evoked potentials that were recorded in the right index finger.</figcaption></figure>

with the TMS pulse, and 3) to ensure that the simulation of the target action could proceed immediately upon presentation of the verb without waiting for further information. The target verbs were presented either in affirmative form (n = 40) (e.g., “The potato is cooked, I peel it”) or in negative form (n = 40) (e.g., “The potato is cooked, I don’t peel it”), corresponding to the experimental conditions Affirmative and Negative form, respectively. All stimuli order was randomized and counterbalanced.

Various psycholinguistic factors (e.g., written frequency, number of letters and syllables, spelling neighbors, and semantic analysis) were controlled for the verb conditions using the Lexique.org database (New et al., 2004). The statistical tests carried out showed no significant difference between the conditions for all the psycholinguistic factors (See Supplementary section). To confirm the hand-related aspect of the stimuli, we conducted a pilot experiment in which ten participants were asked to rate on a scale from 1 to 5 whether a sentence described a manual action or not (1 = absolutely not a hand action, and 5 = entirely a hand action). A t-test revealed a significant difference (p < 0.001) between the action (4.44 ± 0.89) and non-action (1.38 ± 1.28) verbs.

## Procedure

Participants sat in an armchair and read the sentences on a 19-inch LCD monitor. A custom-made software synchronized the presentation of the stimuli, the TMS pulses, and the electromyographic (EMG) recording. Participants were instructed to stay still while they silently read the sentences. Corticospinal excitability was assessed at rest and during the reading tasks at various stimulation latencies (200, 300, 400, 500, or 600 ms after the verb onset). Importantly, the stimulations at 200, 300, 400, 500, and 600 ms were each delivered in separate trials, not within the same trial. These latencies were chosen based on previous electroencephalogram and TMS studies showing 200 ms to 400 ms as latencies for action semantic processing in parietal and frontal regions (Beres, 2017; Hauk et al., 2006; Kellenbach et al., 2002; Pulvermüller et al., 2001). The latest latencies (500 and 600 ms) were added to catch a potential late shift in the activation latency for negative compared to affirmative sentences.

A familiarization session was conducted before the experimental session, in which participants saw four trials, each starting with a fixation cross (500 ms), followed by a sentence (3000 ms), the pronoun-verb target (2000 ms), then a break before the next trial (5000 ms). Once the participant understood this procedure, four new practice trials were presented, including TMS pulses after the appearance of the target verb.

There was an approximate interval of 9 s between two TMS pulses.

The experimental session was divided into 8 blocks of 43 trials each, yielding 344 trials in total during the experiment. Among the 43 trials in each block, 3 trials included only TMS pulses at rest (upon presentation of the fixation cross), which served as reference stimulations and allowed for comparisons across experimental conditions in that block. For the 40 remaining trials, the TMS pulses were delivered after the verb presentation. In each block, the number of stimulations was equally distributed across all conditions (Action vs. Non-action and Negative vs. Affirmative), and also across the five different stimulation latencies. 16 stimulations were delivered at each latency in each condition, presenting a well-balanced compromise between the duration of the experiment, which encompass 4 distinct conditions and 5 latencies, and a favorable probability of attaining a 95 % confidence interval for corticospinal excitability (Cuypers et al., 2014). Moreover, to avoid mental fatigue and lack of concentration, we introduced a two-minute break between each block.

**EMG recording and TMS set-up.** The EMG signal was recorded using 10 mm-diameter surface electrodes (Contrôle Graphique Médical, Brice Comte-Robert, France) placed over the right first dorsal interosseous (FDI) muscle. Before placing the electrodes, the skin was shaved and cleaned to reduce EMG signal noise (<20 μV). EMG signals were amplified and bandpass filtered on-line (10–500 Hz, Biopac Systems Inc.) and digitized at 2000 Hz for off-line analysis. We calculated the EMGrms for further analysis. Single-pulse TMS was delivered with a figure-eight coil (70 mm in diameter) connected to a Magstim 200 stimulator (Magstim Company Ltd, Whitland). The coil was positioned over the motor area controlling the right FDI muscle. The coil rested tangential to the scalp with the handle pointing backward and laterally at a 45° angle from the midline. Mappings of each participant’s motor cortex determined the optimal coil position (hotspot), where stimulation evoked the highest and most consistent MEP amplitude for the FDI muscle. The hotspot was marked on a bathing cap, and the coil was meticulously placed for each stimulation. We measured the resting motor threshold, which is the minimal TMS intensity to induce a peak-to-peak MEP amplitude of 50 μV in the right FDI muscle for 5 trials out of 10 (Rossini et al., 2015). During the experimental session, the TMS intensity was set at 130 % of the individual resting motor threshold.

**Data and statistical analysis.** Using G* Power (version 3.1.9.4., Faul
et al., 2007) with a medium effect size of 0.30 and a power of 0.9, it was estimated that 22 participants would be needed to observe a potential interaction between Action and Polarity. Due to potential loss of data (10 %) and the variability of TMS-induced responses that we may observe, we concluded that 24 participants would be required for statistical analysis.

The EMG signal was extracted with Matlab (The MathWorks, Natick, Massachusetts, USA), and the peak-to-peak MEP amplitude was measured for all conditions. Before analysis, we removed data falling 2 standard deviations (SDs) above or below individual means for each condition (4.40 % of all trials). Then, the individual mean MEP amplitude for each condition was normalized to rest (% to rest = (condition - rest) / rest) X 100). Of the 26 participants, two were excluded due to extreme values (i.e., over 2 SDs from the group mean), leaving 24 participants in the final analysis. Statistics and data analyses were performed using the Statistica software (Stat Soft, France).

Data normality and sphericity were verified using Shapiro-Wilk and Mauchly tests. In order to assess a general shift in the increase of corticospinal excitability during negated action processing, we first performed a repeated measures ANOVA with Action (Action vs. Non-Action), Polarity (Affirmative vs. Negative) and Latency (200, 300, 400, 500, vs. 600 ms) as within-subject factors. This initial analysis enables us to determine whether the latency of increased corticospinal excitability is influenced by Action or Polarity. The semantically-driven increase in corticospinal excitability that we were interested in measuring would likely be ephemeral, and therefore not present at all latencies. As this increase would likely vary across conditions and participants, we then selected the latency for which the MEP amplitude was at its peak. More specifically, we isolated the highest increase in MEP amplitude among the five stimulation latencies for each participant in each condition. This subject-specific peak method accommodates individual variability in the latency of action semantic processing, and affords probing the motor system when the action representation is active. We submitted these peaks to a repeated measures ANOVA with Action (Action vs. Non-Action) and Polarity (Affirmative vs. Negative) as within-subject factors. Then, one-sample t-tests were used to compare condition MEPs to zero (rest). Finally, to be certain that our results were not biased by muscular activity preceding the TMS pulse, a Friedman ANOVA was used to compare the EMGrms (100 ms-window prior to the artifact) between rest and our experimental conditions (See Supplementary section). The data are presented as mean values (±standard deviation) and the alpha value was set at 0.05.

## Experiment 2

### Participants

Nineteen healthy right-handed individuals (7 women; mean age = 22.05 years-old; range 18–27) participated in the experiment. Participants' handedness was assessed by the Edinburgh inventory (range 0.2–1; Oldfield 1971). All participants were French native speakers with normal or corrected-to-normal vision, without neurological, physical, or psychiatric pathology. Volunteers were first approved for participation by a medical doctor and confirmed their participation with written consent. The experimental protocol and procedures were in accordance with the Declaration of Helsinki and were granted ethics committee approval (excluding pre-registration; CPP SOOM III, ClinicalTrials.gov Identifier: NCT03334526).

### Procedure and stimuli

Stimuli and task were identical to Experiment 1, except for two features. First, we only presented affirmative and negative action sentences (no non-action sentences). Second, we assessed corticospinal excitability and short-interval intracortical inhibition (SICI) at rest or at short and long latencies after verb presentation. For the short latencies, we determined which of 3 latencies (200, 300, and 400 ms) yielded the

highest MEP amplitude (single-pulse TMS) on a set of practice trials at the beginning of the experiment for each participant, and we used this peak latency as their short latency to probe corticospinal excitability and SICI during the experiment. For the long latency, we stimulated at 700, 800, and 900 ms after verb presentation for single- and paired-pulse TMS during the experiment, then chose the latency that induced the greatest increase of corticospinal excitability (single-pulse TMS) and the greatest SICI (paired-pulse TMS) for each individual and each condition for analyses. The choice of the late range from 700 to 900 ms was informed by a second pilot experiment as well as previous research on the two-step process of negation processing indicating that the second step usually occurs around 1-second (Kaup et al., 2006; Kaup et al., 2007; Lüdtke et al., 2008).

Twenty single and twenty paired TMS pulses were delivered per condition (rest, affirmative verb, negative verb) at 4 latencies: one individualized short latency, and 3 long latencies (700, 800 and 900 ms).

### EMG recordings and TMS set-up

The EMG recordings and TMS set-up were almost identical to Experiment 1, except for the TMS parameters and stimulator (Magstim BiStim²) and measurements described above. TMS responses were measured via an adaptive threshold-tracking technique.

**Adaptive threshold-hunting technique and MepTarget.** We used an available online freeware (TMS Motor Threshold Assessment Tool, MTAT 2.0) based on a maximum-likelihood Parameter Estimation by Sequential Testing. We first determined the individual MepTarget amplitude, which is half of the individual maximum MEP amplitude at rest. To determine the MEPTarget amplitude that would be used for all conditions in the experiment, we initially performed a stimulus/response curve at the beginning of the experiment. Specifically, we stimulated the participants starting from 120 % of their individual resting motor threshold and increased the intensity in 10 % increments (12 stimulations per intensity) until the average response reached its maximum. To illustrate, if a participant's MEPmax amplitude corresponds to 2 mV at 150 % of the motor threshold, then the MEPTarget amplitude will be set at 1 mV for the entire experiment and all conditions. Then, we modulated the TMS stimulation intensity of the test stimulation (TS) to match the same MepTarget amplitude for each condition. Therefore, we did not analyze the MEP amplitude as in Experiment 1, but rather the intensity of the TS stimulation, namely the percentage of Maximal Stimulator Output (%MSO). Thus, the intensity of the TS was adjusted trial-by-trial over 20 stimulations per condition. After these 20 stimulations, the software consistently and accurately estimated the %MSO required to achieve the MEPTarget. This approach avoids the recurrent problem of a floor effect in SICI protocols, where inhibitory networks are excessively powerful and the MEPs are occluded, preventing any analysis (Cirillo et al., 2018; Cirillo & Byblow, 2016). From an interpretative standpoint, our approach, which analyzes the %MSO required to achieve the MEPTarget, implies unconventional interpretations. For example, if achieving the MEPTarget during action reading conditions requires a stimulation intensity of 45 %MSO, while at rest or during the non-action reading conditions it requires 50 %MSO, this indicates heightened corticospinal excitability in response to action verbs. Similarly, the same rationale is applied to interpret the SICI results.

**Single-pulse TMS.** The adaptive threshold-tracking single-pulse TMS technique was employed to determine the unconditioned TS stimulation intensity needed to reach the MepTarget amplitude in each condition. For corticospinal excitability, we expressed the single-pulse TS intensity of each experimental condition as a percentage of the single-pulse TS intensity measured at rest (%).

SICI. The adaptive threshold-tracking technique was also used to
investigate SICI modulations during action reading. A subthreshold conditioning pulse (CS) was applied before the TS. The interstimulus interval between conditioning and test stimulations was set at 3 ms, and the conditioning stimulation (CS) was fixed at 60 % of the resting motor threshold (Chen, 2004; Cirillo et al., 2018; Kujirai et al., 1993; Neige et al., 2022). The amount of SICI (expressed in INH%) was quantified for each condition using the following equation (Fisher et al., 2002):

$$ \text{INH}(\%) = \frac{(\text{conditioned TS intensity} - \text{unconditioned TS intensity})}{\text{unconditioned TS intensity}} \times 100 $$

This percentage of inhibition for SICI allowed us to assess the level of intracortical inhibition within M1. This ratio for the experimental condition was then normalized to the ratio at rest (Δ).

## Data and statistical analysis

First, we estimated an effect size of 0.35 from the interaction between Action and Latency in our first experiment (ηp² = 0.114 and power of 0.9). Using G* Power (version 3.1.9.4., Faul et al., 2007), we estimated that around 16 participants would be needed to observe a potential interaction between Polarity and Latency. Due to potential loss of data (10 %) and the variability of TMS-induced responses, 19 participants have been considered for statistical analysis. Statistics and data analyses were performed using the Statistica software (Stat Soft, France). Data normality and sphericity were verified using Shapiro-Wilk and Mauchly tests. As in the first experiment, we selected the timing for which the average corticospinal excitability was highest for an individual, corresponding to the latency where stimulation intensity (expressed %MSO) was the lowest to elicit the MepTarget during single pulse stimulation. Afterwards, we compared MEPs for each condition at

zero (rest) using one-sample t-tests. Then, to assess the influence of Latency and Polarity on corticospinal excitability, we realized a 2-by-2 repeated-measures ANOVA with Latency (Short vs. Long) and Polarity (Affirmative vs. Negative) as within-subject factors. Using the same peak latency that was selected in the corticospinal excitability measure, we performed the same statistical design on SICI. Finally, to be certain that our results were not biased by muscular activity preceding the TMS pulse, we compared the EMGrms (100 ms-window prior to TMS artifact) between rest and our experimental conditions with Friedman ANOVA (See Supplementary section). The data are presented as mean values (± standard deviation) and the alpha value was set at 0.05.

## Results

### Experiment 1

We observed a main effect of Latency (F₄,₉₂ = 9.928, p < 0.000, ηp² = 0.301) and an interaction between Action and Latency (F₄,₉₂ = 2.984, p = 0.022, ηp² = 0.114), with greater corticospinal excitability for action compared to non-action sentences only at 300 ms (p = 0.009). However, we did not observe a main effect of Action (F₁,₂₃ = 1.545, p = 0.226, ηp² = 0.062) or Polarity (F₁,₂₃ = 0.034, p = 0.564, ηp² = 0.014), and there were no interactions between Polarity and Latency (F₄,₉₂ = 0.650p = 0.628, ηp² = 0.027) nor among Action, Polarity and Latency (F₄,₉₂ = 0.391p = 0.814, ηp² = 0.016) (See Fig. 2). This increase in corticospinal excitability supports previous research showing larger motor-evoked potentials when TMS pulses are delivered at 300 ms (Innocenti et al., 2014; Labruna et al., 2011). One hypothesis is that processing action-related language engages motor simulations, thereby fostering dynamic interactions between the language and sensorimotor systems.

<figure><img src="image_3.png" /><figcaption>Fig. 2. Corticospinal excitability for action and non-action sentences in affirmative and negative forms for all TMS latencies (200, 300, 400, 500 and 600 ms). Lines represent mean amplitude relative to rest and shaded areas denote the standard deviation. Affirmative and negative sentences are represented in red and blue, respectively. An Anova revealed greater corticospinal excitability for action compared to non-action sentences only at 300 ms, regardless of the polarity of the sentences. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>
Moreover, we qualitatively observed that all conditions exhibited a peak in MEP amplitude and crucially that the latencies directly preceding and following this peak yielded lower corticospinal excitability. This suggests that the involvement of the motor system is punctual (See Fig. 3).

Using individual peaks (i.e., only the one of the three latencies yielding the highest MEP for a condition), normalized MEPs for affirmative and negative action sentences were different from rest (affirmative: p = 0.007; t = 2.938; negative sentences: p = 0.044; t = 2.121), but non-action sentences were not (affirmative: p = 0.453; t = 0.762; negative: p = 0.290; t = 1.081). Moreover, a main effect of Action was observed (F₁, 23 = 4.865, p = 0.037, ηp² = 0.174), with larger MEP amplitude for Action (8.77 ± 14.87 %) than Non-action sentences (3.31 ± 15.75 %, Cohen's d = 0.36). However, we did not observe any Polarity effect (F₁, 23 = 0.031, p = 0.860, ηp² = 0.001) nor interaction between Action and Polarity (F₁, 23 = 0.134, p = 0.717, ηp² = 0.005) (Fig. 4).

These findings demonstrate greater corticospinal excitability for both negated and affirmed action sentences compared to non-action sentences and to rest. Interestingly, this state of excitability does not seem to be polarity-dependent, meaning that affirmed and negated action sentences seem to engage the M1 in a nearly identical way at these latencies, and more so than negated and affirmed non-action sentences.

## Experiment 2

In contrast to the previous experiment, this second experiment included both short and long latencies and measured both corticospinal excitability and inhibition within M1. Also, we excluded non-action sentences in this experiment, as our hypotheses only concerned the possible differences when the motor system is engaged, which is not the

case for non-action sentences.

## Corticospinal excitability

Due to inter-subject variability of latencies, we selected individual peak MEP increase, as in Experiment 1. We found that corticospinal excitability increased for all conditions in comparison to rest (all p's < 0.05). We did not observe any effects of Polarity (F₁,₁₈ = 0.146, p = 0.706, ηp² = 0.008), Latency (F₁,₁₈ = 1.867, p = 0.188, ηp² = 0.093), nor Latency by Polarity interaction. (F₁,₁₈ = 0.006, p = 0.936, ηp² = 0.000) (See Fig. 5).

These findings show that both affirmative and negative action sentences led to a greater peak of corticospinal excitability in comparison to rest as in Experiment 1, and this increase persisted from early to late latencies. In summary, both affirmative and negative action sentences engage the motor system at both latencies in the current study.

## Short-interval intracortical inhibition (SICI)

First, we found a higher TS intensity to reach the target MEP amplitude for paired-pulse in comparison to single-pulse stimulation at rest, reflecting inhibition within M1 (25.64%; p < 0.001; t = 10.243). Next, using the same peak latency from the corticospinal excitability results from this experiment, we found a larger inhibition at the long latency than at rest for both affirmative (p = 0.005; t = 3.160) and negative sentences (p = 0.002; t = 3.637), whereas the short latency yielded no supplementary inhibition (affirmative, p = 0.218, t = 1.276; negative, p = 0.234, t = 1.231). Moreover, we observed a main effect of Latency (F₁,₁₈ = 12.968, p = 0.002, ηp² = 0.418) with greater inhibition at long (12.057 ± 15.723 %) than short latencies (4.455 ± 15.542 %, Cohen's d = 0.50). Interestingly, this increase was nearly identical for both affirmative and negative sentences, as we did not observe any

<figure><img src="image_4.png" /><figcaption>Fig. 3. Temporal dynamics of the corticospinal excitability surrounding the peak MEP amplitude. Bar plots denote the mean amplitude relative to the rest, with vertical bars representing the standard deviation. The peak MEP amplitudes for affirmative and negative sentences are represented in red and blue, respectively. MEP amplitudes before and after the peak latency are shown in black and gray, respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>Fig. 4. Box plots represent the peak normalized MEPs (% rest) for each condition. Horizontal lines denote the mean, while individual data points are represented by circles. Affirmative and negative sentences are represented in red and blue, respectively. The rmANOVA yielded a main effect of action, independent of sentence polarity. The right side of the panel illustrates raw MEPs of a typical subject (grey lines), with the black line representing the average MEP of the condition for this participant. \* = p < 0.05. § = difference from rest. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>Fig. 5. Corticospinal excitability (CSE) at short and long latencies in Experiment 2. Box plots represent corticospinal excitability (percentage rest). Horizontal lines denote the mean, while individual data points are represented by circles. Statistical analysis (one-sample t-tests) revealed significant differences only when compared to rest for each condition. No main effects or interactions between conditions were observed (rmANOVA). Affirmative and negative sentences are represented in red and blue, respectively. § = difference from rest, NS = non-significant. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>Fig. 6. SICI ratio for affirmative and negative action sentences at short and long latencies in Experiment 2. Box plots represent intracortical inhibition (delta to rest intracortical ratio). Horizontal lines denote the mean, while individual data points are represented by circles. The rmANOVA yielded a main effect of latency with greater inhibition at long compared to short latencies, independent of sentence polarity. One-sample t-tests indicated that only long latencies showed significant differences from rest. \* = p < 0.05. § = difference from rest.</figcaption></figure>

significant main effect of Polarity ($F_{1,18} = 0.499, p = 0.488, \eta p^2 = 0.027$), nor Latency by Polarity interaction. ($F_{1,18} = 0.756, p = 0.395, \eta p^2 = 0.040$) (Fig. 6).

Taken together, these results suggest that negated action sentences do not engage greater intracortical inhibition than affirmed action sentences within M1. At later latencies, inhibition is augmented for both negated and affirmed actions.

## Discussion

The present study describes two original findings regarding the comprehension of negated action sentences. First, negative action sentences exhibited nearly identical increases in corticospinal excitability as affirmative sentences at both short and long latencies following verb presentation. Second, both negated and affirmed sentences exhibited an increase of SICI within M1 at longer latencies. These two findings will be discussed below.

### Increased corticospinal excitability at early latencies for both affirmative and negative actions

The nearly identical increase in corticospinal excitability for negated and affirmed action sentences at early latencies in both experiments suggests that negative action sentences evoke a motor simulation of the to-be negated action in the same way as affirmative sentences do. This finding supports only the initial step of the two-step theory of negated language processing (Beltrán et al. 2021; Kaup et al. 2005, 2006; Kaup, Yaxley, et al. 2007; Lüdtke et al. 2008; Anderson et al. 2010; Scappini and Delfitto 2015), without any direct evidence for negation-specific processing in a second step (see sections below concerning increased inhibition). Two-step theories propose that linguistically negated concepts initially evoke a motor simulation as if they were not negated, as observed in the present study, but also that this simulation is later suppressed in a second step, which is not clearly observed in our study. This proposed two-step process captures both the negation (second step), as well as the concept that is negated (first step), allowing an understanding of what is denied or absent (no smoking vs. no diving).

At the same time, our identical pattern for negated and affirmed action sentences contradicts recent research showing a decrease in
corticospinal excitability after reading negative compared to affirmative action verbs (Papeo et al., 2016) or adverbs (Papitto et al., 2021). There are various potential reasons for this discrepancy. First, there are differences in the linguistic stimuli and the method of presentation between these studies. In the current study, we employed complex sentences presented in two clauses, whereas Papeo et al. (2016) and Papitto et al. (2021) used minimal context (short verb phrases, e.g. “now I write”) and a rapid serial visual presentation, respectively. The richer context and more natural reading presentation may lead to a stronger motor simulation, which might be absent when the context is not strong enough and reading behavior is unnatural. Secondly, measurement timing, which is a significant factor in action reading literature (Borreggine & Kaschak, 2006; Buccino et al., 2005; Kaschak & Borreggine, 2008; Papeo et al., 2009), could also help to explain discrepancies. As detailed above, the increase in MEP amplitude is a peak that occurs at different times across individuals and across types of stimuli. Therefore, this peak may be easy to miss in a given condition, especially when probing at only one moment in time for all individuals and all conditions. In our study, we probed a wider variety of TMS stimulation latencies, performing a novel peak analysis to address individual and condition-based variability in the activation of the action representation over time. If we had not considered individual latencies of corticospinal excitability increase, we may have missed the motor system involvement during the processing of negative action verbs. The combination of these factors may explain why we observed an increase in corticospinal excitability after reading a negative sentence.

### A late peak in corticospinal excitability for both affirmative and negative actions

The increase of corticospinal excitability for both negative and affirmative action sentences at long latencies was rather unexpected. While the early increase of corticospinal excitability is in line with hypotheses supporting the two-stage model and can be explained by facilitation within M1, arising from the motor representations evoked during the reading of action sentences, the origins of the later peak are more difficult to pinpoint. The later increase in corticospinal excitability could arise from a second, later stage of processing of the described action (or a re-processing) within the motor system. On the other hand, it could also reflect inputs from other facilitatory processes originating in regions external to M1. This latter facilitation may be transmitted from regions such as premotor or parietal areas, or even from subcortical or spinal levels of processing (Reis et al., 2008). If this second peak indeed arises from regions external to the motor system, the delay could be driven by the time needed for initial processing within these regions, as well as the time to transmit signals through direct or indirect pathways between these regions and M1 or the corticospinal pathway.

### Increased inhibition for both affirmative and negative actions at long latencies

We observed an increase in SICI within M1 for negated sentences at longer latencies (compared to rest and to shorter latencies), which would seem to support the two-step processing theory during negative sentence reading (Beltrán et al. 2021; Kaup et al. 2005, 2006; Kaup, Yaxley, et al. 2007; Lüdtke et al. 2008; Anderson et al. 2010; Scappini and Delfitto 2015). However, the fact that the same inhibitory pattern was observed for affirmative sentences eliminates the possibility that this inhibition is related to negation processing. Instead, our findings suggest that this inhibitory pattern may reflect a more general mechanism of action language, independent of whether the sentence is negated or affirmative.

One hypothesis for these inhibitory mechanisms during the reading of action sentences could be to limit motor system activation in order to impede unwanted movements. This hypothesis has been put forth in the domain of motor imagery (Jeannerod, 2001; Jeannerod & Decety,

1995), yielding similar results for corticospinal excitability and SICI (Neige et al., 2020). Indeed, the late increase of SICI is simultaneous with the increase of corticospinal excitability for both negated and affirmed sentences at long delays, consistent with the idea that the inhibition serves to limit motor system activation. Corticospinal excitability comprises inhibitory and excitatory processes of the corticospinal tract including both cortical and spinal contributions (Neige et al., 2020). As discussed above, corticospinal facilitation at long latencies could potentially originate outside M1 and exert its influence through direct or indirect pathways (Reis et al., 2008). By contrast, the modulation of SICI observed in our study reflects cortical inhibitory interneurons that are localized within M1. Given that inhibition within M1 is greater at long than short latencies, it is possible that this late inhibition is required to counter increases in corticospinal excitability arriving from other premotor, parietal, or subcortical regions.

The idea of two-step processing of negated actions specifies that to-be negated actions are initially mentally simulated as if they were affirmative, and then in a second step, this simulation is suppressed by recruiting general action inhibitory mechanisms (e.g., Beltrán et al. 2021). Both Experiments 1 and 2 revealed an increase in cortical excitability for negated action sentences at the earlier latencies that was nearly identical to that of affirmed action sentences, and both significantly greater than non-action sentences. However, no difference in cortical excitability nor inhibition between negated and affirmed sentences was observed at longer latencies, at least not within M1 and along the corticospinal pathway. Nevertheless, we must be mindful that the observed lack of difference in inhibition refers specifically to the inhibitory mechanism within M1. Negated concepts may well be inhibited in other systems in the brain such as the dorsolateral prefrontal cortex (dlPFC), the pre-supplementary motor area (pre-SMA), the inferior parietal, or the inferior frontal gyrus. Recent evidence from EEG studies supports distinct inhibitory mechanisms in the inferior frontal gyrus/pre-SMA during negated and affirmative action reading (Beltrán et al., 2018, 2019, 2021; De Vega et al., 2016; Liu et al., 2020; Vitale et al., 2021). These findings permit the speculation that various brain regions and systems contribute differentially to the two stages of processing for negated actions. It is possible that some regions, such as M1 in the case of action language, would contribute to the initial processing step; engaging a representation or simulation of the negated action. This is essential for the ability to understand what has been negated and can be likened to a sort of motoric retrieval of the meaning of the negated concept. It is possible that this information is then relayed to other regions or multi-sensory integration areas where this concept can be inhibited to capture the intended negation.

### Perspectives and limitations

There are several limitations of the present research. First, there were a limited number of experimental trials per participant. As it remains impossible to know exactly when the motor representation will occur and reach its maximum for each subject and each trial, we had to probe several latencies on separate trials and select the peak afterward, discarding the trials that missed the motor facilitation. This is indeed a strength of the current study in that individual differences in processing time are taken into account, but it can also be considered a limitation in that we reduce the number of experimental trials. While the number of trials remained sufficient to measure a significant difference between action and non-action sentences, we nonetheless attempted to overcome this limitation in Experiment 2 by calibrating each subject's individual processing time prior to the test session, and then using that latency during the experimental trials. This procedure was used only for the short latencies, as we considered the facilitation and inhibition at longer latencies to be more susceptible to variations, and thus less stable so we preferred to probe at multiple latencies. We are looking into continuous measures, such as EEG, to further investigate these issues.

A second limitation is the absence of any behavioral measures to
confirm participant engagement during the reading task. Although the differences in excitability between our conditions and rest suggest that participants were engaged, it would have been beneficial to include a verification task to ensure this. Moreover, correlating the results with the participants' level of engagement could provide some interesting findings.

A third limitation is the restriction of our measurements to the motor system. Given the study's focus on action language processing and our interest in motor simulations, this is a deliberate and suitable choice. However, our results raise new questions that implicate regions outside of M1, and further research will indeed be necessary to address the possible inhibition of the negated actions at other brain sites. It would also be interesting to determine whether the increase in corticospinal excitability in the long latencies originates from the motor simulation in M1 or from other brain regions. For example, double-site TMS might be useful in investigating the interaction between M1 and the inferior parietal lobule, which plays a role in comprehension as well as action inhibition.

In conclusion, the present study provides new insights into the processing of negated actions within M1 and along the corticospinal track. The nearly identical augmentation in corticospinal excitability for negated and affirmed action sentences suggests that actions that are linguistically negated are simulated in the same way within the motor system as affirmed actions. This finding is consistent with the initial step of the two-step theory of negated language processing, specifying that negated actions are mentally simulated in a first step. The second step of this theory postulates the suppression of this simulation. At later latencies, we indeed observed increased SICI, but this was the case for both negated and affirmed sentences. Therefore, it is more likely that this inhibition process serves to counter motor facilitation and impede movement during motor cortex activation, as postulated in motor imagery, rather than to annul the negated concept, as proposed by the two-step processing theory. It remains possible that a distributed multimodal network is required to capture the semantic nature of a negated concept, such that the motor system helps to represent an action to be negated, and a subsequent inhibitory process comes into play on this representation in a separate brain region. While the current study lends support for the motor system's role in the initial stage of the two-step theory of negation processing, further research is clearly needed to better specify the second step and the contribution of other brain regions to this process.

## Declaration of competing interest

None declared.

## CRediT authorship contribution statement

**W. Dupont:** Writing – review & editing, Writing – original draft, Methodology, Investigation, Formal analysis, Conceptualization. **C. Papaxanthis:** Writing – review & editing, Validation, Supervision, Resources. **L. Lurquin:** Investigation. **F. Lebon:** Writing – review & editing, Visualizing, Visualization, Validation, Supervision, Project administration, Methodology. **C. Madden-Lombardi:** Writing – review & editing, Visualization, Validation, Supervision, Project administration, Methodology.

## Appendix A. Supplementary material

Supplementary data to this article can be found online at https://doi.org/10.1016/j.neuroscience.2024.12.018.

## Data availability statement

All data from this study are available at https://osf.io/ez8hf/?view_only=27f25d1eb10c40b894db8053fa96012d

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